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Real-world evaluation of physiotherapist-led exercise prehabilitation and rehabilitation during autologous stem cell transplantation in myeloma: a single-centre experience | a0d38975-793f-4005-bb7b-4112e59b3362 | 11752014 | Surgical Procedures, Operative[mh] | Research trials have shown that exercise before, during and after stem cell transplantation is safe and can improve functional capacity and quality of life in people with haematological malignancies. Little is known about the implementation of exercise during stem cell transplantation into routine care and the acceptability in non-research participants.
Physiotherapist-led prehabilitation and rehabilitation as a key component of routine care during autologous stem cell transplant in myeloma at our UK centre is acceptable and shows benefit in improving functional outcomes and quality of life during preparation for and recovery from transplant.
This embedded, pathway-based approach to implementing physiotherapist-led exercise in routine stem cell transplantation care can be adapted to the context of other centres wishing to optimise outcomes through enhanced rehabilitative support.
Multiple myeloma is a plasma cell neoplasm that presents with a variety of clinical manifestations including bone destruction, hypercalcemia, anaemia and renal failure. While it remains incurable, new and effective therapies have resulted in many patients experiencing periods of disease control, punctuated by relapses and varying amounts of treatment-free intervals. Current standard-of-care for transplant-eligible, newly diagnosed myeloma, includes induction chemotherapy treatment, followed by peripheral blood stem cell harvest, high-dose melphalan and autologous stem cell transplantation (ASCT). The recent incorporation of post-ASCT consolidation treatment, followed by maintenance therapy until disease progression has extended progression-free survival in myeloma. While ASCT remains an important intervention in the management of myeloma in improving progression-free survival and overall survival it does not come without short-term and long-term adverse effects. A large population study (n=1969) found patients with myeloma reported the highest peak in fatigue and impaired well-being at 1-month post-ASCT, which subsequently improved over time but was still prevalent in 21%–26% of patients 1-year post-ASCT. Qualitative studies exploring the experiences of patients with myeloma undergoing ASCT report it made them feel ‘dead’ and they perceived their recovery as slow, negative and daunting. Exercise-based rehabilitation plays an important role in reducing the negative side effects of cancer and its treatments. Prehabilitation exercise interventions, aimed at optimising patients for cancer treatment, have been increasingly recognised for their positive effects in presurgical oncology populations. Benefits include improved clinical outcomes by the optimisation of physiological reserve resulting in enhanced resilience to treatment-related inactivity and deconditioning. Meta-analyses of haematopoetic stem cell transplant populations found exercise interventions had a positive effect on functional capacity, lower limb strength, fatigue and quality of life (QoL). In particular, the benefits were more pronounced if exercise interventions were commenced prior to transplantation. Therefore, exercise interventions commenced prior to ASCT could potentially translate into real-world healthcare savings by reducing hospital length-of-stay. A pilot randomised controlled trial in patients with myeloma with exercise before and after ASCT found a high prevalence of functional deficits on initial referral, and reported a positive role for exercise in improving functional capacity, QoL and physical activity pre and post-ASCT. Importantly, those who undertook exercise reported a positive and quicker recovery compared with control participants. Translation of research findings into clinical practice remains a challenge for healthcare professionals, with implementation estimated to take approximately 17 years. Such delays in innovative, evidence-based interventions may result in poorer clinical and functional outcomes, reduced QoL and higher healthcare-associated costs. At our centre, we sought to translate learning from a locally conducted pilot study undertaken within our myeloma ASCT pathway after promising results indicated improved functional capacity, QoL and experience of care. Recognition of the benefits of this work from the research active clinical leadership team and divisional managers allowed for the development of an innovative new rehabilitation service focused on optimising patients for ASCT. We aim to describe an overview of this prehabilitation and rehabilitation pathway designed to integrate seamlessly into, and complement, the established myeloma transplant service, and to present real-world findings related to function and QoL.
Study design and setting This service evaluation describes the implementation of a prehabilitation and rehabilitation pathway for transplant-eligible myeloma patients scheduled to undergo ASCT at a large tertiary referral cancer centre in London, United Kingdom. The pathway was implemented following a pilot study previously carried out at our centre and was financed with fixed-term funding for specialist physiotherapist time (one whole time-equivalent Agenda for Change Band 8a). Elements of the pilot study intervention were adapted for translation to local care, as outlined in the patient and public involvement (PPI) section. In line with the UK Health Departments Research Ethics Service and Health Research Authority guidelines, approval from a Research Ethics Committee was not required as the study was a service evaluation and local governance procedures for quality improvement were followed. Participants Patients with multiple myeloma who were referred for consideration for ASCT following induction treatment were identified in multidisciplinary team meetings and entered the pathway sequentially based on the date of their stem cell harvest consent consultation. There were no exclusion criteria. All patients referred for ASCT were included within this pathway and there was no reliance on clinician referral. Overview of the prehabilitation and rehabilitation pathway The pathway is illustrated in and the intervention component is outlined in using the Template for Intervention Description and Replication and Consensus on Exercise Reporting Template checklists. Participants were notified via telephone prior to their assessment to introduce the programme and to set up a patient-facing hospital portal for the hospital electronic record system (EPIC MyChart). This was to facilitate completion of patient-reported outcomes measures (PROMs) prior to appointments. All physiotherapy assessments occurred face-to-face and coincided with existing myeloma clinical appointments. Pre-ASCT participants were enrolled on a one-off online education session and weekly remotely supervised group exercise sessions. Rehabilitation commenced once the patient was discharged from hospital. Patients were contacted at week 1 and week 3 following discharge to commence an unsupervised walking programme. At 4 weeks post-discharge, they would recommence a weekly remotely supervised group exercise session, which is continued up to 100 days post-ASCT. Assessments Initial appointment and baseline assessment (T0) took place at consent for stem cell harvest. Follow-up assessment took place during preadmission ASCT consenting appointment (T1), typically 1 week prior to ASCT. Final follow-up assessment was approximately 100 days post-ASCT (T2). Patients completed PROMs, either electronically via electronic record system or on paper in clinic. PROMs included European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC) QLQ-C30 and EuroQol EQ5D-5L measures of QOL and Duke Activity Status Index. Participants underwent a 6 min walk test (6MWT), carried out according to guidelines using a 30 m track, and a 1 min timed sit-stand test (1minSTS). A reference equation was used to determine a predicted 6MWT distance for each participant based on their age and sex. Each participant’s actual 6MWT distance and their predicted distance were used to calculate percentage of predicted score. Validated reference scores were used to determine if patients’ 1minSTS outcomes were in line with those expected for their age and sex. Number of weeks between T0 assessment and day of ASCT (prehabilitation phase) and between hospital discharge and T2 assessment (rehabilitation phase) was calculated to ascertain time available to receive input during both phases of the pathway. Length of stay was retrieved from electronic hospital records and compared with historical data, matched for age, gender, conditioning dose and admission type (inpatient vs ambulatory care). Attendance of remotely supervised sessions was recorded and summarised, as were reasons given for non-attendance. On completion of rehabilitation, participants were asked to complete an online anonymous patient experience questionnaire (reported separately). Analysis Demographics, disease characteristics and baseline outcomes were presented using descriptive statistics (mean with SD, median and IQR and range, or frequencies and proportions). Paired sample t-tests were used for pre–post assessment of outcomes. Parametric student t-tests were used where assumptions of distribution and normality were met, otherwise non-parametric Wilcoxon rank test was used. Data were summarised using Microsoft Excel and Jamovi. Standards for Quality Improvement Reporting Excellence (SQUIRE) guidelines were also followed. Patient and public involvement The authors conducted a PPI workshop prior to the implementation of this project. The aim of this workshop was to seek patient input into the transition of the original research-delivered intervention into a clinical service. This input led to the integration of a patient education session and enhancement of the rehabilitation phase to include remotely supervised group exercise sessions, instead of telephone-based support.
This service evaluation describes the implementation of a prehabilitation and rehabilitation pathway for transplant-eligible myeloma patients scheduled to undergo ASCT at a large tertiary referral cancer centre in London, United Kingdom. The pathway was implemented following a pilot study previously carried out at our centre and was financed with fixed-term funding for specialist physiotherapist time (one whole time-equivalent Agenda for Change Band 8a). Elements of the pilot study intervention were adapted for translation to local care, as outlined in the patient and public involvement (PPI) section. In line with the UK Health Departments Research Ethics Service and Health Research Authority guidelines, approval from a Research Ethics Committee was not required as the study was a service evaluation and local governance procedures for quality improvement were followed.
Patients with multiple myeloma who were referred for consideration for ASCT following induction treatment were identified in multidisciplinary team meetings and entered the pathway sequentially based on the date of their stem cell harvest consent consultation. There were no exclusion criteria. All patients referred for ASCT were included within this pathway and there was no reliance on clinician referral.
The pathway is illustrated in and the intervention component is outlined in using the Template for Intervention Description and Replication and Consensus on Exercise Reporting Template checklists. Participants were notified via telephone prior to their assessment to introduce the programme and to set up a patient-facing hospital portal for the hospital electronic record system (EPIC MyChart). This was to facilitate completion of patient-reported outcomes measures (PROMs) prior to appointments. All physiotherapy assessments occurred face-to-face and coincided with existing myeloma clinical appointments. Pre-ASCT participants were enrolled on a one-off online education session and weekly remotely supervised group exercise sessions. Rehabilitation commenced once the patient was discharged from hospital. Patients were contacted at week 1 and week 3 following discharge to commence an unsupervised walking programme. At 4 weeks post-discharge, they would recommence a weekly remotely supervised group exercise session, which is continued up to 100 days post-ASCT.
Initial appointment and baseline assessment (T0) took place at consent for stem cell harvest. Follow-up assessment took place during preadmission ASCT consenting appointment (T1), typically 1 week prior to ASCT. Final follow-up assessment was approximately 100 days post-ASCT (T2). Patients completed PROMs, either electronically via electronic record system or on paper in clinic. PROMs included European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC) QLQ-C30 and EuroQol EQ5D-5L measures of QOL and Duke Activity Status Index. Participants underwent a 6 min walk test (6MWT), carried out according to guidelines using a 30 m track, and a 1 min timed sit-stand test (1minSTS). A reference equation was used to determine a predicted 6MWT distance for each participant based on their age and sex. Each participant’s actual 6MWT distance and their predicted distance were used to calculate percentage of predicted score. Validated reference scores were used to determine if patients’ 1minSTS outcomes were in line with those expected for their age and sex. Number of weeks between T0 assessment and day of ASCT (prehabilitation phase) and between hospital discharge and T2 assessment (rehabilitation phase) was calculated to ascertain time available to receive input during both phases of the pathway. Length of stay was retrieved from electronic hospital records and compared with historical data, matched for age, gender, conditioning dose and admission type (inpatient vs ambulatory care). Attendance of remotely supervised sessions was recorded and summarised, as were reasons given for non-attendance. On completion of rehabilitation, participants were asked to complete an online anonymous patient experience questionnaire (reported separately).
Demographics, disease characteristics and baseline outcomes were presented using descriptive statistics (mean with SD, median and IQR and range, or frequencies and proportions). Paired sample t-tests were used for pre–post assessment of outcomes. Parametric student t-tests were used where assumptions of distribution and normality were met, otherwise non-parametric Wilcoxon rank test was used. Data were summarised using Microsoft Excel and Jamovi. Standards for Quality Improvement Reporting Excellence (SQUIRE) guidelines were also followed.
The authors conducted a PPI workshop prior to the implementation of this project. The aim of this workshop was to seek patient input into the transition of the original research-delivered intervention into a clinical service. This input led to the integration of a patient education session and enhancement of the rehabilitation phase to include remotely supervised group exercise sessions, instead of telephone-based support.
Participant characteristics Between May and October 2023 (6 months), 48 participants were assessed by physiotherapists at the preharvest baseline timepoint (T0). Of these, 46 (96%) proceeded to admission for ASCT. Two patients did not proceed (due to disease progression (n=1) and not deemed fit to proceed (n=1)), and their data were removed from the analysis. The cohort had a mean age of 60.8 (SD 7.8) years, was 57% male with majority of patients being of white ethnicity (74%), married or in civil partnership (65%) and retired (43%). Most patients (98%) were undergoing their first ASCT, and had undergone one line of treatment (96%), with a median time from diagnosis to baseline assessment of 5 months (IQR 4–6). The majority (57%) received standard-of-care induction chemotherapy with daratumumab, velcade, thalidomide and dexamethasone, receiving an average of 4.2 (SD 0.7) cycles. 89% of patients had myeloma-related bone disease on imaging and 41% required immobilisation in a spinal orthotic/brace. Patient characteristics and disease features are presented in . Baseline function and QOL At baseline assessment, during preharvest clinical review, the mean distance walked by participants in the 6MWT was 451.4 m (SD 106.5, range 180–750 m, n=43). The median percentage of predicted score for the cohort was 70.7% (IQR 61–80.2) and 72% of the cohort walked a distance less than 80% of their predicted distance. The mean repetition for the 1 min STS test was 21.9 (SD 11.2, range 0–56, n=46). 72% of the cohort produced below average (<25th centile) scores for their age and sex, with 48% of patients producing a below 2.5th centile score, indicating severely impaired lower limb strength endurance. The EQ5D-5L was dichotomised into ‘no problems’ versus ‘some level of problem’, with the majority of patients reporting some level of problem in 4 out of 5 domains at baseline. Problems with carrying out ‘usual activities’ were most commonly reported (84% n=37), with most reporting slight or moderate problems (68% n=30), followed by experiencing ‘pain’ (78% n=34) and problems with ‘mobility’ (59% n=26). Nearly half of patients (46% n=20) reported moderate or severe levels of pain. Over half the cohort (52% n=23) reported some level of ‘anxiety/depression’. ‘Self-care’ had the lowest reported problems with 33% (n=14) of patients reporting problems, mostly slight. The EQ5D visual analogue scale (VAS) measure of ‘your health today’ had a median score of 70/100 [IQR 44.0, 80.00, n=41]. Baseline scores for selected domains of the EORTC-C30 are outlined in . Outcomes following prehabilitation Of the 46 patients who were assessed at baseline and proceeded to ASCT, 39 (85%) underwent a post-prehabilitation assessment prior to admission for ASCT (T1). Reasons for not undergoing a T1 assessment included missing their preadmission clinical appointment, in which a subsequent physiotherapy assessment not undertaken (n=5, 71.4%), patient did not attend clinical assessment (n=1, 14.3%) or declined to undergo assessment (n=1, 14.3%). There were no differences between the 39 patients included in the pre–post analyses of outcomes compared with the overall cohort in terms of clinical and disease characteristics. They had a mean age of 60.4 (SD 7.9) years, were 56% male and mostly of white ethnicity (72%). The distribution of martial and employment status was the same, as was median time from diagnosis to baseline assessment. Descriptive summaries of each outcome for participants included in the pre–post analyses are summarised in . There was a statistically significant improvement in 6MWT distance (+60 m, 95% CI 41.5 to 78.9, p<0.001) and 1min-STS (+6.8 repetitions 95% CI 4.9 to 8.7, p<0.001) after prehabilitation. Domains of the EORTC which improved significantly included global QoL (+5.9, 95% CI 1.2 to 10.5, p=0.02), physical functioning (+7.9, 95% CI 2.9 to 13.0, p=0.003) and role functioning (+18.0, 95% CI 8.7 to 27.3, p<0.001). The EQ5D VAS score improved significantly (+8.7, 95% CI 2.87 to 14.8, p=0.006). Outcomes following rehabilitation To evaluate the combined effect of prehabilitation before and rehabilitation after ASCT, a pre–post analysis was undertaken comparing baseline outcomes (T0) with day 100 (D100) post-ASCT outcomes (T2). Of the 39 patients included in the pre–post prehabilitation analysis, 33 (85%) also completed outcomes at D100 post-ASCT (T2). Reasons for not undergoing D100 assessment included attending appointment but not completing assessments (n=2, 33%), not reaching the D100 timepoint within the timeframe of the project (n=2, 33%), did not attend clinical assessment (n=1, 17%) or D100 clinical appointment was missed and a physiotherapist assessment was not arranged (n=1, 17%). Between baseline and 100 days post-ASCT, there were improvements in 6MWT distance (+62.8 m, 95% CI 40.7 to 84.9, p<0.001) and 1min-STS (+9.1 reps, 95% CI 5.4 to 12.8, p<0.001). EORTC domains of global QoL (+11.8, 95% CI 5.7, 17.9, p<0.001) and physical functioning (+13.8, 95% CI 7.7, 19.8, p<0.001) improved significantly. There were improvements in role functioning (+19.9, 95% CI 5.1 to 9.5, p<0.001) and overall summary score (+5.7, 95% CI 1.7 to 9.8, p=0.008). The EQ5D VAS score improved (+9.5, 95% CI 2.8 to 16.2, p=0.007). Attendance of prehabilitation and rehabilitation sessions Potential time available for prehabilitation input was estimated from the mean number of weeks between baseline assessment (T0) and day of ASCT, which was 6.8 weeks (SD 3.3, 95% CI 5.9 to 7.8, n=46). Of the 46 patients assessed preharvest, 31 (67%) participants attended at least one remotely supervised group prehabilitation exercise session. Of these participants, the median number of sessions attended within the prehabilitation phase was four sessions (IQR 3–5). 3 (6%) declined to take part in group sessions, 6 (13%) were booked to attend sessions but did not attend any, 6 (13%) exercised independently. The most common reason for not attending or cancelling a booked prehabilitation session was having another medical appointment. With regards to time available to potentially benefit from rehabilitation input, the mean number of weeks between hospital discharge following ASCT and day of D100 clinical assessment was 11.8 weeks (SD 1.7 95% CI 11.3 to 12.4, n=44). 39 (85%) out of 46 patients received early rehabilitation telephone support postdischarge in line with the protocol (median 2 calls (IQR 1.8–2)). Of the 31 patients who attended the prehabilitation classes, 27 (87%) attended at least one remotely supervised group exercise session, with median number of sessions was 6 (IQR 4–6.5) attended in the rehabilitation phase. Four patients (13%) who were expected to attend the rehabilitation exercise classes were unable to attend any due to hospital readmissions and as a result required more telephone calls (median 5.5 calls (IQR 4.3–6.3)). 3 patients (8%) did not answer the calls. The most common reasons for not attending or cancelling a booked rehabilitation session were related to logistical challenges with sessions falling on public holidays or lack of cover for physiotherapist annual leave. Length of stay The median length of stay in those who proceeded to ASCT was 17 days (IQR 15–23, n=43). There was no difference in total length of stay between the service evaluation participants and matched historical data.
Between May and October 2023 (6 months), 48 participants were assessed by physiotherapists at the preharvest baseline timepoint (T0). Of these, 46 (96%) proceeded to admission for ASCT. Two patients did not proceed (due to disease progression (n=1) and not deemed fit to proceed (n=1)), and their data were removed from the analysis. The cohort had a mean age of 60.8 (SD 7.8) years, was 57% male with majority of patients being of white ethnicity (74%), married or in civil partnership (65%) and retired (43%). Most patients (98%) were undergoing their first ASCT, and had undergone one line of treatment (96%), with a median time from diagnosis to baseline assessment of 5 months (IQR 4–6). The majority (57%) received standard-of-care induction chemotherapy with daratumumab, velcade, thalidomide and dexamethasone, receiving an average of 4.2 (SD 0.7) cycles. 89% of patients had myeloma-related bone disease on imaging and 41% required immobilisation in a spinal orthotic/brace. Patient characteristics and disease features are presented in .
At baseline assessment, during preharvest clinical review, the mean distance walked by participants in the 6MWT was 451.4 m (SD 106.5, range 180–750 m, n=43). The median percentage of predicted score for the cohort was 70.7% (IQR 61–80.2) and 72% of the cohort walked a distance less than 80% of their predicted distance. The mean repetition for the 1 min STS test was 21.9 (SD 11.2, range 0–56, n=46). 72% of the cohort produced below average (<25th centile) scores for their age and sex, with 48% of patients producing a below 2.5th centile score, indicating severely impaired lower limb strength endurance. The EQ5D-5L was dichotomised into ‘no problems’ versus ‘some level of problem’, with the majority of patients reporting some level of problem in 4 out of 5 domains at baseline. Problems with carrying out ‘usual activities’ were most commonly reported (84% n=37), with most reporting slight or moderate problems (68% n=30), followed by experiencing ‘pain’ (78% n=34) and problems with ‘mobility’ (59% n=26). Nearly half of patients (46% n=20) reported moderate or severe levels of pain. Over half the cohort (52% n=23) reported some level of ‘anxiety/depression’. ‘Self-care’ had the lowest reported problems with 33% (n=14) of patients reporting problems, mostly slight. The EQ5D visual analogue scale (VAS) measure of ‘your health today’ had a median score of 70/100 [IQR 44.0, 80.00, n=41]. Baseline scores for selected domains of the EORTC-C30 are outlined in .
Of the 46 patients who were assessed at baseline and proceeded to ASCT, 39 (85%) underwent a post-prehabilitation assessment prior to admission for ASCT (T1). Reasons for not undergoing a T1 assessment included missing their preadmission clinical appointment, in which a subsequent physiotherapy assessment not undertaken (n=5, 71.4%), patient did not attend clinical assessment (n=1, 14.3%) or declined to undergo assessment (n=1, 14.3%). There were no differences between the 39 patients included in the pre–post analyses of outcomes compared with the overall cohort in terms of clinical and disease characteristics. They had a mean age of 60.4 (SD 7.9) years, were 56% male and mostly of white ethnicity (72%). The distribution of martial and employment status was the same, as was median time from diagnosis to baseline assessment. Descriptive summaries of each outcome for participants included in the pre–post analyses are summarised in . There was a statistically significant improvement in 6MWT distance (+60 m, 95% CI 41.5 to 78.9, p<0.001) and 1min-STS (+6.8 repetitions 95% CI 4.9 to 8.7, p<0.001) after prehabilitation. Domains of the EORTC which improved significantly included global QoL (+5.9, 95% CI 1.2 to 10.5, p=0.02), physical functioning (+7.9, 95% CI 2.9 to 13.0, p=0.003) and role functioning (+18.0, 95% CI 8.7 to 27.3, p<0.001). The EQ5D VAS score improved significantly (+8.7, 95% CI 2.87 to 14.8, p=0.006).
To evaluate the combined effect of prehabilitation before and rehabilitation after ASCT, a pre–post analysis was undertaken comparing baseline outcomes (T0) with day 100 (D100) post-ASCT outcomes (T2). Of the 39 patients included in the pre–post prehabilitation analysis, 33 (85%) also completed outcomes at D100 post-ASCT (T2). Reasons for not undergoing D100 assessment included attending appointment but not completing assessments (n=2, 33%), not reaching the D100 timepoint within the timeframe of the project (n=2, 33%), did not attend clinical assessment (n=1, 17%) or D100 clinical appointment was missed and a physiotherapist assessment was not arranged (n=1, 17%). Between baseline and 100 days post-ASCT, there were improvements in 6MWT distance (+62.8 m, 95% CI 40.7 to 84.9, p<0.001) and 1min-STS (+9.1 reps, 95% CI 5.4 to 12.8, p<0.001). EORTC domains of global QoL (+11.8, 95% CI 5.7, 17.9, p<0.001) and physical functioning (+13.8, 95% CI 7.7, 19.8, p<0.001) improved significantly. There were improvements in role functioning (+19.9, 95% CI 5.1 to 9.5, p<0.001) and overall summary score (+5.7, 95% CI 1.7 to 9.8, p=0.008). The EQ5D VAS score improved (+9.5, 95% CI 2.8 to 16.2, p=0.007).
Potential time available for prehabilitation input was estimated from the mean number of weeks between baseline assessment (T0) and day of ASCT, which was 6.8 weeks (SD 3.3, 95% CI 5.9 to 7.8, n=46). Of the 46 patients assessed preharvest, 31 (67%) participants attended at least one remotely supervised group prehabilitation exercise session. Of these participants, the median number of sessions attended within the prehabilitation phase was four sessions (IQR 3–5). 3 (6%) declined to take part in group sessions, 6 (13%) were booked to attend sessions but did not attend any, 6 (13%) exercised independently. The most common reason for not attending or cancelling a booked prehabilitation session was having another medical appointment. With regards to time available to potentially benefit from rehabilitation input, the mean number of weeks between hospital discharge following ASCT and day of D100 clinical assessment was 11.8 weeks (SD 1.7 95% CI 11.3 to 12.4, n=44). 39 (85%) out of 46 patients received early rehabilitation telephone support postdischarge in line with the protocol (median 2 calls (IQR 1.8–2)). Of the 31 patients who attended the prehabilitation classes, 27 (87%) attended at least one remotely supervised group exercise session, with median number of sessions was 6 (IQR 4–6.5) attended in the rehabilitation phase. Four patients (13%) who were expected to attend the rehabilitation exercise classes were unable to attend any due to hospital readmissions and as a result required more telephone calls (median 5.5 calls (IQR 4.3–6.3)). 3 patients (8%) did not answer the calls. The most common reasons for not attending or cancelling a booked rehabilitation session were related to logistical challenges with sessions falling on public holidays or lack of cover for physiotherapist annual leave.
The median length of stay in those who proceeded to ASCT was 17 days (IQR 15–23, n=43). There was no difference in total length of stay between the service evaluation participants and matched historical data.
This service development project focused on translating local research data into the delivery of a prehabilitation and rehabilitation pathway integrated into standard-of-care practice for patients with myeloma undergoing ASCT at our centre. Delivered in a hybrid format, participants were assessed face-to-face during routine clinic appointments and engaged in remotely supervised exercise intervention. This structure allowed for the objective assessment of functional outcomes in clinic and increased the ability to engage in supervised exercise sessions remotely. This approach has been highlighted as preferable to patients with myeloma due to the wide geographical reach of specialist haematopoietic transplant centres in the UK and reported reluctance to engage in frequent travel to attend face-to-face sessions. This study found deficits in functional capacity and QoL, which may be higher than anticipated. Patients with transplant-eligible myeloma are considered to be physically ‘fitter’ than their non-transplant eligible counterparts, in order to tolerate high-dose treatment with melphalan. At baseline, patients assessed in this evaluation had lower than expected QoL scores. EORTC domains of physical functioning, role functioning, social functioning and global health were all low compared with published reference values for patients with myeloma. EORTC group scores for physical functioning were lower than published cut-off scores for clinical importance among patients with cancer. In contrast, the cohort had lower median scores for fatigue and pain than myeloma population reference values, indicating lower symptomology. However, when considering thresholds for clinical importance in mixed cancer populations, the cohort score for pain did indicate clinically important levels of pain, which may reflect the high representation of patients with myeloma-related bone disease and history of spinal bracing. There was a high proportion of patients with walking distance and sit-to-stand test results that were lower than published reference values. Literature indicates that a 6MWT score of <80% predicted is indicative of impaired functional capacity, and 1min-STS scores of <2.5th centile reference scores is indicative of severely impaired lower body muscular strength and endurance. 72% of participants produced 6MWT distances<80% predicted and 48% were in the lowest 2.5th centile for 1min-STS, indicating high levels of impaired functional capacity and fitness among these patients prior to stem cell harvest. These proportions are greater than reported in our previous pilot study, where 53% (n=19) of participants were found to have impaired functional capacity. The measurement of such outcomes in a real-world population reinforces published data that the prevalence of functional deficits is greater than those from reference study populations. Furthermore, it builds on the existing literature, which emphasised the need for objective measures of function to be included as part of routine pre-transplant clinical assessments. Clinically significant improvements in patient function and QoL prior to admission for ASCT were observed in this service evaluation and maintained by D100 post-ASCT. Walking distance and lower limb strength improvements from prehabilitation were two times that of the published minimal importance differences for these measures respectively and further gains in lower limb strength were evident with rehabilitation input following ASCT. Mean 6MWT distance for this cohort at preadmission and D100 post-ASCT were in line with those found in patients with myeloma more than 1-year post-ASCT, which could suggest earlier return of functional capacity with timely rehabilitation intervention around ASCT. Greater than MID changes in EORTC QoL domain of physical functioning corroborates the objectively measured changes in walking distance and strength. EORTC domains of global QoL and physical functioning improved within or beyond the MID suggested for patients with myeloma, respectively. The significant improvement in EQ5D VAS score after prehabilitation was also in line with MID for patients with cancer. These combined effects, along with positive improvements in other domains and overall QoL, highlight the importance of patient engagement in physical interventions on QoL and support the need for rehabilitative approaches in cancer treatment pathways. The value of utilising the time prior to ASCT admission cannot be underestimated. The effects of diagnosis and early induction treatment on QoL and physical activity have been documented in myeloma. Furthermore, the desire from patients to engage in exercise to ‘build up’ prior to ASCT is contrasted with experiences of lack of specialised support needed to overcome the barriers to exercising independently in the context of bone disease and pain. This service evaluation indicates promise in embedding pathway-based prehabilitation, with hybrid delivery using remotely supervised exercise and education, as an effective tool for optimising patients in the time frame pre-ASCT. The acceptability of prehabilitation and rehabilitation around ASCT is further evidenced by this service evaluation. Real-world delivery of clinical rehabilitation interventions may give a more realistic insight into uptake and adherence to interventions previously tested in research settings. By offering this service sequentially to patients referred for ASCT, and by conducting physiotherapy assessments aligned with myeloma clinical appointments, we were able to collect objective measures and comprehensive real-world follow-up data. This supports the feasibility of integrating functional and PROM assessments along standard-of-care without significant service disruption. Attendance to at least one remotely delivered exercise session was high in both prehabilitation and rehabilitation phases, with average attendance of four and six sessions in the 7 and 12 weeks available in each phase, respectively. Patients requiring additional telephone support due to slower recovery and/or hospital readmissions post-transplant influenced the lower attendance rate in the rehabilitation phase. The use of stratification of rehabilitation input depending on baseline outcomes or response to hospital admission was not undertaken but is planned for future evaluations. Lower physical functioning was noted to be a significant factor in influencing attendance, with those who had poorer physical function at baseline, and less social support, being impacted the most. Stratification of patients according to functional deficits and self-efficacy to engage in independent exercise programmes could help facilitate tailoring of rehabilitation support, including strategies to help overcome barriers to access, and allow for greater efficiency in resource allocation and intervention strategies. In the context of limited workforce resources and increasing healthcare demand, such an approach could help identify patients who may require additional input, and therefore facilitate equitable access to healthcare interventions. This work has a number of limitations. As a service development evaluation in a single UK centre, these results may lack applicability to other transplant centres with patients with myeloma undergoing ASCT. Lack of control group or historical data related to function and QoL limits the interpretation of results. In addition, adherence to exercise programmes, particularly in terms of duration and intensity, and whether carried out with and without supervision, was not captured. Although our previous research showed promise in increasing physical activity, the local EHR lacked a reliable measurement for physical activity as part of standard of care, which would have been useful in assessing activity outside of specific physiotherapy interventions.
The time between induction chemotherapy and admission for ASCT provides an opportunity to support patients with myeloma to regain physical function and QoL lost during induction treatment and to optimise their performance status prior to proceeding to transplant. This service evaluation of a physiotherapist-led exercise prehabilitation and rehabilitation pathway, built on previous locally delivered research, reinforces the potential benefits of integrating a pathway-based prehabilitation intervention alongside standard medical and nursing care in patients with myeloma planned for ASCT. Hybrid delivery of exercise interventions using face-to-face assessments and remotely supervised group exercise and education is a feasible and promising approach to optimising patients pre-ASCT. This study supports the use of objective measures of function and QoL as important tools for the comprehensive assessment of fitness prior to undergoing ASCT. The higher-than-expected levels of impaired functional capacity evident in our patients prior to ASCT highlight the impact of haematological malignancies and disease-related morbidity on overall fitness, even for those deemed suitable to proceed to transplant with high-dose melphalan. Despite this, the introduction of physiotherapy interventions resulted in clinically significant improvements in functional outcomes that were seen prior to admission for ASCT and were maintained at 100 days post-ASCT. The role of prehabilitation and rehabilitation in enhancing outcomes for patients with myeloma is promising and warrants further investigation using both research and real-world studies.
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Internet use patterns and their relationship with frailty in older Japanese adults | ce002c44-18bd-48b0-9548-e49c168e7b0e | 11951635 | Pathologic Processes[mh] | The empowering effects of digital technology development on healthy aging has become a topic of interest in recent years. The use of technologies, such as the internet, have been recognized as an emerging social factor of health , and health systems are exploring how internet resources can be connected to community-based health policies. However, due to digital divide, limited evidence is currently available for older populations. Furthermore, while previous studies examined the effects of internet use on various health issues, such as depression, loneliness, cognitive function, and physical activity [ – ], the relationship between internet use and frailty remains unclear. To our knowledge, only one report has shown independent protective effects of online activities on frailty in postmenopausal women . However, how different internet use patterns relate to frailty among older adults remains underexplored. Frailty often manifests as physical, psychological, and social vulnerability, leading to an increased risk of adverse health outcomes, such as disability and mortality . It is regarded as a pre-disability stage and is preventable or reversible through effective interventions . Therefore, the prevention of frailty is a public health issue that is being prioritized in Japan, which has a super-aged society. While a digital divide persists (with an overall internet usage rate of 97.5% among those aged 20–64 compared to 60.9% among those aged 65 and above), internet use has grown most rapidly among older population in recent years . This trend enhances the feasibility of studying digital health factors in this population and emphasizes the necessity of understanding how internet technology may empower older individuals to prevent frailty. Internet use patterns exhibit significant variation, encompassing social engagement, information searching, online entertainment, e-shopping, and e-learning. The latest report reveals that the most common internet activities among older Japanese internet users are sending and receiving emails, searching for information, and using social networking services such as free calling apps. In contrast, social networking service use is the most common activity among individuals aged under 50 years . Hypothetically, these diverse patterns may have different effects on frailty. For example, online social activities may help reduce social isolation, mental stress, and other factors associated with frailty [ – ]. Information platforms may be linked to higher health literacy . On the other hand, we must consider possibility of variations of “internet paradox” on frailty. It’s reported that prolonged online social life may reduce face-to-face interactions, contribute to depression, and lower life satisfaction . Frequent searching online information may connect with mental stress .The heterogeneity of internet use behaviors among older adults necessitates a comprehensive segmentation analysis for developing targeted interventions. Moreover, the prevalence of frailty and non-internet users is higher among rural area, which raise concerns that rural older adults may face a new kind of health inequality driven by the digital divide . The present study aimed to determine internet use patterns among rural older adults in Japan and to investigate the relationship between these distinct internet use patterns and frailty.
Samples We conducted a postal survey of 1,800 community-dwelling older adults ≥ 65 years in a rural town in the north of Osaka, Japan, between February and March 2021. Participants received an anonymous self-reported paper questionnaire with reply envelopes by postal mail. Samples were randomly selected using age- and sex-based stratified random sampling with a stratified sampling ratio of 20% from the Basic Resident Registration System. In total, 1,288 questionnaires were valid (response rate 71.6%). We excluded individuals requiring long-term care, living in nursing homes, or those who did not answer questions on internet use, leaving 908 individuals to analyze. Ethics The present study was approved by the Osaka University Clinical Research Review Committee (number: 20369). Participants provided written informed consent to participate in the study. Frailty Frailty was measured using the Kihon Checklist (KCL) developed by the Ministry of Health, Labor, and Welfare, Japan. KCL is considered as a type of deficit model . It contains 25 items divided into seven domains: instrumental activities of daily living, physical function, nutrition, oral function, social domain, cognitive domain, and depression. Each item is scored as either present or absent, and we summarized a total KCL score (the range: 0–25 points) for participants with no missing items. In this study, we used the widely accepted KCL cut-off score of ≥ 8 to define a frail status . This cut-off value has been validated for its effectiveness in identifying frailty as well as predicting the risk of dependency and mortality in Japan . Internet use patterns In the present study, we designed a 6-point scale (never, < one day/week, one day/week, 2–3 days/week, 4–5 days/week, and 6–7 days/week) to collect information on the average weekly frequencies of eight internet activities in the previous month. These activities included sending e-mail, texting/video calls via social messaging apps, health information searching, COVID-19-related information searching, medical services usage, online learning, online shopping, and online entertainment. Details of the questionnaire items in English are provided in Supplementary data (Text ). The scale demonstrated good reliability (Cronbach’s alpha > 0.7) and inter-item correlations were weak (Spearman’s ρ less than 0.7 with most less than 0.4). We standardized all the eight inputs before applying a K-means clustering analysis to identify patterns of internet usage. To assess the optimal number of clusters, multiple clustering analyses (k = 2–8) were conducted. Based on the Euclidean distance and interpretability of clusters, three patterns of internet usage were identified: ‘Less Use’, characterized by minimal activity; ‘Social Use’, characterized by significant engagement in social activities; and ‘Functional Use’, characterized by extensive engagement in information searching, online entertainment, and online shopping (see Fig. , discussed in detail in the Results section). As a supplementary data, we reported the distribution of varied frequencies of each item across the clusters in Table . Statistical analysis All analyses were conducted using STATA version 17 MP. We identified the basic characteristics of the three patterns of internet usage, which were confirmed using the k-means cluster analysis. We compared characteristics among three internet use clusters using a t -test for continuous variables and the chi‐squared test for categorical values. We then used unadjusted and adjusted logistic regression models to assess the relationships between the three clusters (with ‘less use’ as the reference group) and frailty. In adjusted models, we adjusted for variables associated with frailty based on summaries from previous research . Covariate adjustments included age, sex (male/female), subjective family economic status (not wealthy, normal, wealthy), living alone (yes/no), work (yes/no), physical activity (≥ once a week/never), smoking (yes/no), and multimorbidity (none/one/two or more conditions, including hypertension, diabetes, dyslipidemia, heart disease, cerebrovascular disease, and respiratory disease). Additionally, we conducted stratified analyses by sex and age (65–74 years, ≥ 75 years). To minimize any estimation bias from missing data, we used multiple imputation by a chained equation as a sensitivity analysis. We generated 20 imputed datasets, replicated analyses of each imputed dataset and pooled the results obtained using Rubin’s rule (Table ).
We conducted a postal survey of 1,800 community-dwelling older adults ≥ 65 years in a rural town in the north of Osaka, Japan, between February and March 2021. Participants received an anonymous self-reported paper questionnaire with reply envelopes by postal mail. Samples were randomly selected using age- and sex-based stratified random sampling with a stratified sampling ratio of 20% from the Basic Resident Registration System. In total, 1,288 questionnaires were valid (response rate 71.6%). We excluded individuals requiring long-term care, living in nursing homes, or those who did not answer questions on internet use, leaving 908 individuals to analyze.
The present study was approved by the Osaka University Clinical Research Review Committee (number: 20369). Participants provided written informed consent to participate in the study.
Frailty was measured using the Kihon Checklist (KCL) developed by the Ministry of Health, Labor, and Welfare, Japan. KCL is considered as a type of deficit model . It contains 25 items divided into seven domains: instrumental activities of daily living, physical function, nutrition, oral function, social domain, cognitive domain, and depression. Each item is scored as either present or absent, and we summarized a total KCL score (the range: 0–25 points) for participants with no missing items. In this study, we used the widely accepted KCL cut-off score of ≥ 8 to define a frail status . This cut-off value has been validated for its effectiveness in identifying frailty as well as predicting the risk of dependency and mortality in Japan .
In the present study, we designed a 6-point scale (never, < one day/week, one day/week, 2–3 days/week, 4–5 days/week, and 6–7 days/week) to collect information on the average weekly frequencies of eight internet activities in the previous month. These activities included sending e-mail, texting/video calls via social messaging apps, health information searching, COVID-19-related information searching, medical services usage, online learning, online shopping, and online entertainment. Details of the questionnaire items in English are provided in Supplementary data (Text ). The scale demonstrated good reliability (Cronbach’s alpha > 0.7) and inter-item correlations were weak (Spearman’s ρ less than 0.7 with most less than 0.4). We standardized all the eight inputs before applying a K-means clustering analysis to identify patterns of internet usage. To assess the optimal number of clusters, multiple clustering analyses (k = 2–8) were conducted. Based on the Euclidean distance and interpretability of clusters, three patterns of internet usage were identified: ‘Less Use’, characterized by minimal activity; ‘Social Use’, characterized by significant engagement in social activities; and ‘Functional Use’, characterized by extensive engagement in information searching, online entertainment, and online shopping (see Fig. , discussed in detail in the Results section). As a supplementary data, we reported the distribution of varied frequencies of each item across the clusters in Table .
All analyses were conducted using STATA version 17 MP. We identified the basic characteristics of the three patterns of internet usage, which were confirmed using the k-means cluster analysis. We compared characteristics among three internet use clusters using a t -test for continuous variables and the chi‐squared test for categorical values. We then used unadjusted and adjusted logistic regression models to assess the relationships between the three clusters (with ‘less use’ as the reference group) and frailty. In adjusted models, we adjusted for variables associated with frailty based on summaries from previous research . Covariate adjustments included age, sex (male/female), subjective family economic status (not wealthy, normal, wealthy), living alone (yes/no), work (yes/no), physical activity (≥ once a week/never), smoking (yes/no), and multimorbidity (none/one/two or more conditions, including hypertension, diabetes, dyslipidemia, heart disease, cerebrovascular disease, and respiratory disease). Additionally, we conducted stratified analyses by sex and age (65–74 years, ≥ 75 years). To minimize any estimation bias from missing data, we used multiple imputation by a chained equation as a sensitivity analysis. We generated 20 imputed datasets, replicated analyses of each imputed dataset and pooled the results obtained using Rubin’s rule (Table ).
Internet use patterns Three internet use clusters were identified, as shown in Fig. , which presents z-scores for the frequency of various internet activities within each cluster in a heat map format. Cluster 1, named “Less use”, comprised 52.6% of the analyzed sample and exhibited the lowest frequency across all input internet activities (below the overall mean). Cluster 2, named “Social use” (28.7%), generally scored higher z-scores than Cluster 1, with z-scores for sending e-mails and texting/video calls via social messaging apps were the highest across activities and clusters. Based on previous studies, we named this cluster as “social use” as email and texting/video calls were considered as social technology, indicating a pattern focused on social connectivity . In Cluster 3 (“Functional use”, 18.6%), z-scores for each activity were above the overall mean. Within this cluster, the highest frequencies were observed in activities related to information searching, followed by online shopping and entertainment activities like watching YouTube or online game. Participant characteristics Table shows descriptive characteristics and significant differences across the clusters. Cluster 1 (“Less use”) had a significantly higher percentage of older adults (52.64%), particularly those ≥ 75 years (50.64% in Cluster 1 vs. 31.27% in Cluster 2 and 23.21% in Cluster 3), and more females (48.63% in Cluster 1 vs. 36.75% in Cluster 3). Additionally, Cluster 1 had fewer individuals with wealthy (16.70%) and working status (18.90%) than the other clusters. It also included more frail individuals (30.55%) and fewer physically active people (63.24%) than Cluster 2 (“Social use”). The only significant difference observed between Clusters 2 and 3 (“Functional use”) was in the prevalence of frailty, with Cluster 3 showing a higher proportion (26.42% in Cluster 3 vs. 15.55% in Cluster 2). Associations between internet use patterns and frailty Table shows the relationships between internet use clusters and frailty, alongside the results from sex- and age-stratified analyses. In comparison with the “Less use” group (Reference), the “Social use” group (Cluster 2) had lower odds of frailty (odds ratio [OR], 0.42; 95% confidence interval [CI], 0.28–0.63), whereas the “Functional use” group did not show a significant association (OR, 0.82; 95% CI, 0.54–1.23). After adjusting for age, sex, socioeconomic status, health status, and lifestyle factors, the negative relationship between “Social use” and frailty remained significant (OR, 0.54; 95% CI, 0.35–0.84). Stratified analyses revealed that this relationship was consistent across sexes, with correlations between “Social use” and frailty in both males (OR, 0.54; 95% CI, 0.31–0.94) and females (OR, 0.46; 95% CI, 0.21–0.97). However, further age-group stratification indicated that the relationship between “Social use” and frailty was only present in males aged 65–74 years (OR, 0.41; 95% CI, 0.19–0.92) and females ≥ 75 years (OR, 0.25; 95% CI, 0.06–0.997). As a sensitivity analysis, we replicated the models from Table using multiple imputed data and obtained similar results (Table ).
Three internet use clusters were identified, as shown in Fig. , which presents z-scores for the frequency of various internet activities within each cluster in a heat map format. Cluster 1, named “Less use”, comprised 52.6% of the analyzed sample and exhibited the lowest frequency across all input internet activities (below the overall mean). Cluster 2, named “Social use” (28.7%), generally scored higher z-scores than Cluster 1, with z-scores for sending e-mails and texting/video calls via social messaging apps were the highest across activities and clusters. Based on previous studies, we named this cluster as “social use” as email and texting/video calls were considered as social technology, indicating a pattern focused on social connectivity . In Cluster 3 (“Functional use”, 18.6%), z-scores for each activity were above the overall mean. Within this cluster, the highest frequencies were observed in activities related to information searching, followed by online shopping and entertainment activities like watching YouTube or online game.
Table shows descriptive characteristics and significant differences across the clusters. Cluster 1 (“Less use”) had a significantly higher percentage of older adults (52.64%), particularly those ≥ 75 years (50.64% in Cluster 1 vs. 31.27% in Cluster 2 and 23.21% in Cluster 3), and more females (48.63% in Cluster 1 vs. 36.75% in Cluster 3). Additionally, Cluster 1 had fewer individuals with wealthy (16.70%) and working status (18.90%) than the other clusters. It also included more frail individuals (30.55%) and fewer physically active people (63.24%) than Cluster 2 (“Social use”). The only significant difference observed between Clusters 2 and 3 (“Functional use”) was in the prevalence of frailty, with Cluster 3 showing a higher proportion (26.42% in Cluster 3 vs. 15.55% in Cluster 2).
Table shows the relationships between internet use clusters and frailty, alongside the results from sex- and age-stratified analyses. In comparison with the “Less use” group (Reference), the “Social use” group (Cluster 2) had lower odds of frailty (odds ratio [OR], 0.42; 95% confidence interval [CI], 0.28–0.63), whereas the “Functional use” group did not show a significant association (OR, 0.82; 95% CI, 0.54–1.23). After adjusting for age, sex, socioeconomic status, health status, and lifestyle factors, the negative relationship between “Social use” and frailty remained significant (OR, 0.54; 95% CI, 0.35–0.84). Stratified analyses revealed that this relationship was consistent across sexes, with correlations between “Social use” and frailty in both males (OR, 0.54; 95% CI, 0.31–0.94) and females (OR, 0.46; 95% CI, 0.21–0.97). However, further age-group stratification indicated that the relationship between “Social use” and frailty was only present in males aged 65–74 years (OR, 0.41; 95% CI, 0.19–0.92) and females ≥ 75 years (OR, 0.25; 95% CI, 0.06–0.997). As a sensitivity analysis, we replicated the models from Table using multiple imputed data and obtained similar results (Table ).
The present study examined internet use as a health factor in an older population. We specifically aimed to identify whether and which type of internet use was associated with frailty in older adults. We identified three patterns of internet use: “less use”, “social use”, and “functional use”. Among them, “social use” was independently associated with a lower prevalence of frailty compared to “less use”, while ‘functional use’ was not significantly associated with frailty. Furthermore, this relationship was consistent across sexes, but exhibited age-related heterogeneity. To the best of our knowledge, this is the first study to examine the association between internet use and frailty status in community-dwelling older adults, including sex- and age-based heterogeneities in this association. The results showing the protective association of internet use with frailty is consistent with a similar study on postmenopausal middle-aged and older women, which reported the non-use of internet services as a predictor of frailty; however, older men were not included in this study . Another study reported that internet use exerted protective effects against frailty in individuals > 70 years in Spain; however, this relationship was not independent of potential confounders . These studies collectively assumed that the internet’s empowerment in preventing frailty may be attributed to an active, internet-based social life. However, further evidence to support this hypothesis was not provided. The present study contributes additional support for a social pathway linking internet use to frailty. The results obtained herein suggest that the protective effects of internet use against frailty are not simply a matter of presence or absence. Among the various patterns of usage, social use is specifically associated with a lower prevalence of frailty. To verify stability, we performed multiple logistic regressions using the functional use group as a reference group (Table ) and the results obtained consistently revealed a negative relationship between social use and frailty. We identified similar studies, although few, on other health-related topics in older adults. One study reported that the social purpose of a phone, not entertainment purposes, was associated with reduced loneliness , while another study compared seven specific types of internet use between 2013 and 2016 and showed that only communicating with friends or family predicted a lower risk of depression . While the causal pathways linking the social use of digital technology and frailty have not yet been established, we propose several mechanisms: social, psychological, and physical pathways. The effects of internet use on physical and mental health may be mediated through social connections . Digital technology, such as the internet, transcends geographical and physical limitations, facilitating the maintenance or expansion of social networks. Therefore, internet use may empower individuals to grasp the benefits of social capital derived from digital development. For example, online social contact has been reported to reduce loneliness and decrease social isolation [ – ], all of which are well-known risk factors for frailty . Similarly, psychological factors affect frailty in older individuals , and the positive effects of digital technology use on depression have been widely reported [ , , ]. Furthermore, studies have suggesting a boosting effect of digital technology use on self-esteem and social efficiency in older adults , which may have a positive impact on frailty . It is important to note that a strong relationship has been reported between cognitive function and frailty, particularly physical frailty . Internet use in daily life has recently shown to be associated with cognitive function . However, it’ worth noting that one criticism of internet use is its possibility to increase the risk of social isolation in the real world . Some studies suggest that internet use for social interaction (rather than as an escape from the real world) is beneficial for health . Similarly, excessive internet use has been associated with a higher prevalence of depression and cognitive decline, highlighting the importance of moderation . In Japan, older adults generally have low levels of internet use , and the internet users in our data were not heavy users (generally low frequencies; see Table ). Future research considering the extent of internet use and its complex relationship with real-world social networks is needed. Sex- and age-based heterogeneities revealed a negative relationship between social internet use and frailty that was more obvious among young-old males (aged 65–74 years) and old-old females (≥ 75 years). This may be explained by changes in social networks throughout the course of life and sex differences in the social division of labor. In Japan, men in the ‘young-old’ stage (65–74 years) are often transitioning to retirement (Retirement age: 60-65 years in Japan). This transition may be particularly significant for men, as they typically have higher workforce participation rates but lower engagement in informal social networks compared to women in Japan . Therefore, old Japanese men appear to benefit from online social networking because it provides a compensatory role to meet their needs of maintaining a social network during the retirement transition and post-retirement periods; however, men in the ‘old-old’ stage (≥ 75 years) enter a later stage of life where the effects of declining physical abilities become more apparent. On the other hand, women generally have higher social needs in many cultural contexts, making the social deficits due to physical restrictions or shrinking social networks more significant during the ‘old-old’ stage. The social network shrinks in later life stages due to aging and health issues . A previous study reported that Japanese women benefited more than men from bridge social capital . Online social interactions may help females ≥ 75 years to connect with diverse social networks. The impact of online information gathering on health outcomes is not consistent . Some studies highlighted positive impacts on health literacy, health behavior, and physical health , whereas others reported that online information searches caused anxiety . The present study, conducted in Japan during the COVID-19 pandemic, found no relationship between functional use and frailty. This result may have been affected by psychological stress due to the pandemic, as reported in a previous study . An excessive focus on online information seeking may exacerbate its negative effects on the psychological status. Frail individuals also exhibit higher anxiety levels than non-frail individuals, potentially leading to increased online information-seeking behavior. Additionally, a small percentage of the functional use group engaged in entertainment activities, which may be linked to sedentary behavior . The present results also demonstrated that fewer individuals engaged in physical activity in the functional use group than in the social use group. The present study has several strengths. It is the first to obtain evidence from the oldest population of Japan, a super-aged society. Furthermore, our survey had a high response rate of 71.6%, providing a high level of representativeness. Although there were missing responses on internet use and frailty scales, we obtained consistent results based on multiple imputations, which supports the reliability of the present results. However, there are also several limitations that need to be addressed. Since this was a cross-sectional study, we cannot establish causality. Moreover, our sample comprised older people who were not using long-term care services; therefore, the results obtained may only be generalized to self-reliant older adults in the community. In addition, data were obtained from one area in the second largest city in Japan; therefore, the sample lacks representativeness, making it difficult to generalize to the entire older people in Japan. Similarly, the study sample included only Japanese, and the KCL assessment tool used to identify frailty is primarily applied in Japan. These factors may limit the generalizability of our findings to other countries and populations. Another limitation is that the survey may have some recall bias. It should also be noted that “social use” in this study refers to messaging and video calls via social messaging apps (e.g., LINE), which may present social interactions within close social networks. We are unable to extend our results to broader online social networks such as using of social networking sites (e.g., Facebook), or media sharing apps (e.g., Instagram), and their potential associations with frailty. Different types of social relationships may have varied impacts on health . While Facebook and Instagram usage remains relatively low among older adults in Japan , further research involving specific types of online social use is suggested. Lastly, our classification is based on the cluster analysis of frequencies of internet activities and lacks further differentiation regarding their purposes of use. More detailed data of internet use are needed in future studies.
This cross-sectional study explored the association between internet use patterns and frailty among community-dwelling older adults. Social internet use, but not functional use, was associated with reduced odds of frailty. The association varied based on sex and age, highlighting the potential of technology in promoting social engagement for older population. These results provide timely evidence for incorporating digital technology into health care and highlight the potential in promoting social engagement for older adults. However, these findings are cross-sectional, further longitudinal study is needed to determine the mechanisms.
Below is the link to the electronic supplementary material. Supplementary Material 1
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Synergistic effect of ultrasound and antimicrobial solutions of cecropin P1 in the deactivation of | db94c352-1f2a-4c4f-ac1a-0851bd4372f3 | 10329002 | Microbiology[mh] | Thermal processing is still considered a superior method in the food industry to preserve food and extend shelf life; however, it is an energy-intensive process that results in a loss of food quality. To overcome this limitation, various novel alternative methods have been developed to replace at least partially thermal processing to minimize the loss in food quality at adequate safety levels. Ultrasound has been a part of actively emerging technologies in food processing. The physical and biological effect of sound waves generated from high-frequency ultrasound (100–300 kHz) has been investigated for years, as discussed in an early study by Loomis and colleagues , . However, high-frequency ultrasound (more than 100 kHz) has not been used extensively for food preservation and processing except for food quality monitoring and diagnostic purposes – . Depending on its operating parameters (frequency, energy intensity, exposure time) and food types, ultrasound may have a wide-ranging impact on food components and food sensory qualities, both positive and critical results – . Sound waves with lower frequency (20–100 kHz) yet of higher energy, which is referred to as “conventional power ultrasound,” has been shown to destroy microbial cells with minimum adverse effects on food quality such as vitamins, taste, and color – . The primary antimicrobial effect of ultrasound is due to intense acoustic cavitation generated from the sound wave. Ultrasound alone can make some bacteria inactive, but it requires high power to achieve complete deactivation. For preservation purposes, combining with other physical or chemical treatments can lower the processing cost and enhance its effectiveness. To minimize the thermal effect on food, ultrasound-assisted with temperature (thermosonication), pressure (manosonication), or a combination of both (manothermosonication) has been proven to be effective in reducing microbial levels compared to thermal or ultrasound preservation alone , . Various lab-scale studies using milk, fruit, and vegetable juices have shown that ultrasound-assisted technologies have the advantage of inactivating more bacterial cells with a minimum adverse effect on food sensory characteristics compared to conventional heat treatments – . On the therapeutic application, ultrasound's most researched antimicrobial effect is the co-application with conventional antibiotics. Several investigations demonstrate that a combination of low-intensity and low-frequency ultrasound and antibiotics is more effective in the deactivation of bacteria than antibiotics alone – . Antimicrobial peptides (AMPs) are naturally found in various organisms as part of innate immunity. The unique characteristics of AMPs are their small size (15–40 amino acids) and charge (often overall positive). They also disrupt cell membranes . AMPs have raised broad research interest due to their ability to combat antibiotic resistance and the potential for the replacement of antibiotics , . For food application, it is essential to use naturally derived AMPs that do not exhibit cytotoxicity. Based on animal cell culture studies, cecropin P1 is known to have no cytotoxicity . Antimicrobial peptides at low concentrations kill bacteria by pore formation in the cell membranes. Thus, transient pores formed by ultrasound cavitation should enhance antimicrobial activity. Our previous investigation has shown that a combination of longitudinal ultrasound or probe type (frequency 22 kHz) and AMP melittin in phosphate buffer media is more efficient in reducing cell density (CFU/mL) of Listeria monocytogenes up to four order magnitude compared to melittin or ultrasound alone . A combination of longitudinal ultrasound (22 kHz) and another classic AMP cecropin P1 was able to reduce cell density (CFU/mL) of E. coli O157:H7 up to five orders of magnitude in orange juice and milk . Following our previous study, the primary motivation of this research is to investigate the synergistic effect of a cylindrical ultrasound and a classic AMP cecropin P1 on antimicrobial activity against E. coli O157:H7. The E. coli O157:H7 is the most commonly identified Shiga toxin-producing E. coli (STEC) that can cause severe foodborne disease. Generally, the inactivation of microorganisms by ultrasound depends on many factors, including frequency, ultrasonic power and wave amplitude, temperature, sample volume, composition and physical properties of food, type ultrasound, and microorganism characteristics , , , . For example, the frequency influences the formation and size of cavitation bubbles. At higher frequencies, the acoustic cycle is shorter, giving less time for cavitation bubble formation; therefore, more bubbles with smaller sizes are generated and collapse with less energy – . In this study, a cylindrical ultrasonic processing unit was used to demonstrate the effect of ultrasound frequency and intensity on the synergistic effect of AMP. The design of this cylindrical system is based on the work of Borthwick et al. . The ultrasonic processing system for cell disruption that is commercially available is the probe-based transducer with an attached sonotrode with an activated resonance mode of 20–22 kHz. The design of an ultrasonic transducer having a lower or higher resonance frequency than the standard 20–22 kHz could be challenging. The cylindrical ultrasonic transducer is less bulky than the probe system and would be convenient for handling smaller sample volumes and for use outside the laboratory. Also, there is an inherent risk of hazardous foam formation due to the immersion of the probe in a liquid sample containing pathogens . The cylindrical ultrasonic device used in this study is also capable of continuous processing that can treat larger sample volumes. Therefore, this study aimed to investigate the performance of the cylindrical ultrasonic device against E. coli in combination with antimicrobial peptides for more efficient cell disruption and potential food preservation applications.
Materials Cecropin P1 (3.338, 86 g/mol) was purchased from Sigma-Aldrich (Saint Louis, MO) as a lyophilized powder with 95% purity. Brain Heart Infusion (BHI) medium was purchased from Neogen (Lansing, MI). The E. coli O157:H7 was obtained from Microbiology Laboratory, Department of Food Science, Purdue University, and calcein were purchased from Sigma Aldrich (Saint Louis, MO). In addition, 1,2-Dimyristoyl-sn-glycerol-3-phosphorylcholine (DMPC), Cholesterol, and hexadecyl hydrogen phosphate (DHP) with 99% purity were purchased from Avanti Polar Lipids (Alabaster, AL). The Piezoelectric cylinders with specified resonance frequencies of 14 kHz, 22 kHz, and 47 kHz were purchased from Steiner & Martins Inc. (Doral, FL) to make the cylindrical ultrasonic transducer. Methods E. coli preparation Preparation of E. coli O157:H7 was described elsewhere . Briefly, E. coli O157:H7 was grown in BHI (Neogen, MI) media until it reached 10 9 colony-forming units (CFU) per mL at 37 °C as measured by the plate count method. Design of cylindrical ultrasonic system Three different cylindrical ultrasonic transducers (14, 22, and 47 kHz) for ultrasonic processing systems have been designed and built based on Borthwick et al. . Figure A illustrates a plan view with the system dimensions parameters. Figure B shows the schematic view for the continuous flow ultrasonic processing system. The ultrasonic transducer was driven by an amplifier (RF amplifier model 150A100B, AR, Souderton, PA) and a function generator (Agilent model 33120A, Keysight Technologies, Santa Rosa, CA), which provided a sinusoidal signal. An oscilloscope is used to verify the working frequency (OWON SDS5032E, Zhangzhou, China). Cooling fans was fitted around the transducer to cool the system. Voltage amplitude was measured using a multimeter (Fluke, Everett, WA) with constant gain input and frequency to determine the ultrasound power level. Experimental procedure and analysis Ultrasound experiment For the batch system, inactivation of E. coli O157:H7 in PBS media was conducted using three different treatments: Ultrasound only for 5, 10, and 15 min, cecropin P1 only (20 µg/mL), and a combination of ultrasound with cecropin P1. The concentration of cecropin P1 20 µg/mL was chosen based on its minimum inhibitory concentration . The geometry and size of the sample container is a cylinder with dimension as mentioned in Fig. . The volume of cell suspension is 2 mL for all frequencies (14, 22, and 47 kHz). External fans are used to control the temperature during sonication. The treatment is done semicontinuous with 1 min on and 1 min off during the total treatment time. The initial cell density before all treatments is 10 9 CFU/mL. The treated E. coli samples were then grown on a BHI agar plate at 37 °C for 24 h to determine the number of viable cells per mL (CFU/mL) described previously , . For the continuous flow system (22 kHz), residence time was maintained at 6, 10, 15, and 34 min, and the number of viable cells was determined using the same method. Transmission electron microscopy Morphological changes in the bacterial cell after treatment with different ultrasonication frequencies (14, 22, and 47 kHz) were analyzed using transmission electron microscopy (TEM) as described previously , . Liposome preparation The liposome is employed as a bacterial mimic in dye leakage experiments due to cecropin P1 and ultrasonication experiments. The procedure for preparing liposomes consisting of DMPC, cholesterol, and DHP in a molar ratio of 5:4:1 encapsulated with calcein dye is described elsewhere , . The vesicle suspension was forced through a polycarbonate filter to form uniform lamellar liposomes and measured by Zeta sizer (Malvern Instrument, Worcestershire, UK). Fluorescence dye leakage The fluorescence of calcein dye released from liposome subjected to ultrasound and cecropin P1 treatments was measured based on the previously described protocol . Liposome loaded with calcein dye was treated with ultrasonication and cecropin P1 for 5, 10, and 15 min. The sample was then transferred to Spectrofluorometer (Flexstation II, Molecular Device, USA), and the fluorescence intensity was subsequently measured. The fluorescence intensity of calcein was normalized by the maximum intensity obtained by releasing all calcein from the liposome by adding Triton X-100 , . Fluorescence intensity of leaked calcein is due to pore formation in a liposome due to different treatments and therefore is a measure of deactivation of bacterial mimic. Statistical analysis Analysis of variance (ANOVA) with Tukey’s test was carried out to determine any significant differences ( p < 0.005) among the treatments. The ultrasound and dye leakage experiments were conducted in triplicates, and the mean values with standard deviations (SD) were recorded.
Cecropin P1 (3.338, 86 g/mol) was purchased from Sigma-Aldrich (Saint Louis, MO) as a lyophilized powder with 95% purity. Brain Heart Infusion (BHI) medium was purchased from Neogen (Lansing, MI). The E. coli O157:H7 was obtained from Microbiology Laboratory, Department of Food Science, Purdue University, and calcein were purchased from Sigma Aldrich (Saint Louis, MO). In addition, 1,2-Dimyristoyl-sn-glycerol-3-phosphorylcholine (DMPC), Cholesterol, and hexadecyl hydrogen phosphate (DHP) with 99% purity were purchased from Avanti Polar Lipids (Alabaster, AL). The Piezoelectric cylinders with specified resonance frequencies of 14 kHz, 22 kHz, and 47 kHz were purchased from Steiner & Martins Inc. (Doral, FL) to make the cylindrical ultrasonic transducer.
E. coli preparation Preparation of E. coli O157:H7 was described elsewhere . Briefly, E. coli O157:H7 was grown in BHI (Neogen, MI) media until it reached 10 9 colony-forming units (CFU) per mL at 37 °C as measured by the plate count method. Design of cylindrical ultrasonic system Three different cylindrical ultrasonic transducers (14, 22, and 47 kHz) for ultrasonic processing systems have been designed and built based on Borthwick et al. . Figure A illustrates a plan view with the system dimensions parameters. Figure B shows the schematic view for the continuous flow ultrasonic processing system. The ultrasonic transducer was driven by an amplifier (RF amplifier model 150A100B, AR, Souderton, PA) and a function generator (Agilent model 33120A, Keysight Technologies, Santa Rosa, CA), which provided a sinusoidal signal. An oscilloscope is used to verify the working frequency (OWON SDS5032E, Zhangzhou, China). Cooling fans was fitted around the transducer to cool the system. Voltage amplitude was measured using a multimeter (Fluke, Everett, WA) with constant gain input and frequency to determine the ultrasound power level. Experimental procedure and analysis Ultrasound experiment For the batch system, inactivation of E. coli O157:H7 in PBS media was conducted using three different treatments: Ultrasound only for 5, 10, and 15 min, cecropin P1 only (20 µg/mL), and a combination of ultrasound with cecropin P1. The concentration of cecropin P1 20 µg/mL was chosen based on its minimum inhibitory concentration . The geometry and size of the sample container is a cylinder with dimension as mentioned in Fig. . The volume of cell suspension is 2 mL for all frequencies (14, 22, and 47 kHz). External fans are used to control the temperature during sonication. The treatment is done semicontinuous with 1 min on and 1 min off during the total treatment time. The initial cell density before all treatments is 10 9 CFU/mL. The treated E. coli samples were then grown on a BHI agar plate at 37 °C for 24 h to determine the number of viable cells per mL (CFU/mL) described previously , . For the continuous flow system (22 kHz), residence time was maintained at 6, 10, 15, and 34 min, and the number of viable cells was determined using the same method. Transmission electron microscopy Morphological changes in the bacterial cell after treatment with different ultrasonication frequencies (14, 22, and 47 kHz) were analyzed using transmission electron microscopy (TEM) as described previously , . Liposome preparation The liposome is employed as a bacterial mimic in dye leakage experiments due to cecropin P1 and ultrasonication experiments. The procedure for preparing liposomes consisting of DMPC, cholesterol, and DHP in a molar ratio of 5:4:1 encapsulated with calcein dye is described elsewhere , . The vesicle suspension was forced through a polycarbonate filter to form uniform lamellar liposomes and measured by Zeta sizer (Malvern Instrument, Worcestershire, UK). Fluorescence dye leakage The fluorescence of calcein dye released from liposome subjected to ultrasound and cecropin P1 treatments was measured based on the previously described protocol . Liposome loaded with calcein dye was treated with ultrasonication and cecropin P1 for 5, 10, and 15 min. The sample was then transferred to Spectrofluorometer (Flexstation II, Molecular Device, USA), and the fluorescence intensity was subsequently measured. The fluorescence intensity of calcein was normalized by the maximum intensity obtained by releasing all calcein from the liposome by adding Triton X-100 , . Fluorescence intensity of leaked calcein is due to pore formation in a liposome due to different treatments and therefore is a measure of deactivation of bacterial mimic. Statistical analysis Analysis of variance (ANOVA) with Tukey’s test was carried out to determine any significant differences ( p < 0.005) among the treatments. The ultrasound and dye leakage experiments were conducted in triplicates, and the mean values with standard deviations (SD) were recorded.
preparation Preparation of E. coli O157:H7 was described elsewhere . Briefly, E. coli O157:H7 was grown in BHI (Neogen, MI) media until it reached 10 9 colony-forming units (CFU) per mL at 37 °C as measured by the plate count method.
Three different cylindrical ultrasonic transducers (14, 22, and 47 kHz) for ultrasonic processing systems have been designed and built based on Borthwick et al. . Figure A illustrates a plan view with the system dimensions parameters. Figure B shows the schematic view for the continuous flow ultrasonic processing system. The ultrasonic transducer was driven by an amplifier (RF amplifier model 150A100B, AR, Souderton, PA) and a function generator (Agilent model 33120A, Keysight Technologies, Santa Rosa, CA), which provided a sinusoidal signal. An oscilloscope is used to verify the working frequency (OWON SDS5032E, Zhangzhou, China). Cooling fans was fitted around the transducer to cool the system. Voltage amplitude was measured using a multimeter (Fluke, Everett, WA) with constant gain input and frequency to determine the ultrasound power level.
Ultrasound experiment For the batch system, inactivation of E. coli O157:H7 in PBS media was conducted using three different treatments: Ultrasound only for 5, 10, and 15 min, cecropin P1 only (20 µg/mL), and a combination of ultrasound with cecropin P1. The concentration of cecropin P1 20 µg/mL was chosen based on its minimum inhibitory concentration . The geometry and size of the sample container is a cylinder with dimension as mentioned in Fig. . The volume of cell suspension is 2 mL for all frequencies (14, 22, and 47 kHz). External fans are used to control the temperature during sonication. The treatment is done semicontinuous with 1 min on and 1 min off during the total treatment time. The initial cell density before all treatments is 10 9 CFU/mL. The treated E. coli samples were then grown on a BHI agar plate at 37 °C for 24 h to determine the number of viable cells per mL (CFU/mL) described previously , . For the continuous flow system (22 kHz), residence time was maintained at 6, 10, 15, and 34 min, and the number of viable cells was determined using the same method. Transmission electron microscopy Morphological changes in the bacterial cell after treatment with different ultrasonication frequencies (14, 22, and 47 kHz) were analyzed using transmission electron microscopy (TEM) as described previously , . Liposome preparation The liposome is employed as a bacterial mimic in dye leakage experiments due to cecropin P1 and ultrasonication experiments. The procedure for preparing liposomes consisting of DMPC, cholesterol, and DHP in a molar ratio of 5:4:1 encapsulated with calcein dye is described elsewhere , . The vesicle suspension was forced through a polycarbonate filter to form uniform lamellar liposomes and measured by Zeta sizer (Malvern Instrument, Worcestershire, UK). Fluorescence dye leakage The fluorescence of calcein dye released from liposome subjected to ultrasound and cecropin P1 treatments was measured based on the previously described protocol . Liposome loaded with calcein dye was treated with ultrasonication and cecropin P1 for 5, 10, and 15 min. The sample was then transferred to Spectrofluorometer (Flexstation II, Molecular Device, USA), and the fluorescence intensity was subsequently measured. The fluorescence intensity of calcein was normalized by the maximum intensity obtained by releasing all calcein from the liposome by adding Triton X-100 , . Fluorescence intensity of leaked calcein is due to pore formation in a liposome due to different treatments and therefore is a measure of deactivation of bacterial mimic.
For the batch system, inactivation of E. coli O157:H7 in PBS media was conducted using three different treatments: Ultrasound only for 5, 10, and 15 min, cecropin P1 only (20 µg/mL), and a combination of ultrasound with cecropin P1. The concentration of cecropin P1 20 µg/mL was chosen based on its minimum inhibitory concentration . The geometry and size of the sample container is a cylinder with dimension as mentioned in Fig. . The volume of cell suspension is 2 mL for all frequencies (14, 22, and 47 kHz). External fans are used to control the temperature during sonication. The treatment is done semicontinuous with 1 min on and 1 min off during the total treatment time. The initial cell density before all treatments is 10 9 CFU/mL. The treated E. coli samples were then grown on a BHI agar plate at 37 °C for 24 h to determine the number of viable cells per mL (CFU/mL) described previously , . For the continuous flow system (22 kHz), residence time was maintained at 6, 10, 15, and 34 min, and the number of viable cells was determined using the same method.
Morphological changes in the bacterial cell after treatment with different ultrasonication frequencies (14, 22, and 47 kHz) were analyzed using transmission electron microscopy (TEM) as described previously , .
The liposome is employed as a bacterial mimic in dye leakage experiments due to cecropin P1 and ultrasonication experiments. The procedure for preparing liposomes consisting of DMPC, cholesterol, and DHP in a molar ratio of 5:4:1 encapsulated with calcein dye is described elsewhere , . The vesicle suspension was forced through a polycarbonate filter to form uniform lamellar liposomes and measured by Zeta sizer (Malvern Instrument, Worcestershire, UK).
The fluorescence of calcein dye released from liposome subjected to ultrasound and cecropin P1 treatments was measured based on the previously described protocol . Liposome loaded with calcein dye was treated with ultrasonication and cecropin P1 for 5, 10, and 15 min. The sample was then transferred to Spectrofluorometer (Flexstation II, Molecular Device, USA), and the fluorescence intensity was subsequently measured. The fluorescence intensity of calcein was normalized by the maximum intensity obtained by releasing all calcein from the liposome by adding Triton X-100 , . Fluorescence intensity of leaked calcein is due to pore formation in a liposome due to different treatments and therefore is a measure of deactivation of bacterial mimic.
Analysis of variance (ANOVA) with Tukey’s test was carried out to determine any significant differences ( p < 0.005) among the treatments. The ultrasound and dye leakage experiments were conducted in triplicates, and the mean values with standard deviations (SD) were recorded.
Effect of ultrasound power Figure shows the effect of different power levels on the inactivation of E. coli cells using ultrasound, cecropin P1, and a combination of both at a fixed frequency of 22 kHz. As expected, more deactivations occur for a longer treatment time, although the difference is less significant at 10 and 15 min. Based on ANOVA statistical analysis, the effect of different power levels (1 W, 3 W, 5 W, and 8 W) and treatment types (ultrasound, cecropin P1, and a combination of both) showed significant difference ( p < 0.05) in the deactivation of E. coli . For example, in ultrasonic treatment at a power level of 5W, the cell density decreases from an initial value of 10 9 CFU/mL to 8.8 × 10 7 CFU/mL, 1.8 × 10 7 CFU/mL, and 2.2 × 10 6 CFU/mL for treatment times of 5, 10, and 15 min, respectively, as shown in Fig. . In addition, more cells are deactivated as the power level increases. Under ultrasound treatment for 15 min, cell density decreases to 8.6 × 10 7 CFU/mL from the initial value of 10 9 CFU/mL for a power level of 1W. In contrast, the cell density for a power level of 5W is much lower at a value of 2.2 × 10 6 CFU/mL. As expected, for treatment with cecropin P1 only (in the absence of ultrasound), more deactivation occurred at longer treatment times, resulting in decreased cell density. It is interesting to note that cell density was lower for combined treatment compared to either ultrasound-only or cecropin P1-only treatments. For example, for a power level of 5W and 10 min treatment time, cell density was 1.1 × 10 5 CFU/mL for combined treatment compared to 1.8 × 10 7 CFU/mL for ultrasound and 1.4 × 10 8 CFU/mL for cecropin P1. This result indicated synergism between ultrasonication and cecropin P1 treatments. However, the synergism was more pronounced for intermediate power levels of 3W and 5W ( p < 0.05), especially at longer treatment times. For power levels of 1W and 3W, there was negligible temperature rise for all treatment times. For higher power levels (5W and 8W), the temperature rise was significant (from 23 to 35 °C) only for 15 min treatment time. Ultrasonication leads to pressure waves of ultrasonication frequency in the liquid medium. The amplitude of these waves is higher at higher power inputs . At sufficiently high-power intensities, ultrasonication has been known to destroy microorganisms and enzymes in food and break down microstructures – . Power level is one of the critical factors affecting the efficiency of ultrasound treatment. Low pressure caused by these pressure waves results in the formation of bubbles in the medium due to cavitation. These bubbles collapse, thus resulting in shock waves that emanate radially into the surrounding medium. They interact with neighboring bacterial cell membranes and push the phospholipid heads apart, forming transient pores. High power produces higher pressure amplitude, thereby causing a more significant number of bubbles due to cavitation and more violent collapse. In the previous study , we presented the result from cell deactivation using a commercial probe-type ultrasonic system, which is used to sonicate a larger sample volume of 5 mL compared to the cylindrical system that has a smaller sample volume of 2 mL. If we compare the result from our previous study at a fixed frequency of 22 kHz and power density of 40W/5 mL and 8W/2 mL, respectively, for the probe and cylindrical system, and with an initial cell density of 10 9 CFU/mL, the cylindrical system was able to deactivate cell faster (15 min compared to 30 min) and one order of magnitude higher at lower power level. A similar result has been observed by Borthwick et al. . Their result showed that a tubular ultrasonic processing device (267 kHz, 36W) has six times faster protein release and higher cell deactivation per 10 7 Saccharomyces cerevisiae yeast suspension compared to a 20 kHz probe system within the 60 s. This observation might be due to the radial mode of vibration inward in the cylindrical system, which concentrated pressure at the center of the cylinder. The advantage of a cylindrical ultrasonic processing system also made it possible to sonicate a smaller sample without foaming, which is hard to avoid in a conventional 20 kHz probe-type device. Effect of ultrasound frequencies on synergistic effect Based on results in Fig. , the synergistic effect is more pronounced at a power level of 3W and higher for a longer exposure time (15 min) ( p < 0.05). The most significant synergistic effect can be seen at a power level of 5W ( p < 0.05). As we described previously, the ultrasonication method kills bacterial cells by forming transient pores in the cell membranes due to shock waves generated by the collapse of bubbles formed by cavitation. Thus, transient pores formed by ultrasonication should result in the diffusion of intracellular matter and enhancement of antimicrobial activity . Pore formation due to ultrasonication can also be observed later in TEM images presented in Fig. . In vegetative forms, Gram-negative bacterial cells such as E. coli are more susceptible to ultrasound treatment compared to Gram-positive because they have thinner peptidoglycan , . Figure shows the effect of frequencies at a fixed power level of 8W on the deactivation of E. coli using ultrasound, cecropin P1, and a combination of both. It must be noted that treatment times of only 0.5 and 1 min were investigated and were, therefore, much shorter than those for experiments reported in Fig. . Comparison of deactivation at different frequencies could only be carried out for short treatment times (up to 1 min) since longer treatment times at a higher frequency of 47 kHz resulted in excessive heating of the sample. Deactivation is more at higher frequencies. For example, for an ultrasound treatment time of 1 min, the cell density values were 1.0 × 10 8 , 1.4 × 10 6 , and 1.3 × 10 4 CFU/mL at 14, 22, and 47 kHz, respectively. Cell deactivation was significantly pronounced at higher frequencies ( p < 0.05) than at 14 kHz at these short treatment times. Combined ultrasound and cecropin P1 treatments were more effective than individual treatments ( p < 0.05). For example, for 0.5 min treatment at 47 kHz, cell density for combined treatment was 1.3 × 10 4 CFU/mL compared to 3.1 × 10 5 CFU/mL for ultrasound only and 1.4 × 10 8 CFU/mL for cecropin P1 only. Also, synergism was highest for the highest frequency of 47 kHz, especially at 0.5 min treatment time. Results indicate that cell deactivation for a concise treatment time of 1 min at a higher frequency of 47 kHz is comparable to deactivation at a lower frequency of 22 kHz for a much longer treatment time of 15 min. This result suggests that ultrasonication efficiency increases dramatically at higher frequencies. The formation of transient pores by sonication facilitates cell death by reducing the energy barrier for the formation and growth of pores by cecropin P1 . At sufficiently high intensities, these transient pores can be large enough to cause considerable leakage of intracellular matter, thus leading to cell death. At lower intensities, however, cecropin P1 will adsorb onto the inner lining of the transient pore, with the hydrophilic side chains lining the inside of the pore and the hydrophobic side chains pointing towards the lipid tails. Further adsorption of cecropin P1 onto preexisting pores would result in the growth of these pores, eventually leading to leakage of intracellular matter and cell death , . Hence the synergistic effect between ultrasonication and antimicrobial peptide action. The synergistic effect was observed for longitudinal probe treatment and radial ultrasonic processing using a cylindrical probe. A study done by Ozuna et al. also reported the synergistic effects of antimicrobial peptides of thurincin H (40 μg/mL) and probe-type power ultrasound (frequency of 20–25 kHz, the nominal power of 150 W) in milk and orange juice which effectively inactivate L. innocua and E. coli , with higher levels of inactivation than those observed when applying these technologies separately. The frequency of sound waves influences the number and size of cavitation bubbles. The acoustic cycle at higher frequencies is shorter, giving less time for cavitation bubble formation and producing smaller cavitation bubbles than at lower frequencies. Also, increasing the ultrasonic frequency while maintaining the same ultrasonic power will result in a more significant number of smaller cavitation bubbles. As a result, at higher ultrasonic frequencies, more bubbles formed with a smaller size which collapsed with less energy , . Figure demonstrates that at 1 min of exposure time, the cell deactivation is higher at a higher frequency (47 kHz). The synergistic effect between ultrasonication and cecropin P1 was still visible at this frequency. It could deactivate cells up to six orders of magnitude comparable to a 22 kHz case within 15 min of treatment. However, at 14 kHz, the deactivation is less pronounced compared to 22 and 47 kHz. This result suggests that the increased bubble concentration at a higher frequency is the predominant effect on deactivation. Previous studies have also shown that higher frequencies than 20–25 kHz were able to deactivate more bacterial and algal cells , . The extent of sonication time is limited at 47 kHz due to temperature build-up during cavitation. Therefore, the experiment is carried out for less than 2 min. A better cooling strategy is needed to overcome this. Continuous flow system Deactivation experiments were performed in a continuous flow ultrasonic processing system using a 22 kHz cylindrical transducer at different residence times (6, 10, 15, and 34 min). The viable cell count after treatment in a continuous flow system is presented in Fig. . Higher residence time (34 min) is more effective in deactivating more E. coli cells (up to four orders of magnitude). For example, for ultrasound treatment only, cell density decreased from 3.0 × 10 7 CFU/mL to 8.1 × 10 5 CFU/mL when the residence time was increased from 6 to 34 min (Fig. ). The continuous system also observed synergism between ultrasound and cecropin P1 treatments. Synergism was more pronounced at residence times of 15 and 34 min. For example, combined treatment at 6 min residence time reduced cell density to 6.2 × 10 6 CFU/mL compared to 3.0 × 10 7 and 1.4 × 10 8 CFU/mL for ultrasound and cecropin P1, respectively. On the other hand, at a residence time of 34 min, combined treatment gave 9.9 × 10 4 CFU/mL compared to 8.1 × 10 5 and 1.4 × 10 8 CFU/mL for ultrasound and cecropin P1, respectively. However, the continuous system is less effective in deactivation, as evidenced by cell density reduction only by four orders (10 9 –10 5 ) as opposed to a decrease by six orders (10 9 –10 3 ) for 15 min batch treatments. The synergistic effect and cell deactivation are less in a continuous flow system (Fig. ) if we compare this result with the batch system (Figs. and ) at a comparable power level of 8W. This observation might be due to the lower actual pressure field inside the bacterial suspension. The fixtures in a continuous system might act as an anchor that damped the transducer's vibration. The advantage of using a continuous system over a batch system is the flexibility to treat larger sample volumes without temperature build-up. Dye leakage due to treatment with cecropin P1 and cylindrical ultrasonication As explained in the methods, the fluorescence intensity of leaked calcein from liposome was measured at different times from the moment the sample was transferred to Spectrofluorometer. The fluorescence intensity of the sample was higher than the background when it was transferred to Spectrofluoremeter, thus indicating that dye leakage had occurred due to different treatments. The calcein dye continued to leak, with the fluorescence intensity increasing slowly with time, eventually reaching a constant value at a sufficiently long time (10 min). The final steady-state fluorescence intensity is a measure of total dye leakage and is therefore compared for different treatments in Fig. . Fluorescence intensity increased with ultrasound treatment time, thus indicating more damage to liposomes (more leakage), consistent with cell deactivation results reported earlier. The results also showed that dye leakage is higher for liposomes treated with a combination of cecropin P1 and ultrasonication, demonstrating synergism between the two. Calcein leakage intensity from liposomes depends on acoustic pressure and exposure time, although the differences are minor (Fig. ). The maximum leakage intensity of this marker dye is slightly higher after treatment with a combination of ultrasound and cecropin P1 at 8W for 15 min compared to 3W and 5W, which is also consistent with the cell viability reduction. As explained previously, transient pore formation due to sonication will cause this dye to leak into the environment and finally approach equilibrium. Similar results were also observed in some studies which correlated ultrasound-induced bioeffect with energy density , . Effect of ultrasonication on morphology of bacterial cell Morphological changes in E. coli cells occurred after exposure to ultrasonication at different frequencies (14, 22, and 47 kHz) and a combination of ultrasound and cecropin P1, as can be seen from TEM images in Fig. . The cell wall is disrupted, and the cytoplasmic material is released to the extracellular medium when exposed to ultrasonication and combined treatment. The pore formation, which resulted in leakage of intracellular material, was observed (pointed by red arrow) when E. coli cells were exposed to these treatments. In Fig. C, D and F, we can see multiple pore formations due to 22, 47 kHz, and a combination of ultrasound (22 kHz) and cecropin P1, respectively. Gram-negative bacteria such as E. coli have a thinner cell wall. Thus, it is more sensitive to ultrasound treatment. Based on our previous study , cecropin P1 alone could not completely deactivate E. coli at a minimum inhibitory concentration and a higher concentration, as indicated by the presence of some intact cells. The cylindrical system also observed a similar result (Fig. ). Transmission electron study done by other investigators also showed disintegration of Gram-negative bacteria E. coli B and Klebsiella pneumonia due to probe ultrasound treatment (frequency of 20 and 40 kHz) .
Figure shows the effect of different power levels on the inactivation of E. coli cells using ultrasound, cecropin P1, and a combination of both at a fixed frequency of 22 kHz. As expected, more deactivations occur for a longer treatment time, although the difference is less significant at 10 and 15 min. Based on ANOVA statistical analysis, the effect of different power levels (1 W, 3 W, 5 W, and 8 W) and treatment types (ultrasound, cecropin P1, and a combination of both) showed significant difference ( p < 0.05) in the deactivation of E. coli . For example, in ultrasonic treatment at a power level of 5W, the cell density decreases from an initial value of 10 9 CFU/mL to 8.8 × 10 7 CFU/mL, 1.8 × 10 7 CFU/mL, and 2.2 × 10 6 CFU/mL for treatment times of 5, 10, and 15 min, respectively, as shown in Fig. . In addition, more cells are deactivated as the power level increases. Under ultrasound treatment for 15 min, cell density decreases to 8.6 × 10 7 CFU/mL from the initial value of 10 9 CFU/mL for a power level of 1W. In contrast, the cell density for a power level of 5W is much lower at a value of 2.2 × 10 6 CFU/mL. As expected, for treatment with cecropin P1 only (in the absence of ultrasound), more deactivation occurred at longer treatment times, resulting in decreased cell density. It is interesting to note that cell density was lower for combined treatment compared to either ultrasound-only or cecropin P1-only treatments. For example, for a power level of 5W and 10 min treatment time, cell density was 1.1 × 10 5 CFU/mL for combined treatment compared to 1.8 × 10 7 CFU/mL for ultrasound and 1.4 × 10 8 CFU/mL for cecropin P1. This result indicated synergism between ultrasonication and cecropin P1 treatments. However, the synergism was more pronounced for intermediate power levels of 3W and 5W ( p < 0.05), especially at longer treatment times. For power levels of 1W and 3W, there was negligible temperature rise for all treatment times. For higher power levels (5W and 8W), the temperature rise was significant (from 23 to 35 °C) only for 15 min treatment time. Ultrasonication leads to pressure waves of ultrasonication frequency in the liquid medium. The amplitude of these waves is higher at higher power inputs . At sufficiently high-power intensities, ultrasonication has been known to destroy microorganisms and enzymes in food and break down microstructures – . Power level is one of the critical factors affecting the efficiency of ultrasound treatment. Low pressure caused by these pressure waves results in the formation of bubbles in the medium due to cavitation. These bubbles collapse, thus resulting in shock waves that emanate radially into the surrounding medium. They interact with neighboring bacterial cell membranes and push the phospholipid heads apart, forming transient pores. High power produces higher pressure amplitude, thereby causing a more significant number of bubbles due to cavitation and more violent collapse. In the previous study , we presented the result from cell deactivation using a commercial probe-type ultrasonic system, which is used to sonicate a larger sample volume of 5 mL compared to the cylindrical system that has a smaller sample volume of 2 mL. If we compare the result from our previous study at a fixed frequency of 22 kHz and power density of 40W/5 mL and 8W/2 mL, respectively, for the probe and cylindrical system, and with an initial cell density of 10 9 CFU/mL, the cylindrical system was able to deactivate cell faster (15 min compared to 30 min) and one order of magnitude higher at lower power level. A similar result has been observed by Borthwick et al. . Their result showed that a tubular ultrasonic processing device (267 kHz, 36W) has six times faster protein release and higher cell deactivation per 10 7 Saccharomyces cerevisiae yeast suspension compared to a 20 kHz probe system within the 60 s. This observation might be due to the radial mode of vibration inward in the cylindrical system, which concentrated pressure at the center of the cylinder. The advantage of a cylindrical ultrasonic processing system also made it possible to sonicate a smaller sample without foaming, which is hard to avoid in a conventional 20 kHz probe-type device.
Based on results in Fig. , the synergistic effect is more pronounced at a power level of 3W and higher for a longer exposure time (15 min) ( p < 0.05). The most significant synergistic effect can be seen at a power level of 5W ( p < 0.05). As we described previously, the ultrasonication method kills bacterial cells by forming transient pores in the cell membranes due to shock waves generated by the collapse of bubbles formed by cavitation. Thus, transient pores formed by ultrasonication should result in the diffusion of intracellular matter and enhancement of antimicrobial activity . Pore formation due to ultrasonication can also be observed later in TEM images presented in Fig. . In vegetative forms, Gram-negative bacterial cells such as E. coli are more susceptible to ultrasound treatment compared to Gram-positive because they have thinner peptidoglycan , . Figure shows the effect of frequencies at a fixed power level of 8W on the deactivation of E. coli using ultrasound, cecropin P1, and a combination of both. It must be noted that treatment times of only 0.5 and 1 min were investigated and were, therefore, much shorter than those for experiments reported in Fig. . Comparison of deactivation at different frequencies could only be carried out for short treatment times (up to 1 min) since longer treatment times at a higher frequency of 47 kHz resulted in excessive heating of the sample. Deactivation is more at higher frequencies. For example, for an ultrasound treatment time of 1 min, the cell density values were 1.0 × 10 8 , 1.4 × 10 6 , and 1.3 × 10 4 CFU/mL at 14, 22, and 47 kHz, respectively. Cell deactivation was significantly pronounced at higher frequencies ( p < 0.05) than at 14 kHz at these short treatment times. Combined ultrasound and cecropin P1 treatments were more effective than individual treatments ( p < 0.05). For example, for 0.5 min treatment at 47 kHz, cell density for combined treatment was 1.3 × 10 4 CFU/mL compared to 3.1 × 10 5 CFU/mL for ultrasound only and 1.4 × 10 8 CFU/mL for cecropin P1 only. Also, synergism was highest for the highest frequency of 47 kHz, especially at 0.5 min treatment time. Results indicate that cell deactivation for a concise treatment time of 1 min at a higher frequency of 47 kHz is comparable to deactivation at a lower frequency of 22 kHz for a much longer treatment time of 15 min. This result suggests that ultrasonication efficiency increases dramatically at higher frequencies. The formation of transient pores by sonication facilitates cell death by reducing the energy barrier for the formation and growth of pores by cecropin P1 . At sufficiently high intensities, these transient pores can be large enough to cause considerable leakage of intracellular matter, thus leading to cell death. At lower intensities, however, cecropin P1 will adsorb onto the inner lining of the transient pore, with the hydrophilic side chains lining the inside of the pore and the hydrophobic side chains pointing towards the lipid tails. Further adsorption of cecropin P1 onto preexisting pores would result in the growth of these pores, eventually leading to leakage of intracellular matter and cell death , . Hence the synergistic effect between ultrasonication and antimicrobial peptide action. The synergistic effect was observed for longitudinal probe treatment and radial ultrasonic processing using a cylindrical probe. A study done by Ozuna et al. also reported the synergistic effects of antimicrobial peptides of thurincin H (40 μg/mL) and probe-type power ultrasound (frequency of 20–25 kHz, the nominal power of 150 W) in milk and orange juice which effectively inactivate L. innocua and E. coli , with higher levels of inactivation than those observed when applying these technologies separately. The frequency of sound waves influences the number and size of cavitation bubbles. The acoustic cycle at higher frequencies is shorter, giving less time for cavitation bubble formation and producing smaller cavitation bubbles than at lower frequencies. Also, increasing the ultrasonic frequency while maintaining the same ultrasonic power will result in a more significant number of smaller cavitation bubbles. As a result, at higher ultrasonic frequencies, more bubbles formed with a smaller size which collapsed with less energy , . Figure demonstrates that at 1 min of exposure time, the cell deactivation is higher at a higher frequency (47 kHz). The synergistic effect between ultrasonication and cecropin P1 was still visible at this frequency. It could deactivate cells up to six orders of magnitude comparable to a 22 kHz case within 15 min of treatment. However, at 14 kHz, the deactivation is less pronounced compared to 22 and 47 kHz. This result suggests that the increased bubble concentration at a higher frequency is the predominant effect on deactivation. Previous studies have also shown that higher frequencies than 20–25 kHz were able to deactivate more bacterial and algal cells , . The extent of sonication time is limited at 47 kHz due to temperature build-up during cavitation. Therefore, the experiment is carried out for less than 2 min. A better cooling strategy is needed to overcome this.
Deactivation experiments were performed in a continuous flow ultrasonic processing system using a 22 kHz cylindrical transducer at different residence times (6, 10, 15, and 34 min). The viable cell count after treatment in a continuous flow system is presented in Fig. . Higher residence time (34 min) is more effective in deactivating more E. coli cells (up to four orders of magnitude). For example, for ultrasound treatment only, cell density decreased from 3.0 × 10 7 CFU/mL to 8.1 × 10 5 CFU/mL when the residence time was increased from 6 to 34 min (Fig. ). The continuous system also observed synergism between ultrasound and cecropin P1 treatments. Synergism was more pronounced at residence times of 15 and 34 min. For example, combined treatment at 6 min residence time reduced cell density to 6.2 × 10 6 CFU/mL compared to 3.0 × 10 7 and 1.4 × 10 8 CFU/mL for ultrasound and cecropin P1, respectively. On the other hand, at a residence time of 34 min, combined treatment gave 9.9 × 10 4 CFU/mL compared to 8.1 × 10 5 and 1.4 × 10 8 CFU/mL for ultrasound and cecropin P1, respectively. However, the continuous system is less effective in deactivation, as evidenced by cell density reduction only by four orders (10 9 –10 5 ) as opposed to a decrease by six orders (10 9 –10 3 ) for 15 min batch treatments. The synergistic effect and cell deactivation are less in a continuous flow system (Fig. ) if we compare this result with the batch system (Figs. and ) at a comparable power level of 8W. This observation might be due to the lower actual pressure field inside the bacterial suspension. The fixtures in a continuous system might act as an anchor that damped the transducer's vibration. The advantage of using a continuous system over a batch system is the flexibility to treat larger sample volumes without temperature build-up.
As explained in the methods, the fluorescence intensity of leaked calcein from liposome was measured at different times from the moment the sample was transferred to Spectrofluorometer. The fluorescence intensity of the sample was higher than the background when it was transferred to Spectrofluoremeter, thus indicating that dye leakage had occurred due to different treatments. The calcein dye continued to leak, with the fluorescence intensity increasing slowly with time, eventually reaching a constant value at a sufficiently long time (10 min). The final steady-state fluorescence intensity is a measure of total dye leakage and is therefore compared for different treatments in Fig. . Fluorescence intensity increased with ultrasound treatment time, thus indicating more damage to liposomes (more leakage), consistent with cell deactivation results reported earlier. The results also showed that dye leakage is higher for liposomes treated with a combination of cecropin P1 and ultrasonication, demonstrating synergism between the two. Calcein leakage intensity from liposomes depends on acoustic pressure and exposure time, although the differences are minor (Fig. ). The maximum leakage intensity of this marker dye is slightly higher after treatment with a combination of ultrasound and cecropin P1 at 8W for 15 min compared to 3W and 5W, which is also consistent with the cell viability reduction. As explained previously, transient pore formation due to sonication will cause this dye to leak into the environment and finally approach equilibrium. Similar results were also observed in some studies which correlated ultrasound-induced bioeffect with energy density , .
Morphological changes in E. coli cells occurred after exposure to ultrasonication at different frequencies (14, 22, and 47 kHz) and a combination of ultrasound and cecropin P1, as can be seen from TEM images in Fig. . The cell wall is disrupted, and the cytoplasmic material is released to the extracellular medium when exposed to ultrasonication and combined treatment. The pore formation, which resulted in leakage of intracellular material, was observed (pointed by red arrow) when E. coli cells were exposed to these treatments. In Fig. C, D and F, we can see multiple pore formations due to 22, 47 kHz, and a combination of ultrasound (22 kHz) and cecropin P1, respectively. Gram-negative bacteria such as E. coli have a thinner cell wall. Thus, it is more sensitive to ultrasound treatment. Based on our previous study , cecropin P1 alone could not completely deactivate E. coli at a minimum inhibitory concentration and a higher concentration, as indicated by the presence of some intact cells. The cylindrical system also observed a similar result (Fig. ). Transmission electron study done by other investigators also showed disintegration of Gram-negative bacteria E. coli B and Klebsiella pneumonia due to probe ultrasound treatment (frequency of 20 and 40 kHz) .
The deactivation of E. coli in PBS (pH 7.4) was performed using three different treatments: (1) ultrasound (22 kHz) at different power levels (1, 3, 5, and 8 W) and different exposure times (5, 10, and 15 min), (2) cecropin P1 (20 µg/mL), and (3) combination of both. The number of deactivated cells (CFU/mL) increases as the power level increases, and a synergistic effect is observed at a power level of 3W and higher. A combination of ultrasound and cecropin P1 treatment at 8W for 15 min reduced most of the cells (up to six orders of magnitude reduction) compared to individual treatments. Our results on the effect of different frequencies (14, 22, and 47 kHz) also show that a combination of higher frequency (47 kHz) and cecropin P1 for one minute of exposure time was able to deactivate more cells (up to six orders of magnitude reduction) compared to combined treatment at 14 and 22 kHz. A continuous flow ultrasonic processing system using a cylindrical transducer at 22 kHz with a power level of 8W demonstrated that longer residence time increases cell reduction. Cell reduction up to five orders of magnitude was achieved for the residence time of 34 min. The synergistic effect and cell deactivation at a comparable power level are less in the continuous flow system. This result might be due to a distribution of residence times experienced by the fluid in the cylinder. The dye leakage experiment and TEM confirmed the synergistic effect of ultrasonication and cecropin P1. TEM images show a single and multiple pore formation due to ultrasound and cecropin P1 treatments which lead to cell death.
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Keep the fire burning: a survey study on the role of personal resources for work engagement and burnout in medical residents and specialists in the Netherlands | 64959e17-9cfd-4564-b7c2-5f571e151c9b | 6858141 | Pediatrics[mh] | Healthcare professionals are well-known for their high work engagement, that is, their absorption by their work and dedication to patient care. Unfortunately, such vigour and dedication can also have a flip side. Healthcare professionals work in a very complex system with long and irregular working hours and they need to deal with various high job demands such as time pressure, emotionally taxing patient interactions, work-family conflict and job insecurity. These high job demands cause alarming high rates of burnout symptoms such as emotional exhaustion and cynicism in healthcare compared with other professions. Among physicians, medical residents seem to be especially at risk for burnout, with burnout symptoms often being reported by one out of four residents. This is hardly surprising: in addition to the job demands that all physicians face, residents also face high educational demands, need to get used to clinical rotations and shifts, experience high responsibility yet limited autonomy and experience high uncertainty about their future career. Additionally, residency marks a period that is characterised by stressful and demanding life events such as marriage and getting children. Obviously, burnout has a strong negative impact on healthcare professionals and their employers. Most important, burnout symptoms are associated with decreased quality of care through delayed decision making, unprofessional work behaviours (ie, conflict) and suboptimal patient care (ie, not adequately discussing treatment options with patients or making medical errors). Also, burnout is accompanied by long-term sickness leave and early retirement. It is the highly critical work environment of healthcare professionals and the high-stake consequences of their functioning that call for a deeper understanding of the demands and resources that relate to the work engagement and well-being (ie, a lack of burnout) of these professionals. Similarly, it is important to understand which factors can help physicians to stay motivated in spite of the demands they face. An important result of motivation is work engagement, a positive work-related state of mind characterised by vigour, dedication and absorption. Work engagement has been linked to employee performance across professions, including healthcare. Healthcare professionals who are engaged are also less likely to commit medical errors. Consequently, both (a lack of) burnout and work engagement are important components for the optimal functioning of healthcare professionals. Earlier research conceptualised burnout and work engagement as opposite poles of a continuum that are mutually exclusive. Recent research has evidenced that burnout and work engagement are (negatively) related, yet different constructs (ie, low burnout does not necessarily imply high engagement). Furthermore, these studies have shown that job characteristics that are associated with the prevalence of burnout are different from those that are associated with work engagement. Surprisingly, few of these studies were carried out in healthcare settings. Yet, knowledge of the job characteristics that relate to burnout and work engagement among healthcare professionals is essential to develop tailored interventions (eg, training, coaching) that support these professionals in their optimal functioning. Theoretical Framework: The Job Demands—Resources Model The Job Demands—Resources (JD-R) model proposes that work engagement and well-being are promoted when (healthcare) professionals have job resources that help them to cope with high job demands and that bolster their motivation. Generally, the JD-R model differentiates between two universal types of characteristics that people find in their jobs: that is, job demands on the one hand and job resources on the other hand. Job demands refer to ‘those physical, psychological, social or organisational aspects of the job that require sustained physical, and/or psychological effort and are therefore associated with physiological and/or psychological costs’. Examples of job demands are workload, time pressure and emotional demands. High job demands require professionals to spend sustained effort in order to meet perceived demands, which gradually drain resources and ultimately lead to depletion and exhaustion. That being said, job demands are considered the prime factor leading to burnout. Fortunately, professionals also have job resources that support them in coping with job demands. Such job resources, that are, ‘physical, psychological, social or organisational aspects of the job that help to either achieve work goals, reduce job demands and the associated physiological and psychological costs, or stimulate personal growth, learning and development’ can comprise both situational/external and personal/internal resources. Situational resources are, for example, colleague and supervisory support, and the amount of autonomy professionals have in their work. However, resources are not exclusively found in the environment, but people can also create them for themselves. Personal resources refer to individual psychological states such as an individual’s psychological capital (including self-efficacy, hope, optimism and resilience), self-compassion (treating oneself with kindness when things go wrong) and psychological flexibility (the ability to choose behaviours that are in line with one’s goals and values) that mirror people’s perception to control and impact successfully on the environment. Apart from supporting employees in coping with job demands, situational and personal resources are also important in their own right as they are considered the prime factor leading to work engagement. Meta-analytic studies have shown, for example, that colleague and supervisory support and optimism and self-efficacy were positively related to work engagement. The current study builds on the JD-R model that considers burnout and work engagement as independent yet correlated constructs and job demands and (situational and personal) resources as the main predictors of burnout and work engagement, respectively. Although the relationships between demands and resources as antecedents and burnout and work engagement as outcomes are confirmed in numerous studies, research also shows that the strength of these relationships varies. This variation is likely due to the different professional samples and work contexts that were studied. While residents and specialists work in the same occupational setting, they may face different job characteristics and, hence, different job demands and resources. As such, it is particularly relevant to examine whether the job demands, resources and outcomes, and the relationships among these variables, differ between residents and specialists. Insight into this topic can inform stakeholders how to regulate workplace practices in order to foster physician well-being and work engagement. Importantly, such information can ensure the effectiveness of interventions because it allows us to tailor interventions to a specific situation or group and tap into personal and situational characteristics that can be changed at the individual and the group level, respectively. In the current study, we therefore investigate how job demands (workload, job insecurity, work-family conflict), situational resources (autonomy, supervisor support, colleague support) and personal resources (psychological capital, self-compassion, psychological flexibility) relate to work engagement and burnout among specialists and residents.
The Job Demands—Resources (JD-R) model proposes that work engagement and well-being are promoted when (healthcare) professionals have job resources that help them to cope with high job demands and that bolster their motivation. Generally, the JD-R model differentiates between two universal types of characteristics that people find in their jobs: that is, job demands on the one hand and job resources on the other hand. Job demands refer to ‘those physical, psychological, social or organisational aspects of the job that require sustained physical, and/or psychological effort and are therefore associated with physiological and/or psychological costs’. Examples of job demands are workload, time pressure and emotional demands. High job demands require professionals to spend sustained effort in order to meet perceived demands, which gradually drain resources and ultimately lead to depletion and exhaustion. That being said, job demands are considered the prime factor leading to burnout. Fortunately, professionals also have job resources that support them in coping with job demands. Such job resources, that are, ‘physical, psychological, social or organisational aspects of the job that help to either achieve work goals, reduce job demands and the associated physiological and psychological costs, or stimulate personal growth, learning and development’ can comprise both situational/external and personal/internal resources. Situational resources are, for example, colleague and supervisory support, and the amount of autonomy professionals have in their work. However, resources are not exclusively found in the environment, but people can also create them for themselves. Personal resources refer to individual psychological states such as an individual’s psychological capital (including self-efficacy, hope, optimism and resilience), self-compassion (treating oneself with kindness when things go wrong) and psychological flexibility (the ability to choose behaviours that are in line with one’s goals and values) that mirror people’s perception to control and impact successfully on the environment. Apart from supporting employees in coping with job demands, situational and personal resources are also important in their own right as they are considered the prime factor leading to work engagement. Meta-analytic studies have shown, for example, that colleague and supervisory support and optimism and self-efficacy were positively related to work engagement. The current study builds on the JD-R model that considers burnout and work engagement as independent yet correlated constructs and job demands and (situational and personal) resources as the main predictors of burnout and work engagement, respectively. Although the relationships between demands and resources as antecedents and burnout and work engagement as outcomes are confirmed in numerous studies, research also shows that the strength of these relationships varies. This variation is likely due to the different professional samples and work contexts that were studied. While residents and specialists work in the same occupational setting, they may face different job characteristics and, hence, different job demands and resources. As such, it is particularly relevant to examine whether the job demands, resources and outcomes, and the relationships among these variables, differ between residents and specialists. Insight into this topic can inform stakeholders how to regulate workplace practices in order to foster physician well-being and work engagement. Importantly, such information can ensure the effectiveness of interventions because it allows us to tailor interventions to a specific situation or group and tap into personal and situational characteristics that can be changed at the individual and the group level, respectively. In the current study, we therefore investigate how job demands (workload, job insecurity, work-family conflict), situational resources (autonomy, supervisor support, colleague support) and personal resources (psychological capital, self-compassion, psychological flexibility) relate to work engagement and burnout among specialists and residents.
Study population From January to December 2017, we collected data from attending (specialists) and resident physicians at four academic hospitals and one general hospital in the Netherlands. The physicians were specialised or trained in pediatrics, internal medicine or neurology. Because this study is part of a larger programme offering individual coaching to physicians, the sample consists of physicians that signed up for the coaching programme or control participants. The choice of departments and hospitals that were invited for participation in this study was based on internal logistics. That is, because the coaching programme was only offered to physicians and residents from the pediatrics department, a relatively high number of participants in this sample are pediatricians. A comparison of the gender demographics of this sample with the broader population indicates that the sample of residents is representative of the hospital population. However, female specialists are over-represented in our sample. Limitations of generalisability will be discussed. Procedure All physicians were invited by email to complete an online survey. Participation was voluntary; participants provided informed consent for participation in the study. We took measures to safeguard the anonymity and confidentiality of all participants. Measures To capture the different components of the JD-R model, we included job demands, job resources, personal resources, burnout and work engagement in the survey, as well as demographics. Job demands Job demands were assessed with three scales: workload, job insecurity and work-family conflict. Workload was assessed with four items from the Quantitative Workload Inventory and two additional items (α=0.85). An example item measuring quantitative workload is: ‘How often does your job require you to work fast?’ The two additional items were ‘How often does your job require you to work overtime?’ and ‘How often do you experience emotional strain from your job?’. The items were scored on a five-point scale ranging from 1 (‘never’) to 5 (‘always’). Higher scores indicate higher frequency, that is, higher workload. Job insecurity , that is, ‘the perceived threat of job loss and the worries related to that threat’ was measured with an adapted version of the Job Insecurity Scale. The scale consisted of five items (α=0.83) including ‘Chances are, that in the future I won’t be able to find the job that I want’ or ‘I am feeling insecure about the future of my career’. The items were scored on a seven-point scale ranging from 1 (‘not at all applicable’) to 7 (‘very applicable’). Higher scores indicate stronger applicability, that is, higher job insecurity. Work-Family Conflict was measured with four items of the Work-Family Conflict Scale (α=0.87) measuring the extent to which ‘the general demands of, time devoted to, and strain created by the work interfere with performing family-related responsibilities’. An example item is: ‘The demands of my work interfere with my home and family life’. The items were scored on a seven-point scale ranging from 1 (‘not at all applicable’) to 7 (‘very applicable’). Higher scores indicate stronger agreement with the proposition, that is, higher work-family conflict. Job resources Job resources encompassed autonomy, supervisor support and colleague support. Autonomy was measured with nine items from the Work Design Questionnaire (α=0.93) assessing perceived autonomy with regard to work scheduling and methods and decision-making. Example items include ‘The job allows me to plan how I do my work’, ‘The job provides me with significant autonomy in making decisions’ and ‘The job allows me to make decisions about what methods I use to complete my work’, respectively. The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher autonomy. Supervisor support , that is, the experienced psychological and work support from the supervisor, was assessed with six items from Vinokur et al (α=0.95). Example items include ‘My supervisor provides me with encouragement’ or ‘My supervisor says things that raise my self-confidence’. For residents, supervisory support measured the support received from the training supervisor, whereas for specialists supervisor support measured the support received from the head of the department. The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher supervisor support. Colleague support, the experienced psychological and work support from colleagues, was assessed with the same six items as supervisor support (α=0.94), but the items referred to colleagues instead of the supervisor. Also here, higher scores indicate stronger agreement with the proposition, that is, higher colleague support. Personal resources We included three personal resources: psychological capital, self-compassion and psychological flexibility. Psychological capital was measured with 12 items reflecting hope, optimism, resilience and self-efficacy from the validated Dutch version of the Psychological Capital Questionnaire (α=0.88). The items include ‘Right now I see myself as being pretty successful at work’ (hope), ‘I always look on the bright side of things regarding my job’ (optimism), ‘When I have a setback at work, I have trouble recovering from it, moving on (R)’ (resilience) and ‘When encountering difficult problems in my work, I know how to solve them’ (self-efficacy). The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher psychological capital. Self-compassion , entailing ‘treating oneself with kindness, recognising one’s shared humanity and being mindful when considering negative aspects of oneself’, was measured with six items from the Self-Compassion Scale (α=0.72). Example items are: ‘When I am going through a very hard time, I give myself the caring and tenderness I need’ (self-kindness), ‘I try to see my failings as part of the human condition’ (common humanity) and ‘When something painful happens I try to take a balanced view of the situation’ (mindfulness). The items were scored on a five-point scale ranging from 1 (‘rarely’) to 5 (‘almost always’). Higher scores indicate higher frequency, that is, higher self-compassion. Psychological flexibility, that is, the ability to flexibly take appropriate action towards achieving goals and values, even in the presence of challenging or unwanted events was measured with seven items of the Work Acceptance and Action Questionnaire (α=0.81). Example items include ‘I am able to work effectively in spite of any personal worries that I have’ and ‘I can work effectively, even when I doubt myself.’ The items were scored on a five-point scale ranging from 1 (‘rarely’) to 5 (‘almost always’). Higher scores indicate higher frequency, that is, higher psychological flexibility. Outcomes The outcome variables included in this study were burnout symptoms and work engagement. Burnout was measured with the Dutch version of the Maslach Burnout Inventory—General Survey. The instrument consists of three subscales measuring exhaustion, cynicism and professional efficacy. Because exhaustion and cynicism constitute the essence of the burnout syndrome, we only measured these two components. Exhaustion was measured with five items (α=0.84). An example item is: ‘Working all day is really a strain for me.’ The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Cynicism was measured with four items (α=0.77). An example item is: ‘I noticed that I have got too much distance from my work.’ The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher exhaustion and cynicism, respectively. Work engagement , including vigour, dedication and absorption at work, was measured with nine items from the Utrecht Work Engagement Scale (α=0.90). Example items include: ‘When I get up in the morning, I feel like going to work’ (vigour), ‘I am enthusiastic about my job’ (dedication) and ‘When I am working I forget everything around me’ (absorption). The items were scored on a seven-point scale ranging from 1 (‘never’) to 7 (‘always’). Higher scores indicate higher frequency, that is, higher work engagement. Statistical analysis Factor structure To examine whether the items loaded on their respective scales, we performed separate confirmatory factor analyses (CFAs) for the scales representing job demands, job resources and personal resources, respectively. As each of these predictors consists of three scales, we compared a three-factor model to a one-factor model. We report the factor loadings and the commonly used model fit criteria, that is, the chi-square goodness-of-fit value, the chi-square divided by df (CMIN/DF), the comparative fit index (CFI), the root mean square error of approximation (RMSEA) and the standardised root mean squared residual (SRMR). Between-group variance Because participants (n=192) can be considered as nested within (four) academic hospitals and (three) specialisations, we first assessed between-group variance within our data. A multilevel mixed-method analysis estimating a random intercept model was conducted to calculate between level-2 variance (The final Hessian matrix was not positive definite as the intercept variance was zero). Control variables We explored the association between potential control variables (ie, age, gender, having children, job tenure, signed up for coaching) and the dependent variables by means of regression analyses for residents and specialists separately. Path analysis The relationships between the independent (job demands, job resources and personal resources) and dependent variables (exhaustion, cynicism and work engagement) were examined with path analysis using IBM SPSS AMOS 25 (IBM SPSS, Chicago, Illinois, USA). In a first step, we modelled a latent variable termed burnout based on the observed variables exhaustion and cynicism. Modelling these two outcome variables on one latent variable was justified both theoretically and statistically (correlation of r =0.58, p<0.01 between exhaustion and cynicism). A path model with independent variables and work engagement and burnout as dependent variables was tested using a covariance matrix as input and maximum likelihood estimation. This analysis adequately captures the nature of the associations between the independent and dependent variables and was therefore chosen over regular ordinary least squares regression analyses. Furthermore, this analysis allowed for a multigroup comparison, testing possible differences in model estimates between residents and specialists. Again, we report the commonly used model fit criteria as described earlier. Patient and public involvement This study investigated factors associated with work engagement and burnout in medical specialists and residents. No patients or public representatives were involved in the study.
From January to December 2017, we collected data from attending (specialists) and resident physicians at four academic hospitals and one general hospital in the Netherlands. The physicians were specialised or trained in pediatrics, internal medicine or neurology. Because this study is part of a larger programme offering individual coaching to physicians, the sample consists of physicians that signed up for the coaching programme or control participants. The choice of departments and hospitals that were invited for participation in this study was based on internal logistics. That is, because the coaching programme was only offered to physicians and residents from the pediatrics department, a relatively high number of participants in this sample are pediatricians. A comparison of the gender demographics of this sample with the broader population indicates that the sample of residents is representative of the hospital population. However, female specialists are over-represented in our sample. Limitations of generalisability will be discussed.
All physicians were invited by email to complete an online survey. Participation was voluntary; participants provided informed consent for participation in the study. We took measures to safeguard the anonymity and confidentiality of all participants.
To capture the different components of the JD-R model, we included job demands, job resources, personal resources, burnout and work engagement in the survey, as well as demographics. Job demands Job demands were assessed with three scales: workload, job insecurity and work-family conflict. Workload was assessed with four items from the Quantitative Workload Inventory and two additional items (α=0.85). An example item measuring quantitative workload is: ‘How often does your job require you to work fast?’ The two additional items were ‘How often does your job require you to work overtime?’ and ‘How often do you experience emotional strain from your job?’. The items were scored on a five-point scale ranging from 1 (‘never’) to 5 (‘always’). Higher scores indicate higher frequency, that is, higher workload. Job insecurity , that is, ‘the perceived threat of job loss and the worries related to that threat’ was measured with an adapted version of the Job Insecurity Scale. The scale consisted of five items (α=0.83) including ‘Chances are, that in the future I won’t be able to find the job that I want’ or ‘I am feeling insecure about the future of my career’. The items were scored on a seven-point scale ranging from 1 (‘not at all applicable’) to 7 (‘very applicable’). Higher scores indicate stronger applicability, that is, higher job insecurity. Work-Family Conflict was measured with four items of the Work-Family Conflict Scale (α=0.87) measuring the extent to which ‘the general demands of, time devoted to, and strain created by the work interfere with performing family-related responsibilities’. An example item is: ‘The demands of my work interfere with my home and family life’. The items were scored on a seven-point scale ranging from 1 (‘not at all applicable’) to 7 (‘very applicable’). Higher scores indicate stronger agreement with the proposition, that is, higher work-family conflict. Job resources Job resources encompassed autonomy, supervisor support and colleague support. Autonomy was measured with nine items from the Work Design Questionnaire (α=0.93) assessing perceived autonomy with regard to work scheduling and methods and decision-making. Example items include ‘The job allows me to plan how I do my work’, ‘The job provides me with significant autonomy in making decisions’ and ‘The job allows me to make decisions about what methods I use to complete my work’, respectively. The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher autonomy. Supervisor support , that is, the experienced psychological and work support from the supervisor, was assessed with six items from Vinokur et al (α=0.95). Example items include ‘My supervisor provides me with encouragement’ or ‘My supervisor says things that raise my self-confidence’. For residents, supervisory support measured the support received from the training supervisor, whereas for specialists supervisor support measured the support received from the head of the department. The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher supervisor support. Colleague support, the experienced psychological and work support from colleagues, was assessed with the same six items as supervisor support (α=0.94), but the items referred to colleagues instead of the supervisor. Also here, higher scores indicate stronger agreement with the proposition, that is, higher colleague support. Personal resources We included three personal resources: psychological capital, self-compassion and psychological flexibility. Psychological capital was measured with 12 items reflecting hope, optimism, resilience and self-efficacy from the validated Dutch version of the Psychological Capital Questionnaire (α=0.88). The items include ‘Right now I see myself as being pretty successful at work’ (hope), ‘I always look on the bright side of things regarding my job’ (optimism), ‘When I have a setback at work, I have trouble recovering from it, moving on (R)’ (resilience) and ‘When encountering difficult problems in my work, I know how to solve them’ (self-efficacy). The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher psychological capital. Self-compassion , entailing ‘treating oneself with kindness, recognising one’s shared humanity and being mindful when considering negative aspects of oneself’, was measured with six items from the Self-Compassion Scale (α=0.72). Example items are: ‘When I am going through a very hard time, I give myself the caring and tenderness I need’ (self-kindness), ‘I try to see my failings as part of the human condition’ (common humanity) and ‘When something painful happens I try to take a balanced view of the situation’ (mindfulness). The items were scored on a five-point scale ranging from 1 (‘rarely’) to 5 (‘almost always’). Higher scores indicate higher frequency, that is, higher self-compassion. Psychological flexibility, that is, the ability to flexibly take appropriate action towards achieving goals and values, even in the presence of challenging or unwanted events was measured with seven items of the Work Acceptance and Action Questionnaire (α=0.81). Example items include ‘I am able to work effectively in spite of any personal worries that I have’ and ‘I can work effectively, even when I doubt myself.’ The items were scored on a five-point scale ranging from 1 (‘rarely’) to 5 (‘almost always’). Higher scores indicate higher frequency, that is, higher psychological flexibility. Outcomes The outcome variables included in this study were burnout symptoms and work engagement. Burnout was measured with the Dutch version of the Maslach Burnout Inventory—General Survey. The instrument consists of three subscales measuring exhaustion, cynicism and professional efficacy. Because exhaustion and cynicism constitute the essence of the burnout syndrome, we only measured these two components. Exhaustion was measured with five items (α=0.84). An example item is: ‘Working all day is really a strain for me.’ The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Cynicism was measured with four items (α=0.77). An example item is: ‘I noticed that I have got too much distance from my work.’ The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher exhaustion and cynicism, respectively. Work engagement , including vigour, dedication and absorption at work, was measured with nine items from the Utrecht Work Engagement Scale (α=0.90). Example items include: ‘When I get up in the morning, I feel like going to work’ (vigour), ‘I am enthusiastic about my job’ (dedication) and ‘When I am working I forget everything around me’ (absorption). The items were scored on a seven-point scale ranging from 1 (‘never’) to 7 (‘always’). Higher scores indicate higher frequency, that is, higher work engagement.
Job demands were assessed with three scales: workload, job insecurity and work-family conflict. Workload was assessed with four items from the Quantitative Workload Inventory and two additional items (α=0.85). An example item measuring quantitative workload is: ‘How often does your job require you to work fast?’ The two additional items were ‘How often does your job require you to work overtime?’ and ‘How often do you experience emotional strain from your job?’. The items were scored on a five-point scale ranging from 1 (‘never’) to 5 (‘always’). Higher scores indicate higher frequency, that is, higher workload. Job insecurity , that is, ‘the perceived threat of job loss and the worries related to that threat’ was measured with an adapted version of the Job Insecurity Scale. The scale consisted of five items (α=0.83) including ‘Chances are, that in the future I won’t be able to find the job that I want’ or ‘I am feeling insecure about the future of my career’. The items were scored on a seven-point scale ranging from 1 (‘not at all applicable’) to 7 (‘very applicable’). Higher scores indicate stronger applicability, that is, higher job insecurity. Work-Family Conflict was measured with four items of the Work-Family Conflict Scale (α=0.87) measuring the extent to which ‘the general demands of, time devoted to, and strain created by the work interfere with performing family-related responsibilities’. An example item is: ‘The demands of my work interfere with my home and family life’. The items were scored on a seven-point scale ranging from 1 (‘not at all applicable’) to 7 (‘very applicable’). Higher scores indicate stronger agreement with the proposition, that is, higher work-family conflict.
Job resources encompassed autonomy, supervisor support and colleague support. Autonomy was measured with nine items from the Work Design Questionnaire (α=0.93) assessing perceived autonomy with regard to work scheduling and methods and decision-making. Example items include ‘The job allows me to plan how I do my work’, ‘The job provides me with significant autonomy in making decisions’ and ‘The job allows me to make decisions about what methods I use to complete my work’, respectively. The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher autonomy. Supervisor support , that is, the experienced psychological and work support from the supervisor, was assessed with six items from Vinokur et al (α=0.95). Example items include ‘My supervisor provides me with encouragement’ or ‘My supervisor says things that raise my self-confidence’. For residents, supervisory support measured the support received from the training supervisor, whereas for specialists supervisor support measured the support received from the head of the department. The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher supervisor support. Colleague support, the experienced psychological and work support from colleagues, was assessed with the same six items as supervisor support (α=0.94), but the items referred to colleagues instead of the supervisor. Also here, higher scores indicate stronger agreement with the proposition, that is, higher colleague support.
We included three personal resources: psychological capital, self-compassion and psychological flexibility. Psychological capital was measured with 12 items reflecting hope, optimism, resilience and self-efficacy from the validated Dutch version of the Psychological Capital Questionnaire (α=0.88). The items include ‘Right now I see myself as being pretty successful at work’ (hope), ‘I always look on the bright side of things regarding my job’ (optimism), ‘When I have a setback at work, I have trouble recovering from it, moving on (R)’ (resilience) and ‘When encountering difficult problems in my work, I know how to solve them’ (self-efficacy). The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher psychological capital. Self-compassion , entailing ‘treating oneself with kindness, recognising one’s shared humanity and being mindful when considering negative aspects of oneself’, was measured with six items from the Self-Compassion Scale (α=0.72). Example items are: ‘When I am going through a very hard time, I give myself the caring and tenderness I need’ (self-kindness), ‘I try to see my failings as part of the human condition’ (common humanity) and ‘When something painful happens I try to take a balanced view of the situation’ (mindfulness). The items were scored on a five-point scale ranging from 1 (‘rarely’) to 5 (‘almost always’). Higher scores indicate higher frequency, that is, higher self-compassion. Psychological flexibility, that is, the ability to flexibly take appropriate action towards achieving goals and values, even in the presence of challenging or unwanted events was measured with seven items of the Work Acceptance and Action Questionnaire (α=0.81). Example items include ‘I am able to work effectively in spite of any personal worries that I have’ and ‘I can work effectively, even when I doubt myself.’ The items were scored on a five-point scale ranging from 1 (‘rarely’) to 5 (‘almost always’). Higher scores indicate higher frequency, that is, higher psychological flexibility.
The outcome variables included in this study were burnout symptoms and work engagement. Burnout was measured with the Dutch version of the Maslach Burnout Inventory—General Survey. The instrument consists of three subscales measuring exhaustion, cynicism and professional efficacy. Because exhaustion and cynicism constitute the essence of the burnout syndrome, we only measured these two components. Exhaustion was measured with five items (α=0.84). An example item is: ‘Working all day is really a strain for me.’ The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Cynicism was measured with four items (α=0.77). An example item is: ‘I noticed that I have got too much distance from my work.’ The items were scored on a seven-point scale ranging from 1 (‘totally disagree’) to 7 (‘totally agree’). Higher scores indicate stronger agreement with the proposition, that is, higher exhaustion and cynicism, respectively. Work engagement , including vigour, dedication and absorption at work, was measured with nine items from the Utrecht Work Engagement Scale (α=0.90). Example items include: ‘When I get up in the morning, I feel like going to work’ (vigour), ‘I am enthusiastic about my job’ (dedication) and ‘When I am working I forget everything around me’ (absorption). The items were scored on a seven-point scale ranging from 1 (‘never’) to 7 (‘always’). Higher scores indicate higher frequency, that is, higher work engagement.
Factor structure To examine whether the items loaded on their respective scales, we performed separate confirmatory factor analyses (CFAs) for the scales representing job demands, job resources and personal resources, respectively. As each of these predictors consists of three scales, we compared a three-factor model to a one-factor model. We report the factor loadings and the commonly used model fit criteria, that is, the chi-square goodness-of-fit value, the chi-square divided by df (CMIN/DF), the comparative fit index (CFI), the root mean square error of approximation (RMSEA) and the standardised root mean squared residual (SRMR). Between-group variance Because participants (n=192) can be considered as nested within (four) academic hospitals and (three) specialisations, we first assessed between-group variance within our data. A multilevel mixed-method analysis estimating a random intercept model was conducted to calculate between level-2 variance (The final Hessian matrix was not positive definite as the intercept variance was zero). Control variables We explored the association between potential control variables (ie, age, gender, having children, job tenure, signed up for coaching) and the dependent variables by means of regression analyses for residents and specialists separately. Path analysis The relationships between the independent (job demands, job resources and personal resources) and dependent variables (exhaustion, cynicism and work engagement) were examined with path analysis using IBM SPSS AMOS 25 (IBM SPSS, Chicago, Illinois, USA). In a first step, we modelled a latent variable termed burnout based on the observed variables exhaustion and cynicism. Modelling these two outcome variables on one latent variable was justified both theoretically and statistically (correlation of r =0.58, p<0.01 between exhaustion and cynicism). A path model with independent variables and work engagement and burnout as dependent variables was tested using a covariance matrix as input and maximum likelihood estimation. This analysis adequately captures the nature of the associations between the independent and dependent variables and was therefore chosen over regular ordinary least squares regression analyses. Furthermore, this analysis allowed for a multigroup comparison, testing possible differences in model estimates between residents and specialists. Again, we report the commonly used model fit criteria as described earlier.
To examine whether the items loaded on their respective scales, we performed separate confirmatory factor analyses (CFAs) for the scales representing job demands, job resources and personal resources, respectively. As each of these predictors consists of three scales, we compared a three-factor model to a one-factor model. We report the factor loadings and the commonly used model fit criteria, that is, the chi-square goodness-of-fit value, the chi-square divided by df (CMIN/DF), the comparative fit index (CFI), the root mean square error of approximation (RMSEA) and the standardised root mean squared residual (SRMR).
Because participants (n=192) can be considered as nested within (four) academic hospitals and (three) specialisations, we first assessed between-group variance within our data. A multilevel mixed-method analysis estimating a random intercept model was conducted to calculate between level-2 variance (The final Hessian matrix was not positive definite as the intercept variance was zero).
We explored the association between potential control variables (ie, age, gender, having children, job tenure, signed up for coaching) and the dependent variables by means of regression analyses for residents and specialists separately.
The relationships between the independent (job demands, job resources and personal resources) and dependent variables (exhaustion, cynicism and work engagement) were examined with path analysis using IBM SPSS AMOS 25 (IBM SPSS, Chicago, Illinois, USA). In a first step, we modelled a latent variable termed burnout based on the observed variables exhaustion and cynicism. Modelling these two outcome variables on one latent variable was justified both theoretically and statistically (correlation of r =0.58, p<0.01 between exhaustion and cynicism). A path model with independent variables and work engagement and burnout as dependent variables was tested using a covariance matrix as input and maximum likelihood estimation. This analysis adequately captures the nature of the associations between the independent and dependent variables and was therefore chosen over regular ordinary least squares regression analyses. Furthermore, this analysis allowed for a multigroup comparison, testing possible differences in model estimates between residents and specialists. Again, we report the commonly used model fit criteria as described earlier.
This study investigated factors associated with work engagement and burnout in medical specialists and residents. No patients or public representatives were involved in the study.
In total, we invited a number of 247 physicians to take part in this survey of whom 75 physicians had signed up for a personal coaching programme that would start in a few months. A total number of n=193 physicians were included in this study after application of inclusion criteria (inclusion criteria: minimal response time >15 min, survey was filled out no later than 1 week after the first coaching session; survey progress ≥80%) (response rate=78%). The study population included 151 women (78.2%) and 42 men (21.8%). The mean age was 36.5 years ( SD =8.5). One hundred and twenty-four residents (64.2%) and 69 medical specialists (35.8%) participated. Participants were working in the field of pediatrics (n=142; 73.6%), neurology (n=14; 7.3%) and internal medicine (n=37; 19.2%). See for a description of participants’ characteristics. Internal consistency (Cronbach’s alpha) was acceptable for all scales (see ). Factor structure All items loaded on their respective scales. Factor loadings were on average 0.73, 0.81 and 0.60 for job demands, job resources and personal resources, with three items loading below 0.40 and a minimal loading of 0.28. These items were included because the scales were validated test instruments with overall high internal consistencies. The modification indices provided by the CFAs indicated that some items shared error variance. In order to improve the model fit, we allowed covariation of error variance between these items. Covariation was only allowed for items originating from the same scale. All three models provided adequate fit to the data with χ 2 (86)=153.74, p<0.001, χ 2 /df=1.79, CFI=0.95, RMSEA=0.06, SRMR=0.06; χ 2 (180)=312.75, p<0.001, χ 2 /df=1.74, CFI=0.97, RMSEA=0.06, SRMR=0.06 and χ 2 (262)=435.96, p<0.001, χ 2 /df=1.66, CFI=0.90, RMSEA=0.06, SRMR=0.07 for the three-factor models representing job demands, job resources and personal resources, respectively. Our results showed that the hypothesised three-factor model of these predictors provided a better fit to the data than a common factor model (eg, fit indices of the common factor model of job demands: χ 2 (89)=864.96, p<0.001, χ 2 /df=9.72, CFI=0.46, RMSEA=0.21, SRMR=0.19). The differences in the chi-square goodness-of-fit value between the three-factor and the common factor models were significant, all p ’ s<0.001. These results allow us to conclude that the factor structure assumed in our path model is appropriate. Between-group variance A multivariate generalised linear model analysis confirmed that hospitals and specialisations did not significantly differ on exhaustion, cynicism and work engagement. Therefore, it was not necessary to account for group-level effects when estimating the relationships between the independent and dependent variables. Control variables The results showed that only the control variables job tenure; b =0.23, p=0.02 (related to exhaustion for residents), b =0.24, p=0.02 (related to cynicism for residents) and signed up for coaching (response options were: 1=yes, 2=no); b =−0.31, p=0.01 (related to exhaustion for specialists) were related to exhaustion, cynicism or engagement. Therefore, and to save power, we only included job tenure and signed up for coaching as control variables in the further analyses. Descriptives and group differences describes means, SD and differences in study variables for residents and specialists, respectively. Independent sample t-tests were performed to investigate mean-level differences in study variables comparing residents and specialists. Compared with specialists, residents reported significantly lower workload ( M =3.29, SD=0.68 vs M =3.52, SD=0.83, p <0.05 (significance values were p=0.039 when equal variances were assumed and p=0.052 when equal variances were not assumed)), lower autonomy ( M =4.10, SD=0.99 vs M =5.19, SD=1.02, p<0.01) and lower work engagement ( M =4.93, SD=0.77 vs M =5.21, SD=0.88, p<0.05). However, residents reported significantly higher job insecurity than specialists ( M =4.26, SD=1.17 vs M =3.03, SD=1.27, p<0.01). Path analyses Preliminary analyses As suggested by Jöreskog and Sörbom, we first specified an initial model based on our research question, and then adjusted the model according to the modification indices it produced, allowing covariation between all predictor variables, as well as covariation between job tenure and autonomy. Because both indicators of burnout highly correlated with engagement, we allowed covariation of error variance between exhaustion and cynicism with engagement. Testing the initial path model for specialists and residents separately revealed that the control variable signed up for coaching was not related to any of the two outcomes in both subsamples. We, therefore, removed this variable from the analysis and continued the analysis with only job tenure as control variable. Model fit The path analysis showed a satisfactory fit to the data, χ 2 (51)=109.25, p<0.001, χ 2 /df=2.14, CFI=0.96, RMSEA=0.06, SRMR=0.06. In order to improve the model fit, we removed the paths that were non-significant for both residents and specialists. We removed the paths from job insecurity and supervisor support to burnout. Further, we removed the paths from workload, job insecurity, work-family conflict, autonomy, supervisor support and job tenure to work engagement as they were not significant, partly despite significant zero-order correlations between these variables (see ). The model resulted in an improved fit of χ 2 (75)=132.33, p<0.001, χ 2 /df=1.76, CFI=0.96, RMSEA=0.05, SRMR=0.06. The tested model is presented in . The model explained 53.9% of the variance in burnout and 27.9% of variance in work engagement. Relationships with burnout The standardised path coefficients with burnout as outcome are presented in . Job demands Separate tests for residents and specialists suggested that there were no differences between both groups: workload was positively related to burnout for residents ( b =0.20, p=0.011) and specialists ( b =0.22, p=0.009). A multigroup comparison test confirmed that these relationships did not significantly differ, p>0.05. Furthermore, separate tests for both groups suggested that work-family conflict as a job demand differed between residents and specialists: it was positively related to burnout for residents ( b =0.33, p<0.001) but not for specialists (p>0.05). However, these relationships did not significantly differ in a multigroup comparison test, p>0.05. Job resources Separate tests for both groups suggested that there were differences between residents and specialists regarding autonomy: autonomy was positively related to burnout for residents ( b =0.19, p=0.016) but not for specialists (p>0.05). However, these differences did not significantly differ in a multigroup comparison test, p>0.05. Furthermore, separate tests for both groups suggested that colleague support differed between residents and specialists: it was not related to burnout for residents (p>0.05) but was negatively related to burnout for specialists ( b =−0.41, p<0.001). However, these relationships did not significantly differ in a multigroup comparison test, p=0.088. Personal resources Separate tests for both groups suggested that there were differences between residents and specialists regarding the personal resource psychological capital: psychological capital was not related to burnout for residents (p>0.05) but was negatively related to burnout for specialists ( b =−0.58, p<0.001). A multigroup comparison test confirmed that these relationships significantly differed, p=0.003. Furthermore, separate tests for both groups suggested that self-compassion differed between residents and specialists: self-compassion was negatively related to burnout for residents ( b =−0.22, p=0.017) but not related to burnout for specialists (p>0.05). However, these relationships did not significantly differ in a multigroup comparison test, p=0.072. Also, separate tests suggested that there were differences between residents and specialists regarding the personal resource psychological flexibility: it was related to burnout for residents ( b =−0.31, p<0.001) but not related to burnout for specialists (p>0.05). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.003. Relationships with work engagement The standardised path coefficients with work engagement as outcome are presented in . Job resources Separate tests suggested that there were differences regarding colleague support between residents and specialists: colleague support was not related to work engagement for residents (p>0.05) but was positively related to work engagement for specialists ( b =0.49, p<0.001). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.001. Personal resources Separate tests for both groups suggested that there were no differences between residents and specialists regarding psychological capital: psychological capital was positively related to work engagement for both residents ( b =0.37, p<0.001) and specialists ( b =0.55, p<0.001). A multigroup comparison test confirmed that these relationships did not significantly differ, p>0.05. Furthermore, separate tests for both groups suggested that there were differences between residents and specialists regarding self-compassion: self-compassion was not related to work engagement for residents (p>0.05) but was negatively related to work engagement for specialists ( b =−0.33, p=0.004). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.003. Also, separate tests for both groups suggested that there were differences between residents and specialists regarding psychological flexibility: psychological flexibility was positively related to work engagement for residents ( b =0.17, p=0.035) but not for specialists (p>0.05). However, a multigroup comparison test showed that these relationships did not significantly differ, p=0.778.
All items loaded on their respective scales. Factor loadings were on average 0.73, 0.81 and 0.60 for job demands, job resources and personal resources, with three items loading below 0.40 and a minimal loading of 0.28. These items were included because the scales were validated test instruments with overall high internal consistencies. The modification indices provided by the CFAs indicated that some items shared error variance. In order to improve the model fit, we allowed covariation of error variance between these items. Covariation was only allowed for items originating from the same scale. All three models provided adequate fit to the data with χ 2 (86)=153.74, p<0.001, χ 2 /df=1.79, CFI=0.95, RMSEA=0.06, SRMR=0.06; χ 2 (180)=312.75, p<0.001, χ 2 /df=1.74, CFI=0.97, RMSEA=0.06, SRMR=0.06 and χ 2 (262)=435.96, p<0.001, χ 2 /df=1.66, CFI=0.90, RMSEA=0.06, SRMR=0.07 for the three-factor models representing job demands, job resources and personal resources, respectively. Our results showed that the hypothesised three-factor model of these predictors provided a better fit to the data than a common factor model (eg, fit indices of the common factor model of job demands: χ 2 (89)=864.96, p<0.001, χ 2 /df=9.72, CFI=0.46, RMSEA=0.21, SRMR=0.19). The differences in the chi-square goodness-of-fit value between the three-factor and the common factor models were significant, all p ’ s<0.001. These results allow us to conclude that the factor structure assumed in our path model is appropriate.
A multivariate generalised linear model analysis confirmed that hospitals and specialisations did not significantly differ on exhaustion, cynicism and work engagement. Therefore, it was not necessary to account for group-level effects when estimating the relationships between the independent and dependent variables.
The results showed that only the control variables job tenure; b =0.23, p=0.02 (related to exhaustion for residents), b =0.24, p=0.02 (related to cynicism for residents) and signed up for coaching (response options were: 1=yes, 2=no); b =−0.31, p=0.01 (related to exhaustion for specialists) were related to exhaustion, cynicism or engagement. Therefore, and to save power, we only included job tenure and signed up for coaching as control variables in the further analyses.
describes means, SD and differences in study variables for residents and specialists, respectively. Independent sample t-tests were performed to investigate mean-level differences in study variables comparing residents and specialists. Compared with specialists, residents reported significantly lower workload ( M =3.29, SD=0.68 vs M =3.52, SD=0.83, p <0.05 (significance values were p=0.039 when equal variances were assumed and p=0.052 when equal variances were not assumed)), lower autonomy ( M =4.10, SD=0.99 vs M =5.19, SD=1.02, p<0.01) and lower work engagement ( M =4.93, SD=0.77 vs M =5.21, SD=0.88, p<0.05). However, residents reported significantly higher job insecurity than specialists ( M =4.26, SD=1.17 vs M =3.03, SD=1.27, p<0.01).
Preliminary analyses As suggested by Jöreskog and Sörbom, we first specified an initial model based on our research question, and then adjusted the model according to the modification indices it produced, allowing covariation between all predictor variables, as well as covariation between job tenure and autonomy. Because both indicators of burnout highly correlated with engagement, we allowed covariation of error variance between exhaustion and cynicism with engagement. Testing the initial path model for specialists and residents separately revealed that the control variable signed up for coaching was not related to any of the two outcomes in both subsamples. We, therefore, removed this variable from the analysis and continued the analysis with only job tenure as control variable. Model fit The path analysis showed a satisfactory fit to the data, χ 2 (51)=109.25, p<0.001, χ 2 /df=2.14, CFI=0.96, RMSEA=0.06, SRMR=0.06. In order to improve the model fit, we removed the paths that were non-significant for both residents and specialists. We removed the paths from job insecurity and supervisor support to burnout. Further, we removed the paths from workload, job insecurity, work-family conflict, autonomy, supervisor support and job tenure to work engagement as they were not significant, partly despite significant zero-order correlations between these variables (see ). The model resulted in an improved fit of χ 2 (75)=132.33, p<0.001, χ 2 /df=1.76, CFI=0.96, RMSEA=0.05, SRMR=0.06. The tested model is presented in . The model explained 53.9% of the variance in burnout and 27.9% of variance in work engagement. Relationships with burnout The standardised path coefficients with burnout as outcome are presented in . Job demands Separate tests for residents and specialists suggested that there were no differences between both groups: workload was positively related to burnout for residents ( b =0.20, p=0.011) and specialists ( b =0.22, p=0.009). A multigroup comparison test confirmed that these relationships did not significantly differ, p>0.05. Furthermore, separate tests for both groups suggested that work-family conflict as a job demand differed between residents and specialists: it was positively related to burnout for residents ( b =0.33, p<0.001) but not for specialists (p>0.05). However, these relationships did not significantly differ in a multigroup comparison test, p>0.05. Job resources Separate tests for both groups suggested that there were differences between residents and specialists regarding autonomy: autonomy was positively related to burnout for residents ( b =0.19, p=0.016) but not for specialists (p>0.05). However, these differences did not significantly differ in a multigroup comparison test, p>0.05. Furthermore, separate tests for both groups suggested that colleague support differed between residents and specialists: it was not related to burnout for residents (p>0.05) but was negatively related to burnout for specialists ( b =−0.41, p<0.001). However, these relationships did not significantly differ in a multigroup comparison test, p=0.088. Personal resources Separate tests for both groups suggested that there were differences between residents and specialists regarding the personal resource psychological capital: psychological capital was not related to burnout for residents (p>0.05) but was negatively related to burnout for specialists ( b =−0.58, p<0.001). A multigroup comparison test confirmed that these relationships significantly differed, p=0.003. Furthermore, separate tests for both groups suggested that self-compassion differed between residents and specialists: self-compassion was negatively related to burnout for residents ( b =−0.22, p=0.017) but not related to burnout for specialists (p>0.05). However, these relationships did not significantly differ in a multigroup comparison test, p=0.072. Also, separate tests suggested that there were differences between residents and specialists regarding the personal resource psychological flexibility: it was related to burnout for residents ( b =−0.31, p<0.001) but not related to burnout for specialists (p>0.05). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.003. Relationships with work engagement The standardised path coefficients with work engagement as outcome are presented in . Job resources Separate tests suggested that there were differences regarding colleague support between residents and specialists: colleague support was not related to work engagement for residents (p>0.05) but was positively related to work engagement for specialists ( b =0.49, p<0.001). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.001. Personal resources Separate tests for both groups suggested that there were no differences between residents and specialists regarding psychological capital: psychological capital was positively related to work engagement for both residents ( b =0.37, p<0.001) and specialists ( b =0.55, p<0.001). A multigroup comparison test confirmed that these relationships did not significantly differ, p>0.05. Furthermore, separate tests for both groups suggested that there were differences between residents and specialists regarding self-compassion: self-compassion was not related to work engagement for residents (p>0.05) but was negatively related to work engagement for specialists ( b =−0.33, p=0.004). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.003. Also, separate tests for both groups suggested that there were differences between residents and specialists regarding psychological flexibility: psychological flexibility was positively related to work engagement for residents ( b =0.17, p=0.035) but not for specialists (p>0.05). However, a multigroup comparison test showed that these relationships did not significantly differ, p=0.778.
As suggested by Jöreskog and Sörbom, we first specified an initial model based on our research question, and then adjusted the model according to the modification indices it produced, allowing covariation between all predictor variables, as well as covariation between job tenure and autonomy. Because both indicators of burnout highly correlated with engagement, we allowed covariation of error variance between exhaustion and cynicism with engagement. Testing the initial path model for specialists and residents separately revealed that the control variable signed up for coaching was not related to any of the two outcomes in both subsamples. We, therefore, removed this variable from the analysis and continued the analysis with only job tenure as control variable.
The path analysis showed a satisfactory fit to the data, χ 2 (51)=109.25, p<0.001, χ 2 /df=2.14, CFI=0.96, RMSEA=0.06, SRMR=0.06. In order to improve the model fit, we removed the paths that were non-significant for both residents and specialists. We removed the paths from job insecurity and supervisor support to burnout. Further, we removed the paths from workload, job insecurity, work-family conflict, autonomy, supervisor support and job tenure to work engagement as they were not significant, partly despite significant zero-order correlations between these variables (see ). The model resulted in an improved fit of χ 2 (75)=132.33, p<0.001, χ 2 /df=1.76, CFI=0.96, RMSEA=0.05, SRMR=0.06. The tested model is presented in . The model explained 53.9% of the variance in burnout and 27.9% of variance in work engagement.
The standardised path coefficients with burnout as outcome are presented in . Job demands Separate tests for residents and specialists suggested that there were no differences between both groups: workload was positively related to burnout for residents ( b =0.20, p=0.011) and specialists ( b =0.22, p=0.009). A multigroup comparison test confirmed that these relationships did not significantly differ, p>0.05. Furthermore, separate tests for both groups suggested that work-family conflict as a job demand differed between residents and specialists: it was positively related to burnout for residents ( b =0.33, p<0.001) but not for specialists (p>0.05). However, these relationships did not significantly differ in a multigroup comparison test, p>0.05. Job resources Separate tests for both groups suggested that there were differences between residents and specialists regarding autonomy: autonomy was positively related to burnout for residents ( b =0.19, p=0.016) but not for specialists (p>0.05). However, these differences did not significantly differ in a multigroup comparison test, p>0.05. Furthermore, separate tests for both groups suggested that colleague support differed between residents and specialists: it was not related to burnout for residents (p>0.05) but was negatively related to burnout for specialists ( b =−0.41, p<0.001). However, these relationships did not significantly differ in a multigroup comparison test, p=0.088. Personal resources Separate tests for both groups suggested that there were differences between residents and specialists regarding the personal resource psychological capital: psychological capital was not related to burnout for residents (p>0.05) but was negatively related to burnout for specialists ( b =−0.58, p<0.001). A multigroup comparison test confirmed that these relationships significantly differed, p=0.003. Furthermore, separate tests for both groups suggested that self-compassion differed between residents and specialists: self-compassion was negatively related to burnout for residents ( b =−0.22, p=0.017) but not related to burnout for specialists (p>0.05). However, these relationships did not significantly differ in a multigroup comparison test, p=0.072. Also, separate tests suggested that there were differences between residents and specialists regarding the personal resource psychological flexibility: it was related to burnout for residents ( b =−0.31, p<0.001) but not related to burnout for specialists (p>0.05). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.003.
Separate tests for residents and specialists suggested that there were no differences between both groups: workload was positively related to burnout for residents ( b =0.20, p=0.011) and specialists ( b =0.22, p=0.009). A multigroup comparison test confirmed that these relationships did not significantly differ, p>0.05. Furthermore, separate tests for both groups suggested that work-family conflict as a job demand differed between residents and specialists: it was positively related to burnout for residents ( b =0.33, p<0.001) but not for specialists (p>0.05). However, these relationships did not significantly differ in a multigroup comparison test, p>0.05.
Separate tests for both groups suggested that there were differences between residents and specialists regarding autonomy: autonomy was positively related to burnout for residents ( b =0.19, p=0.016) but not for specialists (p>0.05). However, these differences did not significantly differ in a multigroup comparison test, p>0.05. Furthermore, separate tests for both groups suggested that colleague support differed between residents and specialists: it was not related to burnout for residents (p>0.05) but was negatively related to burnout for specialists ( b =−0.41, p<0.001). However, these relationships did not significantly differ in a multigroup comparison test, p=0.088.
Separate tests for both groups suggested that there were differences between residents and specialists regarding the personal resource psychological capital: psychological capital was not related to burnout for residents (p>0.05) but was negatively related to burnout for specialists ( b =−0.58, p<0.001). A multigroup comparison test confirmed that these relationships significantly differed, p=0.003. Furthermore, separate tests for both groups suggested that self-compassion differed between residents and specialists: self-compassion was negatively related to burnout for residents ( b =−0.22, p=0.017) but not related to burnout for specialists (p>0.05). However, these relationships did not significantly differ in a multigroup comparison test, p=0.072. Also, separate tests suggested that there were differences between residents and specialists regarding the personal resource psychological flexibility: it was related to burnout for residents ( b =−0.31, p<0.001) but not related to burnout for specialists (p>0.05). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.003.
The standardised path coefficients with work engagement as outcome are presented in . Job resources Separate tests suggested that there were differences regarding colleague support between residents and specialists: colleague support was not related to work engagement for residents (p>0.05) but was positively related to work engagement for specialists ( b =0.49, p<0.001). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.001. Personal resources Separate tests for both groups suggested that there were no differences between residents and specialists regarding psychological capital: psychological capital was positively related to work engagement for both residents ( b =0.37, p<0.001) and specialists ( b =0.55, p<0.001). A multigroup comparison test confirmed that these relationships did not significantly differ, p>0.05. Furthermore, separate tests for both groups suggested that there were differences between residents and specialists regarding self-compassion: self-compassion was not related to work engagement for residents (p>0.05) but was negatively related to work engagement for specialists ( b =−0.33, p=0.004). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.003. Also, separate tests for both groups suggested that there were differences between residents and specialists regarding psychological flexibility: psychological flexibility was positively related to work engagement for residents ( b =0.17, p=0.035) but not for specialists (p>0.05). However, a multigroup comparison test showed that these relationships did not significantly differ, p=0.778.
Separate tests suggested that there were differences regarding colleague support between residents and specialists: colleague support was not related to work engagement for residents (p>0.05) but was positively related to work engagement for specialists ( b =0.49, p<0.001). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.001.
Separate tests for both groups suggested that there were no differences between residents and specialists regarding psychological capital: psychological capital was positively related to work engagement for both residents ( b =0.37, p<0.001) and specialists ( b =0.55, p<0.001). A multigroup comparison test confirmed that these relationships did not significantly differ, p>0.05. Furthermore, separate tests for both groups suggested that there were differences between residents and specialists regarding self-compassion: self-compassion was not related to work engagement for residents (p>0.05) but was negatively related to work engagement for specialists ( b =−0.33, p=0.004). A multigroup comparison test confirmed that these relationships did significantly differ, p=0.003. Also, separate tests for both groups suggested that there were differences between residents and specialists regarding psychological flexibility: psychological flexibility was positively related to work engagement for residents ( b =0.17, p=0.035) but not for specialists (p>0.05). However, a multigroup comparison test showed that these relationships did not significantly differ, p=0.778.
Main findings The goal of this study was to gain insight on the prevailing demands and resources that contribute to burnout and work engagement in medical residents and specialists. This study revealed that residents and specialists face different demands in their work that cannot be measured by the same yardstick but instead require tailored solutions. Confirming prior studies on the stressful demands during residency, our data showed that residents compared with specialists experienced less autonomy and felt more uncertain about the future of their job. Furthermore, symptoms of exhaustion and cynicism among residents increased with tenure, which may at least partly relate to growing feelings of job insecurity (see ). Contrary to what has been reported in previous studies, residents did not report significantly higher exhaustion and cynicism than specialists but, on average, felt less engaged with their work. We suggest that specialists and residents resort to different resources to cope with their job demands. Although both groups have the same level of resources at their disposal, only certain resources contribute to the well-being of specialists and residents, respectively. While specialists benefit from psychological capital and colleague support, residents benefit especially from psychological flexibility and self-compassion. It is likely that residents and specialists—as a function of their role and the career phase they are in—use those resources that bring the greatest benefit when facing job demands at work. This will be discussed subsequently. In addition, psychological capital was found to play a role for the work engagement of both specialists and residents, which corroborates earlier findings among other professional groups. Physicians are exposed to high job demands, both during attendance and residency, which could harm their well-being. However, our study suggests that job demands other than workload (eg, job insecurity, work-family conflict) and a lack of resources (eg, self-compassion, psychological capital and psychological flexibility) play a prominent role in the onset of burnout. The fact that the residents in this study reported a relatively lower workload than specialists, yet reported similar symptoms of burnout, underlines this notion. Generally, our findings suggest that for preventing burnout it is important to focus on those demands and resources that are most relevant for specific groups of physicians (eg, specialists or residents). Specialists may particularly benefit from interventions that raise their psychological capital and—at the team level—foster team cohesion and support, whereas residents may benefit relatively more from interventions that increase their self-compassion and flexibility. Resources that buffer burnout among specialists and residents Personal resources Consistent with prior research, psychological capital played an eminent role for the well-being of specialists. Psychological capital may reduce the risk of burnout in two ways. First, it can counteract the distress associated with a demanding workplace by regulating negative emotions. Second, individuals with high psychological capital tend to perceive job demands as challenges rather than hindrances. That is, they associate job demands with personal gain or growth, evoking positive emotions, instead of fear and threat, evoking negative emotions. Given the buffering capacity of psychological capital, it is surprising that we did not find the same result among residents. Instead, we found that flexibility and self-compassion rather than psychological capital contributed to the well-being of residents. The importance of flexibility and self-compassion among residents may be due to their specific career phase, which is characterised by insecurity, constant feedback and criticism. That is, residency is an extremely challenging period, in which residents have to deal with their newly gained responsibilities (ie, managing uncertainty, breaking bad news) while also processing new information and continuously adapting to new organisational structures and teams. Residents have to shift regularly between their roles as trainee and doctor, experience high challenges at work and are confronted with their relative lack of knowledge and skills when entering residency. More so, residents are taught from medical school on to be critical towards themselves, a necessity that is demanded in a high-stake work environment where carelessness can have radical consequences. Consequently, medical professionals likely adopt a rather self-critical attitude. One way to deal with these stressful work events is to accept one’s inexperience, forgive one’s deficiencies (ie, self-compassion) and remain effective despite self-doubt and worries (ie, psychological flexibility). More specifically, residents need to internalise that despite the current healthcare culture, not knowing, insecurities and mistakes are part of the journey and not a sign of weakness or failure. In addition, psychological flexibility may allow residents to shift between tasks and professional roles, as it facilitates adapting to fluctuating situational demands, shifting perspective and reconfiguring mental resources. Thus, being kind towards oneself and viewing one’s own shortcomings as human can help to safeguard residents against the stressors uniquely present in residency. Colleague support In addition to psychological capital, colleague support also seems to promote the well-being of specialists. Numerous studies have indeed shown that social support is associated with both psychological and physical health outcomes as it ameliorates the impact of stress and strain on health. First, social support may involve emotional support, the feeling that one is loved and cared for. Second, it may involve the provision and sharing of information. Specialists work in relatively permanent teams with interdependent work relationships. Knowing their colleagues and their expertise well, they can ask for and receive emotional but also informational support. Colleagues can provide intimacy or reassurance during emotional and stressful events and they can assist in times of uncertainty and difficult medical inquiries that require another expert opinion. Although our data does not allow any insights in the quality of support received from colleagues, it is possible that the quality of support is different for residents and specialists. Because of the nature of residency (eg, competition and regular rotations), it is likely that colleague relationships are relatively less permanent and fruitful for residents. Although valuing their opinion, residents might not be convinced that they can ultimately lean on a fellow resident’s opinion in solving medical problems. This could explain why residents benefit relatively less from colleague support than specialists. Resources that foster work engagement among specialists and residents Personal resources Our finding that psychological capital is a personal resource that is vital for the work engagement of both residents and specialists corroborates with prior studies among other professional groups. Unexpectedly, self-compassion was negatively rather than positively associated with the work engagement of specialists, while we found no such effect for residents. It is possible that high levels of self-compassion represent a self-protective bias, which serves to deny responsibility for failure. That is, high self-compassion may lean towards attributing failure to external factors (eg, situational constrains, lack of help from others) allowing specialists to maintain positive perceptions of their capabilities. Over a longer period of time, this way of thinking about their own shortcomings may hamper specialists’ personal development and work efforts, which may ultimately cause a reduction in work engagement. It is therefore worth exploring whether the benefits of self-compassion depend on time or whether there is an optimal level—or perhaps a tipping point—at which self-compassion contributes to one’s well-being. Colleague support Colleague support not only buffered the occurrence of burnout but also fostered work engagement among specialists rather than residents. As argued above, specialists as opposed to residents work in more permanent teams. It has been consistently found that the social support in these teams facilitates the work engagement of team members. Study strengths and limitations The participation of both residents and specialists from different specialties and the high response rate (78%) allowed for a realistic display of the demands and resources that physicians encounter during different stages of their career. Our research shows how different demands and resources relate to burnout and work engagement among specific groups of physicians and, as such, advances our understanding of how to intervene when well-being or work engagement are at risk. This is an important first step in the prevention of burnout and the conservation of work engagement among healthcare professionals. Yet, our results also indicate that burnout and work engagement are highly interweaved, just as in numerous prior studies. Consequently, it is important to consider both burnout and work engagement when addressing job functioning as a whole. Finally, our study has some limitations. First, although theory and research point to causal relationships between demands and burnout and resources and work engagement, our design does not allow to draw causal conclusions. It is possible that the proposed relationships in the JD-R model are reversed. For instance, feelings of exhaustion and cynicism may change the way employees perceive their work demands, intensifying the feeling that demands are piling up. Future research could use multiwave designs that can provide insight into the development of study variables over time and the causal dynamics in this process. Second, all data have been gathered using self-report questionnaires. This might lead to a so-called ‘common-method bias’. A potential way to reduce this bias would be to expand the sources of information (eg, supervisors’ assessments of employee burnout and engagement) and the methods of data collection (ie, triangulation of data), for instance by including qualitative data as a next step. We are aware that self-ratings and observer ratings of work characteristics and job demands may not necessarily correlate high. However, we believe that expanding the information source through third-party observations as well as triangulation can help to provide a richer picture of the work characteristics being studied. Another limitation of this study is the relatively small sample size, especially in the group of specialists. To examine if power was sufficient in both samples of residents and specialists, we conducted post hoc power analyses (Soper DS. (2019). Post-hoc Statistical Power Calculator for Multiple Regression (Software). Available from http://www.daniel soper.com/statcalc ) on several unsupported direct effects (eg, paths self-compassion and psychological flexibility to burnout for specialists, path psychological capital to burnout for residents). In all cases, the statistical power was 1.0, indicating that non-significant findings are most likely truly non-significant, that is, that this study had enough power for the conducted analyses. Furthermore, this study is limited by its sample composition, which predominantly consists of female pediatricians or pediatric residents. While the gender demographics of our sample closely matched the broader hospital population for residents, this was not the case for specialists as female specialists were over-represented in our sample. While this is likely due to the intervention context of this study, future studies should include a larger sample with different specialties and ensure a more equal gender distribution to test if these effects are stable across specialties and gender. However, with ample evidence supporting the JD-R model’s presumptions in different professional contexts and in various samples, it is not likely that the results of this study are greatly biased by its sample characteristics. Finally, the concept of colleague support is limited, in the sense that it does not allow for a differentiation between support functions. Ideally, a concept of social support including such a differentiation could help to disentangle how perceived social support helps specialists to counteract stress and exhaustion and promote work engagement. Implications To our knowledge, this is the first study that attempts to reveal the specific demands and resources that may impact burnout and work engagement among residents and specialists. Understanding how demands and resources are linked to physician well-being and engagement is a fundamental premise for designing successful interventions to minimise the risk of burnout. Our results suggest that a one-size-fits-all approach might not be effective for promoting physician well-being but, instead, that interventions should be tailored to the specific needs of specialists and residents. This is in line with a recent call to consider contextual complexities such as specialty or career stage when setting up interventions to promote physician well-being. While interventions for specialists should focus on increasing psychological capital and colleague support, interventions for residents should, in addition to increasing psychological capital, be aimed at increasing self-compassion and psychological flexibility. Interestingly, especially personal resources seemed to preserve physician well-being and engagement. Therefore, targeting personal resources rather than structural constraints seems promising to counter the demands physicians face. Additionally, interventions could also target training institutions and hospitals with the aim of building a culture that facilitates self-compassion, psychological capital and psychological flexibility among their residents and specialists. We consider testing the effectiveness of interventions aiming at fostering personal resources an important future inquiry.
The goal of this study was to gain insight on the prevailing demands and resources that contribute to burnout and work engagement in medical residents and specialists. This study revealed that residents and specialists face different demands in their work that cannot be measured by the same yardstick but instead require tailored solutions. Confirming prior studies on the stressful demands during residency, our data showed that residents compared with specialists experienced less autonomy and felt more uncertain about the future of their job. Furthermore, symptoms of exhaustion and cynicism among residents increased with tenure, which may at least partly relate to growing feelings of job insecurity (see ). Contrary to what has been reported in previous studies, residents did not report significantly higher exhaustion and cynicism than specialists but, on average, felt less engaged with their work. We suggest that specialists and residents resort to different resources to cope with their job demands. Although both groups have the same level of resources at their disposal, only certain resources contribute to the well-being of specialists and residents, respectively. While specialists benefit from psychological capital and colleague support, residents benefit especially from psychological flexibility and self-compassion. It is likely that residents and specialists—as a function of their role and the career phase they are in—use those resources that bring the greatest benefit when facing job demands at work. This will be discussed subsequently. In addition, psychological capital was found to play a role for the work engagement of both specialists and residents, which corroborates earlier findings among other professional groups. Physicians are exposed to high job demands, both during attendance and residency, which could harm their well-being. However, our study suggests that job demands other than workload (eg, job insecurity, work-family conflict) and a lack of resources (eg, self-compassion, psychological capital and psychological flexibility) play a prominent role in the onset of burnout. The fact that the residents in this study reported a relatively lower workload than specialists, yet reported similar symptoms of burnout, underlines this notion. Generally, our findings suggest that for preventing burnout it is important to focus on those demands and resources that are most relevant for specific groups of physicians (eg, specialists or residents). Specialists may particularly benefit from interventions that raise their psychological capital and—at the team level—foster team cohesion and support, whereas residents may benefit relatively more from interventions that increase their self-compassion and flexibility.
Personal resources Consistent with prior research, psychological capital played an eminent role for the well-being of specialists. Psychological capital may reduce the risk of burnout in two ways. First, it can counteract the distress associated with a demanding workplace by regulating negative emotions. Second, individuals with high psychological capital tend to perceive job demands as challenges rather than hindrances. That is, they associate job demands with personal gain or growth, evoking positive emotions, instead of fear and threat, evoking negative emotions. Given the buffering capacity of psychological capital, it is surprising that we did not find the same result among residents. Instead, we found that flexibility and self-compassion rather than psychological capital contributed to the well-being of residents. The importance of flexibility and self-compassion among residents may be due to their specific career phase, which is characterised by insecurity, constant feedback and criticism. That is, residency is an extremely challenging period, in which residents have to deal with their newly gained responsibilities (ie, managing uncertainty, breaking bad news) while also processing new information and continuously adapting to new organisational structures and teams. Residents have to shift regularly between their roles as trainee and doctor, experience high challenges at work and are confronted with their relative lack of knowledge and skills when entering residency. More so, residents are taught from medical school on to be critical towards themselves, a necessity that is demanded in a high-stake work environment where carelessness can have radical consequences. Consequently, medical professionals likely adopt a rather self-critical attitude. One way to deal with these stressful work events is to accept one’s inexperience, forgive one’s deficiencies (ie, self-compassion) and remain effective despite self-doubt and worries (ie, psychological flexibility). More specifically, residents need to internalise that despite the current healthcare culture, not knowing, insecurities and mistakes are part of the journey and not a sign of weakness or failure. In addition, psychological flexibility may allow residents to shift between tasks and professional roles, as it facilitates adapting to fluctuating situational demands, shifting perspective and reconfiguring mental resources. Thus, being kind towards oneself and viewing one’s own shortcomings as human can help to safeguard residents against the stressors uniquely present in residency. Colleague support In addition to psychological capital, colleague support also seems to promote the well-being of specialists. Numerous studies have indeed shown that social support is associated with both psychological and physical health outcomes as it ameliorates the impact of stress and strain on health. First, social support may involve emotional support, the feeling that one is loved and cared for. Second, it may involve the provision and sharing of information. Specialists work in relatively permanent teams with interdependent work relationships. Knowing their colleagues and their expertise well, they can ask for and receive emotional but also informational support. Colleagues can provide intimacy or reassurance during emotional and stressful events and they can assist in times of uncertainty and difficult medical inquiries that require another expert opinion. Although our data does not allow any insights in the quality of support received from colleagues, it is possible that the quality of support is different for residents and specialists. Because of the nature of residency (eg, competition and regular rotations), it is likely that colleague relationships are relatively less permanent and fruitful for residents. Although valuing their opinion, residents might not be convinced that they can ultimately lean on a fellow resident’s opinion in solving medical problems. This could explain why residents benefit relatively less from colleague support than specialists.
Consistent with prior research, psychological capital played an eminent role for the well-being of specialists. Psychological capital may reduce the risk of burnout in two ways. First, it can counteract the distress associated with a demanding workplace by regulating negative emotions. Second, individuals with high psychological capital tend to perceive job demands as challenges rather than hindrances. That is, they associate job demands with personal gain or growth, evoking positive emotions, instead of fear and threat, evoking negative emotions. Given the buffering capacity of psychological capital, it is surprising that we did not find the same result among residents. Instead, we found that flexibility and self-compassion rather than psychological capital contributed to the well-being of residents. The importance of flexibility and self-compassion among residents may be due to their specific career phase, which is characterised by insecurity, constant feedback and criticism. That is, residency is an extremely challenging period, in which residents have to deal with their newly gained responsibilities (ie, managing uncertainty, breaking bad news) while also processing new information and continuously adapting to new organisational structures and teams. Residents have to shift regularly between their roles as trainee and doctor, experience high challenges at work and are confronted with their relative lack of knowledge and skills when entering residency. More so, residents are taught from medical school on to be critical towards themselves, a necessity that is demanded in a high-stake work environment where carelessness can have radical consequences. Consequently, medical professionals likely adopt a rather self-critical attitude. One way to deal with these stressful work events is to accept one’s inexperience, forgive one’s deficiencies (ie, self-compassion) and remain effective despite self-doubt and worries (ie, psychological flexibility). More specifically, residents need to internalise that despite the current healthcare culture, not knowing, insecurities and mistakes are part of the journey and not a sign of weakness or failure. In addition, psychological flexibility may allow residents to shift between tasks and professional roles, as it facilitates adapting to fluctuating situational demands, shifting perspective and reconfiguring mental resources. Thus, being kind towards oneself and viewing one’s own shortcomings as human can help to safeguard residents against the stressors uniquely present in residency.
In addition to psychological capital, colleague support also seems to promote the well-being of specialists. Numerous studies have indeed shown that social support is associated with both psychological and physical health outcomes as it ameliorates the impact of stress and strain on health. First, social support may involve emotional support, the feeling that one is loved and cared for. Second, it may involve the provision and sharing of information. Specialists work in relatively permanent teams with interdependent work relationships. Knowing their colleagues and their expertise well, they can ask for and receive emotional but also informational support. Colleagues can provide intimacy or reassurance during emotional and stressful events and they can assist in times of uncertainty and difficult medical inquiries that require another expert opinion. Although our data does not allow any insights in the quality of support received from colleagues, it is possible that the quality of support is different for residents and specialists. Because of the nature of residency (eg, competition and regular rotations), it is likely that colleague relationships are relatively less permanent and fruitful for residents. Although valuing their opinion, residents might not be convinced that they can ultimately lean on a fellow resident’s opinion in solving medical problems. This could explain why residents benefit relatively less from colleague support than specialists.
Personal resources Our finding that psychological capital is a personal resource that is vital for the work engagement of both residents and specialists corroborates with prior studies among other professional groups. Unexpectedly, self-compassion was negatively rather than positively associated with the work engagement of specialists, while we found no such effect for residents. It is possible that high levels of self-compassion represent a self-protective bias, which serves to deny responsibility for failure. That is, high self-compassion may lean towards attributing failure to external factors (eg, situational constrains, lack of help from others) allowing specialists to maintain positive perceptions of their capabilities. Over a longer period of time, this way of thinking about their own shortcomings may hamper specialists’ personal development and work efforts, which may ultimately cause a reduction in work engagement. It is therefore worth exploring whether the benefits of self-compassion depend on time or whether there is an optimal level—or perhaps a tipping point—at which self-compassion contributes to one’s well-being. Colleague support Colleague support not only buffered the occurrence of burnout but also fostered work engagement among specialists rather than residents. As argued above, specialists as opposed to residents work in more permanent teams. It has been consistently found that the social support in these teams facilitates the work engagement of team members.
Our finding that psychological capital is a personal resource that is vital for the work engagement of both residents and specialists corroborates with prior studies among other professional groups. Unexpectedly, self-compassion was negatively rather than positively associated with the work engagement of specialists, while we found no such effect for residents. It is possible that high levels of self-compassion represent a self-protective bias, which serves to deny responsibility for failure. That is, high self-compassion may lean towards attributing failure to external factors (eg, situational constrains, lack of help from others) allowing specialists to maintain positive perceptions of their capabilities. Over a longer period of time, this way of thinking about their own shortcomings may hamper specialists’ personal development and work efforts, which may ultimately cause a reduction in work engagement. It is therefore worth exploring whether the benefits of self-compassion depend on time or whether there is an optimal level—or perhaps a tipping point—at which self-compassion contributes to one’s well-being.
Colleague support not only buffered the occurrence of burnout but also fostered work engagement among specialists rather than residents. As argued above, specialists as opposed to residents work in more permanent teams. It has been consistently found that the social support in these teams facilitates the work engagement of team members.
The participation of both residents and specialists from different specialties and the high response rate (78%) allowed for a realistic display of the demands and resources that physicians encounter during different stages of their career. Our research shows how different demands and resources relate to burnout and work engagement among specific groups of physicians and, as such, advances our understanding of how to intervene when well-being or work engagement are at risk. This is an important first step in the prevention of burnout and the conservation of work engagement among healthcare professionals. Yet, our results also indicate that burnout and work engagement are highly interweaved, just as in numerous prior studies. Consequently, it is important to consider both burnout and work engagement when addressing job functioning as a whole. Finally, our study has some limitations. First, although theory and research point to causal relationships between demands and burnout and resources and work engagement, our design does not allow to draw causal conclusions. It is possible that the proposed relationships in the JD-R model are reversed. For instance, feelings of exhaustion and cynicism may change the way employees perceive their work demands, intensifying the feeling that demands are piling up. Future research could use multiwave designs that can provide insight into the development of study variables over time and the causal dynamics in this process. Second, all data have been gathered using self-report questionnaires. This might lead to a so-called ‘common-method bias’. A potential way to reduce this bias would be to expand the sources of information (eg, supervisors’ assessments of employee burnout and engagement) and the methods of data collection (ie, triangulation of data), for instance by including qualitative data as a next step. We are aware that self-ratings and observer ratings of work characteristics and job demands may not necessarily correlate high. However, we believe that expanding the information source through third-party observations as well as triangulation can help to provide a richer picture of the work characteristics being studied. Another limitation of this study is the relatively small sample size, especially in the group of specialists. To examine if power was sufficient in both samples of residents and specialists, we conducted post hoc power analyses (Soper DS. (2019). Post-hoc Statistical Power Calculator for Multiple Regression (Software). Available from http://www.daniel soper.com/statcalc ) on several unsupported direct effects (eg, paths self-compassion and psychological flexibility to burnout for specialists, path psychological capital to burnout for residents). In all cases, the statistical power was 1.0, indicating that non-significant findings are most likely truly non-significant, that is, that this study had enough power for the conducted analyses. Furthermore, this study is limited by its sample composition, which predominantly consists of female pediatricians or pediatric residents. While the gender demographics of our sample closely matched the broader hospital population for residents, this was not the case for specialists as female specialists were over-represented in our sample. While this is likely due to the intervention context of this study, future studies should include a larger sample with different specialties and ensure a more equal gender distribution to test if these effects are stable across specialties and gender. However, with ample evidence supporting the JD-R model’s presumptions in different professional contexts and in various samples, it is not likely that the results of this study are greatly biased by its sample characteristics. Finally, the concept of colleague support is limited, in the sense that it does not allow for a differentiation between support functions. Ideally, a concept of social support including such a differentiation could help to disentangle how perceived social support helps specialists to counteract stress and exhaustion and promote work engagement.
To our knowledge, this is the first study that attempts to reveal the specific demands and resources that may impact burnout and work engagement among residents and specialists. Understanding how demands and resources are linked to physician well-being and engagement is a fundamental premise for designing successful interventions to minimise the risk of burnout. Our results suggest that a one-size-fits-all approach might not be effective for promoting physician well-being but, instead, that interventions should be tailored to the specific needs of specialists and residents. This is in line with a recent call to consider contextual complexities such as specialty or career stage when setting up interventions to promote physician well-being. While interventions for specialists should focus on increasing psychological capital and colleague support, interventions for residents should, in addition to increasing psychological capital, be aimed at increasing self-compassion and psychological flexibility. Interestingly, especially personal resources seemed to preserve physician well-being and engagement. Therefore, targeting personal resources rather than structural constraints seems promising to counter the demands physicians face. Additionally, interventions could also target training institutions and hospitals with the aim of building a culture that facilitates self-compassion, psychological capital and psychological flexibility among their residents and specialists. We consider testing the effectiveness of interventions aiming at fostering personal resources an important future inquiry.
With physician well-being being central to optimal patient care, it is important to uncover work characteristics that influence work engagement and burnout. This study revealed that physicians are not a uniform body but that medical residents and specialists face different challenges in their work that require unique resources to resort to. While all physicians are likely to benefit from resources facilitating goal attainment (ie, psychological capital), medical residents may additionally benefit from self-care and flexibility and specialists may additionally benefit from social support. Finally, by respecting also the unique needs of residents and specialists, one can create equal opportunities for all physicians in the challenging workplace that healthcare is.
Reviewer comments Author's manuscript
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Narrative medicine and humanities for health professions education: an experimental study | 01e8820d-be93-4d7f-a335-bd3616f31adf | 10339765 | Patient-Centered Care[mh] | Introduction Because health professionals have been trained to focus on their patients’ history of disease in order to keep patients alive longer than expected , while confronting with life-and death situations, they would pay more attention to the evidence-based medicine, not caring too much about patients’ human experiences concerning pain, suffering, desperation, or even dying . Moreover, with compassion fatigue and empathy burnout due to long working hours and constant experience of death and grief , they may gradually lose the willingness to listen to patients’ illness stories and unable to empathize with patients by imagining their fear and suffering . Therefore, when confronting critical life-and-death situations, health professionals may be unprepared or unable to deal with ethical/moral dilemmas and conflicts, as their focus may prioritize personal, professional, and organizational values . The negligence of patients’ illness experiences may lead to a deterioration in communication among patients, doctors, nurses, therapists, and healthcare professionals . However, the deterioration in communication can be filled up with the use of narrative medicine. Charon defined ‘narrative medicine’ as a skill to develop the ability to ‘recognize, absorb, interpret, and be moved’ by illness stories, which can be used to train health professionals to witness the suffering of patients. Research has shown that sharpening literary narrative skills can bring positive impacts upon health professionals and patients. Also, they can facilitate self-reflection , empathetic connections , and professional identification . As Charon asserted that with the use of illness narrative threads, health professions students and health professionals can give meaning to metaphoric expressions, facilitate the development of moral imagination given contradictory points of view, and most importantly, work together with patients to provide quality care [ , , ]. In addition, through ongoing narrative construction, students can gradually develop a strong connection and identification with the health profession and thus develop their collective professional identity . Narrative medicine focuses on the ethical and humanistic side of medicine. In contrast to evidence-based medicine, which focuses on disease and scientific content, narrative medicine focuses on the communication among patients, patient families, and health professionals . Hence, narrative medicine also plays a significant role in health provider-patient communication in developing a healing relationship, which can be regarded as an interpersonal interaction between patients and providers, including cognitive and affective components, such as caring, empathy, understanding, and how message is transmitted . The illness narrative skills of ‘attention, representation, and affiliation’ can help health professionals increase their sensibility and empathy when faced with dilemmas and frustrating clinical or healthcare situations in order to carry on their professional work . Moreover, while using narrative medicine as a tool to realize their professional limits and predicaments, healthcare professionals can reflect upon ethical/moral dilemmas happening in healthcare settings, and hence give meaning to their own lives while constructing their professional identity . For health professions students, while contemplating over patients’ illness or controversial issues in literary narratives, they can raise skepticism over these issues to make sense of a dilemmatic situation in a clinical or healthcare setting, hence developing self-reflection capacity to explore controversial issues, intellectually and affectively . Moreover, with illness narrative writing and storytelling as self-reflection, they can realize their professional limits and have a chance to pour out their negative emotions, for instance, fear or anger, and thus reach an emotional release and catharsis [ , , ]. Illness stories can also be used to arouse students’ ethical/moral imagination. The ethical/moral issues raised in stories, novels, dramas, poetry lead the would-be health professionals to read the narratives involved in ethical/moral dilemmas and begin to pay attention to human suffering . In addition, through the mimetic actions in novels, memoirs, or illness narratives, they may arouse their ethical/moral imagination to receive, interpret, and ethically/morally reason human’s pain, predicament, or suffering, which would help them better understand and deal with ethical/moral dilemmas when they are going to make decisions later on in real clinical and healthcare settings .
Methods Though narrative medicine has been studied, there is no research using narrative medicine via literature and visual art to form an empathetic connection with those suffering. In order to let health professions students have an opportunity to review narrative medicine and mimetically go through life experiences of patients, patient families, physicians, nurses, and other health professionals, the study intended to use narrative medicine as a mechanism for an empathetic connection with those suffering in literature and visual art to examine whether the narrative medicine-based intervention would positively impact health professions students with regard to professional identity, self-reflection, emotional catharsis, and self-reflective writing competency. Therefore, this study put forward the following research hypotheses, shown as . 2.1. Quasi-experimental design The research adopted a two-group quasi-experimental design to examine the impact of narrative medicine-based intervention on health professions education in terms of professional identity, self-reflection, emotional catharsis, and reflective writing competence. Quasi-experiments are often conducted to examine the effectiveness of an educational intervention in settings in which random assignment is difficult or impossible because the field settings or the groupings may already exist prior to the experiment . A coin flip was used to allocate the two groups in an elective course to the experimental group (IN – EC—Literature and Visual Art; 35 students) and the control group ( non IN – EC—Literature and Visual Art; 32 students). The intervention lasted for 16 weeks and included a 2-hour in-class session and a 2-hour-minimum self-directed study each week. Before and after the intervention, both group students were required to take the pretests and posttests on professional identity, self-reflection, emotional catharsis, and reflective writing competency. The two groups were taught by the same instructor and were provided with the same teaching material, including literature and visual arts. The only difference was that the experimental group was instructed using narrative medicine to form an empathetic connection. After the intervention, both groups were compared with respect to the pretest and posttest results of a professional identity scale, a reflective thinking scale, an emotional catharsis scale, and an analytic reflective writing scoring rubric. The pretest and posttest results were used for data analysis to examine their learning performances and the feasibility of the intervention. Following the questionnaire collection, semi-structured personal interviews were conducted to realize the participants’ inner feelings and reflections about the narrative medicine-based intervention. Twelve students receiving the intervention volunteered to participate in the interview. All the interview content was recorded and transcribed for more detailed analysis. 2.2. Participants In this research, a two-group quasi-experimental design was used. These 67 participants were health professions students in a medical university (mean age = 20.02; SD = 0.23), with varied majors in health disciplines, such as medicine, nursing, dentistry, psychology, nutrition science, physical therapy, occupational therapy, public health, medical informatics, occupational safety and health, etc. Among the 67 students, 40 students (59.70%) were female, and 27 students were male (40.30%). These students had received service-learning education and training upon enrollment. They might go to nursing homes, hospitals, or any medical or healthcare institutions; hence they had some experience of interacting with patients, patient families, and health professionals in clinical and healthcare settings. The research got approval of the Institutional Review Board’s (IRB) of Chung Shang Medical University Hospital (No. CS16157, dated 9 January 2017) in accordance with the relevant ethical research guidelines . Before the data collection, a researcher let students know the research purpose; their identities were kept strictly confidential, and the data were analyzed anonymously. However, the participants in the elective course did not know whether they were in the control group or experimental group in order to prevent bias in research results, such as Hawthorne effect, John Henry effect, etc. As mentioned, the only difference was that the experimental group students were instructed using narrative medicine to form an empathetic connection with those suffering in literature and visual art. Therefore, they were required to go through the three stages of narrative medicine-based mechanism: attention → representation → affiliation. As for the control group, the students did not go through the three stages of narrative medicine to form an empathetic connection but were situated in a traditional lecture class, with some group discussions and question-and-answer exercises. 2.3. Intervention: Illness narrative as an empathetic connection to literature and visual arts study As previously mentioned, the difference between the two groups was the use (or lack thereof) of narrative medicine to form an empathetic connection. To facilitate an empathetic connection to literature and visual arts, the following six narrative skills, proposed by Engel, Zarconi, Pethel, et al. for narrative medicine, were applied while experimental group students were reading or writing narrative medicine: practice of ethical/moral imagination practice of empathic attendance and attentive listening close reading and interpretation of ethical/moral dilemmas in texts reflective writing and narration of illness stories ethical/moral reasoning with illness stories engagement in narrative ethics/morality. In addition, to empathize with people’ predicament and suffering, the experimental group students were also asked to familiarize themselves with the three stages of narrative medicine, attention → representation → affiliation, in order to give meaning to metaphoric expressions and construct ethical or moral imagination from contradictory points of view and thereby reflect upon the medical care process and grasp significance in the narrative medicine. Among the narrative skills, attention referred to being mindfully present in clinical encounters; representation referred to becoming involved in clinical encounters in order to find significance, and affiliation referred to building an emotional connection with patients, patient families, and other healthcare professionals. Because these participants were students from various health disciplines, when introducing scheduled medical ethics/humanities topics, the instructor focused on the ethical and humanistic side of healthcare literature and visual art in critical life-and-death situations to help students build an ethical/moral imagination to manage ethical/moral dilemmas and conflicts so as to prepare these health disciplines students confront ethical, moral, or social issues that might arise in the clinical and healthcare settings . After that, the experimental group read and wrote stories about illness in order to consider the patients’ and healthcare professionals’ viewpoints, as well as patient families’, hence forming an empathetic connection with them. As for the control group students, though using the same material as the students in the experimental group, the instructor did not teach them how to use the three stages of narrative medicine (attention → representation → affiliation) to construct ethical or moral imagination from contradictory points of view. Instead, the instructor adopted a more conventional approach; the control group students were given traditional lectures, not have the chance to access the three stages of narrative medicine (attention → representation → affiliation) to construct ethical or moral imagination. They were given the lectures most of the time and mostly focusing on the explanation of medical ethics and humanities in the teaching material, with no practice of empathic attendance and attentive listening to illness stories. To facilitate peer interaction and discussion about the ethical/moral dilemmas and conflicts hidden in literature and visual arts, after reading medical ethics-/humanities-related issues in the literature and visual arts study, the experimental and control groups were requested to regularly login the Moodle Learning website to post, in approximately 380–500 words, a summary, their feelings, a reflection, or responses or resolutions regarding the dilemmas and issues raised. Since the discussion itself was not in person, the forum provided a comfortable environment where students might scrutinize and learn with each other . Moreover, due to the nature of an asynchronous online discussion, the students were not expected to provide feedback instantaneously, which allowed them more time to reflect and offer comments about the issues. The course content and teaching material are shown in Supplementary 1. 2.4. Instrumentation The study intended to examine whether the narrative medicine-based intervention would positively impact health professions students with regard to professional identity, self-reflection, emotional catharsis, and self-reflective writing competency. Therefore, to reach the objectives, the following scales and rubric were used for measurement. 2.4.1. Professional Identity Scale for Healthcare Students and Providers (PIS-HSP) A collective healthcare professional identity is a key factor to let healthcare professions students and professionals have same goals and values to facilitate interdisciplinary collaboration for quality care . Hence, in order to assess the participants’ level of collective professional identity among the interprofessional healthcare community, Liao and Wang’s study of the PIS-HSP scale was used to measure the participants’ professional identity level, with 9 denoting ‘completely agree’ and 1 denoting ‘completely disagree.’ The short-form PIS-HSP scale, with overall Cronbach’s α 0.89, included 18 items and four factors: ‘professional commitment and devotion’ (6 items; factor loadings: 0.644–0.886; Cronbach’s α: 0.91), ‘emotional identification & belongingness’ (4 items; factor loadings: 0.854–0.888; Cronbach’s α: 0.93), ‘professional goals & values’ (4 items; factor loadings: 0.573–0.943; Cronbach’s α: 0.88), and ‘self-fulfillment & retention tendency’ (4 items; factor loadings: 0.563–0.822; Cronbach’s α: 0.78). The 18-item PIS-HSP scale also showed acceptable convergent validities; also, the discriminant validities were proven with the square root of every AVE value higher than the r between factors . The short-form PIS-HSP scale has a maximum score of 162 and a minimum score of 18. The higher the score, the higher the level of participants’ professional identity . Based on the present sample, the Cronbach’s α for the whole scale and the four factors were 0.97, 0.96, 0.96, 0.92, and 0.91, respectively. 2.4.2. Reflective Thinking Scale for Healthcare Students and Providers (RTS-HSP) Reflective thinking involves deliberate consideration and integration of prior experience and knowledge to facilitate positive interactions between doctors, healthcare professionals, patients, and patient families . To assess the level of reflective thinking, the 9-point Likert scale of RTS-HSP based on the responses of 579 subjects was used, with 9 meaning ‘always’ and 1 meaning ‘never.’ The RTS-HSP, with overall Cronbach’s α 0.87, included four factors and 22 items: reflective skepticism (6 items; factor loadings: 0.66–0.80; Cronbach’s α: 0.84), self-examination (6 items; factor loadings: 0. 65–0.85; Cronbach’s α: 0.84), empathetic reflection (5 items; factor loadings: 0.65–0.77; Cronbach’s α: 0.80), and critical open-mindedness (5 items; factor loadings: 0.60–0.87; Cronbach’s α: 0.77) . The PIS-HSP scale has a maximum score of 198 and a minimum score of 22. The higher the score, the higher the student’s reflective thinking level. Based on the present sample, the Cronbach’s α for the whole scale and the four factors were 0.94, 0.84, 0.91, 0.89, and 0.91, respectively. 2.4.3. Scale Measuring Emotional Catharsis through Illness Narratives (ECS-IN) Emotional catharsis is the process of strongly expressing repressed or immediate negative emotions, such as pity, fear, stress, and anxiety, in order to release hostility or trauma in the mind, and thus generate a certain positive emotion or change in one’s life . In this study, a short form emotional catharsis (ECS-IN) scale was used to measure the emotional catharsis level of students, with 9 indicating ‘strongly agree’ and 1 indicating ‘strongly disagree.’ Students receiving higher scores on the ECS-IN were interpreted as having stronger emotional catharsis. The 18-item ECS-IN, with overall Cronbach’s α 0.946, included three factors: ‘emotional identification as self-healing’ (7 items; factor loadings: 0.747–0.886; Cronbach’s α: 0.930), ‘emotional release for compensation’ (7 items; factor loadings: 0.724–0.814; Cronbach’s α: 0.907), and ‘emotional adjustment for intellectual growth’ (4 items; factor loadings: 0.688–0.899; Cronbach’s α: 0.888). The phrase ‘emotional identification as self-healing’ scale refers to emotional identification with the person in illness narratives to achieve emotional release and self-recovery. The phrase ‘emotional release for compensation’ refers to dealing with inner anxiety, fear, or negative emotions to unleash negative feelings and thus find relief via illness narratives. The “emotional adjustment for intellectual growth’ refers to the use of illness narratives to deal with ambivalences in clinical or healthcare settings so as to regulate emotions and thus reach intellectual growth . The 18-item ECS-IN scale also showed acceptable convergent validities, and the discriminant validities were proven . The ECS-IN scale has a maximum score of 162 and a minimum score of 18. The higher the score, the stronger the emotional catharsis a participant had . Based on the present sample, the Cronbach’s α for the whole scale and the three factors were 0.97, 0.95, 0.94, and 0.95, respectively. 2.4.4. Analytic Reflective Writing Scoring Rubric for Healthcare Students and Providers (ARWSR-HSP) An analytic reflective writing scoring rubric (ARWSR-HSP) developed by the researchers was used to assess students’ reflective writing competency toward medical conflicts and ambivalent feelings in terms of their ‘focus and contextualization,’ ‘ideas and elaboration,’ ‘voices and points of view,’ ‘critical thinking and representation,’ ‘depth of reflection regarding personal growth,’ and ‘language and style.’ Given that the dimensions of ‘critical thinking and representation’ and ‘depth of reflection regarding personal growth’ were salient characteristics, they were doubly weighted. Therefore, the range of possible scores for ARWSR-HSP was 0 to 40. Those who scored between 40 and 35 were considered to have excellent reflective writing; those who scored between 34 and 28, strong reflective writing; those who scored between 27 and 21, good reflective writing; those who scored between 20 and 14, acceptable reflective writing; those who scored between 13 and 7, weak reflective writing; and those who scored between 6 and 0, unacceptable reflective writing. The interrater reliabilities using Spearman’s correlation coefficients were between 0.757 and 0.946; the interrater reliabilities using weighed kappas were between 0.706 and 0.884. The intrarater constancy estimates were between 0.825 and 0.930. Two well-trained blind graders assess students’ reflective competency before and after the intervention to prevent bias in outcome assessment . 2.5. Data analysis The research adopted the Statistical Package for Social Sciences (SPSS; version 14.0) to examine the quantitative data, including one-way MANOVA (Multivariate Analysis of Variance) and one-way MANCOVA (Multivariate Analysis of Covariance). MANOVA and MANCOVA are good for simultaneous measurements of two or more dependent variables in an experimental study with two or more experimental and control groups and hence can protect against Type I errors, compared to running a multiple ANOVA procedure . Prior to the parametric tests, the study first used Skewness and Kurtosis to examine the assumption of normal distribution. According to Hair , to assess whether the skewness and Kurtosis values are in normal distribution, the cut-off values ± 2.58 (at 0.01 significance level) and ± 1.96 (at 0.05 significance level) are most commonly used values. Byrne , after reviewing the kurtosis values, confirmed that kurtosis equal to or greater than 7 indicates a deviation from the normality. Kline thinks that the absolute value of skewness ‘|ˆγ 1 |>3.0 are described as “severely” skewed’|‘|ˆγ 1 |>3.0 are described as “severely” skewed’|‘|ˆγ 1 |>3.0 are described as “severely” skewed’ (p. 76), and that ‘|ˆγ 1 |>3.0 are described as “severely” skewed’the absolute value of kurtosis ‘|ˆγ 1 |>3.0 are described as “severely” skewed’|“the absolute value of kurtosis ‘|ˆγ 2 |>10.0 suggests a problem’|“the absolute value of kurtosis ‘|ˆγ 2 |>10.0 suggests a problem’ (p. 77). Furthermore, to test the multivariate normal distribution, the Mahalanobis distances and the critical points of the Chi-squared distribution were examined. The number of degrees of freedom for the Chi-squared distribution is equal to the number of variables; thus, for three variables, it has three degrees of freedom. At the 0.05 significance level, the corresponding critical point of Chi-square distribution based on three degrees of freedom is 7.815; the corresponding critical point with four degrees of freedom is 9.488; the corresponding critical point with five degrees of freedom is 11.070 . If the maximal Mahalanobis distance is less than the corresponding critical points of the Chi-squared distribution, the sample data are in a multivariate normal distribution . Then, the study used MANOVA to compare multivariate sample means. In order to control the potential initial group differences, the study further used pretest results as covariates and used one-way MANCOVA to adjust the means in order to reduce any systematic bias . The confidence level was 95% ( p < 0.05). In addition, Pillai’s Trace was used to test the homogeneity of variance (the covariance matrices) and to robust Type I error , with the p -value >0.05 indicating the homogeneity of the covariance matrices . The Pearson correlation (| r |) for the variables was also used to test the multicollinearity, with the | r | < 0.9 indicating no evidence of multicollinearity .
Quasi-experimental design The research adopted a two-group quasi-experimental design to examine the impact of narrative medicine-based intervention on health professions education in terms of professional identity, self-reflection, emotional catharsis, and reflective writing competence. Quasi-experiments are often conducted to examine the effectiveness of an educational intervention in settings in which random assignment is difficult or impossible because the field settings or the groupings may already exist prior to the experiment . A coin flip was used to allocate the two groups in an elective course to the experimental group (IN – EC—Literature and Visual Art; 35 students) and the control group ( non IN – EC—Literature and Visual Art; 32 students). The intervention lasted for 16 weeks and included a 2-hour in-class session and a 2-hour-minimum self-directed study each week. Before and after the intervention, both group students were required to take the pretests and posttests on professional identity, self-reflection, emotional catharsis, and reflective writing competency. The two groups were taught by the same instructor and were provided with the same teaching material, including literature and visual arts. The only difference was that the experimental group was instructed using narrative medicine to form an empathetic connection. After the intervention, both groups were compared with respect to the pretest and posttest results of a professional identity scale, a reflective thinking scale, an emotional catharsis scale, and an analytic reflective writing scoring rubric. The pretest and posttest results were used for data analysis to examine their learning performances and the feasibility of the intervention. Following the questionnaire collection, semi-structured personal interviews were conducted to realize the participants’ inner feelings and reflections about the narrative medicine-based intervention. Twelve students receiving the intervention volunteered to participate in the interview. All the interview content was recorded and transcribed for more detailed analysis.
Participants In this research, a two-group quasi-experimental design was used. These 67 participants were health professions students in a medical university (mean age = 20.02; SD = 0.23), with varied majors in health disciplines, such as medicine, nursing, dentistry, psychology, nutrition science, physical therapy, occupational therapy, public health, medical informatics, occupational safety and health, etc. Among the 67 students, 40 students (59.70%) were female, and 27 students were male (40.30%). These students had received service-learning education and training upon enrollment. They might go to nursing homes, hospitals, or any medical or healthcare institutions; hence they had some experience of interacting with patients, patient families, and health professionals in clinical and healthcare settings. The research got approval of the Institutional Review Board’s (IRB) of Chung Shang Medical University Hospital (No. CS16157, dated 9 January 2017) in accordance with the relevant ethical research guidelines . Before the data collection, a researcher let students know the research purpose; their identities were kept strictly confidential, and the data were analyzed anonymously. However, the participants in the elective course did not know whether they were in the control group or experimental group in order to prevent bias in research results, such as Hawthorne effect, John Henry effect, etc. As mentioned, the only difference was that the experimental group students were instructed using narrative medicine to form an empathetic connection with those suffering in literature and visual art. Therefore, they were required to go through the three stages of narrative medicine-based mechanism: attention → representation → affiliation. As for the control group, the students did not go through the three stages of narrative medicine to form an empathetic connection but were situated in a traditional lecture class, with some group discussions and question-and-answer exercises.
Intervention: Illness narrative as an empathetic connection to literature and visual arts study As previously mentioned, the difference between the two groups was the use (or lack thereof) of narrative medicine to form an empathetic connection. To facilitate an empathetic connection to literature and visual arts, the following six narrative skills, proposed by Engel, Zarconi, Pethel, et al. for narrative medicine, were applied while experimental group students were reading or writing narrative medicine: practice of ethical/moral imagination practice of empathic attendance and attentive listening close reading and interpretation of ethical/moral dilemmas in texts reflective writing and narration of illness stories ethical/moral reasoning with illness stories engagement in narrative ethics/morality. In addition, to empathize with people’ predicament and suffering, the experimental group students were also asked to familiarize themselves with the three stages of narrative medicine, attention → representation → affiliation, in order to give meaning to metaphoric expressions and construct ethical or moral imagination from contradictory points of view and thereby reflect upon the medical care process and grasp significance in the narrative medicine. Among the narrative skills, attention referred to being mindfully present in clinical encounters; representation referred to becoming involved in clinical encounters in order to find significance, and affiliation referred to building an emotional connection with patients, patient families, and other healthcare professionals. Because these participants were students from various health disciplines, when introducing scheduled medical ethics/humanities topics, the instructor focused on the ethical and humanistic side of healthcare literature and visual art in critical life-and-death situations to help students build an ethical/moral imagination to manage ethical/moral dilemmas and conflicts so as to prepare these health disciplines students confront ethical, moral, or social issues that might arise in the clinical and healthcare settings . After that, the experimental group read and wrote stories about illness in order to consider the patients’ and healthcare professionals’ viewpoints, as well as patient families’, hence forming an empathetic connection with them. As for the control group students, though using the same material as the students in the experimental group, the instructor did not teach them how to use the three stages of narrative medicine (attention → representation → affiliation) to construct ethical or moral imagination from contradictory points of view. Instead, the instructor adopted a more conventional approach; the control group students were given traditional lectures, not have the chance to access the three stages of narrative medicine (attention → representation → affiliation) to construct ethical or moral imagination. They were given the lectures most of the time and mostly focusing on the explanation of medical ethics and humanities in the teaching material, with no practice of empathic attendance and attentive listening to illness stories. To facilitate peer interaction and discussion about the ethical/moral dilemmas and conflicts hidden in literature and visual arts, after reading medical ethics-/humanities-related issues in the literature and visual arts study, the experimental and control groups were requested to regularly login the Moodle Learning website to post, in approximately 380–500 words, a summary, their feelings, a reflection, or responses or resolutions regarding the dilemmas and issues raised. Since the discussion itself was not in person, the forum provided a comfortable environment where students might scrutinize and learn with each other . Moreover, due to the nature of an asynchronous online discussion, the students were not expected to provide feedback instantaneously, which allowed them more time to reflect and offer comments about the issues. The course content and teaching material are shown in Supplementary 1.
Instrumentation The study intended to examine whether the narrative medicine-based intervention would positively impact health professions students with regard to professional identity, self-reflection, emotional catharsis, and self-reflective writing competency. Therefore, to reach the objectives, the following scales and rubric were used for measurement. 2.4.1. Professional Identity Scale for Healthcare Students and Providers (PIS-HSP) A collective healthcare professional identity is a key factor to let healthcare professions students and professionals have same goals and values to facilitate interdisciplinary collaboration for quality care . Hence, in order to assess the participants’ level of collective professional identity among the interprofessional healthcare community, Liao and Wang’s study of the PIS-HSP scale was used to measure the participants’ professional identity level, with 9 denoting ‘completely agree’ and 1 denoting ‘completely disagree.’ The short-form PIS-HSP scale, with overall Cronbach’s α 0.89, included 18 items and four factors: ‘professional commitment and devotion’ (6 items; factor loadings: 0.644–0.886; Cronbach’s α: 0.91), ‘emotional identification & belongingness’ (4 items; factor loadings: 0.854–0.888; Cronbach’s α: 0.93), ‘professional goals & values’ (4 items; factor loadings: 0.573–0.943; Cronbach’s α: 0.88), and ‘self-fulfillment & retention tendency’ (4 items; factor loadings: 0.563–0.822; Cronbach’s α: 0.78). The 18-item PIS-HSP scale also showed acceptable convergent validities; also, the discriminant validities were proven with the square root of every AVE value higher than the r between factors . The short-form PIS-HSP scale has a maximum score of 162 and a minimum score of 18. The higher the score, the higher the level of participants’ professional identity . Based on the present sample, the Cronbach’s α for the whole scale and the four factors were 0.97, 0.96, 0.96, 0.92, and 0.91, respectively. 2.4.2. Reflective Thinking Scale for Healthcare Students and Providers (RTS-HSP) Reflective thinking involves deliberate consideration and integration of prior experience and knowledge to facilitate positive interactions between doctors, healthcare professionals, patients, and patient families . To assess the level of reflective thinking, the 9-point Likert scale of RTS-HSP based on the responses of 579 subjects was used, with 9 meaning ‘always’ and 1 meaning ‘never.’ The RTS-HSP, with overall Cronbach’s α 0.87, included four factors and 22 items: reflective skepticism (6 items; factor loadings: 0.66–0.80; Cronbach’s α: 0.84), self-examination (6 items; factor loadings: 0. 65–0.85; Cronbach’s α: 0.84), empathetic reflection (5 items; factor loadings: 0.65–0.77; Cronbach’s α: 0.80), and critical open-mindedness (5 items; factor loadings: 0.60–0.87; Cronbach’s α: 0.77) . The PIS-HSP scale has a maximum score of 198 and a minimum score of 22. The higher the score, the higher the student’s reflective thinking level. Based on the present sample, the Cronbach’s α for the whole scale and the four factors were 0.94, 0.84, 0.91, 0.89, and 0.91, respectively. 2.4.3. Scale Measuring Emotional Catharsis through Illness Narratives (ECS-IN) Emotional catharsis is the process of strongly expressing repressed or immediate negative emotions, such as pity, fear, stress, and anxiety, in order to release hostility or trauma in the mind, and thus generate a certain positive emotion or change in one’s life . In this study, a short form emotional catharsis (ECS-IN) scale was used to measure the emotional catharsis level of students, with 9 indicating ‘strongly agree’ and 1 indicating ‘strongly disagree.’ Students receiving higher scores on the ECS-IN were interpreted as having stronger emotional catharsis. The 18-item ECS-IN, with overall Cronbach’s α 0.946, included three factors: ‘emotional identification as self-healing’ (7 items; factor loadings: 0.747–0.886; Cronbach’s α: 0.930), ‘emotional release for compensation’ (7 items; factor loadings: 0.724–0.814; Cronbach’s α: 0.907), and ‘emotional adjustment for intellectual growth’ (4 items; factor loadings: 0.688–0.899; Cronbach’s α: 0.888). The phrase ‘emotional identification as self-healing’ scale refers to emotional identification with the person in illness narratives to achieve emotional release and self-recovery. The phrase ‘emotional release for compensation’ refers to dealing with inner anxiety, fear, or negative emotions to unleash negative feelings and thus find relief via illness narratives. The “emotional adjustment for intellectual growth’ refers to the use of illness narratives to deal with ambivalences in clinical or healthcare settings so as to regulate emotions and thus reach intellectual growth . The 18-item ECS-IN scale also showed acceptable convergent validities, and the discriminant validities were proven . The ECS-IN scale has a maximum score of 162 and a minimum score of 18. The higher the score, the stronger the emotional catharsis a participant had . Based on the present sample, the Cronbach’s α for the whole scale and the three factors were 0.97, 0.95, 0.94, and 0.95, respectively. 2.4.4. Analytic Reflective Writing Scoring Rubric for Healthcare Students and Providers (ARWSR-HSP) An analytic reflective writing scoring rubric (ARWSR-HSP) developed by the researchers was used to assess students’ reflective writing competency toward medical conflicts and ambivalent feelings in terms of their ‘focus and contextualization,’ ‘ideas and elaboration,’ ‘voices and points of view,’ ‘critical thinking and representation,’ ‘depth of reflection regarding personal growth,’ and ‘language and style.’ Given that the dimensions of ‘critical thinking and representation’ and ‘depth of reflection regarding personal growth’ were salient characteristics, they were doubly weighted. Therefore, the range of possible scores for ARWSR-HSP was 0 to 40. Those who scored between 40 and 35 were considered to have excellent reflective writing; those who scored between 34 and 28, strong reflective writing; those who scored between 27 and 21, good reflective writing; those who scored between 20 and 14, acceptable reflective writing; those who scored between 13 and 7, weak reflective writing; and those who scored between 6 and 0, unacceptable reflective writing. The interrater reliabilities using Spearman’s correlation coefficients were between 0.757 and 0.946; the interrater reliabilities using weighed kappas were between 0.706 and 0.884. The intrarater constancy estimates were between 0.825 and 0.930. Two well-trained blind graders assess students’ reflective competency before and after the intervention to prevent bias in outcome assessment .
Professional Identity Scale for Healthcare Students and Providers (PIS-HSP) A collective healthcare professional identity is a key factor to let healthcare professions students and professionals have same goals and values to facilitate interdisciplinary collaboration for quality care . Hence, in order to assess the participants’ level of collective professional identity among the interprofessional healthcare community, Liao and Wang’s study of the PIS-HSP scale was used to measure the participants’ professional identity level, with 9 denoting ‘completely agree’ and 1 denoting ‘completely disagree.’ The short-form PIS-HSP scale, with overall Cronbach’s α 0.89, included 18 items and four factors: ‘professional commitment and devotion’ (6 items; factor loadings: 0.644–0.886; Cronbach’s α: 0.91), ‘emotional identification & belongingness’ (4 items; factor loadings: 0.854–0.888; Cronbach’s α: 0.93), ‘professional goals & values’ (4 items; factor loadings: 0.573–0.943; Cronbach’s α: 0.88), and ‘self-fulfillment & retention tendency’ (4 items; factor loadings: 0.563–0.822; Cronbach’s α: 0.78). The 18-item PIS-HSP scale also showed acceptable convergent validities; also, the discriminant validities were proven with the square root of every AVE value higher than the r between factors . The short-form PIS-HSP scale has a maximum score of 162 and a minimum score of 18. The higher the score, the higher the level of participants’ professional identity . Based on the present sample, the Cronbach’s α for the whole scale and the four factors were 0.97, 0.96, 0.96, 0.92, and 0.91, respectively.
Reflective Thinking Scale for Healthcare Students and Providers (RTS-HSP) Reflective thinking involves deliberate consideration and integration of prior experience and knowledge to facilitate positive interactions between doctors, healthcare professionals, patients, and patient families . To assess the level of reflective thinking, the 9-point Likert scale of RTS-HSP based on the responses of 579 subjects was used, with 9 meaning ‘always’ and 1 meaning ‘never.’ The RTS-HSP, with overall Cronbach’s α 0.87, included four factors and 22 items: reflective skepticism (6 items; factor loadings: 0.66–0.80; Cronbach’s α: 0.84), self-examination (6 items; factor loadings: 0. 65–0.85; Cronbach’s α: 0.84), empathetic reflection (5 items; factor loadings: 0.65–0.77; Cronbach’s α: 0.80), and critical open-mindedness (5 items; factor loadings: 0.60–0.87; Cronbach’s α: 0.77) . The PIS-HSP scale has a maximum score of 198 and a minimum score of 22. The higher the score, the higher the student’s reflective thinking level. Based on the present sample, the Cronbach’s α for the whole scale and the four factors were 0.94, 0.84, 0.91, 0.89, and 0.91, respectively.
Scale Measuring Emotional Catharsis through Illness Narratives (ECS-IN) Emotional catharsis is the process of strongly expressing repressed or immediate negative emotions, such as pity, fear, stress, and anxiety, in order to release hostility or trauma in the mind, and thus generate a certain positive emotion or change in one’s life . In this study, a short form emotional catharsis (ECS-IN) scale was used to measure the emotional catharsis level of students, with 9 indicating ‘strongly agree’ and 1 indicating ‘strongly disagree.’ Students receiving higher scores on the ECS-IN were interpreted as having stronger emotional catharsis. The 18-item ECS-IN, with overall Cronbach’s α 0.946, included three factors: ‘emotional identification as self-healing’ (7 items; factor loadings: 0.747–0.886; Cronbach’s α: 0.930), ‘emotional release for compensation’ (7 items; factor loadings: 0.724–0.814; Cronbach’s α: 0.907), and ‘emotional adjustment for intellectual growth’ (4 items; factor loadings: 0.688–0.899; Cronbach’s α: 0.888). The phrase ‘emotional identification as self-healing’ scale refers to emotional identification with the person in illness narratives to achieve emotional release and self-recovery. The phrase ‘emotional release for compensation’ refers to dealing with inner anxiety, fear, or negative emotions to unleash negative feelings and thus find relief via illness narratives. The “emotional adjustment for intellectual growth’ refers to the use of illness narratives to deal with ambivalences in clinical or healthcare settings so as to regulate emotions and thus reach intellectual growth . The 18-item ECS-IN scale also showed acceptable convergent validities, and the discriminant validities were proven . The ECS-IN scale has a maximum score of 162 and a minimum score of 18. The higher the score, the stronger the emotional catharsis a participant had . Based on the present sample, the Cronbach’s α for the whole scale and the three factors were 0.97, 0.95, 0.94, and 0.95, respectively.
Analytic Reflective Writing Scoring Rubric for Healthcare Students and Providers (ARWSR-HSP) An analytic reflective writing scoring rubric (ARWSR-HSP) developed by the researchers was used to assess students’ reflective writing competency toward medical conflicts and ambivalent feelings in terms of their ‘focus and contextualization,’ ‘ideas and elaboration,’ ‘voices and points of view,’ ‘critical thinking and representation,’ ‘depth of reflection regarding personal growth,’ and ‘language and style.’ Given that the dimensions of ‘critical thinking and representation’ and ‘depth of reflection regarding personal growth’ were salient characteristics, they were doubly weighted. Therefore, the range of possible scores for ARWSR-HSP was 0 to 40. Those who scored between 40 and 35 were considered to have excellent reflective writing; those who scored between 34 and 28, strong reflective writing; those who scored between 27 and 21, good reflective writing; those who scored between 20 and 14, acceptable reflective writing; those who scored between 13 and 7, weak reflective writing; and those who scored between 6 and 0, unacceptable reflective writing. The interrater reliabilities using Spearman’s correlation coefficients were between 0.757 and 0.946; the interrater reliabilities using weighed kappas were between 0.706 and 0.884. The intrarater constancy estimates were between 0.825 and 0.930. Two well-trained blind graders assess students’ reflective competency before and after the intervention to prevent bias in outcome assessment .
Data analysis The research adopted the Statistical Package for Social Sciences (SPSS; version 14.0) to examine the quantitative data, including one-way MANOVA (Multivariate Analysis of Variance) and one-way MANCOVA (Multivariate Analysis of Covariance). MANOVA and MANCOVA are good for simultaneous measurements of two or more dependent variables in an experimental study with two or more experimental and control groups and hence can protect against Type I errors, compared to running a multiple ANOVA procedure . Prior to the parametric tests, the study first used Skewness and Kurtosis to examine the assumption of normal distribution. According to Hair , to assess whether the skewness and Kurtosis values are in normal distribution, the cut-off values ± 2.58 (at 0.01 significance level) and ± 1.96 (at 0.05 significance level) are most commonly used values. Byrne , after reviewing the kurtosis values, confirmed that kurtosis equal to or greater than 7 indicates a deviation from the normality. Kline thinks that the absolute value of skewness ‘|ˆγ 1 |>3.0 are described as “severely” skewed’|‘|ˆγ 1 |>3.0 are described as “severely” skewed’|‘|ˆγ 1 |>3.0 are described as “severely” skewed’ (p. 76), and that ‘|ˆγ 1 |>3.0 are described as “severely” skewed’the absolute value of kurtosis ‘|ˆγ 1 |>3.0 are described as “severely” skewed’|“the absolute value of kurtosis ‘|ˆγ 2 |>10.0 suggests a problem’|“the absolute value of kurtosis ‘|ˆγ 2 |>10.0 suggests a problem’ (p. 77). Furthermore, to test the multivariate normal distribution, the Mahalanobis distances and the critical points of the Chi-squared distribution were examined. The number of degrees of freedom for the Chi-squared distribution is equal to the number of variables; thus, for three variables, it has three degrees of freedom. At the 0.05 significance level, the corresponding critical point of Chi-square distribution based on three degrees of freedom is 7.815; the corresponding critical point with four degrees of freedom is 9.488; the corresponding critical point with five degrees of freedom is 11.070 . If the maximal Mahalanobis distance is less than the corresponding critical points of the Chi-squared distribution, the sample data are in a multivariate normal distribution . Then, the study used MANOVA to compare multivariate sample means. In order to control the potential initial group differences, the study further used pretest results as covariates and used one-way MANCOVA to adjust the means in order to reduce any systematic bias . The confidence level was 95% ( p < 0.05). In addition, Pillai’s Trace was used to test the homogeneity of variance (the covariance matrices) and to robust Type I error , with the p -value >0.05 indicating the homogeneity of the covariance matrices . The Pearson correlation (| r |) for the variables was also used to test the multicollinearity, with the | r | < 0.9 indicating no evidence of multicollinearity .
Results Before any further parametric analysis, the researchers used Skewness and Kurtosis to examine the outliers and multivariate normality. After preliminary analysis, the researchers found no extreme Skewness values and Kurtosis values. The Skewness values were within the range of ± 2, mostly within ± 1; the Kurtosis values were within the range of ± 7. Furthermore, the maximal Mahalanobis distances are less than the corresponding critical points of the Chi-squared distribution: 7.815 for three variables, 9.488 for four variables, and 11.070 for five variables; hence it can be known that the sample data are in a multivariate normal distribution. Also, with no outliers, the data were normally distributed and hence could be used for further parametric analysis and for null hypothesis testing. 3.1. Quantitative results of hypothesis testing 3.1.1. Null Hypothesis 1 There is no difference in the awareness of professional identity between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. To test Null Hypothesis 1, For the pretest of PIS-HSP using MANOVA, the Pillai’s Trace is 1.308 ( p = 0.277 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. The pretest results also did not indicate any significant differences between the means of the experimental group (means = 82.51, 38.86, 36.23, and 32.80) and those of the control group (means = 88.69, 39.88, 37.59, and 30.72) for ‘professional commitment and devotion’ ( F (1, 65) = 0.984; p = 0.325 > 0.05), ‘emotional identification and belongingness’ ( F (1, 65) = 0.063; p = 0.803 > 0.05), ‘professional goals and values’ ( F (1, 65) = 0.465; p = .0.498 > 0.05), and ‘self-fulfillment and retention tendency’ ( F (1, 65) = 1.020; p = 0.316 > 0.05). To put it another way, these two groups were homogeneous in the awareness of professional identity. After the 16-week intervention, with the application of the pretest results as covariates, a one-way MANCOVA was applied to determine whether professional identity pretest scores would make a difference in the posttest scores. For the posttest of PIS-HSP using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.263 and 0.836 (| r | < 0.9), indicating no evidence of multicollinearity. In addition, the MANCOVA results (see ) indicated a significant relationship between the pretest scores and posttest scores in ‘professional commitment and devotion’ (Wilks’ Λ: 0.307; F (4, 58) = 32.703; p < 0.000), ‘emotional identification and belongingness’ (Wilks’ Λ: 0.768; F (4, 58) = 4.382; p < 0.01), ‘professional goals and values’ (Wilks’ Λ: 0.123; F (4, 56) = 103.424; p < 0.000), and ‘self-fulfillment and retention tendency’ (Wilks’ Λ: 0.092; F (4, 56) = 143.678; p < 0.000). Because there were significant relationships between the pretest scores and posttest scores (as in ), in order to reduce any systematic bias, the researchers had to further use one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 49.61, 43.54, and 36.99, respectively) were significantly higher than those of the control group (means = 44.93, 38.82, and 33.30, respectively) in ‘emotional identification and belongingness’ ( p < 0.05), ‘professional goals and values’ ( p < 0.000), and ‘self-fulfillment and retention tendency’ ( p < 0.000). Hence, with the p -value less than 0.05, the null hypothesis was rejected in these three subscales. Nonetheless, in ‘professional commitment and devotion,’ although the adjusted posttest mean of the experimental group was higher (mean = 98.30) than that of the control group (mean = 92.64), there was no significant difference ( p= 0.099 > 0.05) between the two groups. With the p -value larger than 0.05, the null hypothesis failed to be rejected in the subscale. 3.1.2. Null Hypothesis 2 There is no difference in reflective thinking between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. To test Null Hypothesis 2, for the pretest of RTS-HSP using MANOVA, the Pillai’s Trace is 0.246 ( p = 0.911 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the experimental group (means = 34.83, 40.11, 32.86, and 32.40, respectively) and the control group (means = 36.19, 40.41, 32.47, and 32.44, respectively) on reflective skepticism ( F (1, 65) = 0.439; p = 0.510 > 0.05), self-examination ( F (1, 65)=.021; p = 0.887 > 0.05), empathetic reflection ( F (1, 65)=.059; p = 0.809 > 0.05), and critical open-mindedness ( F (1, 65) = 0.001; p = 0.981 > 0.05). That is, these two groups were homogeneous in reflective thinking. After the intervention, with the pretest results as covariates, the researchers adopted a one-way MANCOVA to determine whether professional identity pretest scores would make a difference to the posttest scores. For the posttest of RTS-HSP using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.396 and 0.685 (| r | < 0.9), indicating no evidence of multicollinearity. The MANCOVA results (see ) indicated a significant relationship between the pretest scores and posttest scores in ‘reflective skepticism’ (Wilks’ Λ: 0.343; F (4, 58) = 27.795; p < 0.000), ‘self-examination’ (Wilks’ Λ: 0.371; F (4, 58) = 24.561; p < 0.000), ‘empathetic reflection’ (Wilks’ Λ: 0.557; F (4, 58) = 11.539; p < 0.000), and ‘critical open-mindedness’ (Wilks’ Λ: 0.525; F (4, 58) = 13.112; p < 0.000). Because of the significant relationships between the pretest scores and posttest scores (as in ), to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 44.58, 48.22, 40.05, and 38.33, respectively) were significantly higher than those of the control group (means = 41.30, 44.79, 37.44, and 34.89, respectively) in ‘reflective skepticism,’ ‘self-examination,’ ‘empathetic reflection,’ and ‘critical open-mindedness.’ Hence, the null hypothesis was rejected when the p -value was below 0.05. 3.1.3. Null Hypothesis 3 There is no difference in emotional catharsis between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. For the pretest of ECS-IN using MANOVA, the Pillai’s Trace is 0.491 ( p = 0.690 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the means of the experimental group (means = 74.66, 56.69, and 48.66, respectively) and those of the control group (means = 76.97, 59.47, and 52.03, respectively) in ‘emotional identification as self-healing’ ( F (1, 65) = 0.169; p = 0.682 > 0.05), ‘emotional release for compensation’ ( F (1, 65) = 0.509; p = 0.478 > 0.05), and ‘emotional adjustment for intellectual growth’ ( F (1,65) = 1.327; p = 0.254 > 0.05). That is, these two groups were homogeneous in emotional catharsis. After the intervention, with the pretest results as covariates, a one-way MANCOVA was used to determine whether professional identity pretest scores would make a difference to the posttest scores. For the posttest of ECS-IN using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.682 and 0.828 (| r | < 0.9), indicating no evidence of multicollinearity. The one-way MANCOVA results (see ) also indicated a significant relationship between the pretest scores and posttest scores in ‘emotional identification as self-healing’ (Wilks’ Λ: 0.326; F (3, 60) = 41.276; p < 0.000), ‘emotional release for compensation’ (Wilks’ Λ: 0.314; F (3, 60) = 43.605; p < 0.000), and ‘emotional adjustment for intellectual growth’ (Wilks’ Λ: 0.323; F (3, 60) = 41.869; p < 0.000). Due to the significant relationships between the pretest scores and posttest scores (as in ), to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 66.97 and 60.85, respectively) were significantly higher than those of the control group (means = 63.38 and 57.08, respectively) in ‘emotional release for compensation’ and ‘emotional adjustment for intellectual growth.’ Hence, with the p -value less than 0.05, the null hypothesis was rejected in these two subscales. However, in ‘emotional identification as self-healing,’ although the adjusted posttest mean of the experimental group was higher (mean = 85.70) than that of the control group (mean = 82.14), there was no significant difference ( p = 0.107 > 0.05; see ) between the two groups. When the p -value larger than 0.05, the hypothesis was not rejected in the subscale. 3.1.4. Null Hypothesis 4 There is no difference in reflective writing competency between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. For the pretest of reflective writing competency using MANOVA, the Pillai’s Trace is 0.751 ( p = 0.611 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the experimental group (means = 2.74, 2.17, 2.60, 2.31, 2.43, and 3.46, respectively) and the control group (means = 2.47, 2.16, 2.72, 2.13, 2.63, and 3.38, respectively) in ‘focus and context structure’ ( F (1, 65) = 2.500; p = 0.119 > 0.05), ‘ideas and elaboration’ ( F (1, 65) = 0.006; p = 0.941 > 0.05), ‘voices and points of view’ ( F (1, 65) = 327; p = 0.569 > 0.05), ‘critical thinking and representation’ ( F (1, 65) = 0.949; p = 0.334 > 0.05), ‘depth of reflection on personal growth’ ( F (1, 65) = 0.910; p = 0.344 > 0.05), and ‘language and conventions’ ( F (1, 65) = 0.104; p = 0.748 > 0.05). That is, these two groups were homogeneous in reflective writing competency. After the intervention, with the use of the pretest results as covariates, a one-way MANCOVA was applied to determine whether reflective writing competency pretest scores would make a difference to the posttest scores. For the posttest of reflective writing competency using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.106 and 0.527 (| r | < 0.9), indicating no evidence of multicollinearity. The one-way MANCOVA results (see ) also indicated no significant relationship between the pretest scores and posttest scores in ‘focus and context structure’ (Wilks’ Λ: 0.894; F (6, 54) = 1.064; p = 0.395 > 0.05), ‘ideas and elaboration’ (Wilks’ Λ: 0.930; F (6, 54) = 0.674; p = 0.671 > 0.05), ‘voices and points of view’ (Wilks’ Λ: 0.911; F (6, 54) = 0.877; p = 0.518 > 0.05), ‘critical thinking and representation’ (Wilks’ Λ: 0.887; F (6, 54) = 1.141; p = 0.351 > 0.05), ‘depth of reflection on personal growth’ (Wilks’ Λ: 0.855; F (6, 54) = 1.531; p = 0.186 > 0.05), and ‘language and conventions’ (Wilks’ Λ: 0.824; F (6, 54) = 1.922; p = 0.094 > 0.05). However, in the tests of between-subjects effects, the one-way MANCOVA results indicated a significant interaction between the pretest in ‘critical thinking and representation’ and the posttest in ‘ideas and elaboration’ ( F (1, 59) = 4.558; p = 0.037 < 0.05), between the pretest in ‘critical thinking and representation’ and the posttest in ‘depth of reflection on personal growth’ ( F (1, 59) = 4.537; p = 0.037 < 0.05), and between the pretest in ‘language and conventions’ and the posttest in ‘language and conventions’ ( F (1, 59) = 8.438; p = 0.005 < 0.001). Due to the significant relationship between the pretest scores and posttest scores (as shown in ), in order to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 4.20, 3.90, 4.00, 4.16, and 4.09, respectively) were higher than those of the control group (means = 3.63, 3.14,, 3.63, 3.04, and 3.06, respectively) in ‘focus and context structure,’ ‘ideas and elaboration,’ ‘voices and points of view,’ ‘critical thinking and representation,’ and ‘depth of reflection on personal growth.’ Hence, with the p -value less than 0.05, the hypothesis was rejected in these five subscales. However, in ‘language and conventions,’ although the adjusted posttest mean of the experimental group was higher (mean = 3.77) than that of the control group (mean = 3.54), there was no significant difference ( p = 0.181 > 0.05; see ) between these two groups. With the p -value larger than 0.05, the hypothesis was not rejected in the subscale. This study aimed to examine whether the intervention of narrative medicine to form an empathetic connection could result in positive effects on health professions students with regard to professional identity, self-reflection, emotional catharsis, and reflective writing competency. The findings suggest that before the intervention, both groups were homogeneous in professional identity, self-reflection, emotional catharsis, and reflective writing competency; however, after the intervention, students using narrative medicine to form an empathetic connection had stronger professional identity, a higher reflective thinking level, more emotional catharsis, and greater improvement in reflective writing competency than students not using narrative medicine. To provide a clear illustration of the results, the following table ( ) provides a summary to highlight the differences between the two groups. 3.2. Results of the interviews The results of the student interviews revealed that the students using narrative medicine to from an empathetic connection had stronger professional identity, a higher reflective thinking level, more emotional catharsis, and greater improvement in reflective writing competency than students not using narrative medicine. They enjoyed the class, saying that: Through the three stages of attention-representation-affiliation, I can have a chance to identify with those health professionals and those suffering in literature and visual art scenarios and hence somehow have an emotional identification and belonging to the health profession (F3; F15; F18; M3; M9; M12; F Female student; M Male student). I am glad for going to be a member of the health profession and have a great interest in the profession (F8; F11; F12; F 15; M2; M8; M10). I am willing to devote to my health professional knowledge so as to provide quality care for patients (F3; F8; F11; F 12; F18; M2; M3; M8). Moreover, some participants expressed that while having an emotional connection with those suffering, they could reach a state of emotional catharsis, saying that: While having an emotional connection with those suffering, I can release my negative emotions, such as sadness, grief, anger, etc. and somehow reach a mental or emotional balance in my life (F8; F11; F12; F18; M3; M9; M10; M12). Paying attention to the plots about the death of the dearest, I reach an affiliative connection with them and hence have a chance to vent the grievances I do not want to face (F3; F11; F12; M3; M8). By posting reflections on ethical/moral dilemmas and conflicts, I can safely voice my fears or those strong emotions that I feel embarrassed and afraid to express (F3; F11; F12; F15; F18; M2; M3; M8; M10). Through reading and writing these illness narratives, I am free to express my inner feelings so as to vent my emotions (F8; F11; F15; M3; M9; M12). By releasing emotions through illness narratives, I come to understand that life, death, illness, and aging are part of the human experience and attempt to cope with them (F3; F12; F15; M3; M10; M12). In addition, some students also revealed that through reading these plots regarding ethical/moral dilemmas and conflicts, they learned how to see things from different perspectives, being more reflective and introspective, saying that: I check the credibility of the source of information before deciding how to handle dilemmas and conflicts in the simulated clinical or healthcare scenarios or situations (F3; F8; F11; F18; M3; M9; M10). I try to understand an experience from others’ points of view (F8; F11; F15; F18; M2; M3; M9). I try to consider other people’s feelings from different angles (F3; F11; F12; F18; M2; M8; M10). I try to figure out, question, and test all supporting arguments and refuting arguments about the ethical/moral dilemmas and conflicts (F8; F12; F15; F18; M2; M3; M8; M10). While reflecting on the dilemmas, I try to think and explore both positive and negative thoughts (F3; F11; F5; F18; M2; M8; M9; M12). Based on the above quantitative results and qualitative interview excerpts to triangulate the quantitative results, it is shown that the narrative medicine-based intervention could bring positive effects on the health professions students. After going through the intervention, the students in the experimental group had stronger professional identity, a higher reflective thinking level, more emotional catharsis, and greater improvement in reflective writing competency than those not receiving the intervention, though some subscales not reaching statistical significance.
Quantitative results of hypothesis testing 3.1.1. Null Hypothesis 1 There is no difference in the awareness of professional identity between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. To test Null Hypothesis 1, For the pretest of PIS-HSP using MANOVA, the Pillai’s Trace is 1.308 ( p = 0.277 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. The pretest results also did not indicate any significant differences between the means of the experimental group (means = 82.51, 38.86, 36.23, and 32.80) and those of the control group (means = 88.69, 39.88, 37.59, and 30.72) for ‘professional commitment and devotion’ ( F (1, 65) = 0.984; p = 0.325 > 0.05), ‘emotional identification and belongingness’ ( F (1, 65) = 0.063; p = 0.803 > 0.05), ‘professional goals and values’ ( F (1, 65) = 0.465; p = .0.498 > 0.05), and ‘self-fulfillment and retention tendency’ ( F (1, 65) = 1.020; p = 0.316 > 0.05). To put it another way, these two groups were homogeneous in the awareness of professional identity. After the 16-week intervention, with the application of the pretest results as covariates, a one-way MANCOVA was applied to determine whether professional identity pretest scores would make a difference in the posttest scores. For the posttest of PIS-HSP using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.263 and 0.836 (| r | < 0.9), indicating no evidence of multicollinearity. In addition, the MANCOVA results (see ) indicated a significant relationship between the pretest scores and posttest scores in ‘professional commitment and devotion’ (Wilks’ Λ: 0.307; F (4, 58) = 32.703; p < 0.000), ‘emotional identification and belongingness’ (Wilks’ Λ: 0.768; F (4, 58) = 4.382; p < 0.01), ‘professional goals and values’ (Wilks’ Λ: 0.123; F (4, 56) = 103.424; p < 0.000), and ‘self-fulfillment and retention tendency’ (Wilks’ Λ: 0.092; F (4, 56) = 143.678; p < 0.000). Because there were significant relationships between the pretest scores and posttest scores (as in ), in order to reduce any systematic bias, the researchers had to further use one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 49.61, 43.54, and 36.99, respectively) were significantly higher than those of the control group (means = 44.93, 38.82, and 33.30, respectively) in ‘emotional identification and belongingness’ ( p < 0.05), ‘professional goals and values’ ( p < 0.000), and ‘self-fulfillment and retention tendency’ ( p < 0.000). Hence, with the p -value less than 0.05, the null hypothesis was rejected in these three subscales. Nonetheless, in ‘professional commitment and devotion,’ although the adjusted posttest mean of the experimental group was higher (mean = 98.30) than that of the control group (mean = 92.64), there was no significant difference ( p= 0.099 > 0.05) between the two groups. With the p -value larger than 0.05, the null hypothesis failed to be rejected in the subscale. 3.1.2. Null Hypothesis 2 There is no difference in reflective thinking between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. To test Null Hypothesis 2, for the pretest of RTS-HSP using MANOVA, the Pillai’s Trace is 0.246 ( p = 0.911 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the experimental group (means = 34.83, 40.11, 32.86, and 32.40, respectively) and the control group (means = 36.19, 40.41, 32.47, and 32.44, respectively) on reflective skepticism ( F (1, 65) = 0.439; p = 0.510 > 0.05), self-examination ( F (1, 65)=.021; p = 0.887 > 0.05), empathetic reflection ( F (1, 65)=.059; p = 0.809 > 0.05), and critical open-mindedness ( F (1, 65) = 0.001; p = 0.981 > 0.05). That is, these two groups were homogeneous in reflective thinking. After the intervention, with the pretest results as covariates, the researchers adopted a one-way MANCOVA to determine whether professional identity pretest scores would make a difference to the posttest scores. For the posttest of RTS-HSP using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.396 and 0.685 (| r | < 0.9), indicating no evidence of multicollinearity. The MANCOVA results (see ) indicated a significant relationship between the pretest scores and posttest scores in ‘reflective skepticism’ (Wilks’ Λ: 0.343; F (4, 58) = 27.795; p < 0.000), ‘self-examination’ (Wilks’ Λ: 0.371; F (4, 58) = 24.561; p < 0.000), ‘empathetic reflection’ (Wilks’ Λ: 0.557; F (4, 58) = 11.539; p < 0.000), and ‘critical open-mindedness’ (Wilks’ Λ: 0.525; F (4, 58) = 13.112; p < 0.000). Because of the significant relationships between the pretest scores and posttest scores (as in ), to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 44.58, 48.22, 40.05, and 38.33, respectively) were significantly higher than those of the control group (means = 41.30, 44.79, 37.44, and 34.89, respectively) in ‘reflective skepticism,’ ‘self-examination,’ ‘empathetic reflection,’ and ‘critical open-mindedness.’ Hence, the null hypothesis was rejected when the p -value was below 0.05. 3.1.3. Null Hypothesis 3 There is no difference in emotional catharsis between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. For the pretest of ECS-IN using MANOVA, the Pillai’s Trace is 0.491 ( p = 0.690 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the means of the experimental group (means = 74.66, 56.69, and 48.66, respectively) and those of the control group (means = 76.97, 59.47, and 52.03, respectively) in ‘emotional identification as self-healing’ ( F (1, 65) = 0.169; p = 0.682 > 0.05), ‘emotional release for compensation’ ( F (1, 65) = 0.509; p = 0.478 > 0.05), and ‘emotional adjustment for intellectual growth’ ( F (1,65) = 1.327; p = 0.254 > 0.05). That is, these two groups were homogeneous in emotional catharsis. After the intervention, with the pretest results as covariates, a one-way MANCOVA was used to determine whether professional identity pretest scores would make a difference to the posttest scores. For the posttest of ECS-IN using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.682 and 0.828 (| r | < 0.9), indicating no evidence of multicollinearity. The one-way MANCOVA results (see ) also indicated a significant relationship between the pretest scores and posttest scores in ‘emotional identification as self-healing’ (Wilks’ Λ: 0.326; F (3, 60) = 41.276; p < 0.000), ‘emotional release for compensation’ (Wilks’ Λ: 0.314; F (3, 60) = 43.605; p < 0.000), and ‘emotional adjustment for intellectual growth’ (Wilks’ Λ: 0.323; F (3, 60) = 41.869; p < 0.000). Due to the significant relationships between the pretest scores and posttest scores (as in ), to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 66.97 and 60.85, respectively) were significantly higher than those of the control group (means = 63.38 and 57.08, respectively) in ‘emotional release for compensation’ and ‘emotional adjustment for intellectual growth.’ Hence, with the p -value less than 0.05, the null hypothesis was rejected in these two subscales. However, in ‘emotional identification as self-healing,’ although the adjusted posttest mean of the experimental group was higher (mean = 85.70) than that of the control group (mean = 82.14), there was no significant difference ( p = 0.107 > 0.05; see ) between the two groups. When the p -value larger than 0.05, the hypothesis was not rejected in the subscale. 3.1.4. Null Hypothesis 4 There is no difference in reflective writing competency between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. For the pretest of reflective writing competency using MANOVA, the Pillai’s Trace is 0.751 ( p = 0.611 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the experimental group (means = 2.74, 2.17, 2.60, 2.31, 2.43, and 3.46, respectively) and the control group (means = 2.47, 2.16, 2.72, 2.13, 2.63, and 3.38, respectively) in ‘focus and context structure’ ( F (1, 65) = 2.500; p = 0.119 > 0.05), ‘ideas and elaboration’ ( F (1, 65) = 0.006; p = 0.941 > 0.05), ‘voices and points of view’ ( F (1, 65) = 327; p = 0.569 > 0.05), ‘critical thinking and representation’ ( F (1, 65) = 0.949; p = 0.334 > 0.05), ‘depth of reflection on personal growth’ ( F (1, 65) = 0.910; p = 0.344 > 0.05), and ‘language and conventions’ ( F (1, 65) = 0.104; p = 0.748 > 0.05). That is, these two groups were homogeneous in reflective writing competency. After the intervention, with the use of the pretest results as covariates, a one-way MANCOVA was applied to determine whether reflective writing competency pretest scores would make a difference to the posttest scores. For the posttest of reflective writing competency using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.106 and 0.527 (| r | < 0.9), indicating no evidence of multicollinearity. The one-way MANCOVA results (see ) also indicated no significant relationship between the pretest scores and posttest scores in ‘focus and context structure’ (Wilks’ Λ: 0.894; F (6, 54) = 1.064; p = 0.395 > 0.05), ‘ideas and elaboration’ (Wilks’ Λ: 0.930; F (6, 54) = 0.674; p = 0.671 > 0.05), ‘voices and points of view’ (Wilks’ Λ: 0.911; F (6, 54) = 0.877; p = 0.518 > 0.05), ‘critical thinking and representation’ (Wilks’ Λ: 0.887; F (6, 54) = 1.141; p = 0.351 > 0.05), ‘depth of reflection on personal growth’ (Wilks’ Λ: 0.855; F (6, 54) = 1.531; p = 0.186 > 0.05), and ‘language and conventions’ (Wilks’ Λ: 0.824; F (6, 54) = 1.922; p = 0.094 > 0.05). However, in the tests of between-subjects effects, the one-way MANCOVA results indicated a significant interaction between the pretest in ‘critical thinking and representation’ and the posttest in ‘ideas and elaboration’ ( F (1, 59) = 4.558; p = 0.037 < 0.05), between the pretest in ‘critical thinking and representation’ and the posttest in ‘depth of reflection on personal growth’ ( F (1, 59) = 4.537; p = 0.037 < 0.05), and between the pretest in ‘language and conventions’ and the posttest in ‘language and conventions’ ( F (1, 59) = 8.438; p = 0.005 < 0.001). Due to the significant relationship between the pretest scores and posttest scores (as shown in ), in order to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 4.20, 3.90, 4.00, 4.16, and 4.09, respectively) were higher than those of the control group (means = 3.63, 3.14,, 3.63, 3.04, and 3.06, respectively) in ‘focus and context structure,’ ‘ideas and elaboration,’ ‘voices and points of view,’ ‘critical thinking and representation,’ and ‘depth of reflection on personal growth.’ Hence, with the p -value less than 0.05, the hypothesis was rejected in these five subscales. However, in ‘language and conventions,’ although the adjusted posttest mean of the experimental group was higher (mean = 3.77) than that of the control group (mean = 3.54), there was no significant difference ( p = 0.181 > 0.05; see ) between these two groups. With the p -value larger than 0.05, the hypothesis was not rejected in the subscale. This study aimed to examine whether the intervention of narrative medicine to form an empathetic connection could result in positive effects on health professions students with regard to professional identity, self-reflection, emotional catharsis, and reflective writing competency. The findings suggest that before the intervention, both groups were homogeneous in professional identity, self-reflection, emotional catharsis, and reflective writing competency; however, after the intervention, students using narrative medicine to form an empathetic connection had stronger professional identity, a higher reflective thinking level, more emotional catharsis, and greater improvement in reflective writing competency than students not using narrative medicine. To provide a clear illustration of the results, the following table ( ) provides a summary to highlight the differences between the two groups.
Null Hypothesis 1 There is no difference in the awareness of professional identity between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. To test Null Hypothesis 1, For the pretest of PIS-HSP using MANOVA, the Pillai’s Trace is 1.308 ( p = 0.277 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. The pretest results also did not indicate any significant differences between the means of the experimental group (means = 82.51, 38.86, 36.23, and 32.80) and those of the control group (means = 88.69, 39.88, 37.59, and 30.72) for ‘professional commitment and devotion’ ( F (1, 65) = 0.984; p = 0.325 > 0.05), ‘emotional identification and belongingness’ ( F (1, 65) = 0.063; p = 0.803 > 0.05), ‘professional goals and values’ ( F (1, 65) = 0.465; p = .0.498 > 0.05), and ‘self-fulfillment and retention tendency’ ( F (1, 65) = 1.020; p = 0.316 > 0.05). To put it another way, these two groups were homogeneous in the awareness of professional identity. After the 16-week intervention, with the application of the pretest results as covariates, a one-way MANCOVA was applied to determine whether professional identity pretest scores would make a difference in the posttest scores. For the posttest of PIS-HSP using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.263 and 0.836 (| r | < 0.9), indicating no evidence of multicollinearity. In addition, the MANCOVA results (see ) indicated a significant relationship between the pretest scores and posttest scores in ‘professional commitment and devotion’ (Wilks’ Λ: 0.307; F (4, 58) = 32.703; p < 0.000), ‘emotional identification and belongingness’ (Wilks’ Λ: 0.768; F (4, 58) = 4.382; p < 0.01), ‘professional goals and values’ (Wilks’ Λ: 0.123; F (4, 56) = 103.424; p < 0.000), and ‘self-fulfillment and retention tendency’ (Wilks’ Λ: 0.092; F (4, 56) = 143.678; p < 0.000). Because there were significant relationships between the pretest scores and posttest scores (as in ), in order to reduce any systematic bias, the researchers had to further use one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 49.61, 43.54, and 36.99, respectively) were significantly higher than those of the control group (means = 44.93, 38.82, and 33.30, respectively) in ‘emotional identification and belongingness’ ( p < 0.05), ‘professional goals and values’ ( p < 0.000), and ‘self-fulfillment and retention tendency’ ( p < 0.000). Hence, with the p -value less than 0.05, the null hypothesis was rejected in these three subscales. Nonetheless, in ‘professional commitment and devotion,’ although the adjusted posttest mean of the experimental group was higher (mean = 98.30) than that of the control group (mean = 92.64), there was no significant difference ( p= 0.099 > 0.05) between the two groups. With the p -value larger than 0.05, the null hypothesis failed to be rejected in the subscale.
Null Hypothesis 2 There is no difference in reflective thinking between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. To test Null Hypothesis 2, for the pretest of RTS-HSP using MANOVA, the Pillai’s Trace is 0.246 ( p = 0.911 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the experimental group (means = 34.83, 40.11, 32.86, and 32.40, respectively) and the control group (means = 36.19, 40.41, 32.47, and 32.44, respectively) on reflective skepticism ( F (1, 65) = 0.439; p = 0.510 > 0.05), self-examination ( F (1, 65)=.021; p = 0.887 > 0.05), empathetic reflection ( F (1, 65)=.059; p = 0.809 > 0.05), and critical open-mindedness ( F (1, 65) = 0.001; p = 0.981 > 0.05). That is, these two groups were homogeneous in reflective thinking. After the intervention, with the pretest results as covariates, the researchers adopted a one-way MANCOVA to determine whether professional identity pretest scores would make a difference to the posttest scores. For the posttest of RTS-HSP using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.396 and 0.685 (| r | < 0.9), indicating no evidence of multicollinearity. The MANCOVA results (see ) indicated a significant relationship between the pretest scores and posttest scores in ‘reflective skepticism’ (Wilks’ Λ: 0.343; F (4, 58) = 27.795; p < 0.000), ‘self-examination’ (Wilks’ Λ: 0.371; F (4, 58) = 24.561; p < 0.000), ‘empathetic reflection’ (Wilks’ Λ: 0.557; F (4, 58) = 11.539; p < 0.000), and ‘critical open-mindedness’ (Wilks’ Λ: 0.525; F (4, 58) = 13.112; p < 0.000). Because of the significant relationships between the pretest scores and posttest scores (as in ), to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 44.58, 48.22, 40.05, and 38.33, respectively) were significantly higher than those of the control group (means = 41.30, 44.79, 37.44, and 34.89, respectively) in ‘reflective skepticism,’ ‘self-examination,’ ‘empathetic reflection,’ and ‘critical open-mindedness.’ Hence, the null hypothesis was rejected when the p -value was below 0.05.
Null Hypothesis 3 There is no difference in emotional catharsis between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. For the pretest of ECS-IN using MANOVA, the Pillai’s Trace is 0.491 ( p = 0.690 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the means of the experimental group (means = 74.66, 56.69, and 48.66, respectively) and those of the control group (means = 76.97, 59.47, and 52.03, respectively) in ‘emotional identification as self-healing’ ( F (1, 65) = 0.169; p = 0.682 > 0.05), ‘emotional release for compensation’ ( F (1, 65) = 0.509; p = 0.478 > 0.05), and ‘emotional adjustment for intellectual growth’ ( F (1,65) = 1.327; p = 0.254 > 0.05). That is, these two groups were homogeneous in emotional catharsis. After the intervention, with the pretest results as covariates, a one-way MANCOVA was used to determine whether professional identity pretest scores would make a difference to the posttest scores. For the posttest of ECS-IN using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.682 and 0.828 (| r | < 0.9), indicating no evidence of multicollinearity. The one-way MANCOVA results (see ) also indicated a significant relationship between the pretest scores and posttest scores in ‘emotional identification as self-healing’ (Wilks’ Λ: 0.326; F (3, 60) = 41.276; p < 0.000), ‘emotional release for compensation’ (Wilks’ Λ: 0.314; F (3, 60) = 43.605; p < 0.000), and ‘emotional adjustment for intellectual growth’ (Wilks’ Λ: 0.323; F (3, 60) = 41.869; p < 0.000). Due to the significant relationships between the pretest scores and posttest scores (as in ), to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 66.97 and 60.85, respectively) were significantly higher than those of the control group (means = 63.38 and 57.08, respectively) in ‘emotional release for compensation’ and ‘emotional adjustment for intellectual growth.’ Hence, with the p -value less than 0.05, the null hypothesis was rejected in these two subscales. However, in ‘emotional identification as self-healing,’ although the adjusted posttest mean of the experimental group was higher (mean = 85.70) than that of the control group (mean = 82.14), there was no significant difference ( p = 0.107 > 0.05; see ) between the two groups. When the p -value larger than 0.05, the hypothesis was not rejected in the subscale.
Null Hypothesis 4 There is no difference in reflective writing competency between the health professions students using narrative medicine to form an empathetic connection and those not using narrative medicine. For the pretest of reflective writing competency using MANOVA, the Pillai’s Trace is 0.751 ( p = 0.611 > 0.05), indicating the equal variance and homogeneity of the covariance matrices. There were also no significant differences in the pre-test results between the experimental group (means = 2.74, 2.17, 2.60, 2.31, 2.43, and 3.46, respectively) and the control group (means = 2.47, 2.16, 2.72, 2.13, 2.63, and 3.38, respectively) in ‘focus and context structure’ ( F (1, 65) = 2.500; p = 0.119 > 0.05), ‘ideas and elaboration’ ( F (1, 65) = 0.006; p = 0.941 > 0.05), ‘voices and points of view’ ( F (1, 65) = 327; p = 0.569 > 0.05), ‘critical thinking and representation’ ( F (1, 65) = 0.949; p = 0.334 > 0.05), ‘depth of reflection on personal growth’ ( F (1, 65) = 0.910; p = 0.344 > 0.05), and ‘language and conventions’ ( F (1, 65) = 0.104; p = 0.748 > 0.05). That is, these two groups were homogeneous in reflective writing competency. After the intervention, with the use of the pretest results as covariates, a one-way MANCOVA was applied to determine whether reflective writing competency pretest scores would make a difference to the posttest scores. For the posttest of reflective writing competency using MANCOVA, the Pearson correlation (| r |) values for the factors were between 0.106 and 0.527 (| r | < 0.9), indicating no evidence of multicollinearity. The one-way MANCOVA results (see ) also indicated no significant relationship between the pretest scores and posttest scores in ‘focus and context structure’ (Wilks’ Λ: 0.894; F (6, 54) = 1.064; p = 0.395 > 0.05), ‘ideas and elaboration’ (Wilks’ Λ: 0.930; F (6, 54) = 0.674; p = 0.671 > 0.05), ‘voices and points of view’ (Wilks’ Λ: 0.911; F (6, 54) = 0.877; p = 0.518 > 0.05), ‘critical thinking and representation’ (Wilks’ Λ: 0.887; F (6, 54) = 1.141; p = 0.351 > 0.05), ‘depth of reflection on personal growth’ (Wilks’ Λ: 0.855; F (6, 54) = 1.531; p = 0.186 > 0.05), and ‘language and conventions’ (Wilks’ Λ: 0.824; F (6, 54) = 1.922; p = 0.094 > 0.05). However, in the tests of between-subjects effects, the one-way MANCOVA results indicated a significant interaction between the pretest in ‘critical thinking and representation’ and the posttest in ‘ideas and elaboration’ ( F (1, 59) = 4.558; p = 0.037 < 0.05), between the pretest in ‘critical thinking and representation’ and the posttest in ‘depth of reflection on personal growth’ ( F (1, 59) = 4.537; p = 0.037 < 0.05), and between the pretest in ‘language and conventions’ and the posttest in ‘language and conventions’ ( F (1, 59) = 8.438; p = 0.005 < 0.001). Due to the significant relationship between the pretest scores and posttest scores (as shown in ), in order to reduce any systematic bias, the researchers further used one-way MANCOVA to adjust the means . After adjustment, the MANCOVA results (as in ) showed that the adjusted posttest means of the experimental group (means = 4.20, 3.90, 4.00, 4.16, and 4.09, respectively) were higher than those of the control group (means = 3.63, 3.14,, 3.63, 3.04, and 3.06, respectively) in ‘focus and context structure,’ ‘ideas and elaboration,’ ‘voices and points of view,’ ‘critical thinking and representation,’ and ‘depth of reflection on personal growth.’ Hence, with the p -value less than 0.05, the hypothesis was rejected in these five subscales. However, in ‘language and conventions,’ although the adjusted posttest mean of the experimental group was higher (mean = 3.77) than that of the control group (mean = 3.54), there was no significant difference ( p = 0.181 > 0.05; see ) between these two groups. With the p -value larger than 0.05, the hypothesis was not rejected in the subscale. This study aimed to examine whether the intervention of narrative medicine to form an empathetic connection could result in positive effects on health professions students with regard to professional identity, self-reflection, emotional catharsis, and reflective writing competency. The findings suggest that before the intervention, both groups were homogeneous in professional identity, self-reflection, emotional catharsis, and reflective writing competency; however, after the intervention, students using narrative medicine to form an empathetic connection had stronger professional identity, a higher reflective thinking level, more emotional catharsis, and greater improvement in reflective writing competency than students not using narrative medicine. To provide a clear illustration of the results, the following table ( ) provides a summary to highlight the differences between the two groups.
Results of the interviews The results of the student interviews revealed that the students using narrative medicine to from an empathetic connection had stronger professional identity, a higher reflective thinking level, more emotional catharsis, and greater improvement in reflective writing competency than students not using narrative medicine. They enjoyed the class, saying that: Through the three stages of attention-representation-affiliation, I can have a chance to identify with those health professionals and those suffering in literature and visual art scenarios and hence somehow have an emotional identification and belonging to the health profession (F3; F15; F18; M3; M9; M12; F Female student; M Male student). I am glad for going to be a member of the health profession and have a great interest in the profession (F8; F11; F12; F 15; M2; M8; M10). I am willing to devote to my health professional knowledge so as to provide quality care for patients (F3; F8; F11; F 12; F18; M2; M3; M8). Moreover, some participants expressed that while having an emotional connection with those suffering, they could reach a state of emotional catharsis, saying that: While having an emotional connection with those suffering, I can release my negative emotions, such as sadness, grief, anger, etc. and somehow reach a mental or emotional balance in my life (F8; F11; F12; F18; M3; M9; M10; M12). Paying attention to the plots about the death of the dearest, I reach an affiliative connection with them and hence have a chance to vent the grievances I do not want to face (F3; F11; F12; M3; M8). By posting reflections on ethical/moral dilemmas and conflicts, I can safely voice my fears or those strong emotions that I feel embarrassed and afraid to express (F3; F11; F12; F15; F18; M2; M3; M8; M10). Through reading and writing these illness narratives, I am free to express my inner feelings so as to vent my emotions (F8; F11; F15; M3; M9; M12). By releasing emotions through illness narratives, I come to understand that life, death, illness, and aging are part of the human experience and attempt to cope with them (F3; F12; F15; M3; M10; M12). In addition, some students also revealed that through reading these plots regarding ethical/moral dilemmas and conflicts, they learned how to see things from different perspectives, being more reflective and introspective, saying that: I check the credibility of the source of information before deciding how to handle dilemmas and conflicts in the simulated clinical or healthcare scenarios or situations (F3; F8; F11; F18; M3; M9; M10). I try to understand an experience from others’ points of view (F8; F11; F15; F18; M2; M3; M9). I try to consider other people’s feelings from different angles (F3; F11; F12; F18; M2; M8; M10). I try to figure out, question, and test all supporting arguments and refuting arguments about the ethical/moral dilemmas and conflicts (F8; F12; F15; F18; M2; M3; M8; M10). While reflecting on the dilemmas, I try to think and explore both positive and negative thoughts (F3; F11; F5; F18; M2; M8; M9; M12). Based on the above quantitative results and qualitative interview excerpts to triangulate the quantitative results, it is shown that the narrative medicine-based intervention could bring positive effects on the health professions students. After going through the intervention, the students in the experimental group had stronger professional identity, a higher reflective thinking level, more emotional catharsis, and greater improvement in reflective writing competency than those not receiving the intervention, though some subscales not reaching statistical significance.
Discussion The quantitative results revealed that, in professional identity, there were significant differences in ‘emotional identification and belongingness,’ ‘professional goals and values,’ and ‘self-fulfillment and retention tendency.’ The results revealed that those receiving narrative medicine to form an empathetic connection had the opportunity to observe and reflect over narrative medicine in simulated clinical/healthcare scenarios or situations. Moreover, while interacting with peers or instructors and sharing their opinions or reflections upon the clinical and healthcare issues, having an empathetic connection with others, they could begin to see things not only from certain medical or healthcare group but also from the perspective of an interprofessional community of health professionals. Hence, while taking a step toward realizing their interprofessional goals, values, and identities, in order to facilitate interprofessional collaboration , they would have a stronger collective professional identity for the health profession, with a set of values, goals, attitudes, and skills shared with others within the health profession community. The results are consistent with Monrouxe’s study, suggesting that, narrative medicine can help students have a chance to reflect their professional identities and hence form the ability to develop a sound professional identity for practical purposes. The results also correspond with Miller et al’s study, revealing that the art and humanities training via narrative medicine interventions can help health professions students facilitate their professional identity development . Because the participants had received some service-learning education and training and had some experience to interact with patients, patient families, and professionals, while narrating clinical or healthcare experiences in their service-learning practice or in the literature and visual art scenarios, they can use narrative medicine as a tool to negotiate with and make sense of events around them, such as patient suffering, illness experiences, and professional goals, which would all lead to an impact upon their development of a strong professional identity . In addition, the results also correspond with Beck’s, Cooren’s, and Feldman’s studies , revealing that personal narratives, as well as collective narratives, can help people understand themselves, deal with high emotions, and act reflectively to help develop their own innate and genuine identity. However, there was no significant difference in ‘professional commitment and devotion.’ It could be possible that, because ‘commitment’ refers to one’s emotional connection to an organization and one’s feeling of bearing an obligation to the organization , these students, despite having acquired medical and health care knowledge at school, along with service-learning education and training in the school, have not yet had much chance to assimilate their knowledge and skills with professional training; hence, they have not yet had a chance to connect or commit to an organization. Regarding self-reflection, the students receiving narrative medicine to form an empathetic connection had significantly higher scores in ‘reflective skepticism,’ ‘self-examination,’ ‘empathetic reflection,’ and ‘critical open-mindedness.’ The study corresponds with Dasgupta and Charon’s study on narrative medicine , demonstrating that empathy can bring in a positive impact on self-reflection. The findings also correspond with Karkabi et al.’s, Miller’s et al.’s, and Savitha et al.’s [ , , ] research in that narrative medicine can facilitate self-reflection in health professions education because these illness narratives as narrative medicine can function as reflective narratives to examine ethical/moral challenges, conflicts, or dilemmas in clinical or healthcare scenarios. Moreover, as Liu et al., Jasper, and Savitha et al. suggest, while serving as reflective narratives, narrative medicine can help the narrators to put themselves in someone else’s shoes, and while appreciating diverse perspectives, they can be more open-minded and have insight into those suffering. In addition, while being more empathetically and critically reflective about those suffering, they would shield themselves from unexamined judgments; instead, with sensitivity and sharp observation, illness narrators, through reflection, can resolve personal conflicts, dilemmas, ambivalences, or even discrepancies to facilitate empathetic interactions with patients, thereby developing a more positive relationship between patients and health professionals. Regarding emotional catharsis, there were significant differences in ‘emotional release for compensation’ and ‘emotional adjustment for intellectual growth,’ but not in ‘emotional identification as self-healing.’ The results correspond with Ullrich and Lutgendorf’s and Tsey’s research, which mentioned that narrative journaling and writing, with the use of reflectivity, can lead to an emotional catharsis, as one pours out negative feelings of powerlessness and hence facilitates well-being. Namely, health professions students can use narratives as a channel to manage their ethical/moral conflicts and ambivalent or negative feelings. Moreover, while scrutinizing these conflicts, ambivalences, or negative feelings happening in clinical scenarios, they can construct them into a meaningful storyline, which further validates and confirms their professional identity. Moreover, while reflecting on the narrative medicine, professionals can review mistakes or crucial problems in these clinical cases; they can also reflect on these mistakes or problems and formulate strategies in advance to address these mistakes or problems. As Benigh, Duke et al., and Karkahi et al. [ , , ] suggest, while critically reflecting upon these clinical or healthcare cases or incidents to bring cognitive and affective meaning to the illness narratives, participants may gain insight into the conflicts, ambivalences, and dilemmas in these critical cases and incidents and make sense of them. Therefore, through these illness narratives as narrative medicine, they can free themselves, change their attitudes, find balance, and further reach intellectual growth and improvement . However, although DeSalvo’s study shows that narrative medicine can become ‘healing narratives’ to heal those narrating from trauma, the experimental results showed that experimental group students did not have significantly higher scores in ‘emotional identification as self-healing.’ Nevertheless, their scores were higher than their counterparts’. The reason why experimental group students did not reach a significant difference in ‘emotional identification as self-healing’ could be because the subjects participating in the study were still students, with little clinical or prior healthcare experience in professional practice , not to mention access to acute patients or terminally ill patients. With no or few illness narratives as narrative medicine to reflect upon, they did not have the opportunity to connect their feelings to patients’ suffering or ailments in clinical cases or incidents to bring about insights and reflections. Therefore, it became difficult for them to emotionally identify with those suffering and reach self-healing. As for reflective writing competency, the students receiving narrative medicine to form an empathetic connection received significantly higher scores in ‘focus and context structure,’ ‘ideas and elaboration,’ ‘voices and points of view,’ ‘critical thinking and representation,’ and ‘depth of reflection on personal growth,’ but not in ‘language and conventions.’ As mentioned previously, while using narrative medicine as a means of reflective narratives, students can empathize with others, appreciate different perspectives, and become more open and gain a deeper understanding of those who suffer emotionally and physically . The results revealed that those using narrative medicine demonstrated an insightful understanding of the reflective theme. They could perceive and analyze a specific event or experience in depth, while taking diverse perspectives into consideration. The results correspond with Kea et al.’s research, mentioning that while being engaged in reflective writing, students could achieve self-analysis and reflective thinking. Moreover, through using reflective writing regarding narrative medicine, students can gain access to a diverse perspective, leading them to develop critical thinking abilities, with supporting arguments and counterarguments being thoroughly considered. The results also consistent with Karkahi et al.’s and DasGupta and Charon’s studies , stating that the practice of narrative medicine can increase the depth of reflection and the achievement of personal growth because the practice requires that participants reflect upon daily clinical experiences from their perspectives as healthcare professionals or from the perspectives of others, such as patients, patient families, or even those passing away. While sharing narrative medicine with each other, participants are able to hear different voices and consider multiple perspectives; by critically analyzing these perspectives, they can experience personal growth. However, though those receiving narrative medicine to form an empathetic connection had a higher score in the competence of ‘language and conventions,’ these two groups did not differ significantly in the competence, which involves the ability to use language conventions appropriately for written communication, such as spelling, grammar, punctuation, word choice, and sentence structure. The reason for not reaching a statistical significance could be possible that the competence of ‘language and conventions’ is an essential competence in the development of written comprehension . Both the experimental and control groups, as medical university students, had already required basic language rules and grammatical structure ; therefore, they had at least basic competency, such as choosing appropriate words or correct grammatical structures, to facilitate their reflective writing. Overall, the research findings suggest that the use of narrative medicine is worth recommending to form an empathetic connection. By using narrative skills and the three stages of narrative medicine (attention → representation → affiliation) to form an empathetic connection, students can have more opportunities to mimetically experience the life of patients and those suffering, as well as health professionals. Moreover, they can also develop a better understanding of the difficult situations, conflicts, and dilemmas that people suffer from. Therefore, they can construct their professional identities, enhance their self-reflection, and reach an emotional catharsis.
Conclusion This study demonstrated that the use of narrative medicine to form an empathetic connection could lead to positive learning outcomes for health professions students regarding professional identity, self-reflection, emotional catharsis, and self-reflective writing competency. This research results proved that the use of narrative medicine to form an empathetic connection could bring positive impacts on health professions students because it let these students have opportunities to mimetically experience the lives of patients, patient families, and healthcare professionals, hence gaining a better understanding of the difficult situations, conflicts, and dilemmas that they may suffer from. With the practice of narrative medicine, students could successfully release their emotional stress, find meaning in their lives, and build their professional identity. However, there may be some limitations in the study. First, the study adopted a quasi-experimental design because random assignment of participants was impossible. Second, the study was in a single-blind study; only the participants were blinded, not knowing whether they were in the experimental group or control group. Even though the experimenters had two well-trained blind research assistants code and assess students’ pretest and posttest results, the experimenters knew which study group the participants were in. In addition, although the intervention plays a big role in the lack of listening and empathy in health professions students or professionals, for those experiencing empathy burnout or compassion fatigue, they may lose the patience or willingness in attentive listening and empathy. Additionally, these participants were health professions students majoring in health or medicine adjacent fields, not graduate-level healthcare students or current healthcare workers. Therefore, any researcher wanting to use the results of the study should carefully examine the study context and the similarity of the participants. Future research may examine the feasibility of using narrative medicine to reduce health providers’ empathy burnout or compassion fatigue and preserve their empathy toward their patients.
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Mitigating overuse of antinuclear antibody (ANA) testing through educational intervention: a study in internal medicine and neurology departments | 2d4e7ac6-7eb2-461a-b1eb-fcdbd4b45568 | 11582184 | Internal Medicine[mh] | Antinuclear antibodies (ANAs) directed against a variety of nuclear antigens have been detected in the serum of patients with systemic autoimmune rheumatic diseases and are an important diagnostic marker for patients with systemic lupus erythematosus (SLE) and other ANA-related autoimmune diseases, such as systemic sclerosis, inflammatory myopathies, mixed connective tissue disease, and Sjögren syndrome . However, these antibodies may be detected in the serum of patients with nonrheumatic diseases, as well as in patients with no definable clinical syndrome . Among healthy people, 25–30% are reported to have positive ANA tests at a titer of 1:40, 10–15% at 1:80, and 5% at 1:160 or greater. This frequency increases with age, particularly in women . The interpretation of the ANA test results depends on the pre-test probability of the disease . Inappropriate testing leads to increased healthcare costs and laboratory workload, as well as increased numbers of false-positive results, causing incorrect diagnoses, unnecessary patient anxiety, redundant rheumatology referrals, and even inappropriate treatments . In recent years, eliminating unnecessary medical care has received increasing attention from healthcare systems. Choosing Wisely is a campaign that started in the USA and expanded internationally to decrease unnecessary care by focusing on the value of care and potential risks to patients . As part of the Choosing Wisely campaign, the American College of Rheumatology published a list of five things that physicians and patients should question. The first item on this list is “Do not test for antinuclear antibody (ANA) sub-serologies without a positive ANA and clinical suspicion of immune-mediated disease” . This was adopted in the Choosing Wisely campaign in other countries like Canada, which recommended “Don't order anti-nuclear antibodies (ANA) as a screening test in patients without specific signs or symptoms of systemic lupus erythematosus (SLE) or another connective tissue disease (CTD)” . A study in Alberta, Canada, found that although more than 80% of rheumatologists adhere to these recommendations, 1 in 65 citizens have their ANA tested yearly, ordered mainly by non-specialists . We conducted a quality improvement educational intervention based on the Model for Improvement developed by Associates in Process Improvement . It was intended to reduce physicians’ overuse of ANA testing in internal medicine and neurology departments in an academic medical center. Study design and participants A quality improvement education intervention was conducted at Meir Medical Center, affiliated with Tel Aviv University. It was intended to educate staff about the appropriateness of ANA testing and reduce the overuse of ANA tests in five Internal Medicine and one Neurology departments. Meir Medical Center in Kfar Saba, Israel, has approximately 800 beds. Some of the departments focus on specific patient illnesses. For example, department C has a hepatology orientation; department E, rheumatology; and department A, hematology. Additionally, the neurology department, which routinely orders ANA tests for hospitalized patients presenting with conditions such as suspected vasculitis, stroke in young individuals, and suspected neuropathy, among others, was included. The study spanned a pre-intervention and a post-intervention period, each lasting 6 months. Educational intervention The quality improvement educational intervention took place in December 2021. It was structured as a 30-min group session with various personnel from the departments participating, including 2-3 senior hospitalists specializing in internal medicine, 7-8 residents, and the department head. The same educational intervention was presented individually in all six participating departments. Led by a certified rheumatologist (OTS), with additional support from other certified rheumatologists (YPB, SK), these sessions provided physicians with comprehensive insights into ANA testing. The content covered explanations of laboratory procedures, guidance on appropriate circumstances for requesting ANA testing in routine clinical settings, and the application of Choosing Wisely guidelines for the test (for presentation, see supplementary). During the session, it was highlighted that the ANA test has low specificity and should not be used as a screening test in patients without specific signs or symptoms of SLE or other connective tissue diseases. Additionally, it was noted that when the ANA test is used in cases with a low predictive probability of ANA-associated diseases based on clinical manifestations, there are more false-positive results, leading to overdiagnosis and overtreatment. At the end of the structured presentation, department-specific information was communicated, including insights into their ANA test utilization, presentation of outcome metrics, and relevant comparative data with other participating departments. Past clinical cases involving ANA testing were discussed with the staff of each department. Each department was requested to continue discussing this issue during the next morning’s meetings. Additionally, they were asked to introduce the intervention session to staff members who were absent due to night duty or vacation. The issue continued to be discussed during rheumatology consultations in the departments. ANA testing and positivity All ANA testing was done in the Biochemical Laboratory at Meir Medical Center. ANA testing was done using the indirect immunofluorescence method on HeP-2 cells, according to international guidelines . A positive result was defined as a titer of 1:160 or higher. Outcome measures Outcome measures were the ANA/new patient ratio (APR) to assess the number of ANA tests ordered, and the percentage of positive ANA tests was used to evaluate the appropriateness of patient selection; both were measured 6 months pre-intervention and 6 months post-intervention. The percentage of repeat ANA tests was measured in the internal medicine and the neurology departments 1-year pre-intervention and 1-year post-intervention. Data sources Laboratory databases from Meir Medical Center were used to retrieve ANA data. These included the number of ANA tests performed, test results, and test dates. Information on the number of new patients hospitalized in the specific department was obtained from administrative hospital databases. Patient data were analyzed anonymously. All ANA test data were retrieved from the relevant sources at two time points: 6 months pre-intervention and 6 months after the educational intervention. The data retrieved from the pre-intervention period were used to prepare the feedback provided to the departments during the intervention. The data were obtained retrospectively. Ethical considerations The protocol was reviewed by the Institutional Review Board of Meir Medical Center, and as it was a qualitative study involving medical staff, it did not require approval. Statistical analysis and reporting of results Outcome measures were compared between the pre- and post-intervention periods. All are reported as odds ratios (ORs) with the corresponding 95% confidence intervals (95% CI) and P values. Data were analyzed with SPSS version 27 (IBM Corporation, Armonk, NY). A quality improvement education intervention was conducted at Meir Medical Center, affiliated with Tel Aviv University. It was intended to educate staff about the appropriateness of ANA testing and reduce the overuse of ANA tests in five Internal Medicine and one Neurology departments. Meir Medical Center in Kfar Saba, Israel, has approximately 800 beds. Some of the departments focus on specific patient illnesses. For example, department C has a hepatology orientation; department E, rheumatology; and department A, hematology. Additionally, the neurology department, which routinely orders ANA tests for hospitalized patients presenting with conditions such as suspected vasculitis, stroke in young individuals, and suspected neuropathy, among others, was included. The study spanned a pre-intervention and a post-intervention period, each lasting 6 months. The quality improvement educational intervention took place in December 2021. It was structured as a 30-min group session with various personnel from the departments participating, including 2-3 senior hospitalists specializing in internal medicine, 7-8 residents, and the department head. The same educational intervention was presented individually in all six participating departments. Led by a certified rheumatologist (OTS), with additional support from other certified rheumatologists (YPB, SK), these sessions provided physicians with comprehensive insights into ANA testing. The content covered explanations of laboratory procedures, guidance on appropriate circumstances for requesting ANA testing in routine clinical settings, and the application of Choosing Wisely guidelines for the test (for presentation, see supplementary). During the session, it was highlighted that the ANA test has low specificity and should not be used as a screening test in patients without specific signs or symptoms of SLE or other connective tissue diseases. Additionally, it was noted that when the ANA test is used in cases with a low predictive probability of ANA-associated diseases based on clinical manifestations, there are more false-positive results, leading to overdiagnosis and overtreatment. At the end of the structured presentation, department-specific information was communicated, including insights into their ANA test utilization, presentation of outcome metrics, and relevant comparative data with other participating departments. Past clinical cases involving ANA testing were discussed with the staff of each department. Each department was requested to continue discussing this issue during the next morning’s meetings. Additionally, they were asked to introduce the intervention session to staff members who were absent due to night duty or vacation. The issue continued to be discussed during rheumatology consultations in the departments. All ANA testing was done in the Biochemical Laboratory at Meir Medical Center. ANA testing was done using the indirect immunofluorescence method on HeP-2 cells, according to international guidelines . A positive result was defined as a titer of 1:160 or higher. Outcome measures were the ANA/new patient ratio (APR) to assess the number of ANA tests ordered, and the percentage of positive ANA tests was used to evaluate the appropriateness of patient selection; both were measured 6 months pre-intervention and 6 months post-intervention. The percentage of repeat ANA tests was measured in the internal medicine and the neurology departments 1-year pre-intervention and 1-year post-intervention. Laboratory databases from Meir Medical Center were used to retrieve ANA data. These included the number of ANA tests performed, test results, and test dates. Information on the number of new patients hospitalized in the specific department was obtained from administrative hospital databases. Patient data were analyzed anonymously. All ANA test data were retrieved from the relevant sources at two time points: 6 months pre-intervention and 6 months after the educational intervention. The data retrieved from the pre-intervention period were used to prepare the feedback provided to the departments during the intervention. The data were obtained retrospectively. The protocol was reviewed by the Institutional Review Board of Meir Medical Center, and as it was a qualitative study involving medical staff, it did not require approval. Outcome measures were compared between the pre- and post-intervention periods. All are reported as odds ratios (ORs) with the corresponding 95% confidence intervals (95% CI) and P values. Data were analyzed with SPSS version 27 (IBM Corporation, Armonk, NY). In the pre-educational intervention period, 372 ANA tests were ordered by the internal medicine and neurology departments. The neurology department requested half and the rest from the five internal medicine departments (Fig. ). ANA/new patient ratio (APR) During the pre-educational intervention period, the APR in the neurology department was 43%. The APR decreased in the post-educational intervention period to 27%, with an OR of 0.49 (95% CI 0.37–0.63, P < 0.0001). In the internal medicine departments, it decreased from 2.6% to 2.2%, with an OR of 0.89 (95% CI 0.73–1.10, P = 0.28) (Fig. ). Percentage of positive ANA tests The percentage of positive ANA tests in the neurology department increased from 43% in the pre-educational intervention period to 53% in the post-intervention period, with OR 1.49 (95% CI 0.90–2.46, P = 0.12). In the internal medicine departments, it increased from 48% to 59%, OR 1.56 (95% CI 0.99–2.44, P = 0.0543), overall. An increase in the percentage of positive ANA tests was observed in the individual internal medicine departments as well (Fig. ). Percentage of repeated ANA tests The percentage of repeat ANA tests in the internal medicine departments and the neurology department was 3.4% in the year before the educational intervention and 2.5% in the year after the educational intervention. During the pre-educational intervention period, the APR in the neurology department was 43%. The APR decreased in the post-educational intervention period to 27%, with an OR of 0.49 (95% CI 0.37–0.63, P < 0.0001). In the internal medicine departments, it decreased from 2.6% to 2.2%, with an OR of 0.89 (95% CI 0.73–1.10, P = 0.28) (Fig. ). The percentage of positive ANA tests in the neurology department increased from 43% in the pre-educational intervention period to 53% in the post-intervention period, with OR 1.49 (95% CI 0.90–2.46, P = 0.12). In the internal medicine departments, it increased from 48% to 59%, OR 1.56 (95% CI 0.99–2.44, P = 0.0543), overall. An increase in the percentage of positive ANA tests was observed in the individual internal medicine departments as well (Fig. ). The percentage of repeat ANA tests in the internal medicine departments and the neurology department was 3.4% in the year before the educational intervention and 2.5% in the year after the educational intervention. This study described a quality improvement educational intervention intended to improve the appropriateness of ANA testing in the neurology and internal medicine departments in our hospital. We demonstrated that a straightforward educational intervention was associated with a decrease in the number of ANA tests ordered, as reflected by the APR, and an improvement in patient selection, as reflected by an increase in the proportion of positive ANA test results. Specifically, there was a 50% reduction in ANA tests ordered by the neurology department, which had previously accounted for a substantial portion of all ANA tests. While the decrease in ANA tests ordered by the internal medicine departments was more modest and did not reach statistical significance, this trend was observed consistently across all five departments. Moreover, the departments exhibited enhanced patient selection, indicated by an increase in the percentage of positive test results from 48% to 59% ( P = 0.054). In a study that evaluated utilization patterns, appropriateness, and associated costs of tests in patients referred to rheumatologists, ANA testing was the most frequently ordered investigation and was most likely to be ordered inappropriately, with a low positive result ratio . Barry et al. found that by changing the options in the electronic health record, the ordering patterns shifted toward Choosing Wisely recommendations . Lesuis et al. showed that a relatively simple intervention improved rheumatologists’ behavior in requesting ANA tests. The intervention was a 1-h group session for rheumatologists in three centers, combining an educational meeting with feedback. Six months after the intervention, a booster session was held. They found a significant decrease in the number of ANA tests requested in the post-intervention period. Comparable to our findings, there was a decrease in APR, but unlike our study, Lesuis et al. did not find an increase in the percentage of positive ANA tests. They had a second session and a longer follow-up period than we did and found a decrease in repeat ANA requests after the additional session. We observed a slight decrease in the number of repeat ANA tests in the year following the educational intervention. However, it is essential to note that we cannot definitively attribute this decrease to the educational intervention alone, as there were also changes in how the departments ordered tests during this year. Nevertheless, the ANA test is predominantly ordered by primary care physicians along with a diverse range of clinicians, including internists, dermatologists, nephrologists, neurologists, and gynecologists . Because most ANA tests in our hospital were ordered by the neurology and internal medicine departments, an intervention to improve overall ANA test–requesting behavior was necessary and showed encouraging results. This study had several limitations. It was not a controlled intervention but rather an analysis of the differences in ratios of tests ordered and positive results before and after an educational intervention. Additionally, the departments are heterogeneous, making direct comparisons challenging. For example, internal medicine department C focuses on hepatology, leading to more frequent ANA test requests when autoimmune hepatitis is suspected. In contrast, internal medicine department E has a rheumatology orientation and tends to repeat ANA testing in patients with known systemic autoimmune rheumatic diseases. Unfortunately, we could not retrieve information about which doctor ordered which test. We did not collect individualized patient data on the reason for hospitalization, patients’ diagnoses at discharge, and other clinical information necessary for estimating pre-test probability. Conducting detailed chart reviews would have been resource-intensive. Consequently, we could not directly demonstrate that our educational intervention improved patient selection and did not result in misdiagnoses due to the reduction in ANA testing. However, previous research by Ferrari indicated that the risk of missing a diagnosis of SLE is very low when ANA tests are conducted according to the Canadian Rheumatology Association’s recommendations, which advise against ordering antibody serology unless specific signs and symptoms of SLE are present . Therefore, the likelihood of underdiagnosing ANA-associated diseases was minimal. Lastly, our follow-up period was limited to 6 months, and longer-term monitoring is necessary to assess the sustainability of our implemented changes. Despite its limitations, the favorable outcomes found in this study demonstrate that a simple educational intervention can enhance decision-making and reduce excessive ANA testing and associated laboratory work, which in turn may lead to improved diagnostic and treatment processes. Below is the link to the electronic supplementary material. Supplementary file1 (PDF 497 KB) |
‘Feminization’ of physician workforce in Bangladesh, underlying factors and implications for health system: Insights from a mixed-methods study | 0134c0d0-5237-4f2e-bf13-36def321a7dc | 6329528 | Gynaecology[mh] | In recent times in medical profession, females have started outnumbering their male colleagues, in both developed and developing countries–a phenomenon sometimes referred to as ‘the feminization of medicine’ [ – ].Worldwide, 32% of the medical graduates are females . For instance, in the USA the number of female physicians increased from 27% in 1983 to 48% in 2011 and in Canada, there has been a fourfold increase within a span of 40 years . Similar trends have also been observed in Netherlands and most of its European neighbours, extending as far as Malta and Israel [ , , ]. The South-east Asian countries such as Thailand, China, Malaysia, and Indonesia are also catching up, where female physicians now comprise around 50% of the total number of registered physicians [ – ]. Factors such as humanistic appeal of medicine, socioeconomic status and liberal family environment, early inspiration from a family role model (doctor), parental expectations, and financial prospects have been identified as motivations to enroll in medical schools . In case of females, additional motivations include social prestige emanating from the profession and a high value in the marriage market , cultural preference for female doctors in conservative community , and intrinsic factors like willingness to help poor people arising from an altruistic attitude . Female physicians have preference for few selected specialties (for example, Obstetrics and Gynaecology and Paediatrics as opposed to Surgery) , mainly due to competing life priorities (for instance, marriage, child bearing, and family obligations in a patriarchal society), and work-life imbalance. . They also face challenges relocating to rural job postings because of the existing attitude towards women working in an unknown environment dominated by men . However, their narrow choice of specialty and limited ability to relocate to rural areas has health system implications such as poor availability of primary health care (PHC) services. Consistent with this global trend, Bangladesh is also undergoing a rapid change in sex composition of the physicians. As recent as in 2013, 31% of all registered physicians were females in the country and their number is increasing day by day . Similar trend is observed among the population of medical students as well, for example, 48% of the medical students admitted into the 2015–16 session were female . This phenomenon is throwing a big challenge before the female physicians for advancing their career, including choice of specialties which are often disconnected to the needs and priorities of the health services and medical education . Furthermore, the numbers of female health workers (especially physicians and nurses) working in the rural areas are becoming fewer , which can further exacerbate in coming days due to ongoing influx of women in medical and allied professions. Another problem is attrition or drop-out from the profession with consequent effects on already starved (of qualified professionals) health services. For example, high attrition rate among female physicians have been reported in Bangladesh who never enter into the profession after graduation . This is also commonly seen in Pakistan where many female physicians eventually end up becoming housewives . The secular increase in the number of female physicians is a relatively new phenomenon in Bangladesh and there is dearth of comprehensive and gender disaggregated data on this topic. This information is needed for planning the production of physician workforce in future according to the needs and priorities of health services, and allocate to different specialties as delineated in the country’s human resources for health (HRH) strategy. This study aimed to fill-in these knowledge gaps e.g., regarding the level and trend of sex composition of physicians during 2006–2015, factors that motivate female students to study medicine including the reasons for their parents’ preference for this, choice of particular specialties, challenges faced by them both as students as well as professionals in work and family lives. The findings are expected to inform necessary changes for a gender-sensitive and enabling work and living environment that facilitate female physicians’ retention and career progress, including balanced production of specialists based on the needs and priorities of the health systems .
Conceptual framework The conceptual framework guiding this study is based on current knowledge on the topic ( ). It shows that there are different factors that motivate females to embark on studying medicine. These include personal factors like fulfilling a much cherished dream to help people by being part of a noble profession, gaining social status and respect, and achieving financial security. Familial factors like influence of the parents (more so when either or both are physicians) and relatives are especially important, as they act as family ‘role models’. Besides, better socio-economic status and marriage market prospects (of getting a ‘better’ groom) also attract women and their parents to pursue the study of medicine . However, as discussed above, there are quite some challenges that the female medical students and physicians face in their academic and professional life in a male-dominated society, interfering with balance of their work-home lives. This phenomenon has some implications for the health system of the country as well e.g., problems with deployment and retention in the rural areas due to security and other reasons, substantial attrition resulting from the latter, and crowding in to certain preferred specialties which provide a kind of ‘comfort zone’ (especially for the reproductive age women and women with children) for them. This occurs at the cost of scarcity in other needed specialties in pre-, para-, and non-clinical subjects ( ). Study design This was a cross sectional exploratory study using a triangulation mixed-methods approach. Data were collected from primary and secondary sources, during 17 November—3 December, 2016, by students of the study team (n = 6). Both methods were used in order to obtain precise information on the research topic as well as to triangulate the findings. Secondary data were collected to find out the level and trend of feminization of physician workforce in Bangladesh. Quantitative survey using a structured questionnaire was done to elicit factors motivating female students to enroll in medical schools and their specialty preferences along with the implications on health systems. Besides, qualitative methods such as focus group discussion and in-depth interviews were done to explore challenges faced by the female students and physicians, and parent’s motivation in preferring medicine as a field of study for their daughters ( ). Sample and data collection This study was done as part of the MPH course requirement and sample for FGDs and IDIs were selected conveniently, using personal connections and networks of the MPH students in their respective medical colleges. Thus, primary data were collected from final year female medical students of four selected medical colleges in Dhaka city (two public and two private) (n = 315), a sample of female in-service trainee physicians from these medical colleges (n = 10), and a sample of parents of students participating in the survey (n = 5) ( ). Primary data collection Both quantitative (classroom survey) and qualitative data were collected from final year female students in selected medical colleges. The classroom survey used a pre-tested, self-administered questionnaire. First, permission was obtained from the principal of the sampled medical college few days before the actual survey was conducted. The date and time of the survey was unknown to the students and the faculty, except the principal. This was done to minimise the preconception among participants which might have arisen due to discussion of the survey topic among themselves. On the day of survey, the respective authority was approached with a request to allow the study team to run the survey before the classes began at a particular time. Only the female students were requested to stay in the classroom. The objectives and process of the study was briefly introduced by the study team, followed by instructions on how to fill-in the self-administered questionnaire. They were then requested to participate in the survey on a voluntary basis, assuring them of no consequences in case of non-participation. The study team approached a total of 325 students in the four medical colleges out of which 315 students consented to participate (response rate 97%). The questionnaires were then distributed to those consenting, and the survey took around 30 minutes to complete. The qualitative data were collected using pre-tested guidelines. Two FGDs with female students were conducted, in each of the sampled public and private medical colleges. For in-depth interviews, a sub-sample of the participating students, and a sample of in-service trainee physicians from the sampled medical colleges, were selected and interviewed discreetly at their place of preferences (mostly the dormitory). Besides, five parents of the participating students (conveniently selected) were also interviewed in-depth. The survey questionnaire and qualitative guidelines are submitted as supporting files ( and File). Secondary data collection Secondary data were collected to find out level and trends of sex distribution of physicians over a 10 year (2006–2015) period and admitted students over a six year (2011–2016) period. Bangladesh Medical and Dental Council (BMDC) provided data on registered physicians and the student data was provided by the respective offices of the medical colleges. Sex specific data was searched in the BMDC website ( http://bmdc.org.bd/ ) and manually counted for each year based on the first and last registry number of a year. In case of missing profiles of physicians, verification was done with BMDC and counted again in each related year. The Bangladesh College of Physicians and Surgeons ( https://www.bcpsbd.org/ ) provided data on post graduate memberships (MCPS) and fellowships (FCPS) in seven specific specialties. These were Medicine, Surgery, Paediatrics, Obstetrics and Gynaecology, Ophthalmology, Psychiatry and Anaesthesia. Data analysis Quantitative data were entered into MS excel, cleaned and then analyzed using Stata version 13.0. For the primary data, summary statistics of the age of the respondents were described using mean, and other statistics related to general socio-demographic characteristics were described as proportion. For categorization of the specialties, Anaesthesia, ENT (Ear Nose Throat), Ophthalmology, Orthopaedics, Radiology, and Surgery were grouped into ‘Surgery’. Internal medicine and Psychiatry were grouped together as ‘Medicine’. Finally, Anatomy, Biochemistry, Physiology, Pathology, and Microbiology and Forensic medicine were grouped together as ‘Basic science’. The other specialties such as Clinical research, Public Health, Paediatrics, and Obstetrics and Gynaecology remained as standalone categories. For showing comparison between public and private medical students, Pearson’s χ 2 test or Fisher’s Exact test was used for categorical variables as appropriate and two sample t -test was used for continuous variables. A p -value of less than 0.05 was considered to be statistically significant. For the qualitative data, transcription and translation was done within 24 hours of data collection. The transcripts were read at least three times to get familiar with it. Different a priori codes were prepared while preparing the semi-structured IDI and FGD guidelines. Some codes emerged from repeated reading of the transcripts and inductive codes were prepared. The a priori codes were also divided into sub-codes ( ). Then the data was clustered, compared and categorized, and data display was prepared to identify pattern. The data were analysed by the student investigators [PH, RDG, PYZ, MSJ, NT and AA], under the close supervision of the mentors [NN and MTH] and the supervisors [SMA and TJ]. Data validity check was done by triangulation, member feedback and looking for researchers’ effect. Triangulation was ensured by looking into data from IDIs and FGDs, as well as by selecting respondents from both public and private medical colleges. The qualitative data was checked by all the members of the research team [PH, RDG, PYZ, MSJ, NT and AA, NN, MTH, TJ and SMA]. To reduce researcher’s effect on the setting, time was given to build rapport with the respondent and intentions were clarified during data collection. To minimize the effect of setting on researcher, the field notes and memos were checked by all the members of the research team. Better quality data was given more importance in drawing conclusion. Ethical considerations The study protocol including the data collection tools were approved by the Ethical Review Committee of the BRAC James P Grant School of Public Health, BRAC University. No invasive procedure was involved in this study., Informed written consent was taken from the respondents before data collection began (using self-administered questionnaire for quantitative data, and guidelines and checklists for qualitative data). Also, the respondents were given full freedom to skip any questions or withdraw themselves from the study at any given point without providing any explanation. The quantitative data was given unique identification numbers before entering into the software to maintain anonymity. The qualitative data was also analysed anonymously.
The conceptual framework guiding this study is based on current knowledge on the topic ( ). It shows that there are different factors that motivate females to embark on studying medicine. These include personal factors like fulfilling a much cherished dream to help people by being part of a noble profession, gaining social status and respect, and achieving financial security. Familial factors like influence of the parents (more so when either or both are physicians) and relatives are especially important, as they act as family ‘role models’. Besides, better socio-economic status and marriage market prospects (of getting a ‘better’ groom) also attract women and their parents to pursue the study of medicine . However, as discussed above, there are quite some challenges that the female medical students and physicians face in their academic and professional life in a male-dominated society, interfering with balance of their work-home lives. This phenomenon has some implications for the health system of the country as well e.g., problems with deployment and retention in the rural areas due to security and other reasons, substantial attrition resulting from the latter, and crowding in to certain preferred specialties which provide a kind of ‘comfort zone’ (especially for the reproductive age women and women with children) for them. This occurs at the cost of scarcity in other needed specialties in pre-, para-, and non-clinical subjects ( ).
This was a cross sectional exploratory study using a triangulation mixed-methods approach. Data were collected from primary and secondary sources, during 17 November—3 December, 2016, by students of the study team (n = 6). Both methods were used in order to obtain precise information on the research topic as well as to triangulate the findings. Secondary data were collected to find out the level and trend of feminization of physician workforce in Bangladesh. Quantitative survey using a structured questionnaire was done to elicit factors motivating female students to enroll in medical schools and their specialty preferences along with the implications on health systems. Besides, qualitative methods such as focus group discussion and in-depth interviews were done to explore challenges faced by the female students and physicians, and parent’s motivation in preferring medicine as a field of study for their daughters ( ).
This study was done as part of the MPH course requirement and sample for FGDs and IDIs were selected conveniently, using personal connections and networks of the MPH students in their respective medical colleges. Thus, primary data were collected from final year female medical students of four selected medical colleges in Dhaka city (two public and two private) (n = 315), a sample of female in-service trainee physicians from these medical colleges (n = 10), and a sample of parents of students participating in the survey (n = 5) ( ).
Both quantitative (classroom survey) and qualitative data were collected from final year female students in selected medical colleges. The classroom survey used a pre-tested, self-administered questionnaire. First, permission was obtained from the principal of the sampled medical college few days before the actual survey was conducted. The date and time of the survey was unknown to the students and the faculty, except the principal. This was done to minimise the preconception among participants which might have arisen due to discussion of the survey topic among themselves. On the day of survey, the respective authority was approached with a request to allow the study team to run the survey before the classes began at a particular time. Only the female students were requested to stay in the classroom. The objectives and process of the study was briefly introduced by the study team, followed by instructions on how to fill-in the self-administered questionnaire. They were then requested to participate in the survey on a voluntary basis, assuring them of no consequences in case of non-participation. The study team approached a total of 325 students in the four medical colleges out of which 315 students consented to participate (response rate 97%). The questionnaires were then distributed to those consenting, and the survey took around 30 minutes to complete. The qualitative data were collected using pre-tested guidelines. Two FGDs with female students were conducted, in each of the sampled public and private medical colleges. For in-depth interviews, a sub-sample of the participating students, and a sample of in-service trainee physicians from the sampled medical colleges, were selected and interviewed discreetly at their place of preferences (mostly the dormitory). Besides, five parents of the participating students (conveniently selected) were also interviewed in-depth. The survey questionnaire and qualitative guidelines are submitted as supporting files ( and File).
Secondary data were collected to find out level and trends of sex distribution of physicians over a 10 year (2006–2015) period and admitted students over a six year (2011–2016) period. Bangladesh Medical and Dental Council (BMDC) provided data on registered physicians and the student data was provided by the respective offices of the medical colleges. Sex specific data was searched in the BMDC website ( http://bmdc.org.bd/ ) and manually counted for each year based on the first and last registry number of a year. In case of missing profiles of physicians, verification was done with BMDC and counted again in each related year. The Bangladesh College of Physicians and Surgeons ( https://www.bcpsbd.org/ ) provided data on post graduate memberships (MCPS) and fellowships (FCPS) in seven specific specialties. These were Medicine, Surgery, Paediatrics, Obstetrics and Gynaecology, Ophthalmology, Psychiatry and Anaesthesia.
Quantitative data were entered into MS excel, cleaned and then analyzed using Stata version 13.0. For the primary data, summary statistics of the age of the respondents were described using mean, and other statistics related to general socio-demographic characteristics were described as proportion. For categorization of the specialties, Anaesthesia, ENT (Ear Nose Throat), Ophthalmology, Orthopaedics, Radiology, and Surgery were grouped into ‘Surgery’. Internal medicine and Psychiatry were grouped together as ‘Medicine’. Finally, Anatomy, Biochemistry, Physiology, Pathology, and Microbiology and Forensic medicine were grouped together as ‘Basic science’. The other specialties such as Clinical research, Public Health, Paediatrics, and Obstetrics and Gynaecology remained as standalone categories. For showing comparison between public and private medical students, Pearson’s χ 2 test or Fisher’s Exact test was used for categorical variables as appropriate and two sample t -test was used for continuous variables. A p -value of less than 0.05 was considered to be statistically significant. For the qualitative data, transcription and translation was done within 24 hours of data collection. The transcripts were read at least three times to get familiar with it. Different a priori codes were prepared while preparing the semi-structured IDI and FGD guidelines. Some codes emerged from repeated reading of the transcripts and inductive codes were prepared. The a priori codes were also divided into sub-codes ( ). Then the data was clustered, compared and categorized, and data display was prepared to identify pattern. The data were analysed by the student investigators [PH, RDG, PYZ, MSJ, NT and AA], under the close supervision of the mentors [NN and MTH] and the supervisors [SMA and TJ]. Data validity check was done by triangulation, member feedback and looking for researchers’ effect. Triangulation was ensured by looking into data from IDIs and FGDs, as well as by selecting respondents from both public and private medical colleges. The qualitative data was checked by all the members of the research team [PH, RDG, PYZ, MSJ, NT and AA, NN, MTH, TJ and SMA]. To reduce researcher’s effect on the setting, time was given to build rapport with the respondent and intentions were clarified during data collection. To minimize the effect of setting on researcher, the field notes and memos were checked by all the members of the research team. Better quality data was given more importance in drawing conclusion.
The study protocol including the data collection tools were approved by the Ethical Review Committee of the BRAC James P Grant School of Public Health, BRAC University. No invasive procedure was involved in this study., Informed written consent was taken from the respondents before data collection began (using self-administered questionnaire for quantitative data, and guidelines and checklists for qualitative data). Also, the respondents were given full freedom to skip any questions or withdraw themselves from the study at any given point without providing any explanation. The quantitative data was given unique identification numbers before entering into the software to maintain anonymity. The qualitative data was also analysed anonymously.
The results are presented according to the two methods of data collection used: A) Findings from the quantitative survey Level and trend of sexual composition of physicians (2006–2015) and admitted students (2011–2016) Out of a total of 34, 697 registered physicians (cumulative) during the ten-year period of 2006–2015, 48% (16,482) were male and 52% (18,215) were female ( ). From 2011 to 2016, majority of the students being admitted in the two public and private medical colleges were female (range: 40–58% and 64–71% respectively) ( ). Medicine and Surgery were the most popular specialties amongst males in the ten-year period (87%); for females this was Obstetrics and Gynaecology (96%), followed by Paediatrics (57%). In other specialties, such as Ophthalmology, Psychiatry and Anaesthesia, the proportions of female were found to be 28%, 24% and 11%, respectively ( ). Characteristics of the final year female medical students In case of primary survey, 207 (66%) of the respondents were from public and 107 (34%) were from private medical colleges ( ). Majority of the students (93%) were from urban background, more so in case of students from the private medical colleges ( p = 0.01). Students of private medical colleges came from relatively educated families- their fathers and mothers had post-graduate education in greater proportion than those of the public medical colleges (61% vs. 48% and 44% vs. 26%, respectively), and also, from relatively affluent families (monthly family income >1,00,000 BDT, p <0.001). Reported reasons for choosing to study medicine The most important individual factors motivating the females to choose medical education were social respect accorded to the profession (94%), perceived opportunity to help people (94%), serving a ‘noble’ profession (91%) and fulfilling a ‘childhood dream’ (73%). Significant difference was present between the public and private medical respondents across two motivational factors: social respect to the profession ( p = 0.02) and scientific nature of study ( p = 0.03), the percentage was more so for the private medical students than the public medical students ( ). Among the familial factors, parental pressure (42%) and influence of friends/ relatives and role models (37%) were dominant. Although not significant, more respondents from the private medical colleges (17%) were motivated to choose medicine because of their physician parents ( ). Among the societal factors, contribution to society and social status of the profession were mostly reported (84% and 66% respectively). In total, only 17% reported its marriage value and there was no significant difference between the two types of colleges ( ). Reported preferences for specialization Obstetrics and Gynaecology and ‘Surgery’ were the most common preferred subspecialties (27%), followed by Medicine (20%) and Paediatrics (15%). The predilection towards ‘surgery’ was more among the private medical college students (35% vs. 22%, p = 0.01), while Obstetrics and Gynaecology (32% vs. 19%, p = 0.01) and Paediatrics (18% vs. 9%, p = 0.04) were preferred by those from the public medical colleges ( ). Very few female students (<5%) preferred to study Basic Sciences, Public Health and Clinical Research. B) Findings from the FGDs and IDIs These are described under relevant themes: Parent’s motivational factors for sending their daughters to medical colleges In-depth interviews reveal that the most important motivation underlying parents’ preference for their daughters to study medicine was the charitable nature and social prestige of the profession. According to parents, a girl can help the people, contribute to society and stand in a higher social position through this profession. They thought that it is also safer and more suitable profession for girls. “ First of all , it’s a noble profession . Secondly , there are plenty of opportunities to help and contribute to the lives of people when their lives are in danger . This is also the most respected and secured profession for girls in our society . That’s why I preferred this profession for my daughter . ” ---mother of a private medical college student According to the parents, the diverse work opportunities in medical profession offer an important advantage for girls to work independently in their field of choices, giving attention to her family if necessary. “In medical profession , a girl can work independently; it has a flexibility which is very necessary for a girl because she has to raise her children; she has other obligations for her family…” ---mother of a public medical college student Having a doctor in the family (‘role model’) was considered another important factor by the parents. They perceived that a doctor in the family can help them in taking appropriate decisions in case of medical emergencies. Besides, doctors are considered meritorious and hold a higher status in the society; therefore, becoming the parent of a doctor was a matter of pride to them. “My daughter will be a doctor and serve the people and she will be established. So when I say it to my family members or others then they say that I am a successful parent . When I hear this I feel very proud.” ---father of a public medical college student Sometimes the wishes of the parents take the form of indirect mental pressure to compel the students to study medicine. One in-service trainee physician remarked: “Actually I deeply dislike that parents force their children . Children can have their own dream; after all it’s their own life… parents should support their children for what they want to be… I suffered much in my student life!” ---Female in-service trainee physician Challenges for women working in the medical sector We further explored the challenges medical students face during their academic and training period. These are presented below. i) Socio-cultural norms The female medical students perceived that the most important challenges come from the society and their families. Firstly, they mentioned that after marriage the situation seems to change drastically for the female students and physicians in terms of family support. For example, their husbands and in-laws’ expect that they would prioritise their families over their careers and their workplaces. One respondent explained this situation by saying, “As most girls cannot maintain both career and family life equally , they have to compromise … the situation in Bangladesh is such that , you have to give more preference to married life over career .” ---medical student, public medical college An in-service trainee expressed this more vividly: “I had to compromise with myself ( regarding administrative and social issues ) because that’s what you have to do . How it happened I don’t know … I got habituated . In the beginning I felt bad , I still feel bad , but now I think that there is no point in expressing these things . ” The social construct of the ‘right’ age of marriage is also another issue that creates challenges for the female students and physicians alike. As one of the respondents said, “We must get married within 30 years of age to settle down whereas it does not matter if a man marries at the age of 35years .” ---medical student, public medical college The third major issue that came up was the shift duties especially in the night. According to them, most of the families do not want them to work night shifts. “…That aunty was proudly saying that she didn’t let her daughter work at night , rather she could stay at home not doing any job . ---medical student, public medical college This is echoed by an in-service trainee physician as well: “Often it is seen that when a girl is doing night duty- society asks a lot of questions , even when there is family support…I myself am afraid of what if I don’t get similar support and can’t go ahead with my career as I have planned …” ii) Gender disparities Almost all the female students said that in spite of being equally qualified, society including some of the female patients consider female physicians as less competent compared to male physicians. According to the female students, their male peers used to think them as 'less productive' in their professional life, though they had done better in their student life. However, parents opined that in the past, society used to discriminate between male and female physicians; but this attitude is changing now a days. The gender disparity is also prevalent in case of career choices, job posting, duty shifts, promotion, and their status as physician. The respondents have mentioned that the society, even their teachers, believed that boys are more talented and competent than girls. One respondent highlighted this, “Everyone always thinks that the boys are brainier than us . Even our teachers think in this way . If in a family there’s a daughter and a son , it’s obvious- they want the girl to be doctor and the boy to be engineer . ” ---medical student, private medical college Another respondent said that this attitude of looking at them as inferior to male physicians even extended to the patients: “…They say that public can address us as ‘sister’ as we are female , females are like sisters . But they do not understand that public address a professional as ‘sister’ … They do not understand that people address us ‘sister’ taking us as a nurse . They post lots of statuses (in Facebook) and try to make fun of us” . ---medical student, public medical college The career of husband gets preference over the wife’s, even if they are both physicians. For example, as reflected in the statement below “A male who has already established his career in the country , will not be willing to leave everything behind to accompany her wife if she plans , for example , to study abroad; while under the same circumstance , it’s the girl who has to go with husband without any question… … . ” ---Female in-service trainee physician One of the administrative issues that came up in the discussion was the issue of promotion: “In terms of promotion , authority always tries not to promote girls . They think girls won’t be able to handle the job responsibilities , as they have family to take care of . ” ---medical student, public medical college iii) Workplace insecurity Most of the respondents preferred to work in the health centers located in the urban and peri-urban areas, even if they preferred public sector jobs. The main reasons given were having access to social and family network, better opportunity for professional development including post graduate training, workplace security and also being habituated to the urban lifestyle during the long years in the medical colleges and hospitals during study. They viewed lack of autonomy and patriarchal attitude of the society as a challenge to work in the rural areas. They opined, if conditions improve, more females would be interested to work in the rural areas. “In most of the villages, up until now, females are not given autonomy… the right to do things on their own … so, when a female doctor goes there to work, they think she will do whatever they command . This mentality of the rural people must be changed.” ---medical student, public medical college According to the respondents, the workplace security in the rural health facilities is less than the urban health facilities, which hinders female doctors’ interest in seeking posting in the rural area. “There should be security at the workplace…if there is any mistake while providing care, people literally would tear apart the doctor . They tease and harass the doctors, specially the female doctors. If you can provide security, the female doctors will be motivated to work in the rural areas.” ---medical student, private medical college Students mentioned that they are not encouraged by families to take public sector jobs and subsequent rural postings because of this security issue; often the resistance is unsurmountable for them. Perceived implications by students (and physicians) The students perceived that, given the above challenges, they will have to face certain realities in their professional life. These are presented below. i) Difficulty in taking up rural postings The main difficulty the students perceived was related to the condition of the residential facilities. From anecdotal evidence from their seniors in rural jobs, they perceived the rural facilities to be inadequate (congested, dirty, insecure) to live, and therefore, not congenial for taking up rural postings. The administrative issues were mostly reported by the public medical college students, but the social security issue was reported by both public and private medical college students. One respondent mentioned: “Working in the urban area will be easier for me. After entering into marital life , it will be easier for me to maintain the family.” ---medical student, public medical college ii) Propensity to choose few clinical specialties The students speculated that due to societal norms and gender issues, and difficulty with balancing work-home life, they may have to choose only a few areas for specialization (e.g., Obstetrics and Gynaecology and Paediatrics) like their predecessors, and most of them are unwilling to become teachers of basic medical subjects. However, they thought that in future things may change with changes in society’s attitude. To quote: “People in our country still think that every female doctor will be a gynaecologist … I think upcoming female doctors will pursue different specialties and overcome some stigmas…” ---medical student, public medical college iii) Perceived effects on the health system Most of the students observed that compared to the number of female students, there are not as many practicing female physicians. This is creating a gap, especially in the conservative rural areas where female doctors are needed more for managing the female patients. One respondent said, “Actually in our country female doctor is needed , and most females prefer female doctors . Now those who are becoming MBBS doctors but not pursuing career , our patients are not getting their services , they are being deprived . ” ---medical student, public medical college They also mentioned that when a physician drops out, it is an economic loss to the country given the investment required to produce a doctor. One of the in-service trainee physician mentioned: “Now we see that females are being admitting more in the medical colleges, but at the end of the day, they are dropping out more. It is a waste . A lot of good doctors are not going into career… dropping out will create a gap in the health sector.” An in-service trainee physician explained the scenario in detail: “I think females drop out more . Females have many kinds of bindings . Most females get married during their internship . So once they get into the family life , a lot of things they have to compromise , and eventually the study is hampered . Sometimes it is seen that the subject or career that she wants to choose is not possible because of family , then she opt for more traditional subjects such as Obstetrics and Gynaecology . Some families don’t want the females to pursue career . That’s why I think females flourish more during undergraduate level , but do not do that well in post-graduation . ” Another in-service trainee physician presented the issue of drop-out differently: “I think , first of all , females need to change their own mentalities . Females have to be strong willed to pursue their own career and establish in life and manage both family and social aspects as well … so that females can pursue their dreams and not drop out” .
Level and trend of sexual composition of physicians (2006–2015) and admitted students (2011–2016) Out of a total of 34, 697 registered physicians (cumulative) during the ten-year period of 2006–2015, 48% (16,482) were male and 52% (18,215) were female ( ). From 2011 to 2016, majority of the students being admitted in the two public and private medical colleges were female (range: 40–58% and 64–71% respectively) ( ). Medicine and Surgery were the most popular specialties amongst males in the ten-year period (87%); for females this was Obstetrics and Gynaecology (96%), followed by Paediatrics (57%). In other specialties, such as Ophthalmology, Psychiatry and Anaesthesia, the proportions of female were found to be 28%, 24% and 11%, respectively ( ). Characteristics of the final year female medical students In case of primary survey, 207 (66%) of the respondents were from public and 107 (34%) were from private medical colleges ( ). Majority of the students (93%) were from urban background, more so in case of students from the private medical colleges ( p = 0.01). Students of private medical colleges came from relatively educated families- their fathers and mothers had post-graduate education in greater proportion than those of the public medical colleges (61% vs. 48% and 44% vs. 26%, respectively), and also, from relatively affluent families (monthly family income >1,00,000 BDT, p <0.001). Reported reasons for choosing to study medicine The most important individual factors motivating the females to choose medical education were social respect accorded to the profession (94%), perceived opportunity to help people (94%), serving a ‘noble’ profession (91%) and fulfilling a ‘childhood dream’ (73%). Significant difference was present between the public and private medical respondents across two motivational factors: social respect to the profession ( p = 0.02) and scientific nature of study ( p = 0.03), the percentage was more so for the private medical students than the public medical students ( ). Among the familial factors, parental pressure (42%) and influence of friends/ relatives and role models (37%) were dominant. Although not significant, more respondents from the private medical colleges (17%) were motivated to choose medicine because of their physician parents ( ). Among the societal factors, contribution to society and social status of the profession were mostly reported (84% and 66% respectively). In total, only 17% reported its marriage value and there was no significant difference between the two types of colleges ( ). Reported preferences for specialization Obstetrics and Gynaecology and ‘Surgery’ were the most common preferred subspecialties (27%), followed by Medicine (20%) and Paediatrics (15%). The predilection towards ‘surgery’ was more among the private medical college students (35% vs. 22%, p = 0.01), while Obstetrics and Gynaecology (32% vs. 19%, p = 0.01) and Paediatrics (18% vs. 9%, p = 0.04) were preferred by those from the public medical colleges ( ). Very few female students (<5%) preferred to study Basic Sciences, Public Health and Clinical Research.
Out of a total of 34, 697 registered physicians (cumulative) during the ten-year period of 2006–2015, 48% (16,482) were male and 52% (18,215) were female ( ). From 2011 to 2016, majority of the students being admitted in the two public and private medical colleges were female (range: 40–58% and 64–71% respectively) ( ). Medicine and Surgery were the most popular specialties amongst males in the ten-year period (87%); for females this was Obstetrics and Gynaecology (96%), followed by Paediatrics (57%). In other specialties, such as Ophthalmology, Psychiatry and Anaesthesia, the proportions of female were found to be 28%, 24% and 11%, respectively ( ).
In case of primary survey, 207 (66%) of the respondents were from public and 107 (34%) were from private medical colleges ( ). Majority of the students (93%) were from urban background, more so in case of students from the private medical colleges ( p = 0.01). Students of private medical colleges came from relatively educated families- their fathers and mothers had post-graduate education in greater proportion than those of the public medical colleges (61% vs. 48% and 44% vs. 26%, respectively), and also, from relatively affluent families (monthly family income >1,00,000 BDT, p <0.001).
The most important individual factors motivating the females to choose medical education were social respect accorded to the profession (94%), perceived opportunity to help people (94%), serving a ‘noble’ profession (91%) and fulfilling a ‘childhood dream’ (73%). Significant difference was present between the public and private medical respondents across two motivational factors: social respect to the profession ( p = 0.02) and scientific nature of study ( p = 0.03), the percentage was more so for the private medical students than the public medical students ( ). Among the familial factors, parental pressure (42%) and influence of friends/ relatives and role models (37%) were dominant. Although not significant, more respondents from the private medical colleges (17%) were motivated to choose medicine because of their physician parents ( ). Among the societal factors, contribution to society and social status of the profession were mostly reported (84% and 66% respectively). In total, only 17% reported its marriage value and there was no significant difference between the two types of colleges ( ).
Obstetrics and Gynaecology and ‘Surgery’ were the most common preferred subspecialties (27%), followed by Medicine (20%) and Paediatrics (15%). The predilection towards ‘surgery’ was more among the private medical college students (35% vs. 22%, p = 0.01), while Obstetrics and Gynaecology (32% vs. 19%, p = 0.01) and Paediatrics (18% vs. 9%, p = 0.04) were preferred by those from the public medical colleges ( ). Very few female students (<5%) preferred to study Basic Sciences, Public Health and Clinical Research.
These are described under relevant themes: Parent’s motivational factors for sending their daughters to medical colleges In-depth interviews reveal that the most important motivation underlying parents’ preference for their daughters to study medicine was the charitable nature and social prestige of the profession. According to parents, a girl can help the people, contribute to society and stand in a higher social position through this profession. They thought that it is also safer and more suitable profession for girls. “ First of all , it’s a noble profession . Secondly , there are plenty of opportunities to help and contribute to the lives of people when their lives are in danger . This is also the most respected and secured profession for girls in our society . That’s why I preferred this profession for my daughter . ” ---mother of a private medical college student According to the parents, the diverse work opportunities in medical profession offer an important advantage for girls to work independently in their field of choices, giving attention to her family if necessary. “In medical profession , a girl can work independently; it has a flexibility which is very necessary for a girl because she has to raise her children; she has other obligations for her family…” ---mother of a public medical college student Having a doctor in the family (‘role model’) was considered another important factor by the parents. They perceived that a doctor in the family can help them in taking appropriate decisions in case of medical emergencies. Besides, doctors are considered meritorious and hold a higher status in the society; therefore, becoming the parent of a doctor was a matter of pride to them. “My daughter will be a doctor and serve the people and she will be established. So when I say it to my family members or others then they say that I am a successful parent . When I hear this I feel very proud.” ---father of a public medical college student Sometimes the wishes of the parents take the form of indirect mental pressure to compel the students to study medicine. One in-service trainee physician remarked: “Actually I deeply dislike that parents force their children . Children can have their own dream; after all it’s their own life… parents should support their children for what they want to be… I suffered much in my student life!” ---Female in-service trainee physician Challenges for women working in the medical sector We further explored the challenges medical students face during their academic and training period. These are presented below. i) Socio-cultural norms The female medical students perceived that the most important challenges come from the society and their families. Firstly, they mentioned that after marriage the situation seems to change drastically for the female students and physicians in terms of family support. For example, their husbands and in-laws’ expect that they would prioritise their families over their careers and their workplaces. One respondent explained this situation by saying, “As most girls cannot maintain both career and family life equally , they have to compromise … the situation in Bangladesh is such that , you have to give more preference to married life over career .” ---medical student, public medical college An in-service trainee expressed this more vividly: “I had to compromise with myself ( regarding administrative and social issues ) because that’s what you have to do . How it happened I don’t know … I got habituated . In the beginning I felt bad , I still feel bad , but now I think that there is no point in expressing these things . ” The social construct of the ‘right’ age of marriage is also another issue that creates challenges for the female students and physicians alike. As one of the respondents said, “We must get married within 30 years of age to settle down whereas it does not matter if a man marries at the age of 35years .” ---medical student, public medical college The third major issue that came up was the shift duties especially in the night. According to them, most of the families do not want them to work night shifts. “…That aunty was proudly saying that she didn’t let her daughter work at night , rather she could stay at home not doing any job . ---medical student, public medical college This is echoed by an in-service trainee physician as well: “Often it is seen that when a girl is doing night duty- society asks a lot of questions , even when there is family support…I myself am afraid of what if I don’t get similar support and can’t go ahead with my career as I have planned …” ii) Gender disparities Almost all the female students said that in spite of being equally qualified, society including some of the female patients consider female physicians as less competent compared to male physicians. According to the female students, their male peers used to think them as 'less productive' in their professional life, though they had done better in their student life. However, parents opined that in the past, society used to discriminate between male and female physicians; but this attitude is changing now a days. The gender disparity is also prevalent in case of career choices, job posting, duty shifts, promotion, and their status as physician. The respondents have mentioned that the society, even their teachers, believed that boys are more talented and competent than girls. One respondent highlighted this, “Everyone always thinks that the boys are brainier than us . Even our teachers think in this way . If in a family there’s a daughter and a son , it’s obvious- they want the girl to be doctor and the boy to be engineer . ” ---medical student, private medical college Another respondent said that this attitude of looking at them as inferior to male physicians even extended to the patients: “…They say that public can address us as ‘sister’ as we are female , females are like sisters . But they do not understand that public address a professional as ‘sister’ … They do not understand that people address us ‘sister’ taking us as a nurse . They post lots of statuses (in Facebook) and try to make fun of us” . ---medical student, public medical college The career of husband gets preference over the wife’s, even if they are both physicians. For example, as reflected in the statement below “A male who has already established his career in the country , will not be willing to leave everything behind to accompany her wife if she plans , for example , to study abroad; while under the same circumstance , it’s the girl who has to go with husband without any question… … . ” ---Female in-service trainee physician One of the administrative issues that came up in the discussion was the issue of promotion: “In terms of promotion , authority always tries not to promote girls . They think girls won’t be able to handle the job responsibilities , as they have family to take care of . ” ---medical student, public medical college iii) Workplace insecurity Most of the respondents preferred to work in the health centers located in the urban and peri-urban areas, even if they preferred public sector jobs. The main reasons given were having access to social and family network, better opportunity for professional development including post graduate training, workplace security and also being habituated to the urban lifestyle during the long years in the medical colleges and hospitals during study. They viewed lack of autonomy and patriarchal attitude of the society as a challenge to work in the rural areas. They opined, if conditions improve, more females would be interested to work in the rural areas. “In most of the villages, up until now, females are not given autonomy… the right to do things on their own … so, when a female doctor goes there to work, they think she will do whatever they command . This mentality of the rural people must be changed.” ---medical student, public medical college According to the respondents, the workplace security in the rural health facilities is less than the urban health facilities, which hinders female doctors’ interest in seeking posting in the rural area. “There should be security at the workplace…if there is any mistake while providing care, people literally would tear apart the doctor . They tease and harass the doctors, specially the female doctors. If you can provide security, the female doctors will be motivated to work in the rural areas.” ---medical student, private medical college Students mentioned that they are not encouraged by families to take public sector jobs and subsequent rural postings because of this security issue; often the resistance is unsurmountable for them. Perceived implications by students (and physicians) The students perceived that, given the above challenges, they will have to face certain realities in their professional life. These are presented below. i) Difficulty in taking up rural postings The main difficulty the students perceived was related to the condition of the residential facilities. From anecdotal evidence from their seniors in rural jobs, they perceived the rural facilities to be inadequate (congested, dirty, insecure) to live, and therefore, not congenial for taking up rural postings. The administrative issues were mostly reported by the public medical college students, but the social security issue was reported by both public and private medical college students. One respondent mentioned: “Working in the urban area will be easier for me. After entering into marital life , it will be easier for me to maintain the family.” ---medical student, public medical college ii) Propensity to choose few clinical specialties The students speculated that due to societal norms and gender issues, and difficulty with balancing work-home life, they may have to choose only a few areas for specialization (e.g., Obstetrics and Gynaecology and Paediatrics) like their predecessors, and most of them are unwilling to become teachers of basic medical subjects. However, they thought that in future things may change with changes in society’s attitude. To quote: “People in our country still think that every female doctor will be a gynaecologist … I think upcoming female doctors will pursue different specialties and overcome some stigmas…” ---medical student, public medical college iii) Perceived effects on the health system Most of the students observed that compared to the number of female students, there are not as many practicing female physicians. This is creating a gap, especially in the conservative rural areas where female doctors are needed more for managing the female patients. One respondent said, “Actually in our country female doctor is needed , and most females prefer female doctors . Now those who are becoming MBBS doctors but not pursuing career , our patients are not getting their services , they are being deprived . ” ---medical student, public medical college They also mentioned that when a physician drops out, it is an economic loss to the country given the investment required to produce a doctor. One of the in-service trainee physician mentioned: “Now we see that females are being admitting more in the medical colleges, but at the end of the day, they are dropping out more. It is a waste . A lot of good doctors are not going into career… dropping out will create a gap in the health sector.” An in-service trainee physician explained the scenario in detail: “I think females drop out more . Females have many kinds of bindings . Most females get married during their internship . So once they get into the family life , a lot of things they have to compromise , and eventually the study is hampered . Sometimes it is seen that the subject or career that she wants to choose is not possible because of family , then she opt for more traditional subjects such as Obstetrics and Gynaecology . Some families don’t want the females to pursue career . That’s why I think females flourish more during undergraduate level , but do not do that well in post-graduation . ” Another in-service trainee physician presented the issue of drop-out differently: “I think , first of all , females need to change their own mentalities . Females have to be strong willed to pursue their own career and establish in life and manage both family and social aspects as well … so that females can pursue their dreams and not drop out” .
In-depth interviews reveal that the most important motivation underlying parents’ preference for their daughters to study medicine was the charitable nature and social prestige of the profession. According to parents, a girl can help the people, contribute to society and stand in a higher social position through this profession. They thought that it is also safer and more suitable profession for girls. “ First of all , it’s a noble profession . Secondly , there are plenty of opportunities to help and contribute to the lives of people when their lives are in danger . This is also the most respected and secured profession for girls in our society . That’s why I preferred this profession for my daughter . ” ---mother of a private medical college student According to the parents, the diverse work opportunities in medical profession offer an important advantage for girls to work independently in their field of choices, giving attention to her family if necessary. “In medical profession , a girl can work independently; it has a flexibility which is very necessary for a girl because she has to raise her children; she has other obligations for her family…” ---mother of a public medical college student Having a doctor in the family (‘role model’) was considered another important factor by the parents. They perceived that a doctor in the family can help them in taking appropriate decisions in case of medical emergencies. Besides, doctors are considered meritorious and hold a higher status in the society; therefore, becoming the parent of a doctor was a matter of pride to them. “My daughter will be a doctor and serve the people and she will be established. So when I say it to my family members or others then they say that I am a successful parent . When I hear this I feel very proud.” ---father of a public medical college student Sometimes the wishes of the parents take the form of indirect mental pressure to compel the students to study medicine. One in-service trainee physician remarked: “Actually I deeply dislike that parents force their children . Children can have their own dream; after all it’s their own life… parents should support their children for what they want to be… I suffered much in my student life!” ---Female in-service trainee physician
We further explored the challenges medical students face during their academic and training period. These are presented below. i) Socio-cultural norms The female medical students perceived that the most important challenges come from the society and their families. Firstly, they mentioned that after marriage the situation seems to change drastically for the female students and physicians in terms of family support. For example, their husbands and in-laws’ expect that they would prioritise their families over their careers and their workplaces. One respondent explained this situation by saying, “As most girls cannot maintain both career and family life equally , they have to compromise … the situation in Bangladesh is such that , you have to give more preference to married life over career .” ---medical student, public medical college An in-service trainee expressed this more vividly: “I had to compromise with myself ( regarding administrative and social issues ) because that’s what you have to do . How it happened I don’t know … I got habituated . In the beginning I felt bad , I still feel bad , but now I think that there is no point in expressing these things . ” The social construct of the ‘right’ age of marriage is also another issue that creates challenges for the female students and physicians alike. As one of the respondents said, “We must get married within 30 years of age to settle down whereas it does not matter if a man marries at the age of 35years .” ---medical student, public medical college The third major issue that came up was the shift duties especially in the night. According to them, most of the families do not want them to work night shifts. “…That aunty was proudly saying that she didn’t let her daughter work at night , rather she could stay at home not doing any job . ---medical student, public medical college This is echoed by an in-service trainee physician as well: “Often it is seen that when a girl is doing night duty- society asks a lot of questions , even when there is family support…I myself am afraid of what if I don’t get similar support and can’t go ahead with my career as I have planned …” ii) Gender disparities Almost all the female students said that in spite of being equally qualified, society including some of the female patients consider female physicians as less competent compared to male physicians. According to the female students, their male peers used to think them as 'less productive' in their professional life, though they had done better in their student life. However, parents opined that in the past, society used to discriminate between male and female physicians; but this attitude is changing now a days. The gender disparity is also prevalent in case of career choices, job posting, duty shifts, promotion, and their status as physician. The respondents have mentioned that the society, even their teachers, believed that boys are more talented and competent than girls. One respondent highlighted this, “Everyone always thinks that the boys are brainier than us . Even our teachers think in this way . If in a family there’s a daughter and a son , it’s obvious- they want the girl to be doctor and the boy to be engineer . ” ---medical student, private medical college Another respondent said that this attitude of looking at them as inferior to male physicians even extended to the patients: “…They say that public can address us as ‘sister’ as we are female , females are like sisters . But they do not understand that public address a professional as ‘sister’ … They do not understand that people address us ‘sister’ taking us as a nurse . They post lots of statuses (in Facebook) and try to make fun of us” . ---medical student, public medical college The career of husband gets preference over the wife’s, even if they are both physicians. For example, as reflected in the statement below “A male who has already established his career in the country , will not be willing to leave everything behind to accompany her wife if she plans , for example , to study abroad; while under the same circumstance , it’s the girl who has to go with husband without any question… … . ” ---Female in-service trainee physician One of the administrative issues that came up in the discussion was the issue of promotion: “In terms of promotion , authority always tries not to promote girls . They think girls won’t be able to handle the job responsibilities , as they have family to take care of . ” ---medical student, public medical college iii) Workplace insecurity Most of the respondents preferred to work in the health centers located in the urban and peri-urban areas, even if they preferred public sector jobs. The main reasons given were having access to social and family network, better opportunity for professional development including post graduate training, workplace security and also being habituated to the urban lifestyle during the long years in the medical colleges and hospitals during study. They viewed lack of autonomy and patriarchal attitude of the society as a challenge to work in the rural areas. They opined, if conditions improve, more females would be interested to work in the rural areas. “In most of the villages, up until now, females are not given autonomy… the right to do things on their own … so, when a female doctor goes there to work, they think she will do whatever they command . This mentality of the rural people must be changed.” ---medical student, public medical college According to the respondents, the workplace security in the rural health facilities is less than the urban health facilities, which hinders female doctors’ interest in seeking posting in the rural area. “There should be security at the workplace…if there is any mistake while providing care, people literally would tear apart the doctor . They tease and harass the doctors, specially the female doctors. If you can provide security, the female doctors will be motivated to work in the rural areas.” ---medical student, private medical college Students mentioned that they are not encouraged by families to take public sector jobs and subsequent rural postings because of this security issue; often the resistance is unsurmountable for them.
The students perceived that, given the above challenges, they will have to face certain realities in their professional life. These are presented below. i) Difficulty in taking up rural postings The main difficulty the students perceived was related to the condition of the residential facilities. From anecdotal evidence from their seniors in rural jobs, they perceived the rural facilities to be inadequate (congested, dirty, insecure) to live, and therefore, not congenial for taking up rural postings. The administrative issues were mostly reported by the public medical college students, but the social security issue was reported by both public and private medical college students. One respondent mentioned: “Working in the urban area will be easier for me. After entering into marital life , it will be easier for me to maintain the family.” ---medical student, public medical college ii) Propensity to choose few clinical specialties The students speculated that due to societal norms and gender issues, and difficulty with balancing work-home life, they may have to choose only a few areas for specialization (e.g., Obstetrics and Gynaecology and Paediatrics) like their predecessors, and most of them are unwilling to become teachers of basic medical subjects. However, they thought that in future things may change with changes in society’s attitude. To quote: “People in our country still think that every female doctor will be a gynaecologist … I think upcoming female doctors will pursue different specialties and overcome some stigmas…” ---medical student, public medical college iii) Perceived effects on the health system Most of the students observed that compared to the number of female students, there are not as many practicing female physicians. This is creating a gap, especially in the conservative rural areas where female doctors are needed more for managing the female patients. One respondent said, “Actually in our country female doctor is needed , and most females prefer female doctors . Now those who are becoming MBBS doctors but not pursuing career , our patients are not getting their services , they are being deprived . ” ---medical student, public medical college They also mentioned that when a physician drops out, it is an economic loss to the country given the investment required to produce a doctor. One of the in-service trainee physician mentioned: “Now we see that females are being admitting more in the medical colleges, but at the end of the day, they are dropping out more. It is a waste . A lot of good doctors are not going into career… dropping out will create a gap in the health sector.” An in-service trainee physician explained the scenario in detail: “I think females drop out more . Females have many kinds of bindings . Most females get married during their internship . So once they get into the family life , a lot of things they have to compromise , and eventually the study is hampered . Sometimes it is seen that the subject or career that she wants to choose is not possible because of family , then she opt for more traditional subjects such as Obstetrics and Gynaecology . Some families don’t want the females to pursue career . That’s why I think females flourish more during undergraduate level , but do not do that well in post-graduation . ” Another in-service trainee physician presented the issue of drop-out differently: “I think , first of all , females need to change their own mentalities . Females have to be strong willed to pursue their own career and establish in life and manage both family and social aspects as well … so that females can pursue their dreams and not drop out” .
This study was done to explore the emerging phenomenon of ‘feminization’ of the physician workforce in Bangladesh including its underlying reasons and the challenges it pose to their professional and family lives. Besides, the health system implications of this phenomenon such as problems with rural deployment and retention, system loss (attrition), and shortage of faculty in certain pre- and para-clinical medical subjects were also investigated. These issues are discussed thematically against the backdrop of the evidence presented including its implications for HRH planning in future. Implications of privatization of medical education after 2000: Money mattered more than merit Beginning 2000, medical education began to be privatized officially in Bangladesh and recognized by the Bangladesh Medical and Dental Council (BMDC), the regulatory body for approval and licensing medical colleges. Currently there are 69 approved private medical colleges in the country (out of total 105 in the public and private sector) offering 63% of total available seats. The private medical colleges charge exorbitant tuition and other fees, almost 100 times higher than the public medical colleges. Interestingly in the early years, these colleges did not have to follow stringent admission criteria like those for the public medical colleges. Thus, any student with science and affluent family background got admitted. This is also reflected in the findings which show that the students from the private medical colleges were mostly coming from affluent families compared to public medical colleges, plausibly so because of the high tuition and other fees charged by the former . Again, data in the study reveal that high probability of climbing up the social ladder, high social value and prestige of the profession, better prospects in the marriage market, and opportunity to fulfill ‘dreams of the parents’ by money if not by merit were some of the key underlying reasons. This is consistent with what have been observed in other countries as well . It may be mentioned here that the admission criteria has changed over the last ten years. Now, all aspiring students of science background irrespective of gender or other characteristics, and securing a combined minimum score from the secondary and higher secondary school examinations (total 12 years of education) have to undergo a uniform, centralized admission test. There is a minimum cut off score (for quality control) to be eligible for admission, and the students are ranked according to merit based on scores in the admission test. Again, the medical colleges are also ranked, the public over the private, starting from the best one in the public to the last one in the private sector. The students get selected based on their score and preferences. Thus, there is no barrier for females to get admitted in the public or private medical colleges as it depends on their merit ranking. However, only students who are at the top of merit ranking (usually the first 3,000) can get admitted to the public medical colleges. After all the allocated seats in the public medical colleges are filled up, the rest of the students become eligible to get admitted in the private medical colleges based upon merit ranking. But the catch is: only those who are financially solvent to pay the high admission fees in these colleges can get admitted. So, there is the possibility (and it practically happens) that students with lower merit ranking in the test but from wealthier family have a greater chance of being admitted. These students may be females in greater number, for reasons mentioned above. Motivational factors for female medical students: Financial security and job security are not the whole story Serving a noble profession was mentioned by the overwhelming majority of female respondents, overriding issues such as financial or job security. This may be due to the fact that in patriarchal societies like Bangladesh, financial responsibility for raising and maintaining a family is viewed as the sole purview of men . So, it is assumed that women are less concerned about financial return from the profession unlike their male peers. This was reiterated by the parents’ expressed preference to the perceived altruistic nature of the profession. In the developing countries, altruism has been proposed as a way to improve the performance of the nursing students ; the same can be experimented in case of medical profession as well. Similar findings were also noted in the OECD regions where helping people was the most important factor for motivating the female medical students to take up the profession . Health system implications of ‘feminization’ of medical workforce: Problems of ‘system loss’, rural deployment, and shortage of faculty in pre- and para-clinical subjects In a conservative society like Bangladesh, the need of female physicians cannot be over emphasized. Interestingly enough, the greater proportion of female medical students do not correspond with the proportion of female physicians who are currently active in the profession, as mentioned in the interviews. In the process, many ‘drop out’ and become ‘inactive’, reducing the pool of available physicians on which the health system can draw. We need more detailed data on this ‘system loss’ over time to gauge the exact magnitude of the problem and plan for future medical workforce. The gender equality and equity aspect play a big role in the drop out from medical workforce. Gender equality refers to women having equal opportunity and access to resources as men and gender equity about being fair in terms of professional opportunity irrespective of men and women . The societal belief about the appropriate role for men and women dictates fairness and justice in the professional working structure which sheds light on the disproportion that exists between the number of women in medical education and the number of women in power . Studies show that even though more and more women are coming into medical profession, the socio-cultural norms related to gender roles and expectations of a male-dominated society assume that they are primarily responsible for maintaining home and family life. As such, balancing work and personal life as well as career advancement is a great challenge for women in the medical profession, if necessary support does not come from the family . Besides, the long time required to build an expertise and career in medical profession, while maintaining family, becomes untenable for the female physicians who often fail to reach the leadership position . Combination of these factors sometimes compels a substantial proportion of female physicians to’ drop out’ of the system and become ‘inactive’. This ‘system loss’ from health sector is not uncommon and has also been observed in other countries, for example Pakistan and Japan . Regrettably, the gender norms and attitudes of patriarchal society like that of Bangladesh are not always conducive for a woman to take up rural postings. Personal security concerns in the workplace especially in the rural areas, lack of women-friendly work environment, and problems with work-life balance are some of the underlying reasons which discourage them to take up rural postings and remain in the system. The personal security at workplace is an overwhelming issue for all female health care providers (doctors, nurses), especially for those working in the public sector . This situation makes it challenging for the female physicians to remain in rural postings for long , which is also observed in India . The situation may further exacerbate in future as more and more women will graduate from the medical schools in the coming days. Another concern is the propensity of female physicians to develop career in a few specific clinical specialties, thus contributing to the current situation of shortage of required faculty e.g., in the pre- and para-clinical subjects. Currently, the country fills only 25% of the allocated posts of teachers required for basic medical subjects . Similar situation is also observed in India where females are entering the medical schools in greater numbers, but their representation in different academic sub-specialties are not proportional . Limitations of the study First and foremost, this paper originated from a student project conducted for fulfilling partial requirement of an MPH course, and thus constrained with respect to time and resources. Thus, the findings may not be generalisable for the rest of the female medical students, in-service trainees and physicians in Bangladesh. However, trend analysis of the physician data over time confirmed the emerging ‘female face’ of the physician workforce in the country. Using mixed methods data, this exploratory study presents a fair picture of the scenario and provides insights on motivation of females for enrolling in medical education, challenges of the profession in a not-so-friendly work environment, and subsequent impact on the health systems. For a comprehensive picture of ‘feminization’, further studies are needed using a nationally representative sample and time series data, and more qualitative studies to document their coping and surviving strategies in the system over time, and how these impact on health systems.
Beginning 2000, medical education began to be privatized officially in Bangladesh and recognized by the Bangladesh Medical and Dental Council (BMDC), the regulatory body for approval and licensing medical colleges. Currently there are 69 approved private medical colleges in the country (out of total 105 in the public and private sector) offering 63% of total available seats. The private medical colleges charge exorbitant tuition and other fees, almost 100 times higher than the public medical colleges. Interestingly in the early years, these colleges did not have to follow stringent admission criteria like those for the public medical colleges. Thus, any student with science and affluent family background got admitted. This is also reflected in the findings which show that the students from the private medical colleges were mostly coming from affluent families compared to public medical colleges, plausibly so because of the high tuition and other fees charged by the former . Again, data in the study reveal that high probability of climbing up the social ladder, high social value and prestige of the profession, better prospects in the marriage market, and opportunity to fulfill ‘dreams of the parents’ by money if not by merit were some of the key underlying reasons. This is consistent with what have been observed in other countries as well . It may be mentioned here that the admission criteria has changed over the last ten years. Now, all aspiring students of science background irrespective of gender or other characteristics, and securing a combined minimum score from the secondary and higher secondary school examinations (total 12 years of education) have to undergo a uniform, centralized admission test. There is a minimum cut off score (for quality control) to be eligible for admission, and the students are ranked according to merit based on scores in the admission test. Again, the medical colleges are also ranked, the public over the private, starting from the best one in the public to the last one in the private sector. The students get selected based on their score and preferences. Thus, there is no barrier for females to get admitted in the public or private medical colleges as it depends on their merit ranking. However, only students who are at the top of merit ranking (usually the first 3,000) can get admitted to the public medical colleges. After all the allocated seats in the public medical colleges are filled up, the rest of the students become eligible to get admitted in the private medical colleges based upon merit ranking. But the catch is: only those who are financially solvent to pay the high admission fees in these colleges can get admitted. So, there is the possibility (and it practically happens) that students with lower merit ranking in the test but from wealthier family have a greater chance of being admitted. These students may be females in greater number, for reasons mentioned above.
Serving a noble profession was mentioned by the overwhelming majority of female respondents, overriding issues such as financial or job security. This may be due to the fact that in patriarchal societies like Bangladesh, financial responsibility for raising and maintaining a family is viewed as the sole purview of men . So, it is assumed that women are less concerned about financial return from the profession unlike their male peers. This was reiterated by the parents’ expressed preference to the perceived altruistic nature of the profession. In the developing countries, altruism has been proposed as a way to improve the performance of the nursing students ; the same can be experimented in case of medical profession as well. Similar findings were also noted in the OECD regions where helping people was the most important factor for motivating the female medical students to take up the profession .
In a conservative society like Bangladesh, the need of female physicians cannot be over emphasized. Interestingly enough, the greater proportion of female medical students do not correspond with the proportion of female physicians who are currently active in the profession, as mentioned in the interviews. In the process, many ‘drop out’ and become ‘inactive’, reducing the pool of available physicians on which the health system can draw. We need more detailed data on this ‘system loss’ over time to gauge the exact magnitude of the problem and plan for future medical workforce. The gender equality and equity aspect play a big role in the drop out from medical workforce. Gender equality refers to women having equal opportunity and access to resources as men and gender equity about being fair in terms of professional opportunity irrespective of men and women . The societal belief about the appropriate role for men and women dictates fairness and justice in the professional working structure which sheds light on the disproportion that exists between the number of women in medical education and the number of women in power . Studies show that even though more and more women are coming into medical profession, the socio-cultural norms related to gender roles and expectations of a male-dominated society assume that they are primarily responsible for maintaining home and family life. As such, balancing work and personal life as well as career advancement is a great challenge for women in the medical profession, if necessary support does not come from the family . Besides, the long time required to build an expertise and career in medical profession, while maintaining family, becomes untenable for the female physicians who often fail to reach the leadership position . Combination of these factors sometimes compels a substantial proportion of female physicians to’ drop out’ of the system and become ‘inactive’. This ‘system loss’ from health sector is not uncommon and has also been observed in other countries, for example Pakistan and Japan . Regrettably, the gender norms and attitudes of patriarchal society like that of Bangladesh are not always conducive for a woman to take up rural postings. Personal security concerns in the workplace especially in the rural areas, lack of women-friendly work environment, and problems with work-life balance are some of the underlying reasons which discourage them to take up rural postings and remain in the system. The personal security at workplace is an overwhelming issue for all female health care providers (doctors, nurses), especially for those working in the public sector . This situation makes it challenging for the female physicians to remain in rural postings for long , which is also observed in India . The situation may further exacerbate in future as more and more women will graduate from the medical schools in the coming days. Another concern is the propensity of female physicians to develop career in a few specific clinical specialties, thus contributing to the current situation of shortage of required faculty e.g., in the pre- and para-clinical subjects. Currently, the country fills only 25% of the allocated posts of teachers required for basic medical subjects . Similar situation is also observed in India where females are entering the medical schools in greater numbers, but their representation in different academic sub-specialties are not proportional .
First and foremost, this paper originated from a student project conducted for fulfilling partial requirement of an MPH course, and thus constrained with respect to time and resources. Thus, the findings may not be generalisable for the rest of the female medical students, in-service trainees and physicians in Bangladesh. However, trend analysis of the physician data over time confirmed the emerging ‘female face’ of the physician workforce in the country. Using mixed methods data, this exploratory study presents a fair picture of the scenario and provides insights on motivation of females for enrolling in medical education, challenges of the profession in a not-so-friendly work environment, and subsequent impact on the health systems. For a comprehensive picture of ‘feminization’, further studies are needed using a nationally representative sample and time series data, and more qualitative studies to document their coping and surviving strategies in the system over time, and how these impact on health systems.
The emerging phenomenon of ‘feminization’ of physician workforce has thrown a new challenge before the health system of Bangladesh. The policy makers and practitioners should be cognizant of this, and plan and implement appropriate remedial measures for creating an enabling environment to attract and retain them in the system. The flip side of the coin is the fact that this phenomenon may affect the health system of Bangladesh in a positive direction by increasing its responsiveness because female physicians are found to take better care of patients compared to their male colleagues . Also, pro-active measures are needed for increasing the pool of female specialists in the pre- and para-clinical subjects to cater to increasing needs of the newly established medical, nursing and paramedic institutions in the country.
S1 File Survey questionnaire. (DOCX) Click here for additional data file. S2 File Qualitative guidelines. (DOCX) Click here for additional data file. S3 File Quantitative dataset. (DTA) Click here for additional data file.
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Taxonomic response of bacterial and fungal populations to biofertilizers applied to soil or substrate in greenhouse-grown cucumber | 7eada87e-01da-4510-ad0f-fc12f1b34819 | 9630312 | Microbiology[mh] | Cucumber is an important vegetable crop that is extensively grown and consumed worldwide. Almost 2 Mha were used worldwide to produce about 75 Mt of cucumber in 2018 . China is one of the main countries that produces cucumber. The total cucumber production in China in 2018 was about 56 Mt on about 1 Mha, equivalent to about 53 and 75% of the global quantity and area, respectively . Soil-borne diseases such as Fusarium wilt and root-knot nematodes (RKN, Meloidogyne spp.) significantly decrease cucumber yield and quality by accumulating in the same soil used to produce crops every year , . Those pathogens when left uncontrolled can affect large production areas and thereby significantly limit cucumber production, quality, and expansion of the industry. Soil microorganisms play an indispensable role in the growth and development of plants. They are crucial for the decomposition and transformation of organic matter in the soil, including the degradation of animal and plant residues, the decomposition of humus and the recycling and utilization of nutrients, and even the degradation and purification of organic pollutants , . The growth and quality of cucumbers can also be due to the relative abundance of rhizosphere microorganisms . Plant disease has been correlated with changes in the soil microecology that favors plant pathogens . Excessive dependence on chemical fertilizers to increase crop yield in industrial-scale agricultural production has damaged the environment and harmed human health . Chemical fertilizers can replace biofertilizers which contain beneficial microorganisms that can enhance crop production without harm to human health , . Nutrients and beneficial microflora contained in biofertilizers have led to improved crop production and quality , . They have been reported to reduce ecological degradation and suppress soil-borne diseases . Beneficial microorganisms such as Trichoderma harzianum and Bacillus subtilis in biofertilizers promoted colonization by other microbes, inhibited pathogens, and induced plant systemic resistance to disease . Trichoderma is a commercially-available biocontrol fungal agent applied to soil to control soil-borne pathogens and improve crop growth. Trichoderma exhibits several useful properties including mycoparasitism , absorption of nutrients, good colonization ability , production of antibiotic substances and promotion of plant systemic resistance to pathogens , . Trichoderma stimulated the yield and promoted the establishment of communities of beneficial soil microflora, thereby improving soil microbial activity and enhancing soil fertility . Bacillus is very common bacterium that significantly promoted plant growth and crop yield . Bacillus stimulated synthesis of auxin in plants, and formed endospores and different biologically active compounds important for the biocontrol of plant pathogens , . Substrates can reduce pathogens accumulating in soil-based crops that are continually produced in the same location for many years . Many substrates used in commercial production are not recycled and some were obtained from non-renewable resources, both of which are inconsistent with best-practice sustainable crop production. There is therefore an urgent need to find and implement substrates from renewable resources that are recyclable. Rhizosphere microorganisms present in substrates were not only the driving force for organic nutrient transformation , but also their structure and abundance affected plant growth and development . Exploring the effects of exogenous microbial agents on cucumber yield, quality and rhizosphere environment in substrates has important theoretical and practical significance for improving substrate production and their use. We found no reports of microbial taxonomic changes in response to biofertilizers added to soil or substrates. Our research therefore aimed to: (1) Determine and compare the effects of different microbial fertilizers on the growth of cucumber plants grown in soil or substrate; (2) Determine the effect on the taxonomic structure and function of bacterial and fungal populations exposed to different microbial fertilizers continually applied to soil or substrates; (3) Determine and compare the responses of soil-borne pathogens exposed to different microbial fertilizers in soil or substrates; and (4) Determine cucumber yield in response cucumber plants grown in soil or substrates exposed to different microbial fertilizers.
Greenhouse location In 2021, a large greenhouse in the Changping district of Beijing (GPS: 40° 22′ N, 116° 23′ E) was selected for the research trials. Cucumbers had been continually produced in the greenhouse since 2016. The main components of the substrate include: peat, coconut bran, perlite, vermiculite, and rice husk. The basic physicochemical characteristics of the soil and substrate were shown in Table . Biofertilizers Preparation of Trichoderma spore suspension Trichoderma afroharzianum 267 strain (‘Strain 267’) had been identified and stored in our laboratory since 2019. Strain 267 was cultured on PDA for 5 days, and then the spore suspension was washed with sterilized and distilled water before being filtered through 4-layer gauze. The concentration of the spore suspension was adjusted to 1.0 ± 0.05 × 10 7 spores/mL using a hemocytometer. Commercial microbial fertilizers Bacillus subtilis (BS) or T. harzianum (HZ) biofertilizers were sourced from Hainan Jin Yufeng Biological Engineering Co., Ltd., China. A compound microbial fertilizer (M) with several kinds of functional bacteria was sourced from Inner Mongolia Shengtian Agricultural Technology Co., Ltd. (Mongolia). Field experiment design Cucumber seedlings grown from seed (Jingyou 4, Beijing Wanlongyufeng Seed Co., Ltd., China) were transplanted to soil in the greenhouse in early May 2021. The area of each plot was 1.2 m wide × 25 m long. Six biofertilizer treatments in soil (S) were coded as: Strain 267 (S267), B. subtilis (SBS), B. subtilis / T . harzianum (SBH), compound microbial fertilizer (SM), T . harzianum (SHZ) and control (SCK). Six treatments in substrate (US) were similarly coded: US267, USBS, USBH, USM, USHZ, USCK. The 12 treatments were diluted with deionized water and established in plots following a random block design. The biofertilizers were applied 2, 3 or 4 weeks after the cucumber seedlings were planted in the greenhouse. Cucumber roots were treated with 50 mL/plant of Trichoderma spore suspension (1.0 ± 0.05 × 10 7 spores/mL, treatment 1: Strain 267). Four further commercial biofertilizer treatments were applied to the cucumber seedling roots that comprised 72 mL of B. subtilis biofertilizer diluted 400 times (Treatment 2: BS); 36 mL of B. subtilis and 20 g T. harzianum biofertilizer diluted 400 times (Treatment 3: BH); 72 mL of compound microbial fertilizer diluted 400 times (Treatment 4: M); 40 g of T. harzianum biofertilizer diluted 400 times (Treatment 5: HZ). A sixth treatment was the control consisting of deionized water added to soil and substrate (Treatment 6: CK). Each treatment was replicated 3 times with 100 cucumber seedlings in each replicate. Sample collection Soil and substrate were sampled from each treatment 2–20 cm deep on day 7 after the third application of biofertilizer and when the cucumber plants were uprooted. Soil samples were refrigerated at − 80 and 4 ℃ for later analysis of taxonomic changes in the microbial community and soil-borne pathogens. Soil and substrate physicochemical properties A Futura Continuous Flow Analytical System (Alliance Instruments, France) was used to quantify ammonia nitrogen (NH 4 + –N) and nitrate nitrogen (NO 3– N) concentrations in each soil sample. The available phosphorus (P) was determined according to the method described by Olsen et al. . Available potassium (K) was determined using a FP640 Flame Photometer (Shanghai Instruments Group Co., Ltd., China). The organic matter (OM) content was quantified according to the K 2 Cr 2 O 7 –H 2 SO 4 oxidation reduction method described by Schinner et al. . A MP512-02 Precision Water Meter was used to measure the pH of the soil sample (Shanghai Sanxin Instrumentation, Inc., China). A MP513 Conductivity Meter was used to determine the electrical conductivity (EC) (Shanghai Sanxin Instrumentation, Inc., China) of the soil. Cucumber growth, yield, and soil-borne pathogens Cucumber height and stem diameter were measured every 7 days from the day the seedlings were transplanted. The total marketable yield of cucumber from each treatment was recorded in kg at each harvest. Selective medium methods were used to isolate colonies of Fusarium spp. and Phytophthora spp. in the soil, and to calculate their abundance following the methods described by Komada and Masago , respectively. Extraction of soil and substrate DNA, and PCR amplification Ten grams of soil or substrate were homogenized in 40 mL of sterile water. The homogenate was then filtered through two layers of sterile medical gauze. The gauze was rinsed several times with sterile water to recover residual microorganisms. The filtrate was centrifuged at 10,000–12,000 g at 4 ℃ for 15 min. The total soil and substrate DNA was extracted from each 0.25 g soil and substrate sample following the procedures described in the DNeasy Power Soil Pro Kit (Qiagen Com., China). The extracted DNA was plated out onto 1% agarose gel for electrophoresis, and then the DNA concentration measured using a NanoDrop ND-1000 UV–Vis Spectrophotometer (Thermo Fisher Scientific Inc., USA). The bacterial universal primers 338F [5′-ACTCCTACGGAGCAGGCAG-3′] and 806R [5′-GGACTACHGGGGTWTCTAAT-3′] , and the fungal universal primers ITS1F [5′-CTTGGTCATAGAGGAGTAA-3′] and ITS2R [5′-GCTGCTATCGATGC-3′] , were used to amplify the V3-V4 region of bacteria and the ITS1-ITS2 region of fungi, respectively. PCR products were detected by gel electrophoresis (plated out on 2% agarose) and purified using the EasyPure Quick Gel Extraction Kit (TransGen Biotech Co. Ltd., China) and quantified using the QuantiFluor dsDNA System (Fisher Scientific, USA). High-throughput sequencing The purified PCR products were sequenced at Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China) and the microbial analyses were conducted using the MiSeq PE300 sequencing platform (Illumina Com., USA). The raw sequences were processed using the Mothur software (Version 1.30.2 https://www.mothur.org/wiki/Download_mothur ). Sequences with less than 50 bp, ambiguous bases and those with an average mass less than 20 were removed by FLASH (Version 1.2.11 https://ccb.jhu.edu/software/FLASH/index.shtml ) and Trimmomatic (Version 0.39 http://www.usadellab.org/cms/?page=trimmomatic ) software to obtain the effective sequences . Usearch (Version 7.1 http://drive5.com/uparse/ ) software was used to cluster sequences with 97% similarity into Operational Taxonomic Units (OTUs). Qiime software (Version1.9.1 http://qiime.org/install/index.html ) and Unit database (V7.2 https://unite.ut.ee/ ) were used for species annotation analysis and sample community composition analysis . Qiime software (Version 1.9.1) was used to calculate the richness of the flora (Chao1 index, Shannon index) and the diversity of the flora (Simpson index, Ace index). R software (Version 2.15.3 https://cran.r-project.org/doc/FAQ/R-FAQ.html#Citing-R ) was used to draw the dilution curve and bar diagrams of species at genus level . Statistical analysis The efficacy of the treatments on soil-borne pathogens was calculated using this formula: [12pt]{minimal}
$${} = - X_{1} }}{{X_{0} }} 100$$ Y = X 0 - X 1 X 0 × 100 where Y is the relative efficacy on soil-borne pathogens (%), X 0 is the colony number of soil-borne pathogens in the control group, and X 1 is the colony number of soil-borne pathogens in treatment group. The data were analyzed as a one-way ANOVA using the IBM SPSS Statistics 25 software package (IBM, USA). Before the one-way ANOVA, we performed the Normal distribution test and the homogeneity of variance test (F-test) with the IBM SPSS Statistics 25 software package (IBM, USA), and the raw data met the conditions of ANOVA. Significant differences between treatments were identified using Duncan's new multiple range test at the 0.05 level of significance. All treatments were compared with the control, except where specifically stated. A statement on guidelines Plants experiments in our study complies with the the People's Republic of China plant Bank guideline and legislation.
In 2021, a large greenhouse in the Changping district of Beijing (GPS: 40° 22′ N, 116° 23′ E) was selected for the research trials. Cucumbers had been continually produced in the greenhouse since 2016. The main components of the substrate include: peat, coconut bran, perlite, vermiculite, and rice husk. The basic physicochemical characteristics of the soil and substrate were shown in Table .
Preparation of Trichoderma spore suspension Trichoderma afroharzianum 267 strain (‘Strain 267’) had been identified and stored in our laboratory since 2019. Strain 267 was cultured on PDA for 5 days, and then the spore suspension was washed with sterilized and distilled water before being filtered through 4-layer gauze. The concentration of the spore suspension was adjusted to 1.0 ± 0.05 × 10 7 spores/mL using a hemocytometer. Commercial microbial fertilizers Bacillus subtilis (BS) or T. harzianum (HZ) biofertilizers were sourced from Hainan Jin Yufeng Biological Engineering Co., Ltd., China. A compound microbial fertilizer (M) with several kinds of functional bacteria was sourced from Inner Mongolia Shengtian Agricultural Technology Co., Ltd. (Mongolia).
Trichoderma spore suspension Trichoderma afroharzianum 267 strain (‘Strain 267’) had been identified and stored in our laboratory since 2019. Strain 267 was cultured on PDA for 5 days, and then the spore suspension was washed with sterilized and distilled water before being filtered through 4-layer gauze. The concentration of the spore suspension was adjusted to 1.0 ± 0.05 × 10 7 spores/mL using a hemocytometer.
Bacillus subtilis (BS) or T. harzianum (HZ) biofertilizers were sourced from Hainan Jin Yufeng Biological Engineering Co., Ltd., China. A compound microbial fertilizer (M) with several kinds of functional bacteria was sourced from Inner Mongolia Shengtian Agricultural Technology Co., Ltd. (Mongolia).
Cucumber seedlings grown from seed (Jingyou 4, Beijing Wanlongyufeng Seed Co., Ltd., China) were transplanted to soil in the greenhouse in early May 2021. The area of each plot was 1.2 m wide × 25 m long. Six biofertilizer treatments in soil (S) were coded as: Strain 267 (S267), B. subtilis (SBS), B. subtilis / T . harzianum (SBH), compound microbial fertilizer (SM), T . harzianum (SHZ) and control (SCK). Six treatments in substrate (US) were similarly coded: US267, USBS, USBH, USM, USHZ, USCK. The 12 treatments were diluted with deionized water and established in plots following a random block design. The biofertilizers were applied 2, 3 or 4 weeks after the cucumber seedlings were planted in the greenhouse. Cucumber roots were treated with 50 mL/plant of Trichoderma spore suspension (1.0 ± 0.05 × 10 7 spores/mL, treatment 1: Strain 267). Four further commercial biofertilizer treatments were applied to the cucumber seedling roots that comprised 72 mL of B. subtilis biofertilizer diluted 400 times (Treatment 2: BS); 36 mL of B. subtilis and 20 g T. harzianum biofertilizer diluted 400 times (Treatment 3: BH); 72 mL of compound microbial fertilizer diluted 400 times (Treatment 4: M); 40 g of T. harzianum biofertilizer diluted 400 times (Treatment 5: HZ). A sixth treatment was the control consisting of deionized water added to soil and substrate (Treatment 6: CK). Each treatment was replicated 3 times with 100 cucumber seedlings in each replicate.
Soil and substrate were sampled from each treatment 2–20 cm deep on day 7 after the third application of biofertilizer and when the cucumber plants were uprooted. Soil samples were refrigerated at − 80 and 4 ℃ for later analysis of taxonomic changes in the microbial community and soil-borne pathogens.
A Futura Continuous Flow Analytical System (Alliance Instruments, France) was used to quantify ammonia nitrogen (NH 4 + –N) and nitrate nitrogen (NO 3– N) concentrations in each soil sample. The available phosphorus (P) was determined according to the method described by Olsen et al. . Available potassium (K) was determined using a FP640 Flame Photometer (Shanghai Instruments Group Co., Ltd., China). The organic matter (OM) content was quantified according to the K 2 Cr 2 O 7 –H 2 SO 4 oxidation reduction method described by Schinner et al. . A MP512-02 Precision Water Meter was used to measure the pH of the soil sample (Shanghai Sanxin Instrumentation, Inc., China). A MP513 Conductivity Meter was used to determine the electrical conductivity (EC) (Shanghai Sanxin Instrumentation, Inc., China) of the soil.
Cucumber height and stem diameter were measured every 7 days from the day the seedlings were transplanted. The total marketable yield of cucumber from each treatment was recorded in kg at each harvest. Selective medium methods were used to isolate colonies of Fusarium spp. and Phytophthora spp. in the soil, and to calculate their abundance following the methods described by Komada and Masago , respectively.
Ten grams of soil or substrate were homogenized in 40 mL of sterile water. The homogenate was then filtered through two layers of sterile medical gauze. The gauze was rinsed several times with sterile water to recover residual microorganisms. The filtrate was centrifuged at 10,000–12,000 g at 4 ℃ for 15 min. The total soil and substrate DNA was extracted from each 0.25 g soil and substrate sample following the procedures described in the DNeasy Power Soil Pro Kit (Qiagen Com., China). The extracted DNA was plated out onto 1% agarose gel for electrophoresis, and then the DNA concentration measured using a NanoDrop ND-1000 UV–Vis Spectrophotometer (Thermo Fisher Scientific Inc., USA). The bacterial universal primers 338F [5′-ACTCCTACGGAGCAGGCAG-3′] and 806R [5′-GGACTACHGGGGTWTCTAAT-3′] , and the fungal universal primers ITS1F [5′-CTTGGTCATAGAGGAGTAA-3′] and ITS2R [5′-GCTGCTATCGATGC-3′] , were used to amplify the V3-V4 region of bacteria and the ITS1-ITS2 region of fungi, respectively. PCR products were detected by gel electrophoresis (plated out on 2% agarose) and purified using the EasyPure Quick Gel Extraction Kit (TransGen Biotech Co. Ltd., China) and quantified using the QuantiFluor dsDNA System (Fisher Scientific, USA).
The purified PCR products were sequenced at Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China) and the microbial analyses were conducted using the MiSeq PE300 sequencing platform (Illumina Com., USA). The raw sequences were processed using the Mothur software (Version 1.30.2 https://www.mothur.org/wiki/Download_mothur ). Sequences with less than 50 bp, ambiguous bases and those with an average mass less than 20 were removed by FLASH (Version 1.2.11 https://ccb.jhu.edu/software/FLASH/index.shtml ) and Trimmomatic (Version 0.39 http://www.usadellab.org/cms/?page=trimmomatic ) software to obtain the effective sequences . Usearch (Version 7.1 http://drive5.com/uparse/ ) software was used to cluster sequences with 97% similarity into Operational Taxonomic Units (OTUs). Qiime software (Version1.9.1 http://qiime.org/install/index.html ) and Unit database (V7.2 https://unite.ut.ee/ ) were used for species annotation analysis and sample community composition analysis . Qiime software (Version 1.9.1) was used to calculate the richness of the flora (Chao1 index, Shannon index) and the diversity of the flora (Simpson index, Ace index). R software (Version 2.15.3 https://cran.r-project.org/doc/FAQ/R-FAQ.html#Citing-R ) was used to draw the dilution curve and bar diagrams of species at genus level .
The efficacy of the treatments on soil-borne pathogens was calculated using this formula: [12pt]{minimal}
$${} = - X_{1} }}{{X_{0} }} 100$$ Y = X 0 - X 1 X 0 × 100 where Y is the relative efficacy on soil-borne pathogens (%), X 0 is the colony number of soil-borne pathogens in the control group, and X 1 is the colony number of soil-borne pathogens in treatment group. The data were analyzed as a one-way ANOVA using the IBM SPSS Statistics 25 software package (IBM, USA). Before the one-way ANOVA, we performed the Normal distribution test and the homogeneity of variance test (F-test) with the IBM SPSS Statistics 25 software package (IBM, USA), and the raw data met the conditions of ANOVA. Significant differences between treatments were identified using Duncan's new multiple range test at the 0.05 level of significance. All treatments were compared with the control, except where specifically stated.
Plants experiments in our study complies with the the People's Republic of China plant Bank guideline and legislation.
All the results were reported relative to the control, unless specifically stated to the contrary or for clarity. Growth of cucumber plants in response to different biofertilizers Soil There was no significant difference in cucumber growth before microbial fertilizer was applied. However, some microbial fertilizers significantly increased cucumber height and stem diameter when they were applied within 4 weeks from when the seedlings were planted (Fig. a,b,e,f). In the second week, SHZ and SMF increased plant height by 11.2 and 9.5%, respectively. In the third week, S267, SBS, SBH, SM and SHZ increased plant height by 12.0, 13.8, 15.0, 20.5 and 26.9%, respectively (Fig. a). In the fourth and fifth weeks, some treatments significantly increased cucumber height. In the second and third weeks, S267 significantly increased stem diameter by 21.2 and 16.8% (Fig. b). Over the subsequent 5 weeks, some microbial fertilizer treatments decreased cucumber height and stem diameter (Fig. g,h). Substrate There were no significant differences in cucumber growth before microbial fertilizer microbial fertilizer was applied (Fig. c,d,g,h). However, within 4 weeks of applying the microbial fertilizer, each biofertilizer treatment applied significantly increased cucumber height (Fig. c). US267 and USHZ significantly increased cucumber height by 39.8–75.4% and 56.1–86.1%, respectively. US267, USM and USHZ significantly increased the stem diameter by 76.8–108.9%, 71.1–97.6% and 80.4–122.4%, respectively (Fig. d). Over the subsequent 5 weeks, US267, USM and USHZ treatments continued to significantly increase cucumber height and stem diameter (Fig. g,h). Changes in the taxonomic composition of soil-borne fungal pathogens Soil Biofertilizers application significantly reduced the taxonomic composition of soil-borne fungal pathogens at different times during the cucumber growth period (Tables and ). Fusarium spp. were significantly reduced (T, 63.8% reduction, P < 0.001) after the third application of T. harzianum , which was during the early period ofgrowth (Table ). Phytophthora spp. was significantly reduced (T, 81.6% reduction, P < 0.001) by Strain 267. Fusarium spp. and Phytophthora spp. were significantly reduced by S267, SBS and SHZ. When the cucumber were uprooted during the later period of growth, we observed that SBS, SHZ and S267 treatments had significantly reduced Fusarium spp. and Phytophthora spp. Therefore, S267, SBS and SHZ treatments were considered as the most effective biofertilizers against Fusarium spp. or Phytophthora spp. Strain 267, BS, and HZ effectively controlled soil-borne pathogens. However, the effect of T. 267 and HZ decreased during the late growth stage of cucumber. Substrate Fusarium spp. was significantly reduced (T, 87.5% reduction, P < 0.001) after the third application of USBS, which was during the early period of growth (Table ). Phytophthora spp. was significantly reduced (T, 81.6% reduction, P < 0.001) by strain 267. Fusarium spp. and Phytophthora spp. were significantly reduced by US267, USBS and USHZ. At the time the cucumberwere uprooted during the later period of growth, each treatment had significantly reduced Fusarium spp. by more than 60%. In addition, Phytophthora spp. was significantly reduced (T, 47.9% reduction, P < 0.001) by US267. Therefore, US267, USBS and USHZ treatments were considered as the most effective treatments against Fusarium spp. and Phytophthora spp. Strain 267, BS, and HZ effectively controlled soil-borne pathogens. The effect of T. 267 and HZ increased during the late growth stage of cucumber. Changes in cucumber yield Some treatments significantly increased cucumber yield after microbial fertilizer applications to plants grown in soil (Fig. ). S267, SBS, SM and SHZ significantly increased cucumber yield. S267 and SHZ significantly increased cucumber yield by 28.8 and 26.7%, respectively. US267, USM and USHZ significantly increased cucumber yield by 29.0, 26.5 and 27.4% when they were applied to seedlings grown on substrate (Fig. ). Taxonomic changes to bacterial and fungal populations in soil or substrate Diversity analysis of bacteria A total of 1,709,972 valid reads were obtained from 16S rRNA amplicon sequencing after trimming. The average length of the amplicon was 428 bp. The number of valid sequences detected for each soil sample exceeded 40,000. The sparse curve was flat, which indicated that the genetic data were sufficient for a reasonable estimate of the total taxonomic composition. Analysis of the microbial community diversity index in soil in response to the each biofertilizer treatment showed that the OTU diversity and richness were like the control (Fig. a,b,e,f). In the early stage of the cucumber growth period and after the third application of biofertilizer, and in the late stage of the cucumber growth period when the cucumber were uprooted, there were significant changes observed in the soil and substrate α diversity in the microbial community. In the early stage of cucumber growth, the Shannon diversity index in SBS increased significantly (Fig. a). However, in the late stage of cucumber growth, there was no significant difference in the Shannon diversity index (Fig. e). The Chao1 richness index increased significantly in SM (Fig. f). Analysis of the microbial community diversity index in substrate in response to each biofertilizer treatment showed that the OTU diversity and richness were significantly different to the control (Fig. c,d,g,h). In the early stage of cucumber growth, the Shannon diversity index decreased significantly in USBS, USBH and USHZ (Fig. c). However, the Shannon diversity index increased significantly in US267 and USM. The Chao richness index decreased significantly in USBH, USHZ and US267 (Fig. d). In the late stage of cucumber growth, the Shannon diversity index decreased significantly in USM (Fig. g). The Chao richness index increased significantly in USHZ and US267 (Fig. h). Bacterial hierarchical cluster analysis at the OTU level The results of hierarchical cluster analysis showed that different treatments had different effects on the taxonomic structure of microbes in the soil or substrate at different stages of cucumber plant growth (Fig. a–d). In the early stage of cucumber growth, the microbial communities exposed to SM and in the control were genetically close, compared with the other biofertilizer treatments, which indicated that the soil microbial community structure was changed more by the other biofertilizer treatments than SM (Fig. a). However, in the later stage of cucumber growth the five biofertilizer treatments were well-separated, which indicated that the microbial community structure was changed by the treatments (Fig. c). In the early stage of cucumber growth in substrates, the control bacterial taxa were well-separated from the five biofertilizer treatments (Fig. b). However, the five treatments and control were observed divided into two branches, one for US267 and the other for USCK, USBH, USBS, USM and USHZ. The structure of the microbial community was similar in USBH, USBS, USM and USHZ and the control. The results indicated that US267 had significantly changed the taxonomic structure of the bacterial community. In the late stage of cucumber growth, the five biofertilizer treatments and the control were observed as divided into two branches, one for USCK, USBS and USBH and the other for US267, USM and USHZ (Fig. d). The taxonomic structure of the microbial community was similar in the USBH and USBS to the control. The results indicated that US267, USM and USHZ had significantly changed the composition of the bacterial taxa. Changes in bacterial genera dominance In the early stage of cucumber growth, significant differences were observed in the relative abundance of bacterial genera after applying microbial fertilizer (Fig. a). MND1 was second only to Gaiella in dominance. The relative abundance of Planifilum also increased significantly at that time. In the late stage of cucumber growth, Ilumatobacter became second only to Microvirga in dominance (Fig. c). The relative abundance of Arthrobacter, Pedomicrobium, Dongia, Haliangium, and Devosia also increased significantly at that time. In the early stage of cucumber growth, Pseudolabrys was second only to Bacillus in dominance (Fig. b). The relative abundance of Flavobacterium, Sphingomonas and Pseudomonas also increased significantly. In the late stage of cucumber growth, Bacteroidota became second only to Actinobacteriota in dominance (Fig. d). Actinobacteriota increased significantly in USM and USHZ at that time. Bacteroidota decreased significantly in USBH and USHZ. The relative abundance of Firmicutes increased significantly. LEfSe analysis identified biomarkers that caused significant differences in control (P < 0.05, a, c, LDA = 3; b, d, LDA = 4.0; Fig. a,b,c,d). Fig. a,b,c,d showed five rings in the cladogram, from inside to outside, representing the phylum, class, order, family, and genus taxonomic levels, respectively. The different color nodes (except yellow) on the ring represent significant changes in taxonomic composition due to the biofertilizer treatments. The non-parametric factorial Kruskal–Wallis (KW) sum-rank test and Linear Discriminant Analysis (LDA) estimated the magnitude of the effect of each component (species) abundance on the differential effect. We observed that at the bacterial genus level some major taxa were screened out, which suggested that these biomarkers have the greatest impact on the results. In the early stage of cucumber growth in soil, 3, 1 and 1 biomarkers were found in S267, SBS and SCK, respectively. In the late stage of cucumber growth, 3, 3, 1, 3, 3 and 3 biomarkers were found in S267, SBS, SBH, SM, SHZ and SCK, respectively. In the early stage of cucumber growth in substrate, 1, 2 and 1 biomarkers were found in US267, USBS and USM, respectively. In the late stage of cucumber growth, 1, 1 and 1 biomarkers were found in US267, USBH and USHZ, respectively. The results indicated that g__norank_f__norank_o__ Gaiellales and g__ Blastococcus became prevalent when S267 was applied to the soil during the early stage of cucumber growth, and that g__ Paenibacillus became prevalent when SHZ was applied at the late stage of cucumber growth. LEfSe analysis confirmed that USBS significantly increased the abundance of the c__ Bacilli at the early stage of cucumber growth in substrate, and that US267 and USHZ significantly increased the abundance of p__ Patescibacteria and p__ Firmicutes , respectively, at the late stage of cucumber growth. Changes in fungal genera dominance A total of 1,859,284 valid reads were obtained from ITS rRNA amplicon sequencing after quality trimming. The average length of the amplicon was 321 bp. The number of valid sequences detected for each soil sample exceeded 40,000. The sparse curve was flat which indicated that the genetic data were sufficient for a reasonable estimate of the total taxonomic composition. We observed that the microbial community α diversity of soil in the early and late stages of cucumber growth changed significantly (Fig. a,b,e,f). In the early stage of cucumber growth, there were no significant differences in the diversity index of Shannon and the richness index of Chao (Fig. a,b). However, in the late stage of cucumber growth, the Shannon diversity index increased significantly in SBS, SHZ and SM (Fig. e). At the same time, the richness index of Chao decreased significantly in SBS (Fig. f). Analysis of the fungal diversity index treatment found that OTU diversity and richness was significantly different in response to each biofertilizer (Fig. c,d,g,h). In the early stage of cucumber growth, the Shannon diversity index decreased significantly in SBH, SHZ and SM (Fig. c). The richness index of Chao decreased significantly in SBS (Fig. d). In the late stage of cucumber growth, the Shannon diversity index increased significantly in S267, SBS, SBH and SM (Fig. g). We observed no significant differences in the richness index of Chao (Fig. h). Fungal hierarchical cluster analysis at the OTU level In the early stage of cucumber growth in soil, the taxonomic structure of the microbial community was similar in SBH, S267, SM and SHZ to the control (Fig. a). However, we observed that SBS significantly changed the fungal community. In the late stage of cucumber growth, microbial taxa in the SM and the control samples were genetically close compared with the other biofertilizer treatments, which indicated that the soil fungal taxonomic structure was changed more in the other biofertilizer treatments than in SM (Fig. c). In the early stage of cucumber growth in substrate, the control samples in the fungal community were clustered together and well-separated taxonomically from the five biofertilizer treatments (Fig. b). However, the five treatments and control were divided into one branch for USCK and the other branch comprising US267, USBH, USBS, USM and USHZ. These results indicated that the five treatments had significantly changed the fungal taxonomic composition. In the late stage of cucumber growth, however, the five treatments and control were divided into a branch for USCK, USBS, and USBH and another branch comprising US267, USM and USHZ (Fig. d). The structure of the microbial community was similar in USBS and the control. The results indicated that US267, USM and USHZ had significantly changed the taxonomic fungal composition in the community. Analysis of differences in fungal genera dominance We observed significant differences in the relative abundance of fungal genera in soil after microbial fertilizers were applied (Fig. a,c). In the early stage of cucumber growth, Trichoderma was second only to Aspergillus in dominance (Fig. a). The relative abundance of Plectosphaerella increased significantly in SBS. The relative abundance of Trichocladium increased significantly in response to all biofertilizers, whereas Stachybotrys decreased significantly. In the late stage of cucumber growth, Trichoderma was second only to Chaetomium in fungal dominance (Fig. c). The relative abundance of Chaetomium increased significantly in SM; Trichoderma increased significantly in S267 and SHZ; and Trichocladium increased significantly SHZ, SM and SBH. In general, the relative abundance of Neocosmospora and Schizothecium decreased significantly when exposed to all the biofertilizer treatments. We also observed significant differences in the relative abundance of fungal genera after microbial fertilizer were applied (Fig. b,d). In the early stage of cucumber growth, the relative abundance of Parascedosporium increased significantly in US267 and USM (Fig. b). The relative abundance of Mortierella and Cephalotheca decreased significantly compared to CK treatment. In the late stage of cucumber growth, the relative abundance of Ramophialophora increased significantly in USBH, USBS and USHZ (Fig. d). The relative abundance of Tausonia decreased significantly in USHZ. The relative abundance of Gibellulopsis decreased significantly in USBS and USBH. The relative abundance of Chaetomium increased significantly compared with the control in US267, USBH, USBS and USM. In the early and late stage of cucumber, Tausonia was second only to Ramophialophora in dominance. LEfSe analysis identified the biomarkers that caused significant differences in control (P < 0.05, a, c, LDA = 3; b, d, LDA = 4.0; Fig. a,b,c,d). We observed that the analyses screened out major taxa at the fungal genus level. In the early stage of cucumber growth in soil, 4, 1, 2, 2, 1 and 3 biomarkers were found in S267, SBH, SBS, SM, SHZ and SCK, respectively. In the late stage of cucumber growth, 5, 3, 10, 3, 7 and 3 biomarkers were found in S267, SBH, SBS, SHZ, SM and SCK, respectively. In the early stage of cucumber growth in substrate, 2, 2, 2, 3 and 2 biomarkers were found in US267, USBS, USM, USHZ and USCK, respectively. In the late stage of cucumber growth, 2, 1, 1, 2 and 5 biomarkers were found in US267, USBH, USM, USHZ and USCK, respectively. A large LDA score indicates a greater influence of species abundance on the difference effect. We observed that g_ Trichoderma had larger LDA values in S267 and US267, which indicated that g_ Trichoderma responded strongly to S267 and US267.
Soil There was no significant difference in cucumber growth before microbial fertilizer was applied. However, some microbial fertilizers significantly increased cucumber height and stem diameter when they were applied within 4 weeks from when the seedlings were planted (Fig. a,b,e,f). In the second week, SHZ and SMF increased plant height by 11.2 and 9.5%, respectively. In the third week, S267, SBS, SBH, SM and SHZ increased plant height by 12.0, 13.8, 15.0, 20.5 and 26.9%, respectively (Fig. a). In the fourth and fifth weeks, some treatments significantly increased cucumber height. In the second and third weeks, S267 significantly increased stem diameter by 21.2 and 16.8% (Fig. b). Over the subsequent 5 weeks, some microbial fertilizer treatments decreased cucumber height and stem diameter (Fig. g,h). Substrate There were no significant differences in cucumber growth before microbial fertilizer microbial fertilizer was applied (Fig. c,d,g,h). However, within 4 weeks of applying the microbial fertilizer, each biofertilizer treatment applied significantly increased cucumber height (Fig. c). US267 and USHZ significantly increased cucumber height by 39.8–75.4% and 56.1–86.1%, respectively. US267, USM and USHZ significantly increased the stem diameter by 76.8–108.9%, 71.1–97.6% and 80.4–122.4%, respectively (Fig. d). Over the subsequent 5 weeks, US267, USM and USHZ treatments continued to significantly increase cucumber height and stem diameter (Fig. g,h).
There was no significant difference in cucumber growth before microbial fertilizer was applied. However, some microbial fertilizers significantly increased cucumber height and stem diameter when they were applied within 4 weeks from when the seedlings were planted (Fig. a,b,e,f). In the second week, SHZ and SMF increased plant height by 11.2 and 9.5%, respectively. In the third week, S267, SBS, SBH, SM and SHZ increased plant height by 12.0, 13.8, 15.0, 20.5 and 26.9%, respectively (Fig. a). In the fourth and fifth weeks, some treatments significantly increased cucumber height. In the second and third weeks, S267 significantly increased stem diameter by 21.2 and 16.8% (Fig. b). Over the subsequent 5 weeks, some microbial fertilizer treatments decreased cucumber height and stem diameter (Fig. g,h).
There were no significant differences in cucumber growth before microbial fertilizer microbial fertilizer was applied (Fig. c,d,g,h). However, within 4 weeks of applying the microbial fertilizer, each biofertilizer treatment applied significantly increased cucumber height (Fig. c). US267 and USHZ significantly increased cucumber height by 39.8–75.4% and 56.1–86.1%, respectively. US267, USM and USHZ significantly increased the stem diameter by 76.8–108.9%, 71.1–97.6% and 80.4–122.4%, respectively (Fig. d). Over the subsequent 5 weeks, US267, USM and USHZ treatments continued to significantly increase cucumber height and stem diameter (Fig. g,h).
Soil Biofertilizers application significantly reduced the taxonomic composition of soil-borne fungal pathogens at different times during the cucumber growth period (Tables and ). Fusarium spp. were significantly reduced (T, 63.8% reduction, P < 0.001) after the third application of T. harzianum , which was during the early period ofgrowth (Table ). Phytophthora spp. was significantly reduced (T, 81.6% reduction, P < 0.001) by Strain 267. Fusarium spp. and Phytophthora spp. were significantly reduced by S267, SBS and SHZ. When the cucumber were uprooted during the later period of growth, we observed that SBS, SHZ and S267 treatments had significantly reduced Fusarium spp. and Phytophthora spp. Therefore, S267, SBS and SHZ treatments were considered as the most effective biofertilizers against Fusarium spp. or Phytophthora spp. Strain 267, BS, and HZ effectively controlled soil-borne pathogens. However, the effect of T. 267 and HZ decreased during the late growth stage of cucumber. Substrate Fusarium spp. was significantly reduced (T, 87.5% reduction, P < 0.001) after the third application of USBS, which was during the early period of growth (Table ). Phytophthora spp. was significantly reduced (T, 81.6% reduction, P < 0.001) by strain 267. Fusarium spp. and Phytophthora spp. were significantly reduced by US267, USBS and USHZ. At the time the cucumberwere uprooted during the later period of growth, each treatment had significantly reduced Fusarium spp. by more than 60%. In addition, Phytophthora spp. was significantly reduced (T, 47.9% reduction, P < 0.001) by US267. Therefore, US267, USBS and USHZ treatments were considered as the most effective treatments against Fusarium spp. and Phytophthora spp. Strain 267, BS, and HZ effectively controlled soil-borne pathogens. The effect of T. 267 and HZ increased during the late growth stage of cucumber.
Biofertilizers application significantly reduced the taxonomic composition of soil-borne fungal pathogens at different times during the cucumber growth period (Tables and ). Fusarium spp. were significantly reduced (T, 63.8% reduction, P < 0.001) after the third application of T. harzianum , which was during the early period ofgrowth (Table ). Phytophthora spp. was significantly reduced (T, 81.6% reduction, P < 0.001) by Strain 267. Fusarium spp. and Phytophthora spp. were significantly reduced by S267, SBS and SHZ. When the cucumber were uprooted during the later period of growth, we observed that SBS, SHZ and S267 treatments had significantly reduced Fusarium spp. and Phytophthora spp. Therefore, S267, SBS and SHZ treatments were considered as the most effective biofertilizers against Fusarium spp. or Phytophthora spp. Strain 267, BS, and HZ effectively controlled soil-borne pathogens. However, the effect of T. 267 and HZ decreased during the late growth stage of cucumber.
Fusarium spp. was significantly reduced (T, 87.5% reduction, P < 0.001) after the third application of USBS, which was during the early period of growth (Table ). Phytophthora spp. was significantly reduced (T, 81.6% reduction, P < 0.001) by strain 267. Fusarium spp. and Phytophthora spp. were significantly reduced by US267, USBS and USHZ. At the time the cucumberwere uprooted during the later period of growth, each treatment had significantly reduced Fusarium spp. by more than 60%. In addition, Phytophthora spp. was significantly reduced (T, 47.9% reduction, P < 0.001) by US267. Therefore, US267, USBS and USHZ treatments were considered as the most effective treatments against Fusarium spp. and Phytophthora spp. Strain 267, BS, and HZ effectively controlled soil-borne pathogens. The effect of T. 267 and HZ increased during the late growth stage of cucumber.
Some treatments significantly increased cucumber yield after microbial fertilizer applications to plants grown in soil (Fig. ). S267, SBS, SM and SHZ significantly increased cucumber yield. S267 and SHZ significantly increased cucumber yield by 28.8 and 26.7%, respectively. US267, USM and USHZ significantly increased cucumber yield by 29.0, 26.5 and 27.4% when they were applied to seedlings grown on substrate (Fig. ).
Diversity analysis of bacteria A total of 1,709,972 valid reads were obtained from 16S rRNA amplicon sequencing after trimming. The average length of the amplicon was 428 bp. The number of valid sequences detected for each soil sample exceeded 40,000. The sparse curve was flat, which indicated that the genetic data were sufficient for a reasonable estimate of the total taxonomic composition. Analysis of the microbial community diversity index in soil in response to the each biofertilizer treatment showed that the OTU diversity and richness were like the control (Fig. a,b,e,f). In the early stage of the cucumber growth period and after the third application of biofertilizer, and in the late stage of the cucumber growth period when the cucumber were uprooted, there were significant changes observed in the soil and substrate α diversity in the microbial community. In the early stage of cucumber growth, the Shannon diversity index in SBS increased significantly (Fig. a). However, in the late stage of cucumber growth, there was no significant difference in the Shannon diversity index (Fig. e). The Chao1 richness index increased significantly in SM (Fig. f). Analysis of the microbial community diversity index in substrate in response to each biofertilizer treatment showed that the OTU diversity and richness were significantly different to the control (Fig. c,d,g,h). In the early stage of cucumber growth, the Shannon diversity index decreased significantly in USBS, USBH and USHZ (Fig. c). However, the Shannon diversity index increased significantly in US267 and USM. The Chao richness index decreased significantly in USBH, USHZ and US267 (Fig. d). In the late stage of cucumber growth, the Shannon diversity index decreased significantly in USM (Fig. g). The Chao richness index increased significantly in USHZ and US267 (Fig. h). Bacterial hierarchical cluster analysis at the OTU level The results of hierarchical cluster analysis showed that different treatments had different effects on the taxonomic structure of microbes in the soil or substrate at different stages of cucumber plant growth (Fig. a–d). In the early stage of cucumber growth, the microbial communities exposed to SM and in the control were genetically close, compared with the other biofertilizer treatments, which indicated that the soil microbial community structure was changed more by the other biofertilizer treatments than SM (Fig. a). However, in the later stage of cucumber growth the five biofertilizer treatments were well-separated, which indicated that the microbial community structure was changed by the treatments (Fig. c). In the early stage of cucumber growth in substrates, the control bacterial taxa were well-separated from the five biofertilizer treatments (Fig. b). However, the five treatments and control were observed divided into two branches, one for US267 and the other for USCK, USBH, USBS, USM and USHZ. The structure of the microbial community was similar in USBH, USBS, USM and USHZ and the control. The results indicated that US267 had significantly changed the taxonomic structure of the bacterial community. In the late stage of cucumber growth, the five biofertilizer treatments and the control were observed as divided into two branches, one for USCK, USBS and USBH and the other for US267, USM and USHZ (Fig. d). The taxonomic structure of the microbial community was similar in the USBH and USBS to the control. The results indicated that US267, USM and USHZ had significantly changed the composition of the bacterial taxa. Changes in bacterial genera dominance In the early stage of cucumber growth, significant differences were observed in the relative abundance of bacterial genera after applying microbial fertilizer (Fig. a). MND1 was second only to Gaiella in dominance. The relative abundance of Planifilum also increased significantly at that time. In the late stage of cucumber growth, Ilumatobacter became second only to Microvirga in dominance (Fig. c). The relative abundance of Arthrobacter, Pedomicrobium, Dongia, Haliangium, and Devosia also increased significantly at that time. In the early stage of cucumber growth, Pseudolabrys was second only to Bacillus in dominance (Fig. b). The relative abundance of Flavobacterium, Sphingomonas and Pseudomonas also increased significantly. In the late stage of cucumber growth, Bacteroidota became second only to Actinobacteriota in dominance (Fig. d). Actinobacteriota increased significantly in USM and USHZ at that time. Bacteroidota decreased significantly in USBH and USHZ. The relative abundance of Firmicutes increased significantly. LEfSe analysis identified biomarkers that caused significant differences in control (P < 0.05, a, c, LDA = 3; b, d, LDA = 4.0; Fig. a,b,c,d). Fig. a,b,c,d showed five rings in the cladogram, from inside to outside, representing the phylum, class, order, family, and genus taxonomic levels, respectively. The different color nodes (except yellow) on the ring represent significant changes in taxonomic composition due to the biofertilizer treatments. The non-parametric factorial Kruskal–Wallis (KW) sum-rank test and Linear Discriminant Analysis (LDA) estimated the magnitude of the effect of each component (species) abundance on the differential effect. We observed that at the bacterial genus level some major taxa were screened out, which suggested that these biomarkers have the greatest impact on the results. In the early stage of cucumber growth in soil, 3, 1 and 1 biomarkers were found in S267, SBS and SCK, respectively. In the late stage of cucumber growth, 3, 3, 1, 3, 3 and 3 biomarkers were found in S267, SBS, SBH, SM, SHZ and SCK, respectively. In the early stage of cucumber growth in substrate, 1, 2 and 1 biomarkers were found in US267, USBS and USM, respectively. In the late stage of cucumber growth, 1, 1 and 1 biomarkers were found in US267, USBH and USHZ, respectively. The results indicated that g__norank_f__norank_o__ Gaiellales and g__ Blastococcus became prevalent when S267 was applied to the soil during the early stage of cucumber growth, and that g__ Paenibacillus became prevalent when SHZ was applied at the late stage of cucumber growth. LEfSe analysis confirmed that USBS significantly increased the abundance of the c__ Bacilli at the early stage of cucumber growth in substrate, and that US267 and USHZ significantly increased the abundance of p__ Patescibacteria and p__ Firmicutes , respectively, at the late stage of cucumber growth. Changes in fungal genera dominance A total of 1,859,284 valid reads were obtained from ITS rRNA amplicon sequencing after quality trimming. The average length of the amplicon was 321 bp. The number of valid sequences detected for each soil sample exceeded 40,000. The sparse curve was flat which indicated that the genetic data were sufficient for a reasonable estimate of the total taxonomic composition. We observed that the microbial community α diversity of soil in the early and late stages of cucumber growth changed significantly (Fig. a,b,e,f). In the early stage of cucumber growth, there were no significant differences in the diversity index of Shannon and the richness index of Chao (Fig. a,b). However, in the late stage of cucumber growth, the Shannon diversity index increased significantly in SBS, SHZ and SM (Fig. e). At the same time, the richness index of Chao decreased significantly in SBS (Fig. f). Analysis of the fungal diversity index treatment found that OTU diversity and richness was significantly different in response to each biofertilizer (Fig. c,d,g,h). In the early stage of cucumber growth, the Shannon diversity index decreased significantly in SBH, SHZ and SM (Fig. c). The richness index of Chao decreased significantly in SBS (Fig. d). In the late stage of cucumber growth, the Shannon diversity index increased significantly in S267, SBS, SBH and SM (Fig. g). We observed no significant differences in the richness index of Chao (Fig. h). Fungal hierarchical cluster analysis at the OTU level In the early stage of cucumber growth in soil, the taxonomic structure of the microbial community was similar in SBH, S267, SM and SHZ to the control (Fig. a). However, we observed that SBS significantly changed the fungal community. In the late stage of cucumber growth, microbial taxa in the SM and the control samples were genetically close compared with the other biofertilizer treatments, which indicated that the soil fungal taxonomic structure was changed more in the other biofertilizer treatments than in SM (Fig. c). In the early stage of cucumber growth in substrate, the control samples in the fungal community were clustered together and well-separated taxonomically from the five biofertilizer treatments (Fig. b). However, the five treatments and control were divided into one branch for USCK and the other branch comprising US267, USBH, USBS, USM and USHZ. These results indicated that the five treatments had significantly changed the fungal taxonomic composition. In the late stage of cucumber growth, however, the five treatments and control were divided into a branch for USCK, USBS, and USBH and another branch comprising US267, USM and USHZ (Fig. d). The structure of the microbial community was similar in USBS and the control. The results indicated that US267, USM and USHZ had significantly changed the taxonomic fungal composition in the community. Analysis of differences in fungal genera dominance We observed significant differences in the relative abundance of fungal genera in soil after microbial fertilizers were applied (Fig. a,c). In the early stage of cucumber growth, Trichoderma was second only to Aspergillus in dominance (Fig. a). The relative abundance of Plectosphaerella increased significantly in SBS. The relative abundance of Trichocladium increased significantly in response to all biofertilizers, whereas Stachybotrys decreased significantly. In the late stage of cucumber growth, Trichoderma was second only to Chaetomium in fungal dominance (Fig. c). The relative abundance of Chaetomium increased significantly in SM; Trichoderma increased significantly in S267 and SHZ; and Trichocladium increased significantly SHZ, SM and SBH. In general, the relative abundance of Neocosmospora and Schizothecium decreased significantly when exposed to all the biofertilizer treatments. We also observed significant differences in the relative abundance of fungal genera after microbial fertilizer were applied (Fig. b,d). In the early stage of cucumber growth, the relative abundance of Parascedosporium increased significantly in US267 and USM (Fig. b). The relative abundance of Mortierella and Cephalotheca decreased significantly compared to CK treatment. In the late stage of cucumber growth, the relative abundance of Ramophialophora increased significantly in USBH, USBS and USHZ (Fig. d). The relative abundance of Tausonia decreased significantly in USHZ. The relative abundance of Gibellulopsis decreased significantly in USBS and USBH. The relative abundance of Chaetomium increased significantly compared with the control in US267, USBH, USBS and USM. In the early and late stage of cucumber, Tausonia was second only to Ramophialophora in dominance. LEfSe analysis identified the biomarkers that caused significant differences in control (P < 0.05, a, c, LDA = 3; b, d, LDA = 4.0; Fig. a,b,c,d). We observed that the analyses screened out major taxa at the fungal genus level. In the early stage of cucumber growth in soil, 4, 1, 2, 2, 1 and 3 biomarkers were found in S267, SBH, SBS, SM, SHZ and SCK, respectively. In the late stage of cucumber growth, 5, 3, 10, 3, 7 and 3 biomarkers were found in S267, SBH, SBS, SHZ, SM and SCK, respectively. In the early stage of cucumber growth in substrate, 2, 2, 2, 3 and 2 biomarkers were found in US267, USBS, USM, USHZ and USCK, respectively. In the late stage of cucumber growth, 2, 1, 1, 2 and 5 biomarkers were found in US267, USBH, USM, USHZ and USCK, respectively. A large LDA score indicates a greater influence of species abundance on the difference effect. We observed that g_ Trichoderma had larger LDA values in S267 and US267, which indicated that g_ Trichoderma responded strongly to S267 and US267.
A total of 1,709,972 valid reads were obtained from 16S rRNA amplicon sequencing after trimming. The average length of the amplicon was 428 bp. The number of valid sequences detected for each soil sample exceeded 40,000. The sparse curve was flat, which indicated that the genetic data were sufficient for a reasonable estimate of the total taxonomic composition. Analysis of the microbial community diversity index in soil in response to the each biofertilizer treatment showed that the OTU diversity and richness were like the control (Fig. a,b,e,f). In the early stage of the cucumber growth period and after the third application of biofertilizer, and in the late stage of the cucumber growth period when the cucumber were uprooted, there were significant changes observed in the soil and substrate α diversity in the microbial community. In the early stage of cucumber growth, the Shannon diversity index in SBS increased significantly (Fig. a). However, in the late stage of cucumber growth, there was no significant difference in the Shannon diversity index (Fig. e). The Chao1 richness index increased significantly in SM (Fig. f). Analysis of the microbial community diversity index in substrate in response to each biofertilizer treatment showed that the OTU diversity and richness were significantly different to the control (Fig. c,d,g,h). In the early stage of cucumber growth, the Shannon diversity index decreased significantly in USBS, USBH and USHZ (Fig. c). However, the Shannon diversity index increased significantly in US267 and USM. The Chao richness index decreased significantly in USBH, USHZ and US267 (Fig. d). In the late stage of cucumber growth, the Shannon diversity index decreased significantly in USM (Fig. g). The Chao richness index increased significantly in USHZ and US267 (Fig. h).
The results of hierarchical cluster analysis showed that different treatments had different effects on the taxonomic structure of microbes in the soil or substrate at different stages of cucumber plant growth (Fig. a–d). In the early stage of cucumber growth, the microbial communities exposed to SM and in the control were genetically close, compared with the other biofertilizer treatments, which indicated that the soil microbial community structure was changed more by the other biofertilizer treatments than SM (Fig. a). However, in the later stage of cucumber growth the five biofertilizer treatments were well-separated, which indicated that the microbial community structure was changed by the treatments (Fig. c). In the early stage of cucumber growth in substrates, the control bacterial taxa were well-separated from the five biofertilizer treatments (Fig. b). However, the five treatments and control were observed divided into two branches, one for US267 and the other for USCK, USBH, USBS, USM and USHZ. The structure of the microbial community was similar in USBH, USBS, USM and USHZ and the control. The results indicated that US267 had significantly changed the taxonomic structure of the bacterial community. In the late stage of cucumber growth, the five biofertilizer treatments and the control were observed as divided into two branches, one for USCK, USBS and USBH and the other for US267, USM and USHZ (Fig. d). The taxonomic structure of the microbial community was similar in the USBH and USBS to the control. The results indicated that US267, USM and USHZ had significantly changed the composition of the bacterial taxa.
In the early stage of cucumber growth, significant differences were observed in the relative abundance of bacterial genera after applying microbial fertilizer (Fig. a). MND1 was second only to Gaiella in dominance. The relative abundance of Planifilum also increased significantly at that time. In the late stage of cucumber growth, Ilumatobacter became second only to Microvirga in dominance (Fig. c). The relative abundance of Arthrobacter, Pedomicrobium, Dongia, Haliangium, and Devosia also increased significantly at that time. In the early stage of cucumber growth, Pseudolabrys was second only to Bacillus in dominance (Fig. b). The relative abundance of Flavobacterium, Sphingomonas and Pseudomonas also increased significantly. In the late stage of cucumber growth, Bacteroidota became second only to Actinobacteriota in dominance (Fig. d). Actinobacteriota increased significantly in USM and USHZ at that time. Bacteroidota decreased significantly in USBH and USHZ. The relative abundance of Firmicutes increased significantly. LEfSe analysis identified biomarkers that caused significant differences in control (P < 0.05, a, c, LDA = 3; b, d, LDA = 4.0; Fig. a,b,c,d). Fig. a,b,c,d showed five rings in the cladogram, from inside to outside, representing the phylum, class, order, family, and genus taxonomic levels, respectively. The different color nodes (except yellow) on the ring represent significant changes in taxonomic composition due to the biofertilizer treatments. The non-parametric factorial Kruskal–Wallis (KW) sum-rank test and Linear Discriminant Analysis (LDA) estimated the magnitude of the effect of each component (species) abundance on the differential effect. We observed that at the bacterial genus level some major taxa were screened out, which suggested that these biomarkers have the greatest impact on the results. In the early stage of cucumber growth in soil, 3, 1 and 1 biomarkers were found in S267, SBS and SCK, respectively. In the late stage of cucumber growth, 3, 3, 1, 3, 3 and 3 biomarkers were found in S267, SBS, SBH, SM, SHZ and SCK, respectively. In the early stage of cucumber growth in substrate, 1, 2 and 1 biomarkers were found in US267, USBS and USM, respectively. In the late stage of cucumber growth, 1, 1 and 1 biomarkers were found in US267, USBH and USHZ, respectively. The results indicated that g__norank_f__norank_o__ Gaiellales and g__ Blastococcus became prevalent when S267 was applied to the soil during the early stage of cucumber growth, and that g__ Paenibacillus became prevalent when SHZ was applied at the late stage of cucumber growth. LEfSe analysis confirmed that USBS significantly increased the abundance of the c__ Bacilli at the early stage of cucumber growth in substrate, and that US267 and USHZ significantly increased the abundance of p__ Patescibacteria and p__ Firmicutes , respectively, at the late stage of cucumber growth.
A total of 1,859,284 valid reads were obtained from ITS rRNA amplicon sequencing after quality trimming. The average length of the amplicon was 321 bp. The number of valid sequences detected for each soil sample exceeded 40,000. The sparse curve was flat which indicated that the genetic data were sufficient for a reasonable estimate of the total taxonomic composition. We observed that the microbial community α diversity of soil in the early and late stages of cucumber growth changed significantly (Fig. a,b,e,f). In the early stage of cucumber growth, there were no significant differences in the diversity index of Shannon and the richness index of Chao (Fig. a,b). However, in the late stage of cucumber growth, the Shannon diversity index increased significantly in SBS, SHZ and SM (Fig. e). At the same time, the richness index of Chao decreased significantly in SBS (Fig. f). Analysis of the fungal diversity index treatment found that OTU diversity and richness was significantly different in response to each biofertilizer (Fig. c,d,g,h). In the early stage of cucumber growth, the Shannon diversity index decreased significantly in SBH, SHZ and SM (Fig. c). The richness index of Chao decreased significantly in SBS (Fig. d). In the late stage of cucumber growth, the Shannon diversity index increased significantly in S267, SBS, SBH and SM (Fig. g). We observed no significant differences in the richness index of Chao (Fig. h).
In the early stage of cucumber growth in soil, the taxonomic structure of the microbial community was similar in SBH, S267, SM and SHZ to the control (Fig. a). However, we observed that SBS significantly changed the fungal community. In the late stage of cucumber growth, microbial taxa in the SM and the control samples were genetically close compared with the other biofertilizer treatments, which indicated that the soil fungal taxonomic structure was changed more in the other biofertilizer treatments than in SM (Fig. c). In the early stage of cucumber growth in substrate, the control samples in the fungal community were clustered together and well-separated taxonomically from the five biofertilizer treatments (Fig. b). However, the five treatments and control were divided into one branch for USCK and the other branch comprising US267, USBH, USBS, USM and USHZ. These results indicated that the five treatments had significantly changed the fungal taxonomic composition. In the late stage of cucumber growth, however, the five treatments and control were divided into a branch for USCK, USBS, and USBH and another branch comprising US267, USM and USHZ (Fig. d). The structure of the microbial community was similar in USBS and the control. The results indicated that US267, USM and USHZ had significantly changed the taxonomic fungal composition in the community.
We observed significant differences in the relative abundance of fungal genera in soil after microbial fertilizers were applied (Fig. a,c). In the early stage of cucumber growth, Trichoderma was second only to Aspergillus in dominance (Fig. a). The relative abundance of Plectosphaerella increased significantly in SBS. The relative abundance of Trichocladium increased significantly in response to all biofertilizers, whereas Stachybotrys decreased significantly. In the late stage of cucumber growth, Trichoderma was second only to Chaetomium in fungal dominance (Fig. c). The relative abundance of Chaetomium increased significantly in SM; Trichoderma increased significantly in S267 and SHZ; and Trichocladium increased significantly SHZ, SM and SBH. In general, the relative abundance of Neocosmospora and Schizothecium decreased significantly when exposed to all the biofertilizer treatments. We also observed significant differences in the relative abundance of fungal genera after microbial fertilizer were applied (Fig. b,d). In the early stage of cucumber growth, the relative abundance of Parascedosporium increased significantly in US267 and USM (Fig. b). The relative abundance of Mortierella and Cephalotheca decreased significantly compared to CK treatment. In the late stage of cucumber growth, the relative abundance of Ramophialophora increased significantly in USBH, USBS and USHZ (Fig. d). The relative abundance of Tausonia decreased significantly in USHZ. The relative abundance of Gibellulopsis decreased significantly in USBS and USBH. The relative abundance of Chaetomium increased significantly compared with the control in US267, USBH, USBS and USM. In the early and late stage of cucumber, Tausonia was second only to Ramophialophora in dominance. LEfSe analysis identified the biomarkers that caused significant differences in control (P < 0.05, a, c, LDA = 3; b, d, LDA = 4.0; Fig. a,b,c,d). We observed that the analyses screened out major taxa at the fungal genus level. In the early stage of cucumber growth in soil, 4, 1, 2, 2, 1 and 3 biomarkers were found in S267, SBH, SBS, SM, SHZ and SCK, respectively. In the late stage of cucumber growth, 5, 3, 10, 3, 7 and 3 biomarkers were found in S267, SBH, SBS, SHZ, SM and SCK, respectively. In the early stage of cucumber growth in substrate, 2, 2, 2, 3 and 2 biomarkers were found in US267, USBS, USM, USHZ and USCK, respectively. In the late stage of cucumber growth, 2, 1, 1, 2 and 5 biomarkers were found in US267, USBH, USM, USHZ and USCK, respectively. A large LDA score indicates a greater influence of species abundance on the difference effect. We observed that g_ Trichoderma had larger LDA values in S267 and US267, which indicated that g_ Trichoderma responded strongly to S267 and US267.
We observed that microbial fertilizers applied to soil or substrate in a greenhouse increased cucumber quality, yield and the abundance of bacterial and fungal genera involved in the control of soil-borne pathogens. We observed that some of the biofertilizers that we tested increased the growth of cucumbers grown in soil or substrate. Within 10 weeks of applying them, some treatments such as S267 and SHZ significantly increased cucumber plant height and stem diameter. US267, USM and USHZ significantly increased the stem diameter and plant height of substrate-grown cucumbers. Our findings were consistent with the results of Selvakumar who observed that microbial fertilizers increased the beneficial microorganisms in the rhizosphere and increased plant growth. B. subtilis and Trichoderma were reported as two of the most important plant growth-promoting organisms in commercial agriculture that increased plant growth and influenced the taxonomic composition in the rhizosphere – . Some biofertilizers tested were better at increasing cucumber growth in substrate than others. For example, US267, USM and USHZ significantly improved cucumber growth in all cucumber growth stages. Previous research reported that substrates reduced the production constraints inherent in soil production by reduced the use of water, gas for greenhouse heating and fertilizer . Microorganisms present in microbial fertilizers were reported to promote the transformation of organic nutrients in the substrate; accelerate the absorption, transport, assimilation and accumulation of elements by the plant; improve the plant’s utilization rate of nutrients; and improve the yield and quality of cucumber . Our research showed biofertilizers significantly reduced Fusarium and Phytophthora , which was also reported by Sridharan and Suriani , . We also observed that some microbial biofertilizers significantly reduced fungal soil-borne pathogens, even when the cucumber plants were uprooted. That may have been due the presence of beneficial microorganisms in the biofertilizers that had multiplied rapidly and inhibited the growth of pathogens . We observed that 267, BS and HZ were better at controlling soil-borne pathogens than other biofertilizers, but the efficacy of most of them tested reduced during the late growth stage of cucumber. Conversely, in substrate the efficacy of most biofertilizers we tested increased in the late growth stage, which suggested the microbes in our biofertilizers required sufficient time to colonize the substrate. We noted that the microbes were most likely spread in substrates by water that flowed in one direction. In general, the impact of pathogenic bacteria and fungi under continual cropping was delayed with crops produced on substrates compared to soil . We observed that the biofertilizers had little effect on soil’s bacterial taxonomic diversity, but changed the population abundance of some bacterial taxa which led to a change in community structure. Previous research reported that organic fertilizers can cause changes in the structure of soil microbial communities . In contrast to soil, the biofertilizers applied to substrate significantly affected the bacterial taxonomic diversity. We observed that Strain 267’s increase in bacterial diversity was temporary as bacterial populations levels returned to those observed in the control when the cucumber was uprooted. We observed that the α diversity of the soil’s fungal community in the changed significantly in both the early and late stages of cucumber growth. In the early stage of cucumber growth, there were no significant differences in the diversity index of Shannon and the richness index of Chao compared with the control. In the late stage of cucumber growth, however, the Shannon diversity index increased significantly compared with the control in SBS, SHZ and SM. In addition, we found that the Shannon diversity index decreased significantly in the SBH, SHZ and SM treatments after the third application of biofertilizers. However, the Shannon diversity index increased significantly compared with the control in S267, SBS, SBH and SM at the time the cucumber plants were uprooted. The taxonomic tree results showed that some biofertilizer treatments significantly changed the taxonomic composition of the soil and substrate’s bacterial and fungal communities. In general, we observed that different biofertilizers altered the relative abundance of microbes in different ways. We also observed that soil and substrate microbial diversity differed significantly during the seasonal growth of cucumber. Previous research reported that crop growth stages and fertilization application frequency changed the soil microbial diversity . Some research reported that changes in soil temperature and moisture during the season directly or indirectly influenced the soil microbiome . We observed that biofertilizers added to soil or substrate changed the bacterial community composition. The rhizosphere microbial communities exhibited distinctly different patterns between soil and substrate. Our soil results are consistent with the findings of previous studies that applied functional bacteria or fungi present in biofertilizers to alter the bacterial taxonomic composition of the soil . We observed that the relative abundance of Planifilum , Microvirga, Pedomicrobium and Haliangium increased significantly in the soil in response to biofertilizers. We found that the relative abundance of Planifilum increased significantly in response to biofertilizer application. Planifilum is a potential source of sul genes, which suggests that the application of organic fertilizer may enrich the potential source bacteria for sul genes, such as Planifilum , accelerating the transfer of sul genes . Planifilum is also an important nitrogen-fixing bacterium that secretes xylanase to break down xylan , which is a type of hemicellulose found in plants. We observed that the relative abundance of Microvirga, Pedomicrobium and Haliangium increased significantly. Microvirga spp. are thermo-tolerant bacteria. They are metabolically versatile and widely distributed in nature . In addition, Microvirga is also reported to be an environmental remediator, as it can remove residual contaminants in soil and water . Pedomicrobium is a ubiquitously occurring hyphal-budding organism that can adhere to surfaces and form biofilms in different habitats . Haliangium can produce a type of antifungal metabolite, which inhibits the growth of fungi . We observed that the relative abundance of Flavobacterium, Sphingomonas and Pseudomonas are algicidal bacteria that increased significantly in the substrate in response to biofertilizers. We observed that the relative abundance of Actinobacteria increased significantly in USHZ and USM. Actinobacteria are reported to decompose organic matter and inhibit pathogens , . Firmicutes is drought tolerant and resistant to extreme weather events. It is reported to decontaminate and bioremediate soils that are acidified or contaminated by heavy metals , . Firmicutes may also degrade algae . We observed an increase in Trichocladium fungus, which is involved in lignocellulose degradation . Mortierella , and Tausonia became the dominant fungi in response to biofertilizers in our research. Mortierella is a phosphorus-solubilizing fungus that is important in the soil carbon and phosphorus cycle . Tausonia is a member of the phylum Basidiomycota that is reported to produce auxin-like compounds that inhibit pathogens , and ligninase capable of degrading lignin-containing wastes . The relative abundance of Gibellulopsis decreased significantly in USBH and USBS. Gibellulopsis is a pathogen that can cause plant diseases . We observed an increase in the abundance of Ramophialophora in soil in response to the biofertilizer treatments. At present, little is known about the function of Ramophialophora in soil. The LEfSe diagram showed that the biofertilizers tested significantly influenced the biological grouping of genera of fungi. In particular, Trichoderma 267 significantly changed the soil or substrate bacterial and fungal taxonomic composition. Further studies are needed to verify whether that result was related to the stage of cucumber growth or the “colonization intensity” of both organisms in the microbial fertilizers. We found that some biofertilizer treatments significantly increased cucumber yield, which was consistent with previous research . Strain 267 and Trichoderma harzianum significantly increased cucumber yield more than the other biofertilizers tested. Further studies are needed to verify whether that result was related to the stage of cucumber growth or the “colonization intensity” of both organisms in the microbial fertilizers. Generally, we observed that biofertilizers added to soil or substrate in a greenhouse improved cucumber growth and increased soil-borne pathogen control. Biofertilizers altered the microbial taxonomic structure. As examples, they significantly increased the relative abundance of some beneficial microorganisms, such as Planifilum, Microvirga, Pedomicrobium, and Haliangium in soil , and increased the relative abundance of Flavobacterium, Sphingomonas and Pseudomonas in substrate. The extent that biofertilizers changed the taxonomic composition of bacteria and fungi depended to some extent on the stage of the cucumber growth, and the timing of the biofertilizer application in those stages. Our results shed light on the complex interactions between microbes and the plant rhizosphere when a plant is grown in soil or substrate. Biofertilizers applied to soil or substrate can effectively prevent and control soil-borne diseases, optimize the taxonomic structure of microbial communities, and create a relatively healthy microbial ecological environment for the emergence of many beneficial microorganisms. The ecological functions of soil and substrate were enhanced by increases in the relative abundance of beneficial microorganisms. The substitution of inorganic fertilizer with biofertilizers will reduce the long term detrimental environmental impact of inorganic fertilizers and improve agricultural sustainability. Biofertilizer were effective in substrate, especially at the later stage of cucumber growth. Substrates obtained from sustainable resources and that are recyclable after use can play a significant role in reducing the accumulation of soil-borne diseases that currently limit the expansion of crops that are
continually produced on the same soil each year.
Supplementary Information.
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High expression of guanine nucleotide-binding protein-like-3-like is associated with poor prognosis in esophageal cancer | f20c3802-666b-4ee1-89ed-490eab2ffd48 | 8154413 | Histology[mh] | Introduction Esophageal cancer is one of the most common cancer worldwide, accounting for approximately 3% of cancer cases and 5% of cancer deaths. China has a higher incidence rate of esophageal cancer. Although the incidence rate of esophageal cancer has declined in recent years, the mortality rate of esophageal cancer still ranks the fourth. Therefore, esophageal cancer has always been a major cancer threatening the health of Chinese. To date, patients with esophageal cancer have very little choice other than cytotoxic chemotherapy due to very few targeted drugs. This emphasizes the critical importance of the identification of alternative targets for the development of novel anticancer treatments and biomarkers for the prognosis of esophageal cancer. Guanine nucleotide-binding protein-like-3-like (GNL3L) is an evolutionarily conserved high molecular weight nucleolar GTPase which belongs to the YawG/YIqF/HSR1_MMR1 GTP-binding protein subfamily of GTPases. GNL3L is required for processing ribosomal pre-rRNA and cell proliferation. Overexpression of GNL3L promotes the S phase progression by upregulating E2F1, cyclins A2 and E1, whereas inhibition of GNL3L leads to G2/M arrest. Furthermore, GNL3L has been shown to exert an anti-apoptotic activity through modulating the expression and stability of subunit p65 of nuclear factor-kappa B (NF-κB). GNL3L is upregulated in many types of cancer, including esophageal colorectal, esophageal, and gastric cancers. Kannathasan et al reported that GNL3L promoted tumorigenesis, cell cycle regulation, and anti-apoptosis through NF-κB activation colorectal cancer (CRC) and was upregulated in chemoresistant CRC cells. In addition, GNL3L is also one of factors that are important for the maintenance of tumorigenic property of cancer stem cells (CSCs). GNL3L plays an important role in cancer, including regulating cell proliferation, metastasis, and chemoresistance. [ – ] Whether the expression level of GNL3L affects the prognosis of cancer patients has not yet been reported. To date, there is little knowledge about the role of GNL3L in esophageal cancer. Considering its important role in cancer, this study aimed to explore the clinical significance of GNL3L in esophageal cancer. The results demonstrated that GNL3L was upregulated in esophageal cancer, particularly in those poor differentiation cases. High GNL3L expression was associated with ulcerative type, poor differentiation, and worse prognosis. Therefore, GNL3L might be a potential prognostic biomarker and a potential therapeutic target for esophageal cancer.
Materials and methods 2.1 Patients A total of 218 pairs of esophageal squamous cell carcinoma and adjacent nonmalignant esophageal tissues were obtained from patients who underwent surgery esophagectomy at Taizhou People's Hospital. No patient received chemotherapy, radiotherapy, or immunotherapy before surgery. All patients were treated with at least 2 cycles of platinum-combined adjuvant chemotherapy after surgery. The details of patient characteristics have been described previously. In addition, 30 pairs of esophageal cancer and adjacent nonmalignant esophageal formalin-fixed paraffin-embedded (FFPE) tissues were used to detect the protein levels of GNL3L. The study was approved by the Ethical Committee of Taizhou People's Hospital. Informed consent was obtained from all patients. 2.2 Quantitative real-time polymerase chain reaction (qPCR) The total RNA was extracted from tissues with Trizol reagent (Invitrogen, CA, USA) following the manufacturer's protocol. Complementary DNA (cDNA) was synthesized from 1 μg of total RNA using PrimeScript TM RT reagent Kit with gDNA Eraser (Takara, Dalian, China) according to the manufacture's instructions. QPCR was carried out using the SYBR Premix Ex Taq TM II kit (Tli RNaseH Plus) (Takara, Dalian, China) on ABI 7900 system (Applied Biosystems, CA, USA) according to the manufacturer's instructions. Assays were performed in triplicate for each sample. The relative expression levels of GNL3L were calculated and normalized using the 2 -ΔΔCt method relative to GAPDH. 2.3 Immunohistochemistry (IHC) The protein levels of GNL3L were examined using IHC. The tissue slides were deparaffinized with xylene and dehydrated in a graded series of ethanol (100%, 95% and 80% ethanol) and PBS. After antigen retrieval, slides were incubated in 3% H 2 O 2 to quench endogenous peroxidase activity. Nonspecific binding was blocked by incubation with 10% goat serum in PBS for 1 h at room temperature. The slides then were incubated with a primary monoclonal rabbit anti-GNL3L antibody (Abcam, Cambridge, MA, USA) and subsequently incubated with secondary antibody. The evaluation of IHC staining results was conducted blindly. Staining intensity was scored and the total histological score was calculated as described previously. 2.4 Statistical analyses Statistical analyses were performed using IBM SPSS software version 25.0 (SPSS Inc., IL, USA) and GraphPad Prism 7 (GraphPad Software, CA, USA). A P value < .05 was considered to be statistically significant for all statistical procedure. The differences in mRNA and protein expression levels of GNL3L between esophageal cancer and adjacent tissues were compared with the Mann–Whitney test. Spearman correlation test was used to determine the association between the expression level of GNL3L and tumor size. All patients were divided into low and high GNL3L expression groups according to its median value. Pearson χ 2 and Fisher's exact test were used to evaluated the association between clinicopathologic variables and GNL3L expression. Estimates of overall survival (OS) were from Kaplan–Meier curves and tests of differences by log-rank test. Clinicopathological variables with a value of P < .05 in the univariate Cox regression analysis were further analyzed using multivariate Cox regression.
Patients A total of 218 pairs of esophageal squamous cell carcinoma and adjacent nonmalignant esophageal tissues were obtained from patients who underwent surgery esophagectomy at Taizhou People's Hospital. No patient received chemotherapy, radiotherapy, or immunotherapy before surgery. All patients were treated with at least 2 cycles of platinum-combined adjuvant chemotherapy after surgery. The details of patient characteristics have been described previously. In addition, 30 pairs of esophageal cancer and adjacent nonmalignant esophageal formalin-fixed paraffin-embedded (FFPE) tissues were used to detect the protein levels of GNL3L. The study was approved by the Ethical Committee of Taizhou People's Hospital. Informed consent was obtained from all patients.
Quantitative real-time polymerase chain reaction (qPCR) The total RNA was extracted from tissues with Trizol reagent (Invitrogen, CA, USA) following the manufacturer's protocol. Complementary DNA (cDNA) was synthesized from 1 μg of total RNA using PrimeScript TM RT reagent Kit with gDNA Eraser (Takara, Dalian, China) according to the manufacture's instructions. QPCR was carried out using the SYBR Premix Ex Taq TM II kit (Tli RNaseH Plus) (Takara, Dalian, China) on ABI 7900 system (Applied Biosystems, CA, USA) according to the manufacturer's instructions. Assays were performed in triplicate for each sample. The relative expression levels of GNL3L were calculated and normalized using the 2 -ΔΔCt method relative to GAPDH.
Immunohistochemistry (IHC) The protein levels of GNL3L were examined using IHC. The tissue slides were deparaffinized with xylene and dehydrated in a graded series of ethanol (100%, 95% and 80% ethanol) and PBS. After antigen retrieval, slides were incubated in 3% H 2 O 2 to quench endogenous peroxidase activity. Nonspecific binding was blocked by incubation with 10% goat serum in PBS for 1 h at room temperature. The slides then were incubated with a primary monoclonal rabbit anti-GNL3L antibody (Abcam, Cambridge, MA, USA) and subsequently incubated with secondary antibody. The evaluation of IHC staining results was conducted blindly. Staining intensity was scored and the total histological score was calculated as described previously.
Statistical analyses Statistical analyses were performed using IBM SPSS software version 25.0 (SPSS Inc., IL, USA) and GraphPad Prism 7 (GraphPad Software, CA, USA). A P value < .05 was considered to be statistically significant for all statistical procedure. The differences in mRNA and protein expression levels of GNL3L between esophageal cancer and adjacent tissues were compared with the Mann–Whitney test. Spearman correlation test was used to determine the association between the expression level of GNL3L and tumor size. All patients were divided into low and high GNL3L expression groups according to its median value. Pearson χ 2 and Fisher's exact test were used to evaluated the association between clinicopathologic variables and GNL3L expression. Estimates of overall survival (OS) were from Kaplan–Meier curves and tests of differences by log-rank test. Clinicopathological variables with a value of P < .05 in the univariate Cox regression analysis were further analyzed using multivariate Cox regression.
Results 3.1 Upregulation of GNL3L expression in esophageal cancer tissues The mRNA and protein expression levels of GNL3L in esophageal cancer were examined by qPCR and IHC, respectively. The mRNA expression levels of GNL3L in esophageal cancer tissues were significantly higher than those in adjacent nonmalignant tissues ( P < .001, Figure A). In addition, we evaluated the difference in the mRNA expression level of GNL3L between different clinicopathological variable groups. As shown in Figure B, cases with poor differentiation ( P = .002) had significantly higher level of GNL3L than those with well and moderate differentiation. Although there was no difference in the mRNA expression level of GNL3L between tumor size ≤ 4 cm and tumor size greater than 4 cm ( P = .063), the mRNA expression level of GNL3L was positively correlated with tumor size ( P = .037). With the development of biotechnologies and the continued reduction in costs, omics data is now massively produced. Therefore, integrating online omics data will help to improve the reliability of the findings. The mRNA expression level of GNL3L in esophageal cancer was validated in the Gene Expression Profiling Interactive Analysis (GEPIA) database, in which 286 normal and 182 esophageal cancer tissues were included. The results suggested that the mRNA expression level of GNL3L was significantly upregulated in esophageal cancer (Figure C). which was consistent with our result. We further evaluated the protein expression of GNL3L in 30 pairs of esophageal cancer and adjacent nonmalignant tissues. IHC assays showed that GNL3L was localized in both cytoplasm and nucleus (Figure ). The protein expression levels of GNL3L in esophageal cancer tissues was significantly higher than those in adjacent nonmalignant tissues ( P < .001). 3.2 Association between GNL3L expression and clinicopathological variables of patients with esophageal cancer As shown in Table , high GNL3L expression was significantly associated with clinicopathological variables including pathologic type ( P = .020) and poor differentiation ( P = .007). Furthermore, patients with high GNL3L expression had a tend towards larger tumor size than those with low GNL3L expression, but the difference did not reach statistical significance ( P = .050). There was no correlation between GNL3L expression and other clinical variables including sex, age, drug response, tumor invasion, lymph node metastasis (LNM), and tumor node metastasis stage ( P > .05). 3.3 Survival analyses We also examined the effect of GNL3L on the prognosis of patients with esophageal cancer. There was a significant trend toward decreased survival time with increased expression level of GNL3L. As shown in Figure , high GNL3L expression demonstrated significant correlation with poor OS in patients with esophageal cancer ( P = .008). Univariate and multivariate Cox regression analyses of clinicopathological variables regarding OS were listed in Table . The results revealed that pT category [hazard ratio (HR) = 1.977, 95% confidence interval (CI): 1.244-3.142, P = .004], LNM (HR = 2.349, 95%CI: 1.528–3.611, P < .001), tumor node metastasis stage (HR = 2.050, 95%CI: 1.479–2.840, P < .001), and GNL3L expression (HR = 1.504, 95%CI: 1.102–2.053, P = .010) had a remarkable impact on OS. Multivariate Cox regression analysis was subsequently performed based on the Clinicopathological variables with a value of P < .05 in the univariate Cox regression analysis. The results revealed that LNM (adjusted HR = 1.868, 95%CI: 1.118–3.122, P = .017) and GNL3L expression (adjusted HR = 1.483, 95%CI: 1.066–2.063, P = .019) were independent risk factors affecting OS time. Subsequently, we validated the effect of GNL3L on the prognosis of patients with esophageal cancer using the GEPIA database. The results demonstrated that patients with high GNL3L expression had shorter progression-free survival (PFS) and OS than those with low GNL3L expression ( P < .05). 3.4 Prediction of interaction networks of GNL3L A gene–gene interaction network for GNL3L was constructed using the STRING v11.0 (Figure ), which were further verified by the GEPIA database to enhance the accuracy and reliability of the network. The node representing GNL3L was connected to the nodes of other genes in terms of co-expression and physical interactions. The protein–protein interaction (PPI) network of the top 10 genes was shown in Figure . The top 10 genes displaying the greatest correlations with GNL3L were listed in Table S1 Supplemental Digital Content (see Table, Supplemental Content, which lists top 10 genes co-expressed with GNL3L identified from the PPI network). The results of STRING were consistent with that of GEPIA database. All 10 genes were positively correlated with GNL3L. GNL3L showed the greatest correlation with snoRNA binding [false discovery rate (FDR) = 0.010], followed by GTPase activity (FDR = 0.019), RNA binding (FDR = 0.025), and GTP binding (FDR = 0.025).
Upregulation of GNL3L expression in esophageal cancer tissues The mRNA and protein expression levels of GNL3L in esophageal cancer were examined by qPCR and IHC, respectively. The mRNA expression levels of GNL3L in esophageal cancer tissues were significantly higher than those in adjacent nonmalignant tissues ( P < .001, Figure A). In addition, we evaluated the difference in the mRNA expression level of GNL3L between different clinicopathological variable groups. As shown in Figure B, cases with poor differentiation ( P = .002) had significantly higher level of GNL3L than those with well and moderate differentiation. Although there was no difference in the mRNA expression level of GNL3L between tumor size ≤ 4 cm and tumor size greater than 4 cm ( P = .063), the mRNA expression level of GNL3L was positively correlated with tumor size ( P = .037). With the development of biotechnologies and the continued reduction in costs, omics data is now massively produced. Therefore, integrating online omics data will help to improve the reliability of the findings. The mRNA expression level of GNL3L in esophageal cancer was validated in the Gene Expression Profiling Interactive Analysis (GEPIA) database, in which 286 normal and 182 esophageal cancer tissues were included. The results suggested that the mRNA expression level of GNL3L was significantly upregulated in esophageal cancer (Figure C). which was consistent with our result. We further evaluated the protein expression of GNL3L in 30 pairs of esophageal cancer and adjacent nonmalignant tissues. IHC assays showed that GNL3L was localized in both cytoplasm and nucleus (Figure ). The protein expression levels of GNL3L in esophageal cancer tissues was significantly higher than those in adjacent nonmalignant tissues ( P < .001).
Association between GNL3L expression and clinicopathological variables of patients with esophageal cancer As shown in Table , high GNL3L expression was significantly associated with clinicopathological variables including pathologic type ( P = .020) and poor differentiation ( P = .007). Furthermore, patients with high GNL3L expression had a tend towards larger tumor size than those with low GNL3L expression, but the difference did not reach statistical significance ( P = .050). There was no correlation between GNL3L expression and other clinical variables including sex, age, drug response, tumor invasion, lymph node metastasis (LNM), and tumor node metastasis stage ( P > .05).
Survival analyses We also examined the effect of GNL3L on the prognosis of patients with esophageal cancer. There was a significant trend toward decreased survival time with increased expression level of GNL3L. As shown in Figure , high GNL3L expression demonstrated significant correlation with poor OS in patients with esophageal cancer ( P = .008). Univariate and multivariate Cox regression analyses of clinicopathological variables regarding OS were listed in Table . The results revealed that pT category [hazard ratio (HR) = 1.977, 95% confidence interval (CI): 1.244-3.142, P = .004], LNM (HR = 2.349, 95%CI: 1.528–3.611, P < .001), tumor node metastasis stage (HR = 2.050, 95%CI: 1.479–2.840, P < .001), and GNL3L expression (HR = 1.504, 95%CI: 1.102–2.053, P = .010) had a remarkable impact on OS. Multivariate Cox regression analysis was subsequently performed based on the Clinicopathological variables with a value of P < .05 in the univariate Cox regression analysis. The results revealed that LNM (adjusted HR = 1.868, 95%CI: 1.118–3.122, P = .017) and GNL3L expression (adjusted HR = 1.483, 95%CI: 1.066–2.063, P = .019) were independent risk factors affecting OS time. Subsequently, we validated the effect of GNL3L on the prognosis of patients with esophageal cancer using the GEPIA database. The results demonstrated that patients with high GNL3L expression had shorter progression-free survival (PFS) and OS than those with low GNL3L expression ( P < .05).
Prediction of interaction networks of GNL3L A gene–gene interaction network for GNL3L was constructed using the STRING v11.0 (Figure ), which were further verified by the GEPIA database to enhance the accuracy and reliability of the network. The node representing GNL3L was connected to the nodes of other genes in terms of co-expression and physical interactions. The protein–protein interaction (PPI) network of the top 10 genes was shown in Figure . The top 10 genes displaying the greatest correlations with GNL3L were listed in Table S1 Supplemental Digital Content (see Table, Supplemental Content, which lists top 10 genes co-expressed with GNL3L identified from the PPI network). The results of STRING were consistent with that of GEPIA database. All 10 genes were positively correlated with GNL3L. GNL3L showed the greatest correlation with snoRNA binding [false discovery rate (FDR) = 0.010], followed by GTPase activity (FDR = 0.019), RNA binding (FDR = 0.025), and GTP binding (FDR = 0.025).
Discussion Although the combined application of surgery, chemotherapy, radiotherapy, and targeted therapy can improve the prognosis of patients with esophageal cancer, the therapeutic efficacy of esophageal cancer is still far from satisfaction. The mortality rate of esophageal cancer remains high for many years. In the present study, we found that GNL3L was upregulated in esophageal cancer. High GNL3L expression was an independent risk factor for an unfavorable OS in patients with esophageal cancer. GNL3L contains a central GTP-binding domain and an N-terminal basic domain in which the activity of nucleoplasmic localization signal is dynamically controlled by the GTP-binding motifs. In addition, the C-terminal domain is essential for the export of GNL3L from the nucleus that shuttles between cytoplasm and nucleus in CRM1-dependent manner. GNL3L interacts with and stabilizes MDM2 proto-oncogene (MDM2) protein by preventing the ubiquitination. Depletion of GNL3L not only inhibits proliferation and colony formation but also suppress invasion and migration of cancer cells. In addition to its role in the regulation of cell proliferation, cell cycle, and anti-apoptosis, GNL3L may accelerate NF-κB-mediated inflammation by upregulating inflammatory molecules, such as IL-4 and IL-8, whereas inflammation promotes carcinogenesis and tumor growth, and facilitates angiogenesis, tumor extravasation, and metastasis. It has been revealed that GNL3L is overexpressed in many types of cancers, including esophageal colorectal, esophageal, and gastric cancers. A recent study by Kannathasan et al revealed that high GNL3L expression was associated with chemoresistance. GNL3L exhibits an oncogenic function that promotes cancer development and progression. However, little is known about the clinical significance of GNL3L in human cancer. In the present study, although GNL3L was upregulated in esophageal cancer, there was no association between GNL3L expression and drug response. Therefore, high GNL3L expression may not influence the chemoresistance of esophageal cancer, but confer a more aggressive phenotype to esophageal cancer than low GNL3L expression. These may explain at least partly why patients with high GNL3L expression had poor prognosis. The traditional theory on cancer initiation and development is that cancer arises from the sequential accumulation of mutations. Since stem cells are the longest-living cells within an organism, the initial oncogenic mutations most likely occur in stem cells. CSCs are small subpopulation of cancer cells within the entire tumor mass (0.001–0.1%) that have the properties of tumorigenesis, unlimited self-renewal, and multilineage differentiation potential and are able to form the bulk of the tumor even from a single cell, whereas the majority of cancer cells are differentiated and have little or no ability to generate new cancer cells. [ – ] It is widely believed that CSCs is responsible for cancer chemoresistance, metastasis, and relapse. [ , , ] With the most recent study, Trevellin et al have shown that stem cell markers CD34, CD133, and Nucleostemin are related to poor prognosis of patients with esophageal cancer. A study by Okamoto et al revealed that the NS/GNL3L-TERT-BRG1 complex was important for the maintenance of CSCs. Therefore, cancer cells with high GNL3L expression might be more likely to have a stem cell phenotype. High GNL3L expression could confer higher proliferation capacity, chemoresistance, invasiveness, and metastasis to cancer cells. Although we did not observe an association between GNL3L expression and drug response, there was a significant difference in OS between patients with low and high GNL3L expression. GNL3L might be a potential therapeutic target for the elimination of esophageal CSCs. In summary, this study revealed that GNL3L is evidently upregulated in esophageal cancer. Our findings provide the first evidence that high GNL3L expression is closely related to an unfavorable prognosis. GNL3L might serve as a biomarker and potential therapeutic target for esophageal cancer. Further studies are undoubtedly required to validate our findings and clarify the underlying molecular mechanism of GNL3L in esophageal cancer.
Conceptualization: Hong Yu, Junxing Huang. Formal analysis: Guihong Dai, Hong Yu, Junxing Huang. Funding acquisition: Hong Yu, Junxing Huang. Investigation: Hong Yu. Methodology: Guihong Dai, Zhongying Guo, Huiping Chen. Resources: Guihong Dai, Min Jiang, Huilin Zhou, Jingjing Bao. Supervision: Junxing Huang. Writing – original draft: Guihong Dai, Hong Yu, Junxing Huang. Writing – review & editing: Hong Yu, Junxing Huang.
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The effectiveness of problem-based learning in pediatric medical education in China | e3f5b35f-409a-433e-9ba9-566401adbaa1 | 6336616 | Pediatrics[mh] | Introduction Problem-based learning (PBL) was originally introduced by Barrows and Tamblyn at McMaster University in the late 1960s. In modern educational theory, it is believed that an ideal teaching method is beneficial for knowledge acquisition and practical skills. When compared to the traditional lecture-based learning (LBL) method, the PBL teaching method is more student centered. Students can solve problems and acquire knowledge through teacher-directed groups. [ – ] Many studies have shown that PBL students perform better in problem-solving and autonomous learning. [ – ] However, there is also evidence that the PBL teaching model is not superior to the LBL model in terms of knowledge acquisition in medical education. As an important branch of medical education, pediatrics is of great significance for medical students as they acquire basic clinical knowledge and skills. Pediatric clinical teaching is a practical teaching process between the teachers and students. The ultimate purpose is to improve students’ clinical thinking ability and application of theoretical knowledge to solve practical problems. However, pediatric teaching has unique difficulties compared with adult clinical medicine disciplines. For example, due to the young age of pediatric patients, it is not easy for patients to communicate with the clinicians, which ultimately leads to difficulty in teaching and performing physical examinations. Therefore, it is very important to find a teaching method that can stimulate students’ interest, improve their ability to solve practical problems and cultivate their clinical thinking. Unlike developed Western countries, the application of PBL in medical education is not a conventional teaching method in China for many reasons, and the effectiveness of PBL education in pediatric medicine in China is still controversial. The aim of the current meta-analysis was to investigate the effectiveness of the PBL teaching model compared to the traditional teaching methods of pediatric medical education used in China. The purpose of this meta-analysis was to assess whether the PBL teaching model, when compared to traditional teaching, was associated with the following: higher theoretical knowledge scores, higher skill scores, and higher case analysis scores.
Materials and methods The method used for this meta-analysis is based on the PRISMA checklist guidelines. Ethical approval was unnecessary because this study is a review of previously published articles and does not involve access to individual participants’ data. 2.1 Search strategy We searched Chinese electronic databases, including the China National Knowledge Infrastructure, WanFang Data, the China Science Periodical Database, and the Chinese BioMedical Literature Database. We also searched English electronic databases, including PubMed, Embase, and the Cochrane Central Register of Controlled Trials. The databases were systematically searched from inception up to June 2018. The following keywords were used: “problem-based learning OR PBL” AND “China OR Chinese” AND “pediatric OR children.” There were no language restrictions. 2.2 Inclusion criteria The studies selected for the meta-analysis met the following criteria: the target population was pediatric medical students in China; the interventions used were PBL teaching in the experimental group and LBL teaching in the control group; the study design was controlled trials in pediatric medical education; and the outcome measurements included theoretical knowledge scores, skill scores, or case analysis scores in pediatric medicine. The exclusion criterion was the duplication of published literature, and if duplicate research was published, the study with the largest sample size was retained. All of the titles and abstracts were reviewed independently by the 2 reviewers (YM, XL). Any differences were resolved through consensus, and if necessary, a 3rd reviewer was consulted. 2.3 Assessment of methodologic quality The methodologic quality of each study was evaluated independently by the 2 reviewers (YM, XL) using the Cochrane Collaboration for Systematic Reviews guidelines. The following seven items were assessed: random sequence generation, allocation sequence concealment, blinding of participants and personnel, blinding of the outcome assessment, incomplete outcome data, selective reporting, and other biases. The overall methodologic quality of each included study was assessed as “low risk of bias,” “high risk of bias,” or “unclear risk of bias.” 2.4 Data extraction and outcome measures The 2 reviewers (YM, XL) independently extracted the eligibility study results from the predefined data fields. The following information was extracted: the 1st author's name, the published date, the study type, the number of participants, the major of the students, the course name, the school system, and the outcome measures. The outcome measures used in this meta-analysis were the theoretical knowledge scores, skill scores, and case analysis scores in both the PBL group and the LBL group. 2.5 Data synthesis Statistical analyses were performed using RevMan 5 software (Version 5.3; Cochrane Collaboration, London, UK). The continuous data of the theoretical knowledge, skill, and case analysis scores were used to calculate the standardized mean difference with 95% confidence interval (CI). A test for heterogeneity was completed using the Chi-squared test and the I 2 statistic. If the Chi-squared test >0.1 or if the I 2 < 50%, the fixed effects model was used. A random-effects model was used if the Chi-squared test <0.1 or the I 2 > 50%. Publication bias was assessed independently using funnel plots of the theoretical knowledge, skill, and case analysis scores.
Search strategy We searched Chinese electronic databases, including the China National Knowledge Infrastructure, WanFang Data, the China Science Periodical Database, and the Chinese BioMedical Literature Database. We also searched English electronic databases, including PubMed, Embase, and the Cochrane Central Register of Controlled Trials. The databases were systematically searched from inception up to June 2018. The following keywords were used: “problem-based learning OR PBL” AND “China OR Chinese” AND “pediatric OR children.” There were no language restrictions.
Inclusion criteria The studies selected for the meta-analysis met the following criteria: the target population was pediatric medical students in China; the interventions used were PBL teaching in the experimental group and LBL teaching in the control group; the study design was controlled trials in pediatric medical education; and the outcome measurements included theoretical knowledge scores, skill scores, or case analysis scores in pediatric medicine. The exclusion criterion was the duplication of published literature, and if duplicate research was published, the study with the largest sample size was retained. All of the titles and abstracts were reviewed independently by the 2 reviewers (YM, XL). Any differences were resolved through consensus, and if necessary, a 3rd reviewer was consulted.
Assessment of methodologic quality The methodologic quality of each study was evaluated independently by the 2 reviewers (YM, XL) using the Cochrane Collaboration for Systematic Reviews guidelines. The following seven items were assessed: random sequence generation, allocation sequence concealment, blinding of participants and personnel, blinding of the outcome assessment, incomplete outcome data, selective reporting, and other biases. The overall methodologic quality of each included study was assessed as “low risk of bias,” “high risk of bias,” or “unclear risk of bias.”
Data extraction and outcome measures The 2 reviewers (YM, XL) independently extracted the eligibility study results from the predefined data fields. The following information was extracted: the 1st author's name, the published date, the study type, the number of participants, the major of the students, the course name, the school system, and the outcome measures. The outcome measures used in this meta-analysis were the theoretical knowledge scores, skill scores, and case analysis scores in both the PBL group and the LBL group.
Data synthesis Statistical analyses were performed using RevMan 5 software (Version 5.3; Cochrane Collaboration, London, UK). The continuous data of the theoretical knowledge, skill, and case analysis scores were used to calculate the standardized mean difference with 95% confidence interval (CI). A test for heterogeneity was completed using the Chi-squared test and the I 2 statistic. If the Chi-squared test >0.1 or if the I 2 < 50%, the fixed effects model was used. A random-effects model was used if the Chi-squared test <0.1 or the I 2 > 50%. Publication bias was assessed independently using funnel plots of the theoretical knowledge, skill, and case analysis scores.
Results 3.1 Search results The flow chart of the study inclusion and exclusion criteria is shown in Figure . In total, 317 potentially relevant studies were identified. At the screening stage, 305 studies were excluded, since they did not meet the inclusion criteria. Thus, a total of 12 RCTs, [ – ] including 1003 medical students, were included in the meta-analysis. The analysis included 509 students in the PBL group and 494 students in the LBL group. Sample sizes ranged from 20 to 68. All of the included studies were published between 2007 and 2017. The types of courses included 2 courses on pediatric teaching, 1 course on pediatric nervous system diseases, and 7 courses [ – , ] on pediatric clinical practice. The scores on the pediatric knowledge examination were used to assess the students’ mastery of the related theoretical knowledge, and the scores on the pediatric skill and case analysis tests were used to evaluate the students’ clinical skills. Table shows the baseline characteristics of all of the included studies. Figure shows the risk of bias assessment of the 12 included studies. Nine studies described the methods of the random sequences in detail, [ , , – , ] but the other 3 studies’ methods [ , , ] were unclear. All studies reported any incomplete outcome data, selective reporting, and other biases. The allocation concealment and blinding methods were not stated in these studies. The meta-analysis independently used funnel plots of the theoretical knowledge, skill, and case analysis scores to assess any publication bias; the plots were generally symmetrical and suggested a low publication bias (Figs. – ). 3.2 Meta-analysis of theoretical knowledge scores All of the included studies [ – ] reported relevant data on the theoretical knowledge scores (509 and 494 students in the PBL and LBL groups, respectively). The meta-analysis of the theoretical knowledge scores found that the PBL teaching model significantly increased theoretical knowledge scores by a mean of 1.16 compared to those of the LBL teaching model (95% CI, 0.79–1.52; P < .00001). The random effects model was used for the meta-analysis because of a high level of heterogeneity ( P < .00001, I 2 = 86%) (Fig. ). 3.3 Meta-analysis of skill scores A total of 5 studies [ , , , , ] reported relevant data on skill scores (187 and 183 students in the PBL and LBL groups, respectively). The meta-analysis of the skill scores found that the PBL teaching model significantly increased skill scores by a mean of 1.56 compared with those of the LBL teaching model (95% CI, 0.87–2.25; P < .00001). The random effects model was used for the meta-analysis because of a high level of heterogeneity ( P < .00001, I 2 = 88%) (Fig. ). 3.4 Meta-analysis of case analysis scores A total of 4 studies [ , , , ] reported relevant data on case analysis scores (154 and 142 students in the PBL and LBL groups, respectively). The meta-analysis of the case analysis scores found that the PBL teaching model significantly increased case analysis scores by a mean of 1.54 compared with the LBL teaching model (95% CI, 0.86–2.23; P < .00001). The random effects model was used for the meta-analysis because of a high level of heterogeneity ( P = .0002, I 2 = 85%) (Fig. ).
Search results The flow chart of the study inclusion and exclusion criteria is shown in Figure . In total, 317 potentially relevant studies were identified. At the screening stage, 305 studies were excluded, since they did not meet the inclusion criteria. Thus, a total of 12 RCTs, [ – ] including 1003 medical students, were included in the meta-analysis. The analysis included 509 students in the PBL group and 494 students in the LBL group. Sample sizes ranged from 20 to 68. All of the included studies were published between 2007 and 2017. The types of courses included 2 courses on pediatric teaching, 1 course on pediatric nervous system diseases, and 7 courses [ – , ] on pediatric clinical practice. The scores on the pediatric knowledge examination were used to assess the students’ mastery of the related theoretical knowledge, and the scores on the pediatric skill and case analysis tests were used to evaluate the students’ clinical skills. Table shows the baseline characteristics of all of the included studies. Figure shows the risk of bias assessment of the 12 included studies. Nine studies described the methods of the random sequences in detail, [ , , – , ] but the other 3 studies’ methods [ , , ] were unclear. All studies reported any incomplete outcome data, selective reporting, and other biases. The allocation concealment and blinding methods were not stated in these studies. The meta-analysis independently used funnel plots of the theoretical knowledge, skill, and case analysis scores to assess any publication bias; the plots were generally symmetrical and suggested a low publication bias (Figs. – ).
Meta-analysis of theoretical knowledge scores All of the included studies [ – ] reported relevant data on the theoretical knowledge scores (509 and 494 students in the PBL and LBL groups, respectively). The meta-analysis of the theoretical knowledge scores found that the PBL teaching model significantly increased theoretical knowledge scores by a mean of 1.16 compared to those of the LBL teaching model (95% CI, 0.79–1.52; P < .00001). The random effects model was used for the meta-analysis because of a high level of heterogeneity ( P < .00001, I 2 = 86%) (Fig. ).
Meta-analysis of skill scores A total of 5 studies [ , , , , ] reported relevant data on skill scores (187 and 183 students in the PBL and LBL groups, respectively). The meta-analysis of the skill scores found that the PBL teaching model significantly increased skill scores by a mean of 1.56 compared with those of the LBL teaching model (95% CI, 0.87–2.25; P < .00001). The random effects model was used for the meta-analysis because of a high level of heterogeneity ( P < .00001, I 2 = 88%) (Fig. ).
Meta-analysis of case analysis scores A total of 4 studies [ , , , ] reported relevant data on case analysis scores (154 and 142 students in the PBL and LBL groups, respectively). The meta-analysis of the case analysis scores found that the PBL teaching model significantly increased case analysis scores by a mean of 1.54 compared with the LBL teaching model (95% CI, 0.86–2.23; P < .00001). The random effects model was used for the meta-analysis because of a high level of heterogeneity ( P = .0002, I 2 = 85%) (Fig. ).
Discussion The PBL is a student-centered teaching model, which has been widely used in various medical education programs. However, considering the different educational system and cultural background in China, the effectiveness of the PBL teaching method might be affected, so there is controversy regarding its use in China. As far as we know, there are very few studies that have assessed the role of PBL in pediatric medical education. Therefore, we performed the current meta-analysis to evaluate the effectiveness of the PBL teaching model in pediatric medical education in China. The main finding of the meta-analysis was that the PBL teaching model significantly increased theoretical knowledge scores by a mean of 1.16, skill scores by a mean of 1.56, and case analysis scores by a mean of 1.54 when compared with those of the LBL teaching model. This is consistent with recent PBL studies in pharmaceutical and dental education in China. In clinical practice, the traditional teaching method sees the teacher as the core, while the student can only passively acquire the knowledge; the students might experience a lack of enthusiasm and doubt the doctors’ sense of responsibility. By introducing the PBL teaching method into clinical practice teaching, through reasoning, analyzing and applying their knowledge, students achieve the learning tasks of self-study, reasoning, and knowledge application abilities. On the contrary, the new teaching model also urges teachers to master the latest information and scientific research results. Therefore, the students’ basic knowledge and clinical skills are greatly improved, as well as their communication ability. However, PBL teaching has put forward higher requirements for teachers, especially in the writing of medical records, which not only requires teachers’ professional knowledge but also requires higher comprehensive literacy, as well as different teaching objectives. It is necessary to organize the various contents of medical records and to train the teaching doctors accordingly. For example, if PBL teaching is carried out in a theoretical course, it is necessary to integrate the medical curriculum. Therefore, the growth potential of the PBL teaching model in China depends on more enthusiastic teachers’ participation, and there is still much research to be done in China. Some studies have even reported that PBL has had a negative impact on knowledge examinations due to difficulty acquiring factual knowledge. There are some possible reasons why the results are inconsistent. First, it is necessary to take into account the differences in higher medical education between China and the Western countries. The PBL teaching model is a new teaching model for most Chinese students, since they have not received this kind of education since the beginning of primary school. PBL teaching methods are more likely to stimulate their interest in learning and to contribute to the process of knowledge acquisition. Second, pediatric medicine is a very practical subject. Clinical learning is the starting point for medical students to enter clinical practice and the bridge between theory and practice. It plays the role of connecting the past and the future in medical education. However, the way in which to train qualified clinicians is a problem that has been considered and explored in clinical teaching. The PBL model is a kind of heuristic model between the student-centered and teacher-oriented methods, which is different from the traditional teaching model. [ , , ] By using PBL teaching, students can better receive clinical thinking training at the initial stage of their specialized clinical courses, and the whole teaching process becomes a process of students’ knowledge seeking and discovery. Despite the rapid development of medical technology, basic clinical skills, such as theoretical knowledge, physical examination, and case analysis, are still the most important and effective tools for the diagnosis of diseases. Therefore, the development of these skills in pediatric medical education is essential for medical students. According to our findings, PBL has a strong positive impact on students’ skill performance. The most important aspects of pediatric medical education is to cultivate students’ clinical diagnostic skills and ability to solve clinical problems. Therefore, compared with traditional teaching methods, PBL has more obvious advantages in clinical teaching. The results of this meta-analysis are consistent with previous findings that PBL can effectively improve clinical skills. Wang et al performed a meta-analysis with a total of 2086 medical students, which suggested that PBL seems to be more effective in improving knowledge and skills than traditional teaching methods used in physical diagnostics education in China. These results encourage Chinese educators to find new teaching models, including the PBL teaching model, to improve medical students’ performance and clinical skills. The reasons behind these trends are very simple. In the early years, studies showed that students who received a PBL medical education had definitively better scores on theoretical knowledge and clinical skills than students who received a traditional medical education. [ , , ] Although PBL shows many benefits, it is difficult to apply PBL widely in Chinese pediatric medical education. First, the PBL teaching method requires a long time commitment for students. Second, in the early stages of PBL teaching, students may lack systematic and in-depth theoretical knowledge and focus on problem solving. Therefore, students may be unable to organize and master the internal logical structure of the knowledge, which may increase learning difficulties. Different from the Western countries, Chinese students have long accepted the traditional teaching model, which is considered to be sufficient for accumulating theoretical knowledge. Third, although China has become the world's economic leader, its fast-growing education system is tasked with creating enough medical professionals to care for nearly 20% of the world's population. However, a majority of universities think they do not have enough faculty to teach PBL and that the PBL teaching model takes a long time. Moreover, some universities are not using PBL currently because of a lack of financial and faculty resources. Given the above reasons, this may affect the promotion and application of PBL. In the current meta-analysis, there is also high heterogeneity in the results of the theoretical knowledge, skill, and case study scores, which may be due to the following factors. First, randomized controlled trials (RCTs) are widely believed to provide the highest level of evidence for the effectiveness of intervention. However, it is not always possible to use very strict RCTs in medical education. Although most of the studies in this meta-analysis were designed as RCTs, there were still 3 studies that did not describe their methods for random sequence generation, and none of them described the allocation concealment or blinding methods. Consequently, the methodologic qualities of the methods were not high in this meta-analysis. Second, the definition and implementation of PBL teaching are closely related to the quality of medical education, the ability of the educator, and the cultural background of the medical students in China, and these factors may cause significant differences in the effect of PBL implementation. Third, there are no uniform criteria for assessing the effectiveness of PBL on knowledge and skills. There are some limitations to the present study. First, there were only Chinese medical students included in this study, which suggests the results may be more suitable for Chinese and Asian medicine education than Western medicine education. Therefore, the results of this meta-analysis may have limited geographical generalization. Second, the present study was based on only 12 RCTs with 1003 medical students in pediatric medical education in China up to June 2018, so the sample size was relatively small in this meta-analysis. Thus, a greater number of high-quality RCTs are needed to confirm the above conclusions. Third, a subgroup analysis was not performed based on the different types of courses, because the analysis was limited by incomplete data. Fourth, the methodologic quality of this study on the effectiveness of PBL in Chinese pediatric medical education is generally low, and the results are heterogeneous.
Conclusion The current meta-analysis shows that PBL in pediatric medical education in China appears to be more advantageous than the traditional teaching method in improving theoretical knowledge, skill, and case analysis scores. However, a more controlled design of RCT is needed to confirm the above conclusions in future work.
Data curation: Xiaoxi Lu. Formal analysis: Yimei Ma. Investigation: Yimei Ma. Methodology: Xiaoxi Lu. Software: Yimei Ma. Supervision: Yimei Ma, Xiaoxi Lu. Writing – original draft: Yimei Ma, Xiaoxi Lu. Writing – review & editing: Yimei Ma, Xiaoxi Lu.
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Good clinical scores, no evidence of excessive anterior tibial translation, a high return to sport rate and a low re-injury rate is observed following anterior cruciate ligament reconstruction using autologous hamstrings augmented with suture tape | 3641d44b-3148-4d6a-9986-cc9089233c90 | 10015537 | Suturing[mh] | Anterior cruciate ligament reconstruction (ACLR) is common and, whilst a primary post-operative goal for many patients is a return to sport (RTS), it has been reported that across all patients, only 65% of patients return to their pre-injury level of sport . Furthermore, an overall secondary re-injury rate of 7% has been reported, along with an 8% incidence of contralateral ACL tear, with a combined (ipsilateral and contralateral) ACL injury rate of 23% specifically in patients < 25 years of age who do RTS . The reasons for re-injury are multifactorial , though a recent systematic review reported no significant differences in graft failure rates across varied graft types (quadriceps, hamstring and patellar tendon autografts, or allografts) . In addition to ensuring that strength and functional performance is best restored given their link with re-injury risk , surgical reconstruction techniques involving autograft (or allograft) augmentation have been proposed [ – ] in an attempt to improve outcomes and reduce re-injury rates. ACLR augmentation may permit early ACL reinforcement and graft stability prior to graft incorporation, also expediting post-operative recovery and accelerating rehabilitation . A range of augmented procedures and devices have been reported . Encouraging clinical and RTS outcomes have been more recently reported when using a LARS ligament (LARS, Ligament Augmentation Reconstruction System, Corin Pty. Ltd.) to augment a hamstrings autograft [ , , ], with patient outcomes of those undergoing augmented ACLR better than those undergoing non-augmented ACLR . However, earlier use of synthetic augmentation, including LARS, appeared to present with excessive synovitis and in higher ACL graft failure rates [ – ]. A more recently employed device to augment an ACLR is FiberTape® (Arthrex, Naples, Florida, USA) [ , , , ], with a retrospective comparison of outcomes in patients undergoing ACLR with and without suture augmentation with FiberTape® demonstrating improved outcomes with augmentation . However, studies using FiberTape® augmentation are limited and a greater number of published papers exist related to the use of FiberTape® reinforcement in the context of ACL repair [ – ], rather than reconstruction, although even then many of these are technical notes and not studies reporting patient outcomes. This study presents the clinical outcomes of a prospective patient cohort undergoing ACLR employing autologous hamstrings augmented with suture tape, combined with a progressive, structured rehabilitation programme. With the aforementioned reported re-injury and RTS rates in mind, it was hypothesized that: (1) no significant post-operative differences in anterior tibial translation would exist between the operated and non-operated limbs, (2) a low re-injury rate (< 5%) would be observed over the 24-month period, (3) a high RTS rate (> 70%) would be observed at 12 and 24 months and (4) a significant improvement in patient-reported outcome measures (PROMs) and objective outcomes would be observed following surgery.
Patients Between March 2018 and November 2019, 57 patients scheduled for ACLR employing a hamstrings autograft and augmented with a suture tape were referred by a single surgeon in a private orthopaedic clinic for study discussion, recruitment and subsequent pre-operative review, of which 53 patients elected to participate (Fig. , Level IV prospective case series). Patients were candidates for surgery based on history, current symptoms and orthopaedic clinical examination, whilst magnetic resonance imaging (MRI) confirmed the ACL rupture in all patients. Patients were invited to participate in the study if they were deemed candidates for surgery, were 16–50 years of age (and skeletally mature) and required an isolated primary ACLR, with or without concomitant meniscal surgery. Whilst not encountered, patients were excluded from study participation if they presented with a body mass index (BMI) ≥ 40 or were unwilling or unable to participate in the post-operative rehabilitation protocol (outlined below). Ethics approval was provided by the relevant Human Research Ethics Committee (HREC) and the written consent of all participants was obtained prior to review. The surgical technique All surgeries were performed by the senior author. Examination under anaesthesia was performed prior to tourniquet application to assess laxity of the injured ACL knee in comparison to the contralateral knee and clinically confirm a rupture of the ACL. Knee arthroscopy was subsequently performed to confirm the clinical diagnosis and further evaluate concomitant and/or chondral damage, which was addressed initially if required. Unstable ACL remnant tissue was then removed. The ACL tunnels were routinely dictated by the anatomical positions of the existing ACL remnants. The tibial footprint of the ACL was initially identified, and all unstable remnant was removed. The tibial jig was placed centrally in the tibial footprint, and the tibial tunnel was prepared within the centre of the tibial ACL remnant (Fig. ). Femoral tunnel preparation was performed in a similar way. The femoral anteromedial bundle soft tissue footprint was identified and an awl mark was created. A secondary check was via confirming a prepared tunnel position 2-4 mm off the posterior notch wall, generally in the 2.00 o’clock (left knee) or 10.00 o’clock (right knee) position (Fig. ), with femoral tunnels drilled in maximal knee flexion. The ACL tibial remnant was cleared from the tibia to allow unobstructed passage of the graft within the knee. Semitendinosus and gracilis tendons were harvested from the ipsilateral knee through a 2–3 cm transverse incision approximately 1 cm above the pes anserinus, and prepared as doubled grafts. The combined diameter was measured to establish bone tunnel size reaming, with a minimum graft diameter of 8 mm confirmed for all cases. The harvested hamstring grafts were then passed through the ACL TightRope RT (Arthrex, Naples, Florida, USA) implant loop of the suspensory button creating a 4-strand hamstring graft. A FiberTape® (Arthrex, Naples, Florida, USA) was then attached by a half hitch to the femoral button to act as a ‘seat belt’ augmentation of the graft construct, creating a two-strand internal brace that was essentially placed alongside the autograft (Fig. ). The graft was passaged after placing a suture via a shuttle technique from the tibia through to the button tunnel on the femur. The graft was seated with maximal manual tension whilst cycling the knee ten times. The tibial fixation was performed with a peek interference screw (Arthrex, Naples, Florida, USA), 1 mm larger than the tunnel and positioned in full knee extension. The two internal brace strands were fixed in an accessory position with a knotless anchor 1 cm distal to the tibial tunnel. The knee was place in full extension and the tight rope femoral suture was toggled to optimize maximum graft tension. The final graft construct is shown in Fig. . Rehabilitation A standardized rehabilitation programme was implemented for all patients, aiming for a supervised therapist session every 2 weeks (starting from 2 weeks post-surgery) for the first 5–6 months (12 supervised sessions in total), with ongoing periodic review beyond 6 months post-surgery as required. These sessions were supplemented with an independent home and/or gym-based programme, aiming for 2–3 sessions in total per week. Whilst the home/gym-based programme was not closely monitored, 88.7% (47 of 53) of patients attended ≥ 75% of the designated supervised sessions, with the remaining 11.3% (6 of 53) of patients attending 58–67% of the designated sessions. This was generally due to geographical location and/or COVID-19 restrictions, and these patients were more closely monitored from afar as needed. All supervised rehabilitation was undertaken in a single, private out-patient therapy clinic. Table provides an overview of the programme implemented. In brief, early post-operative management included weight bearing as tolerated, early circulatory (such as foot/ankle pumps) and knee range of motion (ROM) exercises, followed by a progressive programme aiming to restore strength and load capacity, with progression towards running and activities that better prepared the patient for an eventual RTS. Whilst late-stage progression through sport-specific training-based activities was also dependent on the patient’s specific sport, these aspects were not documented as part of the current patient cohort and patients transitioned through these components of training at their own discretion in collaboration with their sporting team. Whilst RTS was not advised until ≥ 9 months post-surgery and patients were counselled on specific objective criteria that should be attained before returning to sports activities (such as the restoration active knee extension ROM and flexion ROM LSI ≥ 90%, ≥ 90% LSI in hop tests and peak isokinetic knee extensor and flexor strength), this was not enforced and still largely at the final discretion of the patient. Patient assessment First, all patients underwent a formal knee laxity exam performed in the clinic by the senior author (PA) at 4 months post-surgery, specifically to assess rotatory laxity grading via pivot shift evaluation. Anterior tibial translation (mm) was measured on both knees during a maximal manual test (MMT) using the KT-1000 knee arthrometer (MEDmetric Corp., San Diego, CA, USA) at 6, 9, 12 and 24 months post-surgery. Active knee flexion and extension range of motion (ROM, degrees) using a hand-held long-arm goniometer was assessed on the operated limb at 6 weeks, as well as 4, 6, 9, 12 and 24 months post-surgery. Patients underwent a 4-hop battery and assessment of peak isokinetic knee extensor and flexor strength (Nm) at 6, 9, 12 and 24 months. The 4-hop battery included the single hop for distance (SHD, m), the 6 m timed hop (6MTH, s), the triple hop for distance (THD, m) and the triple crossover hop for distance (TCHD, m) . Peak isokinetic knee extensor and flexor strength was measured at 90°/s, using an isokinetic dynamometer (Isosport International, Gepps Cross, South Australia). These reviews and all nominated assessments (apart from the laxity exam undertaken by the senior author at 4 months) were undertaken by a qualified therapist, with 20 years of experience undertaking all of the aforementioned assessments. Several patient-reported outcome measures (PROMs) were undertaken pre-surgery and at various post-operative time-points. These included the International Knee Documentation Committee (IKDC) Subjective Knee Evaluation Form , the Knee Outcome Survey (KOS) Activities of Daily Living Scale , the Cincinnati Knee Rating System (CKRS) , the Lysholm Knee Score (LKS) , the Tegner Activity Scale (TAS) , the Anterior Cruciate Ligament Return to Sport after Injury (ACL-RSI) and the Noyes Sports Activity Rating Scale (NSARS) . A satisfaction score was employed at 24 months post-surgery, evaluating patient satisfaction with the surgery overall, as well as with the surgery to relieve pain, improve the ability to perform normal daily and work activities, improve the ability to return to recreational activities (including walking, swimming, cycling, golf, dancing), and improve the ability to participate in sport (including sports such as tennis, netball, soccer and football). A Likert Response Scale was employed with descriptors Very Satisfied, Somewhat Satisfied, Somewhat Dissatisfied and Very Dissatisfied. Data and statistical analysis For this prospective study, a priori sample size power calculation was determined based on the recommendations of Cohen and employing data previously collected and published in patients undergoing ACLR with a hamstrings autograft, augmented with LARS . Therefore, in using this existing data and for an anticipated moderate effect size ( d = 0.67) in the primary outcome (anterior tibial translation as evaluated via side-to-side difference in anterior tibial translation in mm for the KT-1000 at 6 months post-surgery), assuming an SD of 3 mm and at alpha level of 0.05 and a power of 0.9, the sample size was estimated at 49 patients to demonstrate a significant difference in anterior tibial translation between the operated and non-operated knees. Overall, 53 patients were recruited to allow for attrition over the assessment period. For all subjective (PROMs) and objective outcomes, the means (SD, range) were presented at the designated assessment time-points, whilst repeated-measures analysis of variance (ANOVA) was employed to assess change in these outcomes over time. Limb Symmetry Indices (LSIs) were calculated and presented for the hop and strength tests, further categorized by the number and percentage of patients with LSIs ≥ 90% for all four hop tests (at each time-point), as well as all hop tests combined with peak isokinetic knee extension and flexion torque. For KT-1000 anterior tibial translation measures, t tests were employed to compare the operated and non-operated limbs at 6 months post-surgery, whilst repeated-measures ANOVA assessed any change in the side-side limb anterior tibial translation difference over time. KT-1000 anterior tibial translation measures were further categorized based on side-to-side difference as normal (< 3 mm), nearly normal (3–5 mm), abnormal (6–10 mm) and severely abnormal (> 10 mm) . The NSARS was employed to present the number (and percentage) of patients participating in Level 1 (participation 4–7 days/week) or Level 2 (participation 1–3 days per week) activities that included jumping, hard pivoting and cutting sports pre-injury and at 12- and 24 months post-surgery. The number (and percentage) of patients reporting ‘Very Satisfied’, ‘Somewhat Satisfied’, ‘Somewhat Dissatisfied’ and ‘Very Dissatisfied’ within each of the satisfaction domains at 24 months post-surgery was presented. The number (and type) of surgical complications, adverse events, re-operations and re-injuries were presented. Where appropriate, statistical analysis was performed using SPSS software (SPSS, Version 27.0, SPSS Inc., USA), with statistical significance determined at p < 0.05.
Between March 2018 and November 2019, 57 patients scheduled for ACLR employing a hamstrings autograft and augmented with a suture tape were referred by a single surgeon in a private orthopaedic clinic for study discussion, recruitment and subsequent pre-operative review, of which 53 patients elected to participate (Fig. , Level IV prospective case series). Patients were candidates for surgery based on history, current symptoms and orthopaedic clinical examination, whilst magnetic resonance imaging (MRI) confirmed the ACL rupture in all patients. Patients were invited to participate in the study if they were deemed candidates for surgery, were 16–50 years of age (and skeletally mature) and required an isolated primary ACLR, with or without concomitant meniscal surgery. Whilst not encountered, patients were excluded from study participation if they presented with a body mass index (BMI) ≥ 40 or were unwilling or unable to participate in the post-operative rehabilitation protocol (outlined below). Ethics approval was provided by the relevant Human Research Ethics Committee (HREC) and the written consent of all participants was obtained prior to review.
All surgeries were performed by the senior author. Examination under anaesthesia was performed prior to tourniquet application to assess laxity of the injured ACL knee in comparison to the contralateral knee and clinically confirm a rupture of the ACL. Knee arthroscopy was subsequently performed to confirm the clinical diagnosis and further evaluate concomitant and/or chondral damage, which was addressed initially if required. Unstable ACL remnant tissue was then removed. The ACL tunnels were routinely dictated by the anatomical positions of the existing ACL remnants. The tibial footprint of the ACL was initially identified, and all unstable remnant was removed. The tibial jig was placed centrally in the tibial footprint, and the tibial tunnel was prepared within the centre of the tibial ACL remnant (Fig. ). Femoral tunnel preparation was performed in a similar way. The femoral anteromedial bundle soft tissue footprint was identified and an awl mark was created. A secondary check was via confirming a prepared tunnel position 2-4 mm off the posterior notch wall, generally in the 2.00 o’clock (left knee) or 10.00 o’clock (right knee) position (Fig. ), with femoral tunnels drilled in maximal knee flexion. The ACL tibial remnant was cleared from the tibia to allow unobstructed passage of the graft within the knee. Semitendinosus and gracilis tendons were harvested from the ipsilateral knee through a 2–3 cm transverse incision approximately 1 cm above the pes anserinus, and prepared as doubled grafts. The combined diameter was measured to establish bone tunnel size reaming, with a minimum graft diameter of 8 mm confirmed for all cases. The harvested hamstring grafts were then passed through the ACL TightRope RT (Arthrex, Naples, Florida, USA) implant loop of the suspensory button creating a 4-strand hamstring graft. A FiberTape® (Arthrex, Naples, Florida, USA) was then attached by a half hitch to the femoral button to act as a ‘seat belt’ augmentation of the graft construct, creating a two-strand internal brace that was essentially placed alongside the autograft (Fig. ). The graft was passaged after placing a suture via a shuttle technique from the tibia through to the button tunnel on the femur. The graft was seated with maximal manual tension whilst cycling the knee ten times. The tibial fixation was performed with a peek interference screw (Arthrex, Naples, Florida, USA), 1 mm larger than the tunnel and positioned in full knee extension. The two internal brace strands were fixed in an accessory position with a knotless anchor 1 cm distal to the tibial tunnel. The knee was place in full extension and the tight rope femoral suture was toggled to optimize maximum graft tension. The final graft construct is shown in Fig. .
A standardized rehabilitation programme was implemented for all patients, aiming for a supervised therapist session every 2 weeks (starting from 2 weeks post-surgery) for the first 5–6 months (12 supervised sessions in total), with ongoing periodic review beyond 6 months post-surgery as required. These sessions were supplemented with an independent home and/or gym-based programme, aiming for 2–3 sessions in total per week. Whilst the home/gym-based programme was not closely monitored, 88.7% (47 of 53) of patients attended ≥ 75% of the designated supervised sessions, with the remaining 11.3% (6 of 53) of patients attending 58–67% of the designated sessions. This was generally due to geographical location and/or COVID-19 restrictions, and these patients were more closely monitored from afar as needed. All supervised rehabilitation was undertaken in a single, private out-patient therapy clinic. Table provides an overview of the programme implemented. In brief, early post-operative management included weight bearing as tolerated, early circulatory (such as foot/ankle pumps) and knee range of motion (ROM) exercises, followed by a progressive programme aiming to restore strength and load capacity, with progression towards running and activities that better prepared the patient for an eventual RTS. Whilst late-stage progression through sport-specific training-based activities was also dependent on the patient’s specific sport, these aspects were not documented as part of the current patient cohort and patients transitioned through these components of training at their own discretion in collaboration with their sporting team. Whilst RTS was not advised until ≥ 9 months post-surgery and patients were counselled on specific objective criteria that should be attained before returning to sports activities (such as the restoration active knee extension ROM and flexion ROM LSI ≥ 90%, ≥ 90% LSI in hop tests and peak isokinetic knee extensor and flexor strength), this was not enforced and still largely at the final discretion of the patient.
First, all patients underwent a formal knee laxity exam performed in the clinic by the senior author (PA) at 4 months post-surgery, specifically to assess rotatory laxity grading via pivot shift evaluation. Anterior tibial translation (mm) was measured on both knees during a maximal manual test (MMT) using the KT-1000 knee arthrometer (MEDmetric Corp., San Diego, CA, USA) at 6, 9, 12 and 24 months post-surgery. Active knee flexion and extension range of motion (ROM, degrees) using a hand-held long-arm goniometer was assessed on the operated limb at 6 weeks, as well as 4, 6, 9, 12 and 24 months post-surgery. Patients underwent a 4-hop battery and assessment of peak isokinetic knee extensor and flexor strength (Nm) at 6, 9, 12 and 24 months. The 4-hop battery included the single hop for distance (SHD, m), the 6 m timed hop (6MTH, s), the triple hop for distance (THD, m) and the triple crossover hop for distance (TCHD, m) . Peak isokinetic knee extensor and flexor strength was measured at 90°/s, using an isokinetic dynamometer (Isosport International, Gepps Cross, South Australia). These reviews and all nominated assessments (apart from the laxity exam undertaken by the senior author at 4 months) were undertaken by a qualified therapist, with 20 years of experience undertaking all of the aforementioned assessments. Several patient-reported outcome measures (PROMs) were undertaken pre-surgery and at various post-operative time-points. These included the International Knee Documentation Committee (IKDC) Subjective Knee Evaluation Form , the Knee Outcome Survey (KOS) Activities of Daily Living Scale , the Cincinnati Knee Rating System (CKRS) , the Lysholm Knee Score (LKS) , the Tegner Activity Scale (TAS) , the Anterior Cruciate Ligament Return to Sport after Injury (ACL-RSI) and the Noyes Sports Activity Rating Scale (NSARS) . A satisfaction score was employed at 24 months post-surgery, evaluating patient satisfaction with the surgery overall, as well as with the surgery to relieve pain, improve the ability to perform normal daily and work activities, improve the ability to return to recreational activities (including walking, swimming, cycling, golf, dancing), and improve the ability to participate in sport (including sports such as tennis, netball, soccer and football). A Likert Response Scale was employed with descriptors Very Satisfied, Somewhat Satisfied, Somewhat Dissatisfied and Very Dissatisfied.
For this prospective study, a priori sample size power calculation was determined based on the recommendations of Cohen and employing data previously collected and published in patients undergoing ACLR with a hamstrings autograft, augmented with LARS . Therefore, in using this existing data and for an anticipated moderate effect size ( d = 0.67) in the primary outcome (anterior tibial translation as evaluated via side-to-side difference in anterior tibial translation in mm for the KT-1000 at 6 months post-surgery), assuming an SD of 3 mm and at alpha level of 0.05 and a power of 0.9, the sample size was estimated at 49 patients to demonstrate a significant difference in anterior tibial translation between the operated and non-operated knees. Overall, 53 patients were recruited to allow for attrition over the assessment period. For all subjective (PROMs) and objective outcomes, the means (SD, range) were presented at the designated assessment time-points, whilst repeated-measures analysis of variance (ANOVA) was employed to assess change in these outcomes over time. Limb Symmetry Indices (LSIs) were calculated and presented for the hop and strength tests, further categorized by the number and percentage of patients with LSIs ≥ 90% for all four hop tests (at each time-point), as well as all hop tests combined with peak isokinetic knee extension and flexion torque. For KT-1000 anterior tibial translation measures, t tests were employed to compare the operated and non-operated limbs at 6 months post-surgery, whilst repeated-measures ANOVA assessed any change in the side-side limb anterior tibial translation difference over time. KT-1000 anterior tibial translation measures were further categorized based on side-to-side difference as normal (< 3 mm), nearly normal (3–5 mm), abnormal (6–10 mm) and severely abnormal (> 10 mm) . The NSARS was employed to present the number (and percentage) of patients participating in Level 1 (participation 4–7 days/week) or Level 2 (participation 1–3 days per week) activities that included jumping, hard pivoting and cutting sports pre-injury and at 12- and 24 months post-surgery. The number (and percentage) of patients reporting ‘Very Satisfied’, ‘Somewhat Satisfied’, ‘Somewhat Dissatisfied’ and ‘Very Dissatisfied’ within each of the satisfaction domains at 24 months post-surgery was presented. The number (and type) of surgical complications, adverse events, re-operations and re-injuries were presented. Where appropriate, statistical analysis was performed using SPSS software (SPSS, Version 27.0, SPSS Inc., USA), with statistical significance determined at p < 0.05.
Patient demographics and injury/surgery parameters of the 53 patients that were recruited and underwent surgery are demonstrated in Table . Objective results With respect to the 4-month knee laxity exam undertaken by the senior author, all patients presented with a normal (or near normal) pivot shift clinical examination, with no Grade II or III pivot laxity outcomes. For the later-stage KT-1000 assessments, there were no significant anterior tibial translation differences between the operated and non-operated knees at 6 months post-surgery ( p = 0.433), with no significant increase ( p = 0.841) in side-to-side anterior tibial translation from 6 to 24 months (Table ). At 24 months, KT-1000 measurements demonstrated normal (< 3 mm) or near normal (3–5 mm) side-to-side differences in 98.0% of patients (Table ). Knee flexion and extension ROM significantly improved ( p < 0.0001) over time, as did the LSI for peak isokinetic knee extensor torque ( p < 0.0001), the SHD ( p = 0.001), THD ( p = 0.001) and TCHD ( p < 0.0001) (Table ). At 12 months post-surgery, 72.3% of patients presented with an LSI ≥ 90% for every hop test, which dropped to 53.2% of patients when combined with LSIs ≥ 90% for peak isokinetic knee extensor and flexor strength (Table ). This was 79.6% of patients (all four hops) and 61.2% of patients (all four hops combined with strength measures) at 24 months post-surgery (Table ). Subjective results and return to sport All PROMs significantly improved over time ( p < 0.0001) (Table ). As per the NSARS, 90.6% of patients were actively participating in Level 1 or 2 sports that included jumping, hard pivoting, cutting, running, twisting and/or turning pre-injury, which was 70.2% and 85.7% at 12 and 24 months post-surgery, respectively (Table ). At 24-month review, 98.0% of patients were satisfied overall with their surgical outcome, with 93.9% satisfied with their ability to participate in sport (Table ). Complications, re-injuries and secondary surgical procedures Over the course of the 24-month follow-up period, one patient presented with an early wound infection that was treated accordingly without further issue. Three patients underwent secondary surgical procedures, including one patient that underwent arthroscopic lateral meniscectomy for recurrent symptoms at 18 months after his primary ACLR (with an intact ACL at time of secondary surgery) and one patient that underwent lateral meniscal repair at 10 months after his primary ACLR (with an intact ACL at time of secondary surgery, albeit the meniscal tear was new and following a secondary incident). The third patient underwent medial meniscectomy at 6 months after his primary ACLR for recurrent symptoms and, whilst he was doing well and had returned to pivoting sports by 12 months, experienced an ACL re-tear at 17 months after his primary ACLR which continues to be managed non-operatively. This patient had a graft diameter of 9 mm. There were no further ipsilateral re-tears or contralateral tears. The data collected from these patients were still included in the results analysis.
With respect to the 4-month knee laxity exam undertaken by the senior author, all patients presented with a normal (or near normal) pivot shift clinical examination, with no Grade II or III pivot laxity outcomes. For the later-stage KT-1000 assessments, there were no significant anterior tibial translation differences between the operated and non-operated knees at 6 months post-surgery ( p = 0.433), with no significant increase ( p = 0.841) in side-to-side anterior tibial translation from 6 to 24 months (Table ). At 24 months, KT-1000 measurements demonstrated normal (< 3 mm) or near normal (3–5 mm) side-to-side differences in 98.0% of patients (Table ). Knee flexion and extension ROM significantly improved ( p < 0.0001) over time, as did the LSI for peak isokinetic knee extensor torque ( p < 0.0001), the SHD ( p = 0.001), THD ( p = 0.001) and TCHD ( p < 0.0001) (Table ). At 12 months post-surgery, 72.3% of patients presented with an LSI ≥ 90% for every hop test, which dropped to 53.2% of patients when combined with LSIs ≥ 90% for peak isokinetic knee extensor and flexor strength (Table ). This was 79.6% of patients (all four hops) and 61.2% of patients (all four hops combined with strength measures) at 24 months post-surgery (Table ).
All PROMs significantly improved over time ( p < 0.0001) (Table ). As per the NSARS, 90.6% of patients were actively participating in Level 1 or 2 sports that included jumping, hard pivoting, cutting, running, twisting and/or turning pre-injury, which was 70.2% and 85.7% at 12 and 24 months post-surgery, respectively (Table ). At 24-month review, 98.0% of patients were satisfied overall with their surgical outcome, with 93.9% satisfied with their ability to participate in sport (Table ).
Over the course of the 24-month follow-up period, one patient presented with an early wound infection that was treated accordingly without further issue. Three patients underwent secondary surgical procedures, including one patient that underwent arthroscopic lateral meniscectomy for recurrent symptoms at 18 months after his primary ACLR (with an intact ACL at time of secondary surgery) and one patient that underwent lateral meniscal repair at 10 months after his primary ACLR (with an intact ACL at time of secondary surgery, albeit the meniscal tear was new and following a secondary incident). The third patient underwent medial meniscectomy at 6 months after his primary ACLR for recurrent symptoms and, whilst he was doing well and had returned to pivoting sports by 12 months, experienced an ACL re-tear at 17 months after his primary ACLR which continues to be managed non-operatively. This patient had a graft diameter of 9 mm. There were no further ipsilateral re-tears or contralateral tears. The data collected from these patients were still included in the results analysis.
The most important finding from the current study was that an ACLR technique using autologous hamstrings augmented with a suture tape, combined with a structured post-operative rehabilitation programme, produced high-scoring PROMs and patient satisfaction with encouraging performance scores and RTS rates, without evidence of excessive anterior tibial translation and/or a high re-injury rate. No difference in anterior tibial translation between the operated and non-operated limbs was observed, with 98% of patients demonstrating normal (< 3 mm) or near normal (3–5 mm) side-to-side differences up until 24 months post-surgery (the only patient who demonstrated side-to-side anterior tibial translation > 5 mm had suffered a known re-tear). This was in support of the first hypothesis. Further to this, as reported recently by Fiil et al. , excessive post-operative anterior tibial translation may be associated with worse knee-related quality of life, reduced function in sports and an increased revision rate. Whilst the rationale for graft augmentation is largely focussed on early graft reinforcement , the true nature of this reinforcement capacity remains unknown, given the relative lack of biomechanical research on suture tape augmentation. A biomechanical study published by Massey et al. reported a higher load to failure, stiffness and energy to failure when augmenting a graft with internal brace, though this was in the context of ACL repair (not reconstruction). In the current study, only one patient (2%) suffered an ACL re-injury with no contralateral ACL tears up until 24 months, also in support of the second hypothesis. However, it should be acknowledged that whilst Grindem et al. reported an increased re-tear rate up until 9 months post-surgery after which time no further reduction in re-tear risk was observed, theoretically an elevated re-tear risk may extend well after the patient’s RTS so ongoing review is required. Whilst excessive synovitis and high failure rates had limited the ongoing early use of synthetics in ACLR [ – ], these complications were not observed in the current study. In the current study, 70.2% of patients were actively participating in pivoting sports at 12 months post-surgery, which had increased to 85.7% at 24 months (noting that 90.6% of patients were actively participating in pivoting sports pre-injury). This supported the third hypothesis and, of further interest, the 24-month post-operative mean TAS was actually higher than the pre-injury TAS. Whilst similar RTS rates were previously reported in patients following ACLR augmented with LARS , Ardern et al. reported that only 65% of patients return to their pre-injury level of sport, with 55% returning to competitive sport. The higher RTS rates may be influenced by a range of factors including participation and ongoing progression of rehabilitation, which was well adhered to in the current study. Further to this, the underlying rationale for the use of ACLR augmentation is that it may permit early ACL reinforcement and graft stability prior to graft incorporation, also accelerating rehabilitation . Of importance, the encouraging RTS rates currently observed did not appear to increase the risk of excessive anterior tibial translation or re-injury risk. It should be reiterated again that RTS was not advised until ≥ 9 months post-surgery and patients were counselled on specific objective criteria that should be ideally attained before RTS, though this could not be enforced and was at the final discretion of the patient. High-scoring PROMs and high levels of patient satisfaction were reported, whilst mean LSIs ≥ 90% were reported at all post-operative time-points for peak isokinetic knee flexor strength and all hop measures. Furthermore, the mean LSI for peak isokinetic knee extensor strength was ≥ 90% at 12 and 24 months, albeit 75% and 82% at 6 and 9 months, respectively. This was largely in support of the fourth hypothesis. However, when grouped in the form of a performance test battery, 72% and 80% of patients presented with an LSI ≥ 90% for every hop test at 12 and 24 months, respectively. When this test battery further included LSIs ≥ 90% for the knee extensor and flexor strength measures, this was only 53% and 61% at 12 and 24 months, respectively. Despite the low re-injury rate currently observed, existing research has reported an increased re-injury risk if patients fail to meet LSIs ≥ 90% across a range of tests including strength and hop performance measures . In contrast, other research has suggested an increased risk of contralateral ACL injury in the presence of improved strength and/or hop performance symmetry . Therefore, the limitations of employing LSIs to present performance outcomes should be acknowledged, such as the variation in LSI ‘cut-off’ values employed [ , – ] and the potential for LSIs to overestimate function . Whilst the current subjective, objective and RTS outcomes appear similar to those reported previously in patients undergoing ACLR augmented with LARS , and more recent longer term follow-ups of reconstruction/repair with and without other ligament augmentation devices have reported sound clinical results , limited published outcomes exist presenting outcomes specifically after ACLR augmented with FiberTape®. Bodendorfer et al. presented a retrospective comparison of outcomes in patients undergoing ACLR with and without FiberTape® suture augmentation, with augmentation demonstrating less pain, improved PROMs and improved early return to activity, without evidence of over-constraint. A retrospective cohort study published by Barnas et al. reported comparable functional outcomes in patients undergoing surgery for partial ACL tears with synthetic augmentation using either a polyethylene terephthalate tape (Neoligaments) or FiberTape® suture augmentation. A recent retrospective comparison published by Hopper et al. reported comparable re-injury and secondary surgery rates in patients undergoing ACLR versus those undergoing ACL repair with suture tape augmentation, in the context of acute proximal ACL ruptures. Finally, a recent systematic review published by Zheng et al. specifically on the use of suture augmentation for ACLR reported overall favourable clinical outcomes and, whilst being associated with better sports performance compared to standard ACLR, was comparable in most functional scores, knee stability measures and graft failure rates. Most other ACLR papers employing FiberTape® augmentation are technical notes without patient outcomes [ , , ]. A prospective 2-year study published by Heusdens et al. reported improved post-operative outcomes of suture augmentation in the context of ACL repair, with a 4.8% re-rupture rate over the period, but other published papers using FiberTape® augmentation for ACL repair are also limited to technical notes . A number of limitations are acknowledged within the current study. First, it was a single centre study in patients undergoing a specific augmented ACLR technique that does not permit generalization. Furthermore, we acknowledge that there was no comparative group with the current study and, based on the early clinical experience our group had with this augmented ACLR technique, our initial plan was to undertake a robust prospective evaluation of patients undergoing this ACLR technique with close and frequent assessment of outcomes and adverse events, with comparison to existing literature where appropriate. This now provides a framework for a subsequent randomized comparative study. Additionally, it may be argued that it was a heterogeneous group with a wide age range (16–45 years) and almost 50% of patients undergoing concomitant meniscal surgery, though this is also a strength in presenting outcomes in a common community-level cohort embarking on ACLR. Second, we acknowledge that the primary study aim and sample size calculation was focussed around excessive anterior tibial translation (KT-1000 measurements), and both the 4-month pivot shift clinical review, as well as the 6-, 9-, 12- and 24-month KT-1000 reviews, were undertaken on the patient (on both limbs for the KT-1000) in an awake condition, which may be less reliable than an anaesthetized environment. Third, whilst an aim was to report on RTS rates at 12 and 24 months, the actual time to RTS was not documented. Finally, whilst it is acknowledged that rehabilitation can affect strength and function after ACLR [ , , ] and patients underwent a structured rehabilitation programme following surgery (also seeking to document rehabilitation adherence), it is acknowledged that in many community-level ACLR patients, rehabilitation will differ, as will individual patient motivation and exercise diligence.
The current study has demonstrated that ACLR using autologous hamstrings augmented with the suture tape, combined with a structured, post-operative rehabilitation programme, produced high-scoring PROMs and patient satisfaction with encouraging performance scores and RTS rates, without evidence of excessive anterior tibial translation and/or a high re-injury rate. Particularly given the high RTS rates at 24 months post-surgery, ongoing patient review is required to further investigate latter stage re-injury rates.
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Integrating Palliative Care into Oncology Care Worldwide: The Right Care in the Right Place at the Right Time | e8264627-3b23-4c7f-a2b1-ba8f88753c47 | 10009840 | Internal Medicine[mh] | Palliative care is defined as an approach that improves the quality of life of patients and their families facing problems associated with life-threatening illness through the prevention and relief of suffering by means of early identification and impeccable assessment and treatment of pain and other problems, physical, psychosocial, and spiritual . The domains covered by palliative care include not only physical and psychological symptom control, but also other aspects of care, including social and family supports, financial and practical considerations, and spiritual or religious preferences, as well as goals of care and advance care planning. Compelling evidence from multiple randomized controlled trials (RCTs) and meta-analyses has demonstrated that early, specialist palliative care improves quality of life and satisfaction with care in patients with advanced solid tumors and hematological malignancies [ ••, – ]. As a result, international cancer societies recommend integrating palliative care early in the management of patients with advanced cancer . However, most evidence in support of early palliative care originates from resource-rich settings with comprehensive interdisciplinary teams, and from trials conducted in patients with solid tumors attending specialist cancer centres . Although the benefits of early palliative care have been demonstrated clearly in these high-resource settings, the results may not be generalizable to settings with limited resources. Moreover, there remain considerable global inequities in access to palliative care based on geography (high-income versus low- and middle-income countries; urban versus rural settings) and type of malignancy (solid tumor versus hematological malignancy). Indeed, it is estimated that up to two-thirds of the world’s population currently do not have access to palliative care supports or medications such as opioids for symptom relief . Here, we review recent evidence regarding palliative care provision throughout the course of a cancer illness. We argue that in order to ensure that patients worldwide have access to palliative care, all available resources will need to be utilized, including primary care clinicians as well as specialists, practicing in home, inpatient and outpatient settings, and providing care in rural areas in addition to urban centres. This is summarized in Table , which shows the timing and nature of palliative care according to the place of care and level of care provided, based on available evidence. While our premise is that for any given setting, the aim of palliative care should be to provide the right care at the right place at the right time, models of palliative care will need to be flexible and scalable, depending on the health care system and the resources available.
Primary palliative care Primary palliative care involves integration of the fundamental aspects of palliative care (basic symptom management and advance care planning) into the primary care delivered by non-specialist clinicians , and may be provided in inpatient, outpatient and home settings by physicians, nurses, and other interdisciplinary health care professionals. Given the shortage of specialist palliative care clinicians internationally, along with the increasing incidence of cancer in an aging population and the prolonged illness trajectory now typical of most cancers , upscaling primary palliative care is crucial [ , , ••]. Compared with specialist palliative care, strong evidence in support of primary palliative care is lacking. A recent meta-analysis comparing primary and specialist palliative care interventions identified a high risk of bias in all included primary palliative care studies [ ••]. While primary palliative care may improve quality of life, evidence in support of its impact on symptom burden and survival is limited . Barriers to the delivery of high-quality primary palliative care include poor communication between oncology teams and primary care providers, leading to lack of understanding around illness trajectories, especially at the end-of-life; time constraints within primary care; lack of reimbursement for the delivery of primary palliative care which often involves home visits and out-of-hours support of patients and lack of training in primary palliative care competencies . In the outpatient oncology setting, many patients lose touch with their primary care providers after entering the cancer system. Travel time to the office, a positive perception of care, and a 24-h support service have been associated with outpatients with cancer seeing their family physician for palliative care [ •]. In order to improve primary palliative care delivery, core elements of palliative care may need to be extrapolated from specialist models and integrated into the educational curricula of all primary healthcare providers. Models of care that support mentorship or supervision of primary palliative care providers by specialist clinicians should be considered. One existing model of a primary palliative care educational initiative is Pallium, in Canada . This not-for-profit organization is committed to expanding primary palliative care capacity nationally through its accredited “Learning Essential Approaches to Palliative Care” program, and has trained over 28,000 professionals through 1600 courses from 2015 to 2019. Secondary palliative care Secondary palliative care refers to care provided by oncology specialists to inpatients and outpatients in hospital settings. As with primary palliative care, secondary palliative care should be interdisciplinary and include care delivered by medical, radiation, and surgical oncologists and hematologists; oncology nurses; radiation therapists; and allied health professionals such as social workers, physical and occupational therapists, and spiritual care providers . Elements that constitute high-quality secondary palliative care have been defined by a partnership between the American Society of Clinical Oncology (ASCO) and the American Association for Hospice and Palliative Medicine . These include end-of-life care; communication and shared decision-making; advance care planning; referral to palliative care or hospice when appropriate; symptom assessment and management; caregiver supports; care coordination and continuity; psychosocial assessment and management; spiritual care; and cultural considerations . ASCO has published a statement endorsing individualized care for patients with advanced cancer that includes specific attention to symptom management and quality of life issues . In order to ensure providers are well equipped to incorporate these elements into their clinical care, mandatory rotations with specialist palliative care teams should form part of oncology training programs across all disciplines; it has been shown that oncologists who have completed these rotations are more likely to appropriately refer patients to palliative care services . Despite this, a recent survey of hematology-oncology fellowship programs in the United States revealed that only 68% of respondents offered such rotations, with lectures and seminars making up the majority of palliative care education in most programs . Beyond education, additional barriers to secondary palliative care delivery include time constraints within busy oncology practices, as well as remuneration models that often favour patient volumes over time spent with individual patients. As an incentive, both the European Society for Medical Oncology (ESMO) and the Multinational Association of Supportive Care in Cancer (MASCC) have highlighted designated centres of integrated oncology and palliative or supportive care, respectively, based on criteria related to educational, clinical and research domains . Tertiary palliative care Tertiary palliative care refers to the care provided by clinicians with specialist postgraduate training in palliative care, including physicians, nurses, social workers, spiritual care providers, occupational and physical therapists, and pharmacists, among others . Although tertiary palliative care should ideally be widely available, including in inpatient, outpatient and community settings in rural and urban areas, it is disproportionally represented in tertiary comprehensive cancer settings. In addition to providing palliative care to patients with complex needs, these providers should also be available to provide mentorship and clinical support to primary and secondary palliative care providers and to help support capacity-building for these clinicians. At this time, the strongest evidence around the benefits of palliative care is derived from RCTs and meta-analyses of tertiary palliative care interventions: structured interdisciplinary outpatient palliative care consultations have been shown to improve patient symptom burden, quality of life, mood, and survival, and caregiver satisfaction and quality of life . Early referral to specialist palliative care is now endorsed by ASCO, ESMO, and other international cancer organizations, but worldwide shortages of specialist trained clinicians limit the ability to meet the needs of all patients with advanced cancer . Funding to support expansion of tertiary palliative care within cancer centers appears to be limited internationally, even within tertiary centers .
Primary palliative care involves integration of the fundamental aspects of palliative care (basic symptom management and advance care planning) into the primary care delivered by non-specialist clinicians , and may be provided in inpatient, outpatient and home settings by physicians, nurses, and other interdisciplinary health care professionals. Given the shortage of specialist palliative care clinicians internationally, along with the increasing incidence of cancer in an aging population and the prolonged illness trajectory now typical of most cancers , upscaling primary palliative care is crucial [ , , ••]. Compared with specialist palliative care, strong evidence in support of primary palliative care is lacking. A recent meta-analysis comparing primary and specialist palliative care interventions identified a high risk of bias in all included primary palliative care studies [ ••]. While primary palliative care may improve quality of life, evidence in support of its impact on symptom burden and survival is limited . Barriers to the delivery of high-quality primary palliative care include poor communication between oncology teams and primary care providers, leading to lack of understanding around illness trajectories, especially at the end-of-life; time constraints within primary care; lack of reimbursement for the delivery of primary palliative care which often involves home visits and out-of-hours support of patients and lack of training in primary palliative care competencies . In the outpatient oncology setting, many patients lose touch with their primary care providers after entering the cancer system. Travel time to the office, a positive perception of care, and a 24-h support service have been associated with outpatients with cancer seeing their family physician for palliative care [ •]. In order to improve primary palliative care delivery, core elements of palliative care may need to be extrapolated from specialist models and integrated into the educational curricula of all primary healthcare providers. Models of care that support mentorship or supervision of primary palliative care providers by specialist clinicians should be considered. One existing model of a primary palliative care educational initiative is Pallium, in Canada . This not-for-profit organization is committed to expanding primary palliative care capacity nationally through its accredited “Learning Essential Approaches to Palliative Care” program, and has trained over 28,000 professionals through 1600 courses from 2015 to 2019.
Secondary palliative care refers to care provided by oncology specialists to inpatients and outpatients in hospital settings. As with primary palliative care, secondary palliative care should be interdisciplinary and include care delivered by medical, radiation, and surgical oncologists and hematologists; oncology nurses; radiation therapists; and allied health professionals such as social workers, physical and occupational therapists, and spiritual care providers . Elements that constitute high-quality secondary palliative care have been defined by a partnership between the American Society of Clinical Oncology (ASCO) and the American Association for Hospice and Palliative Medicine . These include end-of-life care; communication and shared decision-making; advance care planning; referral to palliative care or hospice when appropriate; symptom assessment and management; caregiver supports; care coordination and continuity; psychosocial assessment and management; spiritual care; and cultural considerations . ASCO has published a statement endorsing individualized care for patients with advanced cancer that includes specific attention to symptom management and quality of life issues . In order to ensure providers are well equipped to incorporate these elements into their clinical care, mandatory rotations with specialist palliative care teams should form part of oncology training programs across all disciplines; it has been shown that oncologists who have completed these rotations are more likely to appropriately refer patients to palliative care services . Despite this, a recent survey of hematology-oncology fellowship programs in the United States revealed that only 68% of respondents offered such rotations, with lectures and seminars making up the majority of palliative care education in most programs . Beyond education, additional barriers to secondary palliative care delivery include time constraints within busy oncology practices, as well as remuneration models that often favour patient volumes over time spent with individual patients. As an incentive, both the European Society for Medical Oncology (ESMO) and the Multinational Association of Supportive Care in Cancer (MASCC) have highlighted designated centres of integrated oncology and palliative or supportive care, respectively, based on criteria related to educational, clinical and research domains .
Tertiary palliative care refers to the care provided by clinicians with specialist postgraduate training in palliative care, including physicians, nurses, social workers, spiritual care providers, occupational and physical therapists, and pharmacists, among others . Although tertiary palliative care should ideally be widely available, including in inpatient, outpatient and community settings in rural and urban areas, it is disproportionally represented in tertiary comprehensive cancer settings. In addition to providing palliative care to patients with complex needs, these providers should also be available to provide mentorship and clinical support to primary and secondary palliative care providers and to help support capacity-building for these clinicians. At this time, the strongest evidence around the benefits of palliative care is derived from RCTs and meta-analyses of tertiary palliative care interventions: structured interdisciplinary outpatient palliative care consultations have been shown to improve patient symptom burden, quality of life, mood, and survival, and caregiver satisfaction and quality of life . Early referral to specialist palliative care is now endorsed by ASCO, ESMO, and other international cancer organizations, but worldwide shortages of specialist trained clinicians limit the ability to meet the needs of all patients with advanced cancer . Funding to support expansion of tertiary palliative care within cancer centers appears to be limited internationally, even within tertiary centers .
Outpatient clinics The outpatient setting is ideally suited for early tertiary palliative care delivery . In this setting, palliative care is typically offered concurrently with disease-modifying cancer therapies to support attending clinics longitudinally . While these clinics are for patients with a variety of cancer diagnoses, referrals tend to come more often from medical oncologists who specialize in solid tumors than malignant hematologists. Several different clinic models have been described, based on available palliative care resources and oncology structures . The two main models are embedded clinics, where palliative care is provided within an existing oncology clinic, and stand-alone clinics, where the palliative care clinic has its own designated clinic space . Both models were traditionally provided in person, although virtual care has become increasingly common during the COVID-19 pandemic, particularly for patients seen in follow up . This new method of communication could potentially overcome some of the factors that limit in person attendance to stand-alone clinics, particularly distance to the hospital . However, evidence regarding virtual care delivery models is limited , and further trials are needed. Embedded models are ideal for smaller palliative care teams working in centres where oncology clinics are not cancer site specific. The ability to see the oncologist and palliative care provider in the same clinic on the same day, and to pool resources between teams, may be advantageous, but the ability to expand or grow embedded palliative care clinics is often limited . Stand-alone palliative care clinics independent of the oncology clinic are more commonly offered at comprehensive cancer centres or centres with sufficient clinician support . Referrals from oncologists are triaged based on urgency, with prioritization of highly symptomatic patients for same-day visits while those with less urgent concerns are booked into a visit that coincides with a future clinic visit to their oncologist . While stand-alone clinics require upfront funding and independent administrative and other resources, they offer greater potential to customize the clinic space, to grow and expand based on demand, and to incorporate interdisciplinary team members in a more comprehensive way than an embedded model typically allows. Because no trials have compared an embedded versus a stand-alone model, the decision to adopt one over the other is pragmatic, based on factors such as cancer center size, palliative care team composition, clinic space availability, and financial considerations . Inpatient consultation services Compared with outpatient studies, where RCTs have focused on patient-reported outcomes, much of the research involving care provided by inpatient specialist palliative care consultation services has been retrospective, focusing on administrative outcomes and economic benefits. In a study of five US hospitals with comprehensive palliative care teams, consultations within 2 and 6 days of admission were shown to reduce hospitalization costs by 24% and 14%, respectively . Similar findings were reported in a meta-analysis of economic evaluations of interdisciplinary palliative care consultations for hospitalized patients with advanced illness . Most of these cost savings appear to come from reduced length of stay and reduced intensity of treatment, and tend to be greater for patients with more comorbidities (four or more), compared with two or fewer . Clinical benefits of inpatient specialist palliative care have also been demonstrated . A systematic review of the impact of palliative care consultations for inpatients showed improvements in pain, quality of life, satisfaction with care and advance care planning discussions . In addition, patients seen by inpatient palliative care teams were more likely to receive home care supports after discharge from hospital and less likely to be readmitted to acute care. Although the emergency department is not an ideal location for a first palliative care consultation, it has nevertheless been demonstrated that emergency department-initiated palliative care consultation in advanced cancer improves quality of life . Palliative care at home For patients whose performance status has declined, those with limited mobility, or older patients who have difficulty going to the hospital or to clinics, in-home palliative care is most practical . A recently published Cochrane review of home-based palliative care demonstrated an increased likelihood of dying at home and an association with improved satisfaction with care; effects on symptom control were unclear from the limited and heterogeneous data . Key elements of home-based palliative care, as identified by patients and caregivers, include the ability to access care 24 h a day, seven days per week, as well as expertise in communication and symptom management . Although home palliative care is ideally provided by primary care providers, logistical issues related to time and traveling to provide home visits, particularly outside regular office hours, represent prominent barriers . In a survey among family doctors and general practitioners, younger primary care physicians were more engageable to provide home palliative care; this was particularly the case if they were provided sufficient remuneration and resources, and if working in a team-based model with access to advice from specialist palliative care colleagues . In recent years, efforts have been made to integrate home-based palliative care earlier into the cancer trajectory . The advantages of early palliative care delivery in the home setting include the ability to focus on information-sharing; psychosocial elements of care; structured and systematic follow up; and future goal setting, whereas late involvement tends to be characterized by crisis-initiated visits and a need to focus on immediate problem-solving. RCTs investigating the feasibility and acceptability of early palliative care offered at home are ongoing [ •]. Palliative care units and residential hospices Inpatient hospices and palliative care units provide a specialist setting to support patients with advanced cancer and their families . Some palliative care units within comprehensive cancer centers provide acute symptom management, such as access to bloodwork, diagnostic imaging, intravenous antibiotics, and blood transfusions, and are suitable for patients who may require a brief admission to optimize their symptoms with a goal to return home. Others focus more on providing symptomatic relief for patients in the last days, weeks, or short months of life, and for whom remaining at home is not feasible or not aligned with their goals of care. Many hospices and palliative care units have admission criteria that include accepting a “do not resuscitate” order, and have limited abilities to support patients who continue to receive active anticancer therapies . Interdisciplinary care is a key component of the support provided in inpatient hospices or palliative care units, provided by specialized palliative care nurses, physicians, social workers, spiritual care providers, physiotherapists, occupational therapists, music therapists, art therapists, pharmacists, and others. Inpatient palliative care units within cancer centres may facilitate increased cancer-directed activities and reduced deaths on inpatient oncology units by supporting the timely transfer of patients to a specialized palliative care setting . Palliative care units also have financial benefits by reducing overall direct costs associated with an acute hospital admission .
The outpatient setting is ideally suited for early tertiary palliative care delivery . In this setting, palliative care is typically offered concurrently with disease-modifying cancer therapies to support attending clinics longitudinally . While these clinics are for patients with a variety of cancer diagnoses, referrals tend to come more often from medical oncologists who specialize in solid tumors than malignant hematologists. Several different clinic models have been described, based on available palliative care resources and oncology structures . The two main models are embedded clinics, where palliative care is provided within an existing oncology clinic, and stand-alone clinics, where the palliative care clinic has its own designated clinic space . Both models were traditionally provided in person, although virtual care has become increasingly common during the COVID-19 pandemic, particularly for patients seen in follow up . This new method of communication could potentially overcome some of the factors that limit in person attendance to stand-alone clinics, particularly distance to the hospital . However, evidence regarding virtual care delivery models is limited , and further trials are needed. Embedded models are ideal for smaller palliative care teams working in centres where oncology clinics are not cancer site specific. The ability to see the oncologist and palliative care provider in the same clinic on the same day, and to pool resources between teams, may be advantageous, but the ability to expand or grow embedded palliative care clinics is often limited . Stand-alone palliative care clinics independent of the oncology clinic are more commonly offered at comprehensive cancer centres or centres with sufficient clinician support . Referrals from oncologists are triaged based on urgency, with prioritization of highly symptomatic patients for same-day visits while those with less urgent concerns are booked into a visit that coincides with a future clinic visit to their oncologist . While stand-alone clinics require upfront funding and independent administrative and other resources, they offer greater potential to customize the clinic space, to grow and expand based on demand, and to incorporate interdisciplinary team members in a more comprehensive way than an embedded model typically allows. Because no trials have compared an embedded versus a stand-alone model, the decision to adopt one over the other is pragmatic, based on factors such as cancer center size, palliative care team composition, clinic space availability, and financial considerations .
Compared with outpatient studies, where RCTs have focused on patient-reported outcomes, much of the research involving care provided by inpatient specialist palliative care consultation services has been retrospective, focusing on administrative outcomes and economic benefits. In a study of five US hospitals with comprehensive palliative care teams, consultations within 2 and 6 days of admission were shown to reduce hospitalization costs by 24% and 14%, respectively . Similar findings were reported in a meta-analysis of economic evaluations of interdisciplinary palliative care consultations for hospitalized patients with advanced illness . Most of these cost savings appear to come from reduced length of stay and reduced intensity of treatment, and tend to be greater for patients with more comorbidities (four or more), compared with two or fewer . Clinical benefits of inpatient specialist palliative care have also been demonstrated . A systematic review of the impact of palliative care consultations for inpatients showed improvements in pain, quality of life, satisfaction with care and advance care planning discussions . In addition, patients seen by inpatient palliative care teams were more likely to receive home care supports after discharge from hospital and less likely to be readmitted to acute care. Although the emergency department is not an ideal location for a first palliative care consultation, it has nevertheless been demonstrated that emergency department-initiated palliative care consultation in advanced cancer improves quality of life .
For patients whose performance status has declined, those with limited mobility, or older patients who have difficulty going to the hospital or to clinics, in-home palliative care is most practical . A recently published Cochrane review of home-based palliative care demonstrated an increased likelihood of dying at home and an association with improved satisfaction with care; effects on symptom control were unclear from the limited and heterogeneous data . Key elements of home-based palliative care, as identified by patients and caregivers, include the ability to access care 24 h a day, seven days per week, as well as expertise in communication and symptom management . Although home palliative care is ideally provided by primary care providers, logistical issues related to time and traveling to provide home visits, particularly outside regular office hours, represent prominent barriers . In a survey among family doctors and general practitioners, younger primary care physicians were more engageable to provide home palliative care; this was particularly the case if they were provided sufficient remuneration and resources, and if working in a team-based model with access to advice from specialist palliative care colleagues . In recent years, efforts have been made to integrate home-based palliative care earlier into the cancer trajectory . The advantages of early palliative care delivery in the home setting include the ability to focus on information-sharing; psychosocial elements of care; structured and systematic follow up; and future goal setting, whereas late involvement tends to be characterized by crisis-initiated visits and a need to focus on immediate problem-solving. RCTs investigating the feasibility and acceptability of early palliative care offered at home are ongoing [ •].
Inpatient hospices and palliative care units provide a specialist setting to support patients with advanced cancer and their families . Some palliative care units within comprehensive cancer centers provide acute symptom management, such as access to bloodwork, diagnostic imaging, intravenous antibiotics, and blood transfusions, and are suitable for patients who may require a brief admission to optimize their symptoms with a goal to return home. Others focus more on providing symptomatic relief for patients in the last days, weeks, or short months of life, and for whom remaining at home is not feasible or not aligned with their goals of care. Many hospices and palliative care units have admission criteria that include accepting a “do not resuscitate” order, and have limited abilities to support patients who continue to receive active anticancer therapies . Interdisciplinary care is a key component of the support provided in inpatient hospices or palliative care units, provided by specialized palliative care nurses, physicians, social workers, spiritual care providers, physiotherapists, occupational therapists, music therapists, art therapists, pharmacists, and others. Inpatient palliative care units within cancer centres may facilitate increased cancer-directed activities and reduced deaths on inpatient oncology units by supporting the timely transfer of patients to a specialized palliative care setting . Palliative care units also have financial benefits by reducing overall direct costs associated with an acute hospital admission .
Most of the evidence demonstrating the benefits of outpatient palliative care interventions comes from trials of patients with solid tumors attending comprehensive cancer centres; less is known about the impact of early palliative care on patients with hematological malignancies (Table ). This section will summarize the evidence in support of early palliative care for patients with both solid tumors and hematological malignancies, highlighting the differences between the two groups as well as areas where further research may be needed. Timing of palliative care for patients with solid tumors Although the right time for palliative care intervention will depend on the setting of care and the resources available, the most compelling evidence has been from RCTs of “early” palliative care. In these trials, “early” was defined either as within 8–12 weeks of diagnosis of advanced cancer and/or a clinical prognosis of between 6 and 24 months . All of these trials utilized a specialized palliative care model and in most, the intervention was interdisciplinary, utilizing at minimum a palliative care physician and advanced practice nurse. The mode of delivery was generally in the outpatient setting, although some trials also enrolled inpatients [ ••, , ••], and one utilized telehealth . Studies have often been limited to patients with lung and/or gastrointestinal cancers, with only three studies with positive results also including other solid tumor malignancies . Overall, these studies demonstrated that early involvement of specialized palliative care resulted in improved quality of life, satisfaction with care and mood, albeit with small effect sizes. These trial results have been corroborated by meta-analyses ; in addition, largescale retrospective studies in real-world settings have shown that early palliative care is associated with a lower risk of dying in hospital, an increased possibility of receiving home-based end-of-life care, and reduced healthcare system costs [ ••, ]. The evidence presented above appears to have resulted in earlier referral to palliative care services in cancer centers [ •, ••], but barriers to early referral remain. These include a lack of trained specialists to provide palliative care and persistent stigma associating palliative care with end-of-life care . Ultimately, systematic screening of all patients with advanced cancer with targeted early referral for patients with particular need may be a more scalable model than uniform early palliative care for all patients with advanced cancer. A secondary analysis of an RCT showed that the benefit of early palliative care was greatest for patients with higher symptom burden [ •], and a recent phase II trial of symptom screening with targeted early specialized palliative care intervention demonstrated the feasibility of this model . However, this model assumes that oncologists and primary care providers will be able to provide basic palliative care, which necessitates better education than is currently provided . As well, a public health strategy is needed to educate and engage policymakers, stakeholders and the public about the relevance and importance of early palliative care . Timing of palliative care for patients with hematologic malignancies Hematologic malignancies (acute and chronic leukemias, lymphomas, and multiple myeloma) are often considered more heterogenous and unpredictable in terms of disease course and prognosis than solid tumors . Patients with hematological malignancies may often experience high physical symptom burden, as well as increased levels of psychosocial distress . Despite this, referrals to specialized palliative care tend to be later for patients with hematological malignancies compared to solid tumors. As a result, there is a relative paucity of evidence in support of early palliative care for patients with hematological malignancies. Unlike trials of early palliative care for patients with solid tumors, most RCTs enrolling patients with hematological malignancies have been conducted in the inpatient setting, and timing of intervention for these studies has been based on timing of admission rather than on prognosis. Two trials of palliative care in outpatient or emergency department settings included patients with haematological malignancies in addition to solid tumors, but the percentage of patients with hematologic malignancies for both of these was only approximately 5% and thus the results cannot be extrapolated to hematologic malignancy populations. Other RCTs exclusive to haematologic malignancies have all recruited inpatients shortly after admission for stem cell transplantation or admission for induction or re-induction chemotherapy [ ••, ••], although a nonrandomized pilot study included outpatients awaiting admission for allogeneic or autologous stem cell transplantation . These trials have all demonstrated the feasibility [ ••, ] of early palliative care and its effectiveness for improving quality of life, mood, and post-traumatic stress for patients with aggressive hematological malignancies such as acute leukemia who are awaiting or have received intensive treatment regimens for their disease [ ••, , ••, ]. Thus, the available evidence for patients with hematologic malignancies supports immediate referral to palliative care for patients with aggressive hematologic malignancies such as acute leukemia who are admitted for intensive treatment for their disease, or those awaiting hemopoietic stem cell transplantation. Further trials are necessary in outpatient populations and for patients with bone marrow failure and indolent hematologic malignancies that are not immediately life-threatening, but are nonetheless associated with a high burden of symptoms.
Although the right time for palliative care intervention will depend on the setting of care and the resources available, the most compelling evidence has been from RCTs of “early” palliative care. In these trials, “early” was defined either as within 8–12 weeks of diagnosis of advanced cancer and/or a clinical prognosis of between 6 and 24 months . All of these trials utilized a specialized palliative care model and in most, the intervention was interdisciplinary, utilizing at minimum a palliative care physician and advanced practice nurse. The mode of delivery was generally in the outpatient setting, although some trials also enrolled inpatients [ ••, , ••], and one utilized telehealth . Studies have often been limited to patients with lung and/or gastrointestinal cancers, with only three studies with positive results also including other solid tumor malignancies . Overall, these studies demonstrated that early involvement of specialized palliative care resulted in improved quality of life, satisfaction with care and mood, albeit with small effect sizes. These trial results have been corroborated by meta-analyses ; in addition, largescale retrospective studies in real-world settings have shown that early palliative care is associated with a lower risk of dying in hospital, an increased possibility of receiving home-based end-of-life care, and reduced healthcare system costs [ ••, ]. The evidence presented above appears to have resulted in earlier referral to palliative care services in cancer centers [ •, ••], but barriers to early referral remain. These include a lack of trained specialists to provide palliative care and persistent stigma associating palliative care with end-of-life care . Ultimately, systematic screening of all patients with advanced cancer with targeted early referral for patients with particular need may be a more scalable model than uniform early palliative care for all patients with advanced cancer. A secondary analysis of an RCT showed that the benefit of early palliative care was greatest for patients with higher symptom burden [ •], and a recent phase II trial of symptom screening with targeted early specialized palliative care intervention demonstrated the feasibility of this model . However, this model assumes that oncologists and primary care providers will be able to provide basic palliative care, which necessitates better education than is currently provided . As well, a public health strategy is needed to educate and engage policymakers, stakeholders and the public about the relevance and importance of early palliative care .
Hematologic malignancies (acute and chronic leukemias, lymphomas, and multiple myeloma) are often considered more heterogenous and unpredictable in terms of disease course and prognosis than solid tumors . Patients with hematological malignancies may often experience high physical symptom burden, as well as increased levels of psychosocial distress . Despite this, referrals to specialized palliative care tend to be later for patients with hematological malignancies compared to solid tumors. As a result, there is a relative paucity of evidence in support of early palliative care for patients with hematological malignancies. Unlike trials of early palliative care for patients with solid tumors, most RCTs enrolling patients with hematological malignancies have been conducted in the inpatient setting, and timing of intervention for these studies has been based on timing of admission rather than on prognosis. Two trials of palliative care in outpatient or emergency department settings included patients with haematological malignancies in addition to solid tumors, but the percentage of patients with hematologic malignancies for both of these was only approximately 5% and thus the results cannot be extrapolated to hematologic malignancy populations. Other RCTs exclusive to haematologic malignancies have all recruited inpatients shortly after admission for stem cell transplantation or admission for induction or re-induction chemotherapy [ ••, ••], although a nonrandomized pilot study included outpatients awaiting admission for allogeneic or autologous stem cell transplantation . These trials have all demonstrated the feasibility [ ••, ] of early palliative care and its effectiveness for improving quality of life, mood, and post-traumatic stress for patients with aggressive hematological malignancies such as acute leukemia who are awaiting or have received intensive treatment regimens for their disease [ ••, , ••, ]. Thus, the available evidence for patients with hematologic malignancies supports immediate referral to palliative care for patients with aggressive hematologic malignancies such as acute leukemia who are admitted for intensive treatment for their disease, or those awaiting hemopoietic stem cell transplantation. Further trials are necessary in outpatient populations and for patients with bone marrow failure and indolent hematologic malignancies that are not immediately life-threatening, but are nonetheless associated with a high burden of symptoms.
Specialist palliative care services tend to be disproportionately located in large urban academic centers and in high-income countries. With more than half of the world’s population residing in rural areas (which make up to 80% of most countries’ landmasses), there is an urgent need to improve access to palliative care in these areas . In low- and middle-income countries, cancer rates are increasing at an alarming rate: 50% of cancer diagnosed annually are in low- and middle-income countries where they are associated with high rates of morbidity and mortality. Policies and strategies that are tailored to resource-limited settings must be developed to maximize access to palliative care , recognizing that the nature, place and time of palliative care will often differ from those in high-income and urban settings. Trials of palliative care interventions in rural settings Patients with advanced cancer who live in rural settings have been shown to be less likely to access palliative care services compared to those residing in urban settings . In addition, living further from a palliative care program is associated with a higher likelihood of dying in hospital and higher costs at the end of life . Identified barriers to specialist palliative care provision in rural settings include lack of cohesive services and communication between clinical settings, demand for services that exceeds supplies of specialist teams where available, and educational gaps for both providers and patients alike . Primary care physicians are important providers of palliative care in rural communities; this includes providing palliative care at home as well as through cohorted inpatient beds designated for palliative care on hospital medical wards . Only a few RCTs of early palliative care have actively sought to include patients from rural settings. The ENABLE II and III trials, which utilized predominantly telehealth interventions delivered by a specialist nurse, recruited participants from three rural-serving cancer centres in the USA, and approximately 60% of participants came from rural communities . Apoyo con cariño was a tailored randomized trial that included urban and rural communities in the state of Colorado in the USA aiming to enhance access to palliative care services among the Latino population . Culturally tailored resources and lay navigator home visits were offered as part of the intervention, which demonstrated improved rates of advance care planning documentation, but there were no significant differences in pain, hospice utilization, or aggressiveness of care at the end of life. In addition, a lay navigator program to improve access to palliative care in 12 rural-serving cancer services in the USA demonstrated less aggressive end-of-life care . Several elements of successful palliative care provision for patients with advanced cancer in rural communities have been identified . These include developing local partnerships with healthcare, cultural, spiritual, and religious groups to appropriately support the needs of patients within each community, offering telehealth visits to minimize the direct and indirect costs associated with travelling to comprehensive cancer centers, utilizing models of care that foster local expertise with support from academic centres (e.g., virtual case conferences, mentorship programs), and initiatives that incentivize oncologists and palliative care specialists working in rural areas. Trials of palliative care interventions in low- and middle-income countries Palliative care is considered a human right based on two principles: the right to health, and the right to be free from cruel, inhuman, or degrading treatment . Based on these principles, several international cancer organizations and societies have advocated for the integration of palliative care services into routine oncology care . In 2018, ASCO published a resource-stratified guideline to provide guidance on the implementation of palliative care in resource-limited settings . The guideline listed seven recommendations, each subclassified based on the setting (basic, limited, or enhanced), intended to be used alongside local documents or policies. Globally, only half of countries currently include palliative care within their national Noncommunicable diseases (NCDs) policies, and only 68% have dedicated funding for palliative care, with a gap of 43% between high-income (91%) and low-and-middle-income countries (48%) . The level of palliative care development within countries is highly associated with each country’s ranking within the World Bank Group, the Human Development Index, and the presence or absence of universal health coverage; and it is classified in 6 groups according to the level of palliative care integration (Table ). In recent years, trials proposing models to enhance access to early palliative care in resource-limited settings have been published. Here we highlight studies from Latin America, Africa, and India as examples of successfully completed RCTs and public health initiatives from low- and middle-income countries. An RCT conducted in a tertiary hospital in Mexico found that a structured navigation program led to a significant increase in accessing specialized palliative care services (74% of the patients enrolled in the intervention arm, compared to 24% from the usual care group) [ ••]. Additionally, 48% of patients enrolled in the intervention group completed advanced directives compared to none in the usual care group and patients in the intervention group experienced better pain relief. In Ethiopia, an RCT demonstrated that early home-based palliative care delivered by palliative care-trained nurses for patients with newly diagnosed cancer significantly reduced health care costs compared with standard oncology care [ •]. In India, feasibility criteria were not met for a trial of early palliative care in patients with advanced lung cancer in a tertiary care center. Only 48% received follow-up at the palliative care clinic, with the remainder not followed up due to being fatigued, busy receiving chemotherapy, or returning to their hometown; however, quality of life and symptoms tended to improve, especially for pain and anxiety . In another RCT of patients with head and neck cancer in India, there was no difference in quality of life, symptom burden or survival at three months between patients randomized to receive early specialized palliative care and those receiving systemic therapy alone [ •], although the standard care arm received some elements of palliative care and 18% received a palliative care consultation. Elsewhere in India, the feasibility of home-based palliative care delivered by community health workers was successfully demonstrated, although additional training may be needed to improve pain and provide psychosocial supports . Finally, Panama represents a good example of a low- and middle-income country where the successful development of a sustainable national palliative care program has been possible . Through universal health coverage that includes palliative care, and the integration of health networks across all clinical settings, successful milestones have been possible; these include the accreditation of a specialist palliative medicine program and an amendment to the “Controlled Substances Act” to facilitate access to essential palliative care medicines.
Patients with advanced cancer who live in rural settings have been shown to be less likely to access palliative care services compared to those residing in urban settings . In addition, living further from a palliative care program is associated with a higher likelihood of dying in hospital and higher costs at the end of life . Identified barriers to specialist palliative care provision in rural settings include lack of cohesive services and communication between clinical settings, demand for services that exceeds supplies of specialist teams where available, and educational gaps for both providers and patients alike . Primary care physicians are important providers of palliative care in rural communities; this includes providing palliative care at home as well as through cohorted inpatient beds designated for palliative care on hospital medical wards . Only a few RCTs of early palliative care have actively sought to include patients from rural settings. The ENABLE II and III trials, which utilized predominantly telehealth interventions delivered by a specialist nurse, recruited participants from three rural-serving cancer centres in the USA, and approximately 60% of participants came from rural communities . Apoyo con cariño was a tailored randomized trial that included urban and rural communities in the state of Colorado in the USA aiming to enhance access to palliative care services among the Latino population . Culturally tailored resources and lay navigator home visits were offered as part of the intervention, which demonstrated improved rates of advance care planning documentation, but there were no significant differences in pain, hospice utilization, or aggressiveness of care at the end of life. In addition, a lay navigator program to improve access to palliative care in 12 rural-serving cancer services in the USA demonstrated less aggressive end-of-life care . Several elements of successful palliative care provision for patients with advanced cancer in rural communities have been identified . These include developing local partnerships with healthcare, cultural, spiritual, and religious groups to appropriately support the needs of patients within each community, offering telehealth visits to minimize the direct and indirect costs associated with travelling to comprehensive cancer centers, utilizing models of care that foster local expertise with support from academic centres (e.g., virtual case conferences, mentorship programs), and initiatives that incentivize oncologists and palliative care specialists working in rural areas.
Palliative care is considered a human right based on two principles: the right to health, and the right to be free from cruel, inhuman, or degrading treatment . Based on these principles, several international cancer organizations and societies have advocated for the integration of palliative care services into routine oncology care . In 2018, ASCO published a resource-stratified guideline to provide guidance on the implementation of palliative care in resource-limited settings . The guideline listed seven recommendations, each subclassified based on the setting (basic, limited, or enhanced), intended to be used alongside local documents or policies. Globally, only half of countries currently include palliative care within their national Noncommunicable diseases (NCDs) policies, and only 68% have dedicated funding for palliative care, with a gap of 43% between high-income (91%) and low-and-middle-income countries (48%) . The level of palliative care development within countries is highly associated with each country’s ranking within the World Bank Group, the Human Development Index, and the presence or absence of universal health coverage; and it is classified in 6 groups according to the level of palliative care integration (Table ). In recent years, trials proposing models to enhance access to early palliative care in resource-limited settings have been published. Here we highlight studies from Latin America, Africa, and India as examples of successfully completed RCTs and public health initiatives from low- and middle-income countries. An RCT conducted in a tertiary hospital in Mexico found that a structured navigation program led to a significant increase in accessing specialized palliative care services (74% of the patients enrolled in the intervention arm, compared to 24% from the usual care group) [ ••]. Additionally, 48% of patients enrolled in the intervention group completed advanced directives compared to none in the usual care group and patients in the intervention group experienced better pain relief. In Ethiopia, an RCT demonstrated that early home-based palliative care delivered by palliative care-trained nurses for patients with newly diagnosed cancer significantly reduced health care costs compared with standard oncology care [ •]. In India, feasibility criteria were not met for a trial of early palliative care in patients with advanced lung cancer in a tertiary care center. Only 48% received follow-up at the palliative care clinic, with the remainder not followed up due to being fatigued, busy receiving chemotherapy, or returning to their hometown; however, quality of life and symptoms tended to improve, especially for pain and anxiety . In another RCT of patients with head and neck cancer in India, there was no difference in quality of life, symptom burden or survival at three months between patients randomized to receive early specialized palliative care and those receiving systemic therapy alone [ •], although the standard care arm received some elements of palliative care and 18% received a palliative care consultation. Elsewhere in India, the feasibility of home-based palliative care delivered by community health workers was successfully demonstrated, although additional training may be needed to improve pain and provide psychosocial supports . Finally, Panama represents a good example of a low- and middle-income country where the successful development of a sustainable national palliative care program has been possible . Through universal health coverage that includes palliative care, and the integration of health networks across all clinical settings, successful milestones have been possible; these include the accreditation of a specialist palliative medicine program and an amendment to the “Controlled Substances Act” to facilitate access to essential palliative care medicines.
Although the scope of palliative care has expanded over the past decade to support early integration alongside cancer care, most evidence in support of this model comes from high-income, resource-rich settings and in patients with solid tumors. This model may not be easily applied in other settings, where challenges related to the patient population, as well as workforce shortages and lack of public policy in support of palliative care, must be acknowledged. Instead, the “best model” will inevitably vary between settings and must be one that allows maximum impact for patients with the greatest needs, starting at the end of life and expanding towards full integration only when the basic needs of dying patients are adequately met. Public health strategies aimed at developing local, sustainable policies integrated into national healthcare plans, as well as comprehensive training programs for healthcare providers across all clinical settings are needed to bridge the current gaps in care across national and international settings, and to ensure that patients can receive the right care, at the right place, and at the right time.
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The emerging paradigm in pediatric rheumatology: harnessing the power of artificial intelligence | 3633815d-f432-473f-89a6-d056b5e419d7 | 11424736 | Internal Medicine[mh] | Artificial intelligence (AI) is a sophisticated field of computer science with numerous subfields and a wide array of applications, dedicated to creating systems capable of performing tasks that typically require human intelligence, including learning, reasoning, problem-solving, and understanding natural language . Demonstrating its capabilities in various areas such as literature, art, and creativity, AI is pushing boundaries with its visual and auditory applications and continues to open new horizons in medicine. AI, by mimicking fundamental aspects of a physician and utilizing extensive knowledge repositories, can formulate differential diagnoses, provide preliminary diagnoses, and even make treatment recommendations. In addition to its contributions to clinical practice, it is making strides towards inspiring academics with the increasing research in recent years . It has been demonstrated to be particularly influential in guiding visual assessments and molecular analyses that require standardization and time, especially in areas where traditional scientific methods fall short . On the other hand, natural language processing (NLP) models, possessing the ability to comprehend and generate human language, have emerged as one of the most rapidly embraced applications by scholars in the scientific research community, challenging the norms of plagiarism and ethical standards. So, while captivating with their linguistic and analytical capabilities, these applications also spark discussions regarding potential misleading interpretations, simulated citations, and the dimension of academic misconduct . Childhood rheumatic diseases are chronic conditions of autoimmune or autoinflammatory origin that affect the joints, muscles, connective tissues, and various other organs. The lack of a diagnostic confirmation test and the necessity for biomarkers, along with the potential importance of imaging or histopathological assessment and staging in treatment decisions for various organ involvements, as well as the significance of autoantibody patterns in autoimmune disorders or genetic analyzes in autoinflammatory diseases, increase the growing expectation for the promising support of AI technology in pediatric rheumatology. Examining the burgeoning connection between pediatric rheumatology and AI, one notices a noteworthy presence of machine learning (ML) and deep learning (DL) algorithms in a restricted set of studies concerning diagnostic approaches. The enthusiasm surrounding ML stems from a pivotal capability: the potential to analyze intricate and extensive data structures. This ability enables the creation of prediction models tailored to enhance the customization, accuracy, and overall effectiveness of diagnoses, prognoses, monitoring, and treatment administration and ultimately improve individual health outcomes . Diverging from traditional methods, it adeptly assesses potential connections between variables without adhering to fixed assumptions and hypotheses, skillfully transcending established patterns . The terminology of AI algorithms is depicted in Fig. . This review aims to provide a comprehensive overview by evaluating the existing literature on the recent relationship between pediatric rheumatology and AI. Original research articles discussing the application of AI in pediatric rheumatology and review articles addressing the relationship between rheumatology and/or pediatric rheumatology and AI have been examined within the scope of the subject. The research and methodological approach were informed by previously published scholarly works . Two authors (OK and SS) independently conducted the literature review. Consistency and appropriateness were verified and confirmed by another author (OK) and reconciled by consensus. An electronic literature search was performed, covering articles from the inception of the databases to May 2024. Boolean operators and medical subject heading terms were used to enhance electronic searches. To systematically address the topic and grasp the current classification and terminology, the search terms “artificial intelligence”, “machine learning”, “deep learning”, “big data”, “supervised learning”, “unsupervised learning”, “reinforcement learning”, computer neural network, “convolutional neural network”, “musculoskeletal”, “rheumatology”, and “pediatric rheumatology” were utilized in searches conducted through Medline/PubMed, Scopus, Web of Science, and Directory of Open Access Journals (DOAJ). Further searches were performed on references of the included studies to ensure comprehensive coverage. The titles and abstracts of all articles relevant to the subject have been evaluated, and the eligibility criteria have been determined by all authors. Articles published in English have been considered. Publications that were not full-text articles (e.g., conference, abstract) have been excluded. The authors have re-analyzed the full texts of review articles exploring the relationship between rheumatology and AI, as well as studies that employed AI algorithms in their methodologies. Data extraction has focused on AI methods used, and outcomes related to pediatric rheumatology. The final reference list was compiled based on the originality and relevance to the broad scope of this review. Finally, the data and information obtained from the publications were systematically categorized and transcribed in line with the main themes and objectives, the AI subtypes and algorithms, the results, and the limitations. Additionally, review articles relevant to the topic were utilized in the description and classification of the methods. To ensure standardization, AI algorithms were examined and categorized into four main subtypes (ML, DL, NLP, expert systems), each with its own subcategories, and recorded accordingly . ML was evaluated under the subheadings of supervised learning, unsupervised learning, and reinforcement learning. Within these subheadings, classification algorithms (such as logistic regression, Support Vector Machines (SVM), decision trees, random forest (RF), k-Nearest Neighbors (k-NN), and Naive Bayes) and regression algorithms (Linear Regression, Polynomial Regression, Ridge Regression, and Lasso Regression) were considered in line with the methodologies of the research articles. Clustering algorithms such as k-Means and hierarchical clustering were also included. Neural networks were assessed under the DL subheading, while Rule-Based, knowledge-based, and fuzzy logic systems were categorized under expert systems. A flow diagram presenting the search strategy and steps is depicted in Fig. . Knowledge-based systems As computer systems gained the ability to think and learn, the concept of ML, a subset of AI, emerged. Rooted in the 1940s, this concept has advanced in recent years due to the digitization of extensive datasets, the development of high-capacity general and graphics processors with superior analytical capabilities and minimal error rates, and its capacity to provide open access to information . The technology we are immersed in daily through smartphones and computers has become a subject of discussion in pediatric rheumatology literature due to its ease in diagnosis, monitoring, and communication. In the 1980s, expert systems mimicking a clinician’s diagnostic reasoning, consisting of a knowledge base and an inference mechanism component, were introduced . A knowledge-based system takes patient data as input and uses an inference engine to match that data with the repository of expert knowledge, providing diagnostic recommendations or treatment options . These systems can assist clinicians by providing evidence-based recommendations and identifying patterns in complex clinical data. The computer-based consultation system AI/RHEUM has been developed for non-rheumatologist physicians to provide diagnostic assistance in this specialty for adults. Although described as promising systems with moderate to excellent performance, none have successfully managed to integrate into daily practice . When evaluated for diagnosing pediatric rheumatic diseases, a modified version of this diagnostic decision support system has achieved a diagnostic accuracy of 92% . This system has been found to be instructive by experts. On the other hand, it has been emphasized that before the more widespread introduction of such expert systems, assessing the sensitivity of the system in diagnosing conditions, reviewing the legal aspects, and resolving financial issues are essential. Recently, an AI-based system named Juvenile Idiopathic Arthritis Dialogue-based Education (JADE) has been developed through a dialogue system to meet the educational needs of families of children with Juvenile Idiopathic Arthritis (JIA) . This system, which contains fundamental information about JIA and generates interactive dialogues that allow parents to ask questions, has aimed to inform parents about JIA better and address their inquiries. The results have been successful; however, concerns about bias arose due to the participants being from a single region and the analysis being conducted by a single coder. Additionally, the limitations have included awareness and experience requirements in using the system . As AI continues to advance, applications that enhance communication also emerge. Large language models and AI-powered chatbots have the potential to provide significant support to families of children with chronic rheumatic conditions, addressing the psychosocial aspects of these diseases. In the United Kingdom, a co-designed proof-of-concept study has been planned to design, develop, and test a chatbot intervention . These chatbots aim to help parents manage their children’s conditions more effectively between hospital visits. By addressing gaps in current clinical care and incorporating user feedback, such AI interventions can enhance the overall well-being of young patients and their families, potentially leading to broader implementation and efficacy trials in the future. In a recent study from a different geographic region, attention was drawn to Generative Pre-trained Transformer (ChatGPT) ‘s ability to process complex information and perform scientific reasoning with sensitivity . Yet, it was also emphasized that caution is necessary as its outputs are inferences from the input literature and may be detrimental to clinical practice. The guidance of patients through digital symptom assessment tools holds promise, particularly in addressing communication and transportation barriers to some extent and expediting the diagnostic process. Comparisons between the diagnostic accuracy of experienced rheumatologists and that of an AI-based symptom monitoring device have yielded encouraging results . However, the integration of these tools into pediatric practice, which requires more detailed examinations and meticulous differential diagnoses, appears challenging. Prediction models for diagnosis and outcome Laboratory use in rheumatic diseases guides the diagnostic approach, but it is not conclusive. In the presentation of the disease, certain clinical findings and values can serve as signals for prognosis and shape treatment management. In a study aiming to create opportunities for conservative approaches in Multisystem inflammatory syndrome in children (MIS-C) management, differentiation of risk groups was intended, and the prognostic values of key clinical and laboratory features in the disease were evaluated via classic ML algorithms (decision tree, SVM, logistic regression analysis, naïve Bayes, and linear discriminant analysis). It has been concluded that brain natriuretic peptide, total protein, ferritin, and D-dimer laboratory tests demonstrated the highest performance . On the other hand, the clinical utility of certain indicators that are essential for differential diagnosis or prognosis may be limited in practical clinical use. Thus, another study aimed to develop a model for screening potential patients diagnosed with anti-melanoma differentiation-associated protein 5 (MDA5) antibody-positive juvenile dermatomyositis (JDM), taking into consideration the limited access to myositis-specific antibodies in many developing countries due to financial and technological challenges. The final prediction model, incorporating eight clinical variables and four auxiliary results, yielded a high predictive accuracy for the risk of anti-MDA5 antibody in JDM, demonstrated by an AUC of 0.975 and validated internally with robust metrics, suggesting its superiority over traditional logistic regression models. In addition to the necessity of external validation to demonstrate the accuracy of this model under different conditions, the value of screening for these antibodies in the proposed group has been emphasized . In another study, a nomogram has been constructed utilizing non-invasive clinical features from patients diagnosed with JDM (sedimentation, interleukin-10, MDA-5). The study concluded that, despite certain methodological limitations, this prediction model could offer clinical guidance in evaluating secondary interstitial lung disease in JDM and predicting long-term prognosis . In the saliva of children with Sjögren’s syndrome ( n = 16), 105 chemokines, cytokines, and biomarkers (CCBM) have been identified 43 of which have exhibited differences compared to healthy controls ( n = 11) . ML methods have been employed to assess the predictive power that links these CCBMs to the disease. It has been highlighted that further studies are needed to determine whether the newly identified CCBMs in the saliva of children diagnosed with Sjögren’s syndrome are reliable early indicators of the disease or rather a representative of the pediatric-specific disease process . Real time data and biomarkers Another area of application is the development of machine-assisted tangible tools as biomarkers, allowing real-time activity monitoring. For instance, a non-invasive and practical tool that assesses knee involvement and can detect activity has been suggested as a biomarker in JIA. Documenting joint acoustic emissions bilaterally and applying signal changes to a ML algorithm has allowed for differentiating children diagnosed with JIA from healthy controls . It has been asserted that this tool could enable screening, monitoring, and prompt treatment. On top of that, the concept has emerged that wearable devices with digital biomarkers could serve as future tools for home disease monitoring, providing objective data for disease tracking . Thermal imaging, capable of detecting temperature alterations in tissue abnormalities, has been explored in the recognition of inflammation in knee and ankle joints in JIA. Despite observed correlations between thermal and visual imaging data, conflicting results have been obtained in different studies . Accelerometers and gyroscopes, capable of measuring the degree of restricted motion in the affected joint by comparing it with normal reference values or the unaffected joint, have been developed . In adult studies, the use of acceleration patterns has been examined to distinguish differences between osteoarthritis, rheumatoid arthritis, and spondyloarthritis . Consequently, the hypothesis has been proposed that these acceleration patterns could also be employed to objectively assess affected joints in JIA . Stratifying patient cluster The inadequacy of the proposed classification criteria to encompass all patients, and the heterogeneity in disease progression and treatment response have necessitated the asset for genomic technologies to formulate a classification that reflects both the clinical phenotype range and the underlying biology of JIA. In 2009, it was demonstrated that previously unidentified cytokines could be determined through cluster analysis of multiplex data, revealing that systemic JIA (sJIA) has a different profile compared to oligoarticular and polyarticular JIA . Furthermore, Van Nieuwenhove et al. aimed to identify common immune signatures between subtypes using the RF technique. The immune signature was particularly prominent in active patients and systemic types. Additionally, the ML analysis of the dataset was able to distinguish patients with JIA from healthy controls with an accuracy of approximately 90% . In the last decade, the use of SVMs along with gene expression profiles in peripheral blood mononuclear cells (PBMCs) has come to the forefront in various medical fields. Applying transcriptomic techniques such as microarray or sequencing to the blood or synovial fluid of rheumatic patients holds promise for disease definition and outcome prediction. While it has been demonstrated that the gene expression signatures in PBMCs from polyarticular JIA patients reflect distinct disease processes and provide a molecular classification of the disease, the goal was to further develop this idea with the support of ML . A relatively ethnically heterogeneous JIA cohort consisting of 23 patients in remission and 27 patients with active disease was planned to be stratified by disease activity with segregated PBMC transcriptomes . For this purpose, four common algorithms, including kNN, RF, SVM with cubic kernel (cSVM), and SVM with Gaussian kernel (gSVM) have been considered. After developing models on the entire dataset for predicting the disease stage, efforts have been made to determine whether the inclusion of different patient populations would impact the model’s performance. The results supported the notion that PBMCs, with the use of fitting analytical tools to enhance classification algorithms, constitute a promising source for developing expression-based biomarkers . Similarly, in another recent study, transcriptome data from whole blood gene expressions have been examined aiming to differentiate rheumatic diseases from reactive/infectious conditions. Using the RF algorithm, it has been emphasized that variations in gene expression in blood cells might precede clinical symptoms. The conclusion drawn was that this observation could be beneficial in identifying new biomarkers for pediatric rheumatic diseases . On the other hand, the heterogeneity within each subset, including a limited number of samples, highlights the need for further validation. In another study utilizing transcriptomic data, a diagnostic model based on the RF algorithm has been developed as a way to distinguish between children with sJIA and healthy children . Through an in-depth examination of datasets from public genetic databases, this study identified four key genes (ALDH1A1, CEACAM1, YBX3, and SLC6A8) that could serve as crucial biomarkers for sJIA. By employing RF techniques with a composite panel of clinical and biomarker variables in non-sJIA patients, the authors have observed enhanced prediction of inactive disease after 18 months, surpassing the predictive capability of conventional determinants alone. The statement suggests that if validated in external cohorts, this approach could pave the way for more rationally designed, biologically based, and personalized treatment strategies in early JIA . In a study utilizing clinical and cytokine expression data, probabilistic principal components analysis (PPCA) through cluster analysis has been employed to identify homogeneous disease subsets . In another study by the same group, sparse multilayer non-negative matrix factorization (NMF) has been developed to uncover data-driven joint patterns predicting clinical phenotypes and disease course. Seven distinct patterns were identified among clinical subtypes . These studies demonstrate that unsupervised ML can identify clinically and biologically significant patterns and classifications. As a result, a stronger connection will be established between clinical outcomes and treatment response, providing evidence that guides the management process. Visual analyses The concept of DL, a subset of ML, undoubtedly plays a significant role in the revival and evolution of AI. DL, manifested through machine perception and computer vision methods, is used in the analysis of medical images with high sensitivity, specificity, and accuracy. AI techniques may help diminish dimensionality or recognize patterns that are not noticeable to the human eye and brain with its detection, quantification, and classification tasks . Most of the studies integrating DL algorithms in rheumatology have been conducted on small and homogeneous datasets . Looking at the current literature in the field of pediatric rheumatology; in a study evaluating the retrospective treatment response of patients diagnosed with Chronic Non-Bacterial Osteomyelitis (CNO), the aim was to develop an ML algorithm that could compare whole-body magnetic resonance imaging (WBMRI) images before and after pamidronate treatment. The results of this algorithm were then intended to be compared with the analysis of a panel of pediatric radiologists . As a result, while machine algorithm could detect new lesions or resolution of a lesion with good precision, it had been unable to accurately classify stable disease . Consequently, the authors underscore the importance of additional research to validate the model in a prospective manner in real-time and ascertain its practicality in a clinical environment. In another study using visual samples, the potential of AI to discriminate children with JDM from healthy controls and assess the capability of nailfold capillaroscopy (NFC) images to reflect disease activity have been evaluated. The assessment of 1120 images obtained from 111 patients and 321 images from 31 healthy controls resulted in the conclusion that a deep neural network named NFC-Net provides a reliable indicator for discrimination and disease status . Individualized treatment algorithms Another agenda route is the elucidation of patients’ clinical and genetic characteristics through AI technology, aiming to create personalized treatment algorithms. In two separate studies conducted by the same group, ML-based models have been developed using electronic medical records to predict the efficacy of methotrexate and etanercept earlier and accurately in JIA patients . The goal was to provide convincing evidence and guidance for treatment algorithms. Among the models used in comparing the results, Extreme Gradient Boosting (XGBoost) algorithm, which works on decision trees, seems to stand out in terms of effectiveness with an accuracy rate of 94.52%. In a different study, the same prediction model was used to predict kidney damage in children diagnosed with IgA vasculitis based on clinical data, demonstrating its potential to reduce the negative effects of invasive procedures . The revealed methods may provide insights into the prognosis and potential complications of the disease, guiding the development of individualized approaches and algorithms. Another goal with the use of advanced algorithms is to contribute to a better understanding of molecular mechanisms and the identification of advanced treatment strategies through silico models based on systems biology. A target-specific treatment strategy for Still’s disease has been investigated using the therapeutic performance mapping system (TPMS), which relies on pattern recognition techniques to create mathematical models simulating the pathophysiology of humans in silico by integrating existing biological, pharmacological, and medical knowledge . The results have confirmed the use of biologics as a suitable immunomodulatory treatment strategy for Still’s disease and supported the benefits of early IL-1 blockade . However, the precise time for windows of opportunity has not been determined for these interventions. In a study from the United Kingdom, the response to methotrexate treatment was assessed using AI methods, resulting in the identification of six different patterns (prediction model AUC values 0.65–0.71). Consequently, beyond traditional yes/no assessments (e.g., ACRPedi30), clusters differing by time or individually have been obtained . Advancements in rheumatology healthcare are underway through the utilization of digital technology, leveraging real-world data and evidence. This involves detecting minimal changes in the disease process, monitoring adverse effects and effectiveness of treatment, and enhancing therapeutic efficacy . Focusing on the advancements and limitations It seems apparent that AI technologies will streamline access to data and enhance efficiency in the realm of pediatric rheumatology, a domain still in the process of maturation. It can provide diagnostic awareness and enable early diagnosis, treatment, data sharing, and communication. On the other hand, efforts to develop biomarkers, which are currently lacking in detecting and monitoring disease activity and treatment response, are precious. Potential complications can be thwarted thanks to tools that will allow nigher and real-time monitoring of disease activity and enable timely intervention . In clinical research, the development of targeted and individualized treatment approaches through multifaceted analysis of large data sets is seen as one of the main goals . Studies focusing on the application of AI in pediatric rheumatic diseases have been designed with the support of biomedical and computer sciences, and they are quite limited in number. The prominent limitations in the current literature are the inadequacy of data breadth and diversity. Just as seeing a substantial number and variety of patients is important for a physician to gain experience, having a wide range of input-output relationships is crucial for a machine to reduce bias and error rates. In this respect, standard protocols encouraging database sharing among different clinical centers can be developed. Additionally, creating representative training datasets that embrace diverse ethnic and geographic compositions, approaches, and procedures is crucial for clinical applicability and reliability . Another issue is the inability to achieve a balance of fit, leading the model to exhibit overfitting or underfitting. Ensuring a balance between model complexity and the training process can aid in generating effective predictions . Legal and ethical concerns persist, particularly regarding the accountability of clinical decisions made by machines and the accumulation of substantial volumes of sensitive data . Furthermore, research involving children requires strict ethical considerations to protect their physical and psychological well-being. Since children typically cannot provide informed consent, consent must be obtained from their parents or legal guardians. Additionally, it is crucial to ensure that healthcare professionals, parents, and patients are adequately informed and educated about the procedure. When dealing with rheumatology registries, it is pivotal to address bioethical issues by meticulously considering privacy provisions, establishing strict ethical guidelines and ordinances, and ensuring their alignment with the pertinent national and regional legal frameworks . Details and limitations of existing literature using ML algorithms with different goals are presented in Table . This review has several limitations. The primary limitation is the diversity of AI algorithms and, consequently, the variation in study methodologies, which creates challenges in reaching standardized and definitive conclusions. Additionally, divergences in terminology and classification can impact the number of articles retrieved. However, in this review, along with commonly used standardized terms, specific keywords were employed to ensure comprehensive coverage. As computer systems gained the ability to think and learn, the concept of ML, a subset of AI, emerged. Rooted in the 1940s, this concept has advanced in recent years due to the digitization of extensive datasets, the development of high-capacity general and graphics processors with superior analytical capabilities and minimal error rates, and its capacity to provide open access to information . The technology we are immersed in daily through smartphones and computers has become a subject of discussion in pediatric rheumatology literature due to its ease in diagnosis, monitoring, and communication. In the 1980s, expert systems mimicking a clinician’s diagnostic reasoning, consisting of a knowledge base and an inference mechanism component, were introduced . A knowledge-based system takes patient data as input and uses an inference engine to match that data with the repository of expert knowledge, providing diagnostic recommendations or treatment options . These systems can assist clinicians by providing evidence-based recommendations and identifying patterns in complex clinical data. The computer-based consultation system AI/RHEUM has been developed for non-rheumatologist physicians to provide diagnostic assistance in this specialty for adults. Although described as promising systems with moderate to excellent performance, none have successfully managed to integrate into daily practice . When evaluated for diagnosing pediatric rheumatic diseases, a modified version of this diagnostic decision support system has achieved a diagnostic accuracy of 92% . This system has been found to be instructive by experts. On the other hand, it has been emphasized that before the more widespread introduction of such expert systems, assessing the sensitivity of the system in diagnosing conditions, reviewing the legal aspects, and resolving financial issues are essential. Recently, an AI-based system named Juvenile Idiopathic Arthritis Dialogue-based Education (JADE) has been developed through a dialogue system to meet the educational needs of families of children with Juvenile Idiopathic Arthritis (JIA) . This system, which contains fundamental information about JIA and generates interactive dialogues that allow parents to ask questions, has aimed to inform parents about JIA better and address their inquiries. The results have been successful; however, concerns about bias arose due to the participants being from a single region and the analysis being conducted by a single coder. Additionally, the limitations have included awareness and experience requirements in using the system . As AI continues to advance, applications that enhance communication also emerge. Large language models and AI-powered chatbots have the potential to provide significant support to families of children with chronic rheumatic conditions, addressing the psychosocial aspects of these diseases. In the United Kingdom, a co-designed proof-of-concept study has been planned to design, develop, and test a chatbot intervention . These chatbots aim to help parents manage their children’s conditions more effectively between hospital visits. By addressing gaps in current clinical care and incorporating user feedback, such AI interventions can enhance the overall well-being of young patients and their families, potentially leading to broader implementation and efficacy trials in the future. In a recent study from a different geographic region, attention was drawn to Generative Pre-trained Transformer (ChatGPT) ‘s ability to process complex information and perform scientific reasoning with sensitivity . Yet, it was also emphasized that caution is necessary as its outputs are inferences from the input literature and may be detrimental to clinical practice. The guidance of patients through digital symptom assessment tools holds promise, particularly in addressing communication and transportation barriers to some extent and expediting the diagnostic process. Comparisons between the diagnostic accuracy of experienced rheumatologists and that of an AI-based symptom monitoring device have yielded encouraging results . However, the integration of these tools into pediatric practice, which requires more detailed examinations and meticulous differential diagnoses, appears challenging. Laboratory use in rheumatic diseases guides the diagnostic approach, but it is not conclusive. In the presentation of the disease, certain clinical findings and values can serve as signals for prognosis and shape treatment management. In a study aiming to create opportunities for conservative approaches in Multisystem inflammatory syndrome in children (MIS-C) management, differentiation of risk groups was intended, and the prognostic values of key clinical and laboratory features in the disease were evaluated via classic ML algorithms (decision tree, SVM, logistic regression analysis, naïve Bayes, and linear discriminant analysis). It has been concluded that brain natriuretic peptide, total protein, ferritin, and D-dimer laboratory tests demonstrated the highest performance . On the other hand, the clinical utility of certain indicators that are essential for differential diagnosis or prognosis may be limited in practical clinical use. Thus, another study aimed to develop a model for screening potential patients diagnosed with anti-melanoma differentiation-associated protein 5 (MDA5) antibody-positive juvenile dermatomyositis (JDM), taking into consideration the limited access to myositis-specific antibodies in many developing countries due to financial and technological challenges. The final prediction model, incorporating eight clinical variables and four auxiliary results, yielded a high predictive accuracy for the risk of anti-MDA5 antibody in JDM, demonstrated by an AUC of 0.975 and validated internally with robust metrics, suggesting its superiority over traditional logistic regression models. In addition to the necessity of external validation to demonstrate the accuracy of this model under different conditions, the value of screening for these antibodies in the proposed group has been emphasized . In another study, a nomogram has been constructed utilizing non-invasive clinical features from patients diagnosed with JDM (sedimentation, interleukin-10, MDA-5). The study concluded that, despite certain methodological limitations, this prediction model could offer clinical guidance in evaluating secondary interstitial lung disease in JDM and predicting long-term prognosis . In the saliva of children with Sjögren’s syndrome ( n = 16), 105 chemokines, cytokines, and biomarkers (CCBM) have been identified 43 of which have exhibited differences compared to healthy controls ( n = 11) . ML methods have been employed to assess the predictive power that links these CCBMs to the disease. It has been highlighted that further studies are needed to determine whether the newly identified CCBMs in the saliva of children diagnosed with Sjögren’s syndrome are reliable early indicators of the disease or rather a representative of the pediatric-specific disease process . Another area of application is the development of machine-assisted tangible tools as biomarkers, allowing real-time activity monitoring. For instance, a non-invasive and practical tool that assesses knee involvement and can detect activity has been suggested as a biomarker in JIA. Documenting joint acoustic emissions bilaterally and applying signal changes to a ML algorithm has allowed for differentiating children diagnosed with JIA from healthy controls . It has been asserted that this tool could enable screening, monitoring, and prompt treatment. On top of that, the concept has emerged that wearable devices with digital biomarkers could serve as future tools for home disease monitoring, providing objective data for disease tracking . Thermal imaging, capable of detecting temperature alterations in tissue abnormalities, has been explored in the recognition of inflammation in knee and ankle joints in JIA. Despite observed correlations between thermal and visual imaging data, conflicting results have been obtained in different studies . Accelerometers and gyroscopes, capable of measuring the degree of restricted motion in the affected joint by comparing it with normal reference values or the unaffected joint, have been developed . In adult studies, the use of acceleration patterns has been examined to distinguish differences between osteoarthritis, rheumatoid arthritis, and spondyloarthritis . Consequently, the hypothesis has been proposed that these acceleration patterns could also be employed to objectively assess affected joints in JIA . The inadequacy of the proposed classification criteria to encompass all patients, and the heterogeneity in disease progression and treatment response have necessitated the asset for genomic technologies to formulate a classification that reflects both the clinical phenotype range and the underlying biology of JIA. In 2009, it was demonstrated that previously unidentified cytokines could be determined through cluster analysis of multiplex data, revealing that systemic JIA (sJIA) has a different profile compared to oligoarticular and polyarticular JIA . Furthermore, Van Nieuwenhove et al. aimed to identify common immune signatures between subtypes using the RF technique. The immune signature was particularly prominent in active patients and systemic types. Additionally, the ML analysis of the dataset was able to distinguish patients with JIA from healthy controls with an accuracy of approximately 90% . In the last decade, the use of SVMs along with gene expression profiles in peripheral blood mononuclear cells (PBMCs) has come to the forefront in various medical fields. Applying transcriptomic techniques such as microarray or sequencing to the blood or synovial fluid of rheumatic patients holds promise for disease definition and outcome prediction. While it has been demonstrated that the gene expression signatures in PBMCs from polyarticular JIA patients reflect distinct disease processes and provide a molecular classification of the disease, the goal was to further develop this idea with the support of ML . A relatively ethnically heterogeneous JIA cohort consisting of 23 patients in remission and 27 patients with active disease was planned to be stratified by disease activity with segregated PBMC transcriptomes . For this purpose, four common algorithms, including kNN, RF, SVM with cubic kernel (cSVM), and SVM with Gaussian kernel (gSVM) have been considered. After developing models on the entire dataset for predicting the disease stage, efforts have been made to determine whether the inclusion of different patient populations would impact the model’s performance. The results supported the notion that PBMCs, with the use of fitting analytical tools to enhance classification algorithms, constitute a promising source for developing expression-based biomarkers . Similarly, in another recent study, transcriptome data from whole blood gene expressions have been examined aiming to differentiate rheumatic diseases from reactive/infectious conditions. Using the RF algorithm, it has been emphasized that variations in gene expression in blood cells might precede clinical symptoms. The conclusion drawn was that this observation could be beneficial in identifying new biomarkers for pediatric rheumatic diseases . On the other hand, the heterogeneity within each subset, including a limited number of samples, highlights the need for further validation. In another study utilizing transcriptomic data, a diagnostic model based on the RF algorithm has been developed as a way to distinguish between children with sJIA and healthy children . Through an in-depth examination of datasets from public genetic databases, this study identified four key genes (ALDH1A1, CEACAM1, YBX3, and SLC6A8) that could serve as crucial biomarkers for sJIA. By employing RF techniques with a composite panel of clinical and biomarker variables in non-sJIA patients, the authors have observed enhanced prediction of inactive disease after 18 months, surpassing the predictive capability of conventional determinants alone. The statement suggests that if validated in external cohorts, this approach could pave the way for more rationally designed, biologically based, and personalized treatment strategies in early JIA . In a study utilizing clinical and cytokine expression data, probabilistic principal components analysis (PPCA) through cluster analysis has been employed to identify homogeneous disease subsets . In another study by the same group, sparse multilayer non-negative matrix factorization (NMF) has been developed to uncover data-driven joint patterns predicting clinical phenotypes and disease course. Seven distinct patterns were identified among clinical subtypes . These studies demonstrate that unsupervised ML can identify clinically and biologically significant patterns and classifications. As a result, a stronger connection will be established between clinical outcomes and treatment response, providing evidence that guides the management process. The concept of DL, a subset of ML, undoubtedly plays a significant role in the revival and evolution of AI. DL, manifested through machine perception and computer vision methods, is used in the analysis of medical images with high sensitivity, specificity, and accuracy. AI techniques may help diminish dimensionality or recognize patterns that are not noticeable to the human eye and brain with its detection, quantification, and classification tasks . Most of the studies integrating DL algorithms in rheumatology have been conducted on small and homogeneous datasets . Looking at the current literature in the field of pediatric rheumatology; in a study evaluating the retrospective treatment response of patients diagnosed with Chronic Non-Bacterial Osteomyelitis (CNO), the aim was to develop an ML algorithm that could compare whole-body magnetic resonance imaging (WBMRI) images before and after pamidronate treatment. The results of this algorithm were then intended to be compared with the analysis of a panel of pediatric radiologists . As a result, while machine algorithm could detect new lesions or resolution of a lesion with good precision, it had been unable to accurately classify stable disease . Consequently, the authors underscore the importance of additional research to validate the model in a prospective manner in real-time and ascertain its practicality in a clinical environment. In another study using visual samples, the potential of AI to discriminate children with JDM from healthy controls and assess the capability of nailfold capillaroscopy (NFC) images to reflect disease activity have been evaluated. The assessment of 1120 images obtained from 111 patients and 321 images from 31 healthy controls resulted in the conclusion that a deep neural network named NFC-Net provides a reliable indicator for discrimination and disease status . Another agenda route is the elucidation of patients’ clinical and genetic characteristics through AI technology, aiming to create personalized treatment algorithms. In two separate studies conducted by the same group, ML-based models have been developed using electronic medical records to predict the efficacy of methotrexate and etanercept earlier and accurately in JIA patients . The goal was to provide convincing evidence and guidance for treatment algorithms. Among the models used in comparing the results, Extreme Gradient Boosting (XGBoost) algorithm, which works on decision trees, seems to stand out in terms of effectiveness with an accuracy rate of 94.52%. In a different study, the same prediction model was used to predict kidney damage in children diagnosed with IgA vasculitis based on clinical data, demonstrating its potential to reduce the negative effects of invasive procedures . The revealed methods may provide insights into the prognosis and potential complications of the disease, guiding the development of individualized approaches and algorithms. Another goal with the use of advanced algorithms is to contribute to a better understanding of molecular mechanisms and the identification of advanced treatment strategies through silico models based on systems biology. A target-specific treatment strategy for Still’s disease has been investigated using the therapeutic performance mapping system (TPMS), which relies on pattern recognition techniques to create mathematical models simulating the pathophysiology of humans in silico by integrating existing biological, pharmacological, and medical knowledge . The results have confirmed the use of biologics as a suitable immunomodulatory treatment strategy for Still’s disease and supported the benefits of early IL-1 blockade . However, the precise time for windows of opportunity has not been determined for these interventions. In a study from the United Kingdom, the response to methotrexate treatment was assessed using AI methods, resulting in the identification of six different patterns (prediction model AUC values 0.65–0.71). Consequently, beyond traditional yes/no assessments (e.g., ACRPedi30), clusters differing by time or individually have been obtained . Advancements in rheumatology healthcare are underway through the utilization of digital technology, leveraging real-world data and evidence. This involves detecting minimal changes in the disease process, monitoring adverse effects and effectiveness of treatment, and enhancing therapeutic efficacy . It seems apparent that AI technologies will streamline access to data and enhance efficiency in the realm of pediatric rheumatology, a domain still in the process of maturation. It can provide diagnostic awareness and enable early diagnosis, treatment, data sharing, and communication. On the other hand, efforts to develop biomarkers, which are currently lacking in detecting and monitoring disease activity and treatment response, are precious. Potential complications can be thwarted thanks to tools that will allow nigher and real-time monitoring of disease activity and enable timely intervention . In clinical research, the development of targeted and individualized treatment approaches through multifaceted analysis of large data sets is seen as one of the main goals . Studies focusing on the application of AI in pediatric rheumatic diseases have been designed with the support of biomedical and computer sciences, and they are quite limited in number. The prominent limitations in the current literature are the inadequacy of data breadth and diversity. Just as seeing a substantial number and variety of patients is important for a physician to gain experience, having a wide range of input-output relationships is crucial for a machine to reduce bias and error rates. In this respect, standard protocols encouraging database sharing among different clinical centers can be developed. Additionally, creating representative training datasets that embrace diverse ethnic and geographic compositions, approaches, and procedures is crucial for clinical applicability and reliability . Another issue is the inability to achieve a balance of fit, leading the model to exhibit overfitting or underfitting. Ensuring a balance between model complexity and the training process can aid in generating effective predictions . Legal and ethical concerns persist, particularly regarding the accountability of clinical decisions made by machines and the accumulation of substantial volumes of sensitive data . Furthermore, research involving children requires strict ethical considerations to protect their physical and psychological well-being. Since children typically cannot provide informed consent, consent must be obtained from their parents or legal guardians. Additionally, it is crucial to ensure that healthcare professionals, parents, and patients are adequately informed and educated about the procedure. When dealing with rheumatology registries, it is pivotal to address bioethical issues by meticulously considering privacy provisions, establishing strict ethical guidelines and ordinances, and ensuring their alignment with the pertinent national and regional legal frameworks . Details and limitations of existing literature using ML algorithms with different goals are presented in Table . This review has several limitations. The primary limitation is the diversity of AI algorithms and, consequently, the variation in study methodologies, which creates challenges in reaching standardized and definitive conclusions. Additionally, divergences in terminology and classification can impact the number of articles retrieved. However, in this review, along with commonly used standardized terms, specific keywords were employed to ensure comprehensive coverage. Artificial intelligence has the potential to enhance ground truth by improving sensitivity, specificity, repeatability, time efficiency, and cost-effectiveness in a specific evaluation . There is a need for AI technologies in the field of pediatric rheumatology. Without ignoring ethical concerns regarding data privacy, the limiting factors of the existing literature should be addressed, and the focus should be on exploring various strategies to overcome them. Technical support and expertise will be required in the development of DL algorithms, but the clinical experiences and knowledge of rheumatologists will shed light on these studies. Therefore, interdisciplinary teamwork is required with the close collaboration of clinicians, biomedical informatics scientists, and ML experts. There is a need for guidelines and general advice on how to ensure and advance the management of big data in a collaborative and ethical manner . Below is the link to the electronic supplementary material. Supplementary Material 1 |
NipahVR: a resource of multi-targeted putative therapeutics and epitopes for the Nipah virus | 813e89ee-c3ae-4a99-8d8a-91b4526cfa43 | 7036594 | Pathology[mh] | Nipah virus (NiV) is a highly pathogenic virus closely related to the Hendra virus (HeV) from the genus Henipavirus of the family Paramyxoviridae . NiV is an enveloped single-stranded RNA (ssRNA), a negative-sense virus of size ~18 250 nucleotides. It encodes nine proteins namely nucleoprotein (N), four proteins encoded by P gene (phosphoprotein (P), W, V, C protein), matrix (M) protein, fusion (F) glycoprotein, attachment glycoproteins (G) and a large polymerase (L) protein . Different NiV proteins play a cardinal role in viral infection and disease manifestation. Viral G protein (attachment protein) first binds to the Ephrin-B2 or B3 cellular receptors found on the neuron, smooth muscles, capillaries and arterial endothelial cells. G protein provides attachment to the host cell surface, which triggers the fusion by the F protein . Subsequently, F protein, a 546 amino acid (aa)-long type I transmembrane protein, mediates fusion of virus and host cell membranes and mediates cell entry . Then, viral RNA content gets synthesized and translated into the proteins. P gene encodes four gene products. A structural P protein (709 aa) is essential for genome replication encoded by unedited mRNA and localized in the cytoplasm. The three additional non-structural proteins (V, W and C) contribute towards the evasion of the innate immune response through inhibiting the different signaling pathways and are crucial for the viral infection. V and W proteins are produced by RNA editing and localized in the cytoplasm and nucleus, respectively, and the second open reading frame (ORF) generates C protein. M protein (352 aa) has a crucial role in viral budding. It also provides firmness to virion through interacting with envelope and F protein. M protein is also known to hijack cellular pathways and machines to facilitate nuclear localization. N protein (532 aa) is mainly responsible for the viral genome encapsidating. The largest NiV protein L retains all the enzymatic functions like genome replication and transcription for the viral RNA synthesis . NiV is an emerging zoonotic virus classified as a category C priority pathogen and biosafety level-4 (BSL-4) agent that signify a rolling threat to humans and animals worldwide . It was originated and first isolated from the village ‘Sungai Nipah’ . It is an etiological agent of diverse diseases such as encephalitis, respiratory illness and fever . Epidemiologically, NiV transmission occurs mainly through infected animals (bats, pigs, etc.) and contaminates food consumption and may spread through person to person . Flying foxes (fruit bats) from the genus Pteropus are known as a natural reservoir and host of the NiV . Among all Pteropus species, P. giganteus (Indian flying fox) mainly distributed in south Asian regions like Bangladesh, India and Pakistan . Other species were also found in different parts of Southeast Asia like P. vampyrus and P. hypomelanus in Malaysia and P. lylei in Thailand and Cambodia . Up to now, various sporadic outbreaks were reported from different countries, mainly from South Asia, i.e. India, Bangladesh, Malaysia and Singapore, since the first incidence of Malaysia in 1998 with the high mortality rate between 40 and 75% depending on clinical manifestations . These are mainly endemic in India and Bangladesh . In India, the first outbreak was reported from the Siliguri, West Bengal, in 2001 with high fatalities due to NiV encephalitis . In this, the involvement of pigs as an infection mediator is not observed, and direct person-to-person transmission was reported that signify high risk to public health . Later in 2007, another outbreak was reported from West Bengal with 100% mortality . Very recently, in May 2018, the first NiV outbreak occurred in southern India in Kozhikode and Malappuram districts of Kerala. Several deaths were reported due to the unavailability of a practical solution, which is of concern to India and the world . Moreover, a study also describes the presence of NiV RNA in Pteropus giganteus in different Indian states signifying it as a natural reservoir in India . However, more surveillance studies are necessary to access the NiV outbreak risk among susceptible populations living in different geographical locations . Furthermore, several NiV outbreaks were also documented from Bangladesh between 2001 to 2015 . These are linked to many deaths due to encephalitis with neurological and respiratory complications . Moreover, different studies also provide information about NiV origin, evolution and stability over time . For example, a study shows the conservation between the isolates from Bangladesh, 2004, and India, 2007, with 99.2 and 99.8%, nucleotide and amino acid similarity, respectively . Similarly, another study also provides phylogenetic analysis and conservation of NiV, i.e. between 96 and 100% . Moreover, a recent report by Ravichandran et al . has also found conservancy among NiV proteins . There are also efforts to combat the NiV, and different strategies (vaccines, immunotherapies, antiviral drugs) were tried to eradicate the infection . Distinct approaches like subunit vaccine , vectored vaccine and live-vectored vaccine mainly utilizing the G and P proteins demonstrated to elicit an immune response . Likewise, a virus-like particle (VLP)-based vaccine is also shown protection against NiV . These experimental vaccines are mainly tested on animal models like a hamster, ferret, cats and pigs . Moreover, a subunit vaccine for use in horses has been developed based on the HeV G protein . Additionally, the use of monoclonal and polyclonal antibodies also showed success in treating NiV infection in animals . However, more studies, i.e. in vitro as well as in vivo, will be required before conducting clinical trials. Likewise, other strategies such as RNA interference (RNAi) through small interfering RNAs (siRNAs) are also used previously to inhibit N and L genes . Further, an anti-viral drug, ribavirin, is also used in infected persons and also tested on animal experiments. However, it did not show good efficiency against the infection . Very recently, a small-molecule antiviral drug favipiravir (T-705) has shown the compelling antiviral activity in the hamster model against the henipaviruses (NiV and HeV) . Likewise, the potential of natural antiviral agents from the medicinal plants can also be explored to combat viruses . Furthermore, studies also provide promising small-molecule inhibitors targeting NiV proteins . Apart from these, there are also some computational efforts to provide solutions in different ways. For example, some studies advocate the computational designing of vaccine epitopes against the specific NiV proteins . Very recently, we have also developed a quantitative structure-activity relationship (QSAR)-based prediction algorithm ‘ anti-Nipah ’ for the identification of effective inhibitors against the NiV . The algorithm will predict the antiviral ability of any query compound against the NiV . However, despite determinations, the Nipah Virus study is generally neglected. Currently, there is no Food and Drug Administration (FDA)-approved therapeutics or prophylactic vaccine available to treat NiV diseases in humans, and treatment is only supportive . Simultaneously, a broad range of Nipah hosts, its pathogenesis and the high fatality rate pose a recurring threat to humanity . Therefore, effective vaccines and therapeutics are an inevitable necessity of time . In the study, we have made efforts to provide potential therapeutic and vaccine solutions targeting all NiV proteins or genes. The resource ‘NipahVR’ may assist the worldwide scientific community in fighting against this lethal pathogen.
Data retrieval Complete genome sequences of the NiV were searched and collected from the NCBI database. In total, 18 complete or near-complete sequences were obtained utilizing the length-filtering criteria of size more than 10 kb and provided on the resource . A facility with a category-wise (i.e. host, geographical area, and country) search option is applied on the web resource for the ease. Different information such as strain/isolate, host/source, length, country and geographical region was cataloged. Further, gene and protein sequences of reference NiV genome (NC_002728.1) are used for the downstream analyses, mainly diagnostic primer designing, vaccine epitope prediction and RNA-based therapeutics (i.e. siRNAs, microRNAs (miRNAs), single guide RNAs (sgRNAs)). Codon analysis Codon bias analysis of the complete genome sequence is performed to explore relative synonymous codon usage (RSCU) and codon frequency. Further, codon preference and context are analyzed employing the Anaconda program . Phylogenomics We have performed phylogenomic analysis to understand the phylogenetic reconstruction of NiV genomes. In the current study, we have employed complete genomes of 15 NiV that cause outbreaks in various Asian countries like India, Bangladesh, Malaysia and Singapore from 1998–2018. The genomic information was extracted from various sources like NCBI, ViPR, Viral zone and research articles . Further, the Molecular Evolutionary Genetics Analysis (MEGAv7.0) software with a Neighbor-joining method was utilized . The evolutionary distance was inferred through the Jukes–Cantor method, with a bootstrap test of 1000 replicates. Diagnostic primers In order to provide diagnostic primers, two strategies were utilized. First published literature was searched for extracting the experimentally used primer pairs for the diagnosis of the Nipah virus along with relevant information. Secondly, putative primer pairs were also designed using the PrimerDesign-M tool , keeping default parameters primarily. Briefly, in the region of interest option, the start and end of each genomic region were provided to design primers specific to the target gene. Further, we have chosen multiple-fragment primer design options with a flex parameter for fragment overlap option for each given genomic region. We have selected the primer length of 20 (minimum) to 25 (maximum) for each gene with the 5% detection limit. Then, complexity limit 2 was set to allow one degenerate position. Further, the maximum difference between melting temperatures (Tm) of reverse and forward primers was taken as 5°C. The window size of 10 was utilized for the investigation of dimerization, while the default dimer ratio (0.9) was chosen. Lastly, the G/C clamp option that helps to specify G or C at 3′ ends of primer was selected. This helps to promote specific binding at 3′ ends due to strong GC bases bonding. Vaccine epitopes For the potential epitope identification, 9-mer overlapping peptides were generated for each NiV-encoded proteins, i.e. N, P, W, V, C, M F, G and L. Further, the analyses were performed in quest to find promiscuous immune response, inducing peptides against the virus as also described previously . In order to have proper immune response different arms of the immune system, i.e. B-cell epitopes, T-cell epitopes and MHC binding is essential, hence considered in the study. The reliable and efficient linear B-cell epitopes of each NiV proteins were predicted using the LBtope algorithm , and strict criteria of 60% were selected. The result is further analyzed and integrated on the web server. Further, in order to identify the efficient MHC class I-binding peptides (putative cytotoxic T lymphocytes (CTL) epitopes) from the Nipah proteins, the ProPred1 prediction server was utilized, and preeminent 4% were selected. Similarly, MHC class II binders (potential T helper (Th) epitopes) were estimated using the ProPred tool , and the uppermost 3% peptides were recommended as promiscuous binders. Furthermore, potential CTL epitopes were also derived using the CTLPred tool developed using the artificial neural network (ANN) and support vector machine (SVM) techniques through employing the combined approach with the default cut-off of 0.51 for ANN and 0.36 for SVM. The top 3 epitopes were selected for each protein. Moreover, experimentally proven NiV epitopes were also searched. siRNAs and miRNAs RNA-based therapeutics could provide an alternative way to fight against the pathogens. For the designing of siRNAs against the different NiV genes, two different algorithms, i.e. a virus-specific algorithm, VIRsiRNApred and DesiRm , were used. Further, the immunomodulatory potential of the siRNAs is deduced using the imrna program . For the prediction of siRNAs using VIRsiRNApred, Model-2 was utilized. It is developed on 1725 viral siRNAs employing hybrid nucleotide frequencies, binary and thermodynamic features. Further, only efficient siRNAs having at least 55% predicted inhibition score were considered. Additionally, off-targets were also elucidated against the Homo sapiens (human) genome assembly GRCh37 (hg19). Correspondingly, potential siRNAs using the threshold of 0.80 were also deduced applying the DesiRm algorithm. Moreover, the imRNA program with the ‘siRNA immunotoxicity’ option along with the ‘screen siRNA library’ module is used to explore the immunomodulatory or non-immunomodulatory potential of siRNAs. SiRNAs with a score of 4.5 and above are considered as immunomodulatory, and less than the threshold is non-immunomodulatory. Moreover, we have also predicted NiV miRNAs. First, the VMir algorithm , which is consists of two programs VMir analyzer and VMir viewer, is used with the default settings to detect the putative precursor miRNAs (pre-miRNAs) hairpin (HP) structure. In brief, the maximum HP size of 200, minimum HP score (100) and minimum window count size of 35 are utilized. Further, these pre-miRNAs were subjected to the MatureBayes tool to identify mature miRNAs. sgRNAs and genome editing Recently, clustered regularly interspaced short palindromic repeat-associated protein (CRISPR/Cas) system-based genome editing employing sgRNAs also shown to have an application to target a particular genomic region or viral pathogen . For this, we have used the ge-CRISPR tool to screen the NiV genes/genome on both forward and reverse strands to discover and extract the possible sgRNAs, i.e. 20 base pair upstream sequences as putative targets based on the protospacer adjacent motif (PAM) mainly ‘NGG’. Web resource development The eventual goal is to provide the web resource of the putative therapeutic regimens and solutions from the study to assist in fighting with the deadly Nipah virus and support scientific society in therapeutic development. This platform, ‘NipahVR’, is hosted on the Linux environment using a LAMP (Linux, Apache HTTP Server, MySQL and PHP) open-source web development platform. The front-end of the web interface is built using the PHP, HTML, CSS and JavaScript as also accomplished earlier , and the back-end of the resource is complemented with MySQL for the data management.
Complete genome sequences of the NiV were searched and collected from the NCBI database. In total, 18 complete or near-complete sequences were obtained utilizing the length-filtering criteria of size more than 10 kb and provided on the resource . A facility with a category-wise (i.e. host, geographical area, and country) search option is applied on the web resource for the ease. Different information such as strain/isolate, host/source, length, country and geographical region was cataloged. Further, gene and protein sequences of reference NiV genome (NC_002728.1) are used for the downstream analyses, mainly diagnostic primer designing, vaccine epitope prediction and RNA-based therapeutics (i.e. siRNAs, microRNAs (miRNAs), single guide RNAs (sgRNAs)).
Codon bias analysis of the complete genome sequence is performed to explore relative synonymous codon usage (RSCU) and codon frequency. Further, codon preference and context are analyzed employing the Anaconda program .
We have performed phylogenomic analysis to understand the phylogenetic reconstruction of NiV genomes. In the current study, we have employed complete genomes of 15 NiV that cause outbreaks in various Asian countries like India, Bangladesh, Malaysia and Singapore from 1998–2018. The genomic information was extracted from various sources like NCBI, ViPR, Viral zone and research articles . Further, the Molecular Evolutionary Genetics Analysis (MEGAv7.0) software with a Neighbor-joining method was utilized . The evolutionary distance was inferred through the Jukes–Cantor method, with a bootstrap test of 1000 replicates.
In order to provide diagnostic primers, two strategies were utilized. First published literature was searched for extracting the experimentally used primer pairs for the diagnosis of the Nipah virus along with relevant information. Secondly, putative primer pairs were also designed using the PrimerDesign-M tool , keeping default parameters primarily. Briefly, in the region of interest option, the start and end of each genomic region were provided to design primers specific to the target gene. Further, we have chosen multiple-fragment primer design options with a flex parameter for fragment overlap option for each given genomic region. We have selected the primer length of 20 (minimum) to 25 (maximum) for each gene with the 5% detection limit. Then, complexity limit 2 was set to allow one degenerate position. Further, the maximum difference between melting temperatures (Tm) of reverse and forward primers was taken as 5°C. The window size of 10 was utilized for the investigation of dimerization, while the default dimer ratio (0.9) was chosen. Lastly, the G/C clamp option that helps to specify G or C at 3′ ends of primer was selected. This helps to promote specific binding at 3′ ends due to strong GC bases bonding.
For the potential epitope identification, 9-mer overlapping peptides were generated for each NiV-encoded proteins, i.e. N, P, W, V, C, M F, G and L. Further, the analyses were performed in quest to find promiscuous immune response, inducing peptides against the virus as also described previously . In order to have proper immune response different arms of the immune system, i.e. B-cell epitopes, T-cell epitopes and MHC binding is essential, hence considered in the study. The reliable and efficient linear B-cell epitopes of each NiV proteins were predicted using the LBtope algorithm , and strict criteria of 60% were selected. The result is further analyzed and integrated on the web server. Further, in order to identify the efficient MHC class I-binding peptides (putative cytotoxic T lymphocytes (CTL) epitopes) from the Nipah proteins, the ProPred1 prediction server was utilized, and preeminent 4% were selected. Similarly, MHC class II binders (potential T helper (Th) epitopes) were estimated using the ProPred tool , and the uppermost 3% peptides were recommended as promiscuous binders. Furthermore, potential CTL epitopes were also derived using the CTLPred tool developed using the artificial neural network (ANN) and support vector machine (SVM) techniques through employing the combined approach with the default cut-off of 0.51 for ANN and 0.36 for SVM. The top 3 epitopes were selected for each protein. Moreover, experimentally proven NiV epitopes were also searched.
RNA-based therapeutics could provide an alternative way to fight against the pathogens. For the designing of siRNAs against the different NiV genes, two different algorithms, i.e. a virus-specific algorithm, VIRsiRNApred and DesiRm , were used. Further, the immunomodulatory potential of the siRNAs is deduced using the imrna program . For the prediction of siRNAs using VIRsiRNApred, Model-2 was utilized. It is developed on 1725 viral siRNAs employing hybrid nucleotide frequencies, binary and thermodynamic features. Further, only efficient siRNAs having at least 55% predicted inhibition score were considered. Additionally, off-targets were also elucidated against the Homo sapiens (human) genome assembly GRCh37 (hg19). Correspondingly, potential siRNAs using the threshold of 0.80 were also deduced applying the DesiRm algorithm. Moreover, the imRNA program with the ‘siRNA immunotoxicity’ option along with the ‘screen siRNA library’ module is used to explore the immunomodulatory or non-immunomodulatory potential of siRNAs. SiRNAs with a score of 4.5 and above are considered as immunomodulatory, and less than the threshold is non-immunomodulatory. Moreover, we have also predicted NiV miRNAs. First, the VMir algorithm , which is consists of two programs VMir analyzer and VMir viewer, is used with the default settings to detect the putative precursor miRNAs (pre-miRNAs) hairpin (HP) structure. In brief, the maximum HP size of 200, minimum HP score (100) and minimum window count size of 35 are utilized. Further, these pre-miRNAs were subjected to the MatureBayes tool to identify mature miRNAs.
Recently, clustered regularly interspaced short palindromic repeat-associated protein (CRISPR/Cas) system-based genome editing employing sgRNAs also shown to have an application to target a particular genomic region or viral pathogen . For this, we have used the ge-CRISPR tool to screen the NiV genes/genome on both forward and reverse strands to discover and extract the possible sgRNAs, i.e. 20 base pair upstream sequences as putative targets based on the protospacer adjacent motif (PAM) mainly ‘NGG’.
The eventual goal is to provide the web resource of the putative therapeutic regimens and solutions from the study to assist in fighting with the deadly Nipah virus and support scientific society in therapeutic development. This platform, ‘NipahVR’, is hosted on the Linux environment using a LAMP (Linux, Apache HTTP Server, MySQL and PHP) open-source web development platform. The front-end of the web interface is built using the PHP, HTML, CSS and JavaScript as also accomplished earlier , and the back-end of the resource is complemented with MySQL for the data management.
NipahVR is an integrative and systematic resource mainly dedicated towards the putative therapeutics and vaccinome against the Nipah virus. A well-structured and dynamic web interface is developed for navigation. It is classified into different divisions like genomes, phylogenomics, molecular diagnostic primers and most importantly vaccine epitopes (B-cell, CTL, MHC-I and -II binders) and therapeutics (siRNAs, sgRNAs, miRNAs). The complete architecture of the NipahVR compendium is shown in , demonstrating all the components. NipahVR genomes Genomic information of available 18 Nipah virus sequences was compiled and provided on the resource . It is equipped with an advance genome search facility for easy navigation. Nipah genomes can be searched using different search options such as host/source (i.e. human, pig, bat), geographical region (Asia) and country (India, Bangladesh, Malaysia) with the detailed meta-information. Codon usage and context We have calculated the codon frequency and pattern in the genomes, which vary due to the nucleotide composition, GC percentage, expression level, etc. Additionally, codon preference is represented through histogram, where rare codons are shown in blue and black color signify preferred codons . The most preferred codons are AAA, AUG, UAA, and GCG, CGC, CGU is the least preferred or rare codons in the Nipah virus reference genome. Additionally, using the Anaconda software, we have also calculated codon pair residual values in the genome, indicating an association between two codons. A two-colored matrix depicting average residual values, red color denotes rare, and green color shows preferred codon pairs . Phylogenomics The reconstructed phylogenetic tree showed the sum of branch length of 0.11. Out of 15, 07 NiV genomes from Malaysia outbreaks (1998–99) were clustered together with the bootstrap of 100. Further, from the 04 NiV genomes from Bangladesh outbreak, two genomes from 2004 and 2010 outbreaks were clustered together. Interestingly, the 02 NiV genomes from the 2008 epidemic of Bangladesh were grouped with the NiV of 2007, West Bengal, India. Moreover, the recent outbreak of the NiV virus in Kerala, India, was found in the Indian and Bangladesh NiV genomes but at a distant branch. The phylogenetic reconstruction of NiV genomes is shown in . The NiV genomes from Asian outbreaks are grouped according to their geographical location. The Malaysian outbreak of NiV was closely related while the Indian and Bangladesh epidemic NiV displayed close resemblance with each other, except the recent Kerala outbreak, which is unrelated with all the NiV genomes. Our phylogenomic study showed that due to the course of time, the NiV showed significant mutations at the genomic level. Molecular diagnostic primers We have collected primer pairs utilized for the detection of the NiV. Detailed information about primers like the respective primer name, a sequence of primer, its orientation (forward and reverse), genomic region and study reference is provided . Overall, 55 forward and 53 reverse primers were reported against different genes of NiV and compiled on the web server. Additionally, we have also designed primer pairs for each gene utilizing the PrimerDesign-M tool. In total, two primer pairs for N-gene; six primer pairs for P-gene; three primer pairs for M-gene; six primer pairs for F-gene; one primer pair for G-gene and nine primer pairs for polymerase gene. Gene name, start–end and melting temperature (Tm) of primers were reported. A detailed list of all predicted primer pairs is provided in . These primers (experimental and designed) will be valuable for the detection and diagnosis of NiV. Putative epitopes In this study, efforts were made for the identification of potential vaccine candidates for the Nipah virus. Epitopes encompassing promising MHC I and II binders, CTL epitopes and B-cell epitopes is cataloged. 9-mer peptides were generated from the Nipah proteins. Overall, 979 MHC-I and 1628 MHC-II binding peptides were deduced and presented on the server. For both MHC-I and II binders, peptide sequence, respective protein region, MHC-alleles and counts were provided. The protein-wise number of peptides for both the MHC classes is shown in . Likewise, 27 potential CTL epitopes with sequence, start–end and allele information were recorded . Furthermore, 400 efficient B-cell epitopes along with sequence, a b-cell confidence score is provided belonging to different Nipah proteins. Among all, for N protein EKKNNQDLK, P (W, V) protein SPEDEEPSS, for C protein LLTLFRRTK, for M protein AAYPLGVGK, for F protein SRLEDRRVR, for G protein DPLLAMDEG and for L protein KLSQNLLVT peptides are the highest-scoring and confident epitopes, which can be focused. Further, we have also found four experimentally proven linear b-cell epitopes, i.e. three for N protein (SIQTKFAP, SNRTQGE and SPSAAE) and G (NQILKPKLISYTLPVVG). However, we did not find any T-cell epitopes. Additionally, we have also analyzed putative epitopes from all the arms of the immune system, i.e. B-cell epitopes, MHC-I and II binders and CTL epitopes to find the common epitopes, which could be promising and can be recommended as the potential vaccine candidates . We have found the 24 epitopes reported to be B-cell epitope and also efficient MHC-I and II binders ; 70 epitopes belonging to both b-cell as well as MHC-I binders ; and 109 epitopes which are b-cell as well as MHC-II binders . Further, there are two epitopes (‘ILSAFNTVI’ (G protein) and ‘FRRNNAIAF’ (M protein)) which are characterized in all three categories, i.e. CTL epitopes and both MHC-I and II binders. Likewise, 13 epitopes from CTL epitopes, and MHC-I binders, 5 epitopes from CTL epitopes and MHC-II binders were catered . Furthermore, two epitopes were found to be as B-cell as well as CTL epitope, i.e. ‘QPSDDKRLS’ from L protein and ‘NLRSRLAAK’ from N protein. Along with this, 278 peptides that are putative MHC-I and II binders were also cataloged . siRNAs and miRNAs RNA-based therapeutic interventions provide another approach to counter lethal viruses through silencing the genes. In this study, we have also tried to provide a compendium of potent siRNAs against the individual NiV genes. Overall, 118 putative siRNAs with very few off-targets using the VIRsiRNApred algorithm, which is developed using the experimentally proven viral siRNAs and 441 siRNAs employing DesiRm tool, were cataloged along with inferred inhibition efficiency in percentage. Additionally, the immunomodulatory potential of these siRNAs is also predicted, which could be helpful and crucial in the development of vaccine adjuvant or RNA-based immunotherapy and therapeutics. Furthermore, the number of siRNA off-targets to the human genome is also presented. The resource provides a complete picture of these efficient siRNAs with a small number of off-targets and detail information such as sense–antisense sequence, gene region, start–end, efficacy scores and immunomodulatory potential. The set of efficacious siRNAs, i.e. 18 using the VIRsiRNApred algorithm and 43 using DesiRm is specified. Furthermore, we have also designed and identified the Nipah precursor and mature miRNAs. Totally, 22 precursor miRNAs (pre-miRNAs) were identified along with 44 mature Nipah-miRNAs (22 5p and 22 3p). Among these, 3 pre-miRNAs are from N, 3 from P/V/C, 1 from M, 2 from F, 3 from G and 10 belong to the L gene. Detailed information related to miRNAs, i.e. mature miRNA sequences (5p and 3p), genomic region, the precursor (hairpin) and mature miRNA location on Nipah genome, precursor (hairpin) length, GC content, score and rank is extracted and provided. sgRNAs and genome editing On the basis of our analysis, overall, 1412 sgRNAs from the NiV were obtained. Out of these, we have found and listed 126 sgRNAs that can act as putative targets against the virus. Apart from this, a list of the 21 most efficient sgRNAs is given in . The output of this displays sequence of sgRNA, associated PAM (NGG), information of strand (sense/antisense), start and end coordinates, AT and GC content and efficiency of each sgRNA (percentage efficiency). This information will be beneficial to predict or identify CRISPR sgRNA targets against NiV and will certainly reduce experimental time and cost.
Genomic information of available 18 Nipah virus sequences was compiled and provided on the resource . It is equipped with an advance genome search facility for easy navigation. Nipah genomes can be searched using different search options such as host/source (i.e. human, pig, bat), geographical region (Asia) and country (India, Bangladesh, Malaysia) with the detailed meta-information.
We have calculated the codon frequency and pattern in the genomes, which vary due to the nucleotide composition, GC percentage, expression level, etc. Additionally, codon preference is represented through histogram, where rare codons are shown in blue and black color signify preferred codons . The most preferred codons are AAA, AUG, UAA, and GCG, CGC, CGU is the least preferred or rare codons in the Nipah virus reference genome. Additionally, using the Anaconda software, we have also calculated codon pair residual values in the genome, indicating an association between two codons. A two-colored matrix depicting average residual values, red color denotes rare, and green color shows preferred codon pairs .
The reconstructed phylogenetic tree showed the sum of branch length of 0.11. Out of 15, 07 NiV genomes from Malaysia outbreaks (1998–99) were clustered together with the bootstrap of 100. Further, from the 04 NiV genomes from Bangladesh outbreak, two genomes from 2004 and 2010 outbreaks were clustered together. Interestingly, the 02 NiV genomes from the 2008 epidemic of Bangladesh were grouped with the NiV of 2007, West Bengal, India. Moreover, the recent outbreak of the NiV virus in Kerala, India, was found in the Indian and Bangladesh NiV genomes but at a distant branch. The phylogenetic reconstruction of NiV genomes is shown in . The NiV genomes from Asian outbreaks are grouped according to their geographical location. The Malaysian outbreak of NiV was closely related while the Indian and Bangladesh epidemic NiV displayed close resemblance with each other, except the recent Kerala outbreak, which is unrelated with all the NiV genomes. Our phylogenomic study showed that due to the course of time, the NiV showed significant mutations at the genomic level.
We have collected primer pairs utilized for the detection of the NiV. Detailed information about primers like the respective primer name, a sequence of primer, its orientation (forward and reverse), genomic region and study reference is provided . Overall, 55 forward and 53 reverse primers were reported against different genes of NiV and compiled on the web server. Additionally, we have also designed primer pairs for each gene utilizing the PrimerDesign-M tool. In total, two primer pairs for N-gene; six primer pairs for P-gene; three primer pairs for M-gene; six primer pairs for F-gene; one primer pair for G-gene and nine primer pairs for polymerase gene. Gene name, start–end and melting temperature (Tm) of primers were reported. A detailed list of all predicted primer pairs is provided in . These primers (experimental and designed) will be valuable for the detection and diagnosis of NiV.
In this study, efforts were made for the identification of potential vaccine candidates for the Nipah virus. Epitopes encompassing promising MHC I and II binders, CTL epitopes and B-cell epitopes is cataloged. 9-mer peptides were generated from the Nipah proteins. Overall, 979 MHC-I and 1628 MHC-II binding peptides were deduced and presented on the server. For both MHC-I and II binders, peptide sequence, respective protein region, MHC-alleles and counts were provided. The protein-wise number of peptides for both the MHC classes is shown in . Likewise, 27 potential CTL epitopes with sequence, start–end and allele information were recorded . Furthermore, 400 efficient B-cell epitopes along with sequence, a b-cell confidence score is provided belonging to different Nipah proteins. Among all, for N protein EKKNNQDLK, P (W, V) protein SPEDEEPSS, for C protein LLTLFRRTK, for M protein AAYPLGVGK, for F protein SRLEDRRVR, for G protein DPLLAMDEG and for L protein KLSQNLLVT peptides are the highest-scoring and confident epitopes, which can be focused. Further, we have also found four experimentally proven linear b-cell epitopes, i.e. three for N protein (SIQTKFAP, SNRTQGE and SPSAAE) and G (NQILKPKLISYTLPVVG). However, we did not find any T-cell epitopes. Additionally, we have also analyzed putative epitopes from all the arms of the immune system, i.e. B-cell epitopes, MHC-I and II binders and CTL epitopes to find the common epitopes, which could be promising and can be recommended as the potential vaccine candidates . We have found the 24 epitopes reported to be B-cell epitope and also efficient MHC-I and II binders ; 70 epitopes belonging to both b-cell as well as MHC-I binders ; and 109 epitopes which are b-cell as well as MHC-II binders . Further, there are two epitopes (‘ILSAFNTVI’ (G protein) and ‘FRRNNAIAF’ (M protein)) which are characterized in all three categories, i.e. CTL epitopes and both MHC-I and II binders. Likewise, 13 epitopes from CTL epitopes, and MHC-I binders, 5 epitopes from CTL epitopes and MHC-II binders were catered . Furthermore, two epitopes were found to be as B-cell as well as CTL epitope, i.e. ‘QPSDDKRLS’ from L protein and ‘NLRSRLAAK’ from N protein. Along with this, 278 peptides that are putative MHC-I and II binders were also cataloged .
RNA-based therapeutic interventions provide another approach to counter lethal viruses through silencing the genes. In this study, we have also tried to provide a compendium of potent siRNAs against the individual NiV genes. Overall, 118 putative siRNAs with very few off-targets using the VIRsiRNApred algorithm, which is developed using the experimentally proven viral siRNAs and 441 siRNAs employing DesiRm tool, were cataloged along with inferred inhibition efficiency in percentage. Additionally, the immunomodulatory potential of these siRNAs is also predicted, which could be helpful and crucial in the development of vaccine adjuvant or RNA-based immunotherapy and therapeutics. Furthermore, the number of siRNA off-targets to the human genome is also presented. The resource provides a complete picture of these efficient siRNAs with a small number of off-targets and detail information such as sense–antisense sequence, gene region, start–end, efficacy scores and immunomodulatory potential. The set of efficacious siRNAs, i.e. 18 using the VIRsiRNApred algorithm and 43 using DesiRm is specified. Furthermore, we have also designed and identified the Nipah precursor and mature miRNAs. Totally, 22 precursor miRNAs (pre-miRNAs) were identified along with 44 mature Nipah-miRNAs (22 5p and 22 3p). Among these, 3 pre-miRNAs are from N, 3 from P/V/C, 1 from M, 2 from F, 3 from G and 10 belong to the L gene. Detailed information related to miRNAs, i.e. mature miRNA sequences (5p and 3p), genomic region, the precursor (hairpin) and mature miRNA location on Nipah genome, precursor (hairpin) length, GC content, score and rank is extracted and provided.
On the basis of our analysis, overall, 1412 sgRNAs from the NiV were obtained. Out of these, we have found and listed 126 sgRNAs that can act as putative targets against the virus. Apart from this, a list of the 21 most efficient sgRNAs is given in . The output of this displays sequence of sgRNA, associated PAM (NGG), information of strand (sense/antisense), start and end coordinates, AT and GC content and efficiency of each sgRNA (percentage efficiency). This information will be beneficial to predict or identify CRISPR sgRNA targets against NiV and will certainly reduce experimental time and cost.
Nipah virus is a priority pathogen from the Paramyxoviridae family and a BSL-4 agent, which causes various diseases such as encephalitis, respiratory illness and fever. Moreover, a high case fatality rate during epidemic, broad host range and lack of therapeutics or prophylactic vaccines critically demand efforts and a multidisciplinary approach to develop combat strategies against this virus. Up to now, very few computational studies focusing on the NiV are performed, and there is no such kind of therapeutic web resource available for it. In the current work, we have developed all-inclusive resource ‘NipahVR’ for the putative therapeutic solutions targeting individual Nipah genes and proteins. It provides a compendium of various components that includes genomics, diagnostic primers, vaccine epitopes (MHC-I and -II binders, CTL, B-cell) and therapeutics (siRNAs, miRNAs, sgRNAs). Here, based on our analysis, we are also endorsing and providing a catalog of potential vaccine epitopes and efficient siRNAs, miRNAs and sgRNAs. However, medicinal plant-based antivirals and other chemical compounds are not in the scope of current work. We anticipate that NipahVR will be useful and assist the wider scientific community in determining efficient antiviral candidates to fight against the Nipah and exterminate the infectivity. We will periodically update and maintain the stable functioning of the NipahVR web resource.
This study is conceived, designed and supervised by M.K. genomic data collection and curation; A.K.G., web server development; A.K.G., codon analysis; A.K.G., vaccine epitope analysis; A.K., K.M., A.K.G., phylogenetic analysis; A.R., sgRNAs and diagnostic primers; K.K., siRNA analysis; S.D., miRNA analysis; A.T., data interpretation; A.K.G., A.K., A.R., M.K.. Manuscript writing, A.K.G., A.R., K.K., M.K.
The authors declare that they have no competing interests.
Manuscript_color_change_baz159 Click here for additional data file. Supplementary_Information_baz159 Click here for additional data file.
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Improving uptake of COVID-19 testing and vaccination in a homeless population: mixed-methods evaluation of community health worker-led education in a shelter | beb23a58-3d6f-4536-a4b8-94c156244c12 | 11647339 | Health Literacy[mh] | Within the context of health determinants, access to quality education and healthcare are recognised by the Healthy People 2030 initiative to have significant impacts on health outcomes, a recognition that demands deeper consideration when addressing the unique challenges faced by people experiencing homelessness (PEH). Nationally, the homeless population experiences a mortality risk 3.5 times higher than housed individuals, bears a disproportionate burden of disability and disease and requires a higher level of care and access to health services, leading to an average life expectancy of 64–69 years, a sharp contrast to 76–81 years for the general population. These health disparities worsened during the COVID-19 pandemic, particularly as congregate shelter settings became increasingly high-risk environments. Unable to adhere to ‘stay at home’ guidelines, PEH were often pushed back to shelters by public officials or the clearing of encampments under claims of public safety. This movement meant putting PEH in environments where social distancing, quarantining and other mitigative behaviours were often impossible. As expected, shelter outbreaks were reported across the USA, where up to 66% of shelter users were positive for the virus. The heightened risk of COVID-19 infection intensified adverse outcomes for PEH as it compounded with pre-existing barriers to accessing services and their experiences of mistrust, stigma and discrimination within healthcare settings. As a result of the challenging landscape of COVID-19, PEH saw an elevated risk of hospitalisation and higher mortality rates, highlighting the urgent need for targeted interventions to address their unique vulnerabilities in the wake of communicable diseases like COVID-19. Subsequently, early publications called for regular testing and prioritisation of vaccination to protect PEH from adverse health outcomes and to limit transmission. Yet multiple countries have encountered similar challenges in vaccinating their homeless populations, with studies observing lower vaccination rates in PEH compared with the general population. To address this, strategies used internationally have included enhancing accessibility, collaborating with community partners, fostering trust and engaging targeted education programmes. These interventions had varying levels of success but often met barriers. The pandemic’s amplification of deep inequities in information and resource access furthered the isolation of the PEH demographic where low health literacy levels have been linked to poor health knowledge and access. In particular, health literacy was identified as a contributing barrier to COVID-19 testing among PEH. For vaccinations, a significant association between low intention to be vaccinated against COVID-19 and low health literacy was drawn, as evidenced by vaccine hesitancy rates among PEH that ranged from 35% to 48% throughout North America and Europe. The mitigatable nature of health literacy as a barrier to testing and vaccination acceptance highlights the importance of interventions centred around building trust and increasing access to accurate health information for informed decision-making. One such solution that emerged throughout the pandemic was the call for community health workers (CHWs) as crucial intermediaries between people who are underserved and healthcare systems. As an already present and trusted workforce in close proximity to the population they serve, their deep knowledge and relationships within their communities can be leveraged to bridge gaps in healthcare access and information. Their roles often include outreach, education and navigation services, putting them in a unique position to reach and educate through culturally sensitive and accessible care. Though minimal, studies explored how CHWs were able to connect to communities hit hardest during the pandemic, how CHWs positively impact under-represented and marginalised populations, and in some instances reach PEH specifically. This study builds on prior community-based participatory research (CBPR) conducted in collaboration with a homelessness services organisation in Indiana, to examine the impacts of COVID-19 on PEH. Early findings from our initial work revealed how knowledge gaps, misinformation and unreliable sources affected PEH perspectives on COVID-19 mitigative behaviours, highlighting the need for improved information dissemination and education. This work also demonstrated the potential outreach capacity of CHWs and supported the deployment of CHWs in homeless shelters as health educators and navigators to health and social services. In March 2021, the homelessness services organisation trained and deployed CHWs to implement and conduct free, voluntary COVID-19 rapid antigen testing, making it available to all guests and tenants of their shelters and supportive housing units. As part of the National Institutes of Health Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiative, this study aimed to identify motivators, demotivators and multilevel barriers to shelter-based COVID rapid testing and vaccination and to assess the impact of CHW-led education on the COVID-related knowledge, attitudes and beliefs of PEH.
Patient and public involvement This study was informed by ongoing CBPR co-led in partnership with a homelessness services agency in Indiana. Research questions were of mutual interest to the community partner organisation and the academic team and were informed by the homelessness service providers’ experience working with the community during the COVID-19 pandemic. The community partner organisation was not involved in the recruitment or conduct of the study but did allow the research team to post flyers and make announcements about the study onsite at the organisation. All study findings were shared with the community partner organisation in real time for their subsequent action and dissemination back to the community. Patients were not involved in this study as it was not clinical research. Study aims and rationale What are key motivators, demotivators and barriers to COVID rapid testing and vaccination among PEH? What is the effect of CHW-led education on the COVID-related knowledge, attitudes and beliefs of PEH? We designed a focus group formatted educational intervention to first learn participants’ knowledge, attitudes and beliefs about COVID-19 testing and vaccination while also providing the opportunity to share reliable information and clarify/correct misconceptions. The decision to integrate a focus group and educational session for the intervention was based on crucial insights gained from PEH in ongoing CBPR studies. The structure of an informal and conversational approach to an educational intervention is supported in literature analysing active learning or group discussion styles. This study used a mixed-methods approach by combining quantitative pre-/post-intervention assessments of participant knowledge and attitudes with additional qualitative insights on motivators and barriers captured during the focus group sessions. A certified CHW (RAZ) trained in research and ethics contributed to all aspects of this study and led key aspects including intervention design, recruitment, data collection, analysis and findings dissemination. Prior to the study, the CHW had experience working with this homeless community in the context of pandemic response and had carried out health programming at the shelter including conducting health assessments, navigation to healthcare appointments, insurance and pandemic relief resources. While this work allowed the CHW to build rapport with the community, they did not share lived experiences of homelessness. Recruitment, consent and compensation In recognition of the marginalisation faced by PEH, and their heightened risk of substance use, mental and physical health challenges, there were essential ethical considerations involved in this study design. Our community–academic partnership provided crucial insights for understanding population-specific risks and benefits and incorporating these into recruitment, eligibility, consenting, compensation and all other aspects of study design. Recruitment was done passively, through flyers and general announcements made onsite at a homelessness engagement centre during meal times; no direct recruitment occurred. Participation eligibility required interested subjects to be 18 years or older, current shelter guests or supportive housing tenants of the homelessness services organisation in Lafayette, Indiana and able to give informed consent. The following four questions were used to assess consent capacity, to ensure participants could comprehend the purpose and potential outcomes of the study, as well as their participation: Can you tell me what you understand to be the purpose of this study? Do you have to participate in this study? Can you tell me what will happen if you agree to take part in this study? What will happen if you decide not to be in the study? If the participant correctly responded to all four questions, they were eligible to participate in the study. If adequate consent capacity was not found, participants were informed they were not able to participate at this time. Interested participants were able to sign up for a focus group at a later date and would be assessed again for consent capacity. During the consent process, researchers clearly explained that their relationship with the organisation or services received would in no way be affected by their participation in the study. Furthermore, the role of the CHW as a member of the research team was clearly defined to mitigate the potential for role confusion between researcher and service provider and maintain research and ethical integrity. All focus groups provided dinner and participants received a US$60 gift card to a local grocery store as compensation for their time. Compensation amounts were agreed on by both community and academic partners to ensure fairness. Study procedures and materials Focus group educational sessions were conducted between November 2021 and April 2022. Each focus group session took up to 2 hours and included the informed consent process, demographic intake questionnaire, pretest, focus group, educational intervention and post-test. Each group had 4–6 participants and adhered to the facility’s COVID-19 safety policies and guidelines at the time. The consent forms, intake and pre-/post-test questionnaires were read aloud to participants privately, and responses were recorded in REDCap’s secure web platform. No one else was present besides the participants and researchers for the entirety of this process. Educational materials The educational materials were adapted from the Centers for Disease Control and Prevention (CDC) guidance made available during the pandemic. All questions and materials used were adjusted to appropriate literacy levels and context, with expressions like ‘stay at home’ altered due to the inappropriateness in a homeless shelter environment. Content for materials was tailored and further informed by the CHW’s experience working with the population as well as findings from the previous CBPR work. The moderator guide and education PowerPoint slides covered any information participants were asked during the pre-tests/post-tests. The educational content presented was reviewed by a nurse who worked part time at the shelter and was updated regularly throughout the intervention to include any updates on vaccinations, COVID-19 strains, etc, as needed and per participant feedback (such as to further clarify key points). Intake and pre/post-test questionnaires The intake questionnaire included demographics and questions to understand participants’ experiences with COVID-19 testing and vaccination. The pre-tests and post-tests, composed of identical questions, consisted of 15 true/false knowledge questions and 4–11 multiple choice attitude and belief questions, dependent on skip logic . Post-tests were administered immediately after intervention completion. Educational focus group interventions Once participants completed the intake process, they were brought into a conference room at the shelter, provided dinner, asked by the CHW to select a pseudonym and given a name tag. The pseudonym served as an additional privacy measure but also became a welcomed icebreaker as the process of choosing a fake name often leading to light conversations with other participants and the moderator. Focus group rules and guidelines were then explained by the CHW, including courtesy measures like asking participants to refrain from sharing any information disclosed by other participants for confidentiality, and that the intent of the group session was not to reach consensus but to respect differing views and opinions. Delivered via PowerPoint presentation with a moderator’s guide, the educational format was designed to promote conversation to understand attitudes and beliefs about COVID-19, and also be informative by asking mostly yes or no questions to engage participants actively before providing an answer. Participants were first prompted with a question and the group engaged in initial discussions allowing researchers to gain insights on topics like testing and vaccine awareness, motivators and demotivators. Subsequently, the CHW presented the correct answer prompting additional discourse for clarification and participant questions. The beginning of the session was signified by the start of the audio recording device and the CHW initiating engagement and on-topic discussion by asking for a ‘show of hands’ of whether participants had experienced COVID-19 testing. In addition to knowledge based yes/no questions, open-ended attitudes/beliefs centred questions were included, such as ‘what do you know about COVID-19’ or ‘what have you heard?’ After the focus group and post-test were completed, participants were thanked for their participation and compensated by gift card. Data storage, confidentiality and analysis All audio recordings were transcribed using Otter.ai and stored in a secure electronic database on a duo-protected Box folder. Quantitative analysis Quantitative data were collected via REDCap, cleaned and analysed using Excel and SPSS V.26 software. Descriptive analyses, including means and SDs, were applied to participants’ responses. Paired t-tests were then used to compare the pre-test and post-test group means, assessing for overall knowledge gain. Additionally, the mean scores per item were compared with determine knowledge gains per item from pre-test to post-test questionnaire. Results for knowledge questions were sorted into levels based on significance; high gains in knowledge/evidence of knowledge gaps (p<0.001), moderate gains in knowledge (p<0.05), low gains in knowledge/already high scores/not statistically significant (p>0.05). Findings from free response options for testing and vaccine questions were sorted into topical themes. Qualitative analysis Qualitative data were collected through the educational focus group sessions to provide additional contextual insights into quantitative findings. Recorded discussions were transcribed and reviewed for accuracy by members of the research team. A codebook was developed both deductively from the interview guide and inductively as codes were iterated or added during analysis. Each transcript was analysed thematically in NVivo V.12, a qualitative coding software program, by at least two independent coders who met at regular intervals for a consensus review of the coded material. Coders began with open coding, followed by axial coding. Themes related to multilevel motivators and demotivators for testing and vaccination were identified, guided by the socioecological model, which posits that health behaviour is influenced by multiple levels of factors (ie, individual, interpersonal and structural). Focus group sessions concluded when the research team determined thematic saturation was achieved.
This study was informed by ongoing CBPR co-led in partnership with a homelessness services agency in Indiana. Research questions were of mutual interest to the community partner organisation and the academic team and were informed by the homelessness service providers’ experience working with the community during the COVID-19 pandemic. The community partner organisation was not involved in the recruitment or conduct of the study but did allow the research team to post flyers and make announcements about the study onsite at the organisation. All study findings were shared with the community partner organisation in real time for their subsequent action and dissemination back to the community. Patients were not involved in this study as it was not clinical research.
What are key motivators, demotivators and barriers to COVID rapid testing and vaccination among PEH? What is the effect of CHW-led education on the COVID-related knowledge, attitudes and beliefs of PEH? We designed a focus group formatted educational intervention to first learn participants’ knowledge, attitudes and beliefs about COVID-19 testing and vaccination while also providing the opportunity to share reliable information and clarify/correct misconceptions. The decision to integrate a focus group and educational session for the intervention was based on crucial insights gained from PEH in ongoing CBPR studies. The structure of an informal and conversational approach to an educational intervention is supported in literature analysing active learning or group discussion styles. This study used a mixed-methods approach by combining quantitative pre-/post-intervention assessments of participant knowledge and attitudes with additional qualitative insights on motivators and barriers captured during the focus group sessions. A certified CHW (RAZ) trained in research and ethics contributed to all aspects of this study and led key aspects including intervention design, recruitment, data collection, analysis and findings dissemination. Prior to the study, the CHW had experience working with this homeless community in the context of pandemic response and had carried out health programming at the shelter including conducting health assessments, navigation to healthcare appointments, insurance and pandemic relief resources. While this work allowed the CHW to build rapport with the community, they did not share lived experiences of homelessness.
In recognition of the marginalisation faced by PEH, and their heightened risk of substance use, mental and physical health challenges, there were essential ethical considerations involved in this study design. Our community–academic partnership provided crucial insights for understanding population-specific risks and benefits and incorporating these into recruitment, eligibility, consenting, compensation and all other aspects of study design. Recruitment was done passively, through flyers and general announcements made onsite at a homelessness engagement centre during meal times; no direct recruitment occurred. Participation eligibility required interested subjects to be 18 years or older, current shelter guests or supportive housing tenants of the homelessness services organisation in Lafayette, Indiana and able to give informed consent. The following four questions were used to assess consent capacity, to ensure participants could comprehend the purpose and potential outcomes of the study, as well as their participation: Can you tell me what you understand to be the purpose of this study? Do you have to participate in this study? Can you tell me what will happen if you agree to take part in this study? What will happen if you decide not to be in the study? If the participant correctly responded to all four questions, they were eligible to participate in the study. If adequate consent capacity was not found, participants were informed they were not able to participate at this time. Interested participants were able to sign up for a focus group at a later date and would be assessed again for consent capacity. During the consent process, researchers clearly explained that their relationship with the organisation or services received would in no way be affected by their participation in the study. Furthermore, the role of the CHW as a member of the research team was clearly defined to mitigate the potential for role confusion between researcher and service provider and maintain research and ethical integrity. All focus groups provided dinner and participants received a US$60 gift card to a local grocery store as compensation for their time. Compensation amounts were agreed on by both community and academic partners to ensure fairness.
Focus group educational sessions were conducted between November 2021 and April 2022. Each focus group session took up to 2 hours and included the informed consent process, demographic intake questionnaire, pretest, focus group, educational intervention and post-test. Each group had 4–6 participants and adhered to the facility’s COVID-19 safety policies and guidelines at the time. The consent forms, intake and pre-/post-test questionnaires were read aloud to participants privately, and responses were recorded in REDCap’s secure web platform. No one else was present besides the participants and researchers for the entirety of this process. Educational materials The educational materials were adapted from the Centers for Disease Control and Prevention (CDC) guidance made available during the pandemic. All questions and materials used were adjusted to appropriate literacy levels and context, with expressions like ‘stay at home’ altered due to the inappropriateness in a homeless shelter environment. Content for materials was tailored and further informed by the CHW’s experience working with the population as well as findings from the previous CBPR work. The moderator guide and education PowerPoint slides covered any information participants were asked during the pre-tests/post-tests. The educational content presented was reviewed by a nurse who worked part time at the shelter and was updated regularly throughout the intervention to include any updates on vaccinations, COVID-19 strains, etc, as needed and per participant feedback (such as to further clarify key points). Intake and pre/post-test questionnaires The intake questionnaire included demographics and questions to understand participants’ experiences with COVID-19 testing and vaccination. The pre-tests and post-tests, composed of identical questions, consisted of 15 true/false knowledge questions and 4–11 multiple choice attitude and belief questions, dependent on skip logic . Post-tests were administered immediately after intervention completion. Educational focus group interventions Once participants completed the intake process, they were brought into a conference room at the shelter, provided dinner, asked by the CHW to select a pseudonym and given a name tag. The pseudonym served as an additional privacy measure but also became a welcomed icebreaker as the process of choosing a fake name often leading to light conversations with other participants and the moderator. Focus group rules and guidelines were then explained by the CHW, including courtesy measures like asking participants to refrain from sharing any information disclosed by other participants for confidentiality, and that the intent of the group session was not to reach consensus but to respect differing views and opinions. Delivered via PowerPoint presentation with a moderator’s guide, the educational format was designed to promote conversation to understand attitudes and beliefs about COVID-19, and also be informative by asking mostly yes or no questions to engage participants actively before providing an answer. Participants were first prompted with a question and the group engaged in initial discussions allowing researchers to gain insights on topics like testing and vaccine awareness, motivators and demotivators. Subsequently, the CHW presented the correct answer prompting additional discourse for clarification and participant questions. The beginning of the session was signified by the start of the audio recording device and the CHW initiating engagement and on-topic discussion by asking for a ‘show of hands’ of whether participants had experienced COVID-19 testing. In addition to knowledge based yes/no questions, open-ended attitudes/beliefs centred questions were included, such as ‘what do you know about COVID-19’ or ‘what have you heard?’ After the focus group and post-test were completed, participants were thanked for their participation and compensated by gift card.
The educational materials were adapted from the Centers for Disease Control and Prevention (CDC) guidance made available during the pandemic. All questions and materials used were adjusted to appropriate literacy levels and context, with expressions like ‘stay at home’ altered due to the inappropriateness in a homeless shelter environment. Content for materials was tailored and further informed by the CHW’s experience working with the population as well as findings from the previous CBPR work. The moderator guide and education PowerPoint slides covered any information participants were asked during the pre-tests/post-tests. The educational content presented was reviewed by a nurse who worked part time at the shelter and was updated regularly throughout the intervention to include any updates on vaccinations, COVID-19 strains, etc, as needed and per participant feedback (such as to further clarify key points).
The intake questionnaire included demographics and questions to understand participants’ experiences with COVID-19 testing and vaccination. The pre-tests and post-tests, composed of identical questions, consisted of 15 true/false knowledge questions and 4–11 multiple choice attitude and belief questions, dependent on skip logic . Post-tests were administered immediately after intervention completion.
Once participants completed the intake process, they were brought into a conference room at the shelter, provided dinner, asked by the CHW to select a pseudonym and given a name tag. The pseudonym served as an additional privacy measure but also became a welcomed icebreaker as the process of choosing a fake name often leading to light conversations with other participants and the moderator. Focus group rules and guidelines were then explained by the CHW, including courtesy measures like asking participants to refrain from sharing any information disclosed by other participants for confidentiality, and that the intent of the group session was not to reach consensus but to respect differing views and opinions. Delivered via PowerPoint presentation with a moderator’s guide, the educational format was designed to promote conversation to understand attitudes and beliefs about COVID-19, and also be informative by asking mostly yes or no questions to engage participants actively before providing an answer. Participants were first prompted with a question and the group engaged in initial discussions allowing researchers to gain insights on topics like testing and vaccine awareness, motivators and demotivators. Subsequently, the CHW presented the correct answer prompting additional discourse for clarification and participant questions. The beginning of the session was signified by the start of the audio recording device and the CHW initiating engagement and on-topic discussion by asking for a ‘show of hands’ of whether participants had experienced COVID-19 testing. In addition to knowledge based yes/no questions, open-ended attitudes/beliefs centred questions were included, such as ‘what do you know about COVID-19’ or ‘what have you heard?’ After the focus group and post-test were completed, participants were thanked for their participation and compensated by gift card.
All audio recordings were transcribed using Otter.ai and stored in a secure electronic database on a duo-protected Box folder. Quantitative analysis Quantitative data were collected via REDCap, cleaned and analysed using Excel and SPSS V.26 software. Descriptive analyses, including means and SDs, were applied to participants’ responses. Paired t-tests were then used to compare the pre-test and post-test group means, assessing for overall knowledge gain. Additionally, the mean scores per item were compared with determine knowledge gains per item from pre-test to post-test questionnaire. Results for knowledge questions were sorted into levels based on significance; high gains in knowledge/evidence of knowledge gaps (p<0.001), moderate gains in knowledge (p<0.05), low gains in knowledge/already high scores/not statistically significant (p>0.05). Findings from free response options for testing and vaccine questions were sorted into topical themes. Qualitative analysis Qualitative data were collected through the educational focus group sessions to provide additional contextual insights into quantitative findings. Recorded discussions were transcribed and reviewed for accuracy by members of the research team. A codebook was developed both deductively from the interview guide and inductively as codes were iterated or added during analysis. Each transcript was analysed thematically in NVivo V.12, a qualitative coding software program, by at least two independent coders who met at regular intervals for a consensus review of the coded material. Coders began with open coding, followed by axial coding. Themes related to multilevel motivators and demotivators for testing and vaccination were identified, guided by the socioecological model, which posits that health behaviour is influenced by multiple levels of factors (ie, individual, interpersonal and structural). Focus group sessions concluded when the research team determined thematic saturation was achieved.
Quantitative data were collected via REDCap, cleaned and analysed using Excel and SPSS V.26 software. Descriptive analyses, including means and SDs, were applied to participants’ responses. Paired t-tests were then used to compare the pre-test and post-test group means, assessing for overall knowledge gain. Additionally, the mean scores per item were compared with determine knowledge gains per item from pre-test to post-test questionnaire. Results for knowledge questions were sorted into levels based on significance; high gains in knowledge/evidence of knowledge gaps (p<0.001), moderate gains in knowledge (p<0.05), low gains in knowledge/already high scores/not statistically significant (p>0.05). Findings from free response options for testing and vaccine questions were sorted into topical themes.
Qualitative data were collected through the educational focus group sessions to provide additional contextual insights into quantitative findings. Recorded discussions were transcribed and reviewed for accuracy by members of the research team. A codebook was developed both deductively from the interview guide and inductively as codes were iterated or added during analysis. Each transcript was analysed thematically in NVivo V.12, a qualitative coding software program, by at least two independent coders who met at regular intervals for a consensus review of the coded material. Coders began with open coding, followed by axial coding. Themes related to multilevel motivators and demotivators for testing and vaccination were identified, guided by the socioecological model, which posits that health behaviour is influenced by multiple levels of factors (ie, individual, interpersonal and structural). Focus group sessions concluded when the research team determined thematic saturation was achieved.
A total of 15 focus groups were conducted with a total of 78 PEH. The majority of participants identified as white (74%, n=58), with 18% of participants identifying as black (n=14), 8% (n=6) as Hispanic and 8% (n=6) as other. Most (73%, n=57) identified as men, 24% as women (n=19) and 3% (n=2) as transgendered or non-binary . Nearly half (49%) were more than 50 years of age, 27% (n=21) between 40 and 49, and 24% between 25 and 49 (n=19). Most (60%, n=47) were staying at a shelter, 22% (n=17) were in permanent supportive housing (PSH) and 12% (n=9) were unsheltered. Almost all knew where to get tested for COVID-19 (96%, n=75) and felt it was easy to get tested (95%, n=74). Of those who had been tested for COVID before (84%, n=65), most (58%, n=38) were tested at least once at the shelter. Roughly half of the participants had been fully vaccinated (51%, n=4), 6% (n=5) were partially vaccinated and 42% (n=33) were not vaccinated. Motivators and demotivators to COVID-19 testing and vaccination presents a comprehensive list of COVID testing and vaccine motivators and demotivators identified from both quantitative pre-test data (see for survey results) and qualitative focus group data. Motivators were conceptualised as reasons participants did or would get tested or vaccinated and how they would encourage PEH to get tested or vaccinated. Demotivators were conceptualised as reasons they did not or would not get tested or vaccinated. Per the socioecological model, these were organised into the individual level (knowledge, attitudes, beliefs and experience), interpersonal level (influences from individuals in social network) and structural level (organisational, environmental, political or cultural influences, such as rules, policies and information dissemination). Testing At the individual level, symptoms, exposure, wanting to know their results (eg, for peace of mind) and being in a high-risk setting such as a shelter were identified as motivators, ‘ Because with us being homeless I mean, we go in and out of public places all the time, and so we never know on whether or not we're going to be around somebody else that has it’—FG13 . Pain or fear of pain was a prominent discussion point in focus groups as an individual-level demotivator or undesirable aspect of testing, ‘ They aint gotta shove that thing all the way up your nose anymore either… A lot of people are scared because of that [P4: I was!] … That’s why I didn’t do it for a long time.’—P3, FG2 . Other individual-level demotivators included concerns about the accuracy of testing, faith/religion, not feeling the need to get tested, fear of results and at the interpersonal level, social isolation, ‘ I think most people don't get tested because they're scared of what they—[P5: they scared of the results]—and then they feel isolated and people avoid them’—P1, FG10, PSH . In terms of interpersonal-level motivators, many were motivated to test when someone in their social network suggests it (ie, friends, family, shelter staff or healthcare provider), and to protect others and prevent spread of the virus, ‘ I’m concerned about, you know, spreading it to other people, you know, giving it to kids and the elderly people. Concern of safety. [P5: I agree with that] [Participants agree].’—P4, FG4 . At the structural level, available and free testing (ie, at the shelter) was a motivator, ‘ But since it’s here, and it’s available, free… Let’s just get tested.’—P1, FG3 . In general, having rapid tests was preferred, because despite some concern about test accuracy, the pain experienced or feared by participants was specific to PCR tests. Having the option to take their own nasal swab was also a structural-level motivator, ‘ I’d rather do it myself than have… instead of have someone else does.’—P1, FG2, as some were uncomfortable with other people swabbing their nose, ‘ I don't like people touching on me um poking at me.’—P5, FG1 . Many who were tested did so because they were required or perceived it as a requirement (eg, by hospital, jail, or work), ‘ I had to do it to keep my job.’—P4, FG1 . While many did not believe testing should be mandatory, particularly by the shelter, it was generally viewed as an effective way to get people to test, including the suggestion for the shelter to ‘ Enforce the rules that we got’—P4, FG11 . In one focus group, participants suggested offering food or refreshments as an incentive to get guests to test, ‘ Offer them food [other participant: yeah, especially the homeless community] [Participants recommend coffee, donuts, hot chocolate, and apple cider]… Refreshments and stuff, so there’s always food like refreshments or something. Someone will weasel their way over there to see what that’s about.—Unknown Participant, FG7, PSH County health department-mandated lockdowns, which required the shelter to restrict access for individuals not exposed on the identification of a positive case at the shelter, were a noteworthy deterrent to testing. This was criticised by many participants as hindering PEH’s ability to obtain services, reminiscent of the challenges presented by the national lockdown, ‘ … maybe a negative is that anytime someone does test positive around here they issue a lockdown and then if someone hadn’t been here that day, if they hadn't been vaccinated or don't want to for religious preferences or whatever the reason being, um they're denied services until lockdown’s over and usually when one person tests positive more people end up testing positive.’—P2, FG12 . Other demotivators included faith/religion, and as one person suggested, ‘credibility of the test site’ and ‘testing personnel’. Having inadequate information dissemination was also mentioned, ‘ I never needed to [get tested] but to be honest with you, I didn't know you can get tested. No one ever told me that.’—P4, FG14 . This translated to the need for COVID-19 education dissemination at the shelter as a method to motivate and encourage testing among guests. Participants made several suggestions on topics and ways to disseminate education, such as emphasising the severity of COVID, highlighting the cost of testing and vaccination, and making more announcements at the shelter to get the word out, ‘ P1: Give them some general information like the knowledge you just told us… P3: Be informed about … cost… Let them know how many people have died. Then they might wanna go get a shot.—FG2’ Vaccination At the individual level, preventing severe illness or death and keeping oneself and others safe were important motivators for many participants, ‘ … it [the vaccine] reduces your chances of getting it [COVID] and reduces the like, if you do get it, it reduces your chances of getting like severely sick. And it also reduces your chances of spreading it.’—P3, FG3 . Focus group discussions (FGDs) revealed many misconceptions about vaccines that explain fear and mistrust of the vaccine as a demotivator, such as the belief that the vaccine was developed too quickly and that the vaccine contains a live virus, ‘ It’s just like the flu virus the flu—I don’t want that shot, why would you give me the flu to make me better? It’s just crazy.’—FG9 (PSH ). There was also scepticism on how much protection the vaccine could provide, given that COVID-19 infection is still possible , ‘You can still get corona; you can still get corona virus with the shot.’—FG7, PSH . Others reported religious beliefs, concern of vaccine side effects, belief that having COVID-19 was enough protection, and not being concerned about getting really sick from COVID-19 as demotivators. At the interpersonal level, while many reported keeping others safe as a motivator to getting vaccinated, some were motivated by a doctor’s suggestion, or as one person stated ‘peer pressure’. Hearsay from social networks created more misconceptions about the vaccine that served as demotivators, for example, that the vaccine is ‘part of government conspiracy and contains a tracking chip’, ‘ A lot of people won’t take the [vaccine] cause they think they put in a chip ya or you get tracked.’—P3, FG5 . Other hearsay shared were that vaccines ‘can give you COVID’, harming your health through ‘heart attacks, blood clots, all kinds of things’, and even cause death, ‘ Heard you get the shot, you die.’—P1, FG13 At the structural level, while providing free vaccines, receiving an incentive to be vaccinated and requiring vaccination (eg, by one’s workplace) were identified as motivators, misinformation about COVID and the safety of the vaccine contributed to uncertainty of getting vaccinated, ‘ … the clearer we are about you know, some of the information, that’s, that’s probably one of the biggest fights that’s been about this is, is misinformation and getting correct and reliable information has probably been one of the biggest things for most Americans.’—P3, FG Post-intervention knowledge gains and attitude shifts The mean pre-test score was 10.76 out of 15 (SD=2.16), while the mean post-test score was 13.58 out of 15 (SD=1.72) (p<0.001). Most participants (n=71, 91%) improved by at least 1 and up to 10 points in their post-test scores. shows pre-/post-test knowledge scores per item, accompanied by qualitative insights shared during group sessions to provide additional context for the numerical scorings. The findings are categorised into three sections: high, moderate and low knowledge gains. High knowledge gains were observed for specific items, namely misconceptions about vaccine fertility (pre-test: 38%, post-test: 87%, p<0.001) and COVID-19 vaccines giving you the virus (pretest: 42%, post-test: 85%, p<0.001). There was a spectrum of viewpoints on both topics (see ), centred around the uncertainty of effects and ranging from complete belief in misconceptions to trust or knowledge of vaccine regulations and purpose. Knowledge gains and varying viewpoints were seen in the testing-related questions as well, including the cost of COVID-19 tests (pretest: 54%, post-test: 94%, p<0.001) with some participants unaware of free test access, the possibility to test negative but still have COVID-19 (pretest: 69%, post-test: 94%, p<0.001) and participants’ awareness of rapid testing options, asked as whether it is possible to have your results in 15 min (pretest: 73%, post-test: 97%, p<0.001). The supporting quotes in represent the scope of individuals existing knowledge and awareness of the testing topics, demonstrating, for example, how some participants understood the variation between the testing options by using result time, swab location/depth and accuracy as differentiation methods of rapid versus PCR (often representing PCR with comments like brain scraper, the one that touches your brain, etc). Participants displayed mixed feelings about the effectiveness of COVID-19 vaccines in the comments they shared, and topics such as protection against severe outcomes (pre-test: 60%, post-test 81%, p<0.001) and minimising the spread (pre-test: 77%, post-test: 91%, p<0.05) saw high to moderate knowledge gains. There was a general understanding that some degree of protection is offered through vaccination, with one participant stating they were upset when they discovered protection was not 100%. Other areas saw lower or no significant knowledge gains due to high pretest scores, however, the qualitative findings still provide important insights into these questions. For example, whether or not to get a COVID-19 vaccine if you’ve had COVID-19 before, participants generally knew that it is recommended to get it (pretest 81%, post-test 91%, p<0.05), but despite awareness, some didn’t necessarily agree with this recommendation by health agencies (‘THEY’ as depicted in ). Attitudes towards testing and vaccination were positively influenced postintervention. Of those not vaccinated (n=33), 21% were willing to get the vaccine initially, and this increased to 39% after the educational intervention, with ‘I don’t know’ responses decreasing from 39% to 18%. Participants’ willingness to get tested after exposure also increased from 83% to 92% after the session (see ). PEH perspective on CHW-led education sessions and preferred methods related to information sharing During the FGDs, participants provided valuable feedback on their experience with this style of educational intervention, discussed their preferred information sources and expressed their interests in various topics beyond COVID-19. Participants mainly provided positive feedback and appreciation for the information shared in the groups, which they found to be informative and trustworthy coming from the CHW. In addition, one participant brought up that they not only benefited from what the CHW shared, but found value in a setting with an opportunity to learn from others, ‘ I haven't been keeping up on anything lately, and what that man said [other FGD participant] uh sort of informed me that there’s more on the way, testing, better testing and uh I like that…’—P4 . The participants also identified specific sources they trust when seeking information, including the news and the CDC. However, scepticism was expressed, and participants contributed concerns of misinformation to changing guidance delivered by health authorities, one stating, ‘ A lot of contrary information. When Fauci first came out, masks are not necessary, masks are not necessary. Now two masks. You know, it just changes every day. It’s ridiculous’—P6, FG8 . Others mentioned online media’s responsibility for the spread of misleading information, ‘ I think that was probably one of the biggest things that hurt this whole situation we're in, is social media and this the era we live in of cell phones and spread of just hearsay and misinformation is so bad nowadays is like wildflower .’ —P3, FG12 . Overall, participants highlighted the importance of trustworthy and credible sources in gaining accurate information and that they value information from community members and experts, such as local university professors in a relevant field of study, local community officials, including CHWs and health department employees. This expanded to people with lived experience or who work in close proximity to the topics they would educate, deeming them more trustworthy sources because they have ‘seen more’. Discussions also included nurses and medical doctors, however, some preferred community members stating ‘ Doctors- they don't explain stuff completely.’—P1, FG3 .
presents a comprehensive list of COVID testing and vaccine motivators and demotivators identified from both quantitative pre-test data (see for survey results) and qualitative focus group data. Motivators were conceptualised as reasons participants did or would get tested or vaccinated and how they would encourage PEH to get tested or vaccinated. Demotivators were conceptualised as reasons they did not or would not get tested or vaccinated. Per the socioecological model, these were organised into the individual level (knowledge, attitudes, beliefs and experience), interpersonal level (influences from individuals in social network) and structural level (organisational, environmental, political or cultural influences, such as rules, policies and information dissemination). Testing At the individual level, symptoms, exposure, wanting to know their results (eg, for peace of mind) and being in a high-risk setting such as a shelter were identified as motivators, ‘ Because with us being homeless I mean, we go in and out of public places all the time, and so we never know on whether or not we're going to be around somebody else that has it’—FG13 . Pain or fear of pain was a prominent discussion point in focus groups as an individual-level demotivator or undesirable aspect of testing, ‘ They aint gotta shove that thing all the way up your nose anymore either… A lot of people are scared because of that [P4: I was!] … That’s why I didn’t do it for a long time.’—P3, FG2 . Other individual-level demotivators included concerns about the accuracy of testing, faith/religion, not feeling the need to get tested, fear of results and at the interpersonal level, social isolation, ‘ I think most people don't get tested because they're scared of what they—[P5: they scared of the results]—and then they feel isolated and people avoid them’—P1, FG10, PSH . In terms of interpersonal-level motivators, many were motivated to test when someone in their social network suggests it (ie, friends, family, shelter staff or healthcare provider), and to protect others and prevent spread of the virus, ‘ I’m concerned about, you know, spreading it to other people, you know, giving it to kids and the elderly people. Concern of safety. [P5: I agree with that] [Participants agree].’—P4, FG4 . At the structural level, available and free testing (ie, at the shelter) was a motivator, ‘ But since it’s here, and it’s available, free… Let’s just get tested.’—P1, FG3 . In general, having rapid tests was preferred, because despite some concern about test accuracy, the pain experienced or feared by participants was specific to PCR tests. Having the option to take their own nasal swab was also a structural-level motivator, ‘ I’d rather do it myself than have… instead of have someone else does.’—P1, FG2, as some were uncomfortable with other people swabbing their nose, ‘ I don't like people touching on me um poking at me.’—P5, FG1 . Many who were tested did so because they were required or perceived it as a requirement (eg, by hospital, jail, or work), ‘ I had to do it to keep my job.’—P4, FG1 . While many did not believe testing should be mandatory, particularly by the shelter, it was generally viewed as an effective way to get people to test, including the suggestion for the shelter to ‘ Enforce the rules that we got’—P4, FG11 . In one focus group, participants suggested offering food or refreshments as an incentive to get guests to test, ‘ Offer them food [other participant: yeah, especially the homeless community] [Participants recommend coffee, donuts, hot chocolate, and apple cider]… Refreshments and stuff, so there’s always food like refreshments or something. Someone will weasel their way over there to see what that’s about.—Unknown Participant, FG7, PSH County health department-mandated lockdowns, which required the shelter to restrict access for individuals not exposed on the identification of a positive case at the shelter, were a noteworthy deterrent to testing. This was criticised by many participants as hindering PEH’s ability to obtain services, reminiscent of the challenges presented by the national lockdown, ‘ … maybe a negative is that anytime someone does test positive around here they issue a lockdown and then if someone hadn’t been here that day, if they hadn't been vaccinated or don't want to for religious preferences or whatever the reason being, um they're denied services until lockdown’s over and usually when one person tests positive more people end up testing positive.’—P2, FG12 . Other demotivators included faith/religion, and as one person suggested, ‘credibility of the test site’ and ‘testing personnel’. Having inadequate information dissemination was also mentioned, ‘ I never needed to [get tested] but to be honest with you, I didn't know you can get tested. No one ever told me that.’—P4, FG14 . This translated to the need for COVID-19 education dissemination at the shelter as a method to motivate and encourage testing among guests. Participants made several suggestions on topics and ways to disseminate education, such as emphasising the severity of COVID, highlighting the cost of testing and vaccination, and making more announcements at the shelter to get the word out, ‘ P1: Give them some general information like the knowledge you just told us… P3: Be informed about … cost… Let them know how many people have died. Then they might wanna go get a shot.—FG2’ Vaccination At the individual level, preventing severe illness or death and keeping oneself and others safe were important motivators for many participants, ‘ … it [the vaccine] reduces your chances of getting it [COVID] and reduces the like, if you do get it, it reduces your chances of getting like severely sick. And it also reduces your chances of spreading it.’—P3, FG3 . Focus group discussions (FGDs) revealed many misconceptions about vaccines that explain fear and mistrust of the vaccine as a demotivator, such as the belief that the vaccine was developed too quickly and that the vaccine contains a live virus, ‘ It’s just like the flu virus the flu—I don’t want that shot, why would you give me the flu to make me better? It’s just crazy.’—FG9 (PSH ). There was also scepticism on how much protection the vaccine could provide, given that COVID-19 infection is still possible , ‘You can still get corona; you can still get corona virus with the shot.’—FG7, PSH . Others reported religious beliefs, concern of vaccine side effects, belief that having COVID-19 was enough protection, and not being concerned about getting really sick from COVID-19 as demotivators. At the interpersonal level, while many reported keeping others safe as a motivator to getting vaccinated, some were motivated by a doctor’s suggestion, or as one person stated ‘peer pressure’. Hearsay from social networks created more misconceptions about the vaccine that served as demotivators, for example, that the vaccine is ‘part of government conspiracy and contains a tracking chip’, ‘ A lot of people won’t take the [vaccine] cause they think they put in a chip ya or you get tracked.’—P3, FG5 . Other hearsay shared were that vaccines ‘can give you COVID’, harming your health through ‘heart attacks, blood clots, all kinds of things’, and even cause death, ‘ Heard you get the shot, you die.’—P1, FG13 At the structural level, while providing free vaccines, receiving an incentive to be vaccinated and requiring vaccination (eg, by one’s workplace) were identified as motivators, misinformation about COVID and the safety of the vaccine contributed to uncertainty of getting vaccinated, ‘ … the clearer we are about you know, some of the information, that’s, that’s probably one of the biggest fights that’s been about this is, is misinformation and getting correct and reliable information has probably been one of the biggest things for most Americans.’—P3, FG
At the individual level, symptoms, exposure, wanting to know their results (eg, for peace of mind) and being in a high-risk setting such as a shelter were identified as motivators, ‘ Because with us being homeless I mean, we go in and out of public places all the time, and so we never know on whether or not we're going to be around somebody else that has it’—FG13 . Pain or fear of pain was a prominent discussion point in focus groups as an individual-level demotivator or undesirable aspect of testing, ‘ They aint gotta shove that thing all the way up your nose anymore either… A lot of people are scared because of that [P4: I was!] … That’s why I didn’t do it for a long time.’—P3, FG2 . Other individual-level demotivators included concerns about the accuracy of testing, faith/religion, not feeling the need to get tested, fear of results and at the interpersonal level, social isolation, ‘ I think most people don't get tested because they're scared of what they—[P5: they scared of the results]—and then they feel isolated and people avoid them’—P1, FG10, PSH . In terms of interpersonal-level motivators, many were motivated to test when someone in their social network suggests it (ie, friends, family, shelter staff or healthcare provider), and to protect others and prevent spread of the virus, ‘ I’m concerned about, you know, spreading it to other people, you know, giving it to kids and the elderly people. Concern of safety. [P5: I agree with that] [Participants agree].’—P4, FG4 . At the structural level, available and free testing (ie, at the shelter) was a motivator, ‘ But since it’s here, and it’s available, free… Let’s just get tested.’—P1, FG3 . In general, having rapid tests was preferred, because despite some concern about test accuracy, the pain experienced or feared by participants was specific to PCR tests. Having the option to take their own nasal swab was also a structural-level motivator, ‘ I’d rather do it myself than have… instead of have someone else does.’—P1, FG2, as some were uncomfortable with other people swabbing their nose, ‘ I don't like people touching on me um poking at me.’—P5, FG1 . Many who were tested did so because they were required or perceived it as a requirement (eg, by hospital, jail, or work), ‘ I had to do it to keep my job.’—P4, FG1 . While many did not believe testing should be mandatory, particularly by the shelter, it was generally viewed as an effective way to get people to test, including the suggestion for the shelter to ‘ Enforce the rules that we got’—P4, FG11 . In one focus group, participants suggested offering food or refreshments as an incentive to get guests to test, ‘ Offer them food [other participant: yeah, especially the homeless community] [Participants recommend coffee, donuts, hot chocolate, and apple cider]… Refreshments and stuff, so there’s always food like refreshments or something. Someone will weasel their way over there to see what that’s about.—Unknown Participant, FG7, PSH County health department-mandated lockdowns, which required the shelter to restrict access for individuals not exposed on the identification of a positive case at the shelter, were a noteworthy deterrent to testing. This was criticised by many participants as hindering PEH’s ability to obtain services, reminiscent of the challenges presented by the national lockdown, ‘ … maybe a negative is that anytime someone does test positive around here they issue a lockdown and then if someone hadn’t been here that day, if they hadn't been vaccinated or don't want to for religious preferences or whatever the reason being, um they're denied services until lockdown’s over and usually when one person tests positive more people end up testing positive.’—P2, FG12 . Other demotivators included faith/religion, and as one person suggested, ‘credibility of the test site’ and ‘testing personnel’. Having inadequate information dissemination was also mentioned, ‘ I never needed to [get tested] but to be honest with you, I didn't know you can get tested. No one ever told me that.’—P4, FG14 . This translated to the need for COVID-19 education dissemination at the shelter as a method to motivate and encourage testing among guests. Participants made several suggestions on topics and ways to disseminate education, such as emphasising the severity of COVID, highlighting the cost of testing and vaccination, and making more announcements at the shelter to get the word out, ‘ P1: Give them some general information like the knowledge you just told us… P3: Be informed about … cost… Let them know how many people have died. Then they might wanna go get a shot.—FG2’
At the individual level, preventing severe illness or death and keeping oneself and others safe were important motivators for many participants, ‘ … it [the vaccine] reduces your chances of getting it [COVID] and reduces the like, if you do get it, it reduces your chances of getting like severely sick. And it also reduces your chances of spreading it.’—P3, FG3 . Focus group discussions (FGDs) revealed many misconceptions about vaccines that explain fear and mistrust of the vaccine as a demotivator, such as the belief that the vaccine was developed too quickly and that the vaccine contains a live virus, ‘ It’s just like the flu virus the flu—I don’t want that shot, why would you give me the flu to make me better? It’s just crazy.’—FG9 (PSH ). There was also scepticism on how much protection the vaccine could provide, given that COVID-19 infection is still possible , ‘You can still get corona; you can still get corona virus with the shot.’—FG7, PSH . Others reported religious beliefs, concern of vaccine side effects, belief that having COVID-19 was enough protection, and not being concerned about getting really sick from COVID-19 as demotivators. At the interpersonal level, while many reported keeping others safe as a motivator to getting vaccinated, some were motivated by a doctor’s suggestion, or as one person stated ‘peer pressure’. Hearsay from social networks created more misconceptions about the vaccine that served as demotivators, for example, that the vaccine is ‘part of government conspiracy and contains a tracking chip’, ‘ A lot of people won’t take the [vaccine] cause they think they put in a chip ya or you get tracked.’—P3, FG5 . Other hearsay shared were that vaccines ‘can give you COVID’, harming your health through ‘heart attacks, blood clots, all kinds of things’, and even cause death, ‘ Heard you get the shot, you die.’—P1, FG13 At the structural level, while providing free vaccines, receiving an incentive to be vaccinated and requiring vaccination (eg, by one’s workplace) were identified as motivators, misinformation about COVID and the safety of the vaccine contributed to uncertainty of getting vaccinated, ‘ … the clearer we are about you know, some of the information, that’s, that’s probably one of the biggest fights that’s been about this is, is misinformation and getting correct and reliable information has probably been one of the biggest things for most Americans.’—P3, FG
The mean pre-test score was 10.76 out of 15 (SD=2.16), while the mean post-test score was 13.58 out of 15 (SD=1.72) (p<0.001). Most participants (n=71, 91%) improved by at least 1 and up to 10 points in their post-test scores. shows pre-/post-test knowledge scores per item, accompanied by qualitative insights shared during group sessions to provide additional context for the numerical scorings. The findings are categorised into three sections: high, moderate and low knowledge gains. High knowledge gains were observed for specific items, namely misconceptions about vaccine fertility (pre-test: 38%, post-test: 87%, p<0.001) and COVID-19 vaccines giving you the virus (pretest: 42%, post-test: 85%, p<0.001). There was a spectrum of viewpoints on both topics (see ), centred around the uncertainty of effects and ranging from complete belief in misconceptions to trust or knowledge of vaccine regulations and purpose. Knowledge gains and varying viewpoints were seen in the testing-related questions as well, including the cost of COVID-19 tests (pretest: 54%, post-test: 94%, p<0.001) with some participants unaware of free test access, the possibility to test negative but still have COVID-19 (pretest: 69%, post-test: 94%, p<0.001) and participants’ awareness of rapid testing options, asked as whether it is possible to have your results in 15 min (pretest: 73%, post-test: 97%, p<0.001). The supporting quotes in represent the scope of individuals existing knowledge and awareness of the testing topics, demonstrating, for example, how some participants understood the variation between the testing options by using result time, swab location/depth and accuracy as differentiation methods of rapid versus PCR (often representing PCR with comments like brain scraper, the one that touches your brain, etc). Participants displayed mixed feelings about the effectiveness of COVID-19 vaccines in the comments they shared, and topics such as protection against severe outcomes (pre-test: 60%, post-test 81%, p<0.001) and minimising the spread (pre-test: 77%, post-test: 91%, p<0.05) saw high to moderate knowledge gains. There was a general understanding that some degree of protection is offered through vaccination, with one participant stating they were upset when they discovered protection was not 100%. Other areas saw lower or no significant knowledge gains due to high pretest scores, however, the qualitative findings still provide important insights into these questions. For example, whether or not to get a COVID-19 vaccine if you’ve had COVID-19 before, participants generally knew that it is recommended to get it (pretest 81%, post-test 91%, p<0.05), but despite awareness, some didn’t necessarily agree with this recommendation by health agencies (‘THEY’ as depicted in ). Attitudes towards testing and vaccination were positively influenced postintervention. Of those not vaccinated (n=33), 21% were willing to get the vaccine initially, and this increased to 39% after the educational intervention, with ‘I don’t know’ responses decreasing from 39% to 18%. Participants’ willingness to get tested after exposure also increased from 83% to 92% after the session (see ).
During the FGDs, participants provided valuable feedback on their experience with this style of educational intervention, discussed their preferred information sources and expressed their interests in various topics beyond COVID-19. Participants mainly provided positive feedback and appreciation for the information shared in the groups, which they found to be informative and trustworthy coming from the CHW. In addition, one participant brought up that they not only benefited from what the CHW shared, but found value in a setting with an opportunity to learn from others, ‘ I haven't been keeping up on anything lately, and what that man said [other FGD participant] uh sort of informed me that there’s more on the way, testing, better testing and uh I like that…’—P4 . The participants also identified specific sources they trust when seeking information, including the news and the CDC. However, scepticism was expressed, and participants contributed concerns of misinformation to changing guidance delivered by health authorities, one stating, ‘ A lot of contrary information. When Fauci first came out, masks are not necessary, masks are not necessary. Now two masks. You know, it just changes every day. It’s ridiculous’—P6, FG8 . Others mentioned online media’s responsibility for the spread of misleading information, ‘ I think that was probably one of the biggest things that hurt this whole situation we're in, is social media and this the era we live in of cell phones and spread of just hearsay and misinformation is so bad nowadays is like wildflower .’ —P3, FG12 . Overall, participants highlighted the importance of trustworthy and credible sources in gaining accurate information and that they value information from community members and experts, such as local university professors in a relevant field of study, local community officials, including CHWs and health department employees. This expanded to people with lived experience or who work in close proximity to the topics they would educate, deeming them more trustworthy sources because they have ‘seen more’. Discussions also included nurses and medical doctors, however, some preferred community members stating ‘ Doctors- they don't explain stuff completely.’—P1, FG3 .
This study investigated the impact of CHW-delivered education for PEH in Indiana, aiming to address misinformation and promote COVID-19 testing and vaccination. Overall, considerable knowledge gains and positive attitude shifts were achieved, demonstrating the impact of CHW-led education on COVID-19-related knowledge, attitudes and beliefs. The blended focus group and education session garnered insights towards critical knowledge gaps, motivators, demotivators and barriers to COVID-19 testing and vaccination. Guided by the socioecological model, these insights further our understanding of the multilevel interactions influencing PEH access to and utilisation of testing and vaccination during the COVID-19 pandemic. This revealed key incentives as well as legitimate yet often mitigatable barriers including fear of pain from testing, inadequate dissemination of information and vaccine misinformation. In regard to testing, our findings align with other studies that found barriers such as cost, logistics and the impact of limited culturally sensitive messaging on health literacy to be codependent and compounding. Our previous study also identified that prior to testing being available at the shelter, participants’ confusion around testing costs in healthcare settings if uninsured led to not being tested. This study found that despite the mitigation of cost and other structural barriers by having testing available onsite at the shelter, critical knowledge gaps and lack of adequate information dissemination regarding free testing availability still presented barriers to uptake. The results of our intervention showed improved knowledge and attitudes towards testing, demonstrating the effectiveness of and highlighting the need for educational interventions, in addition to improving accessibility. A scoping review and meta-analysis of COVID-19 prevalence and vaccine hesitancy in the homeless population found that suspicion of adverse side effects and doubts over vaccine clinical trials were significant contributors to hesitancy, and emphasised factors like low health literacy as well. Our findings align with these concerns, as our FGDs revealed similar misconceptions about vaccines, such as fears regarding the speed of vaccine development and concerns or doubts about vaccine efficacy. Our intervention resulted in improved vaccination attitudes and knowledge, supporting the review’s suggestion for COVID-19 vaccine education among PEH. Additionally, our study also highlights the influence of misinformation from social networks as a barrier to vaccination acceptance. Though online media was identified as a source of information for PEH, our participants expressed a desire for better sources. They expressed interest and need for information that is consistent, accessible and diverse, and they want to be informed about their community by their community. This provides a key opportunity for public health to leverage interventions led by CHWs and other outreach professionals with shared lived experience and underscores the importance of future interventions that consider the crucial perspectives of PEH. Educational interventions remain an important method for promoting preventive health behaviours among PEH and are often called on as a recommendation for homeless shelters. However, these recommendations are often impractical for shelter staff to implement. Homeless shelters and other high-risk congregate settings are typically not well-resourced healthcare facilities that can simultaneously implement CDC guidelines such as testing while also upholding their essential mission of providing shelter and food to those in existing crises. Already limited, their ability to provide education and resources to inform and motivate individuals about available resources, such as COVID-19 testing and vaccination, is stretched. Even when staff at homeless shelters have the capacity to disseminate health information, our previous CBPR studies reported findings of PEH populations experiencing poor communication and discrimination with homeless shelter staff, pointing at other community assets like CHWs or the local health department to remediate health literacy barriers. The findings from our study align with existing literature in highlighting the effectiveness of CHWs in reaching populations excluded or met with barriers in accessing health information and resources during a pandemic by expanding on community relationships to build trust, establish knowledge, and address hesitancy and misinformation. One study used Community Health Outreach Workers to administer incentivised testing to unsheltered PEH and found that along with using mobile testing to improve accessibility, trusted community members can help overcome barriers to accessing and accepting COVID-19 testing and vaccines. This study also contributes important insights on CBPR as a valuable tool for centring the priorities and knowledge of communities in research efforts. CBPR can meaningfully inform appropriate educational interventions for PEH, including key content and delivery approaches. This study leveraged PEH and CHW relationships to understand, convey and tend to the unique challenges faced by this population during the COVID-19 pandemic. Combining an educational session with a qualitative focus group discussion led to a comprehensive understanding of the complex factors contributing to the COVID-19-related knowledge and practices of PEH. This style and its administration by CHWs allowed for real-time tailoring of educational material based on participant needs and was supported by the feedback collected from participants during sessions. There were several limitations of this study. First, it focuses on a specific PEH population in Lafayette, Indiana, and recruitment was limited to people using the engagement centre services. This may have led to the exclusion of unsheltered and unserved homeless populations, limiting the generalisability of our findings. Furthermore, participant knowledge gains and attitude shifts were only evaluated immediately following the intervention, limiting our understanding of whether these gains were sustained. Future work should target a larger, more diverse population of PEH, including people experiencing housing instability, and those who are unsheltered, as well as cover a longer period that includes follow-up with participants over time to measure the sustainability of the intervention’s impact. Future work should also examine the holistic impact of using and encouraging shelter-based COVID-19 rapid testing on the shelter environment.
10.1136/bmjopen-2024-087134 online supplemental file 1
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Single breast incision for breast conservation surgery and sentinel lymph node biopsy: a systematic review | 17e1d05b-8af1-4692-b4de-de5887b249d5 | 11874896 | Biopsy[mh] | Single‐incision breast conserving surgery (BCS) and sentinel lymph node biopsy (SLNB) allows for wide local excision of the tumour and access to both the axilla and internal mammary nodes via a single breast incision. It has previously been termed MABS (minimal access breast surgery) and TANE (transmammary axillary lymph node evaluation). The technique was first described in 1994 by Smellie et al . from the Royal Marsden Hospital, UK, during a period where there was a movement towards more aesthetically aware oncological choices with the use of Kraissl rather than Langer's lines as well as the start of oncoplastic breast surgical practice. The breast incision is chosen without compromising the best cosmetic and oncological outcomes for the breast. BCS is completed prior to SLNB. Access to the draining lymph node basin is achieved via mobilization along the chest wall between layers of the pectoral fascia using good assistance, adequate lighting and long, thin retractors (as depicted in Figure ). Once the lateral edge of pectoralis major is reached via the retromammary space, the clavipectoral fascia is opened to access the axillary nodes. Bromberg and Giordano use the assistance of an extra small Alexis wound retractor (Applied Alexis wound retractor, Applied Medical Resources Co., Rancho Santa Margarita, CA, USA) to make benefit of the ‘moving breast window’. This process is easier if the breast is larger, particularly if it is also ptotic but can often be achieve across a broad range of breast phenotypes. Objectives: This review consolidates the current literature on the efficacy, safety, functional and aesthetic outcomes of single‐incision breast conserving surgery and sentinel lymph node biopsy.
A comprehensive search of EMBASE, Medline, Pubmed, and GoogleScholar was conducted from inception to 7 July 2024 using PRISMA guidelines for peer‐reviewed articles assessing single‐incision BCS for the treatment of breast cancer and access to the axilla. This included studies that assessed oncoplastic techniques as part of BCS, as well as studies that included axillary dissection (AD) as well as SLNB. The references of the included articles were also reviewed to identify additional relevant publications. See Appendix for the full search strategy used and Figure for the PRISMA flow diagram. Studies were excluded if ‘minimal access breast surgery’ or ‘minimally invasive breast surgery’ referred to endoscopic‐assisted, or robot‐assisted breast surgery. Case reports and surgical ‘how I do it’ descriptive studies with no patient outcomes where were excluded. The outcomes assessed included the success rate for removal of sentinel nodes, the number of nodes harvested, patient and surgeon satisfaction, axillary pain, cosmesis, complication rate, oncological outcomes and surgical time.
The literature search generated 426 articles. Four hundred were excluded by abstract review with the remaining 26 articles reviewed in full. An additional three articles were retrieved from review of full article reference lists. Thirteen articles were excluded, leaving 10 articles meeting the inclusion criteria. Reasons for exclusion included ‘minimal access breast surgery’ referring to endoscopic‐assisted or robotic‐assisted techniques only, if no patient outcomes were reported or if the article was a case report. A total of 10 studies were identified that met the inclusion criteria. Four studies compared a single‐incision approach for BCS and SLNB or AC versus a conventional two‐incision technique. Three of these were retrospective , , and one of these was prospective. The remaining six studies were observational only with no comparison group. The number of patients, success of technique (axillary and internal mammary nodal basins), number of nodes removed, surgical time and complication rate are summarized in Table . Tumour location The distribution of tumour location is summarized in Table and Figure . Across all studies, 79.29% of tumours were located in the upper outer quadrant. In their axillary SLNB only group, Spillane and Brennan reported an overall success rate of 86%, but a 96% success rate if the tumour was in the upper outer quadrant or lateral, compared with 50% where the tumour was located medially, inferiorly or in the lower inner quadrant. Acea‐Nebril et al . had two of 154 patients that required conversion of the procedure to an additional axillary approach. For both these cases, the incision was from the inframammary fold for tumours in the upper inner quadrant. Nodal harvest The average number of dissected nodes was reported in eight studies with all studies reporting a mean or medial between 2 and 4 nodes. , , , , , , , Acea Nebril found no difference in number of sentinel lymph nodes excised between their single incision versus standard two incision groups (mean 2.14 ± 0.99 vs. 2.04 ± 1.09, P = 0.284), nor in the number of positive sentinel lymph nodes (0.35 ± 0.65 vs. 0.36 ± 0.75, P = 0686). AD via a single incision was assessed in eight studies. , , , , , , , All 17 patients who underwent AD in the case series by Mohsen et al . had tumours in the upper outer quadrant with incision in the lateral mammary fold. Spillane and Brennan reported nine patients who had AD via the breast incision. Seven tumours were in the upper outer quadrant, with one in the upper inner quadrant and one in the lower outer quadrant. The mean number of nodes dissected in 15 cases of AD via a separate incision was 13 (range 6–23) compared with 19.4 (range 8–31) in the single‐incision group. Of the nine AD performed in the study by Cocilovo et al . four patients required a separate axillary incision. The number of nodes removed via a single incision ranged from 5 to 17, versus 10 to 30 in the patients that required a separate incision to be made. Similarly, Bromberg et al . had a trend towards increased number of nodes excised in the two‐incision group (median 4, IQR: 1 to 13) compared with (median 2, IQR: 1 to 5) in their single‐incision arm although these results encompass a combination of both AD and SLNB with no further distinction or reporting of the percentage of AC patients in each arm. Dissection of the internal mammary nodes (IMN) via a single breast incision was only reported by Spillane and Brennan. Seventeen patients underwent BCS and axillary and internal mammary SLNB via the same incision and 13 patients had a single incision for BCS and internal mammary SLNB with a separate axillary incision for axillary SLNB. One patient required three separate incisions to safely access the breast and both lymph node groups, however, the presence of a breast prosthesis in this case was likely a confounding factor. This was the only patient in their study that required a parasternal incision to access the IMN. Cosmesis Cosmesis was not formally assessed by any study with a validated scoring system. For tumours in the upper outer quadrant, Mohsen et al . report excellent aesthetic outcomes in 80% of cases – rated by the patient and two surgeons with consideration of volume symmetry, shape of breast contour, symmetry of nipple‐areolar complex (NAC) position, ipsilateral scarring and post‐irradiation consequences. Nguyen‐Strauli et al . found increased axillary skin retraction in the two‐incision arm in their retrospective cohort series of 134 patients (6.3% vs. 0, P = 0.019). Patient satisfaction Acea‐Nebril assessed patient satisfaction with the Breast‐Q™ questionnaire and found that the single incision group had higher post‐operative satisfaction with both the breast (mean of 78.17 ± 15.97 vs. 66.65 ± 13.76, P = 0.002) and the information provided by the surgeon (85.32 ± 16.59 vs. 72.10 ± 20.99, P = 0.01). There was no difference found in other aspects of the Breast‐Q™ questionnaire including physical psychological or sexual wellbeing at 12–24 months post‐completion of adjuvant radiotherapy. Pain Nguyen‐Strauli et al . defined axillary neuralgia as pain in the armpit present at three or more months post‐operatively and found increased axillary neuralgia in their two‐incision arm (10.4% vs. 1.2%, P = 0.0139). Acea‐Nebril et al . also reported a trend towards increased axillary neuralgia in their two‐incision arm (5.41%) compared with their single‐incision arm (1.32%) although this did not reach statistical significance with their cohort of 226 patients. Surgical time Three studies found decreased surgical time with the single‐incision group including Lovasik et al . (median of 56 min (IQR 46.5, 73.3) vs. 64 min (IQR 54.5, 75.5), p 0.026), Nguyen‐Strauli et al . (mean of 91 min ± 33 vs. 113 min ± 37 P < 0.001) and Bromberg et al . (median 130 min (range 30–220) vs. 180 min (range 50–275)). The extended surgical times reported by Bromberg et al . are likely as a result of the additional use of intra‐operative radiotherapy as well as frozen section in their patients. Conversely, Acea‐Nebril et al . found that the single‐incision group had longer surgical time (88.54 ± 49.35 min vs. 69.93 ± 38.43, P = 0.017). However, when divided into lumpectomy versus use of oncoplastic technique (41% of cases in the single‐incision arm vs. 18% in the two‐incision arm), no difference in time was found. We also note that the patients who had level two oncoplastic techniques performed in this study also had symmetrisation performed on the contralateral breast and this was included in the surgical time. Complication rate The most common complications reported in the majority of studies included breast haematoma, seroma, wound infection or dehiscence, skin retraction and nipple necrosis. No statistically significant difference in complication rate was demonstrated in any of the comparative studies between a single‐incision versus conventional two‐incision. , , While not statistically significant, Nguyen‐Strauli et al . reported a trend towards a difference in location of seroma between the two groups, with the single‐incision group having more breast seromas (7% vs. 0%) whereas the two incision group had more axillary seromas (8% vs. 1%). Acea‐Nebril et al . also assessed lymphoedema rates and found no difference between the two groups (2.70 vs. 2.63% P = 0.208). Oncological safety Bromberg et al . assessed margins and local recurrence – they reported adequate margins with no need for reoperation or recurrence in either arm, although their cohort was small (60 patients in total), with a median follow‐up time of only 7.5 months (range 1–16 months). This was despite a decreased excision volume in the single incision arm (16.3 (2–90) vs. 42.4 (5–270)). None of the studies reported long‐term oncological data.
The distribution of tumour location is summarized in Table and Figure . Across all studies, 79.29% of tumours were located in the upper outer quadrant. In their axillary SLNB only group, Spillane and Brennan reported an overall success rate of 86%, but a 96% success rate if the tumour was in the upper outer quadrant or lateral, compared with 50% where the tumour was located medially, inferiorly or in the lower inner quadrant. Acea‐Nebril et al . had two of 154 patients that required conversion of the procedure to an additional axillary approach. For both these cases, the incision was from the inframammary fold for tumours in the upper inner quadrant.
The average number of dissected nodes was reported in eight studies with all studies reporting a mean or medial between 2 and 4 nodes. , , , , , , , Acea Nebril found no difference in number of sentinel lymph nodes excised between their single incision versus standard two incision groups (mean 2.14 ± 0.99 vs. 2.04 ± 1.09, P = 0.284), nor in the number of positive sentinel lymph nodes (0.35 ± 0.65 vs. 0.36 ± 0.75, P = 0686). AD via a single incision was assessed in eight studies. , , , , , , , All 17 patients who underwent AD in the case series by Mohsen et al . had tumours in the upper outer quadrant with incision in the lateral mammary fold. Spillane and Brennan reported nine patients who had AD via the breast incision. Seven tumours were in the upper outer quadrant, with one in the upper inner quadrant and one in the lower outer quadrant. The mean number of nodes dissected in 15 cases of AD via a separate incision was 13 (range 6–23) compared with 19.4 (range 8–31) in the single‐incision group. Of the nine AD performed in the study by Cocilovo et al . four patients required a separate axillary incision. The number of nodes removed via a single incision ranged from 5 to 17, versus 10 to 30 in the patients that required a separate incision to be made. Similarly, Bromberg et al . had a trend towards increased number of nodes excised in the two‐incision group (median 4, IQR: 1 to 13) compared with (median 2, IQR: 1 to 5) in their single‐incision arm although these results encompass a combination of both AD and SLNB with no further distinction or reporting of the percentage of AC patients in each arm. Dissection of the internal mammary nodes (IMN) via a single breast incision was only reported by Spillane and Brennan. Seventeen patients underwent BCS and axillary and internal mammary SLNB via the same incision and 13 patients had a single incision for BCS and internal mammary SLNB with a separate axillary incision for axillary SLNB. One patient required three separate incisions to safely access the breast and both lymph node groups, however, the presence of a breast prosthesis in this case was likely a confounding factor. This was the only patient in their study that required a parasternal incision to access the IMN.
Cosmesis was not formally assessed by any study with a validated scoring system. For tumours in the upper outer quadrant, Mohsen et al . report excellent aesthetic outcomes in 80% of cases – rated by the patient and two surgeons with consideration of volume symmetry, shape of breast contour, symmetry of nipple‐areolar complex (NAC) position, ipsilateral scarring and post‐irradiation consequences. Nguyen‐Strauli et al . found increased axillary skin retraction in the two‐incision arm in their retrospective cohort series of 134 patients (6.3% vs. 0, P = 0.019).
Acea‐Nebril assessed patient satisfaction with the Breast‐Q™ questionnaire and found that the single incision group had higher post‐operative satisfaction with both the breast (mean of 78.17 ± 15.97 vs. 66.65 ± 13.76, P = 0.002) and the information provided by the surgeon (85.32 ± 16.59 vs. 72.10 ± 20.99, P = 0.01). There was no difference found in other aspects of the Breast‐Q™ questionnaire including physical psychological or sexual wellbeing at 12–24 months post‐completion of adjuvant radiotherapy.
Nguyen‐Strauli et al . defined axillary neuralgia as pain in the armpit present at three or more months post‐operatively and found increased axillary neuralgia in their two‐incision arm (10.4% vs. 1.2%, P = 0.0139). Acea‐Nebril et al . also reported a trend towards increased axillary neuralgia in their two‐incision arm (5.41%) compared with their single‐incision arm (1.32%) although this did not reach statistical significance with their cohort of 226 patients.
Three studies found decreased surgical time with the single‐incision group including Lovasik et al . (median of 56 min (IQR 46.5, 73.3) vs. 64 min (IQR 54.5, 75.5), p 0.026), Nguyen‐Strauli et al . (mean of 91 min ± 33 vs. 113 min ± 37 P < 0.001) and Bromberg et al . (median 130 min (range 30–220) vs. 180 min (range 50–275)). The extended surgical times reported by Bromberg et al . are likely as a result of the additional use of intra‐operative radiotherapy as well as frozen section in their patients. Conversely, Acea‐Nebril et al . found that the single‐incision group had longer surgical time (88.54 ± 49.35 min vs. 69.93 ± 38.43, P = 0.017). However, when divided into lumpectomy versus use of oncoplastic technique (41% of cases in the single‐incision arm vs. 18% in the two‐incision arm), no difference in time was found. We also note that the patients who had level two oncoplastic techniques performed in this study also had symmetrisation performed on the contralateral breast and this was included in the surgical time.
The most common complications reported in the majority of studies included breast haematoma, seroma, wound infection or dehiscence, skin retraction and nipple necrosis. No statistically significant difference in complication rate was demonstrated in any of the comparative studies between a single‐incision versus conventional two‐incision. , , While not statistically significant, Nguyen‐Strauli et al . reported a trend towards a difference in location of seroma between the two groups, with the single‐incision group having more breast seromas (7% vs. 0%) whereas the two incision group had more axillary seromas (8% vs. 1%). Acea‐Nebril et al . also assessed lymphoedema rates and found no difference between the two groups (2.70 vs. 2.63% P = 0.208).
Bromberg et al . assessed margins and local recurrence – they reported adequate margins with no need for reoperation or recurrence in either arm, although their cohort was small (60 patients in total), with a median follow‐up time of only 7.5 months (range 1–16 months). This was despite a decreased excision volume in the single incision arm (16.3 (2–90) vs. 42.4 (5–270)). None of the studies reported long‐term oncological data.
This review has summarized the efficacy and safety of the current published literature regarding single‐incision BCS and SLNB. Whilst cosmesis was only formally reported by a single study, the aesthetic benefits of a single‐incision technique are inherently evident. Not only does it avoid the additional scar, but the retromammary dissection allows for better glandular approximation to provide excellent cosmetic outcomes in both breast contour and skin. This is supported by increased patient satisfaction formally assessed by Acea‐Nebril et al . in their Breast‐Q™ questionnaire although it should be noted that their results may be confounded by the high proportion of patients who underwent level I and II oncoplastic procedures (compared with lumpectomy alone) in the single‐incision group. Hypertrophic scarring of the axilla following SLNB or AD has been reported in the literature to be 17%. , Obviously a single‐incision technique negates this which may be of particular importance for patients of Black and Asian ethnicity, who have been reported to have up to 20 times the rates of keloid scarring. , Additionally, this technique avoids a medial chest wall scar in the cleavage triangle during IMN dissection, a location prone to keloid scarring. Scar pain following axillary surgery has been reported to be 3.7% (SLNB) and 13.7% (AD) which may be mitigated by avoiding an additional axillary skin incision. , This was corroborated by Nguyen‐Strauli et al . where patients reported axillary pain at 1.2% with a single‐incision technique compared to 10.4% with two incisions ( P = 0.01) at three or more months follow‐up post‐operatively. While technically the axilla is most accessible via incisions designed for tumours in the upper outer quadrant, use of a single incision has been demonstrated to be feasible in tumours of all areas of the breast accessed from a wide range of incisions, including both level one and two oncoplastic techniques. , , , , , , , As outlined in all the studies describing the technique in detail, appropriate case selection, use of retromammary plane for dissection, with long retractors, appropriate lighting and utilizing the ‘moving breast window’ is critical to success. , , The technique should not compromise the best oncological and cosmetic breast incision. While it can be considered for all breast cancers, each case should be carefully assessed so as not to compromise the safety and accuracy of the sentinel lymph node procedure with oncological principles as the primary priority. Considerations should include the presence of implants, medial tumours, small dense breasts with no ptosis and pectus excavatum, all of which were reasons for the failure of this technique. , While none of the studies have had sufficient sample size or follow‐up to adequately assess lymphoedema, Nguyen‐Strauli et al . reported two (4.2%) incidences of lymphoedema in their two‐incision arm compared with no cases for the single incision arm P = 0.056. It is postulated that leaving the skin intact in the axilla would spare a small number of dermal lymphatics as well as facilitate early mobilization with decreased pain. Whether a true difference in lymphoedema rates between the two approaches remains unanswered. The average sentinel nodal harvest of 2–4 among all studies included in this review is comparable with most large trials which average between 2 and 3 nodes harvested. However, despite an equivalent nodal harvest and margin rate, the current body of literature lacks sufficient data on the oncological outcomes of this technique. Comprehensive, larger‐scale comparative studies with longer‐term follow‐up is necessary to confirm oncological non‐inferiority. Nevertheless, the single‐incision technique has been demonstrated in the literature to be a surgically safe, efficient and cosmetically advantageous approach with improved axillary pain and patient satisfaction.
WLE and SLNB through a single incision is a surgically safe and feasible procedure. In appropriately selected cases it can be considered in all quadrants of the breast with superior cosmetic outcomes, decreased pain and improved patient satisfaction. Further research and long‐term follow‐up studies are needed to consolidate these findings and confirm oncological safety.
Andrew J. Spillane is an Editorial Board member of ANZ Journal of Surgery and a co‐author of this article. To minimize bias, they were excluded from all editorial decision‐making related to the acceptance of this article for publication. Otherwise, Lucy P. Aitchison and Andrew J. Spillane have no conflicts of interest or financial arrangements to disclose.
Lucy P. Aitchison: Data curation; formal analysis; investigation; methodology; writing – original draft; writing – review and editing. Andrew J. Spillane: Conceptualization; supervision; writing – review and editing.
Data S1 Supporting information.
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Endocrine-exocrine | 49fd26de-487e-4e6e-9ed1-a3f2bf8010d4 | 11914046 | Digestive System[mh] | Pancreatitis is one of the most common causes of hospitalization worldwide and represents higher prevalence in the elderly – . Chronic inflammation accumulates during natural aging and has been identified as responsible for the onset of many diseases, including pancreatitis and type 2 diabetes mellitus (T2DM) . Recent clinical data showed that the incidence of pancreatitis increases in patients with T2DM – , indicating the endocrine part of the pancreas participants in pancreatitis formation. However, the underlined mechanisms remain elusive. The endocrine pancreatic islets have a well-recognized anatomical and physiological integration with the exocrine pancreas and regulate its function . Involvement of the islet-acinar axis (IAA) has been suggested in the islet-acinar portal system for the physiological regulation of acinar cell function by islet peptides , . A recent study found that islet β-cell-derived cholecystokinin (CCK) acts on acinar cells via the IAA to promote the progression of pancreatic ductal adenocarcinoma (PDAC) , suggesting that endocrine islet β-cells can crosstalk with acinar cells. In addition, β-cell inflammation exacerbates pancreatitis through chemokine signaling , . These findings suggest that factors secreted abnormally by pancreatic β-cells play a key role in the development of pancreatitis. One possibility is that abnormal secretion of microRNAs (miRNAs) may be involved. Pancreatic β-cells are known to mediate intercellular communication through the secretion of extracellular vesicles (EVs) rich in miRNAs, resulting in reduced insulin sensitivity and secretion capacity in a paracrine or distal manner and elevated blood glucose levels . However, a regulatory role for miRNAs carried by EVs derived from β-cells has not been established for pancreatitis. We have previously demonstrated that senescent β-cells released miR-503-322 as small EVs (~45 nm) which were transported into peripheral target organs to cause insulin resistance, thereby leading to the onset of T2DM . Serendipitously, overexpression of miR-503 in β cells caused pancreatitis-like changes with age, suggesting that miR-503 secreted by endocrine β-cells may be important in regulating exocrine functions including pancreatitis. The X-linked miR-503 , clustered with miR-322 has been investigated and shown to play an important role in modulating cell proliferation, cell differentiation, and tissue remodeling . In the present study, we found that during natural aging, primary miR-503-322 ( Pri-miR-503 ) was transcribed in the endocrine islets while mature miR-503 and miR-322 could be detected in both endocrine and exocrine pancreas. Increased levels of miR-503-322 in senescent acinar cells were derived from β-cells and intra-acinar miR-503-322 promoted pancreatitis by targeting MAP kinase-interacting kinases (MKNK1). The regulation mode was also conserved in aged population, adding further evidence for endocrine-exocrine crosstalk in regulating pancreatitis and providing therapeutic targets for the prevention and treatment of aging-associated pancreatitis.
Senescent β-cell-derived miR-503-322 promoted pancreatitis in mice Our previous study showed that β-cell-specific miR-503 transgenic (βTG) mice suffered from insulin resistance and β-cell dysfunction, leading to T2DM . Coincidentally, we noted that the βTG mice also showed chronic pancreatitis (CP)-like changes with advanced age, including diffuse expansion of the interlobar septae, fat accumulation, and fibrosis (Fig. ). Adult βTG mice also showed significant exacerbation of caerulein-induced AP attack, as evidenced by pancreatic edema, macrophage infiltration, and more severe histologic scorings compared with the WT mice (Fig. ). To understand the role of β-cell miR-503 on the development of pancreatitis, the expressing distribution of miR-503 in βTG mice was detected. We found that Pri-miR-503 was significantly increased in islets but not in acini, while the mature miR-503 was increased in both islets and acini (Fig. ), suggesting β-cell miR-503 entering acinar cells. The same expression profiles of Pri-miR-503 and mature miR-503 and miR-322 were also observed in aged mice (Fig. ). We previously reported that senescent β-cells secrete miR-503-322 within EVs . To validate our findings, we measured miR-503 and miR-322 (namely miR-424 in humans) levels in EVs from a 69-year-old human islet donor after senescent cell removal using senolytics ABT263 (Fig. ). Previous studies have shown that senescent β-cells can be specifically killed in vitro with ABT263 . A 48-hour treatment with ABT263 reduced β-galactosidase-positive cells and p16INK4a fluorescence in insulin-positive β-cells, and consequently, the secretion of miR-503-424 in EVs was diminished (Fig. ). These results make us think about the contribution of β-cell miR-503-322 to pancreatitis in older age. Consistent with our hypothesis, aged mice showed a more severe form of caerulein-induced AP compared to younger mice (Fig. ), which could be significantly improved by blocking β-cell miR-503-322 levels. An insulin 2 promoter-driven sponge-AAV (SP-AAV) specifically expressed in β cells resulted in decreased expression levels of miR-503-322 in pancreas (Fig. ). Meanwhile, caerulein-induced AP measured by serum amylase and lipase levels, pancreatic edema, histologic scorings were significantly ameliorated in aged mice infected with SP-AAV (Fig. ). These findings indicate that increased levels of miR-503-322 in senescent β cells contribute pancreatitis severity associated with older age. β cell secreted small extracellular vesicles containing miR-503-322 to enter acinar cells We previously verified that islet-derived EVs were secreted from insulin granules and were trafficked into liver and adipose tissues via circulation . Whether those EVs entered acinar cells was unknown. Here, we show that acinar cells indiscriminately engulfed EVs in vitro models (Fig. ), and acinar cells that received EVs purified from βTG islets had significantly greater levels of miR-503 than acinar cells that received EVs from wildtype (WT) islets (Fig. ). To validate the specificity of β-cells, we used the cell-permeable zinc-selective dye FluoZin TM -3, which selectively sorts pancreatic β-cells without compromising their viability or function , enabling enrichment of β-cell-derived EVs (βEVs) (Fig. ). Transmission electron microscopy (TEM) revealed βEVs with a diameter of about 45 nm (Fig. ), and nanoparticle tracking analysis (NTA) confirmed size of 42 nm (Fig. ). Western blotting confirmed high expression of EV markers (ALIX, TSG101, and CD63), but not GAPDH which was not included in EVs (Fig. ). Although the concentration was not different, βEVs released from βTG were found to package more miR-503 than those from WT β-cells (Fig. ). The in vitro uptake of βEVs by acinar cells and flow cytometry data showed that acinar cells can internalize βEVs with no significant difference in uptake efficiency (Figs. and ). Whereas the level of miR-503 in acinar cells receiving βTG-βEVs was significantly higher than those receiving WT-βEVs (Fig. ). We also injected labeled islet-derived EVs into mice via pancreatic ductal infusion and observed that acinar cells indiscriminately engulfed EVs in vivo (Fig. ). To avoid the influence of insulin resistance and hyperglycemia in βTG mice , we constructed RIP2-cre; miR-503-322 KI (βKI) mice which were not overtly diabetic (Fig. ). βKI mice also exhibited an exacerbation of caerulein-induced AP compared to littermate controls (Fig. ). Thus, we concluded that β-cell-derived small EVs enter acinar cells and drive pancreatitis at a miR-503-322 –dependent manner in mice. Elevation of miR-503-322 in acinar cells triggers both acute and CP Next, we sought to investigate the effects of miR-503-322 under inducible global elevation conditions by using CAG-creER; miR-503-322 KI (CKI). After tamoxifen induction three times, Pri-miR-503 expression levels were significantly elevated in the pancreas, skeletal muscle and other metabolic tissues (Fig. ). Surprisingly, CKI mice started to lose weight and activity, culminating in death due to severe AP within 6 days of the first induction, as observed by significantly increased serum amylase and lipase levels, abdominal infiltration of neutrophils and macrophages, and pancreatic saponification, necrosis and histological analysis (Fig. ). However, no concomitant histological changes were observed in other major abdominal organs (Fig. ). Severe AP-induced systemic inflammatory responses were shown by inverted serum ratios of neutrophils and lymphocytes, and elevated serum levels of C-reactive protein (Fig. ). These results validate that the global overexpression of miR-503-322 promotes severe AP, indicating the specificity of the miR-503-322 for pancreas damage. To rule out the contribution of other tissues, Pdx1-cre; miR-503-322 KI (heterozygous PKI/WT and homozygous PKI/KI) mice were used to yield high pancreatic-specific expression of miR-503-322 . The pancreatic Pri-miR-503 expression was increased in the heterozygous PKI mice (PKI/WT) compared to WT controls and was further increased in the homozygous mice (PKI/KI) (Fig. ). The PKI/KI mice showed an unexpected weight loss at ~6 weeks of age, while the PKI/WT mice showed no change during natural growth (Figs. and ). The most prominent features of CP, including pancreatic atrophy, fibrosis, tubular complexes, and inflammatory infiltration were observed in PKI/WT mice, with more severe CP and gross changes in the homozygous PKI/KI mice (Figs. and ). Accordingly, PKI/KI mice could not survive for 12 weeks (Fig. ). PDX1 is a master regulator in pancreas organogenesis while the maturation and identity preservation of islet β-cells and δ-cells , . To avoid development defect, inducible acini-specific miR-503-322 ( Elastase- CreER; miR-503-322 KI, EKI) mice were also constructed, and overexpression verified post-induction for 3 days (Fig. ). After tamoxifen injection, the EKI mice showed significantly increased indicators of AP, including macrophage infiltration, tissue damage, and necrosis (Figs. and ), and had a 50% mortality rate (Fig. ). Those mice that survived developed histology of CP one month post-induction, manifested as pancreatic atrophy (Fig. ), fibrosis, fat replacement, and acinar-to-ductal metaplasia (ADM, Fig. ), while a return to normal levels of serum amylase and lipase (Fig. ). As shown in Fig. , EKI female mice presented an AP phenotype similar to that of male mice 5 days after tamoxifen induction. The above findings demonstrate that global, pancreatic, and acinar cell-specific overexpression of miR-503-322 can directly trigger (severe) acute and CP in a dose- and tissue-dependent manner. MiR-503-322 knockout alleviated caerulein-induced acute pancreatitis The possibility that ablation of miR-503-322 could alleviate AP was investigated by the global deletion of miR-503-322 (KO) (Fig. ). The KO mice were viable and fertile, with normal body weight (Fig. ). Histology of the pancreas revealed normal pancreatic morphology (Fig. ). Challenging the KO and WT mice with caerulein or PBS and assessing for AP severity revealed markedly lower pancreatic edema and amylase and lipase levels in the KO group (Fig. ). Histological examination revealed reduced pancreatic acinar cell damage, less interstitial expansion (indication of edema), and diminished macrophage infiltration in KO mice during the acute AP phase (Fig. ). To highlight the influence of aging on pancreatitis, 1-year-old KO mice were treated with caerulein. The findings revealed that KO mice experienced a significant alleviation of caerulein-induced AP compared to control mice (Fig. ). Together, these data demonstrate that the deletion of miR-503-322 can significantly alleviate caerulein-induced AP. MiR-503-322 promotes pancreatitis by inhibiting zymogen secretion and acinar cell proliferation Next, we sought to identify the mechanisms by which miR-503-322 promotes the development of pancreatitis. TEM images from the pancreas of the PKI/WT mice revealed an increased number of zymogen granules (Fig. ). However, the significantly lower transcript levels of pancreatic enzyme-related genes implied that this did not represent an increased production of zymogen in the acinar cells (Fig. ) but was possibly an indication of a secretion defect. Therefore, we isolated acini and assessed their secretory ability in response to caerulein. The amylase release was significantly lower from the PKI cells than from the WT cells (Fig. ). The acinar cells from aged mice showed a similar response to that of the PKI cells, with a reduced secretion of pancreatic enzymes (Fig. ), in agreement with the results of previous studies . By contrast, the primary acinar cells from the KO mice showed enhanced amylase secretion (Fig. ). The defect of enzyme secretion was attributed to the loss of cytoskeleton modulation from tip to basolateral membranes of acinar cells responding to caerulein (Fig. ). Enzyme secretion defects may cause trypsinogen activation. We observed that trypsinogen activation in acini was visualized by using rhodamine 110 (BZiPAR) which revealed a clear enrichment of green fluorescence in PKI cells (Fig. ), and serum trypsin activity was enhanced in the PKI mice (Fig. ). These findings indicate that miR-503-322 inhibits pancreatic enzyme secretion and promotes the intracellular accumulation of zymogen. Subsequent zymogen activation in situ may promote pancreas damage of miR-503-322 elevated mice. Activation of trypsinogen by lysosomal enzymes after fusion of the lysosome is the classical mode of pancreatic enzyme activation during AP , . TEM images of the pancreas from PKI mice show morphological signs of this activation, including numerous autophagy vacuoles in the cytoplasm and abundant zymogen granules varying in size and electron density and sometimes fused together to form irregular “lakes” (Fig. ). These phenomena suggest a classical activation of intracellular zymogen in the lysosomes of acinar cells that highly express miR-503-322 . We verified this by inducing pancreatitis in WT and EKI mice by administration of chloroquine, which destroys the acidic environment in autophagic lysosomes (Fig. ). The AP phenotype was alleviated in EKI mice treated with chloroquine, as evidenced by a smaller weight loss, reduced serum amylase and lipase levels, and less tissue damage compared to saline-treated control mice, despite a similar pancreas weight (Fig. ). AP significantly stimulates the proliferation of acinar cells almost immediately at the point of injury . Not surprisingly, immunofluorescence staining for PCNA revealed a reduction in the numbers of proliferating acinar cells in the mice expressing high levels of the miR-503-322 , and an increased proliferation of mesenchymal cells (Fig. ). Conversely, ablation of miR-503-322 enhanced acinar cell proliferation during the repair phase of caerulein-induced AP (Fig. ). We also conducted a similar test in aged mice and again observed a significant decrease in acinar cell proliferation similar to that seen in the high miR-503-322 expression model mice (Fig. ). Taken together, these data suggest that miR-503-322 suppresses zymogen secretion to initiate acute pancreatitis. Meanwhile, miR-503-322 also inhibits the regenerative proliferation of acinar cells to promote the formation of CP. MKNK1 is a target of miR-503-322 and acinar cell-specific restoration of it reverses the phenotype of pancreatitis in mice We previously used unbiased proteomics to identify target genes of miR-503 in regulating peripheral insulin resistance and β-cell dysfunction . By analyzing the same proteomics data combined with Targetscan software analysis, five genes (MKNK1, CCNE1, IGF1R, PI3KR1 and INSR) were potential targets (Fig. ). After extensively searching and reading literature, we found that the MKNK1, mostly expressed in the exocrine pancreas might contribute to miR-503-322 –caused pancreatitis. MKNK1 plays an indispensable role in physiological exocrine secretory response . Consistent with published data, phosphorylation of MKNK1 and its downstream eIF4E was increased 4 hr after the first caerulein injection and gradually recovered (Fig. ). MKNK1 was redistributed to the basolateral region after caerulein administration, assisting acinar cell secretion (Fig. ). Previous studies showed that ablation of MKNK1 results in exacerbation of pancreatitis caused by caerulein due to defects of zymogen secretion and acinar cell proliferative in mice , making us pursue the role of MKNK1 as a target gene of miR-503-322 . Our proteomics analysis showed a decrease in MKNK1 after miR-503 elevation. Dual-luciferase assay confirmed the regulatory role of miR-503-322 on the 3’UTR of Mknk1 gene (Figs. and B). Next, immunohistochemistry staining of pancreas sections revealed clear suppression of MKNK1 protein amount in the three miR-503-322 overexpressing mouse model. (Fig. ), while upregulation of MKNK1 was induced by caerulein in KO mice (Fig. ). The protein levels of MKNK1 and its associated P-MKNK1/P-eIF4E signaling were significantly reduced in the pancreas of miR-503-322 overexpressing model mice and aged mice, and by contrast increased in pancreas of miR-503-322 knockout mice and aged mice with β-cell-specific blocking miR-503-322 (Figs. and ). Taken together, these findings suggest that miR-503-322 targets MKNK1-eIF4E pathway to inhibit zymogen secretion and acinar cell proliferation, thereby leading to acute and CP. Next, we tested whether reconstitution of MKNK1 in pancreas could reverse pancreatitis of EKI mice following the schematic diagram (Fig. ). We generated an AAV, serotype pancreas (MKNK1-AAV) that directs specific MKNK1 overexpression in the exocrine pancreas. As shown in Fig. , MKNK1 was highly expressed in the acini, but not in the islets of MKNK1-AAV mice. Restoration of MKNK1 also rescued the miR-503-322 -suppressive protein levels of phos-MKNK1 and phos-eIF4E in the EKI pancreas (Fig. ). Consequently, MKNK1-AAV-infected EKI mice showed lessened AP phenotypes compared to Ctr-AAV-infected EKI mice. In detail, the loss of body weight, increased serum levels of amylase and lipase, increased number of macrophage infiltration, and tissue damage in Ctr-AAV infected EKI mice were largely reduced in MKNK1-AAV infected EKI mice (Fig. ). On the other hand, inhibition of MKNK1 by a verified inhibitor, CGP 57380 further exacerbated caerulein-caused AP phenotypes, and totally erased miR-503-322 knockout driven protective effects (Fig. ). These results from acinar cell MKNK1 reconstitution and specific MKNK1 inhibitor support our view that the deficiency of MKNK1 in acini is primarily responsible for the pancreatitis observed in miR-503-322 elevated mice. Evidence of miR-503 and MKNK1 in aging-associated pancreatitis changes in the Chinese population As the expression of miR-503 is specifically increased in senescent β cells in mice, we also considered its change in humans. Pancreas sections from elderly adults (EA) showed CP-like changes, including atrophy of the acinar cells, interstitial expansion, and a marked increase in fibrosis (Fig. ), as well as a significant reduction in the proportion of proliferating acinar cells (Fig. ), compared to that from young adults (YA). Intriguingly, miRNA in situ hybridization showed greater expression of miR-503 in islets than in acini in pancreatic sections from EA group (Fig. ), whereas expression of miR-503 was almost undetectable in YA group (Fig. ). The expression of MKNK1 was significantly downregulated in the acini from the EA pancreas compared to that from the YA pancreas (Fig. ). Moreover, the co-localization of MKNK1 and AMY1 in the young acini was dislocated in the elderly acini (Fig. ), indicating activation of MKNK1 in the EA. Thus, the increased level of miR-503 in the acini may come from the islet β cells and contribute to the decreased but activated MKNK1 protein in the elderly Chinese population. Numerous studies have reported that exocrine pancreas function is impaired in both healthy and diabetic older adults independent of gastrointestinal disease, judged by serum levels of amylase and maximum bicarbonate concentration , . Consistently, we observed a significantly decreased level of serum amylase in the EA with T2DM (EA + DM) compared to that in YA, moreover, the EAs also showed a decreased amylase level (Fig. ). Further analysis showed that serum concentration of miR-503 in EVs was elevated in the elderly compared to that in the YAs and was further elevated in the EA + DM (Fig. ). The human subjects displayed negative associations of serum amylase levels with both age and serum concentrations of miR-503 in EVs (Fig. ). These results support the pancreatic exocrine insufficiency in elderly and diabetic patients and point out serum concentrations of miR-503 in EVs as a molecular marker of ageing-associated pancreatitis in the Chinese population.
miR-503-322 promoted pancreatitis in mice Our previous study showed that β-cell-specific miR-503 transgenic (βTG) mice suffered from insulin resistance and β-cell dysfunction, leading to T2DM . Coincidentally, we noted that the βTG mice also showed chronic pancreatitis (CP)-like changes with advanced age, including diffuse expansion of the interlobar septae, fat accumulation, and fibrosis (Fig. ). Adult βTG mice also showed significant exacerbation of caerulein-induced AP attack, as evidenced by pancreatic edema, macrophage infiltration, and more severe histologic scorings compared with the WT mice (Fig. ). To understand the role of β-cell miR-503 on the development of pancreatitis, the expressing distribution of miR-503 in βTG mice was detected. We found that Pri-miR-503 was significantly increased in islets but not in acini, while the mature miR-503 was increased in both islets and acini (Fig. ), suggesting β-cell miR-503 entering acinar cells. The same expression profiles of Pri-miR-503 and mature miR-503 and miR-322 were also observed in aged mice (Fig. ). We previously reported that senescent β-cells secrete miR-503-322 within EVs . To validate our findings, we measured miR-503 and miR-322 (namely miR-424 in humans) levels in EVs from a 69-year-old human islet donor after senescent cell removal using senolytics ABT263 (Fig. ). Previous studies have shown that senescent β-cells can be specifically killed in vitro with ABT263 . A 48-hour treatment with ABT263 reduced β-galactosidase-positive cells and p16INK4a fluorescence in insulin-positive β-cells, and consequently, the secretion of miR-503-424 in EVs was diminished (Fig. ). These results make us think about the contribution of β-cell miR-503-322 to pancreatitis in older age. Consistent with our hypothesis, aged mice showed a more severe form of caerulein-induced AP compared to younger mice (Fig. ), which could be significantly improved by blocking β-cell miR-503-322 levels. An insulin 2 promoter-driven sponge-AAV (SP-AAV) specifically expressed in β cells resulted in decreased expression levels of miR-503-322 in pancreas (Fig. ). Meanwhile, caerulein-induced AP measured by serum amylase and lipase levels, pancreatic edema, histologic scorings were significantly ameliorated in aged mice infected with SP-AAV (Fig. ). These findings indicate that increased levels of miR-503-322 in senescent β cells contribute pancreatitis severity associated with older age.
miR-503-322 to enter acinar cells We previously verified that islet-derived EVs were secreted from insulin granules and were trafficked into liver and adipose tissues via circulation . Whether those EVs entered acinar cells was unknown. Here, we show that acinar cells indiscriminately engulfed EVs in vitro models (Fig. ), and acinar cells that received EVs purified from βTG islets had significantly greater levels of miR-503 than acinar cells that received EVs from wildtype (WT) islets (Fig. ). To validate the specificity of β-cells, we used the cell-permeable zinc-selective dye FluoZin TM -3, which selectively sorts pancreatic β-cells without compromising their viability or function , enabling enrichment of β-cell-derived EVs (βEVs) (Fig. ). Transmission electron microscopy (TEM) revealed βEVs with a diameter of about 45 nm (Fig. ), and nanoparticle tracking analysis (NTA) confirmed size of 42 nm (Fig. ). Western blotting confirmed high expression of EV markers (ALIX, TSG101, and CD63), but not GAPDH which was not included in EVs (Fig. ). Although the concentration was not different, βEVs released from βTG were found to package more miR-503 than those from WT β-cells (Fig. ). The in vitro uptake of βEVs by acinar cells and flow cytometry data showed that acinar cells can internalize βEVs with no significant difference in uptake efficiency (Figs. and ). Whereas the level of miR-503 in acinar cells receiving βTG-βEVs was significantly higher than those receiving WT-βEVs (Fig. ). We also injected labeled islet-derived EVs into mice via pancreatic ductal infusion and observed that acinar cells indiscriminately engulfed EVs in vivo (Fig. ). To avoid the influence of insulin resistance and hyperglycemia in βTG mice , we constructed RIP2-cre; miR-503-322 KI (βKI) mice which were not overtly diabetic (Fig. ). βKI mice also exhibited an exacerbation of caerulein-induced AP compared to littermate controls (Fig. ). Thus, we concluded that β-cell-derived small EVs enter acinar cells and drive pancreatitis at a miR-503-322 –dependent manner in mice.
miR-503-322 in acinar cells triggers both acute and CP Next, we sought to investigate the effects of miR-503-322 under inducible global elevation conditions by using CAG-creER; miR-503-322 KI (CKI). After tamoxifen induction three times, Pri-miR-503 expression levels were significantly elevated in the pancreas, skeletal muscle and other metabolic tissues (Fig. ). Surprisingly, CKI mice started to lose weight and activity, culminating in death due to severe AP within 6 days of the first induction, as observed by significantly increased serum amylase and lipase levels, abdominal infiltration of neutrophils and macrophages, and pancreatic saponification, necrosis and histological analysis (Fig. ). However, no concomitant histological changes were observed in other major abdominal organs (Fig. ). Severe AP-induced systemic inflammatory responses were shown by inverted serum ratios of neutrophils and lymphocytes, and elevated serum levels of C-reactive protein (Fig. ). These results validate that the global overexpression of miR-503-322 promotes severe AP, indicating the specificity of the miR-503-322 for pancreas damage. To rule out the contribution of other tissues, Pdx1-cre; miR-503-322 KI (heterozygous PKI/WT and homozygous PKI/KI) mice were used to yield high pancreatic-specific expression of miR-503-322 . The pancreatic Pri-miR-503 expression was increased in the heterozygous PKI mice (PKI/WT) compared to WT controls and was further increased in the homozygous mice (PKI/KI) (Fig. ). The PKI/KI mice showed an unexpected weight loss at ~6 weeks of age, while the PKI/WT mice showed no change during natural growth (Figs. and ). The most prominent features of CP, including pancreatic atrophy, fibrosis, tubular complexes, and inflammatory infiltration were observed in PKI/WT mice, with more severe CP and gross changes in the homozygous PKI/KI mice (Figs. and ). Accordingly, PKI/KI mice could not survive for 12 weeks (Fig. ). PDX1 is a master regulator in pancreas organogenesis while the maturation and identity preservation of islet β-cells and δ-cells , . To avoid development defect, inducible acini-specific miR-503-322 ( Elastase- CreER; miR-503-322 KI, EKI) mice were also constructed, and overexpression verified post-induction for 3 days (Fig. ). After tamoxifen injection, the EKI mice showed significantly increased indicators of AP, including macrophage infiltration, tissue damage, and necrosis (Figs. and ), and had a 50% mortality rate (Fig. ). Those mice that survived developed histology of CP one month post-induction, manifested as pancreatic atrophy (Fig. ), fibrosis, fat replacement, and acinar-to-ductal metaplasia (ADM, Fig. ), while a return to normal levels of serum amylase and lipase (Fig. ). As shown in Fig. , EKI female mice presented an AP phenotype similar to that of male mice 5 days after tamoxifen induction. The above findings demonstrate that global, pancreatic, and acinar cell-specific overexpression of miR-503-322 can directly trigger (severe) acute and CP in a dose- and tissue-dependent manner.
knockout alleviated caerulein-induced acute pancreatitis The possibility that ablation of miR-503-322 could alleviate AP was investigated by the global deletion of miR-503-322 (KO) (Fig. ). The KO mice were viable and fertile, with normal body weight (Fig. ). Histology of the pancreas revealed normal pancreatic morphology (Fig. ). Challenging the KO and WT mice with caerulein or PBS and assessing for AP severity revealed markedly lower pancreatic edema and amylase and lipase levels in the KO group (Fig. ). Histological examination revealed reduced pancreatic acinar cell damage, less interstitial expansion (indication of edema), and diminished macrophage infiltration in KO mice during the acute AP phase (Fig. ). To highlight the influence of aging on pancreatitis, 1-year-old KO mice were treated with caerulein. The findings revealed that KO mice experienced a significant alleviation of caerulein-induced AP compared to control mice (Fig. ). Together, these data demonstrate that the deletion of miR-503-322 can significantly alleviate caerulein-induced AP.
promotes pancreatitis by inhibiting zymogen secretion and acinar cell proliferation Next, we sought to identify the mechanisms by which miR-503-322 promotes the development of pancreatitis. TEM images from the pancreas of the PKI/WT mice revealed an increased number of zymogen granules (Fig. ). However, the significantly lower transcript levels of pancreatic enzyme-related genes implied that this did not represent an increased production of zymogen in the acinar cells (Fig. ) but was possibly an indication of a secretion defect. Therefore, we isolated acini and assessed their secretory ability in response to caerulein. The amylase release was significantly lower from the PKI cells than from the WT cells (Fig. ). The acinar cells from aged mice showed a similar response to that of the PKI cells, with a reduced secretion of pancreatic enzymes (Fig. ), in agreement with the results of previous studies . By contrast, the primary acinar cells from the KO mice showed enhanced amylase secretion (Fig. ). The defect of enzyme secretion was attributed to the loss of cytoskeleton modulation from tip to basolateral membranes of acinar cells responding to caerulein (Fig. ). Enzyme secretion defects may cause trypsinogen activation. We observed that trypsinogen activation in acini was visualized by using rhodamine 110 (BZiPAR) which revealed a clear enrichment of green fluorescence in PKI cells (Fig. ), and serum trypsin activity was enhanced in the PKI mice (Fig. ). These findings indicate that miR-503-322 inhibits pancreatic enzyme secretion and promotes the intracellular accumulation of zymogen. Subsequent zymogen activation in situ may promote pancreas damage of miR-503-322 elevated mice. Activation of trypsinogen by lysosomal enzymes after fusion of the lysosome is the classical mode of pancreatic enzyme activation during AP , . TEM images of the pancreas from PKI mice show morphological signs of this activation, including numerous autophagy vacuoles in the cytoplasm and abundant zymogen granules varying in size and electron density and sometimes fused together to form irregular “lakes” (Fig. ). These phenomena suggest a classical activation of intracellular zymogen in the lysosomes of acinar cells that highly express miR-503-322 . We verified this by inducing pancreatitis in WT and EKI mice by administration of chloroquine, which destroys the acidic environment in autophagic lysosomes (Fig. ). The AP phenotype was alleviated in EKI mice treated with chloroquine, as evidenced by a smaller weight loss, reduced serum amylase and lipase levels, and less tissue damage compared to saline-treated control mice, despite a similar pancreas weight (Fig. ). AP significantly stimulates the proliferation of acinar cells almost immediately at the point of injury . Not surprisingly, immunofluorescence staining for PCNA revealed a reduction in the numbers of proliferating acinar cells in the mice expressing high levels of the miR-503-322 , and an increased proliferation of mesenchymal cells (Fig. ). Conversely, ablation of miR-503-322 enhanced acinar cell proliferation during the repair phase of caerulein-induced AP (Fig. ). We also conducted a similar test in aged mice and again observed a significant decrease in acinar cell proliferation similar to that seen in the high miR-503-322 expression model mice (Fig. ). Taken together, these data suggest that miR-503-322 suppresses zymogen secretion to initiate acute pancreatitis. Meanwhile, miR-503-322 also inhibits the regenerative proliferation of acinar cells to promote the formation of CP.
miR-503-322 and acinar cell-specific restoration of it reverses the phenotype of pancreatitis in mice We previously used unbiased proteomics to identify target genes of miR-503 in regulating peripheral insulin resistance and β-cell dysfunction . By analyzing the same proteomics data combined with Targetscan software analysis, five genes (MKNK1, CCNE1, IGF1R, PI3KR1 and INSR) were potential targets (Fig. ). After extensively searching and reading literature, we found that the MKNK1, mostly expressed in the exocrine pancreas might contribute to miR-503-322 –caused pancreatitis. MKNK1 plays an indispensable role in physiological exocrine secretory response . Consistent with published data, phosphorylation of MKNK1 and its downstream eIF4E was increased 4 hr after the first caerulein injection and gradually recovered (Fig. ). MKNK1 was redistributed to the basolateral region after caerulein administration, assisting acinar cell secretion (Fig. ). Previous studies showed that ablation of MKNK1 results in exacerbation of pancreatitis caused by caerulein due to defects of zymogen secretion and acinar cell proliferative in mice , making us pursue the role of MKNK1 as a target gene of miR-503-322 . Our proteomics analysis showed a decrease in MKNK1 after miR-503 elevation. Dual-luciferase assay confirmed the regulatory role of miR-503-322 on the 3’UTR of Mknk1 gene (Figs. and B). Next, immunohistochemistry staining of pancreas sections revealed clear suppression of MKNK1 protein amount in the three miR-503-322 overexpressing mouse model. (Fig. ), while upregulation of MKNK1 was induced by caerulein in KO mice (Fig. ). The protein levels of MKNK1 and its associated P-MKNK1/P-eIF4E signaling were significantly reduced in the pancreas of miR-503-322 overexpressing model mice and aged mice, and by contrast increased in pancreas of miR-503-322 knockout mice and aged mice with β-cell-specific blocking miR-503-322 (Figs. and ). Taken together, these findings suggest that miR-503-322 targets MKNK1-eIF4E pathway to inhibit zymogen secretion and acinar cell proliferation, thereby leading to acute and CP. Next, we tested whether reconstitution of MKNK1 in pancreas could reverse pancreatitis of EKI mice following the schematic diagram (Fig. ). We generated an AAV, serotype pancreas (MKNK1-AAV) that directs specific MKNK1 overexpression in the exocrine pancreas. As shown in Fig. , MKNK1 was highly expressed in the acini, but not in the islets of MKNK1-AAV mice. Restoration of MKNK1 also rescued the miR-503-322 -suppressive protein levels of phos-MKNK1 and phos-eIF4E in the EKI pancreas (Fig. ). Consequently, MKNK1-AAV-infected EKI mice showed lessened AP phenotypes compared to Ctr-AAV-infected EKI mice. In detail, the loss of body weight, increased serum levels of amylase and lipase, increased number of macrophage infiltration, and tissue damage in Ctr-AAV infected EKI mice were largely reduced in MKNK1-AAV infected EKI mice (Fig. ). On the other hand, inhibition of MKNK1 by a verified inhibitor, CGP 57380 further exacerbated caerulein-caused AP phenotypes, and totally erased miR-503-322 knockout driven protective effects (Fig. ). These results from acinar cell MKNK1 reconstitution and specific MKNK1 inhibitor support our view that the deficiency of MKNK1 in acini is primarily responsible for the pancreatitis observed in miR-503-322 elevated mice.
miR-503 and MKNK1 in aging-associated pancreatitis changes in the Chinese population As the expression of miR-503 is specifically increased in senescent β cells in mice, we also considered its change in humans. Pancreas sections from elderly adults (EA) showed CP-like changes, including atrophy of the acinar cells, interstitial expansion, and a marked increase in fibrosis (Fig. ), as well as a significant reduction in the proportion of proliferating acinar cells (Fig. ), compared to that from young adults (YA). Intriguingly, miRNA in situ hybridization showed greater expression of miR-503 in islets than in acini in pancreatic sections from EA group (Fig. ), whereas expression of miR-503 was almost undetectable in YA group (Fig. ). The expression of MKNK1 was significantly downregulated in the acini from the EA pancreas compared to that from the YA pancreas (Fig. ). Moreover, the co-localization of MKNK1 and AMY1 in the young acini was dislocated in the elderly acini (Fig. ), indicating activation of MKNK1 in the EA. Thus, the increased level of miR-503 in the acini may come from the islet β cells and contribute to the decreased but activated MKNK1 protein in the elderly Chinese population. Numerous studies have reported that exocrine pancreas function is impaired in both healthy and diabetic older adults independent of gastrointestinal disease, judged by serum levels of amylase and maximum bicarbonate concentration , . Consistently, we observed a significantly decreased level of serum amylase in the EA with T2DM (EA + DM) compared to that in YA, moreover, the EAs also showed a decreased amylase level (Fig. ). Further analysis showed that serum concentration of miR-503 in EVs was elevated in the elderly compared to that in the YAs and was further elevated in the EA + DM (Fig. ). The human subjects displayed negative associations of serum amylase levels with both age and serum concentrations of miR-503 in EVs (Fig. ). These results support the pancreatic exocrine insufficiency in elderly and diabetic patients and point out serum concentrations of miR-503 in EVs as a molecular marker of ageing-associated pancreatitis in the Chinese population.
In this study, we demonstrated that miR-503-322 derived from endocrine β-cells promotes aging-associated pancreatitis by targeting MKNK1 in exocrine acinar cells. miR-503-322 , which is produced by senescent β-cells, had an in situ effect in acinar cells that inhibits zymogen secretion and regenerative proliferation. Thus, the miR-503-322 –MKNK1 axis caused pancreas autodigestion and repairing damage, leading to the onset of acute and CP in mice. This discovery provides an epigenetic mechanism for pancreatitis and adds to the existing evidence of crosstalk between pancreatic endocrine and exocrine. Gallstones and excessive alcohol use are known to be the major causes of AP in the clinic. Our study identified miR-503-322 derived from senescent β-cells as a factor that complements traditional etiologies of pancreatitis. Evidence suggests that insulin resistance and diabetes also play roles in pancreatitis , . MiR-503-322 secreted by senescent β cells contributes to pancreatitis, independent of insulin resistance and diabetes, as shown by increased severity of caerulein-induced AP in βKI mice prior to hyperglycemia and insulin resistance. However, in conditions of insulin resistance and diabetes, miR-503-322 exacerbates the severity of pancreatitis, as evidenced by the pancreas-specific knock-in heterozygous and homozygous mice with concomitant exacerbation of diabetes and a more severe pancreatitis phenotype. Previous studies have noted that patients with diabetes develop exocrine dysfunction without obvious symptoms or abnormalities of the pancreatic ducts, termed diabetic pancreatic exocrine disease (DEP) , . Several hypotheses have been proposed to explain the features of DEP – . However, none of these concepts are sufficient to explain all the pathological findings. Our previous results showed a significant upregulation of islet miR-503 expression in patients with T2DM . Suggested by our current investigation, the expressed miR-503 can then enter and accumulate in the exocrine acini, where it triggers damage to some of the acinar cells and causes CP-like changes in the exocrine pancreas due to repeated pancreas damage. Most studies report higher overall morbidity and mortality from pancreatitis in the elderly , and several explanations for this phenomenon have been put forward , . The present results confirmed that β-cell-derived miR-503-322 promotes both acute and chronic damage in the exocrine pancreas and increases mouse mortality with acute and high miR-503-322 expression (CKI and PKI/KI mice). Therefore, miR-503-322 may be a common pathogenic factor that can explain the higher morbidity and mortality from pancreatitis in the elderly. Histologically, focal fibrosis also appears to be common in the pancreas of the elderly , . This is consistent with the observations in human pancreatic sections in the present study. Clinical studies have indicated that pancreatic exocrine function is impaired in healthy older individuals without any gastrointestinal disease . The human subjects displayed negative associations of serum amylase levels with both age and serum concentrations of miR-503 . These results support pancreatic exocrine insufficiency in the elderly and diabetic patients. In our study, we found that miR-503 inhibits pancreatic enzyme secretion in acinar cells by targeting MKNK1. Decreased MKNK1 expression resulted in dysregulated cytoskeletal remodeling, thus defective movement of zymogen granules from tip to basolateral membrane, which ended up with enzyme secretion defect. Secretion of pancreatic enzyme inhibition with upregulation of miR-503 expression in normal elderly individuals manifests as lower serum amylase levels. However, it is crucial to note that this secretory blockage can precipitate the accumulation of digestive enzymes in acinar cells, which ultimately results in autodigestion, causing cellular damage and acute attack. In such cases, a transient yet significant release of large quantities of amylase into the serum resulted in a temporary elevation of serum amylase levels. We propose that serum amylase levels are elevated in elderly patients during acute attacks, despite the upregulation of miR-503 . Although the correlations of tissue and serum miR-503-322 and MKNK1 expression in the aging human population may not necessarily validate the proposed mechanisms and functions observed in transgenic mice, these findings provide valuable clues for further studies of aging-associated pancreatitis. In humans, AP and CP are diagnosed based on well-defined criteria , . In mouse models of pancreatitis, while classic symptoms like upper epigastric pain and vomiting are absent, affected mice may show reduced activity and weight loss. Diagnosis relies on increased plasma pancreatic enzyme levels, particularly amylase and lipase, and the pathological features of pancreatic tissue. In our study, global miR-503-322 overexpressing mice showed increased serum amylase and lipase on day two, with amylase normalizing by day five and lipase remaining elevated. Acinar cell-specific miR-503-322 knock-in mice exhibited significant enzyme upregulation on day three, with no further changes or decreases. Pancreatic pathology, quantified using a scoring system described by Schmidt et al. is essential for diagnosis . Human pancreatitis follows a course of acute attacks, interventions, and recurrent attacks, ultimately leading to CP . In mouse models, some mice die without prompt treatment, whereas survivors develop CP. The timescale of pancreatitis was more distinct in the inducible acini-specific miR-503-322 knock-in mouse model. AP was significantly detected two days after tamoxifen injection, with a 50% mortality rate. Mice that survived developed histology of CP one-month post-induction, manifested as pancreatic atrophy, fibrosis, fat replacement, and acinar-to-ductal metaplasia, while returning to normal levels of serum amylase and lipase. Despite the morphology of a human pancreas and timescale of developing pancreatitis making it difficult to discern acute and CP in a mouse model, we differentiated AP and CP in mice through serum enzymes and pancreatic pathology. In healthy adults, miR-503-322 is expressed mainly in lung, heart, and skeletal muscle progenitor cells . Upregulation of miR-503-322 occurs in aging acinar cells and is likely to arise from pancreatic β-cells, based on our present observations. Our evidence for this is that blocking miR-503-322 in islet β-cells of aging mice alleviated caerulein-induced pancreatitis. Our previous findings revealed that miR-503 from pancreatic islet β-cells reaches the liver and adipose tissue in the form of exosomes, which are known to transport biologically active proteins and miRNAs in their active forms to neighboring cells or distant organs – . Thus, the involvement of EVs in inter-organ and intra-organ crosstalk has been increasingly studied , . EVs derived from mesenchymal stem cells have been reported as a treatment for AP by delivering mitochondria and anti-inflammatory factors , . In addition, senescent β cells have been reported to secrete senescence-associated secretory phenotypes that are rich in EVs and cause dysfunction of adjacent cells through paracrine effects , . The reported anatomical characteristics of an IAA permit the access of high concentrations of islet-derived miR-503-322 to exocrine cells. Indeed, a recent study has determined that islet CCK can promote Kras -driven PDAC development of an endocrine exchange signal other than insulin , supporting the existence of endocrine-exocrine crosstalk via IAA. Therefore, we hypothesize that islet-derived miR-503-322 is transferred via EVs and the IAA into acinar cells. Our results support MKNK1 as a miR-503-322 target gene for the development of pancreatitis. However, MKNK1-knockout mice showed normal pancreatic histology , which was inconsistent with the phenotype of AP induced by miR-503-322 . This normal histologic may reflect the presence of other compensatory pathways in MKNK1-knockout mice as the use of a global mouse model. Indeed, the knockout of MKNK1 adds to the growing list of proteins that have a protective role during AP , whereas the acute induction of miR-503-322 lacks an effective compensatory mechanism. Alternatively, other target genes of miR-503-322 co-regulating the development of pancreatitis may exist. Moreover, EVs carrying miR-503-322 may function through inter-organ crosstalk to regulate the severity of AP as shown in CKI mice. In addition, tamoxifen administration occasionally causes pancreatitis also reminded us that the effect of tamoxifen itself cannot be ignored, although it was added to the control group . The mechanisms involved in these possibilities need to be unraveled in further studies. In conclusion, we demonstrate the role and mechanism of action for pancreatic endocrine-derived miR-503-322 in promoting pancreatitis in the elderly. Blocking miR-503-322 in β-cells of aged mice showed good inhibitory effects on pancreatitis, revealing miR-503-322 as a potential therapeutic target for elderly patients with pancreatitis.
Human biospecimen acquisition For human pancreas sections and islets study, conducted in Organ Transplant Center, Tianjin First Central Hospital, Nankai University, Tianjin, China. A total of 20 healthy individuals were recruited, of these, 10 were YA (18–25 years old) and 10 were the EA (60–85 years old) for human pancreas sections. Human islet donor from an elderly person. Islets were digested into single cells with 0.25% trypsin-EDTA (Gibco, USA) and treated with ABT263 (5 μM) (MCE, China) for 48 h, followed by a change to the fresh culture medium. After 24 h, EVs were enriched in the supernatant, and the cells were stained with β-galactosidase (Beyotime, China). Quantification was performed with three replicates per group, at least 15 microscopic fields per well, and a minimum count of 1000 cells. The detailed information of donors was listed in Table . Informed consent was obtained from all patients, and the research protocol was reviewed and approved by the research ethics committee of Tianjin First Central Hospital (No. 2018N112KY). For blood sample collection, conducted in the Department of Endocrinology, Geriatric Hospital of Nanjing Medical University, Nanjing, China, 160 individuals were recruited, including 65 YA (18-55 years old), 65 EA (60-85 years old), and 30 EA with T2DM (EA + DM). Fasting blood samples, collected from all participants, were centrifuged at 850 × g for 20 min to separate sera and blood cells, the sera were used for miR-503 concentration analysis. Detailed information about donors, including age range, fasting blood glucose levels, and history of prior diseases, was listed in Table . The study was approved by the research ethics committee of Nanjing Medical University (2022006), and all the volunteers gave written informed consent. Animal studies Animal studies were approved by the Research Animal Care Committee of Nanjing Medical University (IACUC-1707023 and IACUC-2004040). Generation of the mouse miR-503-322 knock-in mouse (H11-CAG-LSL- miR-503-322 Cas9-KI) by CRISPR/Cas9 was outsourced to GemPharmatech Co, Ltd. The mice were created on the C57BL/6 J genetic background. The gRNA (5′- CTGAGCCAACAGTGGTAGTA -3′) to the Hipp11 (H11) locus, the donor vector containing the “CAG-loxP-Stop-loxP-mouse miR-503-322 -polyA” cassette, and Cas9 mRNA were co-injected into fertilized mouse eggs to generate targeted conditional knock-in offspring. Rat insulin 2 promoter ( RIP2 )-Cre (JAX:003573), CAG -CreER (JAX:004453) and PDX1 -Cre (JAX:014647) mice were obtained from the Jackson Laboratory. Elastase ( ELA ) - CreER mice were obtained from Dr. Xianghui Fu (Professor of the West China Hospital, Sichuan University). We then crossed KI mice with CAG- CreER, PDX1 -Cre, ELA- CreER, and RIP2- Cre mice, respectively, to obtain global inducible (CKI), pancreas-specific (PKI), acinar cell-specific inducible (EKI), and islet β-cell-specific (βKI) overexpressing miR-503-322 mice. Details on each animal strain are listed in Table . EKI or CKI and their litter control mice were injected intraperitoneally with tamoxifen solution, 100 mg/kg, in corn oil, for three consecutive days to induce miR-503-322 overexpression in acinar cells or the whole body, respectively. The control groups used their respective littermates and were genotyped as KI-positive and Cre-negative. All experimental mice were heterozygous except for PKI mice, which included both homozygotes and heterozygotes. MiR-503 transgenic mice (βTG) and miR-503-322 global deletion mice (KO) were also generated by GemPharmatech Co, Ltd. Refer to our previous findings for the exact construction workflow . Aged C57BL6/J mice were purchased from GemPharmatech Co, Ltd. The animals were randomly allocated to experimental groups, at least four per group, not according to genotype to minimize potential confounding factors. Male mice were mostly used in this study, and female mice were also involved to rule out the sex bias, as described in the figure legends. Mice were housed in a temperature- and humidity-controlled environment (23–25 °C, 12-h light/dark cycle, 60–70% humidity) in a specific pathogen-free facility at Nanjing Medical University and provided with free access to commercial rodent chow (Research Diets, D12450J) and tap water. Health was monitored at least weekly by weight, food and water intake, and general assessment of animal activity, panting, and fur condition. Mice were euthanized by CO 2 asphyxiation when met euthanasia criteria. Adult animals of both genders were used in tamoxifen induction studies. Collected blood serum was used to measure amylase and lipase. The pancreatic tissue was collected and immediately embedded in an optimum cutting temperature compound for hematoxylin and eosin staining, evaluation of necrosis, and immunohistochemistry. Pancreatic acinar cell experiments Mouse pancreatic acini were isolated using the standard collagenase digestion protocol . Acini were isolated and left to recover for 30 min at 37 °C before stimulation with the indicated concentrations of caerulein (MCE, Shanghai, China) to assess the secretory capacity. The supernatant for amylase activity was analyzed with a commercial kit (JianCheng Bioengineering Institute, Nanjing, China) and the percentage of amylase secretion was calculated. To visualize trypsinogen activation in acinar cells, freshly prepared acini were loaded with active trypsin enzyme substrate BZiPAR (10 μM) (Invitrogen, America) and incubated for 30 min. For cytoskeletal analysis, pancreatic acini were isolated and incubated with or without caerulein (0.01 μM) for 30 min. At the indicated times, the cells were harvested and stained for F-actin with phalloidin and nuclei. Images were captured and analyzed by a confocal laser scanning microscope (Olympus FV1200). The image fluorescence intensity was analyzed with ImageJ software. For flow cytometry analysis, EVs labeled with PKH67 were co-incubated with freshly isolated acini for 8 h. Following this, the samples were digested into single cells and subsequently analyzed to determine the percentage of FITC-positive cells. Induction of murine pancreatitis Caerulein was solubilized in phosphate-buffered saline at a final concentration of 15 mg/mL. Experimental mice were challenged with caerulein (50 mg/kg, intraperitoneal injection, once an hour, six times) to induce AP. Control animals received an equal amount of saline. The parameters of AP were assessed 2 h after the last caerulein treatment. Edema, serum lipase (ElabScience, Wuhan, China), amylase and trypsin activity (JianCheng Bioengineering Institute, Nanjing, China) were analyzed as parameters of pancreatitis. Necrosis and acinar cell damage quantified by morphometry . Tissue damage was quantified using scoring system as describe by Schmidt et al. . Histopathology, immunohistochemistry, and immunofluorescence Mice were euthanized by CO 2 asphyxiation and tissue was dissected, rinsed in PBS and fixed overnight in 4% paraformaldehyde (Servicebio). Paraffin embedding, serial sectioning, H&E and Masson staining of all samples were commissioned from Servicebio Technologies. After dewaxing and antigen retrieval, the pancreatic paraffinic sections were incubated with primary antibodies overnight at 4 °C. According fluorescent-conjugated secondary antibodies (Proteintech) were used for multiple labeling, and the nuclei were stained with Hoechst 33342 (5 μg/mL) (Sigma-Aldrich). Fluorescent images were visualized by a confocal laser scanning microscope (Olympus FV1200). Immunohistochemistry staining was labeled with a DAB substrate system (BCA Kit) (Gene Tech), and positively labeled cells were captured by a light microscope (Leica, Germany). Quantification was done with at least three mice per group, three sections per mouse (50 µm apart), and at least 10 microscopic fields per section. The antibodies are listed in Table . Pancreatic ductal infusion of adeno-associated viral (AAV) vectors Pancreatic ductal infusion was performed following the standard surgical protocol . Serotype 2/8 under insulin 2 promoter of HBAAV2/8-insulin 2-scrambled sequence-zsGreen (Ctr) and HBAAV2/8-insulin 2-mmu-miR-503/322-5p-sponge-zsGreen (SP) were provided by the company of Hanheng Biotechnology Co, Ltd. AAV titer of 10 11 /mL in PBS, 100 μL total volume in 20 g body weight mice was infused at a rate of 6 μL/min. After infusion and suture, surgical mice were placed on a heated pad (37 °C) until full recovery. Ketoprofen (Sigma, k1751) at a dose of 5 mg/kg once per day was given continuously for 3 d for post-surgery analgesia. Serotype pancreas of PAAV-CMV-MCS-EF1-mNeonGreen-WPRE (Ctr-AAV) and PAAV-CMV-MKNK1-flag-EF1-mNeonGreen-WPRE (MKNK1-AAV) were provided by the company of OBIO Technology Co, Ltd and were administered to mice via intraperitoneal injection. AAV titer of 10 11 /mL in PBS, 100 μL total volume in 20 g body weight mice. Locked nucleic acid (LNA)-based in situ hybridization of miR-503 Locked nucleic acid-based in situ assay was introduced to detect miR-503 in human pancreas sections. Double-labeled with carboxyfluorescein (FAM), LNA-enhanced probes including U6 snRNA control probe, negative scramble-miR control and has- miR-503 were constructed by QIAGEN. The assay was performed according to the manufacturer’s protocol . In short, sample slides were deparaffinized in xylene and ethanol solutions at room temperature (15–25 °C) and digested with Proteinase K reagent for 10 min at 37 °C. After washing, each sample was reacted with 50 µL of hybridization mix (1 nM LNA U6 snRNA probe, 40 nM double-FAM LNA miR-503 probe and scramble-miR) in a programmed hybridizer for 1 h. After strictly washing and blocking, the samples were incubated with anti-FAM reagent for 1 h and labeled with alkaline phosphatase substrates for 2 h. The nuclei were labeled with Nuclear Fast Red. All sample slices were visualized by light microscopy. Islet and β cell-derived EVs isolation and identification Freshly isolated islets were cultured in serum-EVs-free medium (11.1 mM glucose) for 7 days, with the medium replaced and collected every 24 h. Mouse islets were digested into single cells and treated with FluoZin TM -3 (5 μM) (Thermo Fisher Scientific) for 30 min, followed by fluorescence-activated cell sorting to obtain purified β-cells. β-cells were cultured in 0.1 mg/mL poly-D-lysine (Beyotime, China)-coated well plates and EVs-free medium for 3 days and supernatants were collected for enrichment. The culture medium was centrifuged at 300 × g for 5 min and then at 3000 × g for 20 min to remove cells and other debris, followed by centrifugation at 10,000 × g for 30 min to remove large vesicles. Then, the supernatant was centrifuged at 110,000 × g for 2 h. EVs were collected from the pellets and resuspended in an FBS-free medium or PBS. All centrifugation steps were performed at 4 °C. For the identification of EVs, TEM, NTA, and Western blot analyses were performed. For TEM, EVs were fixed overnight at 4 °C in a droplet of 2.5% glutaraldehyde in PBS (pH 7.2). The samples were then washed with PBS three times (10 min each) and post-fixed in 1% osmium tetroxide for 60 min at room temperature. Samples were then embedded in 10% gelatin, fixed in glutaraldehyde at 4 °C, cut into several blocks (<1 mm 3 in volume), and dehydrated for 10-min dehydration steps in alcohol at increasing concentrations (30%, 50%, 70%, 90%, 95%, and 100% × 3). Pure alcohol was then replaced with propylene oxide, and the samples were infiltrated with Quetol 812 epoxy resin at increasing concentrations (25%, 50%, 75%, and 100%) with propylene oxide for a minimum of 3 h per step. Next, the samples were embedded in 100% fresh Quetol 812, polymerized at 35 °C for 12 h, and then at 60 °C for 24 h. Ultrathin sections (100 nm) were obtained from the prepared samples using a Leica UC6 ultramicrotome. Finally, the samples were post-stained with uranyl acetate for 10 min and lead citrate for 5 min at room temperature and observed using an FEI Tecnai T20 TEM operated at 120 kV. NTA was performed using a NanoSight NS300 system (NanoSight), which focuses a laser beam through a suspension of the particle of interest. The results were visualized by light scattering. For western blotting, ALIX, TSG101, and CD63 were used as markers for nano-vesicles and GAPDH was used as a negative control. For cell imaging, EVs were labeled with PKH67 (Sigma-Aldrich) for 1 h and then washed three times with PBS. PKH67-labeled EVs (6e + 5 particles/35 mm culture dish) were resuspended in PBS and then incubated with freshly isolated acini for 8 h. The acini were then stained with phalloidin (MCE) for 15 min and Hoechst 33342 for 8 min. Images were taken and analyzed by a confocal laser scanning microscope (Olympus FV1200). Plasmid construction and dual-luciferase reporter assay The WT and mutant 3’ UTR-luciferase constructs containing miR-503-322 binding site of mouse Mknk1 were generated by annealing and cloning the short sequences into pMIR-REPORT Luciferase miRNA Expression Reporter Vector (Ambion) between the SpeI and HindIII sites. Primer sequences are listed in Table . Luciferase activities were measured using the Dual-Glo Luciferase Assay System (Promega, America) on a TD-20/20 Luminometer (Turner BioSystems, America) according to the manufacturer’s protocols. Quantitative RT-PCR Total RNA was extracted from cells and tissues using Trizol reagent (Invitrogen). cDNA was synthesized from total RNA using a ReverTra Ace Kit (TOYOBO, Japan). qPCR of Pri-miRNA and miRNA were performed using the THUNDERBIRD probe qPCR Mix (TOYOBO, Japan), and SYBR Green qPCR Master Mix (Vazyme, China) for mRNA on Roche LightCycle480 II Sequence Detection System (Roche, Switzerland). Primers of qPCR for pri-miRNA and miRNA were purchased from Thermofisher Co., Ltd, other primer sequences were available in Table . Western blot analysis Cells or tissues were lysed with ice-cold RIPA buffer (Thermo Fisher Scientific), supplemented with 0.5 mM EDTA and Halt protease/phosphatase inhibitor cocktail (Thermo Fisher Scientific), rotated at 4 °C for 15–30 min to mix, and centrifuged at maximum speed for 15 min to collect whole cell lysates. Protein concentration was measured with the BCA protein assay (Takara). Thirty mg of total protein per sample was loaded into 4–12% NuPAGE Tris-Bis (Thermo Fisher Scientific) gradient gels and separated by SDS-PAGE. Proteins were transferred to PVDF membranes (Millipore Billerica) and blocked with 5% milk. Beta-actin and α-tubulin were used as loading controls. Primary antibodies were detected with HRP-conjugated (Sigma-Aldrich) secondary antibodies for chemiluminescent detection (Perkin Elmer ECL). Protein quantification was performed by ImageJ (NIH Image). Key reagents and antibodies are listed in Table . Statistical analysis All results were expressed as mean ± SEM. Results were analyzed with GraphPad Prism software (version 8.3.0, San Diego, CA, USA). Two-tailed unpaired Student’s t test was used for the comparison of two sets. Differences in means between multiple groups were analyzed by ordinary one-way analysis of variance followed by Tukey’s multiple comparisons. Two-way ANOVA followed by Tukey’s multiple comparisons was used for two-way analysis. Linear regression analysis was performed using GraphPad Prism software. Pearson correlation analysis was used to test for correlations. In all analyses, P < 0.05 was considered statistically significant. Reporting summary Further information on research design is available in the linked to this article.
For human pancreas sections and islets study, conducted in Organ Transplant Center, Tianjin First Central Hospital, Nankai University, Tianjin, China. A total of 20 healthy individuals were recruited, of these, 10 were YA (18–25 years old) and 10 were the EA (60–85 years old) for human pancreas sections. Human islet donor from an elderly person. Islets were digested into single cells with 0.25% trypsin-EDTA (Gibco, USA) and treated with ABT263 (5 μM) (MCE, China) for 48 h, followed by a change to the fresh culture medium. After 24 h, EVs were enriched in the supernatant, and the cells were stained with β-galactosidase (Beyotime, China). Quantification was performed with three replicates per group, at least 15 microscopic fields per well, and a minimum count of 1000 cells. The detailed information of donors was listed in Table . Informed consent was obtained from all patients, and the research protocol was reviewed and approved by the research ethics committee of Tianjin First Central Hospital (No. 2018N112KY). For blood sample collection, conducted in the Department of Endocrinology, Geriatric Hospital of Nanjing Medical University, Nanjing, China, 160 individuals were recruited, including 65 YA (18-55 years old), 65 EA (60-85 years old), and 30 EA with T2DM (EA + DM). Fasting blood samples, collected from all participants, were centrifuged at 850 × g for 20 min to separate sera and blood cells, the sera were used for miR-503 concentration analysis. Detailed information about donors, including age range, fasting blood glucose levels, and history of prior diseases, was listed in Table . The study was approved by the research ethics committee of Nanjing Medical University (2022006), and all the volunteers gave written informed consent.
Animal studies were approved by the Research Animal Care Committee of Nanjing Medical University (IACUC-1707023 and IACUC-2004040). Generation of the mouse miR-503-322 knock-in mouse (H11-CAG-LSL- miR-503-322 Cas9-KI) by CRISPR/Cas9 was outsourced to GemPharmatech Co, Ltd. The mice were created on the C57BL/6 J genetic background. The gRNA (5′- CTGAGCCAACAGTGGTAGTA -3′) to the Hipp11 (H11) locus, the donor vector containing the “CAG-loxP-Stop-loxP-mouse miR-503-322 -polyA” cassette, and Cas9 mRNA were co-injected into fertilized mouse eggs to generate targeted conditional knock-in offspring. Rat insulin 2 promoter ( RIP2 )-Cre (JAX:003573), CAG -CreER (JAX:004453) and PDX1 -Cre (JAX:014647) mice were obtained from the Jackson Laboratory. Elastase ( ELA ) - CreER mice were obtained from Dr. Xianghui Fu (Professor of the West China Hospital, Sichuan University). We then crossed KI mice with CAG- CreER, PDX1 -Cre, ELA- CreER, and RIP2- Cre mice, respectively, to obtain global inducible (CKI), pancreas-specific (PKI), acinar cell-specific inducible (EKI), and islet β-cell-specific (βKI) overexpressing miR-503-322 mice. Details on each animal strain are listed in Table . EKI or CKI and their litter control mice were injected intraperitoneally with tamoxifen solution, 100 mg/kg, in corn oil, for three consecutive days to induce miR-503-322 overexpression in acinar cells or the whole body, respectively. The control groups used their respective littermates and were genotyped as KI-positive and Cre-negative. All experimental mice were heterozygous except for PKI mice, which included both homozygotes and heterozygotes. MiR-503 transgenic mice (βTG) and miR-503-322 global deletion mice (KO) were also generated by GemPharmatech Co, Ltd. Refer to our previous findings for the exact construction workflow . Aged C57BL6/J mice were purchased from GemPharmatech Co, Ltd. The animals were randomly allocated to experimental groups, at least four per group, not according to genotype to minimize potential confounding factors. Male mice were mostly used in this study, and female mice were also involved to rule out the sex bias, as described in the figure legends. Mice were housed in a temperature- and humidity-controlled environment (23–25 °C, 12-h light/dark cycle, 60–70% humidity) in a specific pathogen-free facility at Nanjing Medical University and provided with free access to commercial rodent chow (Research Diets, D12450J) and tap water. Health was monitored at least weekly by weight, food and water intake, and general assessment of animal activity, panting, and fur condition. Mice were euthanized by CO 2 asphyxiation when met euthanasia criteria. Adult animals of both genders were used in tamoxifen induction studies. Collected blood serum was used to measure amylase and lipase. The pancreatic tissue was collected and immediately embedded in an optimum cutting temperature compound for hematoxylin and eosin staining, evaluation of necrosis, and immunohistochemistry.
Mouse pancreatic acini were isolated using the standard collagenase digestion protocol . Acini were isolated and left to recover for 30 min at 37 °C before stimulation with the indicated concentrations of caerulein (MCE, Shanghai, China) to assess the secretory capacity. The supernatant for amylase activity was analyzed with a commercial kit (JianCheng Bioengineering Institute, Nanjing, China) and the percentage of amylase secretion was calculated. To visualize trypsinogen activation in acinar cells, freshly prepared acini were loaded with active trypsin enzyme substrate BZiPAR (10 μM) (Invitrogen, America) and incubated for 30 min. For cytoskeletal analysis, pancreatic acini were isolated and incubated with or without caerulein (0.01 μM) for 30 min. At the indicated times, the cells were harvested and stained for F-actin with phalloidin and nuclei. Images were captured and analyzed by a confocal laser scanning microscope (Olympus FV1200). The image fluorescence intensity was analyzed with ImageJ software. For flow cytometry analysis, EVs labeled with PKH67 were co-incubated with freshly isolated acini for 8 h. Following this, the samples were digested into single cells and subsequently analyzed to determine the percentage of FITC-positive cells.
Caerulein was solubilized in phosphate-buffered saline at a final concentration of 15 mg/mL. Experimental mice were challenged with caerulein (50 mg/kg, intraperitoneal injection, once an hour, six times) to induce AP. Control animals received an equal amount of saline. The parameters of AP were assessed 2 h after the last caerulein treatment. Edema, serum lipase (ElabScience, Wuhan, China), amylase and trypsin activity (JianCheng Bioengineering Institute, Nanjing, China) were analyzed as parameters of pancreatitis. Necrosis and acinar cell damage quantified by morphometry . Tissue damage was quantified using scoring system as describe by Schmidt et al. .
Mice were euthanized by CO 2 asphyxiation and tissue was dissected, rinsed in PBS and fixed overnight in 4% paraformaldehyde (Servicebio). Paraffin embedding, serial sectioning, H&E and Masson staining of all samples were commissioned from Servicebio Technologies. After dewaxing and antigen retrieval, the pancreatic paraffinic sections were incubated with primary antibodies overnight at 4 °C. According fluorescent-conjugated secondary antibodies (Proteintech) were used for multiple labeling, and the nuclei were stained with Hoechst 33342 (5 μg/mL) (Sigma-Aldrich). Fluorescent images were visualized by a confocal laser scanning microscope (Olympus FV1200). Immunohistochemistry staining was labeled with a DAB substrate system (BCA Kit) (Gene Tech), and positively labeled cells were captured by a light microscope (Leica, Germany). Quantification was done with at least three mice per group, three sections per mouse (50 µm apart), and at least 10 microscopic fields per section. The antibodies are listed in Table .
Pancreatic ductal infusion was performed following the standard surgical protocol . Serotype 2/8 under insulin 2 promoter of HBAAV2/8-insulin 2-scrambled sequence-zsGreen (Ctr) and HBAAV2/8-insulin 2-mmu-miR-503/322-5p-sponge-zsGreen (SP) were provided by the company of Hanheng Biotechnology Co, Ltd. AAV titer of 10 11 /mL in PBS, 100 μL total volume in 20 g body weight mice was infused at a rate of 6 μL/min. After infusion and suture, surgical mice were placed on a heated pad (37 °C) until full recovery. Ketoprofen (Sigma, k1751) at a dose of 5 mg/kg once per day was given continuously for 3 d for post-surgery analgesia. Serotype pancreas of PAAV-CMV-MCS-EF1-mNeonGreen-WPRE (Ctr-AAV) and PAAV-CMV-MKNK1-flag-EF1-mNeonGreen-WPRE (MKNK1-AAV) were provided by the company of OBIO Technology Co, Ltd and were administered to mice via intraperitoneal injection. AAV titer of 10 11 /mL in PBS, 100 μL total volume in 20 g body weight mice.
miR-503 Locked nucleic acid-based in situ assay was introduced to detect miR-503 in human pancreas sections. Double-labeled with carboxyfluorescein (FAM), LNA-enhanced probes including U6 snRNA control probe, negative scramble-miR control and has- miR-503 were constructed by QIAGEN. The assay was performed according to the manufacturer’s protocol . In short, sample slides were deparaffinized in xylene and ethanol solutions at room temperature (15–25 °C) and digested with Proteinase K reagent for 10 min at 37 °C. After washing, each sample was reacted with 50 µL of hybridization mix (1 nM LNA U6 snRNA probe, 40 nM double-FAM LNA miR-503 probe and scramble-miR) in a programmed hybridizer for 1 h. After strictly washing and blocking, the samples were incubated with anti-FAM reagent for 1 h and labeled with alkaline phosphatase substrates for 2 h. The nuclei were labeled with Nuclear Fast Red. All sample slices were visualized by light microscopy.
Freshly isolated islets were cultured in serum-EVs-free medium (11.1 mM glucose) for 7 days, with the medium replaced and collected every 24 h. Mouse islets were digested into single cells and treated with FluoZin TM -3 (5 μM) (Thermo Fisher Scientific) for 30 min, followed by fluorescence-activated cell sorting to obtain purified β-cells. β-cells were cultured in 0.1 mg/mL poly-D-lysine (Beyotime, China)-coated well plates and EVs-free medium for 3 days and supernatants were collected for enrichment. The culture medium was centrifuged at 300 × g for 5 min and then at 3000 × g for 20 min to remove cells and other debris, followed by centrifugation at 10,000 × g for 30 min to remove large vesicles. Then, the supernatant was centrifuged at 110,000 × g for 2 h. EVs were collected from the pellets and resuspended in an FBS-free medium or PBS. All centrifugation steps were performed at 4 °C. For the identification of EVs, TEM, NTA, and Western blot analyses were performed. For TEM, EVs were fixed overnight at 4 °C in a droplet of 2.5% glutaraldehyde in PBS (pH 7.2). The samples were then washed with PBS three times (10 min each) and post-fixed in 1% osmium tetroxide for 60 min at room temperature. Samples were then embedded in 10% gelatin, fixed in glutaraldehyde at 4 °C, cut into several blocks (<1 mm 3 in volume), and dehydrated for 10-min dehydration steps in alcohol at increasing concentrations (30%, 50%, 70%, 90%, 95%, and 100% × 3). Pure alcohol was then replaced with propylene oxide, and the samples were infiltrated with Quetol 812 epoxy resin at increasing concentrations (25%, 50%, 75%, and 100%) with propylene oxide for a minimum of 3 h per step. Next, the samples were embedded in 100% fresh Quetol 812, polymerized at 35 °C for 12 h, and then at 60 °C for 24 h. Ultrathin sections (100 nm) were obtained from the prepared samples using a Leica UC6 ultramicrotome. Finally, the samples were post-stained with uranyl acetate for 10 min and lead citrate for 5 min at room temperature and observed using an FEI Tecnai T20 TEM operated at 120 kV. NTA was performed using a NanoSight NS300 system (NanoSight), which focuses a laser beam through a suspension of the particle of interest. The results were visualized by light scattering. For western blotting, ALIX, TSG101, and CD63 were used as markers for nano-vesicles and GAPDH was used as a negative control. For cell imaging, EVs were labeled with PKH67 (Sigma-Aldrich) for 1 h and then washed three times with PBS. PKH67-labeled EVs (6e + 5 particles/35 mm culture dish) were resuspended in PBS and then incubated with freshly isolated acini for 8 h. The acini were then stained with phalloidin (MCE) for 15 min and Hoechst 33342 for 8 min. Images were taken and analyzed by a confocal laser scanning microscope (Olympus FV1200).
The WT and mutant 3’ UTR-luciferase constructs containing miR-503-322 binding site of mouse Mknk1 were generated by annealing and cloning the short sequences into pMIR-REPORT Luciferase miRNA Expression Reporter Vector (Ambion) between the SpeI and HindIII sites. Primer sequences are listed in Table . Luciferase activities were measured using the Dual-Glo Luciferase Assay System (Promega, America) on a TD-20/20 Luminometer (Turner BioSystems, America) according to the manufacturer’s protocols.
Total RNA was extracted from cells and tissues using Trizol reagent (Invitrogen). cDNA was synthesized from total RNA using a ReverTra Ace Kit (TOYOBO, Japan). qPCR of Pri-miRNA and miRNA were performed using the THUNDERBIRD probe qPCR Mix (TOYOBO, Japan), and SYBR Green qPCR Master Mix (Vazyme, China) for mRNA on Roche LightCycle480 II Sequence Detection System (Roche, Switzerland). Primers of qPCR for pri-miRNA and miRNA were purchased from Thermofisher Co., Ltd, other primer sequences were available in Table .
Cells or tissues were lysed with ice-cold RIPA buffer (Thermo Fisher Scientific), supplemented with 0.5 mM EDTA and Halt protease/phosphatase inhibitor cocktail (Thermo Fisher Scientific), rotated at 4 °C for 15–30 min to mix, and centrifuged at maximum speed for 15 min to collect whole cell lysates. Protein concentration was measured with the BCA protein assay (Takara). Thirty mg of total protein per sample was loaded into 4–12% NuPAGE Tris-Bis (Thermo Fisher Scientific) gradient gels and separated by SDS-PAGE. Proteins were transferred to PVDF membranes (Millipore Billerica) and blocked with 5% milk. Beta-actin and α-tubulin were used as loading controls. Primary antibodies were detected with HRP-conjugated (Sigma-Aldrich) secondary antibodies for chemiluminescent detection (Perkin Elmer ECL). Protein quantification was performed by ImageJ (NIH Image). Key reagents and antibodies are listed in Table .
All results were expressed as mean ± SEM. Results were analyzed with GraphPad Prism software (version 8.3.0, San Diego, CA, USA). Two-tailed unpaired Student’s t test was used for the comparison of two sets. Differences in means between multiple groups were analyzed by ordinary one-way analysis of variance followed by Tukey’s multiple comparisons. Two-way ANOVA followed by Tukey’s multiple comparisons was used for two-way analysis. Linear regression analysis was performed using GraphPad Prism software. Pearson correlation analysis was used to test for correlations. In all analyses, P < 0.05 was considered statistically significant.
Further information on research design is available in the linked to this article.
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4-Thiazolidinone-Bearing Hybrid Molecules in Anticancer Drug Design | 861a9e76-5671-438e-98c2-2663aab273db | 9654980 | Pharmacology[mh] | Cancer diseases are a colossal problem for humanity, and according to data from the World Health Organization (WHO), they are the major cause of death among people under 70 years . This poses a significant challenges to research focused on the development of novel and more effective pharmaceuticals without the disadvantages/adverse effects of classic/conventional anticancer chemotherapeutics, which usually include a low therapeutic index, development of resistance to treatment, and low bioavailability . The modern medicinal chemistry of anticancer agents actively uses a wide set of tools for updating anticancer agent libraries and pipelines with the aim to achieve the desired biological activity and overcome the limitations of known chemotherapeutics. Molecular-hybridization approaches are important synthetic strategies in the design of drug-like small molecules with more powerful and biologically more extensive anticancer properties than the initial compounds . 4-Thiazolidinone scaffolds belong to privileged structures in drug design . The most successful molecules from this class of heterocycles include epalrestat and glitazones , which has made a significant contribution to diabetes therapy. Over the last decade, 4-thiazolidinone derivatives have continued to be the focus of research by medicinal chemists and have once again returned to the world pharmaceutical market. Thus, the 5-ylidene derivative of 2-(alkyl)imino-4-thiazolidinone Ponesimod (Ponvory) was approved by the FDA in 2021 as a potential drug for the treatment of multiple sclerosis and psoriasis . 4-Thiazolidinone scaffolds are widely used for the development of anticancer agents, and a number of recent reviews have been published dedicated to this area of drug design . The works in question include material devoted specifically to derivatives of 2-thioxothiazolidin-4-one (rhodanine) and thiazolidine-2,4-dione , which possess antitumor properties. Therefore, this review’s purpose was to highlight the anticancer properties of 2-imino-4-thiazolidinone derivatives and 2-3-disubstituted 4-thiazolidinones as well as several recent works devoted to 2-thioxothiazolidin-4-one (rhodanine) or thiazolidin-2,4-dione derivatives. For the writing of this review, the research articles, short communications, letters, and reports from the scientific databases Scopus (Elsevier), SciFinder (Chemical Abstracts), and PubMed were analyzed from the years 2017 to 2022. Information from patents was not included in the present study. Moreover, the main emphasis of the present review was on the application of molecular hybridization strategies such as the hybridization of scaffolds, the hybrid-pharmacophore approach, analogue-based drug design in synthesis, and the development of novel potent antitumor agents with 4-thiazolidinone scaffolds. A series of publications reported the successful application of molecular hybridization methods and strategies for the design of novel anticancer agents based on obtaining hybrids of the type “approved drugs-4-thiazolidinone scaffolds”. The drugs from different pharmacological groups were used as parent molecules for further hybridization and development. 2.1. Anticancer Drug–4-Thiazolidinones Hybrids Türe et al. reported on the design and synthesis of a series of novel hybrid molecules containing imatinib (Gleevec) moiety. Imatinib was the first-in-class protein kinase inhibitor approved by the FDA in 2001 and had a revolutionary impact on the treatment of most cases of chronic myeloid leukemia (CML) . Obtained by Türe et al., 5-benzylidene-2-arylimino-4-thiazolidinone-bearing imatinib analogs were screened for their antimitotic activity on K562 (chronic myeloid leukemia), PC3 (prostate cancer), and SHSY-5Y (neuroblastoma) cell lines, and the three most potent cytotoxic hybrids, 1–3 , were identified. Compounds 1–3 induced apoptotic cell death. Moreover, cycle arrest in the G0/G1 phase was caused by compounds 2 and 3 , while compound 1 inhibited the cell cycle in the G2/M phase. Hybrid molecules 1 and 3 proved to have stronger genotoxic effects than imatinib against K562 cells . 2.2. NSAID–4-Thiazolidinones Hybrids Recent decades have been marked by an increased interest in the use of potential NSAIDs for the treatment of cancer or using NSAIDs scaffolds/molecules for the design of new antimitotic agents . Ramadan W.S. et al. used a hybridization approach involving anti-inflammatory drug-5-aminosalicylic acid and 5-ylidene-4-thiazolidinone scaffolds with the aim of designing new promising anti-cancer agents . Synthesized hybrids were tested on a panel of seven cancer cell lines, and two molecules, 4 and 5 , were found to be efficient in some types of cancer compared to the effect of doxorubicin (reference drug), with the highest activity level detected on the MCF7 line, with IC 50 values of 0.31 and 0.30 µM, respectively. Furthermore, tumor specificity and minimal effects on normal fibroblasts were observed for 4 and 5 . In vitro studies of the molecular mechanisms of action for 4 and 5 revealed the induction of DNA damage, cell cycle arrest in the G2/M phase, and the induction of apoptosis as indicated by annexin-V staining and the activation of caspases. Moreover, it was found that both compounds modulate the expression and activity of several factors in the DNA damage response pathway, cyclins/cyclin-dependent kinases, and CDC25 phosphatase. NSAID–diclofenac was used for the design of potential anticancer agents by Shepeta et al. . A series of diclofenac-4-thiazolidinones hybrids with a hydrazine linker in the molecules were synthesized and tested on antitumor activity in a 60 line screening program (DTP NCI) . Two novel hybrids, 6 and 7 , displayed slight anticancer activity, and an in vitro cytostatic effect was observed on the leukemia CCRF-CEM, with a percentage of growth (GP%) of 56.82% for molecule 6 , on the non-small-cell lung cancer NCIH522, with a GP of 54.32%, and on colon cancer HCT-116, with a GP% of 57.71% of cell lines for hybrid 7 . Holota et al. reported on pyrazolin-5-one bearing 4-thiazolidinone hybrid 8 with moderate anticancer activity, with GP% values of 68 % and 87 % on the NCI-H460 (Lung cancer) and SF-268 (CNS cancer) lines, respectively, at 10 μM concentration. 2.3. Antibacterial Drug–4-Thiazolidinones Hybrids A series of novel 4-thiazolidinone-sulfanilamide hybrids incorporating substituted indolin-2-one moieties were designed as possible human carbonic anhydrase (hCA) inhibitors by Eldehna et al. . The new hybrids were evaluated in vitro for their inhibitory activity against hCA I, II, IV, and IX, and all molecules were active in variable degrees. Moreover, all compounds were examined for their anti-proliferative activity against breast cancer MCF-7 and colorectal cancer Caco-2 cell lines, and hybrid 9 was found to be the most potent against MCF-7, with an IC 50 of 3.96 ± 0.21 µM. In-depth studies showed that hybrid 9 provoked the intrinsic apoptotic mitochondrial pathway in MCF-7 cells, which was evidenced by the enhanced expression of the pro-apoptotic protein Bax and the reduced expression of the anti-apoptotic protein Bcl-2 as well as up-regulated active caspase-3 and caspase-9, cytochrome C, and p53 levels. Multifunctional sulfanilamide-bearing hybrids were developed and tested against HepG2 and MDA-MB-231 cancer cell lines by Sunil Kumar et al. . Among the tested hybrids, compound 10 was identified as potent against the MBA-MB-231 cell line and showed the highest cytotoxic activity, with an IC 50 value of 17.45 µM, which was higher than in the case of the standard drug cisplatin. Special attention from the point of view of analog- and fragment-based anticancer drug design is warranted in the case of the molecule ciminalum, which is a p -nitro-α-chlorocinnamic aldehyde or (2 Z )-2-chloro-3-(4-nitrophenyl)prop-2-enal (CAS 3626-97-9) and was used as a drug in medical practice in the former Soviet Union as an active antimicrobial agent against Gram-positive and Gram-negative microorganisms. The diversity-oriented approach was applied for the synthesis of ciminalum-4-thiazolidinone hybrid molecules, and a series of derivatives were reported by Buzun and Finiuk . For such a hybrid type, SAR analysis revealed that the presence of carboxylic acids , p-hydroxyphenyl , or (4-hydroxyphenyl)-pyrrolidine-2,5-dione substituents at position 3 of the 4-thiazolidinone ring determines the most effective anti-tumor activity, while the absence of a substituent or presence of an additional ciminalum substituent at position 3 leads to a weakening in activity. Among the synthesized and screened hybrids, derivative 11 was cytotoxic toward MCF-7 and MDA-MB-231 breast cancer cell lines, with IC 50 values of 5.02 µM and 15.24 µM, respectively . The hybrid 11 induced the extrinsic and intrinsic apoptotic pathways and caused a reduction in topoisomerase II concentration in both tested human breast cancer cell lines. The affinity of hybrid 11 to topoisomerase II was also confirmed by docking simulations. In addition, molecule 11 caused a decrease in the levels of Beklin-1, LC3A (the microtubule-associated protein 1A/1B light chain 3A), and LC3B (the microtubule-associated protein 1A/1B light chain 3B), suggesting its influence on the autophagy process. A ciminalum–4-thiazolidinone hybrid 12 possessed a high activity level in NCI 60-Cell-line screening (MG_MID GI 50 = 1.57 µM and TGI = 13.3 µM). The analysis of activity inside cancer panels revealed a certain sensitivity profile in the GI 50 concentration range of < 0.01–0.02 µM toward leukemia (MOLT-4, SR), colon cancer (SW-620), CNS cancer (SF-539), and melanoma (SK-MEL-5) cell lines. In the same paper , the high cytotoxicity of 3-((Z)-5-((Z)-2-chloro-3-(4-nitrophenyl)allylidene)-4-oxo-2-thioxothiazolidin-3-yl)propanoic acid 13 against cell lines of gastric cancer (AGS), human colon cancer (DLD-1), and breast cancers (MCF-7 and MDA-MB-231), with values of GI 50 2.69, 3.67, 3.62, and 1.63 µM, respectively, was established. Finiuk et al. reported on ciminalum–4-thiazolidinone hybrids containing phenyl-pyrrolidine-2,5-dione moieties in the molecules. The hit-compounds 14 and 15 , possessing micromolar cytotoxic activity towards leukemia, colon cancer, CNS, and ovarian cancer cell lines, were identified following a 60 lines NCI protocol with total MG_MID GI 50 values of 1.76 and 1.73 μM, respectively. Treatment by 14 and 15 led to the significant inhibition of T-leukemia cells of the Jurkat line, with high selectivity indices of 29.4 and 56.6, respectively. Hybrids 14 and 15 altered the levels of mitochondrial apoptosis-associated proteins (Bax and EndoG, Bcl-2) and caused apoptosis toward human T-leukemia cells of the Jurkat line. However, the application of 14 and 15 did not affect the morphology and the DNA intactness in mitogen-activated lymphocytes of the peripheral blood of healthy human donors. Türe et al. reported on the design and synthesis of a series of novel hybrid molecules containing imatinib (Gleevec) moiety. Imatinib was the first-in-class protein kinase inhibitor approved by the FDA in 2001 and had a revolutionary impact on the treatment of most cases of chronic myeloid leukemia (CML) . Obtained by Türe et al., 5-benzylidene-2-arylimino-4-thiazolidinone-bearing imatinib analogs were screened for their antimitotic activity on K562 (chronic myeloid leukemia), PC3 (prostate cancer), and SHSY-5Y (neuroblastoma) cell lines, and the three most potent cytotoxic hybrids, 1–3 , were identified. Compounds 1–3 induced apoptotic cell death. Moreover, cycle arrest in the G0/G1 phase was caused by compounds 2 and 3 , while compound 1 inhibited the cell cycle in the G2/M phase. Hybrid molecules 1 and 3 proved to have stronger genotoxic effects than imatinib against K562 cells . Recent decades have been marked by an increased interest in the use of potential NSAIDs for the treatment of cancer or using NSAIDs scaffolds/molecules for the design of new antimitotic agents . Ramadan W.S. et al. used a hybridization approach involving anti-inflammatory drug-5-aminosalicylic acid and 5-ylidene-4-thiazolidinone scaffolds with the aim of designing new promising anti-cancer agents . Synthesized hybrids were tested on a panel of seven cancer cell lines, and two molecules, 4 and 5 , were found to be efficient in some types of cancer compared to the effect of doxorubicin (reference drug), with the highest activity level detected on the MCF7 line, with IC 50 values of 0.31 and 0.30 µM, respectively. Furthermore, tumor specificity and minimal effects on normal fibroblasts were observed for 4 and 5 . In vitro studies of the molecular mechanisms of action for 4 and 5 revealed the induction of DNA damage, cell cycle arrest in the G2/M phase, and the induction of apoptosis as indicated by annexin-V staining and the activation of caspases. Moreover, it was found that both compounds modulate the expression and activity of several factors in the DNA damage response pathway, cyclins/cyclin-dependent kinases, and CDC25 phosphatase. NSAID–diclofenac was used for the design of potential anticancer agents by Shepeta et al. . A series of diclofenac-4-thiazolidinones hybrids with a hydrazine linker in the molecules were synthesized and tested on antitumor activity in a 60 line screening program (DTP NCI) . Two novel hybrids, 6 and 7 , displayed slight anticancer activity, and an in vitro cytostatic effect was observed on the leukemia CCRF-CEM, with a percentage of growth (GP%) of 56.82% for molecule 6 , on the non-small-cell lung cancer NCIH522, with a GP of 54.32%, and on colon cancer HCT-116, with a GP% of 57.71% of cell lines for hybrid 7 . Holota et al. reported on pyrazolin-5-one bearing 4-thiazolidinone hybrid 8 with moderate anticancer activity, with GP% values of 68 % and 87 % on the NCI-H460 (Lung cancer) and SF-268 (CNS cancer) lines, respectively, at 10 μM concentration. A series of novel 4-thiazolidinone-sulfanilamide hybrids incorporating substituted indolin-2-one moieties were designed as possible human carbonic anhydrase (hCA) inhibitors by Eldehna et al. . The new hybrids were evaluated in vitro for their inhibitory activity against hCA I, II, IV, and IX, and all molecules were active in variable degrees. Moreover, all compounds were examined for their anti-proliferative activity against breast cancer MCF-7 and colorectal cancer Caco-2 cell lines, and hybrid 9 was found to be the most potent against MCF-7, with an IC 50 of 3.96 ± 0.21 µM. In-depth studies showed that hybrid 9 provoked the intrinsic apoptotic mitochondrial pathway in MCF-7 cells, which was evidenced by the enhanced expression of the pro-apoptotic protein Bax and the reduced expression of the anti-apoptotic protein Bcl-2 as well as up-regulated active caspase-3 and caspase-9, cytochrome C, and p53 levels. Multifunctional sulfanilamide-bearing hybrids were developed and tested against HepG2 and MDA-MB-231 cancer cell lines by Sunil Kumar et al. . Among the tested hybrids, compound 10 was identified as potent against the MBA-MB-231 cell line and showed the highest cytotoxic activity, with an IC 50 value of 17.45 µM, which was higher than in the case of the standard drug cisplatin. Special attention from the point of view of analog- and fragment-based anticancer drug design is warranted in the case of the molecule ciminalum, which is a p -nitro-α-chlorocinnamic aldehyde or (2 Z )-2-chloro-3-(4-nitrophenyl)prop-2-enal (CAS 3626-97-9) and was used as a drug in medical practice in the former Soviet Union as an active antimicrobial agent against Gram-positive and Gram-negative microorganisms. The diversity-oriented approach was applied for the synthesis of ciminalum-4-thiazolidinone hybrid molecules, and a series of derivatives were reported by Buzun and Finiuk . For such a hybrid type, SAR analysis revealed that the presence of carboxylic acids , p-hydroxyphenyl , or (4-hydroxyphenyl)-pyrrolidine-2,5-dione substituents at position 3 of the 4-thiazolidinone ring determines the most effective anti-tumor activity, while the absence of a substituent or presence of an additional ciminalum substituent at position 3 leads to a weakening in activity. Among the synthesized and screened hybrids, derivative 11 was cytotoxic toward MCF-7 and MDA-MB-231 breast cancer cell lines, with IC 50 values of 5.02 µM and 15.24 µM, respectively . The hybrid 11 induced the extrinsic and intrinsic apoptotic pathways and caused a reduction in topoisomerase II concentration in both tested human breast cancer cell lines. The affinity of hybrid 11 to topoisomerase II was also confirmed by docking simulations. In addition, molecule 11 caused a decrease in the levels of Beklin-1, LC3A (the microtubule-associated protein 1A/1B light chain 3A), and LC3B (the microtubule-associated protein 1A/1B light chain 3B), suggesting its influence on the autophagy process. A ciminalum–4-thiazolidinone hybrid 12 possessed a high activity level in NCI 60-Cell-line screening (MG_MID GI 50 = 1.57 µM and TGI = 13.3 µM). The analysis of activity inside cancer panels revealed a certain sensitivity profile in the GI 50 concentration range of < 0.01–0.02 µM toward leukemia (MOLT-4, SR), colon cancer (SW-620), CNS cancer (SF-539), and melanoma (SK-MEL-5) cell lines. In the same paper , the high cytotoxicity of 3-((Z)-5-((Z)-2-chloro-3-(4-nitrophenyl)allylidene)-4-oxo-2-thioxothiazolidin-3-yl)propanoic acid 13 against cell lines of gastric cancer (AGS), human colon cancer (DLD-1), and breast cancers (MCF-7 and MDA-MB-231), with values of GI 50 2.69, 3.67, 3.62, and 1.63 µM, respectively, was established. Finiuk et al. reported on ciminalum–4-thiazolidinone hybrids containing phenyl-pyrrolidine-2,5-dione moieties in the molecules. The hit-compounds 14 and 15 , possessing micromolar cytotoxic activity towards leukemia, colon cancer, CNS, and ovarian cancer cell lines, were identified following a 60 lines NCI protocol with total MG_MID GI 50 values of 1.76 and 1.73 μM, respectively. Treatment by 14 and 15 led to the significant inhibition of T-leukemia cells of the Jurkat line, with high selectivity indices of 29.4 and 56.6, respectively. Hybrids 14 and 15 altered the levels of mitochondrial apoptosis-associated proteins (Bax and EndoG, Bcl-2) and caused apoptosis toward human T-leukemia cells of the Jurkat line. However, the application of 14 and 15 did not affect the morphology and the DNA intactness in mitogen-activated lymphocytes of the peripheral blood of healthy human donors. The structural motifs of natural products always serve as an excellent source for drug-like molecules from the perspective of the design of anticancer agents . 3.1. Monoterpene–4-Thiazolidinone Hybrids Fawzi et al. synthesized 4-acetyl-1-methylcyclohexenothiosemicarbazones and 4-acetyl-1-methylcyclohexeno-2-imino-4-thiazolidinone hybrids based on a monoterpene backbone structure, that of limona ketone, containing hydrazone linker in the molecules . The cytotoxicity of the obtained compounds was evaluated on HT-1080, A549, and MCF-7 cell lines. Compounds 16 and 17 proved to be the most cytotoxic on HT-1080 lines, demonstrating IC 50 s of 15.85 µM and 16.13 µM, respectively. Through molecular docking, these compounds were found to form stable ligand-caspase-3 complexes. In addition, compound 17 was revealed to be the most potent in generating apoptosis and caspases-3/7 activation, including S-phase cell cycle inhibition in HT-1080 cells, while compound 16 exhibited a lower degree of apoptosis induction compared to compound 17 , in turn inducing G0/G1 phase arrest in the same cells. Oubella et al. developed hybrids containing the monoterpene-carvone skeleton and 4-thiazolidinone scaffolds linked by the 1,2,3-triazole ring . The novel hybrids were screened for their anticancer activity against four cell lines: breast MCF-7 and MDA-MB-231, lung A-549 and fibrosarcoma HT-1080. The highest cytotoxic activity was demonstrated by compounds 18 and 19 . Expanding the study, the researchers proved that such activity is generated through the induction of apoptosis via caspase-3, as confirmed by molecular docking, and effects on the cell cycle, specifically arresting cells in S and G2/M phases in HT-1080 and A-549 cells, respectively. Applying thymol as part of the structure of novel hybrids with 4-thiazolidinone scaffolds is a promising approach. A synthesis and anticancer activity evaluation of a series of thymol–4-thiazolidinone hybrids was reported by El-Miligy et al. . Among the new hybrids compounds, 20–22 exhibited the highest activity against human colorectal cancer (CRC) cell lines (Caco-2 and HCT-116) at doses less than their EC 100 on normal human cells. Furthermore, compounds 21 and 22 induced apoptosis-dependent death and caspase activation by >50% in human CRC cell lines. Furthermore, compounds 20–22 showed in vitro inhibitory activity against both PIM-1/2 kinases comparable to the reference, staurosporine. 3.2. Coumarin 4-Thiazolidinones Hybrids The application of the coumarin motif is an attractive direction in anticancer drug design . Following this strategy, Sigalapalli et al. reported the synthesis of novel molecular hybrids of 4-thiazolidinone–umbelliferone (7-hydroxycoumarin) as prominent cytotoxic agents. The most active derivative, 23 , showed the highest potency against A549 cells, with an IC 50 value of 0.96 ± 1.09 µM and a selectivity index of 51.7. The in-depth study of hybrid 23 showed apoptosis induction by the annexin-v/PI dual staining assay; its effect on different phases of the cell cycle; the inhibition of tubulin polymerization at an IC 50 value of 2.65 ± 0.47 µM; and its effective binding with CT-DNA. In silico experiments revealed a prominent binding affinity towards the α/β-tubulin receptor with remarkable protein–ligand interactions and binding energy in the case of 23 . Thacker et al. reported the synthesis of coumarin–4-thiazolidinone hybrids with pyrazole linker in the molecules as potential hCA inhibitors. The results obtained by the authors indicated the selective inhibition by synthesized hybrids of the tumor-associated isoforms hCA IX and XII but not in the case of the off-target isoforms, hCA I and II. Compound 24 , with the best hCA XII inhibition constant value, 61.5 nM, was considered the lead compound for further developing selective and potent hCA IX inhibitors. The synthesis and evaluation of antiproliferative activity in A549 (lung cancer), MDA-MB-231 and BT-474 (breast cancer), HepG2 (liver cancer), and HCT-116 (colon cancer) cell lines using an MTT of coumarin-2–iminothiazolidin-4-one hybrids were reported by Sigalapalli et al. . Hybrid molecule 25 showed excellent anti-proliferative activity on the breast cancer cell lines MDA-MB-231 and BT-474 (IC 50 of 0.95 ± 1.88 and 1.22 ± 0.08 µM, respectively) and lung cancer cell line A549 (IC 50 = 1.28 ± 0.98 μM). The cell cycle analysis disclosed that 25 showed significant G2/M phase arrest in MDA-MB-231 cells. Furthermore, hybrid 25 significantly inhibited tubulin polymerization, with an IC 50 value of 3.54 ± 0.2 µM, and caused apoptosis-mediated cell death in MDA-MB-231 cells. In silico studies inferred that hybrid 25 binds at the colchicine binding site of the tubulin, with prominent binding affinity. 3.3. Hybrids of 4-Thiazolidinones with Steroidal Skeleton Steroids are important and physiologically significant natural compounds, opening up the possibility of structural tuning with the aim of achieving and developing valuable pharmacological properties including potent anticancer activity . Živković et al. designed a series of mono- and bis-4-thiazolidinone-containing hybrids with androstene derivatives. For the synthesized hybrids, anticancer activity studies were performed on six cancer lines: HeLa (cervical adenocarcinoma), K562 (chronic myelogenous leukemia), MDA-MB-453 (breast carcinoma), MDA-MB-361 (breast adenocarcinoma), LS174 (colon adenocarcinoma), A549 (lung carcinoma), and MRC-5 (normal lung fibroblast line). All the obtained molecules exhibited selective concentration-dependent cytotoxicity on all tested lines. The strongest response to the tested compound was observed on the K562 and HeLa cell lines, where the IC 50 of the majority oscillated around 10 µM, with the IC 50 of the cisplatin reference compound for these lines being 5.7 µM and 5.2 µM, respectively. Compared to the positive control, these compounds exhibited lower toxicity to normal cells. Hybrids 26 and 27 were found to be the most active and inhibited the cell cycle in HeLa cells in subG1, S, and G2/M phases and induced apoptosis by an intrinsic and extrinsic pathway. Fawzi et al. synthesized 4-acetyl-1-methylcyclohexenothiosemicarbazones and 4-acetyl-1-methylcyclohexeno-2-imino-4-thiazolidinone hybrids based on a monoterpene backbone structure, that of limona ketone, containing hydrazone linker in the molecules . The cytotoxicity of the obtained compounds was evaluated on HT-1080, A549, and MCF-7 cell lines. Compounds 16 and 17 proved to be the most cytotoxic on HT-1080 lines, demonstrating IC 50 s of 15.85 µM and 16.13 µM, respectively. Through molecular docking, these compounds were found to form stable ligand-caspase-3 complexes. In addition, compound 17 was revealed to be the most potent in generating apoptosis and caspases-3/7 activation, including S-phase cell cycle inhibition in HT-1080 cells, while compound 16 exhibited a lower degree of apoptosis induction compared to compound 17 , in turn inducing G0/G1 phase arrest in the same cells. Oubella et al. developed hybrids containing the monoterpene-carvone skeleton and 4-thiazolidinone scaffolds linked by the 1,2,3-triazole ring . The novel hybrids were screened for their anticancer activity against four cell lines: breast MCF-7 and MDA-MB-231, lung A-549 and fibrosarcoma HT-1080. The highest cytotoxic activity was demonstrated by compounds 18 and 19 . Expanding the study, the researchers proved that such activity is generated through the induction of apoptosis via caspase-3, as confirmed by molecular docking, and effects on the cell cycle, specifically arresting cells in S and G2/M phases in HT-1080 and A-549 cells, respectively. Applying thymol as part of the structure of novel hybrids with 4-thiazolidinone scaffolds is a promising approach. A synthesis and anticancer activity evaluation of a series of thymol–4-thiazolidinone hybrids was reported by El-Miligy et al. . Among the new hybrids compounds, 20–22 exhibited the highest activity against human colorectal cancer (CRC) cell lines (Caco-2 and HCT-116) at doses less than their EC 100 on normal human cells. Furthermore, compounds 21 and 22 induced apoptosis-dependent death and caspase activation by >50% in human CRC cell lines. Furthermore, compounds 20–22 showed in vitro inhibitory activity against both PIM-1/2 kinases comparable to the reference, staurosporine. The application of the coumarin motif is an attractive direction in anticancer drug design . Following this strategy, Sigalapalli et al. reported the synthesis of novel molecular hybrids of 4-thiazolidinone–umbelliferone (7-hydroxycoumarin) as prominent cytotoxic agents. The most active derivative, 23 , showed the highest potency against A549 cells, with an IC 50 value of 0.96 ± 1.09 µM and a selectivity index of 51.7. The in-depth study of hybrid 23 showed apoptosis induction by the annexin-v/PI dual staining assay; its effect on different phases of the cell cycle; the inhibition of tubulin polymerization at an IC 50 value of 2.65 ± 0.47 µM; and its effective binding with CT-DNA. In silico experiments revealed a prominent binding affinity towards the α/β-tubulin receptor with remarkable protein–ligand interactions and binding energy in the case of 23 . Thacker et al. reported the synthesis of coumarin–4-thiazolidinone hybrids with pyrazole linker in the molecules as potential hCA inhibitors. The results obtained by the authors indicated the selective inhibition by synthesized hybrids of the tumor-associated isoforms hCA IX and XII but not in the case of the off-target isoforms, hCA I and II. Compound 24 , with the best hCA XII inhibition constant value, 61.5 nM, was considered the lead compound for further developing selective and potent hCA IX inhibitors. The synthesis and evaluation of antiproliferative activity in A549 (lung cancer), MDA-MB-231 and BT-474 (breast cancer), HepG2 (liver cancer), and HCT-116 (colon cancer) cell lines using an MTT of coumarin-2–iminothiazolidin-4-one hybrids were reported by Sigalapalli et al. . Hybrid molecule 25 showed excellent anti-proliferative activity on the breast cancer cell lines MDA-MB-231 and BT-474 (IC 50 of 0.95 ± 1.88 and 1.22 ± 0.08 µM, respectively) and lung cancer cell line A549 (IC 50 = 1.28 ± 0.98 μM). The cell cycle analysis disclosed that 25 showed significant G2/M phase arrest in MDA-MB-231 cells. Furthermore, hybrid 25 significantly inhibited tubulin polymerization, with an IC 50 value of 3.54 ± 0.2 µM, and caused apoptosis-mediated cell death in MDA-MB-231 cells. In silico studies inferred that hybrid 25 binds at the colchicine binding site of the tubulin, with prominent binding affinity. Steroids are important and physiologically significant natural compounds, opening up the possibility of structural tuning with the aim of achieving and developing valuable pharmacological properties including potent anticancer activity . Živković et al. designed a series of mono- and bis-4-thiazolidinone-containing hybrids with androstene derivatives. For the synthesized hybrids, anticancer activity studies were performed on six cancer lines: HeLa (cervical adenocarcinoma), K562 (chronic myelogenous leukemia), MDA-MB-453 (breast carcinoma), MDA-MB-361 (breast adenocarcinoma), LS174 (colon adenocarcinoma), A549 (lung carcinoma), and MRC-5 (normal lung fibroblast line). All the obtained molecules exhibited selective concentration-dependent cytotoxicity on all tested lines. The strongest response to the tested compound was observed on the K562 and HeLa cell lines, where the IC 50 of the majority oscillated around 10 µM, with the IC 50 of the cisplatin reference compound for these lines being 5.7 µM and 5.2 µM, respectively. Compared to the positive control, these compounds exhibited lower toxicity to normal cells. Hybrids 26 and 27 were found to be the most active and inhibited the cell cycle in HeLa cells in subG1, S, and G2/M phases and induced apoptosis by an intrinsic and extrinsic pathway. Hybrids with 4-thiazolidinone scaffolds as potent anticancer agents are the most intensively studied type of hybrids in recent years and represents the largest group of molecules among recently published data. 4.1. Furan–4-Thiazolidinone Hybrids Tahmasvand et al. reported on the design and synthesis of eight novel 4-thiazolidinone hybrids which were evaluated for their in vitro anticancer activity against MDA-MB-231, HT-29, and HepG2 cell lines. The furan-bearing hybrid 28 demonstrated very strong activity against the three cell lines after 72 h with IC 50 values of 1.9 µM, 6.5 µM, and 5.4 µM, respectively, which was comparable to the control sample with the reference compound doxorubicin. Hybrid 28 induced apoptosis through the regulation of pro-caspase 3 and cell cycle arrest in the G1/S phase. In addition, compound 28 downregulated MMP-9 mRNA expression in MDA-MB-231 cells. In vivo studies performed for hybrid 28 on mouse line 4T1 demonstrated a dose-dependent reduction in mammary tumor growth without weight loss in the test model. 4.2. Pyrrole–4-Thiazolidinone Hybrids A pyrrole core was used as a pharmacophore in the design of potential antimitotic agents by Shawky et al. . The synthesized hybrid molecules 29–31 exhibited potent cytotoxicity, with an IC 50 of 0.10–0.60 µM against three cancer cell lines: MCF-7, A2780, and HT29. Additional studies showed that hybrid 29 induced G1 cell cycle arrest and apoptosis in MCF-7 cells and displayed inhibitory activity against CDK2, with an IC 50 of 0.63 µM. The pyrrolidine-2,5-dione–4-thiazolidinone hybrid 32 was reported by Finiuk et al. . Compound 32 exhibited moderate activity in the 60 lines screening DTP NCI , with a GP% value of 68.20 % on the MDA-MB-445 (Melanoma) cell line and with a GI 50 value of 47.50 µM towards the HeLa cell line. Additionally, hybrid 32 demonstrated low toxicity towards normal human keratinocytes of the HaCaT line, with a GI 50 value of >100 μM. 4.3. Pyrazole–4-Thiazolidinone Hybrids A series of 4-thiazolidinone-pyrazole hybrids connected via a ylidene linker were synthesized by Bhat et al. . An in vitro screening of the synthesized hybrids revealed that compounds 33 and 34 exhibited potent anticancer properties against the MDA-MB-231 cell line, with IC 50 values 24.6 and 29.8 μM, respectively (MTT assay). Furthermore, molecule 34 exhibited superior protection of normal HDF cells than 33 . Additionally, the anticancer potency of the compounds was justified by using in silico studies. SAR analysis concluded by the authors suggests the importance of the presence of dichlorosubstituted arylamino moiety in position two of the 4-thiazolidinone core in enhancing potency. Mushtaque et al. reported on the synthesis and anticancer assessment of a pyrazole-bearing hybrid molecule, 35 . Docking studies for the hybrid 35 revealed that the molecule could interact through the minor groove of DNA. Additionally, MTT-assay data showed that compound 35 was non-toxic up to concentrations of 282.32 µg/mL against the cancerous MCF-7 cell line and 200 µg/mL against Siha cells. 4.4. Pyrazole-Purine–4-Thiazolidinone Hybrids Hybrids containing pyrazole, purine, and 4-thiazolidinone scaffolds were developed by Afifi et al. as potential anticancer agents. The most potent cytotoxic activity among all the analyzed hybrids was shown by compound 36 , with IC 50 values of 18.85 µM, 23.43 µM, 23.08 µM, 23.08 µM, and 18.50 µM for the A549, MCF-7, HepG-2, Caco-2, and PC-3 cell lines, respectively, whereas the values for the reference compound 5-fluorouracil oscillated around 90 µM. As with cytotoxic activity, compound 36 showed the strongest antioxidant properties; however, these were slightly weaker than in the case of the reference compound, ascorbic acid. 4.5. Pyrazole-Piperazine–4-Thiazolidinone Hybrids In study , new pyrazole-based 4-thiazolidinones hybrids linked with piperazine moiety were reported as promising selective VEGFR2 tyrosine kinase inhibitors. Among all the tested compounds, the derivatives 37–39 were found to be the most active and selective against the HepG-2 cancer cell line, with IC 50 values 0.06 ± 0.003 µM, 0.03 ± 0.006 µM, and 0.06 ± 0.004 µM, respectively, and with the significant selectivity indices: 8.09, 11.40, and 4.37, respectively. Also, the synthesized hybrids showed potent VEGFR2 tyrosine kinase inhibitory activities, with lower IC 50 values than that of the reference drug, staurosporine, with this potency being confirmed by additional docking studies which demonstrated that 37–39 could act as inhibitors of VEGFR2 tyrosine kinase via the stabilization of the enzyme inactive DFG-out conformation. 4.6. Pyrazoline-Pyrrole–4-Thiazolidinone Hybrids Safaa I. Elewa et al. reported the synthesis and in vitro and in silico study of novel pyrazoline–4-thiazolidinone hybrids with a pyrrole ring in the molecules. The newly synthesized derivatives 40 and 41 exhibited remarkable cytotoxic activities with promising IC 50 values in terms of cytotoxicity against MCF-7 and HCT-116 cells using the MTT assay. Hybrid 41 exhibited potent cytotoxicity against MCF-7 and HCT-116 cell lines, with IC 50 values of 5.05 and 3.08 µM, compared to respective doxorubicin IC 50 values of 7.27 and 8.92 µM. Compound 40 showed a lower activity level, with IC 50 values of 15.67 on MCF-7 and 19.39 µM on HCT-116 cell lines. Both hybrids 40 and 41 were found to be nontoxic against normal WISH cells, with IC 50 values of more than 50.0 µM. Additionally, all the molecules reported in the article were screened for their binding activity toward CDK-2 kinase activity using a molecular docking study, and the obtained results suggest the tested compounds could be possible CDK-2 inhibitors. 4.7. Isoxazole–4-Thiazolidinone Hybrids The synthesis of the hybrid 2-(4-fluorophenyl)-3-(5-methylisoxazol-3-yl)thiazolidin-4-one, 42 , as a potential antimitotic agent was reported by Ramesh et al. . The results of an in vitro cytotoxicity assessment employing the MTT assay as per the ATCC protocol, using three human cancer cell lines, HeLa (cervical cancer), MCF-7 (breast cancer), A549 (human lung cancer), and HEK-293 (normal human embryonic kidney cells), indicated that hybrid 42 exhibited excellent anticancer activity against MCF7 and displayed less cytotoxicity towards normal HEK293 cell lines. Hybrid molecule 42 inhibited the cell proliferation of HeLa by 58%, 87%, and 94% at 6.25 µM, 25 µM, and 50 µM concentrations, respectively. In terms of inhibition, 59% and 65% inhibition were observed at a 50 µM concentration on breast cancer (MCF7) and lung cancer (A549) cell lines, respectively, by compound 42 . At lower concentrations, compound 42 has less effect on normal cell lines (HEK293). Additionally, a molecular docking study explored the binding mode and possible interactions between the synthesized compound and the ATP binding site of the EGFR kinase domain. 4.8. Thiazole–4-Thiazolidinone Hybrids A series of 5-enamine–4-thiazolidinones with phenylalanine moiety in the molecules was designed and reported by Holota et al. . Among the synthesized derivatives, the hybrid 43 , with a thiazole-bearing scaffold in the molecule, was found to be highly active in the 60 lines screening. Compound 43 demonstrated inhibition activity against (GI 50 < 10 μM) against all 59 human tumor cell lines, with average GI 50 /TGI/LC 50 values of 2.57/57.27/94.71 μM, respectively. Preliminary SAR provided by the authors revealed that the presence of thiazole substituent is crucial for anticancer activity whereas a change in the hydrogen atom, aniline derivatives, or 1,2,4-triazole nucleus leads to the disappearance of the effect. 4.9. Triazole–4-Thiazolidinone Hybrids Two series of merged 1,2,4-triazole–4-thiazolidinone hybrids with ylidene and enamine linkers in the molecules were designed and synthesized by Holota et al. . The obtained hybrids were studied for their antitumor activity in an NCI 60 lines screening and a number of the compounds presented excellent anticancer properties at 10 µM. Derivatives 44 and 45 were found to be the most active against cancer cell lines, with total mean GI 50 values of 3.54 µM ( 44 ) and 10.96 µM ( 45 ), without causing toxicity to normal somatic HEK293 cells, with IC 50 values of 28.99 µM ( 44 ) and 24.43 µM ( 45 ). An SAR analysis performed by authors revealed that both the presence and position of a chlorine atom in the benzylidene area of molecules play a crucial role in the realization of the anticancer effect . 4.10. Pyridine–4-Thiazolidinone Hybrids A series of 17 novel pyridine-thiazolidinone hybrids were synthesized, characterized, and evaluated as potential hCA inhibitors by Ansari et al. . Of all the synthesized hybrids, derivatives 46 and 47 had the most potent CAIX inhibition activity in the esterase assay, with IC 50 values of 1.61 µM and 1.84 µM, respectively. The evaluated cytotoxicity for 46 and 47 on a HEK-293 was 249.6µM and 230.4µM, respectively. The evaluated anticancer activities against MCF-7 (breast cancer cell line) and HepG-2 (liver cancer cell line) were IC 50 values of 13.0 µM and 19.2 µM, respectively, for hybrid 46 and values of 12.4 µM and 16.2 µM, respectively, for 47 . In , the synthesis and study of molecules 48 and 49 , as modified analogues of hybrids 46 and 47, was reported. The authors applied the bioisosteric replacement of the pyridine core by the substituted benzene ring for the design of novel target molecules with desirable anticancer properties. Despite the promising evaluated in silico features, the newly synthesized analogues 48 and 49 were found to be less active compared to the hybrids 46 and 47 against the HepG-2 cell line. The molecular hybridization approach was applied for the synthesis of pyridine–4-thiazolidinone hybrids with aim of the synthesis of potential antiglioblastoma agents by Campos et al. . Among sixteen synthesized compounds, derivatives 50–52 displayed potent antitumor activities against the tested glioblastoma cell lines and exhibited IC 50 values 2.17, 6.24, and 2.93 μM, respectively, in the C6 cell line, well below the standard drug temozolomide. The mechanism of action studies demonstrated that derivatives 50 and 52 induced apoptosis, significantly increasing the percentage of cells in the Sub-G1 phase in the absence of necrosis. Consistent with these results, the caspase-3/7 assay revealed that derivative 50 presents pro-apoptotic activity due to the significant stimulation of caspases-3/7. Moreover, hybrids 50–52 increased antioxidant defense, decreased reactive oxygen species (ROS) production, and modulated redox status. 4.11. Pyridine-Piperazine–4-Thiazolidinone Hybrids The attempt to design potential antimitotic agents following the hybridization of pyridine, piperazine, and 4-thiazolidinone scaffolds was reported by Demirci et al. . The synthesized hybrids were evaluated on the PC-3, DU145, and LNCaP prostate cancer cell lines. All the studied molecules possessed satisfactory calculated pharmacokinetic properties. Compound 53 showed the most potent activity level inside the tested series, with an IC 50 of 36.75 µM on the PC-3 cancer line, while the other cancer cells tested showed no response to the compounds used (IC 50 > 500 µM). 4.12. Pyridine-Thiazole–4-Thiazolidinone Hybrids Hussein et al. applied a hybrid-pharmacophore approach for the design of novel biologically active 4-thiazolidinones. Among the synthesized molecules, compound 54 exhibited the most potent cytotoxic activity and was found to be more effective on the WI-38 normal human lung fibroblast cell line, with an IC 50 of 92 µg/mL, but not as effective on the A549 and MDA-MB-31 cancer cells, with IC 50 values of 357 µg/mL and 505 µg/mL, respectively. 4.13. Indole–4-Thiazolidinone Hybrids Indole scaffolds are often used for the design and development of 4-thiazolidinone hybrids as anticancer agents. Sigalapalli et al. reported on the synthesis of a small library of hybrid molecules containing 4-thiazolidinone and indole scaffolds linked by an aliphatic linker with aim of the designing tubulin polymerization inhibitors. The novel compounds were tested on five human cell lines of the lung (A549, NCI-H460), breast (MDA-MB-231), and colon (HCT-29, HCT-15), using podophyllotoxin as a reference compound. The synthesized compound 55 showed the strongest activity against both colon cancer cell lines, with an IC 50 value of 0.92µM for HCT-15. Meanwhile, against the normal human lung epithelial cell line (L132), the IC 50 value for the compound was 10.84 µM, indicating that compound 55 is 10-fold more selective against the colon cell line. SARs analysis performed by the authors revealed that the antiproliferative activity of phenethyl-thiazolidinone-indole hybrids is higher than that of benzyl-thiazolidinone-indole ones. Furthermore, it was observed that hybrids without a substituent at the nitrogen atom into indole core are more active than N-alkyl/aryl-substituted ones. In addition, the presence of the methoxy group at the phenyl ring of the side chain of hybrid compounds leads to higher activity than halogen substituents. Extended analyses on compound 55 revealed that the compound inhibited the cell cycle of HCT-15 cells in sub G1 and G2/M phases, additionally inhibited tubulin more strongly compared to the reference compound, induced intracellular ROS, and decreased the mitochondrial potential, causing cell death by apoptosis . Oliveira et al. reported on the synthesis of novel 4-thiazolidinone derivatives with an indole backbone. Hybrid 56 possessed the most potent anticancer activity and was active against the MCF-7 cell line, with an IC 50 of 6.06 µM, the OVCAR-3 cell line, with an IC 50 of 5.12 µM, and the HaCat cell line, with IC 50 of 6.23 µM. A series of novel indole-azolidinone hybrids with 5-fluoro-3-formyl-1 H -indole-2-carboxylic acid methyl ester scaffolds were synthesized via the Knoevenagel reaction . Among the synthesized compounds, hybrid 57 was found to be the most active and exhibited toxicity in the 60 lines screening, with total GI 50 of 0.45/0.65 µM and with IC 50 values toward cancer cells MCF-7-0.70 µM, HCT116-0.80 µM, A549-9.70 µM, and HepG2-12.00 µM. Meanwhile, the non-malignant cells (human keratinocytes of HaCaT line and murine embryonic fibroblasts of Balb/c 3T3 line) possessed moderate sensitivity to hybrid 57 . Furthermore, compound 57 induced apoptosis in studied tumor cells via caspase-3-, PARP1-, and Bax-dependent mechanisms; however, it did not affect the G1/S transition in HepG2 cells. Additionally, hybrid 57 impaired nuclear DNA in HepG2, HCT116, and MCF-7 cells without intercalating this biomolecule, but much fewer DNA damage events were induced by 57 in normal Balb/c 3T3 fibroblasts compared with HepG2 carcinoma cells. 4.14. Isatine–4-Thiazolidinone Hybrids Isatin is an endogenously occurring molecule in human tissues, based on the structure of which tyrosine kinase inhibitor Sunitinib (Sutent ® ) was established. Sunitinib was approved by the FDA in 2006 for the treatment of the imatinib-resistant cancers advanced metastatic renal cell carcinoma and gastrointestinal stromal tumors. El-Naggar et al. reported a series of isatine–4-thiazolidinone hybrids, among which molecule 58 possessed strong cytotoxicity, with IC 50 values of 7.6 µM and 8.4 µM on the MDA-MB-231 and MCF-7 cell lines, respectively. Furthermore, compound 58 was active on WI-38 (nontumorigenic human lung fibroblast cell line) and MCF-10A (human breast epithelial cell line), with IC 50 values of 49.1 µM and 73.1 µM, respectively. In addition, hybrid 58 significantly induced the expression of the pro-apoptotic protein Bax, inhibited the expression of the anti-apoptotic protein Bcl-2, and increased the level of caspase-3 compared to the control sample. Fouad et al. developed a series of isatine–4-thiazolidinone conjugates as potential antimitotic agents. Compound 59 was effective against colorectal cancer cell line KM12, melanoma cell line UACC-62, ovarian cancer cell line IGROV1, cancer cell line SK-OV-3, and renal cell carcinoma lines (A498, ACHN, CAKI-1, RXF393, and UO-31). Compounds’ activity towards CAKI-1 and UO-31, with IC 50 values of 4.74 and 3.99 µM, equal to the cytotoxic potency of the reference compound sunitinib. The derivative 59 arrested the cell cycle in the G2/M and pre-G1 phase and inhibited cyclin-dependent kinase (CDK) activity. In addition, in silico and in vivo studies demonstrated that compound 59 has an excellent physicochemical and pharmacokinetic profile (which PK and docking can develop). Szychowski et al. reported studies on the anticancer potential of an isatine–4-thiazolidinone hybrid modified with a 3,5-diaryl-2-pyrazoline scaffold 60 . The impact of hybrid 60 on cytotoxicity, the apoptotic process, and metabolism in the human squamous carcinoma (SCC-15) cell line was evaluated. The results obtained by the authors showed that the studied molecule 60 exhibits both cytotoxic and proapoptotic properties at a 10–100 µM concentration range. The activation of caspase-3 was caused by 60 and was accompanied by an LDH release and resazurin reduction. Additionally, increased DCF fluorescence in a wide range of concentrations after 6, 24, and 48 h of exposure was observed after treatment with 60, which suggests the stimulation of ROS production. The properties of 60 established by the authors make it a promising tool for further research as an anti-cancer agent. 4.15. Quinoline–4-Thiazolidinone Hybrids Batran et al. reported on the synthesis of quinoline–4-thiazolidinone hybrids as potential antimitotic agents. Molecule 61 was active against the MCF-7 breast cancer cell line, with an IC 50 value of 98.79 µM. Nafie et al. studied another series of quinolone–4-thiazolidinone hybrids. Five of the ten compounds showed strong cytotoxic activity against the HCT-116 cell line, comparable to 5-FU, while compound 62 was the most potent cytotoxic, excluding effects on normal intestinal FHC cells. The compound’s inhibitory activity against EGFR was also confirmed, where it acted at a similar level to the reference compound erlotinib. In addition, hybrid 62 caused the induction of apoptosis and cell cycle arrest in the G2 and S phases. Moreover, it was confirmed to increase the expression levels of p53, PUMA, Bax, caspase-3, -8, and -9 protein genes, and the downregulation of Bcl-2. In in vivo studies, the LD 50 value was established, which was 6 mg/kg BW. It was observed that the use of this hybrid causes a reduction in tumor size comparable to 5-FU (the inhibition ratio was 52.92% for 62 and 57.16% for 5-FU), with the preservation of biochemical and histochemical structures being close to normal. A new series of quinolone–4-thiazolidinone hybrid molecules were reported by Kumar et al. . All the compounds were screened in vitro for their anticancer activities against MDA-MB-231 and MCF-7 cell lines using an MTT assay. Derivative 63 was found to be the most potent against the MDA-MB-231 cell line, with an IC 50 8.16 of μM, and, at the same time, non-toxic to the human normal kidney HEK 293 cell line, with an IC 50 of 846.93 μM. Additionally, it was established in the in silico studies (docking, molecular dynamic studies) that hybrid 63 arrested the cell cycle at the G2/M phase and possesses binding properties with N-acetyl transferase (hNAT-1) protein. The authors suggest that the identified quinolinone–4-thiazolidinone hybrid 63 could be considered as a new chemotype targeting hNAT-1 and could be used for hit/lead compound generation in anticancer drug design and discovery. Qi et al. reported on the application of the hybrid-pharmacophore approach using a 4-phenoxy-6,7-dimethoxyquinoline moiety as a key part of foretinib and cabozatinib molecules in the design of novel multi-tyrosine kinase inhibitors based on 4-thiazolidinone core . Structural modification of phenyl rings A and B as well as quinoline ring C was applied in the molecular design. As a result, hit-compounds with inhibitory activity toward mesenchymale epithelial transition factor (c-Met) ( 64,65,68 ) and toward HT-29 (human colon cancer cell line) ( 66–68 ) were identified. 4.16. Quinazoline–4-Thiazolidinone Hybrids A series of hybrids with a quinazoline scaffold was synthesized by Samridhi Thakral et al. . The synthesized compounds were screened for their in vitro cytotoxic and growth-inhibitory activities against MCF-7 and Hep-G2 cell lines using the MTT assay method in comparison with the activity of the known anticancer drug doxorubicin. The hybrid with a chlorine atom at the m -position in the phenyl ring attached to the 4-thiazolidinone nucleus at position two ( 69 ) was found to be the most active against the hepatic cell line, with an IC 50 of 1.79 µg/mL. The presence of the methoxy-group at the p -position in the mentioned phenyl ring ( 70 ) leads to activity against breast cancer cell line MCF-7, with an IC 50 of 1.94 µg/mL. The IC 50 value for the standard drug in this study was found to be 0.09 µg/ml. 4.17. Benzimidazole–4-Thiazolidinone Hybrids Sharma et al. reported design and synthesis as potential apoptotic agents of a series of new benzimidazole–4-thiazolidinedione hybrid molecules. All the new twenty synthesized hybrids were evaluated for their in vitro cytotoxic potential against selected human cancer cell lines: breast (MDA-MB-231), prostate (PC-3), cervical (HeLa), lung (A549), bone (HT1080), and a normal kidney cells (HeK-293T) using the MTT assay. Eleven of the twenty described hybrids were active in the nanomolar concentration range (IC 50 values from 0.096 µM to 0.98 µM) on lung cancer (A549) cell lines, and four compounds showed a broad spectrum of cytotoxic activity on all the examined cancer cells in the range of 0.096–4.58 µM. Among them, compounds 71 and 72 were found to be the most active, with IC 50 values range on all lines (except PC-3 for 71 ) of 0.096–0.32 µM and with low cytotoxicity in the HeK-293T line, with IC 50 values of 6.76 and 6.65 µM respectively. In-depth studies of the impact of 71 and 72 on A549 lung cancer cells revealed a remarkable inhibition of cell migration through the disruption of the F-actin assembly. Moreover, treatment with 71 and 72 led to the collapse of the mitochondrial membrane potential (DJm) and increased the levels of ROS in A549 cells. Reported in were the results of different studies suggesting that such hybrids have the potential to be developed as cytotoxic agents and their structural modifications could lead to a new generation of promising anticancer agents. 4.18. Imidazopyridine–4-Thiazolidinone Hybrids Iqbal et al. reported the synthesis of two series of imidazopyridine–4-thiazolidinone hybrid molecules and an evaluation of their anticancer activity on a panel of three human cancer cell lines: MCF-7 (human breast cancer), A549 (human lung cancer), and DU145 (human prostate cancer). Among the synthesized hybrids, derivatives 73–75 were found to be the most active, with IC 50 values at the micromolar level. The preliminary SAR provided by the authors revealed that anticancer activity was connected to the R1 nature . The docking results suggested that the synthesized hybrids 73–75 could be potential EGFR kinase inhibitors. Tahmasvand et al. reported on the design and synthesis of eight novel 4-thiazolidinone hybrids which were evaluated for their in vitro anticancer activity against MDA-MB-231, HT-29, and HepG2 cell lines. The furan-bearing hybrid 28 demonstrated very strong activity against the three cell lines after 72 h with IC 50 values of 1.9 µM, 6.5 µM, and 5.4 µM, respectively, which was comparable to the control sample with the reference compound doxorubicin. Hybrid 28 induced apoptosis through the regulation of pro-caspase 3 and cell cycle arrest in the G1/S phase. In addition, compound 28 downregulated MMP-9 mRNA expression in MDA-MB-231 cells. In vivo studies performed for hybrid 28 on mouse line 4T1 demonstrated a dose-dependent reduction in mammary tumor growth without weight loss in the test model. A pyrrole core was used as a pharmacophore in the design of potential antimitotic agents by Shawky et al. . The synthesized hybrid molecules 29–31 exhibited potent cytotoxicity, with an IC 50 of 0.10–0.60 µM against three cancer cell lines: MCF-7, A2780, and HT29. Additional studies showed that hybrid 29 induced G1 cell cycle arrest and apoptosis in MCF-7 cells and displayed inhibitory activity against CDK2, with an IC 50 of 0.63 µM. The pyrrolidine-2,5-dione–4-thiazolidinone hybrid 32 was reported by Finiuk et al. . Compound 32 exhibited moderate activity in the 60 lines screening DTP NCI , with a GP% value of 68.20 % on the MDA-MB-445 (Melanoma) cell line and with a GI 50 value of 47.50 µM towards the HeLa cell line. Additionally, hybrid 32 demonstrated low toxicity towards normal human keratinocytes of the HaCaT line, with a GI 50 value of >100 μM. A series of 4-thiazolidinone-pyrazole hybrids connected via a ylidene linker were synthesized by Bhat et al. . An in vitro screening of the synthesized hybrids revealed that compounds 33 and 34 exhibited potent anticancer properties against the MDA-MB-231 cell line, with IC 50 values 24.6 and 29.8 μM, respectively (MTT assay). Furthermore, molecule 34 exhibited superior protection of normal HDF cells than 33 . Additionally, the anticancer potency of the compounds was justified by using in silico studies. SAR analysis concluded by the authors suggests the importance of the presence of dichlorosubstituted arylamino moiety in position two of the 4-thiazolidinone core in enhancing potency. Mushtaque et al. reported on the synthesis and anticancer assessment of a pyrazole-bearing hybrid molecule, 35 . Docking studies for the hybrid 35 revealed that the molecule could interact through the minor groove of DNA. Additionally, MTT-assay data showed that compound 35 was non-toxic up to concentrations of 282.32 µg/mL against the cancerous MCF-7 cell line and 200 µg/mL against Siha cells. Hybrids containing pyrazole, purine, and 4-thiazolidinone scaffolds were developed by Afifi et al. as potential anticancer agents. The most potent cytotoxic activity among all the analyzed hybrids was shown by compound 36 , with IC 50 values of 18.85 µM, 23.43 µM, 23.08 µM, 23.08 µM, and 18.50 µM for the A549, MCF-7, HepG-2, Caco-2, and PC-3 cell lines, respectively, whereas the values for the reference compound 5-fluorouracil oscillated around 90 µM. As with cytotoxic activity, compound 36 showed the strongest antioxidant properties; however, these were slightly weaker than in the case of the reference compound, ascorbic acid. In study , new pyrazole-based 4-thiazolidinones hybrids linked with piperazine moiety were reported as promising selective VEGFR2 tyrosine kinase inhibitors. Among all the tested compounds, the derivatives 37–39 were found to be the most active and selective against the HepG-2 cancer cell line, with IC 50 values 0.06 ± 0.003 µM, 0.03 ± 0.006 µM, and 0.06 ± 0.004 µM, respectively, and with the significant selectivity indices: 8.09, 11.40, and 4.37, respectively. Also, the synthesized hybrids showed potent VEGFR2 tyrosine kinase inhibitory activities, with lower IC 50 values than that of the reference drug, staurosporine, with this potency being confirmed by additional docking studies which demonstrated that 37–39 could act as inhibitors of VEGFR2 tyrosine kinase via the stabilization of the enzyme inactive DFG-out conformation. Safaa I. Elewa et al. reported the synthesis and in vitro and in silico study of novel pyrazoline–4-thiazolidinone hybrids with a pyrrole ring in the molecules. The newly synthesized derivatives 40 and 41 exhibited remarkable cytotoxic activities with promising IC 50 values in terms of cytotoxicity against MCF-7 and HCT-116 cells using the MTT assay. Hybrid 41 exhibited potent cytotoxicity against MCF-7 and HCT-116 cell lines, with IC 50 values of 5.05 and 3.08 µM, compared to respective doxorubicin IC 50 values of 7.27 and 8.92 µM. Compound 40 showed a lower activity level, with IC 50 values of 15.67 on MCF-7 and 19.39 µM on HCT-116 cell lines. Both hybrids 40 and 41 were found to be nontoxic against normal WISH cells, with IC 50 values of more than 50.0 µM. Additionally, all the molecules reported in the article were screened for their binding activity toward CDK-2 kinase activity using a molecular docking study, and the obtained results suggest the tested compounds could be possible CDK-2 inhibitors. The synthesis of the hybrid 2-(4-fluorophenyl)-3-(5-methylisoxazol-3-yl)thiazolidin-4-one, 42 , as a potential antimitotic agent was reported by Ramesh et al. . The results of an in vitro cytotoxicity assessment employing the MTT assay as per the ATCC protocol, using three human cancer cell lines, HeLa (cervical cancer), MCF-7 (breast cancer), A549 (human lung cancer), and HEK-293 (normal human embryonic kidney cells), indicated that hybrid 42 exhibited excellent anticancer activity against MCF7 and displayed less cytotoxicity towards normal HEK293 cell lines. Hybrid molecule 42 inhibited the cell proliferation of HeLa by 58%, 87%, and 94% at 6.25 µM, 25 µM, and 50 µM concentrations, respectively. In terms of inhibition, 59% and 65% inhibition were observed at a 50 µM concentration on breast cancer (MCF7) and lung cancer (A549) cell lines, respectively, by compound 42 . At lower concentrations, compound 42 has less effect on normal cell lines (HEK293). Additionally, a molecular docking study explored the binding mode and possible interactions between the synthesized compound and the ATP binding site of the EGFR kinase domain. A series of 5-enamine–4-thiazolidinones with phenylalanine moiety in the molecules was designed and reported by Holota et al. . Among the synthesized derivatives, the hybrid 43 , with a thiazole-bearing scaffold in the molecule, was found to be highly active in the 60 lines screening. Compound 43 demonstrated inhibition activity against (GI 50 < 10 μM) against all 59 human tumor cell lines, with average GI 50 /TGI/LC 50 values of 2.57/57.27/94.71 μM, respectively. Preliminary SAR provided by the authors revealed that the presence of thiazole substituent is crucial for anticancer activity whereas a change in the hydrogen atom, aniline derivatives, or 1,2,4-triazole nucleus leads to the disappearance of the effect. Two series of merged 1,2,4-triazole–4-thiazolidinone hybrids with ylidene and enamine linkers in the molecules were designed and synthesized by Holota et al. . The obtained hybrids were studied for their antitumor activity in an NCI 60 lines screening and a number of the compounds presented excellent anticancer properties at 10 µM. Derivatives 44 and 45 were found to be the most active against cancer cell lines, with total mean GI 50 values of 3.54 µM ( 44 ) and 10.96 µM ( 45 ), without causing toxicity to normal somatic HEK293 cells, with IC 50 values of 28.99 µM ( 44 ) and 24.43 µM ( 45 ). An SAR analysis performed by authors revealed that both the presence and position of a chlorine atom in the benzylidene area of molecules play a crucial role in the realization of the anticancer effect . A series of 17 novel pyridine-thiazolidinone hybrids were synthesized, characterized, and evaluated as potential hCA inhibitors by Ansari et al. . Of all the synthesized hybrids, derivatives 46 and 47 had the most potent CAIX inhibition activity in the esterase assay, with IC 50 values of 1.61 µM and 1.84 µM, respectively. The evaluated cytotoxicity for 46 and 47 on a HEK-293 was 249.6µM and 230.4µM, respectively. The evaluated anticancer activities against MCF-7 (breast cancer cell line) and HepG-2 (liver cancer cell line) were IC 50 values of 13.0 µM and 19.2 µM, respectively, for hybrid 46 and values of 12.4 µM and 16.2 µM, respectively, for 47 . In , the synthesis and study of molecules 48 and 49 , as modified analogues of hybrids 46 and 47, was reported. The authors applied the bioisosteric replacement of the pyridine core by the substituted benzene ring for the design of novel target molecules with desirable anticancer properties. Despite the promising evaluated in silico features, the newly synthesized analogues 48 and 49 were found to be less active compared to the hybrids 46 and 47 against the HepG-2 cell line. The molecular hybridization approach was applied for the synthesis of pyridine–4-thiazolidinone hybrids with aim of the synthesis of potential antiglioblastoma agents by Campos et al. . Among sixteen synthesized compounds, derivatives 50–52 displayed potent antitumor activities against the tested glioblastoma cell lines and exhibited IC 50 values 2.17, 6.24, and 2.93 μM, respectively, in the C6 cell line, well below the standard drug temozolomide. The mechanism of action studies demonstrated that derivatives 50 and 52 induced apoptosis, significantly increasing the percentage of cells in the Sub-G1 phase in the absence of necrosis. Consistent with these results, the caspase-3/7 assay revealed that derivative 50 presents pro-apoptotic activity due to the significant stimulation of caspases-3/7. Moreover, hybrids 50–52 increased antioxidant defense, decreased reactive oxygen species (ROS) production, and modulated redox status. The attempt to design potential antimitotic agents following the hybridization of pyridine, piperazine, and 4-thiazolidinone scaffolds was reported by Demirci et al. . The synthesized hybrids were evaluated on the PC-3, DU145, and LNCaP prostate cancer cell lines. All the studied molecules possessed satisfactory calculated pharmacokinetic properties. Compound 53 showed the most potent activity level inside the tested series, with an IC 50 of 36.75 µM on the PC-3 cancer line, while the other cancer cells tested showed no response to the compounds used (IC 50 > 500 µM). Hussein et al. applied a hybrid-pharmacophore approach for the design of novel biologically active 4-thiazolidinones. Among the synthesized molecules, compound 54 exhibited the most potent cytotoxic activity and was found to be more effective on the WI-38 normal human lung fibroblast cell line, with an IC 50 of 92 µg/mL, but not as effective on the A549 and MDA-MB-31 cancer cells, with IC 50 values of 357 µg/mL and 505 µg/mL, respectively. Indole scaffolds are often used for the design and development of 4-thiazolidinone hybrids as anticancer agents. Sigalapalli et al. reported on the synthesis of a small library of hybrid molecules containing 4-thiazolidinone and indole scaffolds linked by an aliphatic linker with aim of the designing tubulin polymerization inhibitors. The novel compounds were tested on five human cell lines of the lung (A549, NCI-H460), breast (MDA-MB-231), and colon (HCT-29, HCT-15), using podophyllotoxin as a reference compound. The synthesized compound 55 showed the strongest activity against both colon cancer cell lines, with an IC 50 value of 0.92µM for HCT-15. Meanwhile, against the normal human lung epithelial cell line (L132), the IC 50 value for the compound was 10.84 µM, indicating that compound 55 is 10-fold more selective against the colon cell line. SARs analysis performed by the authors revealed that the antiproliferative activity of phenethyl-thiazolidinone-indole hybrids is higher than that of benzyl-thiazolidinone-indole ones. Furthermore, it was observed that hybrids without a substituent at the nitrogen atom into indole core are more active than N-alkyl/aryl-substituted ones. In addition, the presence of the methoxy group at the phenyl ring of the side chain of hybrid compounds leads to higher activity than halogen substituents. Extended analyses on compound 55 revealed that the compound inhibited the cell cycle of HCT-15 cells in sub G1 and G2/M phases, additionally inhibited tubulin more strongly compared to the reference compound, induced intracellular ROS, and decreased the mitochondrial potential, causing cell death by apoptosis . Oliveira et al. reported on the synthesis of novel 4-thiazolidinone derivatives with an indole backbone. Hybrid 56 possessed the most potent anticancer activity and was active against the MCF-7 cell line, with an IC 50 of 6.06 µM, the OVCAR-3 cell line, with an IC 50 of 5.12 µM, and the HaCat cell line, with IC 50 of 6.23 µM. A series of novel indole-azolidinone hybrids with 5-fluoro-3-formyl-1 H -indole-2-carboxylic acid methyl ester scaffolds were synthesized via the Knoevenagel reaction . Among the synthesized compounds, hybrid 57 was found to be the most active and exhibited toxicity in the 60 lines screening, with total GI 50 of 0.45/0.65 µM and with IC 50 values toward cancer cells MCF-7-0.70 µM, HCT116-0.80 µM, A549-9.70 µM, and HepG2-12.00 µM. Meanwhile, the non-malignant cells (human keratinocytes of HaCaT line and murine embryonic fibroblasts of Balb/c 3T3 line) possessed moderate sensitivity to hybrid 57 . Furthermore, compound 57 induced apoptosis in studied tumor cells via caspase-3-, PARP1-, and Bax-dependent mechanisms; however, it did not affect the G1/S transition in HepG2 cells. Additionally, hybrid 57 impaired nuclear DNA in HepG2, HCT116, and MCF-7 cells without intercalating this biomolecule, but much fewer DNA damage events were induced by 57 in normal Balb/c 3T3 fibroblasts compared with HepG2 carcinoma cells. Isatin is an endogenously occurring molecule in human tissues, based on the structure of which tyrosine kinase inhibitor Sunitinib (Sutent ® ) was established. Sunitinib was approved by the FDA in 2006 for the treatment of the imatinib-resistant cancers advanced metastatic renal cell carcinoma and gastrointestinal stromal tumors. El-Naggar et al. reported a series of isatine–4-thiazolidinone hybrids, among which molecule 58 possessed strong cytotoxicity, with IC 50 values of 7.6 µM and 8.4 µM on the MDA-MB-231 and MCF-7 cell lines, respectively. Furthermore, compound 58 was active on WI-38 (nontumorigenic human lung fibroblast cell line) and MCF-10A (human breast epithelial cell line), with IC 50 values of 49.1 µM and 73.1 µM, respectively. In addition, hybrid 58 significantly induced the expression of the pro-apoptotic protein Bax, inhibited the expression of the anti-apoptotic protein Bcl-2, and increased the level of caspase-3 compared to the control sample. Fouad et al. developed a series of isatine–4-thiazolidinone conjugates as potential antimitotic agents. Compound 59 was effective against colorectal cancer cell line KM12, melanoma cell line UACC-62, ovarian cancer cell line IGROV1, cancer cell line SK-OV-3, and renal cell carcinoma lines (A498, ACHN, CAKI-1, RXF393, and UO-31). Compounds’ activity towards CAKI-1 and UO-31, with IC 50 values of 4.74 and 3.99 µM, equal to the cytotoxic potency of the reference compound sunitinib. The derivative 59 arrested the cell cycle in the G2/M and pre-G1 phase and inhibited cyclin-dependent kinase (CDK) activity. In addition, in silico and in vivo studies demonstrated that compound 59 has an excellent physicochemical and pharmacokinetic profile (which PK and docking can develop). Szychowski et al. reported studies on the anticancer potential of an isatine–4-thiazolidinone hybrid modified with a 3,5-diaryl-2-pyrazoline scaffold 60 . The impact of hybrid 60 on cytotoxicity, the apoptotic process, and metabolism in the human squamous carcinoma (SCC-15) cell line was evaluated. The results obtained by the authors showed that the studied molecule 60 exhibits both cytotoxic and proapoptotic properties at a 10–100 µM concentration range. The activation of caspase-3 was caused by 60 and was accompanied by an LDH release and resazurin reduction. Additionally, increased DCF fluorescence in a wide range of concentrations after 6, 24, and 48 h of exposure was observed after treatment with 60, which suggests the stimulation of ROS production. The properties of 60 established by the authors make it a promising tool for further research as an anti-cancer agent. Batran et al. reported on the synthesis of quinoline–4-thiazolidinone hybrids as potential antimitotic agents. Molecule 61 was active against the MCF-7 breast cancer cell line, with an IC 50 value of 98.79 µM. Nafie et al. studied another series of quinolone–4-thiazolidinone hybrids. Five of the ten compounds showed strong cytotoxic activity against the HCT-116 cell line, comparable to 5-FU, while compound 62 was the most potent cytotoxic, excluding effects on normal intestinal FHC cells. The compound’s inhibitory activity against EGFR was also confirmed, where it acted at a similar level to the reference compound erlotinib. In addition, hybrid 62 caused the induction of apoptosis and cell cycle arrest in the G2 and S phases. Moreover, it was confirmed to increase the expression levels of p53, PUMA, Bax, caspase-3, -8, and -9 protein genes, and the downregulation of Bcl-2. In in vivo studies, the LD 50 value was established, which was 6 mg/kg BW. It was observed that the use of this hybrid causes a reduction in tumor size comparable to 5-FU (the inhibition ratio was 52.92% for 62 and 57.16% for 5-FU), with the preservation of biochemical and histochemical structures being close to normal. A new series of quinolone–4-thiazolidinone hybrid molecules were reported by Kumar et al. . All the compounds were screened in vitro for their anticancer activities against MDA-MB-231 and MCF-7 cell lines using an MTT assay. Derivative 63 was found to be the most potent against the MDA-MB-231 cell line, with an IC 50 8.16 of μM, and, at the same time, non-toxic to the human normal kidney HEK 293 cell line, with an IC 50 of 846.93 μM. Additionally, it was established in the in silico studies (docking, molecular dynamic studies) that hybrid 63 arrested the cell cycle at the G2/M phase and possesses binding properties with N-acetyl transferase (hNAT-1) protein. The authors suggest that the identified quinolinone–4-thiazolidinone hybrid 63 could be considered as a new chemotype targeting hNAT-1 and could be used for hit/lead compound generation in anticancer drug design and discovery. Qi et al. reported on the application of the hybrid-pharmacophore approach using a 4-phenoxy-6,7-dimethoxyquinoline moiety as a key part of foretinib and cabozatinib molecules in the design of novel multi-tyrosine kinase inhibitors based on 4-thiazolidinone core . Structural modification of phenyl rings A and B as well as quinoline ring C was applied in the molecular design. As a result, hit-compounds with inhibitory activity toward mesenchymale epithelial transition factor (c-Met) ( 64,65,68 ) and toward HT-29 (human colon cancer cell line) ( 66–68 ) were identified. A series of hybrids with a quinazoline scaffold was synthesized by Samridhi Thakral et al. . The synthesized compounds were screened for their in vitro cytotoxic and growth-inhibitory activities against MCF-7 and Hep-G2 cell lines using the MTT assay method in comparison with the activity of the known anticancer drug doxorubicin. The hybrid with a chlorine atom at the m -position in the phenyl ring attached to the 4-thiazolidinone nucleus at position two ( 69 ) was found to be the most active against the hepatic cell line, with an IC 50 of 1.79 µg/mL. The presence of the methoxy-group at the p -position in the mentioned phenyl ring ( 70 ) leads to activity against breast cancer cell line MCF-7, with an IC 50 of 1.94 µg/mL. The IC 50 value for the standard drug in this study was found to be 0.09 µg/ml. Sharma et al. reported design and synthesis as potential apoptotic agents of a series of new benzimidazole–4-thiazolidinedione hybrid molecules. All the new twenty synthesized hybrids were evaluated for their in vitro cytotoxic potential against selected human cancer cell lines: breast (MDA-MB-231), prostate (PC-3), cervical (HeLa), lung (A549), bone (HT1080), and a normal kidney cells (HeK-293T) using the MTT assay. Eleven of the twenty described hybrids were active in the nanomolar concentration range (IC 50 values from 0.096 µM to 0.98 µM) on lung cancer (A549) cell lines, and four compounds showed a broad spectrum of cytotoxic activity on all the examined cancer cells in the range of 0.096–4.58 µM. Among them, compounds 71 and 72 were found to be the most active, with IC 50 values range on all lines (except PC-3 for 71 ) of 0.096–0.32 µM and with low cytotoxicity in the HeK-293T line, with IC 50 values of 6.76 and 6.65 µM respectively. In-depth studies of the impact of 71 and 72 on A549 lung cancer cells revealed a remarkable inhibition of cell migration through the disruption of the F-actin assembly. Moreover, treatment with 71 and 72 led to the collapse of the mitochondrial membrane potential (DJm) and increased the levels of ROS in A549 cells. Reported in were the results of different studies suggesting that such hybrids have the potential to be developed as cytotoxic agents and their structural modifications could lead to a new generation of promising anticancer agents. Iqbal et al. reported the synthesis of two series of imidazopyridine–4-thiazolidinone hybrid molecules and an evaluation of their anticancer activity on a panel of three human cancer cell lines: MCF-7 (human breast cancer), A549 (human lung cancer), and DU145 (human prostate cancer). Among the synthesized hybrids, derivatives 73–75 were found to be the most active, with IC 50 values at the micromolar level. The preliminary SAR provided by the authors revealed that anticancer activity was connected to the R1 nature . The docking results suggested that the synthesized hybrids 73–75 could be potential EGFR kinase inhibitors. Summarizing the structure–activity relationship analysis, the following trends can be observed. As reported in this review, 4-thiazolidinone-bearing hybrid molecules with anticancer activity mostly belong to the linked type of hybrids , and only molecules, 44 and 45, could be characterized as merged/fused hybrids. Hybrids mostly contain two or three potential pharmacophores (approved drugs and natural or privileged heterocyclic scaffolds) in their molecules. Most parts of the hybrids contain linked pharmacophores in positions C2 or C5, whereas substitution at the position N3 was used less often for design. Applying imino/amino- and hydrazone-linkers between pharmacophores and a 4-thiazolidinone core at position two was often used in the design of novel hybrid molecules with potential anticancer activity . Good results were obtained using a pyrazoline linker at position two in the 4-thiazolidinone ring. It is worth noting that using of pyrazolines is a promising direction in the construction of hybrid molecules with anticancer properties. Pyrazolines can be considered cyclic bioisosteres of the hydrazone-linker which possess their own pharmacological profile and could be additionally substituted with potential anticancer pharmacophores. This makes pyrazoline scaffolds a desirable aspect of the hybrid molecules. In some cases, pharmacologically attractive substituents were linked to the C2 position of the 4-thiazolidinone core without a linker through the carbon–carbon bond. At the N3 position, as methylene-and amino groups were used as linkers, urea moiety or the linker was absent. Often position N3 was unsubstituted in the structures of reported molecules or was substituted with alkyl/aryl-groups or amino acids. The introduction of the enamine linker at C5 of the 4-thiazolidinone ring was used in molecules 43–45; however, in the case of hybrids 44 and 45, such a structure modification led to the disappearance of activity. The design using a ylidene linker at C5 was much more popular and resulted in the majority of reported hit/lead compounds. The analysis of the mechanisms of anticancer effects reported in this review for hybrid molecules showed that they possess a complex mechanism of action and additional in-depth studies are needed in this area . A large number of hybrid molecules were characterized as potent apoptosis inducers via multiple mechanisms. Caspase-dependent (intrinsic) and extrinsic pathways, with the upregulation of anti-apoptotic signals and downregulation of pro-apoptotic signals, were the most often indicated. An important reported mechanism for antimitotic activity was an impact on the cell cycle with arrest following in different phases. Moreover, enzymes such as PIM-and tyrosine kinases as well as carbonic anhydrases were used as molecular targets for the design of novel 4-thiazolidinones with anticancer activity. Some reported hybrids were found to be promising tubuline inhibitors and inducers of ROS generation. The molecular hybridization strategy is a popular trend and an attractive research direction, providing endless source of significant opportunities in the design of new 4-thiazolidinone-bearing hybrid molecules with potential anticancer activity. A combination of potential pharmacophores in one molecule is one of the possible approaches used to achieve multi-target and polypharmacological effects for small molecules and is especially essential in the case of antimitotic agents. The hybridization of scaffolds, the hybrid-pharmacophore approach, and analogue-based drug design are key tools that are widely used by synthetic and medicinal chemists in this field. The hybridization of the 4-thiazolidinone core with early approved drugs, natural compounds, and privileged heterocyclic scaffolds is the most frequently used method in the development of novel molecules with antimitotic effects. The application of a molecular hybridization methodology allowed for identification of the new “hit” and “lead” hybrid compounds which target valid and important targets in carcinogenesis. The mentioned strategies and methodologies will remain relevant to studies over the next decade, and new wave/direction in the design of potential antimitotic agents using the hybridization of 4-thiazolidione scaffolds with biomolecules such as monoclonal antibodies, etc., can be expected. The data presented in this review contribute to the SAR profile of 4-thiazolidinone-based hybrid molecules for further exploration in the design, improvement, and optimization of new molecules with antitumor activity. |
Biological Activities of Organic Extracts of the Genus | 72e61290-8e64-4be0-a24b-46ec38225717 | 9230106 | Pharmacology[mh] | The Aristolochiaceae family is represented by seven genera: Asarum , Saruma , Lactoris , Hydnora , Prosopanche , Thottea , and Aristolochia . About 550 species are known, distributed in the tropics and temperate zones of America, Asia, and Australia . Traditionally, the Aristolochiaceae family was located in the Aristolochiales order by Cronquist (1981) and Takhtajan (1997). Recent studies indicate that it belongs to the Piperales order . The genus Aristolochia is the most abundant of the Aristolochiaceae family and has been widely used in traditional Chinese medicine mainly , the genus is integrated by 550 species, making it the most important genus of the family . Most of the species of this genus are perennial, herbaceous, distributed in bushes, in coiled or liana form, showy flowers, prostrate or tuberous rhizomes, as well as leaves with the presence of essential oils . In the last two decades, the genus Aristolochia has generated great interest due to the abundance of mainly secondary metabolites, terpenes, and alkaloids . Aristolochias species exist in various parts of the world; however, some species have been identified in Mexico: A. buntingii Pfeifer, A. tresmariae Ferris, A. pacifica Santana Mich. & Paizanni, A. savannoidea Paizanni & M. Ramírez, A. tuitensis Santana Mich. & Paizanni, A. manantlanensis Santana Mich., A. malacophylla Standl., A. odoratissima L., A. styloglossa Pfeifer, A. foetida Kunth, A. tequilana S. Watson, A. luzmariana Santana Mich. and A. emiliae Santana Mich. & Solís for which there are no phytochemical or biological studies showing the presence of active compounds . Other species such as A. cardiantha Pfeifer, A. flexuosa Duch., A. glossa Pfeifer, A. malacophylla Standl., A. mutabilis Pfeifer, A. mycteria Pfeifer, and A. tentaculata O. C. Schmidt, have also been identified in the state of Michoacán, in localities near the Bajío area, in Mexico . Some of the species of the genus Aristolochia are characterized by having compounds such as aristolochic acids that are attributed to adverse health effects. However, these compounds can be related to other lower-risk applications. Otherwise, there are also phenolic and terpene compounds that show beneficial effects in different biological aspects, which is why it is important to know which ones are related to the different species for subsequent studies. Therefore, this systematic review examined the published pharmacological and ethnomedicinal literature of different Aristolochias species for possible studies associated with phytochemicals from organic extracts and beneficial effects.
Aristolochia Genus The secondary metabolites responsible for the biological effects of the species of the Aristolochia genus generally are usually aristolochic acids and their derivatives, as well as monoterpenes such as thujene, camphene, and carene, kaurene-type diterpenes, triterpenes such as lupeol, among others. Likewise, alkaloid metabolites derived from aristolactams and phenolic compounds of the lignan type are involved in these functions . Aristolochia is the most abundant genus in the Aristolochiaceae family. The species of this genus are used ornamentally and in traditional medicine as a source of abortifacients, emmenagogues, sedatives, analgesics, anti-cancers, anti-inflammatories, muscle relaxants, antihistamines, antiparasitics, to treat cholera, abdominal pain, rheumatism, antimalarial, skin problems, and different types of bites and stings from animals and insects . The use of plant extracts in traditional medicine is profitable because no elaborate procedures are required to obtain them, production costs are low, and the materials to obtain them are accessible . For these reasons, several studies have used extracts of different solvents to obtain metabolites using different parts of the plant. The extracts as well as the active compounds that comprise the Aristolochia species have been used in pharmacological aspects and in traditional medicine frequently in recent years. 2.1. Ethnomedicinal Use A variety of traditional uses for species of the genus Aristolochia were found in the literature. Of the traditional uses cited, the most common uses are anticancer (33 articles) , antibacterial (31 articles) , antioxidants (18 articles) , snake anti-venom (13 articles) , anti-inflammatory (11 articles) , abdominal pain (11 articles) , antiparasitic (7 articles) , insecticide an predator protection (7 articles) , anti-malarial (5 articles) , skin diseases (5 articles) , fever (4 articles) , headache (4 articles) . Other beneficial effects such as, antifungal activities , antinociceptive , changes in the estrous cycle , antifibrosis , hepatoprotection, nephroprotection , neuroprotective effect , antiurcer , antiallergic , immune effect , angiogenic , osteogenic differentiation of gingival mesenchymal stem cells , antidiabetic , control of melanogenesis , antihemorrhagic , antispasmodic , antitoxin , liver protector , bronchitis, constipation, rheumatism and bladder diseases , heart protector , antidyslipidemic , healing of wounds , acaricide , expectorant, antitussive, antihistamine and pain reliever . Also, traditional uses include mainly the root of the plant (42 articles), the leaves (31 articles), the stems (17 articles), aerial parts (15 articles), and the whole plant (15 articles). Some forms of use of Aristolochia plants for ethnomedicinal use in snakebites are drinking whole plant juice and leaves, aqueous extract (AE) orally and applying a root paste to the wound and giving a root paste orally. In skin diseases, the shade-dried root powder is taken orally for 48 days. In fever, the leaves are chewed during the illness. The headache is treated with the formation of a paste placed on the forehead. In abdominal pain, the use of a decoction of the roots is used. In the treatment of malaria, the plant is used in decoction . 2.2. Phytochemical Studies The review of the literature allowed knowing phytochemicals that have a higher prevalence such as phenanthrene derivatives, phenolic compounds, fatty acids, and isoprenoid derivatives. Extracted and polar roots showed a higher prevalence of phenanthrene derivatives and phenolic compounds. The roots and aerial parts of the medium and low-polarity extracts showed a higher presence of fatty acids and derived isoprenoids. The most prominent phytochemicals are shown in . 2.3. Pharmacological Activity Pharmacological studies have been carried out using crude extracts and bioactive compounds from different species of Aristolochia . The beneficial effects that most prevailed in this review were: anticancer activity, antibacterial, antiparasitic and antiviral activity, antiplatelet activity, antioxidant activity, neuroprotective activity, changes in the estrous cycle, antidiabetic potential, anti-inflammatory activity, and antifibrotic activity. shows the common beneficial and ethnomedicinal effects of Aristolochia species in traditional medicine. 2.3.1. Anticancer Activity In aerial parts of A. longa L., a greater in vitro cytotoxic effect was determined on RD (embryonal rhabdomyosarcoma cells) (IC 50 = 0.015 mg/mL) of a dichloromethane extract (DCME), followed by the hexane extract (HXE) on BSR (kidney adenocarcinoma of hamster cells) (IC 50 = 0.018 mg/mL). The least cytotoxic effect was shown in the HXE and DCME analyzed in Vero (monkey kidney cancer cells) cells (IC 50 = 0.250 mg/mL) as well as in the methanolic extract (ME) of RD (IC 50 = 0.200 mg/mL) and BSR (IC 50 = 0.350 mg/mL). The compounds implicated in this beneficial activity are attributed to linoleic acid chloride, oleic acid, and limonene-6-ol, pivalate . The possible mechanisms of cytotoxicity of the compounds characterized in the HXE and DCME could be related to the cleavage of the plasma membrane and the release of its content into the extracellular medium . A. longa L. exhibited an in vitro cytotoxic effect of HXE of the root on RD cells (IC 50 = 0.0151 mg/mL) showing a relationship of its activity to flavonoids (76.41 ± 8.74 mg GAE/g), while the HXE the cytotoxicity in healthy PBMC (human peripheral blood mononuclear) cells was lower (IC 50 = 0.0625 mg/mL) . The chloroform extract (CE) from the roots of A. baetica L. showed cytotoxic activity (IC 50 = 0.2160 mg/mL) in vitro against MCF-7 (breast cancer cells) by means of the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] colorimetric assay. Aristolochic acid I was identified and contributed to the cytotoxicity of the extract . A study of the CE of leaves of A. indica L. was carried out and cytotoxicity was obtained with the MTT assay at 48 h after treatment in MCF-7 cells (IC 50 = 0.347 mg/mL) using Taxol™ (IC 50 = 1.17 × 10 −8 M) as a standard control. The compounds identified in the CE of the leaves were flavonoids, tannins, glycosides, phenols, saponins, terpenoids, and amino acids . Compounds such as alkaloids, flavonoids, steroids, and anthraquinones from the aerial parts of the CE of A. ringens Vahl. caused a cytotoxic effect against HepG-2 (human liver cancer cells) (IC 50 = 0.0164 mg/mL) and on MCF-7 cells (IC 50 = 0.0816 mg/mL) . In DCME collected in 2018 from A. foetida Kunth, IC 50 values were determined for leaves of 0.0473 mg/mL and for stems with IC 50 values of 0.0459 mg/mL in MCF-7 cells. Components in the extracts can cause late apoptotic cell death through the intrinsic pathway in the cancer cell line. The main compounds identified were methyl hexadecanoate; hexadecanoic acid; 2-butoxyethyl dodecanoate; ethyl hexadecanoate; methyl octadeca-9,12,15-trienoate; and (9 Z ,12 Z ,15 Z )-octadeca-9,12,15-trienoic acid that allow cytotoxic activity . Essential oils from the aerial parts of A. fordiana Hemsl. were evaluated against HepG-2 cells (IC 50 = 0.69 mg/mL) and the MCF-7 cell line (IC 50 = 0.22 mg/mL) for 72 h attributing its effect to the compounds β -caryophyllene, limonene, and linalool. Doxorubicin was used as a positive control in HepG-2 (IC 50 = 0.00049 mg/mL) and MCF-7 (IC 50 = 0.00022 mg/mL) . The sesquiterpene 2,2,7,7-tetramethyltricyclo[6.2.1.0(1,6)]undec-4-en-3-one has been identified and characterized as the main compound in essential oils of A. mollissima Hance. Essential oils from rhizomes showed cytotoxic activity in ACHN (kidney adenocarcinoma cells) (IC 50 = 0.0223 mg/mL), MCF-7 (IC 50 = 0.0206 mg/mL), Bel-7402 (human liver carcinoma cells) (IC 50 = 0.0331 mg/mL), HepG-2 (IC 50 = 0.0332 mg/mL), and HeLa (human cervix carcinoma cells) (IC 50 = 0.0386 mg/mL) compared to aerial parts with the exception of MDA-MB-435S (melanoma cells) (IC 50 = 0.0203 mg/mL) . The cytotoxic effect of an AE of the root of A. longa L. on breast cancer cell lines was evaluated in vitro by means of the MTT assay, whose activity may be related to flavonols, flavones, and/or flavonoid glycosides . On the other hand, tests were carried out on human red blood cells with an AE of aerial parts of A. longa L. collected in Algeria in March 2018. The AE did not show high percentages of hemolysis (68.75 ± 6.11%; 200 mg/mL). The concentration of polyphenols [283.68 ± 0.60 mg GAE (gallic acid equivalent)/g] and flavonoids (10.50 ± 0.03 mg QE (quercetin equivalent)/g) could influence hemolysis, which is important to consider the dose of the AE in traditional cancer medicine . Ethanol extract (EE) and DCME:ME from A. ringens Vahl. roots were evaluated in vitro and in vivo and compared with 5-fluorouracil. However, the study lacked the characterization of the bioactive compounds to corroborate their anticancer therapeutic approach . Likewise, in the ME of leaves of the species A. macroura Gomes., the active components were not specifically mentioned and their cytotoxic activity against HepG-2 cells (IC 50 = 0.513 mg/mL) was higher compared to other species such as Schinus molle L. (IC 50 = 0.050 mg/mL) . In a chemical and biological study of A. maurorum L., the main components of roots and aerial parts of ME were aristolochic acid I, II, and IIIa. However, the compound that showed the greatest cytotoxic effect was aristolochic acid I (IC 50 = 1.43 × 10 −8 M, in Artemia salina ); it is worth mentioning that the biological evaluation of the cytotoxic activity was not carried out in cancer cells . The ME of the roots of A. baetica L. demonstrated antiproliferative effect against T-24 (human bladder cancer cells) IC 50 = 0.048 mg/mL and HT-29 (human colon cancer cells) IC 50 = 0.100 mg/mL relative to HepG-2 (IC 50 = 0.380 mg/mL). The antiproliferative effect can be attributed to phytochemicals identified mostly as polyphenols, alkaloids, flavonoids, saponins, and tannins and their possible mechanism of action against cancer cells via intrinsic apoptosis . The polar extracts such as the ME ones mentioned above, as well as the EE one from the roots of A. bracteolata Lam. have shown highly effective cytotoxic activity against MCF-7 cells (IC 50 = 0.0191 mg/mL), where saponins, alkaloids, flavonoids, sterols, and carbohydrates were identified as major components . The mechanism of cell death against cancer cells that phenolic compounds can present involves the inhibition of enzymes compromising the cell cycle . The ME of stems and leaves of A. tadungensis T. V. Do & Luu. was evaluated in HeLa (IC 50 = 0.0083 mg/mL), PANC-1 (human pancreas cell line) IC 50 = 0.0826 mg/mL, and A-549 (human lung cell line) IC 50 = 0.0755 mg/mL. The aristolochiaside compounds with cytotoxic effect on HeLa (IC 50 = 7.59 × 10 −6 M) and on PANC-1 (IC 50 = 5.47 × 10 −5 M) were characterized and identified. Only in the PANC-1 cell line the IC 50 values were > 2.5 × 10 −5 M . Aristolactam AIIIa showed cytotoxicity against A-549 cells (IC 50 = 2.40 × 10 −5 M). Camptothecin (1.35 × 10 −6 M) was used as a control . Aristolactam AIIIa can induce apoptosis and cell cycle arrest in the G2/M phase in cancer cells . In particular, in the EE of the rhizomes of A. championii Merr. & Chun. The aristolochic acid derivative aristchamic-A showed higher cytotoxic activity against HCT-116 (human colon cancer cells) IC 50 = 5.00 × 10 −7 M, HepG-2 (IC 50 = 7.37 × 10 −6 M), BGC-823 (human gastric carcinoma cells) IC 50 = 2.66 × 10 −6 M and NCI-H1650 (human lung cancer cell line) IC 50 = 7.50 × 10 −7 M. The activity of aristolochic acid derivatives could be associated with the 9,10-dihydroaristolochic acid skeleton . From an EE of roots, aristolochic acid I was identified in A. indica L., which showed antitumor action in adenocarcinoma 755 in mice at a dose of 2 mg/kg . At low doses, aristolochic acids can arrest the G2/M phase of the cell cycle and cause DNA damage by increasing reactive oxygen species (4.0 × 10 −6 M) as well as activating apoptosis in higher doses (4.0 × 10 −5 M) . Despite the controversy over the nephrotoxicity and carcinogenic effects of aristolochic acids and their derivatives, they can be focused on cytotoxic treatments . The cytotoxic effect on MG-63 (human osteosarcoma cells) was determined with eupomatenoid-7 (IC 50 = 1.19 × 10 −5 M) and HepG-2 with eupomatenoid-5 (IC 50 = 9.15 × 10 −6 M) isolated from the EE of aerial parts of A. fordiana Hemsl. Cisplatin was used as a positive control against MG-63 (IC 50 = 5.31 × 10 −6 M) and HepG-2 (IC 50 = 5.21 × 10 −6 M) . On the other hand, in the species A. galeata Mart., a cytotoxic effect was found against HeLa cells of the ethanolic extract (IC 50 = 0.369 mg/mL) and by partitioning the dichloromethane fraction (IC 50 = 0.09 mg/mL) was obtained whose cytotoxic effect was greater with respect to the fractions of hexane, ethyl acetate, and hydroethanolic. The secondary metabolites determined in the EE and the dichloromethane fraction were flavonoids, steroids, and triterpenes . In HK-2 (renal cells), 28 ME from different species of the genus Aristolochia were tested, so that aristolactam BI, aristolochic acid D, and aristolactam IIIa may be responsible for the genotoxic and cytotoxic activity. The possible mechanism of action of aristolochic acids and their derivatives causes apoptosis and arrest of the G2/M phase of the cell cycle . Of the 68 extracts tested on cancer cells, 31 extracts had an IC 50 < 0.1 mg/mL . shows different cancer cell lines against organic extracts of different species of the genus Aristolochia . 2.3.2. Antibacterial, Antiparasitic and Antiviral Activity Mohanraj et al. (2009) identified from essential oils of leaves of A. elegans Mast. sesquiterpenes β-caryophyllene and iso -caryophyllene with antibacterial activity against Klebsiella pneumoniae, Vibrio cholerae, Salmonella typhi , and S . paratyphi A. The aforementioned compounds, as well as bicyclogermacrene, are attributed to antiviral activity against the HIV-1 antigen p24 with an inhibition of 35.6–14.9% . Phenolic compounds such as fargesin, (8 R ,8′ R ,9 R )-cubebin and eupomatenoid-1 were identified in HXE from the rhizomes of A. elegans Mast. which favored the inhibition of M. tuberculosis at a minimum inhibitory concentration (MIC) of 50 µg/mL. Eupomatenoid-1 showed antiparasitic activity (IC 50 < 1.93 × 10 −9 M) against E. histolytica and G. lamblia . Navarro-García et al. (2011) determined that in the DCME from A. brevipes Benth. roots collected in Mexico, the aristolactam I presented greater antibacterial activity against Mycobacterium tuberculosis H37Rv with an MIC between 8.52 × 10 −8 and 4.26 × 10 −8 M . Likewise, in A. taliscana Hook. & Arn., the rhizome HXE exhibited antibacterial activity (MIC = 0.7 mg/mL) as well as the isolated compound eupomatenoid-7 (MIC = 2.15 × 10 −6 M) inhibiting the growth of Escherichia coli, Pseudomona fluorescens , and Listeria monocytogenesis . In the research carried out by León-Díaz et al. (2013), the HXE root of A. taliscana Hook. & Arn. (−)-licarin-A was isolated whose concentration of 5 mg/kg reduced pneumonia in mice infected with M. tuberculosis . The linoleic acid chloride, oleic acid, and limonene-6-ol, pivalate were isolated from DCME from the tubers of the A. longa L. species, the present activity was evident against Rhodococcus sp: R. equi, GK1, and GK3 (with an inhibition zone of 30 mm at 50 mg/mL) . The HXE of A. longa L. exhibited antibacterial activity (10 mg/mL) against Staphylococcus aureus , determining a total inhibitory effect with a zone of inhibition of 8.5 mm. The antibacterial activity may be related to the amount of polyphenols and flavonoids in the organic extract of A. longa L. . Essential oils promote the loss of the integrity of the cell membrane by releasing the cell material to the external environment, in addition to the inhibition of proteins and biofilms . It is worth mentioning that the extracts of A. longa L. mentioned above exceed 0.1 mg/mL, so they would not be suitable for use as antibacterials . 2.3.3. Antiplatelet Activity In A. maurorum L., the main components of the roots and aerial parts of the ME were aristolochic acid I (1.17 × 10 −6 M), II (1.28 × 10 −6 M), and IIIa (1.22 × 10 −6 M). These components showed an antiplatelet activity of 100% and the assay was compared with the standard acetylsalicylic acid (3.05 × 10 −5 M) showing an inhibition of platelet aggregation of 100%. Compounds were evaluated using an automatic platelet aggregometer and coagulation tracer . 2.3.4. Antioxidant Activity In A. taliscana Hook. & Arn. in HXE of rhizomes, the ABTS assay (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) was performed to measure the ability of the compounds to trap the ABTS •+ radical. The results obtained were expressed as antioxidant activity of eupomatenoid-7 (151.2 mg GAE/g) and (±)-licarin-A (143.4 mg GAE/g) and were the most active at both points of the determination (minute 1 and 7 of the reaction) . The antioxidant activity is dependent on hydroxyl groups, to which its antioxidant effect is attributed, which is why licarin-B and eupomatenoid-1 did not present this condition. A. bracteolata Lam. showed activity to chelate iron with an antioxidant capacity of 44 ± 0.01%, whose activity is attributed to phenolic compounds . In the ME of A. longa L., it was determined that it has a high amount of polyphenols and flavonoids, and it showed a remarkable antioxidant activity. The total content of phenolic compounds of A. longa L. showed that the ME of roots presented the concentrations of polyphenols and flavonoids with 101.4 mg of GAE/g and 54.21 mg of QE/g of extract, respectively . 2.3.5. Neuroprotective Activity Dihydrobenzofuran neolignans, 2-aryldihydrobenzofurans, 8- O -4′-neolignan, and analogs (3.0 × 10 −5 M) as well as the EE of the stem (0.01 mg/mL) of A. fordiana Hemsl. exhibited a neuroprotective effect that prevents cell death in hippocampal cells (HT-22) . 2.4. In Vivo Studies on Extracts of the Genus Aristolochia 2.4.1. Changes in the Estrous Cycle In tubers of the EE of the species A. indica L., an application has been found regarding changes in the estrous cycle in vivo with a dose of 150 mg/kg of extract . The compounds involved in the effect of the extract were not shown. 2.4.2. Antidiabetic Potential From the EE of roots of A. ringens Vahl., aristolone was identified and it was shown to have an antidiabetic potential in rats at concentrations of 300–75 mg/kg, so this part of the plant could be used in decoctions for the treatment of diabetes with the approval of more relevant studies . 2.4.3. Antifibrotic Activity The compounds - iso -bicyclogermacrenal and spatulenol (3.0 × 10 −5 M) present in the ethyl acetate extract (EAE) of A. yunnanensis Franch. stems were responsible for promoting antifibrotic concentration effects in vivo . However, the concentrations in which the pure compound was handled under in vivo conditions turned out to be high for antifibrotic activity. The genus Aristolochia has extensive traditional and pharmacological uses in various pathological conditions. Therefore, it is an attractive subject for future clinical and experimental research. 2.4.4. Anti-Inflammatory Activity In particular, in A. krisagathra Sivar. & Pradeep., studies of EE of the whole plant have been carried out. An anti-inflammatory activity of 87.1% was obtained with a dose of 400 mg/kg in rats. The compounds that could act in biological activity are alkaloid, anthraquinone, coumarin, flavonoid, phenol, quinone, saponin, steroid, tannin, terpenoid, sugar, glycoside, and xanthoprotein . The anti-inflammatory activity of (−)-hinokinin in tumor necrosis factor- α (TNF- α ) IC 50 = 0.0775 M and interleukin-6 (IL-6) IC 50 = 0.0205 M and aristolactam I (TNF- α ; IC 50 = 0.1168 M, IL-6; IC 50 = 0.0520 M) of A. indica L. in aerial parts of the DCME and EAE, respectively . In in vivo and in vitro studies, doses greater than 200 mg/kg are not usually recommended, as well as values in pure compounds > 2.5 × 10 −5 M . 2.4.5. Snake Anti-Venom Activity The hexanic extract from the roots of A. elegans Mast. was subjected to an inhibition assay of smooth muscle contraction induced by scorpion venom ( Centruroides limpidus limpidus ) in an isolated guinea pig ileum model with an inhibition of 41.66% (0.4 mg/mL), whose effects are related to neolignan-type compounds . On the other hand, in vivo studies in albino mice using a ME from the whole plant of the species A. indica L. demonstrated neutralization against Daboia russelli venom at a dose of 0.14 mg. However, no mention is made of the metabolites responsible for the activity . Compounds obtained from polar extracts, especially aristolochic acids, as mentioned above, are not considered safe compounds according to the International Agency for Research on Cancer (WHO), due to their carcinogenic effects. Despite developing these problems, they can be oriented towards their possible use as antivenoms. Likewise, the presence of aristolochic acids, aristolactams, and their derivatives can be used as chemotaxonomic markers in species of the genus Aristolochia . 2.4.6. Cancer Treatment The AE of A. longa L. roots (5000 mg/kg) did not show hepatic and renal toxicity in a preclinical assay by oral administration in rats. More studies are warranted on its possible use in breast cancer therapy. The possible compounds responsible for the beneficial activity could be the flavonols, flavones, and/or flavonoid glycosides identified in the extract . In addition to the bioactive compounds mentioned above, the amount of lectin in A. longa L. extracts was not favorable for potential cancer treatment in an in vitro immunological activity assay . The use of AE of A. longa L. rhizomes as in vivo anticancer treatment in gingival tumorigenesis caused tissue damage as well as pulmonary and toxicity problems. This could be due to the presence of aristolochic acids in the extract . In a preclinical assay against S-180 solid tumors from BALB/c mice, A. ringens Vahl. roots from extracts of EE (120 mg/kg) and DCME:ME (110 mg/kg) produced a significant value ( p < 0.05) in tumor growth over a period of 9–13 days compared to control models. However, the characterization of the polar and moderately polar extracts lacked phytochemical information .
A variety of traditional uses for species of the genus Aristolochia were found in the literature. Of the traditional uses cited, the most common uses are anticancer (33 articles) , antibacterial (31 articles) , antioxidants (18 articles) , snake anti-venom (13 articles) , anti-inflammatory (11 articles) , abdominal pain (11 articles) , antiparasitic (7 articles) , insecticide an predator protection (7 articles) , anti-malarial (5 articles) , skin diseases (5 articles) , fever (4 articles) , headache (4 articles) . Other beneficial effects such as, antifungal activities , antinociceptive , changes in the estrous cycle , antifibrosis , hepatoprotection, nephroprotection , neuroprotective effect , antiurcer , antiallergic , immune effect , angiogenic , osteogenic differentiation of gingival mesenchymal stem cells , antidiabetic , control of melanogenesis , antihemorrhagic , antispasmodic , antitoxin , liver protector , bronchitis, constipation, rheumatism and bladder diseases , heart protector , antidyslipidemic , healing of wounds , acaricide , expectorant, antitussive, antihistamine and pain reliever . Also, traditional uses include mainly the root of the plant (42 articles), the leaves (31 articles), the stems (17 articles), aerial parts (15 articles), and the whole plant (15 articles). Some forms of use of Aristolochia plants for ethnomedicinal use in snakebites are drinking whole plant juice and leaves, aqueous extract (AE) orally and applying a root paste to the wound and giving a root paste orally. In skin diseases, the shade-dried root powder is taken orally for 48 days. In fever, the leaves are chewed during the illness. The headache is treated with the formation of a paste placed on the forehead. In abdominal pain, the use of a decoction of the roots is used. In the treatment of malaria, the plant is used in decoction .
The review of the literature allowed knowing phytochemicals that have a higher prevalence such as phenanthrene derivatives, phenolic compounds, fatty acids, and isoprenoid derivatives. Extracted and polar roots showed a higher prevalence of phenanthrene derivatives and phenolic compounds. The roots and aerial parts of the medium and low-polarity extracts showed a higher presence of fatty acids and derived isoprenoids. The most prominent phytochemicals are shown in .
Pharmacological studies have been carried out using crude extracts and bioactive compounds from different species of Aristolochia . The beneficial effects that most prevailed in this review were: anticancer activity, antibacterial, antiparasitic and antiviral activity, antiplatelet activity, antioxidant activity, neuroprotective activity, changes in the estrous cycle, antidiabetic potential, anti-inflammatory activity, and antifibrotic activity. shows the common beneficial and ethnomedicinal effects of Aristolochia species in traditional medicine. 2.3.1. Anticancer Activity In aerial parts of A. longa L., a greater in vitro cytotoxic effect was determined on RD (embryonal rhabdomyosarcoma cells) (IC 50 = 0.015 mg/mL) of a dichloromethane extract (DCME), followed by the hexane extract (HXE) on BSR (kidney adenocarcinoma of hamster cells) (IC 50 = 0.018 mg/mL). The least cytotoxic effect was shown in the HXE and DCME analyzed in Vero (monkey kidney cancer cells) cells (IC 50 = 0.250 mg/mL) as well as in the methanolic extract (ME) of RD (IC 50 = 0.200 mg/mL) and BSR (IC 50 = 0.350 mg/mL). The compounds implicated in this beneficial activity are attributed to linoleic acid chloride, oleic acid, and limonene-6-ol, pivalate . The possible mechanisms of cytotoxicity of the compounds characterized in the HXE and DCME could be related to the cleavage of the plasma membrane and the release of its content into the extracellular medium . A. longa L. exhibited an in vitro cytotoxic effect of HXE of the root on RD cells (IC 50 = 0.0151 mg/mL) showing a relationship of its activity to flavonoids (76.41 ± 8.74 mg GAE/g), while the HXE the cytotoxicity in healthy PBMC (human peripheral blood mononuclear) cells was lower (IC 50 = 0.0625 mg/mL) . The chloroform extract (CE) from the roots of A. baetica L. showed cytotoxic activity (IC 50 = 0.2160 mg/mL) in vitro against MCF-7 (breast cancer cells) by means of the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] colorimetric assay. Aristolochic acid I was identified and contributed to the cytotoxicity of the extract . A study of the CE of leaves of A. indica L. was carried out and cytotoxicity was obtained with the MTT assay at 48 h after treatment in MCF-7 cells (IC 50 = 0.347 mg/mL) using Taxol™ (IC 50 = 1.17 × 10 −8 M) as a standard control. The compounds identified in the CE of the leaves were flavonoids, tannins, glycosides, phenols, saponins, terpenoids, and amino acids . Compounds such as alkaloids, flavonoids, steroids, and anthraquinones from the aerial parts of the CE of A. ringens Vahl. caused a cytotoxic effect against HepG-2 (human liver cancer cells) (IC 50 = 0.0164 mg/mL) and on MCF-7 cells (IC 50 = 0.0816 mg/mL) . In DCME collected in 2018 from A. foetida Kunth, IC 50 values were determined for leaves of 0.0473 mg/mL and for stems with IC 50 values of 0.0459 mg/mL in MCF-7 cells. Components in the extracts can cause late apoptotic cell death through the intrinsic pathway in the cancer cell line. The main compounds identified were methyl hexadecanoate; hexadecanoic acid; 2-butoxyethyl dodecanoate; ethyl hexadecanoate; methyl octadeca-9,12,15-trienoate; and (9 Z ,12 Z ,15 Z )-octadeca-9,12,15-trienoic acid that allow cytotoxic activity . Essential oils from the aerial parts of A. fordiana Hemsl. were evaluated against HepG-2 cells (IC 50 = 0.69 mg/mL) and the MCF-7 cell line (IC 50 = 0.22 mg/mL) for 72 h attributing its effect to the compounds β -caryophyllene, limonene, and linalool. Doxorubicin was used as a positive control in HepG-2 (IC 50 = 0.00049 mg/mL) and MCF-7 (IC 50 = 0.00022 mg/mL) . The sesquiterpene 2,2,7,7-tetramethyltricyclo[6.2.1.0(1,6)]undec-4-en-3-one has been identified and characterized as the main compound in essential oils of A. mollissima Hance. Essential oils from rhizomes showed cytotoxic activity in ACHN (kidney adenocarcinoma cells) (IC 50 = 0.0223 mg/mL), MCF-7 (IC 50 = 0.0206 mg/mL), Bel-7402 (human liver carcinoma cells) (IC 50 = 0.0331 mg/mL), HepG-2 (IC 50 = 0.0332 mg/mL), and HeLa (human cervix carcinoma cells) (IC 50 = 0.0386 mg/mL) compared to aerial parts with the exception of MDA-MB-435S (melanoma cells) (IC 50 = 0.0203 mg/mL) . The cytotoxic effect of an AE of the root of A. longa L. on breast cancer cell lines was evaluated in vitro by means of the MTT assay, whose activity may be related to flavonols, flavones, and/or flavonoid glycosides . On the other hand, tests were carried out on human red blood cells with an AE of aerial parts of A. longa L. collected in Algeria in March 2018. The AE did not show high percentages of hemolysis (68.75 ± 6.11%; 200 mg/mL). The concentration of polyphenols [283.68 ± 0.60 mg GAE (gallic acid equivalent)/g] and flavonoids (10.50 ± 0.03 mg QE (quercetin equivalent)/g) could influence hemolysis, which is important to consider the dose of the AE in traditional cancer medicine . Ethanol extract (EE) and DCME:ME from A. ringens Vahl. roots were evaluated in vitro and in vivo and compared with 5-fluorouracil. However, the study lacked the characterization of the bioactive compounds to corroborate their anticancer therapeutic approach . Likewise, in the ME of leaves of the species A. macroura Gomes., the active components were not specifically mentioned and their cytotoxic activity against HepG-2 cells (IC 50 = 0.513 mg/mL) was higher compared to other species such as Schinus molle L. (IC 50 = 0.050 mg/mL) . In a chemical and biological study of A. maurorum L., the main components of roots and aerial parts of ME were aristolochic acid I, II, and IIIa. However, the compound that showed the greatest cytotoxic effect was aristolochic acid I (IC 50 = 1.43 × 10 −8 M, in Artemia salina ); it is worth mentioning that the biological evaluation of the cytotoxic activity was not carried out in cancer cells . The ME of the roots of A. baetica L. demonstrated antiproliferative effect against T-24 (human bladder cancer cells) IC 50 = 0.048 mg/mL and HT-29 (human colon cancer cells) IC 50 = 0.100 mg/mL relative to HepG-2 (IC 50 = 0.380 mg/mL). The antiproliferative effect can be attributed to phytochemicals identified mostly as polyphenols, alkaloids, flavonoids, saponins, and tannins and their possible mechanism of action against cancer cells via intrinsic apoptosis . The polar extracts such as the ME ones mentioned above, as well as the EE one from the roots of A. bracteolata Lam. have shown highly effective cytotoxic activity against MCF-7 cells (IC 50 = 0.0191 mg/mL), where saponins, alkaloids, flavonoids, sterols, and carbohydrates were identified as major components . The mechanism of cell death against cancer cells that phenolic compounds can present involves the inhibition of enzymes compromising the cell cycle . The ME of stems and leaves of A. tadungensis T. V. Do & Luu. was evaluated in HeLa (IC 50 = 0.0083 mg/mL), PANC-1 (human pancreas cell line) IC 50 = 0.0826 mg/mL, and A-549 (human lung cell line) IC 50 = 0.0755 mg/mL. The aristolochiaside compounds with cytotoxic effect on HeLa (IC 50 = 7.59 × 10 −6 M) and on PANC-1 (IC 50 = 5.47 × 10 −5 M) were characterized and identified. Only in the PANC-1 cell line the IC 50 values were > 2.5 × 10 −5 M . Aristolactam AIIIa showed cytotoxicity against A-549 cells (IC 50 = 2.40 × 10 −5 M). Camptothecin (1.35 × 10 −6 M) was used as a control . Aristolactam AIIIa can induce apoptosis and cell cycle arrest in the G2/M phase in cancer cells . In particular, in the EE of the rhizomes of A. championii Merr. & Chun. The aristolochic acid derivative aristchamic-A showed higher cytotoxic activity against HCT-116 (human colon cancer cells) IC 50 = 5.00 × 10 −7 M, HepG-2 (IC 50 = 7.37 × 10 −6 M), BGC-823 (human gastric carcinoma cells) IC 50 = 2.66 × 10 −6 M and NCI-H1650 (human lung cancer cell line) IC 50 = 7.50 × 10 −7 M. The activity of aristolochic acid derivatives could be associated with the 9,10-dihydroaristolochic acid skeleton . From an EE of roots, aristolochic acid I was identified in A. indica L., which showed antitumor action in adenocarcinoma 755 in mice at a dose of 2 mg/kg . At low doses, aristolochic acids can arrest the G2/M phase of the cell cycle and cause DNA damage by increasing reactive oxygen species (4.0 × 10 −6 M) as well as activating apoptosis in higher doses (4.0 × 10 −5 M) . Despite the controversy over the nephrotoxicity and carcinogenic effects of aristolochic acids and their derivatives, they can be focused on cytotoxic treatments . The cytotoxic effect on MG-63 (human osteosarcoma cells) was determined with eupomatenoid-7 (IC 50 = 1.19 × 10 −5 M) and HepG-2 with eupomatenoid-5 (IC 50 = 9.15 × 10 −6 M) isolated from the EE of aerial parts of A. fordiana Hemsl. Cisplatin was used as a positive control against MG-63 (IC 50 = 5.31 × 10 −6 M) and HepG-2 (IC 50 = 5.21 × 10 −6 M) . On the other hand, in the species A. galeata Mart., a cytotoxic effect was found against HeLa cells of the ethanolic extract (IC 50 = 0.369 mg/mL) and by partitioning the dichloromethane fraction (IC 50 = 0.09 mg/mL) was obtained whose cytotoxic effect was greater with respect to the fractions of hexane, ethyl acetate, and hydroethanolic. The secondary metabolites determined in the EE and the dichloromethane fraction were flavonoids, steroids, and triterpenes . In HK-2 (renal cells), 28 ME from different species of the genus Aristolochia were tested, so that aristolactam BI, aristolochic acid D, and aristolactam IIIa may be responsible for the genotoxic and cytotoxic activity. The possible mechanism of action of aristolochic acids and their derivatives causes apoptosis and arrest of the G2/M phase of the cell cycle . Of the 68 extracts tested on cancer cells, 31 extracts had an IC 50 < 0.1 mg/mL . shows different cancer cell lines against organic extracts of different species of the genus Aristolochia . 2.3.2. Antibacterial, Antiparasitic and Antiviral Activity Mohanraj et al. (2009) identified from essential oils of leaves of A. elegans Mast. sesquiterpenes β-caryophyllene and iso -caryophyllene with antibacterial activity against Klebsiella pneumoniae, Vibrio cholerae, Salmonella typhi , and S . paratyphi A. The aforementioned compounds, as well as bicyclogermacrene, are attributed to antiviral activity against the HIV-1 antigen p24 with an inhibition of 35.6–14.9% . Phenolic compounds such as fargesin, (8 R ,8′ R ,9 R )-cubebin and eupomatenoid-1 were identified in HXE from the rhizomes of A. elegans Mast. which favored the inhibition of M. tuberculosis at a minimum inhibitory concentration (MIC) of 50 µg/mL. Eupomatenoid-1 showed antiparasitic activity (IC 50 < 1.93 × 10 −9 M) against E. histolytica and G. lamblia . Navarro-García et al. (2011) determined that in the DCME from A. brevipes Benth. roots collected in Mexico, the aristolactam I presented greater antibacterial activity against Mycobacterium tuberculosis H37Rv with an MIC between 8.52 × 10 −8 and 4.26 × 10 −8 M . Likewise, in A. taliscana Hook. & Arn., the rhizome HXE exhibited antibacterial activity (MIC = 0.7 mg/mL) as well as the isolated compound eupomatenoid-7 (MIC = 2.15 × 10 −6 M) inhibiting the growth of Escherichia coli, Pseudomona fluorescens , and Listeria monocytogenesis . In the research carried out by León-Díaz et al. (2013), the HXE root of A. taliscana Hook. & Arn. (−)-licarin-A was isolated whose concentration of 5 mg/kg reduced pneumonia in mice infected with M. tuberculosis . The linoleic acid chloride, oleic acid, and limonene-6-ol, pivalate were isolated from DCME from the tubers of the A. longa L. species, the present activity was evident against Rhodococcus sp: R. equi, GK1, and GK3 (with an inhibition zone of 30 mm at 50 mg/mL) . The HXE of A. longa L. exhibited antibacterial activity (10 mg/mL) against Staphylococcus aureus , determining a total inhibitory effect with a zone of inhibition of 8.5 mm. The antibacterial activity may be related to the amount of polyphenols and flavonoids in the organic extract of A. longa L. . Essential oils promote the loss of the integrity of the cell membrane by releasing the cell material to the external environment, in addition to the inhibition of proteins and biofilms . It is worth mentioning that the extracts of A. longa L. mentioned above exceed 0.1 mg/mL, so they would not be suitable for use as antibacterials . 2.3.3. Antiplatelet Activity In A. maurorum L., the main components of the roots and aerial parts of the ME were aristolochic acid I (1.17 × 10 −6 M), II (1.28 × 10 −6 M), and IIIa (1.22 × 10 −6 M). These components showed an antiplatelet activity of 100% and the assay was compared with the standard acetylsalicylic acid (3.05 × 10 −5 M) showing an inhibition of platelet aggregation of 100%. Compounds were evaluated using an automatic platelet aggregometer and coagulation tracer . 2.3.4. Antioxidant Activity In A. taliscana Hook. & Arn. in HXE of rhizomes, the ABTS assay (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) was performed to measure the ability of the compounds to trap the ABTS •+ radical. The results obtained were expressed as antioxidant activity of eupomatenoid-7 (151.2 mg GAE/g) and (±)-licarin-A (143.4 mg GAE/g) and were the most active at both points of the determination (minute 1 and 7 of the reaction) . The antioxidant activity is dependent on hydroxyl groups, to which its antioxidant effect is attributed, which is why licarin-B and eupomatenoid-1 did not present this condition. A. bracteolata Lam. showed activity to chelate iron with an antioxidant capacity of 44 ± 0.01%, whose activity is attributed to phenolic compounds . In the ME of A. longa L., it was determined that it has a high amount of polyphenols and flavonoids, and it showed a remarkable antioxidant activity. The total content of phenolic compounds of A. longa L. showed that the ME of roots presented the concentrations of polyphenols and flavonoids with 101.4 mg of GAE/g and 54.21 mg of QE/g of extract, respectively . 2.3.5. Neuroprotective Activity Dihydrobenzofuran neolignans, 2-aryldihydrobenzofurans, 8- O -4′-neolignan, and analogs (3.0 × 10 −5 M) as well as the EE of the stem (0.01 mg/mL) of A. fordiana Hemsl. exhibited a neuroprotective effect that prevents cell death in hippocampal cells (HT-22) .
In aerial parts of A. longa L., a greater in vitro cytotoxic effect was determined on RD (embryonal rhabdomyosarcoma cells) (IC 50 = 0.015 mg/mL) of a dichloromethane extract (DCME), followed by the hexane extract (HXE) on BSR (kidney adenocarcinoma of hamster cells) (IC 50 = 0.018 mg/mL). The least cytotoxic effect was shown in the HXE and DCME analyzed in Vero (monkey kidney cancer cells) cells (IC 50 = 0.250 mg/mL) as well as in the methanolic extract (ME) of RD (IC 50 = 0.200 mg/mL) and BSR (IC 50 = 0.350 mg/mL). The compounds implicated in this beneficial activity are attributed to linoleic acid chloride, oleic acid, and limonene-6-ol, pivalate . The possible mechanisms of cytotoxicity of the compounds characterized in the HXE and DCME could be related to the cleavage of the plasma membrane and the release of its content into the extracellular medium . A. longa L. exhibited an in vitro cytotoxic effect of HXE of the root on RD cells (IC 50 = 0.0151 mg/mL) showing a relationship of its activity to flavonoids (76.41 ± 8.74 mg GAE/g), while the HXE the cytotoxicity in healthy PBMC (human peripheral blood mononuclear) cells was lower (IC 50 = 0.0625 mg/mL) . The chloroform extract (CE) from the roots of A. baetica L. showed cytotoxic activity (IC 50 = 0.2160 mg/mL) in vitro against MCF-7 (breast cancer cells) by means of the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] colorimetric assay. Aristolochic acid I was identified and contributed to the cytotoxicity of the extract . A study of the CE of leaves of A. indica L. was carried out and cytotoxicity was obtained with the MTT assay at 48 h after treatment in MCF-7 cells (IC 50 = 0.347 mg/mL) using Taxol™ (IC 50 = 1.17 × 10 −8 M) as a standard control. The compounds identified in the CE of the leaves were flavonoids, tannins, glycosides, phenols, saponins, terpenoids, and amino acids . Compounds such as alkaloids, flavonoids, steroids, and anthraquinones from the aerial parts of the CE of A. ringens Vahl. caused a cytotoxic effect against HepG-2 (human liver cancer cells) (IC 50 = 0.0164 mg/mL) and on MCF-7 cells (IC 50 = 0.0816 mg/mL) . In DCME collected in 2018 from A. foetida Kunth, IC 50 values were determined for leaves of 0.0473 mg/mL and for stems with IC 50 values of 0.0459 mg/mL in MCF-7 cells. Components in the extracts can cause late apoptotic cell death through the intrinsic pathway in the cancer cell line. The main compounds identified were methyl hexadecanoate; hexadecanoic acid; 2-butoxyethyl dodecanoate; ethyl hexadecanoate; methyl octadeca-9,12,15-trienoate; and (9 Z ,12 Z ,15 Z )-octadeca-9,12,15-trienoic acid that allow cytotoxic activity . Essential oils from the aerial parts of A. fordiana Hemsl. were evaluated against HepG-2 cells (IC 50 = 0.69 mg/mL) and the MCF-7 cell line (IC 50 = 0.22 mg/mL) for 72 h attributing its effect to the compounds β -caryophyllene, limonene, and linalool. Doxorubicin was used as a positive control in HepG-2 (IC 50 = 0.00049 mg/mL) and MCF-7 (IC 50 = 0.00022 mg/mL) . The sesquiterpene 2,2,7,7-tetramethyltricyclo[6.2.1.0(1,6)]undec-4-en-3-one has been identified and characterized as the main compound in essential oils of A. mollissima Hance. Essential oils from rhizomes showed cytotoxic activity in ACHN (kidney adenocarcinoma cells) (IC 50 = 0.0223 mg/mL), MCF-7 (IC 50 = 0.0206 mg/mL), Bel-7402 (human liver carcinoma cells) (IC 50 = 0.0331 mg/mL), HepG-2 (IC 50 = 0.0332 mg/mL), and HeLa (human cervix carcinoma cells) (IC 50 = 0.0386 mg/mL) compared to aerial parts with the exception of MDA-MB-435S (melanoma cells) (IC 50 = 0.0203 mg/mL) . The cytotoxic effect of an AE of the root of A. longa L. on breast cancer cell lines was evaluated in vitro by means of the MTT assay, whose activity may be related to flavonols, flavones, and/or flavonoid glycosides . On the other hand, tests were carried out on human red blood cells with an AE of aerial parts of A. longa L. collected in Algeria in March 2018. The AE did not show high percentages of hemolysis (68.75 ± 6.11%; 200 mg/mL). The concentration of polyphenols [283.68 ± 0.60 mg GAE (gallic acid equivalent)/g] and flavonoids (10.50 ± 0.03 mg QE (quercetin equivalent)/g) could influence hemolysis, which is important to consider the dose of the AE in traditional cancer medicine . Ethanol extract (EE) and DCME:ME from A. ringens Vahl. roots were evaluated in vitro and in vivo and compared with 5-fluorouracil. However, the study lacked the characterization of the bioactive compounds to corroborate their anticancer therapeutic approach . Likewise, in the ME of leaves of the species A. macroura Gomes., the active components were not specifically mentioned and their cytotoxic activity against HepG-2 cells (IC 50 = 0.513 mg/mL) was higher compared to other species such as Schinus molle L. (IC 50 = 0.050 mg/mL) . In a chemical and biological study of A. maurorum L., the main components of roots and aerial parts of ME were aristolochic acid I, II, and IIIa. However, the compound that showed the greatest cytotoxic effect was aristolochic acid I (IC 50 = 1.43 × 10 −8 M, in Artemia salina ); it is worth mentioning that the biological evaluation of the cytotoxic activity was not carried out in cancer cells . The ME of the roots of A. baetica L. demonstrated antiproliferative effect against T-24 (human bladder cancer cells) IC 50 = 0.048 mg/mL and HT-29 (human colon cancer cells) IC 50 = 0.100 mg/mL relative to HepG-2 (IC 50 = 0.380 mg/mL). The antiproliferative effect can be attributed to phytochemicals identified mostly as polyphenols, alkaloids, flavonoids, saponins, and tannins and their possible mechanism of action against cancer cells via intrinsic apoptosis . The polar extracts such as the ME ones mentioned above, as well as the EE one from the roots of A. bracteolata Lam. have shown highly effective cytotoxic activity against MCF-7 cells (IC 50 = 0.0191 mg/mL), where saponins, alkaloids, flavonoids, sterols, and carbohydrates were identified as major components . The mechanism of cell death against cancer cells that phenolic compounds can present involves the inhibition of enzymes compromising the cell cycle . The ME of stems and leaves of A. tadungensis T. V. Do & Luu. was evaluated in HeLa (IC 50 = 0.0083 mg/mL), PANC-1 (human pancreas cell line) IC 50 = 0.0826 mg/mL, and A-549 (human lung cell line) IC 50 = 0.0755 mg/mL. The aristolochiaside compounds with cytotoxic effect on HeLa (IC 50 = 7.59 × 10 −6 M) and on PANC-1 (IC 50 = 5.47 × 10 −5 M) were characterized and identified. Only in the PANC-1 cell line the IC 50 values were > 2.5 × 10 −5 M . Aristolactam AIIIa showed cytotoxicity against A-549 cells (IC 50 = 2.40 × 10 −5 M). Camptothecin (1.35 × 10 −6 M) was used as a control . Aristolactam AIIIa can induce apoptosis and cell cycle arrest in the G2/M phase in cancer cells . In particular, in the EE of the rhizomes of A. championii Merr. & Chun. The aristolochic acid derivative aristchamic-A showed higher cytotoxic activity against HCT-116 (human colon cancer cells) IC 50 = 5.00 × 10 −7 M, HepG-2 (IC 50 = 7.37 × 10 −6 M), BGC-823 (human gastric carcinoma cells) IC 50 = 2.66 × 10 −6 M and NCI-H1650 (human lung cancer cell line) IC 50 = 7.50 × 10 −7 M. The activity of aristolochic acid derivatives could be associated with the 9,10-dihydroaristolochic acid skeleton . From an EE of roots, aristolochic acid I was identified in A. indica L., which showed antitumor action in adenocarcinoma 755 in mice at a dose of 2 mg/kg . At low doses, aristolochic acids can arrest the G2/M phase of the cell cycle and cause DNA damage by increasing reactive oxygen species (4.0 × 10 −6 M) as well as activating apoptosis in higher doses (4.0 × 10 −5 M) . Despite the controversy over the nephrotoxicity and carcinogenic effects of aristolochic acids and their derivatives, they can be focused on cytotoxic treatments . The cytotoxic effect on MG-63 (human osteosarcoma cells) was determined with eupomatenoid-7 (IC 50 = 1.19 × 10 −5 M) and HepG-2 with eupomatenoid-5 (IC 50 = 9.15 × 10 −6 M) isolated from the EE of aerial parts of A. fordiana Hemsl. Cisplatin was used as a positive control against MG-63 (IC 50 = 5.31 × 10 −6 M) and HepG-2 (IC 50 = 5.21 × 10 −6 M) . On the other hand, in the species A. galeata Mart., a cytotoxic effect was found against HeLa cells of the ethanolic extract (IC 50 = 0.369 mg/mL) and by partitioning the dichloromethane fraction (IC 50 = 0.09 mg/mL) was obtained whose cytotoxic effect was greater with respect to the fractions of hexane, ethyl acetate, and hydroethanolic. The secondary metabolites determined in the EE and the dichloromethane fraction were flavonoids, steroids, and triterpenes . In HK-2 (renal cells), 28 ME from different species of the genus Aristolochia were tested, so that aristolactam BI, aristolochic acid D, and aristolactam IIIa may be responsible for the genotoxic and cytotoxic activity. The possible mechanism of action of aristolochic acids and their derivatives causes apoptosis and arrest of the G2/M phase of the cell cycle . Of the 68 extracts tested on cancer cells, 31 extracts had an IC 50 < 0.1 mg/mL . shows different cancer cell lines against organic extracts of different species of the genus Aristolochia .
Mohanraj et al. (2009) identified from essential oils of leaves of A. elegans Mast. sesquiterpenes β-caryophyllene and iso -caryophyllene with antibacterial activity against Klebsiella pneumoniae, Vibrio cholerae, Salmonella typhi , and S . paratyphi A. The aforementioned compounds, as well as bicyclogermacrene, are attributed to antiviral activity against the HIV-1 antigen p24 with an inhibition of 35.6–14.9% . Phenolic compounds such as fargesin, (8 R ,8′ R ,9 R )-cubebin and eupomatenoid-1 were identified in HXE from the rhizomes of A. elegans Mast. which favored the inhibition of M. tuberculosis at a minimum inhibitory concentration (MIC) of 50 µg/mL. Eupomatenoid-1 showed antiparasitic activity (IC 50 < 1.93 × 10 −9 M) against E. histolytica and G. lamblia . Navarro-García et al. (2011) determined that in the DCME from A. brevipes Benth. roots collected in Mexico, the aristolactam I presented greater antibacterial activity against Mycobacterium tuberculosis H37Rv with an MIC between 8.52 × 10 −8 and 4.26 × 10 −8 M . Likewise, in A. taliscana Hook. & Arn., the rhizome HXE exhibited antibacterial activity (MIC = 0.7 mg/mL) as well as the isolated compound eupomatenoid-7 (MIC = 2.15 × 10 −6 M) inhibiting the growth of Escherichia coli, Pseudomona fluorescens , and Listeria monocytogenesis . In the research carried out by León-Díaz et al. (2013), the HXE root of A. taliscana Hook. & Arn. (−)-licarin-A was isolated whose concentration of 5 mg/kg reduced pneumonia in mice infected with M. tuberculosis . The linoleic acid chloride, oleic acid, and limonene-6-ol, pivalate were isolated from DCME from the tubers of the A. longa L. species, the present activity was evident against Rhodococcus sp: R. equi, GK1, and GK3 (with an inhibition zone of 30 mm at 50 mg/mL) . The HXE of A. longa L. exhibited antibacterial activity (10 mg/mL) against Staphylococcus aureus , determining a total inhibitory effect with a zone of inhibition of 8.5 mm. The antibacterial activity may be related to the amount of polyphenols and flavonoids in the organic extract of A. longa L. . Essential oils promote the loss of the integrity of the cell membrane by releasing the cell material to the external environment, in addition to the inhibition of proteins and biofilms . It is worth mentioning that the extracts of A. longa L. mentioned above exceed 0.1 mg/mL, so they would not be suitable for use as antibacterials .
In A. maurorum L., the main components of the roots and aerial parts of the ME were aristolochic acid I (1.17 × 10 −6 M), II (1.28 × 10 −6 M), and IIIa (1.22 × 10 −6 M). These components showed an antiplatelet activity of 100% and the assay was compared with the standard acetylsalicylic acid (3.05 × 10 −5 M) showing an inhibition of platelet aggregation of 100%. Compounds were evaluated using an automatic platelet aggregometer and coagulation tracer .
In A. taliscana Hook. & Arn. in HXE of rhizomes, the ABTS assay (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) was performed to measure the ability of the compounds to trap the ABTS •+ radical. The results obtained were expressed as antioxidant activity of eupomatenoid-7 (151.2 mg GAE/g) and (±)-licarin-A (143.4 mg GAE/g) and were the most active at both points of the determination (minute 1 and 7 of the reaction) . The antioxidant activity is dependent on hydroxyl groups, to which its antioxidant effect is attributed, which is why licarin-B and eupomatenoid-1 did not present this condition. A. bracteolata Lam. showed activity to chelate iron with an antioxidant capacity of 44 ± 0.01%, whose activity is attributed to phenolic compounds . In the ME of A. longa L., it was determined that it has a high amount of polyphenols and flavonoids, and it showed a remarkable antioxidant activity. The total content of phenolic compounds of A. longa L. showed that the ME of roots presented the concentrations of polyphenols and flavonoids with 101.4 mg of GAE/g and 54.21 mg of QE/g of extract, respectively .
Dihydrobenzofuran neolignans, 2-aryldihydrobenzofurans, 8- O -4′-neolignan, and analogs (3.0 × 10 −5 M) as well as the EE of the stem (0.01 mg/mL) of A. fordiana Hemsl. exhibited a neuroprotective effect that prevents cell death in hippocampal cells (HT-22) .
2.4.1. Changes in the Estrous Cycle In tubers of the EE of the species A. indica L., an application has been found regarding changes in the estrous cycle in vivo with a dose of 150 mg/kg of extract . The compounds involved in the effect of the extract were not shown. 2.4.2. Antidiabetic Potential From the EE of roots of A. ringens Vahl., aristolone was identified and it was shown to have an antidiabetic potential in rats at concentrations of 300–75 mg/kg, so this part of the plant could be used in decoctions for the treatment of diabetes with the approval of more relevant studies . 2.4.3. Antifibrotic Activity The compounds - iso -bicyclogermacrenal and spatulenol (3.0 × 10 −5 M) present in the ethyl acetate extract (EAE) of A. yunnanensis Franch. stems were responsible for promoting antifibrotic concentration effects in vivo . However, the concentrations in which the pure compound was handled under in vivo conditions turned out to be high for antifibrotic activity. The genus Aristolochia has extensive traditional and pharmacological uses in various pathological conditions. Therefore, it is an attractive subject for future clinical and experimental research. 2.4.4. Anti-Inflammatory Activity In particular, in A. krisagathra Sivar. & Pradeep., studies of EE of the whole plant have been carried out. An anti-inflammatory activity of 87.1% was obtained with a dose of 400 mg/kg in rats. The compounds that could act in biological activity are alkaloid, anthraquinone, coumarin, flavonoid, phenol, quinone, saponin, steroid, tannin, terpenoid, sugar, glycoside, and xanthoprotein . The anti-inflammatory activity of (−)-hinokinin in tumor necrosis factor- α (TNF- α ) IC 50 = 0.0775 M and interleukin-6 (IL-6) IC 50 = 0.0205 M and aristolactam I (TNF- α ; IC 50 = 0.1168 M, IL-6; IC 50 = 0.0520 M) of A. indica L. in aerial parts of the DCME and EAE, respectively . In in vivo and in vitro studies, doses greater than 200 mg/kg are not usually recommended, as well as values in pure compounds > 2.5 × 10 −5 M . 2.4.5. Snake Anti-Venom Activity The hexanic extract from the roots of A. elegans Mast. was subjected to an inhibition assay of smooth muscle contraction induced by scorpion venom ( Centruroides limpidus limpidus ) in an isolated guinea pig ileum model with an inhibition of 41.66% (0.4 mg/mL), whose effects are related to neolignan-type compounds . On the other hand, in vivo studies in albino mice using a ME from the whole plant of the species A. indica L. demonstrated neutralization against Daboia russelli venom at a dose of 0.14 mg. However, no mention is made of the metabolites responsible for the activity . Compounds obtained from polar extracts, especially aristolochic acids, as mentioned above, are not considered safe compounds according to the International Agency for Research on Cancer (WHO), due to their carcinogenic effects. Despite developing these problems, they can be oriented towards their possible use as antivenoms. Likewise, the presence of aristolochic acids, aristolactams, and their derivatives can be used as chemotaxonomic markers in species of the genus Aristolochia . 2.4.6. Cancer Treatment The AE of A. longa L. roots (5000 mg/kg) did not show hepatic and renal toxicity in a preclinical assay by oral administration in rats. More studies are warranted on its possible use in breast cancer therapy. The possible compounds responsible for the beneficial activity could be the flavonols, flavones, and/or flavonoid glycosides identified in the extract . In addition to the bioactive compounds mentioned above, the amount of lectin in A. longa L. extracts was not favorable for potential cancer treatment in an in vitro immunological activity assay . The use of AE of A. longa L. rhizomes as in vivo anticancer treatment in gingival tumorigenesis caused tissue damage as well as pulmonary and toxicity problems. This could be due to the presence of aristolochic acids in the extract . In a preclinical assay against S-180 solid tumors from BALB/c mice, A. ringens Vahl. roots from extracts of EE (120 mg/kg) and DCME:ME (110 mg/kg) produced a significant value ( p < 0.05) in tumor growth over a period of 9–13 days compared to control models. However, the characterization of the polar and moderately polar extracts lacked phytochemical information .
In tubers of the EE of the species A. indica L., an application has been found regarding changes in the estrous cycle in vivo with a dose of 150 mg/kg of extract . The compounds involved in the effect of the extract were not shown.
From the EE of roots of A. ringens Vahl., aristolone was identified and it was shown to have an antidiabetic potential in rats at concentrations of 300–75 mg/kg, so this part of the plant could be used in decoctions for the treatment of diabetes with the approval of more relevant studies .
The compounds - iso -bicyclogermacrenal and spatulenol (3.0 × 10 −5 M) present in the ethyl acetate extract (EAE) of A. yunnanensis Franch. stems were responsible for promoting antifibrotic concentration effects in vivo . However, the concentrations in which the pure compound was handled under in vivo conditions turned out to be high for antifibrotic activity. The genus Aristolochia has extensive traditional and pharmacological uses in various pathological conditions. Therefore, it is an attractive subject for future clinical and experimental research.
In particular, in A. krisagathra Sivar. & Pradeep., studies of EE of the whole plant have been carried out. An anti-inflammatory activity of 87.1% was obtained with a dose of 400 mg/kg in rats. The compounds that could act in biological activity are alkaloid, anthraquinone, coumarin, flavonoid, phenol, quinone, saponin, steroid, tannin, terpenoid, sugar, glycoside, and xanthoprotein . The anti-inflammatory activity of (−)-hinokinin in tumor necrosis factor- α (TNF- α ) IC 50 = 0.0775 M and interleukin-6 (IL-6) IC 50 = 0.0205 M and aristolactam I (TNF- α ; IC 50 = 0.1168 M, IL-6; IC 50 = 0.0520 M) of A. indica L. in aerial parts of the DCME and EAE, respectively . In in vivo and in vitro studies, doses greater than 200 mg/kg are not usually recommended, as well as values in pure compounds > 2.5 × 10 −5 M .
The hexanic extract from the roots of A. elegans Mast. was subjected to an inhibition assay of smooth muscle contraction induced by scorpion venom ( Centruroides limpidus limpidus ) in an isolated guinea pig ileum model with an inhibition of 41.66% (0.4 mg/mL), whose effects are related to neolignan-type compounds . On the other hand, in vivo studies in albino mice using a ME from the whole plant of the species A. indica L. demonstrated neutralization against Daboia russelli venom at a dose of 0.14 mg. However, no mention is made of the metabolites responsible for the activity . Compounds obtained from polar extracts, especially aristolochic acids, as mentioned above, are not considered safe compounds according to the International Agency for Research on Cancer (WHO), due to their carcinogenic effects. Despite developing these problems, they can be oriented towards their possible use as antivenoms. Likewise, the presence of aristolochic acids, aristolactams, and their derivatives can be used as chemotaxonomic markers in species of the genus Aristolochia .
The AE of A. longa L. roots (5000 mg/kg) did not show hepatic and renal toxicity in a preclinical assay by oral administration in rats. More studies are warranted on its possible use in breast cancer therapy. The possible compounds responsible for the beneficial activity could be the flavonols, flavones, and/or flavonoid glycosides identified in the extract . In addition to the bioactive compounds mentioned above, the amount of lectin in A. longa L. extracts was not favorable for potential cancer treatment in an in vitro immunological activity assay . The use of AE of A. longa L. rhizomes as in vivo anticancer treatment in gingival tumorigenesis caused tissue damage as well as pulmonary and toxicity problems. This could be due to the presence of aristolochic acids in the extract . In a preclinical assay against S-180 solid tumors from BALB/c mice, A. ringens Vahl. roots from extracts of EE (120 mg/kg) and DCME:ME (110 mg/kg) produced a significant value ( p < 0.05) in tumor growth over a period of 9–13 days compared to control models. However, the characterization of the polar and moderately polar extracts lacked phytochemical information .
A total of 141 publications were included in this review. SciFinder and EBSCO were used to search for articles that analyzed the beneficial effects of Aristolochia in the period from 2005 to 2021. Eighty-eight different species of Aristolochia were considered and reviewed by International Plant Names Index and World Flora Online. The inclusion criteria that were retained included: phytochemicals, Aristolochia , beneficial effects, extract, pharmacology, and ethnomedicinal. Articles were excluded based on the following criteria: articles that did not address the intervention, articles without adequate Aristolochia species theoretical foundations, and articles that did not include Aristolochia species.
The review in the literature about biological activities allowed identifying studies of different species of the genus Aristolochia highlighting phytochemical and pharmacological aspects, and their possible clinical applications. In the roots and leaves, a greater number of beneficial effects were found. From this review, it is concluded that the information detailed the relevant species of the genus Aristolochia as promising candidates for natural uses in human health of greater relevance in extracts and pure compounds in anticancer activities. More selective studies are suggested in terms of concentration parameters as well as clinical studies for higher quality.
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Differences in Weight Loss Postsleeve Gastrectomy Among Patients With Various Types of Obesity Based on Waist-To-Hip Ratio Classification | f55a0015-e271-4ac0-9b5d-47c2fbb0c37a | 11925632 | Surgical Procedures, Operative[mh] | Obesity has become a major public health problem in most developed countries, with the number of obese adults worldwide reaching 500 million and growing rapidly . Obesity not only increases the risk of cardiovascular, digestive, and endocrine system diseases but also seriously damages human health [ – ]. According to the latest international guidelines for metabolic and bariatric surgery (MBS) indications, MBS is recommended for individuals with a body mass index (BMI) > 35 kg/m 2 regardless of the presence or severity of comorbidities. For individuals with a BMI valve ranging from 30 to 34.9 kg/m 2 and metabolic diseases, MBS treatment should be considered. In addition, the BMI threshold should be adjusted for Asian populations: BMI > 25 kg/m 2 indicates clinical obesity, while BMI > 27.5 kg/m 2 should be considered for MBS treatment . Based on the latest guidelines for MBS indications, Asian individuals with a BMI > 27.5 kg/m 2 are recommended to undergo MBS treatment. BMI is commonly used as a measure of total body fat content; however, the waist-to-hip ratio (WHR) can provide a more intuitive and straightforward reflection of fat distribution in various types of patients with obesity. Relevant studies indicate that the distribution of adipose tissue plays a significant role in the development of obesity . Patients with more abdominal fat are more likely to suffer from obesity-related complications. Therefore, the relationship between abdominal fat and obesity is very close. According to a 2018 survey undertaken by the International Federation for the Study of Obesity (IFSO), laparoscopic sleeve gastrectomy (LSG) has become the most common weight-loss surgery globally, accounting for 55.4% of all weight loss surgeries . However, it is unclear whether LSG has different effects on weight loss in various types of patients with morbid obesity.
2.1. Participants This study included 360 patients with obesity who underwent LSG at the Qianfoshan Hospital, Jinan, Shandong Province, China, from December 2019 to September 2024. All patients received unified postoperative guidance and health education. This study included 109 men and 251 women. The mean BMI value was 41.25 (30.12–69.44) and the mean age was 32 years (14–62). 2.2. Inclusion/Exclusion Criteria Inclusion criteria were as follows: (1) age 16–65 years old; (2) patients who met the surgical indications of the American Society for Metabolic and Bariatric Surgery and IFSO MBS indications (2022 edition); and (3) postoperative patients who could be followed up normally. Exclusion criteria were as follows: (1) patients who needed to use obesogenic drugs due to their condition after surgery; (2) patients who became pregnant shortly after surgery; and (3) patients lost to follow-up for unknown reasons. 2.3. Grouping Method Central obesity was defined as a WHR > 0.85 in women and > 1.0 in men. Noncentral obesity was defined as a WHR ≤ 0.85 in women and ≤ 1.0 in men . 2.4. Data Collection Data were collected independently by two individuals. Weight was measured without shoes and with minimal clothing to an accuracy of 0.1 kg. The height measurements were accurate to 0.01 m. BMI was calculated as the weight in kilograms divided by the square of the height in meters. The World Health Organization (WHO) Stepwise Approach to Surveillance protocol for measuring waist circumference instructs that the measurement be made at the approximate midpoint between the lower margin of the last palpable rib and the top of the iliac crest. The hip circumference should be measured around the widest part of the hip. Measurements were made using antitensile tape, which was placed close to the body of the patient. Participants should stand with their feet together, arms at their sides, weight evenly distributed, and wear a minimal amount of clothing. Participants should be relaxed and measurements should be taken at the end of normal expiration. Each measurement should be repeated twice. If the two measurements are within 1 cm of each other, the mean value should be calculated. If the difference between the two measurements is more than 1 cm, the two measurements should be repeated . After LSG, we conducted thorough follow-ups at 1, 3, 6, and 12 month postsurgery through a combination of hospital visits and telephone interviews. These follow-up visits included assessments of postoperative height and weight, procedure-related complications, and the remission of preoperative comorbidities. Per cent total weight loss (% TWL) was calculated using the following formula: (1) Weight loss preoperative weight × 100 % . Per cent excess weight loss (% EWL) was defined as follows: (2) % EWL = weight loss baseline excess weight × 100 % . Baseline excess weight was calculated as follows: (3) Baseline excess weight = baseline weight — minus ideal weight . The ideal weight is based on the weight of the person at a BMI of 23 kg/m2 . 2.5. Laboratory Measurements Fasting (12 h fast) blood samples were obtained for blood chemistry, including blood cell analysis (5 class method), albumin, glucose, triglycerides, high-density lipoprotein, low-density lipoprotein, cholesterol, alanine aminotransferase, aspartate aminotransferase, glycosylated hemoglobin A1c, fasting insulin, and fasting C-peptide. 2.6. Statistical Analysis The study population was analyzed overall and then, after grouping according to sex, for men and women. Central obesity was classified according to WHR. Descriptive data satisfying normal distribution were expressed as the mean ± standard deviation and those satisfying skewed distribution were expressed as the median (P25 and P75). The incidence of obesity-related complications was compared between the central and the noncentral obesity groups. The chi-square test was used for preoperative evaluation. Two independent sample t -test and rank sum test were used to compare the characteristics between the two groups, and the t -test and rank sum test were used to compare the difference of weight loss effect. Linear regression was used to determine the factors affecting EWL and TWL. A two-tailed p value < 0.05 was used to infer statistical significance. Statistical analysis was performed using SPSS software Version 26.0 for Windows (SPSS, Inc., Chicago, IL, United States).
This study included 360 patients with obesity who underwent LSG at the Qianfoshan Hospital, Jinan, Shandong Province, China, from December 2019 to September 2024. All patients received unified postoperative guidance and health education. This study included 109 men and 251 women. The mean BMI value was 41.25 (30.12–69.44) and the mean age was 32 years (14–62).
Inclusion criteria were as follows: (1) age 16–65 years old; (2) patients who met the surgical indications of the American Society for Metabolic and Bariatric Surgery and IFSO MBS indications (2022 edition); and (3) postoperative patients who could be followed up normally. Exclusion criteria were as follows: (1) patients who needed to use obesogenic drugs due to their condition after surgery; (2) patients who became pregnant shortly after surgery; and (3) patients lost to follow-up for unknown reasons.
Central obesity was defined as a WHR > 0.85 in women and > 1.0 in men. Noncentral obesity was defined as a WHR ≤ 0.85 in women and ≤ 1.0 in men .
Data were collected independently by two individuals. Weight was measured without shoes and with minimal clothing to an accuracy of 0.1 kg. The height measurements were accurate to 0.01 m. BMI was calculated as the weight in kilograms divided by the square of the height in meters. The World Health Organization (WHO) Stepwise Approach to Surveillance protocol for measuring waist circumference instructs that the measurement be made at the approximate midpoint between the lower margin of the last palpable rib and the top of the iliac crest. The hip circumference should be measured around the widest part of the hip. Measurements were made using antitensile tape, which was placed close to the body of the patient. Participants should stand with their feet together, arms at their sides, weight evenly distributed, and wear a minimal amount of clothing. Participants should be relaxed and measurements should be taken at the end of normal expiration. Each measurement should be repeated twice. If the two measurements are within 1 cm of each other, the mean value should be calculated. If the difference between the two measurements is more than 1 cm, the two measurements should be repeated . After LSG, we conducted thorough follow-ups at 1, 3, 6, and 12 month postsurgery through a combination of hospital visits and telephone interviews. These follow-up visits included assessments of postoperative height and weight, procedure-related complications, and the remission of preoperative comorbidities. Per cent total weight loss (% TWL) was calculated using the following formula: (1) Weight loss preoperative weight × 100 % . Per cent excess weight loss (% EWL) was defined as follows: (2) % EWL = weight loss baseline excess weight × 100 % . Baseline excess weight was calculated as follows: (3) Baseline excess weight = baseline weight — minus ideal weight . The ideal weight is based on the weight of the person at a BMI of 23 kg/m2 .
Fasting (12 h fast) blood samples were obtained for blood chemistry, including blood cell analysis (5 class method), albumin, glucose, triglycerides, high-density lipoprotein, low-density lipoprotein, cholesterol, alanine aminotransferase, aspartate aminotransferase, glycosylated hemoglobin A1c, fasting insulin, and fasting C-peptide.
The study population was analyzed overall and then, after grouping according to sex, for men and women. Central obesity was classified according to WHR. Descriptive data satisfying normal distribution were expressed as the mean ± standard deviation and those satisfying skewed distribution were expressed as the median (P25 and P75). The incidence of obesity-related complications was compared between the central and the noncentral obesity groups. The chi-square test was used for preoperative evaluation. Two independent sample t -test and rank sum test were used to compare the characteristics between the two groups, and the t -test and rank sum test were used to compare the difference of weight loss effect. Linear regression was used to determine the factors affecting EWL and TWL. A two-tailed p value < 0.05 was used to infer statistical significance. Statistical analysis was performed using SPSS software Version 26.0 for Windows (SPSS, Inc., Chicago, IL, United States).
3.1. Baseline Patient Characteristics A total of 360 patients were enrolled in this observational study (men: 109, 30.3%; women: 251, 69.7%). The mean BMI of all patients was 41.25 (30.12–69.44), and the mean age was 32 years (14–62). The mean BMI of the men was 45.57 ± 7.74, and the mean waist-hip ratio was 1.01 ± 0.05. The mean BMI of the women was 38.89 (35.20, 42.32), and the mean WHR was 0.92 ± 0.07. A total of 360 patients completed the 1 month follow-up, 312 patients completed the 3 month follow-up, 208 patients completed the 6 month follow-up and 136 patients completed the 12 month follow-up. 3.2. Comparison of Preoperative Information In obese patients, various obesity-related comorbidities are common. Women and patients with type 2 diabetes are more likely to develop central obesity ( ). There were significant differences in BMI and white blood cell counts between women in the central and noncentral obesity groups. Women with central obesity had higher preoperative BMI and white blood cell counts ( ). The differences in GGT, PLT, HbA1c, and FPG levels were more obvious in men of the central and noncentral obesity groups. Men with central obesity had lower PLT and higher GGT, HbA1c, and FPG levels ( ). 3.3. Weight Loss When EWL was used as a measure of postoperative weight loss effect, women in the noncentral obesity group showed a better weight loss effect than those in the central obesity group in the first and third months after surgery, while there was no significant difference in the sixth- and twelfth-months postsurgery ( and ). There was no difference in postoperative weight loss between men in the central and noncentral obesity groups of males ( and ). When TWL was used as a measure of postoperative weight loss effect, the effect of weight loss in the first month after surgery in women with noncentral obesity was slightly better than that in women with central obesity. There was no difference between the third, sixth, and twelfth months after surgery ( and ). There was no difference in postoperative weight loss between the men in the central and noncentral obesity groups ( and ). We carried out multiple linear regression analysis to further explore the factors affecting the weight loss effect. To evaluate the influence of central obesity, we conducted a linear regression analysis of % TWL and % EWL at each time point after surgery in and . % TWL, % EWL, and BMI were approximately normally distributed. There was no significant multicollinearity for the factors affecting % TWL and % EWL. We observed that WHR significantly affected weight loss in the first and third postoperative months. The effect of BMI on weight loss within 1 year after surgery was statistically significant. Patient gender and age demonstrate no significant association with postoperative weight loss outcomes. Similarly, preoperative comorbidities such as metabolic syndrome or type 2 diabetes mellitus do not exhibit clinically meaningful effects on weight reduction efficacy following surgery. However, the temporal impact of pre-existing metabolic disorders on postoperative weight loss varies significantly: a history of hypertension is associated with attenuated weight loss during the first postoperative month, while hyperlipidemia predominantly influences outcomes in the third postoperative month. The research findings demonstrate that patients with central obesity complicated by hypertension and/or hyperlipidemia exhibit significantly restricted weight loss during the early postoperative period. These findings underscore the importance of considering specific metabolic comorbidities when formulating postoperative management strategies for this patient population.
A total of 360 patients were enrolled in this observational study (men: 109, 30.3%; women: 251, 69.7%). The mean BMI of all patients was 41.25 (30.12–69.44), and the mean age was 32 years (14–62). The mean BMI of the men was 45.57 ± 7.74, and the mean waist-hip ratio was 1.01 ± 0.05. The mean BMI of the women was 38.89 (35.20, 42.32), and the mean WHR was 0.92 ± 0.07. A total of 360 patients completed the 1 month follow-up, 312 patients completed the 3 month follow-up, 208 patients completed the 6 month follow-up and 136 patients completed the 12 month follow-up.
In obese patients, various obesity-related comorbidities are common. Women and patients with type 2 diabetes are more likely to develop central obesity ( ). There were significant differences in BMI and white blood cell counts between women in the central and noncentral obesity groups. Women with central obesity had higher preoperative BMI and white blood cell counts ( ). The differences in GGT, PLT, HbA1c, and FPG levels were more obvious in men of the central and noncentral obesity groups. Men with central obesity had lower PLT and higher GGT, HbA1c, and FPG levels ( ).
When EWL was used as a measure of postoperative weight loss effect, women in the noncentral obesity group showed a better weight loss effect than those in the central obesity group in the first and third months after surgery, while there was no significant difference in the sixth- and twelfth-months postsurgery ( and ). There was no difference in postoperative weight loss between men in the central and noncentral obesity groups of males ( and ). When TWL was used as a measure of postoperative weight loss effect, the effect of weight loss in the first month after surgery in women with noncentral obesity was slightly better than that in women with central obesity. There was no difference between the third, sixth, and twelfth months after surgery ( and ). There was no difference in postoperative weight loss between the men in the central and noncentral obesity groups ( and ). We carried out multiple linear regression analysis to further explore the factors affecting the weight loss effect. To evaluate the influence of central obesity, we conducted a linear regression analysis of % TWL and % EWL at each time point after surgery in and . % TWL, % EWL, and BMI were approximately normally distributed. There was no significant multicollinearity for the factors affecting % TWL and % EWL. We observed that WHR significantly affected weight loss in the first and third postoperative months. The effect of BMI on weight loss within 1 year after surgery was statistically significant. Patient gender and age demonstrate no significant association with postoperative weight loss outcomes. Similarly, preoperative comorbidities such as metabolic syndrome or type 2 diabetes mellitus do not exhibit clinically meaningful effects on weight reduction efficacy following surgery. However, the temporal impact of pre-existing metabolic disorders on postoperative weight loss varies significantly: a history of hypertension is associated with attenuated weight loss during the first postoperative month, while hyperlipidemia predominantly influences outcomes in the third postoperative month. The research findings demonstrate that patients with central obesity complicated by hypertension and/or hyperlipidemia exhibit significantly restricted weight loss during the early postoperative period. These findings underscore the importance of considering specific metabolic comorbidities when formulating postoperative management strategies for this patient population.
Recently, many studies have used computed tomography scans to quantify the abdominal fat area to analyze obesity and related comorbidities . Therefore, we considered an approach that uses anthropometric parameters to determine fat distribution in patients with obesity to analyze differences in postoperative weight loss. WHR can concisely and clearly indicate the fat distribution of patients, and it is not harmful to patients. On the basis of WHR, patients could be classified as having central or noncentral obesity according to the WHO criteria . Given that the participants in this study were all Chinese patients, a WHR cutoff point suitable for Asian patients with obesity was used . This study investigated the difference in weight loss in patients with various types of obesity after LSG. The number of women in our cohort was twice that of men, but the mean BMI of men was higher than that of women. We found that there was a significant difference in the weight loss effect exhibited by women in the central and noncentral obesity groups in the early postoperative period, but there was no significant difference in the weight loss effect of the men in these two patient groups. This may be related to the different metabolic characteristics and physiological structure of men and women, which needs further study. We conducted an analysis of weight loss effect according to sex because the cutoff points for WHR differed between men and women and because women were more likely to have central obesity ( ). Based on our data, we suggest that reasonable diet and exercise interventions should be carried out for women with central obesity in order to obtain better weight loss in the early postoperative period. The results were different when we employed various other indicators (such as % EWL or % TWL) to measure the effect of postoperative weight loss. % EWL is more focused on the loss of excess weight and can more accurately reflect the success of surgery, especially for those who are already overweight but were unable to reach the ideal weight . % TWL reflects the overall weight loss after surgery . Many studies have found that there are significant differences in % EWL, but not in % TWL, due to the differences in regions, populations, and types of surgery . In addition, some data were missing from each phase of our postoperative follow-up data, which may have had some effect on the results. In the present study, women with central obesity had higher BMI and white blood cell counts, which were associated with more abdominal fat in patients with central obesity. Abdominal adipose tissue secretes a variety of inflammatory factors, such as tumor necrosis factor and interleukin-6, which can stimulate the immune system and lead to leukocytosis . Men with central obesity had higher HbA1c and FPG levels, which is consistent with the fact that patients with type 2 diabetes are more likely to develop central obesity. Previous studies have shown that patients with type 2 diabetes mellitus and central obesity are at a greater risk of cardiovascular disease . Central obesity represents more abdominal fat, and increased abdominal fat not only affects sleep quality but also increases the risk of gout . Studies have shown that patients with central obesity are also more likely to suffer from cholelithiasis, and WHR is positively correlated with the severity of hepatic steatosis . WHR was found to be the best predictor of hypertension among 10 obesity-related indicators . Therefore, central obesity is closely related to a variety of obesity-related complications. Hence, it is necessary to carry out reasonable dietary and exercise interventions and even drug intervention for patients with central obesity after surgery. One study found no association between WHR and percent weight change with diet management alone for weight loss . Therefore, the use of LSG in the treatment of central obesity is highly effective. This study primarily focuses on the waist-to-weight ratio as a key predictive indicator for postoperative weight loss outcomes. However, it is important to note that other multidimensional factors may also influence weight loss efficacy, including demographic characteristics (gender and age), clinical features (preoperative comorbidities), behavioral factors (physical activity levels and dietary adherence), and genetic factors (genetic predisposition) [ – ]. The research findings demonstrate that patients with central obesity complicated by hypertension and/or hyperlipidemia exhibit significantly restricted weight loss during the early postoperative period. For this specific population, implementing early dietary interventions and exercise guidance can significantly enhance weight loss outcomes. However, this study has the following limitations: First, postoperative dietary management and exercise interventions were not included as study variables. The existing literature suggests that systematic lifestyle interventions can lead to more significant weight loss outcomes in the year after surgery . Second, the influence of genetic factors was not considered. Research indicates that patients carrying multiple obesity-related genetic loci tend to have relatively poorer weight loss outcomes after surgery . Based on these findings, future research will focus on the following areas for improvement: (1) developing a multifactorial predictive model that incorporates genetic predisposition; (2) systematically evaluating the long-term effects of postoperative lifestyle interventions; and (3) exploring the mechanisms of gene-environment interactions on weight loss efficacy. Delving deeper into these research directions will contribute to the development of personalized postoperative management strategies. The follow-up period in this study was limited to 12 months postoperatively, which may not sufficiently reflect the long-term stability of weight loss outcomes or comprehensively assess potential long-term complications (such as weight regain and micronutrient deficiencies). Based on existing literature, the weight stabilization period for patients after laparoscopic sleeve gastrectomy (LSG) typically occurs beyond 12 months postoperatively, suggesting that extending the follow-up duration holds significant clinical value for phenotype-specific analysis . Therefore, we recommend that future research prioritize the establishment of longitudinal follow-up cohorts spanning 3–5 years. Such a study design would facilitate the evaluation of the durability of weight loss outcomes in patients with different obesity types. However, due to the current lack of systematic long-term follow-up data, these research directions have yet to be realized. This limitation underscores the importance of establishing standardized long-term follow-up mechanisms, which will be a key focus of our team's next research efforts. Our study has several limitations: (1) This study utilized a retrospective design, which inherently limits the ability to establish causal relationships between preoperative WHR classification and postoperative weight loss outcomes. Potential confounding factors, such as unmeasured lifestyle variables or selection bias, may influence the observed associations. Future prospective studies with standardized protocols for data collection and adjustment for confounding variables (e.g., socioeconomic status and medication use) are needed to validate these findings. (2) The differences in preoperative laboratory examination data between men and women cohorts may be related to insufficient sample size, and the fact that long-term follow-up data are missing, which may have a certain impact on the analysis of the difference of weight loss effect. (3) The absence of data on postoperative behavioral changes (such as dietary and exercise habits) and genetic factors represents a significant limitation. These variables should be prioritized in future research directions. (4) The follow-up period was only 1 year, so the long-term effect of weight loss could not be evaluated. Future research should focus on this aspect. (5) This study only focused on the Chinese population and was a single-center study. Due to the differences in WHR cutoff points in different countries and regions, future multicenter and multiregion studies should be carried out to clarify the difference in weight loss effect between the central and non-central obesity groups.
LSG can effectively treat morbid obesity and alleviate the related metabolic diseases associated with obesity, as well as reduce postoperative complications. Women with central obesity have worse early weight loss outcomes. The WHR can serve as an independent predictor of early weight loss outcomes. This can provide corresponding postoperative treatment plans for patients with different types of obesity to achieve better weight loss outcomes.
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New Technologies for Kidney Surgery Planning 3D, Impression, Augmented Reality 3D, Reconstruction: Current Realities and Expectations | 45ae8032-12cd-4940-9c0b-f5785528ec00 | 8143991 | Patient Education as Topic[mh] | Three-dimensional printing (3DP) has emerged in the late 1980s, but its application in medical field dates to 2000s . Until recently, its use was limited mostly to orthopedics and dentistry. As three-dimensional (3D) printers have become more widespread and affordable, a rapid increase in the use of 3DP in medicine has been registered. Currently, several types of technologies are available for printing such as binder jetting, material jetting, vat photopolymerization technologies, and powder bed fusion; furthermore 3D printers can now generate object from different materials such as plastics, wax, ceramics, and metal . In recent years, 3DP-technology (3DPT) allowed to manufacture models to produce facsimiles of patients’ organs, even entire body parts, to be used for training purposes and to improve surgical planning. Moreover, the introduction of artificial realities created with the help of software (virtual realities VR, augmented realities) represents a further step in 3DPT allowing the surgeon to perform guided-surgery without giving up concentration on the operating field. Aim of this review is to examine the application of 3DP in kidney surgery; in particular we focus on surgical planning, patient education, training, and augmented reality (AR).
Pre-operative planning is crucial to improve surgical outcome and to reduce possible intra- or post-operative complications. 3D models (3DM) could play an important role helping the surgeons to properly understand patient specific anatomy and guiding their intraoperative decisions. 3D anatomical replicas printed directly from patients DICOM images (CT scan or MRI) have been used to aid information in the preoperative planning of complex surgical procedures and trying to reduce perioperative complications . Surgical planning with 3DM has significant advantages over the current two-dimensional (2D) images. Surgeons have a more realistic overview and better comprehension of the area on which they’re going to perform surgery. Possible benefits provided from these models are better decision-making and consequently increased surgical confidence. Applications of 3DP in Nephron Sparing Surgery (NSS) More than a half of publications about 3DM in urology reported surgical planning as their primary outcome. In the era of nephron-sparing surgery (NSS), due to the complex anatomy and vasculature, the potential prolonged renal ischemia, and the often unclear tumor depth invasion, is not surprising that the majority of studies have focused their attention on kidney cancer . Even if ablative techniques and active surveillance are possible choices in selected patients, surgical treatment for renal masses still represents the gold standard and has evolved, through years, to a NSS approach. Until 2011, there were no studies proving better outcomes of partial nephrectomy (PN) instead radical nephrectomy (RN) . In 2012, Sun and colleagues demonstrated for the first time that, in multivariable analysis, patients who underwent PN were significantly less likely to die for other-causes mortality (OCM) compared with the RN cohort ( p = 0.04), stating that PN should be offered “whenever technically feasible” . Nevertheless, feasible does not always mean easy: higher R.E.N.A.L. score masses are more prone to result in higher Clavien–Dindo post-operative complications ( p = 0.043) and significant drop in post-operative renal function ( p = 0.004), due to surgical complexity . Prior to consider surgical outcomes, preoperative planning can strongly be influenced by 3DM, especially in case of complex renal masses. Urology has moved from open to minimally invasive surgery (MIS) and from radical organ extirpation to NSS. As a result, surgeons need to rely on models that can give them a better understanding of patients’ disease helping in improving surgical planning. Silberstein et al. in 2014 performed 5 PNs (4 robotic and 1 open) with complete excision of renal masses after creating 5 customized, patient-specific, 3D kidney models . The main characteristic of these models was the enhanced renal lesions suspicious for malignancy. In this study, all interventions were successfully performed with an average ischemia time of 21 min, all surgical margins were negative, and complications were minimal. A preliminary report by Zhang et al. showed that, in patients with T1 renal masses eligible for NSS, 3DMs had higher scores in surgical planning . Furthermore, the two surgeons involved stated that intraoperative consultation of the 3DM was helpful for relationship of the tumor with surrounding tissues, depth of resection, and avoidance of key structures injuries such as renal hilum. However, no specific questions regarding how the 3DMs impacted surgical planning decisions were administered. After 1 year, Wake et al. selected 10 renal neoplasms scoring more than 5 (range 6–10) at R.E.N.A.L. nephrometry score, and submitted 2D images before 3DMs to three experienced urologic oncology surgeons . After submission of models, 30–50% of surgeons were prone to change the surgical approach, with the largest impact about transperitoneal or retroperitoneal approach and clamping. Porpiglia et al. evaluated the usefulness of 3D printed kidney models and surgeon’s perception. Based on their data, 3DMs seemed to influence surgeons in the choice of the most appropriate type of ischemia (off-clamp vs global ischemia vs partial ischemia) and the type of resection to perform (enucleation or enucleoresection) without difference on the basis of surgeons’ experience . However, good planning doesn’t always mean good surgical outcomes. Many studies have focused their attention also on results after 3DMs visualization and to what extent they can influence surgeries. In a feasibility study by Rundstedt et al., a patient-specific presurgical protocol for robot-assisted PN (RAPN) was developed . In their study, 10 patients with solid renal masses underwent RAPN after preoperative rehearsal using 3D-printed kidney models made by a silicon-based material. R.E.N.A.L. nephrometry scores were between 7 and 11 (mean 8.9). Authors compared resection times of the model and the tumor. Their results showed no statistically significant difference between the 3DM and the excised tumor in mean resection time (6:58 vs 8:22 min, p = 0.162) and volumes excised (38.50 vs 41.79 mm 3 , p = 0.976). Only 1/10 patients had positive surgical margins. Authors concluded that pre-surgical rehearsal could significantly improve resection strategy, but this study lacks of a control group. Another feasibility study investigating how 3D printed kidney models can influence surgical procedures was performed by Maddox et al. . With the aim of allowing preoperative and robotic surgical simulation, authors constructed patient-specific physical 3DMs made by materials that could approximate quite well the properties of renal tissue. Seven models were successfully created, and PN and renorrhaphy were performed on each replica. After simulation, all patients underwent RAPN with negative surgical margins, reporting an average warm ischemia time of 25 min. Mean R.E.N.A.L. nephrometry score was 7.4. Comparing the seven cases and the “Tulane Urology prospectively maintained RAPN database,” surgeries with 3DMs had larger tumors, fewer complications, longer warm ischemic time, fewer positive margins, and shorter hospitalization, but the only statistically significant finding was a decreased estimated blood loss (EBL) (185.7 vs. 235.6 ml, p = 0.01), suggesting that preoperative 3DM rehearsal may decrease the learning curve for trainees and improve surgical outcomes. Otherwise, authors admitted that further evaluation was needed. Kyung et al. compared 17 patients who underwent PN aided by prior consultation of 3D patient-specific kidney models with a control group consisting of patients who underwent PN from the same surgeon and approximately during the same time period (2014–2015) . Similarly to Maddox, authors found that the only statistically significant difference was diminished intra-operative blood loss (IBL) (182 cc vs. 310 cc, p < 0.01). No complications occurred in the 3D printed group. Moreover, patients reported an overall improved understanding of the disease, surgical procedure, and trust in surgical team after consultation of the 3DM. Despite the relatively small cohort, the frequent lack of a control group and the low statistical power, these studies have contributed to support the efficacy of 3DM simulation before complex renal surgery. Recently, Fan et al. retrospectively analyzed data of 69 patients who underwent 3D laparoscopic PN (LPN) and 58 who underwent traditional LPN between January 2016 and February 2018 . They reported a significant reduction in warm ischemia time (WIT) in the 3D group (24.1 ± 5.1 for the 3D cohort and 26.6 ± 4.2 min in the traditional LPN, p < 0.05), against a longer surgery waiting time (13.6 ± 3.4 days and 7.0 ± 0.6 days, respectively, p < 0.05). Subgroup analysis according to R.E.N.A.L. scores confirmed that, in patients with scores ≥ 8, the 3D group had significantly shorter WIT and less IBL (131.9 ± 78.5 vs 179.2 ± 76.1, p < 0.05) than the traditional LPN group. Finally, a Japanese group reported their preliminary experience of what they called “4D surgical navigation” in minimally invasive off-clamp PN . It consists of a full-scale size 3D printed kidney designed so that the tumor and its margin (2–5 mm around the tumor) could be removed. This feature allowed the surgeon to visualize, during surgical planning, both pre- and post-resection kidney (the fourth considered dimension was the time). Models helped the surgeons to create a working mental map for resection. Ten patients with complex renal masses (R.E.N.A.L. score ≥ 8) were selected and underwent minimally invasive off-clamp PN with acceptable perioperative outcomes and surgical margins that resulted to be nearly identical to 3D printed tumors. A statistically significant difference was found in the time of intraoperative ultrasound with a 3D model compared to standard surgeries (mean 3.3 min vs 6.3 min, respectively, p = 0.021). Moreover, surgeons claimed the usefulness of 3DM tactile feedback. In contrast, 4 to 9 h were needed for printing and 3 to 9 days to complete the model. Costs of the models ranged from 450 to 680 dollars. Applications of 3DP in Percutaneous Nephrolithotomy (PCNL) Nephrolithiasis is a common disease, and recent data show a prevalence up to 15% and an overall incidence rate growing . Among endourologic techniques, percutaneous nephrolithotomy (PCNL) represents the gold standard for renal stones larger than 20 mm due to advantages in operative time and morbidity rates . Renal access isn’t always performed by urologists due to a not so easy learning curve. In fact, many studies have focused on imaging modalities used for guidance during percutaneous access for both urologists and radiologists. Anyhow, optimal selection of calyx for puncture and nephrostomy tract is one of the most important steps of PCNL surgical planning. Difficulties include performing a trajectory that leads directly to the target stone without affecting neighbors’ structures. Inadvertent organ injuries as well as multiple tracts before achieving the correct calyx access can lead to an increase in surgery duration, higher complications rates, and consequently to a longer post-operative length of stay (LOS) . In recent years, the rapid development of patient-specific 3D segmentation and reconstruction in Urology has led to the combination of patient-specific 3DMs with preoperative planning for needle guidance during PCNL procedures. In 2015, Gadzhiev et al. proposed a plasticine 3D replica of pelvicalyceal system on 32 patients with staghorn stones taken to the operating room and used as a reference model . Percutaneous renal access was performed successfully in all cases; more than a half (56%) had a single tract with an overall stone-free rate (SFR) after second look of 87.3%. In 2019, Xu et al. printed 36 patient-specific 3DMs (3 for each patient) and simulated 3 puncture sites from upper-, middle- and lower-pole calyces . The puncture site that achieved the better SFR in the model was then used as reference during surgery, and a good correspondence was founded between post-operative stone volume of the model and of the patient ( p < 0.001, 95% CI). In late 2019, an Italian group presented a clinical case of a 30-year-old man with left renal stone (25 × 15 mm) . A 3D digital and physical renal model to aid the surgeon during procedure in planning and guiding the percutaneous access during PCNL was performed. The patient safely underwent PCNL with 1 single percutaneous puncture (time of puncture 2 min). Overall surgical time was 90 min. Post-operative CT scan confirmed patient’s SFR. Brehmer et al. evaluated how 3D-CT reconstructions could influence the choice of access route and treatment outcomes in 35 patients planned for PCNL (88% with complex renal stone) . Access route were planned on 3D-CT reconstructions using anatomical landmarks (ribs, spinous process, etc.). The results were a change of access plan in 15/28 patients, while in 7 patients, access could not be planned without 3D-CT, totaling 22/35 (63%). Sixty-nine percent of these patients (24/35) were stone-free after single PCNL. Similarly, Li et al. performed image segmentation and 3D reconstruction from CT scans of 15 patients with complex renal stone, including one patient with a horseshoe kidney, 8 patients with partial/complete staghorn stones, and 6 patients with multiple renal stones . Virtual safe and reliable percutaneous renal access route were established for each patient by comprehensive planning based on the 3DM of renal stones. The safest and most effective percutaneous tract for stone clearance was planned on the models and then uploaded onto a screen during procedure in the operating room. The surgeon could visualize the reconstructed 3DM adjusting kidney transparency and felt more confident and comfortable with the access aided by the virtual puncture. During lithotripsy, the 3D models offered a panoramic view of the stone and collecting system guiding intraoperative nephroscopy. PCNL were completed successfully in all 15 patients, the one-session SFR was 93.3 %, and the final SFR was 100%. Future studies are required, with larger cohorts, but Manning hypothesis of “practice before you play” could become the standard of care for complex surgeries .
More than a half of publications about 3DM in urology reported surgical planning as their primary outcome. In the era of nephron-sparing surgery (NSS), due to the complex anatomy and vasculature, the potential prolonged renal ischemia, and the often unclear tumor depth invasion, is not surprising that the majority of studies have focused their attention on kidney cancer . Even if ablative techniques and active surveillance are possible choices in selected patients, surgical treatment for renal masses still represents the gold standard and has evolved, through years, to a NSS approach. Until 2011, there were no studies proving better outcomes of partial nephrectomy (PN) instead radical nephrectomy (RN) . In 2012, Sun and colleagues demonstrated for the first time that, in multivariable analysis, patients who underwent PN were significantly less likely to die for other-causes mortality (OCM) compared with the RN cohort ( p = 0.04), stating that PN should be offered “whenever technically feasible” . Nevertheless, feasible does not always mean easy: higher R.E.N.A.L. score masses are more prone to result in higher Clavien–Dindo post-operative complications ( p = 0.043) and significant drop in post-operative renal function ( p = 0.004), due to surgical complexity . Prior to consider surgical outcomes, preoperative planning can strongly be influenced by 3DM, especially in case of complex renal masses. Urology has moved from open to minimally invasive surgery (MIS) and from radical organ extirpation to NSS. As a result, surgeons need to rely on models that can give them a better understanding of patients’ disease helping in improving surgical planning. Silberstein et al. in 2014 performed 5 PNs (4 robotic and 1 open) with complete excision of renal masses after creating 5 customized, patient-specific, 3D kidney models . The main characteristic of these models was the enhanced renal lesions suspicious for malignancy. In this study, all interventions were successfully performed with an average ischemia time of 21 min, all surgical margins were negative, and complications were minimal. A preliminary report by Zhang et al. showed that, in patients with T1 renal masses eligible for NSS, 3DMs had higher scores in surgical planning . Furthermore, the two surgeons involved stated that intraoperative consultation of the 3DM was helpful for relationship of the tumor with surrounding tissues, depth of resection, and avoidance of key structures injuries such as renal hilum. However, no specific questions regarding how the 3DMs impacted surgical planning decisions were administered. After 1 year, Wake et al. selected 10 renal neoplasms scoring more than 5 (range 6–10) at R.E.N.A.L. nephrometry score, and submitted 2D images before 3DMs to three experienced urologic oncology surgeons . After submission of models, 30–50% of surgeons were prone to change the surgical approach, with the largest impact about transperitoneal or retroperitoneal approach and clamping. Porpiglia et al. evaluated the usefulness of 3D printed kidney models and surgeon’s perception. Based on their data, 3DMs seemed to influence surgeons in the choice of the most appropriate type of ischemia (off-clamp vs global ischemia vs partial ischemia) and the type of resection to perform (enucleation or enucleoresection) without difference on the basis of surgeons’ experience . However, good planning doesn’t always mean good surgical outcomes. Many studies have focused their attention also on results after 3DMs visualization and to what extent they can influence surgeries. In a feasibility study by Rundstedt et al., a patient-specific presurgical protocol for robot-assisted PN (RAPN) was developed . In their study, 10 patients with solid renal masses underwent RAPN after preoperative rehearsal using 3D-printed kidney models made by a silicon-based material. R.E.N.A.L. nephrometry scores were between 7 and 11 (mean 8.9). Authors compared resection times of the model and the tumor. Their results showed no statistically significant difference between the 3DM and the excised tumor in mean resection time (6:58 vs 8:22 min, p = 0.162) and volumes excised (38.50 vs 41.79 mm 3 , p = 0.976). Only 1/10 patients had positive surgical margins. Authors concluded that pre-surgical rehearsal could significantly improve resection strategy, but this study lacks of a control group. Another feasibility study investigating how 3D printed kidney models can influence surgical procedures was performed by Maddox et al. . With the aim of allowing preoperative and robotic surgical simulation, authors constructed patient-specific physical 3DMs made by materials that could approximate quite well the properties of renal tissue. Seven models were successfully created, and PN and renorrhaphy were performed on each replica. After simulation, all patients underwent RAPN with negative surgical margins, reporting an average warm ischemia time of 25 min. Mean R.E.N.A.L. nephrometry score was 7.4. Comparing the seven cases and the “Tulane Urology prospectively maintained RAPN database,” surgeries with 3DMs had larger tumors, fewer complications, longer warm ischemic time, fewer positive margins, and shorter hospitalization, but the only statistically significant finding was a decreased estimated blood loss (EBL) (185.7 vs. 235.6 ml, p = 0.01), suggesting that preoperative 3DM rehearsal may decrease the learning curve for trainees and improve surgical outcomes. Otherwise, authors admitted that further evaluation was needed. Kyung et al. compared 17 patients who underwent PN aided by prior consultation of 3D patient-specific kidney models with a control group consisting of patients who underwent PN from the same surgeon and approximately during the same time period (2014–2015) . Similarly to Maddox, authors found that the only statistically significant difference was diminished intra-operative blood loss (IBL) (182 cc vs. 310 cc, p < 0.01). No complications occurred in the 3D printed group. Moreover, patients reported an overall improved understanding of the disease, surgical procedure, and trust in surgical team after consultation of the 3DM. Despite the relatively small cohort, the frequent lack of a control group and the low statistical power, these studies have contributed to support the efficacy of 3DM simulation before complex renal surgery. Recently, Fan et al. retrospectively analyzed data of 69 patients who underwent 3D laparoscopic PN (LPN) and 58 who underwent traditional LPN between January 2016 and February 2018 . They reported a significant reduction in warm ischemia time (WIT) in the 3D group (24.1 ± 5.1 for the 3D cohort and 26.6 ± 4.2 min in the traditional LPN, p < 0.05), against a longer surgery waiting time (13.6 ± 3.4 days and 7.0 ± 0.6 days, respectively, p < 0.05). Subgroup analysis according to R.E.N.A.L. scores confirmed that, in patients with scores ≥ 8, the 3D group had significantly shorter WIT and less IBL (131.9 ± 78.5 vs 179.2 ± 76.1, p < 0.05) than the traditional LPN group. Finally, a Japanese group reported their preliminary experience of what they called “4D surgical navigation” in minimally invasive off-clamp PN . It consists of a full-scale size 3D printed kidney designed so that the tumor and its margin (2–5 mm around the tumor) could be removed. This feature allowed the surgeon to visualize, during surgical planning, both pre- and post-resection kidney (the fourth considered dimension was the time). Models helped the surgeons to create a working mental map for resection. Ten patients with complex renal masses (R.E.N.A.L. score ≥ 8) were selected and underwent minimally invasive off-clamp PN with acceptable perioperative outcomes and surgical margins that resulted to be nearly identical to 3D printed tumors. A statistically significant difference was found in the time of intraoperative ultrasound with a 3D model compared to standard surgeries (mean 3.3 min vs 6.3 min, respectively, p = 0.021). Moreover, surgeons claimed the usefulness of 3DM tactile feedback. In contrast, 4 to 9 h were needed for printing and 3 to 9 days to complete the model. Costs of the models ranged from 450 to 680 dollars.
Nephrolithiasis is a common disease, and recent data show a prevalence up to 15% and an overall incidence rate growing . Among endourologic techniques, percutaneous nephrolithotomy (PCNL) represents the gold standard for renal stones larger than 20 mm due to advantages in operative time and morbidity rates . Renal access isn’t always performed by urologists due to a not so easy learning curve. In fact, many studies have focused on imaging modalities used for guidance during percutaneous access for both urologists and radiologists. Anyhow, optimal selection of calyx for puncture and nephrostomy tract is one of the most important steps of PCNL surgical planning. Difficulties include performing a trajectory that leads directly to the target stone without affecting neighbors’ structures. Inadvertent organ injuries as well as multiple tracts before achieving the correct calyx access can lead to an increase in surgery duration, higher complications rates, and consequently to a longer post-operative length of stay (LOS) . In recent years, the rapid development of patient-specific 3D segmentation and reconstruction in Urology has led to the combination of patient-specific 3DMs with preoperative planning for needle guidance during PCNL procedures. In 2015, Gadzhiev et al. proposed a plasticine 3D replica of pelvicalyceal system on 32 patients with staghorn stones taken to the operating room and used as a reference model . Percutaneous renal access was performed successfully in all cases; more than a half (56%) had a single tract with an overall stone-free rate (SFR) after second look of 87.3%. In 2019, Xu et al. printed 36 patient-specific 3DMs (3 for each patient) and simulated 3 puncture sites from upper-, middle- and lower-pole calyces . The puncture site that achieved the better SFR in the model was then used as reference during surgery, and a good correspondence was founded between post-operative stone volume of the model and of the patient ( p < 0.001, 95% CI). In late 2019, an Italian group presented a clinical case of a 30-year-old man with left renal stone (25 × 15 mm) . A 3D digital and physical renal model to aid the surgeon during procedure in planning and guiding the percutaneous access during PCNL was performed. The patient safely underwent PCNL with 1 single percutaneous puncture (time of puncture 2 min). Overall surgical time was 90 min. Post-operative CT scan confirmed patient’s SFR. Brehmer et al. evaluated how 3D-CT reconstructions could influence the choice of access route and treatment outcomes in 35 patients planned for PCNL (88% with complex renal stone) . Access route were planned on 3D-CT reconstructions using anatomical landmarks (ribs, spinous process, etc.). The results were a change of access plan in 15/28 patients, while in 7 patients, access could not be planned without 3D-CT, totaling 22/35 (63%). Sixty-nine percent of these patients (24/35) were stone-free after single PCNL. Similarly, Li et al. performed image segmentation and 3D reconstruction from CT scans of 15 patients with complex renal stone, including one patient with a horseshoe kidney, 8 patients with partial/complete staghorn stones, and 6 patients with multiple renal stones . Virtual safe and reliable percutaneous renal access route were established for each patient by comprehensive planning based on the 3DM of renal stones. The safest and most effective percutaneous tract for stone clearance was planned on the models and then uploaded onto a screen during procedure in the operating room. The surgeon could visualize the reconstructed 3DM adjusting kidney transparency and felt more confident and comfortable with the access aided by the virtual puncture. During lithotripsy, the 3D models offered a panoramic view of the stone and collecting system guiding intraoperative nephroscopy. PCNL were completed successfully in all 15 patients, the one-session SFR was 93.3 %, and the final SFR was 100%. Future studies are required, with larger cohorts, but Manning hypothesis of “practice before you play” could become the standard of care for complex surgeries .
In the last decade, shared decision-making is becoming more and more widespread since patients claim an increasing role in medical decision-making. In this perspective, pre-operative imaging plays a crucial role in patient counselling and shared surgical decision-making for patients eligible to major kidney surgery . However, many patients experience difficulties in the interpretation of conventional radiological images. To date, there are few 3D guided surgery studies that focused on preoperative patients’ education. Assuring to patients an improved understanding of their anatomy and conditions, as well as planned procedures, is often underestimated while it could give a more informed consent and reduce pre-operative anxiety. Many studies have explored possible ways to reduce the comprehension gap between surgeon and patient creating 3DMs and comparing to 2D imaging in patient undergoing PN. Wake and colleagues prospectively enrolled 49 patients eligible for PN who underwent routine clinical imaging before surgery . The cohort was randomized in two groups: one receiving pre-operative planning with standard imaging and the other with the addition of printed patient-specific 3DM. During surgical planning, a 5-point Likert scale questionnaire was administered to patients and used to determine their understanding. Their study showed better results and consequently a better understanding in the 3DMs cohort compared to 2D imaging group, with a statistically significant difference in comprehension of cancer size and location ( p = 0.04 and p = 0.012, respectively), disease and treatment plan ( p = 0.014), helping the patient to decide consciously to undergo PN instead of RN. Similar results were showed by Teishima et al. in 29 patients who were candidates to RAPN in 2018 . The 3DM created consisted of the kidney, tumor, ureter, vasculature, and also inferior vena cava and abdominal aorta. A dedicated visual analog scale was used to evaluate perception and understanding. In all patients’ questionnaire issues ( p = 0.0006 in anatomy-related issue, p = 0.0004 in tumor-related issue, and p = 0.0015 in procedure-related issue) and in 2/3 of the issues of questionnaire administered to 19 family members ( p = 0.0186 in anatomy-related issue and p = 0.0051 in tumor-related issue), the 3DM reached a statistically significantly higher score than conventional CT alone. Moreover, in all CT issues, 64-year-old or younger patients scored better than the elder ones. Robot-assisted surgery is not so widespread and affordable, so many centers perform NSS with the aid of laparoscopy. Zhang et al. investigated the impact of 3DMs in T1 renal cancer patients who underwent LPN . From CT images, 10 3D kidney models were printed successfully. Renal arteries and veins, collecting system including the ureter, and tumor were preserved and all colored differently, while perirenal fat tissue was removed. Two questionnaires with open ended were plotted. Against a relatively low production price (150 dollars per model), high score were registered among patients (9 or over in all four questions) while, among experienced urologists, details of renal vasculature and the collecting system were scored less favorably. In 2015, a prospective pilot study was conducted on 7 patients with a primary diagnosis of kidney cancer eligible for PN . From four-phase multi-detector computerized tomography (MDCT) scanning, renal volume data were extracted and a life-size specific 3DM for each patient was printed with transparent resin for renal parenchyma, to better show renal vasculature, collecting system and the renal tumor. Before and after 3DM presentation, questionnaires were administered to patients and their answers analyzed: understanding on kidney physiology (16.7%, p = 0.018), anatomy (50%, p = 0.026), and planned surgical procedure (44.6%, p = 0.026) was statistically significant, with an overall improvement of 37.6%. During an international urological meeting organized on January 2017, Porpiglia and colleagues presented 3DMs of 10 patients who underwent live minimally invasive PN and evaluated the results of 3DMs in overall understanding during a preoperative counseling between patient and surgeon . All patients completed a specifically built Face&Content questionnaire that showed favorable scores (at least 9/10) about the use of the technology during preoperative case discussion, improving their comprehension of the disease and the intervention. During the same year, Atalay et al. investigated the feasibility and the impact of personalized 3D-printed pelvicalyceal system models prior to PCNL . Five anatomically accurate models of the renal collecting system of patients with unilateral complex renal stones were successfully generated. Authors stated that, after the 3DM presentation, the mean understanding improvement rate was higher, in particular basic kidney anatomy improved by 60% ( p = 0.017), kidney stone position by 50% ( p = 0.02), planned surgical procedure by 60% ( p = 0.017), and understanding of complications-related surgery by 64% ( p = 0.015). Schmit et al., in their pilot prospective study, compared 25 patients of the standard group with as many of the experimental group which received education using a 3D printed renal cryoablation model . Initial results reported a statistically significant improvement in patient understanding ( p = 0.007) from explanation of cryoablation with 3DMs compared to 2D imaging but, after adjusting for the physician providing the education, the 3DM didn’t show a significant improvement anymore ( p = 0.22).
Recent papers have underlined how urology trainees are less prone to participate during surgeries in the operating room due to more complex and minimally invasive procedures being introduced . A lower exposure of residents to major procedures, as well as for novice inexperienced surgeons, is leading to poor satisfaction of surgical training and lower confidence performing surgeries independently . Moreover, COVID-19 pandemic has rapidly affected surgical training due to the substantial decrease in election procedures in favor of urgent cases [ – ]. In this scenario, surgical training in urology may suffer more than before, and pursuing innovation in learning surgeries needs to be a cornerstone of trainees education that, with new tools, could even be implemented . Considering this background, another possible application of 3DMs is simulation-based training (hands-on surgical practice) for novice and inexperienced surgeons. 3DMs could provide a safe scenario for training, especially for residents, without harming patients and guarantying always the standard of care. Monda et al. recently evaluated 3D printed molds of a patient’s kidney with renal mass as a training tool for robotic NSS . Twenty-four surgeons of different training levels performed four trials simulations for each one on silicone renal tumor models. A dedicated questionnaire regarding the realism and the overall feeling of the model, and usefulness for surgical training, was administered, and overall results were, respectively, 79.2 and 90.2. Renal artery clamping times, preserved renal parenchyma, positive margins, and Global Evaluative Assessment of Robotic Skills (GEARS) scores were all found to improve ( p < 0.001, p = 0.025, p = 0.024, p ≤ 0.020, p ≤ 0.006, respectively) even if clamping times and GEARS scores proved to be significantly better in experienced surgeons hands ( p ≤ 0.005, p ≤ 0.025, respectively). Ghazi et al., in a prospective study, created a simulated inanimate model made of poly-vinyl alcohol (PVA) hydrogels using a patient’s CT scan with a 42-mm upper pole renal tumor (R.E.N.A.L. score 7) and stiffened to the desired consistency in order to simulate live surgery . To replicate the entire surgical procedure, the kidney replica was layered in its anatomical configuration and surrounded by perinephric fat, neighboring organs, and posterior abdominal musculature. All steps of RAPN were simulated. The model resulted to have good face and content validity (average score of 3/5 and 4/5, respectively), providing a useful tool for evaluating and even improving surgical skills. Statistically significant difference was demonstrated in operative time (OT), ischemia time (IT), surgical margins, and EBL (all values had p < 0.01). During the same year, 3D printed renal models with enhancing masses were tested on 23 first-year medical trainee for characterization, localization, and understanding of renal malignancy . The 6 renal models were printed from a transparent plastic resin, and the tumor was delineated by a red hue. To medical trainee were asked to complete R.E.N.A.L. nephrometry score separately using 2D images and 3DMs and then complete a questionnaire about the experience. Overall R.E.N.A.L. score accuracy was significantly improved with the 3DM ( p < 0.01). In particular, R N and L components of the score (radius, nearness and location) showed the higher improvement ( p < 0.001) using the models. All these findings suggest that 3DP could help to improve trainees’ understanding and characterization of renal masses. Furthermore, when compared to expert urologists, the interrater agreement improved with the 3DMs ( p = 0.002). Marconi et al. showed how 3DMs of 15 patients scheduled for laparoscopic nephrectomy (LN) helped in identifying anatomic structures more quickly and accurately . The lower the experience the higher the improvement, so medical students had the highest benefit (53.9% ± 4.14% of correct answers with 3DMs), instead of experienced urologists and radiologists. Moreover, time was almost 50% shorter than reviewing 2D CT scans (60.67 ± 25.5 s vs 127.04±35.91 s, respectively). About complex renal calculi, few authors have explored the possibility of surgical training using 3DMs. Firstly, in 2008, a French group exploiting a rapid prototyping technique created patient-specific silicone 3DMs from CT scans allowing surgical team and residents to train on the model before surgery, predicting difficulties due to patient’s anatomy . After training, the patient underwent PCNL without complications and discharged at post-operative day 1. On the other hand, only one patient has been enrolled, and few surgical outcomes were evaluated. Subsequently, Stone et al. evaluated 15 consecutive PCNL performed by a single urologist . Among these, 7 patients had specific 3DMs used for preoperative rehearsal and training. In addition to patients’ collecting system and staghorn calculi, also the kidney, spine, and posterior abdominal wall were created and assembled. All steps of a PCNL were simulated, including fluoroscopic access. Outcomes from the first 8 patients without prior rehearsal were compared to the 3D group, showing that mean fluoroscopy time was significantly lower in the second group (6.2 and 12.7 min, respectively, p = 0.03), but the higher improvement was registered on the average number of percutaneous needle access attempts that resulted to be lower in the 3D group (1.8 vs 5 attempts, p < 0.001). Antonelli et al. have gone beyond the scope of surgical training studying the benefits of a novel device (polyethylene sack called “PercSac”) deployed into a 3D printed collecting system to capture stones and their fragments during PCNL simulations, in order to prevent stone migration . The average time for stone fragmentation resulted to be significantly shorter in the PercSac group (217 s vs 340 s of the control group, p = 0.028), and total time for complete stone was significantly shorter too (293 s vs 376 s, p = 0.047). In vitro simulation provided a safe environment for training and testing the efficacy of the novel device, laying the groundwork for in vivo surgeries. Renal access is one of the most important and complex steps in learning PCNL and ideally should be practiced outside the operating room particularly for residents. Simulations could be expensive and time-consuming. To satisfy the need of a cheap but accurate 3DM for PCNL training, Turney et al. successfully produced water-soluble plastic 3DMs of human collecting system to safely practice the fluoroscopy triangulation for percutaneous renal puncture . However, results focused on costs while no estimation of number of punctures needed was reported neither improvement of surgical skills. The reduction of caseload and the increasing focus on patient safety have impacted on resident surgical training. Ghazi and colleagues validated a full-immersion platform for simulation before PCNL . After producing 3D human pelvicalyceal system, kidney and adjacent structures, all steps of PCNL (percutaneous renal access, nephroscopy, and lithotripsy) were simulated by 5 experts and 10 novices from both international radiology (access only) and urology (full procedure) departments. 3DMs were rated high on realism and educational effectiveness and provided a useful tool for surgical simulation and training and also for skill evaluation before hands-on procedure. The greatest impact resulted on teaching and refining technical skills (4.71/5) as well as evaluation of performance (4.57/5). Obviously, it was registered a significant difference between experts and novices in mean fluoroscopy time, number of percutaneous access attempts, and needle repositioning.
AR refers to the alignment or superimposition of intraoperative, or, more commonly, preoperative imaging onto a patient’s actual images or video, in real time. This allows the surgeon to simultaneously assimilate important visual information from the operative field with imaging modalities that usually play a passive role within the operating room (US, CT, MRI). The reconstructed images are registered onto anatomic landmarks and tracked by the computer according to the surgeon’s tissue manipulation and the camera movements. The 3D virtual models (3DVM) have been increasingly utilized in a virtual environment for medical education and surgical planning over the last decade to provide an increased understanding of kidney anatomy. Head-mounted display systems have been proposed during preoperative planning to visualize 3DMs as holograms. A mixed-reality tool using zSpace workstation (a computer connected to a stereoscopic screen which allows to visualize virtual objects) was developed by Antonelli and colleagues . A simulation environment can be visualized on the real one, and this experience seemed to improve preoperative planning for partial nephrectomy. Compared with a CT scan, mixed-reality technology could provide much detailed anatomical information. Augmented reality, properly linked with operating systems, allows to add information to the real environment and to overlay 3D constructed virtual images. Nowadays, it is possible to visualize kidney 3D reconstructions as holograms in a mixed-reality environment. Porpiglia et al. pioneering study showed that augmented reality is a feasible and useful technology in an intraoperative setting . Hyper accuracy 3D (HA3D) models were integrated with the Da Vinci robot and used during partial nephrectomies for selective clamping. This augmented reality experienced resulted to be as valid as the cognitive guidance with the addition that the surgeon could stay constantly focused on the operative field. The excision phase of PN can almost surely be considered the hardest step and an additional guidance by augmented reality showed promising results. A similar study was conducted by Checcucci et al during a urological international meeting organized at their Institution on January 2019 . Surgeons’ perception of mixed reality for PN was evaluated. HA3D were performed based on pre-operative CT scans. Then, a virtual environment was created with the possibility to interact with 3DMs by using HoloLens. This mixed reality setting scored very high on both surgical planning (8/10) and anatomical accuracy (9/10). Furthermore, participants enthusiastic about its potential role in understanding of surgical complexity: after HoloLens mixed reality experience, 64.4 and 44.4% of the participants would have change their clamping and/or resection approach. Singla et al. augmented-reality system provided an instrument tracking for excision phase . Surgeries were successfully performed, and, by this tracking system, the amount of health parenchyma excised was significantly reduced (from 30.6 ± 5.5 to 17.5 ± 2.4 ml, p < 0.05) as well as the difference depth from the tumor underside to cut resulted to be statistically significant (from 10.2 ± 4.1 to 3.3 ± 2.3 mm, p < 0.05). Recently, a system which allows to overlap endoscopic images on 3DVM was develop and experienced during RAPN. Kobayashi et al. used this tool and evaluated the skills of two expert surgeons on identification and dissection of the renal artery . This technology showed how the number of inefficient robotic motions was significantly reduced. A single center experience on preoperative patient counseling was reported by Wake et al. . A 5-point Likert scale was used to evaluate overall comprehension of clinical cases after mixed-reality experience using HoloLens to visualize 3DMs. Compared with mixed reality, 3DMs showed better results in the understanding of clinical cases. Even if NSS is the most frequent surgery in which AR has been applied, endoscopic surgery, specifically for complex renal stones, has been tested with this immersive new tool. From 2017 to 2018, Parkhomenko et al. evaluated four surgeons of different expertise in PCNL used immersive virtual reality (iVR) models during preoperative planning . The new technology improved surgeon’s understanding of the optimal calix entry and stone location and conformation ( p < 0.01) than CT imaging alone, altering the operative approach in 40% of cases. In patients that tried iVR, an important reduction of preoperative anxiety due to an improved comprehension of surgery was registered. The retrospective matched-paired analysis showed how iVR group had a statistically significant decrease in EBL (50 vs 100 mL, p < 0.01), fluoroscopy time (180 vs 226 s, p < 0.01), as well as a fewer punctures (1.13 vs 1.46, p = 0.09) and a higher SFR (39% vs 20%, p = 0.15). Similarly, a Turkish group evaluated a novel software to calculate the correct access point and angle for PCNL by using pre-operative CT . Two scans, 27 s and 10 min after injection of contrast agent, were taken in prone PCNL position. In an augmented reality setting, 3DM was placed virtually onto real object and then calculated access point in 50 patients. According to the calculated direction angle, an access needle was displayed virtually on the object. Accuracy of insertion of needle was checked by feeling crepitation on stone surface and observing tip of needle touching stone in a control CT scan. However, the authors stated that further research is required to test its accuracy and safety in humans.
Several applications of 3DP have been proposed in the last few years in many fields. As far as innovation in 3DP technology gets better, 3D patient-specific models are becoming more affordable and widespread, even in smaller centers. Possible applications of 3DP in kidney surgery include surgical planning, patient education, training, and intraoperative AR, leading to goals never thought before. The disposability of 3D models in healthcare scenarios might improve surgical outcomes, learning curves of novice surgeons and residents, as well as patients’ understanding and compliance, allowing a more shared surgical decision-making. Further studies aimed to standardize this technology application are needed to guarantee a new and universally shared way to approach kidney procedures.
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Community-acquired pneumonia – use of chest x-rays for diagnosis in family practice | 49414153-998f-479f-95ce-03d27e3fd6b6 | 9615378 | Family Medicine[mh] | Community-acquired pneumonia is an infectious disease with a wide spectrum of presentation, carrying the potential for high morbidity and mortality, particularly in the elderly population and among patients with significant comorbidities . Accurate diagnosis of pneumonia is essential for appropriate care and appropriate use of antibiotics. Clinical diagnosis based on history taking and physical examination is subject to misjudgement due to lower levels of accuracy (74% sensitivity, 84% specificity ). This may lead to over- or underuse of antibiotics . Chest x-ray is the recommended examination for diagnosis of pneumonia, according to guidelines and regularly used textbooks, which prescribe chest radiograph as an obvious component of the pneumonia diagnostic process. However, in contrast to the conditions in emergency departments, chest x-ray examination is not always accessible in the community. A Cochrane review aimed to evaluate the effectiveness of chest radiographs in addition to clinical judgement, compared to clinical judgement alone, in the management of acute lower respiratory infections. It concluded that there is no difference in the outcome of pneumonia detected with or without actual use of a chest x-ray, but there remains a concern of over-prescription of antibiotics. Our study aimed to assess compliance with guidelines for use of chest x-rays in the diagnosis of community acquired pneumonia, according to doctors’ referral during the visit and patients’ adherence thereafter.
This was an observational database study. The study population comprised patients above 18 years of age who were under the care of Clalit Health Services (CHS). CHS is one of four health maintenance organizations in Israel which people may choose for their medical care within the national health insurance scheme. People are registered with their family physician, to whom visits are free of charge. Similarly, blood tests are free of charge while x-ray examination carries a small fee. The immediate tests available for use in the practice are ECG and urinalysis. Blood tests are transferred to the laboratories and results can be retrieved within 24 h. The study region is the northern periphery of Israel, where CHS provides care for 583,000 people, over 70% of the region’s residents. In the northern region care is provided to CHS patients in 250 clinics, of which 160 are rural clinics and the remainder are urban health centres and medium-sized primary care clinics. x-rays are performed in health centres or in designated radiology facilities. Interpretation of the chest X-ray is obtained within 24 h. CHS operates an integrated electronic medical and administrative file for each patient, based on the International Classification of Diseases (9th Revision). Chronic diseases that take part in the Quality Measures program, such as type 2 diabetes, cardiovascular diseases, asthma, and chronic obstructive pulmonary disease (COPD), are also cross-validated against medication possession records and laboratory data through an automated disease-specific process . The study population comprised cases where patients visited their family doctors over the course of one year in 2015, with a visit diagnosis of pneumonia. The index visit was defined as the first in a six-week period with pneumonia in the diagnosis field. Information on the interpretation of the x-ray was retrieved during a 14-day period from the day of the index visit. As a result, without having other measures, the diagnosis of pneumonia was clinical, based on the patient’s history and findings in the physical examination. All subsequent visits with the same diagnosis during a six-week period, as well as visits following hospitalization, visits to the emergency department, and chest x-rays performed later than 14 days from the index visit, were omitted from the study. Independent demographic variables included patient gender and age. Accessibility of radiology facilities was defined by their location: either in the same health centre and city as the family doctor, or outside the city. Variables of chronic comorbidities included diabetes, COPD, asthma, ischemic heart disease and heart failure, and current or past smoking. The outcome measure was a referral for a chest x-ray. We compared cases that were or were not referred for a chest x-ray. Among cases that were referred for a chest x-ray, we compared adherence vs. non-adherence to the referral. Statistical analyses The data were analysed by SAS version 9.4. Categorical data were reported as percentages . Association with referral for a chest x-ray or adherence with the referral for a chest x-ray was performed using the Chi-square test. A logistic regression model was designed to examine the prediction of actual use of a chest x-ray (for all pneumonia patients), taking into account demographic and morbidity variables. P-values of less than 0.05 were considered significant.
The data were analysed by SAS version 9.4. Categorical data were reported as percentages . Association with referral for a chest x-ray or adherence with the referral for a chest x-ray was performed using the Chi-square test. A logistic regression model was designed to examine the prediction of actual use of a chest x-ray (for all pneumonia patients), taking into account demographic and morbidity variables. P-values of less than 0.05 were considered significant.
We followed 4,230 cases that were eligible for the study because the visit was terminated with a diagnosis of pneumonia during one year. The study sample contained a high proportion of patients over 40 years of age (75.2%). Radiology facilities were located more often outside the city where the family doctor’s practice is located (63.8%). A diagnosis of at least one of the listed chronic comorbidities was reported in 24.4% of those patients (Table ). Referrals for chest x-rays were reported in 2,503 cases of diagnosis with pneumonia (59.2%). A higher rate of referral was reported in patients aged 40–64 than in patients aged 18–39 or 65 years and older, and in patients who were referred to a radiology facility in the same health centre or city compared to a facility outside the city (Fig. a). Rate of referral was higher in smokers than non-smokers. In patients with comorbidities, the rate of referral was not higher, but rather lower, than in patients without comorbidities (Fig. b). Adherence to the referral for a chest x-ray was detected in 1,920 (76.7%) of the cases that were referred for chest x-rays. Within this group of patients, a higher rate was observed in patients aged 65 and older than in younger age groups, and in patients who were referred to a radiology facility in the same health centre or city than in those referred to a facility outside the city (Fig. a). Rates of adherence were similar across health variables (Fig. b). As mentioned above, chest x-rays were used in 1,920 cases (45.4% of patients with a diagnosis of pneumonia during the visit). We fitted a model to predict the actual use of chest x-rays. The model included 4,230 cases: 1,920 that were referred and adhered to the referral, vs. 1,727 that were not referred and did not undergo a chest x-ray and 583 that were referred but did not adhere to the referral . Actual use of chest x-rays was higher among patients who were referred to a radiology facility in the same health centre or city than in those referred to a facility outside the city [OR = 2.4; 95% CI: 2.1–2.8]; it was also higher in patients aged 65 and older, and in those aged 40–64, than in those below the age of 40 [OR = 1.3; 95% CI: 1.1–1.6, OR = 1.2; 95% CI: 1.0–1.4, respectively]. Having any chronic disease was negatively associated with actual use of a chest x-ray (Table ).
Our study brings evidence from real life data demonstrating only partial compliance with guidelines for diagnosing pneumonia. Specifically, we have provided evidence on the underuse of chest x-rays for confirming the diagnosis of pneumonia by family doctors. Less than half of the patients who received a pneumonia diagnosis from their family doctor underwent a chest x-ray. Family doctors referred 60% of cases with pneumonia as the visit diagnosis; 78% of them adhered to the referral. Accessibility of the radiology facility seems to be a major factor contributing to actual use of chest x-rays, associated both with referral by family doctors and adherence by their patients. Another predicting factor was older age – people older than 65 adhered more than others to the referral for a chest x-ray. Chronic comorbidity was not associated with actual use of chest x-rays, even with respect to diseases more associated with pulmonary morbidity, such as asthma and COPD. The northern district of CHS is spread over a large area in the periphery of Israel. Care is provided through many clinics varying in size from rural villages to urban health centres. Radiology facilities can be located in the same health center as the family doctor or away from the primary care clinic, necessitating a special drive after the visit to the family doctor that can last up to an hour. Patients make their own arrangements for transportation, often by private car. This infrastructure may influence the family doctors’ decision and their patients’ adherence. The higher rate of adherence in patients aged 65 and older to the referral for a chest x-ray can be explained by acknowledgement of the threat of pneumonia at older age. In the absence of radiology evidence for pneumonia, the medical decision is empirical and based on evidence with weak validity. We assume that diagnosis of pneumonia is linked to antibiotic treatment. According to our study outcomes, more than half of the patients were managed without radiological evidence, possibly with antibiotics . The added value of x-rays in the diagnostic process for pneumonia was evaluated in a study 8 conducted both in primary care clinics and a hospital emergency department; it reported 74% sensitivity and 84% specificity for clinical diagnosis without chest x-rays, but only 27% positive predictive value. Hopstaken et al. 14 demonstrated that diagnosis of pneumonia based on history taking and physical examination alone led to misjudgement and misuse of antibiotics, reflected in 86% overuse and 16% underuse. Another study showed that 20% of patients who presented to primary care clinics with cough and fever had x-ray findings compatible with pneumonia; when the diagnosis was based on clinical judgement alone the rate of antibiotic prescription was twice as high. Given the barriers set by long distances in the periphery, other options for confirming a bedside diagnosis of pneumonia should be considered. A systematic and meta-review found that clinical features such as respiratory rate > 20/min, temperature ≥ 38 °C, pulse rate > 100/min and crackles showed the best pooled positive likelihood for pneumonia . Another study conducted in primary care clinics recorded the outcome of visits of patients suspected for pneumonia according to doctors’ suspicions based on findings in physical examinations and results of blood tests, compared to the outcome of chest x-rays. In this study, the results of c-reactive protein (CRP) blood tests contributed more than physical examination parameters to the diagnosis of pneumonia . A Cochrane review from 2014 evaluated the contribution of the point of care (CRP) test for appropriate use of antibiotics for pneumonia. The authors concluded that the CRP test could assist in clinical diagnosis. The review included studies that did not necessarily use x-rays. The use of point of care ultrasound for diagnosis is a promising tool, but it is still not in sufficiently wide use due to training and cost limitations . Strengths and limitations Our study brings evidence from a comprehensive database with high validity of doctors’ activities and patients’ performance. However, our study is limited by missing variables indicating the clinical situation that could influence the doctors’ judgement, such as indications for severity of the disease. Similarly, we did not have the results of the chest x-rays, so we cannot discuss the implications for patient care. We also can only assume antibiotic use, since it was outside the aims and scope of our study.
Our study brings evidence from a comprehensive database with high validity of doctors’ activities and patients’ performance. However, our study is limited by missing variables indicating the clinical situation that could influence the doctors’ judgement, such as indications for severity of the disease. Similarly, we did not have the results of the chest x-rays, so we cannot discuss the implications for patient care. We also can only assume antibiotic use, since it was outside the aims and scope of our study.
According to guidelines, clinical diagnosis of pneumonia should be confirmed by chest x-ray. In practice, more patients are treated without radiological evidence of pneumonia. Accessibility of radiology facilities appears to be an important contributing factor for both doctors’ and patients’ decisions. This indicates a need to develop other measures to confirm or at least rule out the diagnosis of pneumonia according to the severity of the condition, together with improving accessibility to radiology facilities.
Below is the link to the electronic supplementary material. Supplementary Material 1
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Une localisation inhabituelle d’un carcinome primitif cutané rare: à propos d’un cas | 79327249-87c5-4874-8cd7-4a535ac1e25c | 9269034 | Anatomy[mh] | Les carcinomes annexiels sont rares et représentent moins de 1% des tumeurs malignes cutanées . Le carcinome scléreux des glandes sudorales, également nommé carcinome annexiel microkystique, a été décrit pour la première fois en 1982 par Goldstein et al . . En absence d´arguments histologiques et immunohistochimique, ce diagnostic pose le problème de diagnostic différentiel avec l´adénocarcinome eccrine NOS qui reste un diagnostic d´élimination. Elle pose également le problème de diagnostic différentiel avec des tumeurs bénignes et d´autres tumeurs malignes d´où l´enjeu pour le pathologiste de savoir évoquer ce diagnostic. Nous rapportons un nouveau cas de localisation inhabituelle péri anale chez une jeune patiente en bon état général.
Information du patient: une femme de 33 ans, femme au foyer, sans antécédents particuliers, qui présentait depuis un an un prurit péri-anal mise sous traitement symptomatique sans amélioration. Résultats cliniques: à l´examen physique, on trouvait une performance status à 0, un bilan étiologique de prurit est réalisé, revenant normal. Par la suite, la symptomatologie s´est aggravée par l´apparition d´une induration péri-anale qui s´étend à tout le périnée avec épaississement scléreux cutané. Il n´est pas noté d´autres signes associés ni d´altération de l´état général. Chronologie: l´histoire de la maladie remonte à un an par l´apparition d´un prurit péri anal motivant la consultation chez plusieurs médecins qui l´ont mis sous traitement symptomatique sans amélioration, puis un bilan de prurit a été demandé, revenu normal. Par la suite un dermatologue a procédé à une biopsie cutanée. Démarche diagnostique: une biopsie de la peau péri-anale est réalisée suspectant un lichen scléro-atrophique ou une Morphée. L´examen histologique retrouve un tissu cutané tapissé par un épiderme régulier, le derme et l´hypoderme sont manifestement infiltrés par une prolifération tumorale maligne, disposée en amas, en travées grêles et en rares structures glandulaire. Les cellules sont de grandes tailles, munies de noyaux irréguliers, tantôt hyperchromatiques tantôt à chromatine vésiculeuse et nucléolés. Le cytoplasme est éosinophile. Quelques figures de mitoses sont observées. Le stroma est scléreux et comporte des engainements périnerveux ( , , ). Il n´est pas noté de différenciation malpighienne sur ce prélèvement. A l´étude immunohistochimique, les cellules tumorales expriment la CK AE1/AE3, la CK7. Elles n´expriment pas l´Ecadhérine, la P63, la CK20, le CDX2, l´Her2, les récepteurs hormonaux, les marqueurs mélaniques, les marqueurs neuroendocrines ni les marqueurs lymphoïdes ( , , ). Une localisation cutanée d´un carcinome peu différencié a été évoquée. Un bilan d´extension est demandé afin d´étiqueter l´origine (examen, gynécologique (avec FCV et biopsie du col), examen proctologique, une TDM thoraco-abdomino-pelvienne, une endoscopie digestive haute et basse (avec des biopsies étagées) et une écho-mammographie mammaire), tout est revenu normal en dehors de la TDM qui objective un épaississement de la graisse péri-rectale et anale, ainsi que le grand ementum et le mésentère. Les marqueurs tumoraux (ACE et CA19-9) sont négatifs. Par la suite, une IRM périnéo-pelvienne est réalisée objectivant les mêmes atteintes décrites sur la TDM ainsi qu´un envahissement des plans musculaires périnéaux et du rectum (confirmé par l´histologie de la biopsie rectale) ( ). Intervention thérapeutique: une radiothérapie est indiquée après discussion en réunion de concertation pluridisciplinaire, vu l´étendue de la lésion, et l´impossibilité de subir une intervention chirurgicale carcinologique. Suivi et résultats des interventions thérapeutiques: après la fin de la radiothérapie, une IRM d´évaluation a été réalisée, objectivant une bonne réponse radiologique. Consentement éclairé: la patiente a donné son consentement éclairé.
Le carcinome scléreux des glandes sudorales a été décrit pour la première fois en 1982 par Goldstein et al . , ils ont décrit dans leur papier cinq tumeurs siégeant au niveau du visage et se caractérisent histologiquement par une différenciation glandulaire eccrine, des kystes kératosiques, des cordons et des amas cellulaires uniformes, une stroma collagenique et scléreuse, une infiltration des tissus sous cutanés et une invasion périnerveuse. Par la suite, en 1985, Cooper et al. ont revu une série des 2000 cas de carcinomes cutanés de localisation faciale, à partir de laquelle ils ont sélectionné 20 cas, dont 3 pathologistes ont été d´accord pour le diagnostic de carcinome scléreux des glandes sudorales . Ce groupe de carcinome annexiel, qui partage les aspects morphologiques sus cités, se caractérise par sa rareté et son évolution clinique lente et profonde, parfois sur des années, ce qui lui confère une présentation clinique bénigne sous forme de plaques, papules, ou indurations dont l´épiderme est souvent normale ou rétractée. Ceci pourrait conduire à un retard de diagnostic de malignité entraînant ainsi un retard de prise en charge optimale de la tumeur et une augmentation de la morbidité en raison d´une infiltration profonde et progression localement avancé comme l´illustre notre cas . Cette tumeur survient chez l´adulte jeune et le sujet âgé avec un âge moyen de 44-64 ans, sans prédilection de sexe . Dans 85% des cas, la tumeur se développe au niveau de la région tête et cou, avec une préférence pour la peau périorbitaire et la région centro-faciale , des cas ont été rapporté au niveau de la région axillaire, des membres, du tronc, des fesses et de la région génitale dont la vulve et la région péri-anal qui a été décrite pour la première fois par Murata et al. en 1997 et depuis aucun cas n´a été rapporté dans cette localisation à notre connaissance, notre cas est considéré le deuxième. L´antécédent lointain d´exposition aux rayonnements radioactifs est retrouvé chez environ 19%-50% des patients atteints de ce carcinome, d´autres facteurs prédisposant comprennent l´exposition aux rayons ultraviolets et l´immunodépression . Ce carcinome a porté plusieurs dénominations depuis sa première description, dans la 4 e édition de la classification OMS des tumeurs de la peau 2018, il est appelé « carcinome annexiel microkystique » et ayant comme synonymes « carcinome scléreux des glandes eccrines » . Il s´agit d´une tumeur dermique à caractère invasif avec un tropisme nerveux. Elle est faite de proportions variables de travées, de massifs essentiellement en profondeur et en zones d´invasion périlésionnelles, des glandes étirées et des kystes kératinisants sont observés essentiellement en superficie, la présence des deux aspects architecturaux permet de poser le diagnostic. Les cellules s´organisent au moins en deux assises, elles sont monomorphes, basophiles, au noyau arrondi, à chromatine dense ou vésiculeuse, au cytoplasme réduit, les mitoses sont rares. La nécrose est habituellement absente. Les engainements périnerveux sont classiques. Le stroma est scléreuse [ , , ]. Dans les localisations habituelles (visage), le diagnostic différentiel se fait essentiellement avec le carcinome basocellulaire sclérodermiforme, le trichoépithéiome desmoplastique, et le syringome, le diagnostic est autant difficile si la biopsie est superficielle. La présence des kystes kératinisants est une aide diagnostique. Le syringome se représente sous forme de petites papules multiples et superficielles alors que le carcinome scléreux eccrine se présente sous forme de lésion unique, rétractée et invasive . Dans les localisations inhabituelles, comme l´est notre cas, le diagnostic différentiel se fait avec une métastase d´un carcinome d´une autre origine, dans ce cas l´histoire clinique et l´immunohistochimie permettent de redresser le diagnostic. La négativité du BEREP4 est un marqueur fiable pour éliminer le CBC sclérodermiforme (BEREP4+). Les marqueurs de cellules souches folliculaires CK15, CK19, sont utilisés pour discriminer le trichoépithéliome desmoplastique du carcinome scléreux eccrine. Ce dernier est CK19+/CK15-, à l´inverse du trichoépithéliome desmoplastique . L´EMA et l´ACE soulignent les structures glandulaires sébacées. La p63 a une positivité hétérogène avec un marquage uniquement des cellules périphériques des massifs tumoraux dans le carcinome scléreux eccrine . La chirurgie radicale avec marges saines, notamment la microchirurgie de Mohs dans les localisations faciales péri-orificielles, reste le traitement de référence. La radiothérapie est indiquée en adjuvant dans les cas à haut risque de récidive ou dans les cas dont la chirurgie est impossible comme notre cas. La chimiothérapie et les thérapeutiques ciblées sont en cours d´étude . La surveillance doit être rapprochée tous les 6 à 12 mois pendant les 5 premières années après traitement en raison de risque de récidive allant de 15 à 60% .
Ce cas illustre une localisation inhabituelle d´un carcinome annexiel cutané rare. Il faut penser au carcinome annexiel microkystique ou carcinome scléreux eccrine devant toute lésion cutanée d´aspect clinique scléreux rétracté, d´évolution lente et dans un contexte de conservation de l´état général et d´absence d´histoire clinique néoplasique. Une biopsie assez profonde est essentielle pour faire un bon diagnostic anatomopathologique et une meilleure prise en charge thérapeutique.
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null | be244ef1-5ef8-4f6d-a28b-d92d554b67b1 | 10254448 | Pharmacology[mh] | Acorus tatarinowii Schott. ( A. tatarinowii ) is a common perennial herbaceous plant . It is mainly distributed from northern temperate to subtropical regions, especially in China, Japan, India, Thailand, and Korea . A. tatarinowii is one of the most widely distributed and frequently used natural medicinal plants from the genus Acorus and has a long documented history of medicinal use in the empirical medical system. A. tatarinowii first appeared as a traditional Chinese medicine (TCM) in the earliest Chinese medicinal classic work Shennong’s Classic of Materia Medica (written more than 2000 years ago during the Han Dynasty). It is widely used in folk medicine for treating complex and difficult ailments as well as some serious diseases and has achieved remarkable therapeutic effects. It was included for the first time in the 1963 edition of the Pharmacopoeia of the People’s Republic of China as a TCM in clinical use and was continuously included until the latest 2020 edition . Dried rhizomes are the main A. tatarinowii medicinal parts, and these have been commonly used alone or combined with other TCM in China to treat stroke, dementia, depression, seizure, and mental disorders for centuries . Many Chinese medicinal formulae containing A. tatarinowii have been widely used in clinical practice. At the same time, many commercial Chinese patented medicinal products containing A. tatarinowii are circulating in the market to treat specific diseases. Moreover, certain active ingredients are extracted from A. tatarinowii as pharmaceutical raw materials . As a medicinal plant, A. tatarinowii has significantly contributed to people’s health and the traditional medical systems. Over the past few decades, A. tatarinowii has attracted increasing interest as an important medicinal plant from both researchers in natural medicine and pharmaceutical institutions. Significant progress in the isolation and identification of A. tatarinowii active constituents has been made. A. tatarinowii contains many phytochemical components with diverse structures and different activities. Thus far, more than 160 components have been identified and characterized. They mainly include phenylpropanoids, terpenoids, lignans, flavonoids, alkaloids, amides, organic acids, and others. Modern pharmacological studies have shown that these chemical components have potent properties, such as antidepressant, antiepileptic, anticonvulsant, antianxiety, antifatigue, and antifungal properties, and they have been shown to improve Alzheimer’s disease (AD) . It is worth noting that A. tatarinowii has shown potent neuroprotective effects. A. tatarinowii can reduce brain nerve injury by regulating neurotransmitter levels and improving blood circulation in the brain. It offers good protection for the brain’s nervous system. Whether used alone or as a prescription, A. tatarinowii is an important and indispensable herb to treat depression and is used in the TCM treatment system . However, some clinical observations have shown that the active ingredients of A. tatarinowii have potential toxicity. Therefore, it is necessary to be cautious in using A. tatarinowii as a treatment method, strictly control the dose of A. tatarinowii , and better protect people’s health . If it is disturbed and stimulated by the external environment, it will aggravate the poisoning condition. Therefore, safety measures and comprehensive research should be carried out in the future . The exploitation and TCM applications in the prevention and treatment of various diseases are gradually growing due to the in-depth study of TCM. Thus, research on A. tatarinowii is becoming increasingly necessary . Research on A. tatarinowii has advanced significantly due to recent international growth in TCM recognition and contemporary scientific and technical advancements. Reviewing the existing and available literature, it was found that although a large number of studies have been carried out on A. tatarinowii , they mainly focus on a single aspect of its phytochemistry or pharmacology. However, there is still a lack of a comprehensive review specifically for A. tatarinowii . Therefore, it is very important and necessary to conduct a comprehensive review of the research progress on A. tatarinowii in recent years. This is the first up-to-date review of A. tatarinowii research developments which includes its botany, traditional uses, phytochemistry, and pharmacology. It offers a review of A. tatarinowii research, points out gaps in existing research, and suggests new areas for investigation. The authors hope this review will inspire new research on the pharmacological effects and processes behind A. tatarinowii therapeutic effects and provide researchers with a wider perspective and fresh ideas for studying the plant’s present and prospective uses. A. tatarinowii is a semi-evergreen perennial hairless plant. It usually grows in creeks, ponds, and other humid environments below 2600 m. According to the online records of China’s flora ( http://www.cn-flora.ac.cn/index.html accessed on 15 March 2023), it has a creeping rhizome. The rhizome is aromatic, with a thickness of 2–5 mm, externally light brown, and its internode length is 3–5 mm, with mostly fibrous roots. The rhizome’s upper part is very dense, and branches are often fibrous, persisting at the leaf base. Leaves are sessile with a thin leaf blade, with membranous leaf sheaths up to 5 mm wide on both sides of the base, ascending to the middle of the leaf blade, tapering, and undergoing abscission. The leaf blade is dark green, linear, 20–30 cm long, and its base is folded in half and spread above the middle. It is 7–13 mm wide, with a tapering apex, no middle rib, many parallel veins, and a slightly raised angle. It has an axillary inflorescence stalk, 4–15 cm long, that is triangular. The bracts are 13–25 cm long, the fleshy spikes are 2–5 times longer, and are subequal in length. The inflorescences are terete, 4–6.5 cm long, 4–7 mm thick, superficially acuminate, erect, or slightly curved. The flowers are white. The mature fruit is 7–8 cm long and up to 1 cm thick. The young fruits are green, yellow-green, or yellow-white when mature. The flowering period is from February to June. Usually, rhizomes are dug out in autumn and winter, and leaves and fibrous roots are removed, cleaned, and further dried to obtain the medicinal part of A. tatarinowii . The A. tatarinowii herbal parts used in Chinese medicine are usually flat or long and thick. The plant’s features are shown in . The outer skin is gray-brown, with some visible links and root marks. The cut surface is fibrous, white, or reddish, with distinct rings and oil spots. It has a sweet odor and a bitter, pungent taste. The observation of some sections of A. tatarinowii under the microscope showed that the outer wall of epidermal cells on the transverse section of the A. tatarinowii rhizome was thickened and brown, and some also contained reddish-brown substances. The cortex of A. tatarinowii is wide, with scattered fiber bundles and leaf trace vascular bundles. The leaf trace vascular bundle is externally hardened, and the vascular bundle sheath fibers are ringed and lignified; the endodermis is clearly visible. The vascular bundle of the middle column is of the wood type and outer type, and the vascular bundle sheath fiber is less. The cells around the fiber bundles and vascular bundle sheath fibers contain calcium oxalate crystals, forming crystalline fibers. Round-like oil cells are scattered in parenchyma cells that contain starch granules. A. tatarinowii has been widely used as a medicinal plant in China for 2000 years. Since ancient times, researchers have continuously explored and exploited TCM practices. TCM uses in the treatment and prevention of disease have boosted trust and resolve in its advancement and innovation. In the recorded history of folk culture, A. tatarinowii is a commonly used TCM. Generally speaking, each TCM has its inherent taste and characteristics. A. tatarinowii has a bitter and spicy taste and a warm nature. In addition, according to the different meridians of each TCM, A. tatarinowii has a stimulating effect on the heart and stomach meridians. Based on its action on these meridians, it can calm the mind, resolve dampness, harmonize the stomach, and unblock painful obstructions. It releases the exterior while dispersing cold and expelling wind-dampness. The property of sexual taste meridian attribution is very important in guiding clinical drug applications in the TCM system . It is used for multiple medicinal purposes, traditionally for treating epilepsy, depression, fever, dizziness after a high fever, deafness, heartache, stomachache, and other diseases. A. tatarinowii has a long medicinal use history in China, and it is not only an important TCM itself but is also a critical part of TCM prescriptions . In addition to using A. tatarinowii to treat different diseases, A. tatarinowii can be combined with different TCMs to achieve improved therapeutic effects. For example, A. tatarinowii is commonly used with TCMs such as bupleurum and turmeric, which have significant antidepressant effects, to prepare a mixed formulation to improve its antidepressant effect. It is commonly used in depression-like disorders in the clinical environment . Further, preclinical studies have shown that A. tatarinowii has strong antidepressant activity. Many studies have found that its water extract, ethanol extract, and extract with other solvents have strong activity from the perspective of different extraction methods. Further studies have shown that the active ingredient asarone exhibits a strong antidepressant effect and is of great research value . In addition to this, the A. tatarinowii ethanol extract has antifungal activity and can be used to treat digestive diseases, such as diarrhea . In addition, in Korean medicine, after a lot of verification, it has also been found that A. tatarinowii has a positive therapeutic effect on brain diseases such as meningitis and is also effective for AD, Parkinson’s disease (PD), and other neurological diseases caused by population aging. In addition, the process of A. tatarinowii treating brain diseases and nervous system diseases has been found to be the same as in our cognition of the TCM system . In short, the various therapeutic effects of A. tatarinowii in traditional uses, as well as its potential for future applications, have been supported by abundant evidence and warrant further investigation. To date, A. tatarinowii has been investigated from a phytochemical perspective. The literature indicates the presence of numerous chemical compounds, such as phenylpropanoids, terpenoids, lignans, flavonoids, alkaloids, amides, organic acids, and other classes. Until now, more than 160 compounds have been isolated and characterized. These compounds are summarized in . 4.1. Phenylpropanoids Phenylpropanoids are a class of natural compounds that contain one or several C6-C3 units in their structure. Phenylpropanoids isolated from A. tatarinowii often have a specific characteristic structure, bearing methoxy groups in the benzene ring. Till now, 35 phenylpropanoids ( 1 – 35 ) have been isolated from the rhizomes of A. tatarinowii . Among the phenylpropanoids, α-asarone and β-asarone were reported to be the major A. tatarinowii constituents. 4.2. Sesquiterpenes At present, more than 20 sesquiterpenoids have been isolated from A. tatarinowii . Sesquiterpenes are the most abundant group of terpenoids, whose skeleton is composed of 3 isoprene units and contains 15 carbon atoms. The oxygenated derivatives of sesquiterpenes have a strong aroma and biological activity and are also important raw materials in the medicine, food, and cosmetics industries. Most sesquiterpenes in A. tatarinowii are monocyclic sesquiterpenes . 4.3. Lignans Lignans are a class of natural compounds that result from the polymerization of two molecules (a few are from three or four molecules) of phenylpropanoid derivatives, and they are mainly present in the wood and resin of plants. The lignan monomers are mainly composed of cinnamic acid, cinnamyl alcohol, propenyl benzene, and allyl benzene . At present, more than 40 lignans have been extracted from A. tatarinowii , mainly divided into two structural types: monoepoxide lignans and double epoxide lignans. Among them, Veraguensin ( 65 ), Magnosalicin ( 66 ), (2 S ,3 R )-ceplignan ( 71 ), (2 R ,3 S )-ceplignan ( 72 ), Acortatarinowin I ( 75 ), Acortatarinowin J ( 76 ), Acortatarinowin K ( 77 ), Acortatarinowin L ( 78 ), Saucernetindiol ( 82 ), Machilin-I ( 83 ), and others are monoepoxide lignans, while Tatarinowin ( 62 ), Eudesmin ( 67 ), (±)-Acortatarinowin F ( 90 ), and (±)-Pinoresinol ( 106 ) are double epoxide lignans . 4.4. Flavonoids Flavonoids are a class of compounds with a core nucleus of a 2-phenyl chromone molecule and no oxygen-containing group substitution at the 3-position. They are widely present in the plant kingdom and are among the most active natural active ingredients . Three flavonoid glycosides have been isolated from rhizomes of A. tatarinowii : Kaempferol-3- O -rutinoside ( 107 ), Rhoifolin ( 108 ), and Isoschaftoside ( 109 ). Compared with other compounds, there is not a lot of information on A. tatarinowii flavonoid structure. Therefore, future efforts should be made to isolate and characterize flavonoids in A. tatarinowii . The chemical structures of the flavonoid compounds are shown in . 4.5. Alkaloids Alkaloids are secondary metabolites that contain nitrogen atoms in the negative oxidation state and are present in biological organisms. They are alkaline organic compounds containing nitrogen. Alkaloids are also important plant chemical constituents known to have various pharmacological effects in humans and animals. To date, seven alkaloids ( 110 – 116 ) have been isolated from A. tatarinowii . 4.6. Amides Acyl compounds linked to nitrogen atoms are termed amides, a class of nitrogen-containing carboxylic acid derivatives. The amide bond is the most typical functional group in chemical, biological, and pharmaceutical compound synthesis. Because of the importance of amide bonds, their synthesis has become the most commonly used reaction in drug synthesis. Over 11 amides have been discovered in A. tatarinowii ( 117 – 127 ), which are derived from a straight chain amide with an isobutyl group . 4.7. Organic Acids Organic acids are a class of compounds containing carboxyl groups and are abundant in the leaves, roots, and especially fruits of plants. Most of them are present in the form of salt, and some of them are combined into esters. Thirteen organic acids were isolated from A. tatarinowii , of which 128 – 132 were aromatic organic acids. Most organic acids isolated from A. tatarinowii exhibit weak acidity . 4.8. Others In addition to the compound classes mentioned above, more than 20 other compounds have been isolated from A. tatarinowii , including the diterpenoids Tatarol ( 142 ) and Tataroside ( 143 ), the phenolic compounds Aspidinol ( 148 ) and Apocynin ( 149 ), the esters 3-butyl-phthalide ( 152 ) and diisocaprylphthalate ( 163 ), the ether polymer Bisasaricin ( 156 ), and others . The above findings illustrate the wide chemical composition of A. tatarinowii , which is of immense future research value. Phenylpropanoids are a class of natural compounds that contain one or several C6-C3 units in their structure. Phenylpropanoids isolated from A. tatarinowii often have a specific characteristic structure, bearing methoxy groups in the benzene ring. Till now, 35 phenylpropanoids ( 1 – 35 ) have been isolated from the rhizomes of A. tatarinowii . Among the phenylpropanoids, α-asarone and β-asarone were reported to be the major A. tatarinowii constituents. At present, more than 20 sesquiterpenoids have been isolated from A. tatarinowii . Sesquiterpenes are the most abundant group of terpenoids, whose skeleton is composed of 3 isoprene units and contains 15 carbon atoms. The oxygenated derivatives of sesquiterpenes have a strong aroma and biological activity and are also important raw materials in the medicine, food, and cosmetics industries. Most sesquiterpenes in A. tatarinowii are monocyclic sesquiterpenes . Lignans are a class of natural compounds that result from the polymerization of two molecules (a few are from three or four molecules) of phenylpropanoid derivatives, and they are mainly present in the wood and resin of plants. The lignan monomers are mainly composed of cinnamic acid, cinnamyl alcohol, propenyl benzene, and allyl benzene . At present, more than 40 lignans have been extracted from A. tatarinowii , mainly divided into two structural types: monoepoxide lignans and double epoxide lignans. Among them, Veraguensin ( 65 ), Magnosalicin ( 66 ), (2 S ,3 R )-ceplignan ( 71 ), (2 R ,3 S )-ceplignan ( 72 ), Acortatarinowin I ( 75 ), Acortatarinowin J ( 76 ), Acortatarinowin K ( 77 ), Acortatarinowin L ( 78 ), Saucernetindiol ( 82 ), Machilin-I ( 83 ), and others are monoepoxide lignans, while Tatarinowin ( 62 ), Eudesmin ( 67 ), (±)-Acortatarinowin F ( 90 ), and (±)-Pinoresinol ( 106 ) are double epoxide lignans . Flavonoids are a class of compounds with a core nucleus of a 2-phenyl chromone molecule and no oxygen-containing group substitution at the 3-position. They are widely present in the plant kingdom and are among the most active natural active ingredients . Three flavonoid glycosides have been isolated from rhizomes of A. tatarinowii : Kaempferol-3- O -rutinoside ( 107 ), Rhoifolin ( 108 ), and Isoschaftoside ( 109 ). Compared with other compounds, there is not a lot of information on A. tatarinowii flavonoid structure. Therefore, future efforts should be made to isolate and characterize flavonoids in A. tatarinowii . The chemical structures of the flavonoid compounds are shown in . Alkaloids are secondary metabolites that contain nitrogen atoms in the negative oxidation state and are present in biological organisms. They are alkaline organic compounds containing nitrogen. Alkaloids are also important plant chemical constituents known to have various pharmacological effects in humans and animals. To date, seven alkaloids ( 110 – 116 ) have been isolated from A. tatarinowii . Acyl compounds linked to nitrogen atoms are termed amides, a class of nitrogen-containing carboxylic acid derivatives. The amide bond is the most typical functional group in chemical, biological, and pharmaceutical compound synthesis. Because of the importance of amide bonds, their synthesis has become the most commonly used reaction in drug synthesis. Over 11 amides have been discovered in A. tatarinowii ( 117 – 127 ), which are derived from a straight chain amide with an isobutyl group . Organic acids are a class of compounds containing carboxyl groups and are abundant in the leaves, roots, and especially fruits of plants. Most of them are present in the form of salt, and some of them are combined into esters. Thirteen organic acids were isolated from A. tatarinowii , of which 128 – 132 were aromatic organic acids. Most organic acids isolated from A. tatarinowii exhibit weak acidity . In addition to the compound classes mentioned above, more than 20 other compounds have been isolated from A. tatarinowii , including the diterpenoids Tatarol ( 142 ) and Tataroside ( 143 ), the phenolic compounds Aspidinol ( 148 ) and Apocynin ( 149 ), the esters 3-butyl-phthalide ( 152 ) and diisocaprylphthalate ( 163 ), the ether polymer Bisasaricin ( 156 ), and others . The above findings illustrate the wide chemical composition of A. tatarinowii , which is of immense future research value. Modern pharmacological research has revealed that A. tatarinowii exerts various pharmacological activities, including antidepressant, antiepileptic, anticonvulsant, antianxiety, neuroprotective, antifatigue, antifungal, improving AD, and others. These increasingly in-depth pharmacological studies provide an improved scientific basis for clinical practice . The properties of A. tatarinowii active compounds, their pharmacological effects, and potential mechanisms of action on the basis of different types of extracts and compounds are summarized in . 5.1. Antidepressant Properties Depression, under the increasing pressure of social activities, has gradually become one of the most common psychiatric disorders. It severely limits psychosocial functioning and quality of life. At the same time, it is becoming a heavy economic burden to society and families . Studies have shown that the water extract of A. tatarinowii can be effective against depression. Experiments were carried out using the forced swimming test (FST), tail suspension test (TST), and locomotor activity (LA) in mice. The mice were acclimated in a quiet laboratory for 60 min and then placed in water alone for 6 min. The mice were suspended from the tail end with tape at about 2 cm from the tail tip so that the mice were suspended 15 cm from the ground. Their movement within the next 30 min was recorded using a high-definition digital camera. The immobility time of mice in the above conditions was recorded. The results confirmed that the A. tatarinowii water extracts significantly decreased mice immobility time but did not alter the mice’s locomotor activity. At the same time, the serotonin transporter (SERT) activity was significantly increased at a dose of 100 μg/mL of the A. tatarinowii water extract. Moreover, the petroleum ether extract of A. tatarinowii also significantly increased SERT activity at a dose of 1.56 μg/mL. In contrast, the water extract after petroleum ether processing significantly inhibited SERT activity at 50–100 μg/mL. Thus, A. tatarinowii could regulate SERT activities in a bidirectional manner, potentially exerting its antidepressant properties . In addition, α-asarone and β-asarone, the main components of essential oil (EO) from the rhizome of A. tatarinowii , were found to exhibit antidepressant effects. The same experiment was carried out in mice, showing that at a 5, 10, and 20 mg/kg dose of α-asarone and β-asarone, the immobility time of mice was significantly reduced ( p > 0.01). The antidepressant, imipramine, was the positive control at a dose of 15 mg/kg. Notably, α-asarone significantly reduced the immobility time at doses of 10 and 20 mg/kg ( p > 0.05 and p > 0.01) compared with the control. Furthermore, the immobility time was also decreased by β-asarone at a dose of 20 mg/kg ( p > 0.05). The mean immobility times after α-asarone and β-asarone administration were as follows: α-asarone (5, 10, and 20 mg/kg) 205.1 ± 19, 178 ± 15, and 159 ± 17 s, β-asarone (5, 10, and 20 mg/kg) 223 ± 23, 198 ± 18, and 179 ± 18 s. These results indicate dose-dependent antidepressive-like activities of α-asarone and β-asarone . In addition, to evaluate the influence of the A. tatarinowii β-asarone on depressive-like behavior induced by the chronic unpredictable mild stress (CUMS) model, the CUMS rat model of depression was used. During 28 straight days at a volume of 0.01 g/mL, β-asarone (25 mg/kg/day) or an equivalent amount of saline served as the control for rats exposed to CUMS. When compared to CUMS-exposed rats, the time spent motionless was considerably decreased by 29% after being administered β-asarone ( p < 0.05). Moreover, the Sucrose Preference Test (SPT) revealed that sucrose preference was 45% lower in CUMS-exposed rats as compared with non-stressed control rats. Additionally, β-asarone in A. tatarinowii was shown to promote hippocampal neuronal neurogenesis in CUMS-exposed rats, significantly increasing the CREB and BDNF mRNA levels. Furthermore, this research also showed that adult neurogenesis plays a role in the antidepressant-like behavioral outcomes of β-asarone, indicating that β-asarone from A. tatarinowii is a prospective option for the treatment of depression . In conclusion, A. tatarinowii extracts can have a potent antidepressant effect, providing an important natural medicine option for treating depression. 5.2. Antiepileptic Properties Epilepsy is a neurological disease caused by abnormal neuron discharge in the brain. Its onset often leads to temporary brain dysfunction, accompanied by fainting, convulsions, and other pathological reactions, affecting the normal life of many patients . Studies have shown that A. tatarinowii extract has antiepileptic effects . The maximal electroshock (MES), pentylenetetrazol (PTZ) maximal seizure, and prolonged PTZ kindling models were used to test the extract’s antiepileptic properties. Mice with persistent convulsions with tonic hindlimb extension were randomly divided into different groups. Electric stimulation was given 45 min after intraperitoneal administration of the drug or normal saline (NS), and each group’s convulsive rate was recorded. PTZ at 100 mg/kg was injected intraperitoneally 45 min after the drug or NS administration. Convulsive and mortality rates, as well as seizure latency, were recorded. The results indicated that both the decoction (at a dose of 10–20 g/kg) and volatile oil (at 1.25 g/kg) of A. tatarinowii significantly decreased the epileptic rate in the MES model. The A. tatarinowii decoction was effective in the PTZ model, with decreased epileptic and mortality rates. In the dosage range studied, the A. tatarinowii volatile oil was unable to prevent seizures, although a dose of 1.25 g/kg was observed to lengthen seizure latency and reduce mortality. The long-term PTZ kindling model was established in male Sprague Dawley (SD) rats. In the PTZ kindling model, γ—aminobutyric acid (GABA) immunohistochemical reaction (IR) (GABA-IR) neurons decreased significantly compared with the normal group. After therapy with the decoction and volatile oil, the severity of the seizures dramatically diminished in the treated groups. As compared to PTZ kindling controls, more GABA-IR neurons were discovered. Morphological examination also indicated that GABA-IR neuron loss was less severe in the drug-treated groups. All in all, both the decoction and volatile oil extracted from A. tatarinowii were shown to possess antiepileptic properties. The volatile oil was less effective for PTZ-induced epilepsies. Both extracts could prevent epileptic episodes, as well as epilepsy-related GABAergic neuron damage in the brain in the prolonged PTZ kindling model . These results provide a scientific basis for the clinical antiepileptic application of A. tatarinowii and benefit the development and production of novel antiepileptic drugs. 5.3. Anticonvulsant Properties The typical clinical manifestations of convulsive seizures are sudden loss of consciousness and sudden generalized or localized, tonic or clonic facial and limb muscle convulsions. Prolonged convulsions can cause hyperthermia, hypoxic brain damage, cerebral edema, and even cerebral hernia, which can be life-threatening . A. tatarinowii lignans, especially eudesmin, have shown significant anticonvulsant effects on mice. MES- and PTZ-induced seizures in male mice were used to evaluate the anticonvulsant activities of eudesmin. Mice were pretreated with intraperitoneal injections of eudesmin (5, 10, and 20 mg/kg), while NS (20 kg/mL) was used as the blank control group. Mice from the MES model group were intraperitoneally injected with phenytoin (20 mg/kg) again, while the PTZ model group was injected with diazepam (4 mg/kg). After 30 min, the MES model group was given an electric shock, and the PTZ model group was subcutaneously injected with PTZ (90 mg/kg). The results showed that eudesmin exhibited significant anticonvulsant effects at the 5, 10, and 20 mg/kg doses. In addition, no convulsion or death was observed in the mice treated with the positive control drugs phenytoin 20 mg/kg and diazepam 4 mg/kg. Finally, the eudesmin mechanism of action was investigated by determining the glutamic acid (Glu) and gamma-aminobutyric acid (GABA) content in epileptic mice and glutamate decarboxylase 65 (GAD65), GABAA, Bcl-2, and caspase-3 gene expression in the brain of chronic epileptic rats. The MES and PTZ test results revealed that eudesmin isolated from A. tatarinowii possesses significant anticonvulsant effects. Furthermore, after eudesmin treatment, the GABA content increased, whereas the Glu content decreased, and the ratio of Glu/GABA decreased. Moreover, GAD65, GABAA, and Bcl-2 were up-regulated after treatment with eudesmin, whereas caspase-3 was down-regulated. In summary, the anticonvulsant effect of eudesmin isolated from A. tatarinowii may be associated with the up-regulation of GABAA and GAD65 expression and neuron anti-apoptosis in the brain . Another study found that the anticonvulsant effect against the pain models in mice was observed when an A. tatarinowii methanol extract was administered orally at 100 and 200 mg/kg doses. The anticonvulsant effect was studied through the PTZ-induced seizures method. The results suggest that the activity of GABA might potentiate the anticonvulsant effects . In summary, these findings may provide novel directions or insights into treating convulsions using TCM, such as A. tatarinowii. 5.4. Antianxiety Properties One of the most prevalent mental diseases and the primary contributor to psychosocial dysfunction is anxiety. This disorder causes high costs in terms of healthcare use, disability, loss of productivity, and patient quality of life . A frequent comorbidity of chronic pain is anxiety illness. Those who experience chronic pain are more likely to develop anxiety problems, according to earlier research. Tian et al. discovered that A. tatarinowii extract has potential antianxiety properties. Previous studies have shown that anxiety-like behavior could be induced in mice with persistent inflammatory pain. First, to induce chronic inflammatory pain, a single dose of complete Freund’s adjuvant (CFA) (50% of 10 μL CFA) was injected into the plantar surface of the left hind paw. Mice exhibited significant anxiety-like behavior two weeks after the CFA injection . The mice were placed in a central square device, allowing free movement for 5 min. The number of entries and time spent in each treatment arm were recorded. Mice were placed in the box’s center and allowed to explore freely for 15 min. A decrease in the time spent and the number of entries in the open arms in the elevated plus maze test (EPMT) revealed the anxiety-related behavioral phenotype as well as a decrease in the percentage of time spent in central areas in the open field test (OFT). Administration of α-asarone (2 and 20 mg/kg) for one week (from day 8 to day 14 after CFA injection) inhibited the anxiety-like behavior in a dose-dependent manner without affecting locomotor activity. This was achieved by regulating the balance between GABAergic and glutamatergic transmission in the basolateral (BLA), achieving partially inhibited chronic pain-induced anxiety-like behaviors in mice . On the other hand, it has been suggested that GABAergic inhibition is essential for the modulation and maintenance of excitation/inhibition balance. GABAA receptors play the most important role in GABAergic inhibition. Clinically, some anxiolytic drugs exert their effects by binding with the GABAA receptors . The above investigations will serve as a guide for more in-depth clinical uses of A. tatarinowii for the treatment of anxiety. 5.5. Neuroprotective Properties At present, there are many protective mechanisms for neurological disorders, and oxidative stress in the neuronal cell has been proposed to play a crucial role in disease progression . The use of A. tatarinowii and its primary components, α-asarone and β-asarone, in treating neurological illnesses, particularly in neuroprotection, has been supported by a number of lines of evidence . Test-butyl hydroperoxide (tBHP)-induced rat primary astrocytes were used to evaluate the neuroprotective properties of the volatile oil and asarone from A. tatarinowii . Primary cultured rat astrocytes were plated and pretreated with different medications for 48 h. Then, the cultures were treated with tBHP for 3 h. Cultured rat astrocytes were pretreated with α-asarone, β-asarone, or the A. tatarinowii volatile oil for 48 h. The A. tatarinowii representative constituents exhibited promising protective effects on the cultures. The administration of tBHP in the cultures led to the induction of oxidative stress and cell death, with the application of tBHP considerably lowering cell viability in a dose-dependent manner. The application of these A. tatarinowii representative constituents protected against cell death induced by the tBHP challenge. The tBHP-induced cell death in the cultured astrocytes was considerably decreased after a dose-dependent pretreatment. The A. tatarinowii representative constituents did not show cytotoxicity nor a proliferating effect on the cultures in all the concentrations (0.5 to 15 μg/mL) applied. In addition, α-asarone and β-asarone (3, 10, and 30 mg/kg) have demonstrated antioxidant effects in several animal seizure models . They perform a crucial protective function in maintaining normal levels of superoxide dismutase, lipid peroxidation, catalase, and glutathione-peroxidase in various stressed-out areas of rat brains. This suggests that they play a neuroprotective role through an antioxidant pathway . Moreover, the β-asarone of A. tatarinowii exhibited neuroprotective effects against spatial memory impairment and synaptogenesis in the chronic lead (Pb)-exposed rats. Both SD developmental rat pups and adult rats were used in the study. Rat pups were exposed to Pb throughout the lactation period, and β-asarone (10 and 40 mg/kg) was given intraperitoneally from postnatal day 14 to 21. In addition, the adult rats were exposed to Pb from the embryo stage to 11 weeks old, and β-asarone (2.5, 10, and 40 mg/kg) was given during the period from 9 to 11 weeks old. The Morris water maze test and Golgi–Cox staining method were used to assess spatial memory ability and synaptogenesis. Rats were anesthetized with CO 2 and quickly decapitated. The brains were longitudinally cut into two halves. One hemisphere was processed for morphological staining, and the other hemisphere was used to examine specific protein expression. It should be noted that A. tatarinowii constituents can pass through the blood–brain barrier quickly . It effectively attenuated the Pb-induced reduction of spine density in hippocampal CA1 and dentate gyrus areas in a dose-dependent manner both in developmental and adult rats. At the same time, the Pb-induced impairments of learning and memory were partially rescued. In addition, it resulted in the up-regulation of NR2B, Arc, and Wnt7a protein expression, as well as an increase in the mRNA levels of Arc/Arg3.1 and Wnt7a . In conclusion, the neuroprotective properties of A. tatarinowii offer an intriguing treatment strategy for a variety of neurological disorders. 5.6. Protective Effects against Alzheimer’s Disease AD is a degenerative disease of the central nervous system primarily characterized by the progressive loss of cognition and memory. AD has several pathological hallmarks, including extracellular amyloid plaque formation, intracellular neurofibrillary tangles, and neuronal loss . The most important feature of AD is the gradual, irreversible cognitive ability loss through amyloid β (Aβ) plaque formation and of neurofibrillary tangles composed of tau protein . Previous studies have shown that this TCM has ameliorative and protective properties against neurodegenerative diseases, such as Parkinson’s disease and AD, hypoxic–ischemic encephalopathy, and cerebrovascular diseases . β-asarone, the main A. tatarinowii constituent, plays an important role in the central nervous system. Wang et al. established the AD cell model, culturing PC12 cells in vitro , and Aβ 1–42 was then added into the medium at different concentrations and time points. As the concentration of Aβ 1–42 and time increased, the PC12 cell viability decreased in a dose-dependent manner; at the same time, cytotoxicity and LDH increased. Moreover, senescent cells clearly increased in cells treated with Aβ 1–42 . After establishing a stable AD cell model, they investigated the effects of gradient concentrations of β-asarone (12, 24, 36, 72, and 144 μM) or donepezil (10, 20, and 40 μM). The β-asarone protective effect on cell proliferation was dose-dependent; the low-dose group demonstrated a better protective effect than the high-dose group. Subsequently, 24, 36, and 72 μM of β-asarone and 9.6 μM of donepezil were chosen as the ideal concentrations, respectively. Compared with model cells, β-asarone and donepezil both improved cell proliferation and decreased cell damage . At the same time, they also decreased the cell senescence rate. In conclusion, the study demonstrated that the β-asarone in A. tatarinowii can inhibit Aβ, which has a significant therapeutic effect against toxic protein deposition . Another study used adult male Wistar rats to examine the effects of β-asarone on neurodegeneration brought on by intrahippocampal injection of Aβ. The Alzheimer’s disease model was established, and then the rats were treated with β-asarone (12.5, 25, and 50 mg/kg). Rats were randomly divided into groups and were bilaterally injected with Aβ. Thirty days before Aβ administration, an intragastric tube was used to administer β-asarone for fifty days, every day. Once the rats were sacrificed, the hippocampal homogenate’s oxidative stress parameters, superoxide dismutase (SOD), and glutathione peroxidase (GPX) activity were assessed. The results showed that β-asarone at doses of 25 and 50 mg/kg significantly increased the levels of antioxidant enzymes, including SOD and GPX. Moreover, β-asarone significantly decreased cell loss in the cerebral cortex and hippocampus . These findings suggest that A. tatarinowii and its active constituent β-asarone have potential therapeutic effects against Alzheimer’s disease, which could be useful for the development of new drugs. 5.7. Antifatigue Properties Fatigue may be defined as the inability to maintain the expected muscle strength, leading to reduced performance during prolonged exercise. However, the cause is usually not muscle fatigue but an increase in serotonin or 5-hydroxytryptamine (5-HT) concentration in the brain during prolonged exercise . A. tatarinowii is an ancient TCM tonic nourishment that can be used as an antifatigue medicine. The influence of A. tatarinowii on endurance exercise was determined by the fatigue time of adult male rats during a treadmill exercise. Rats were injected with A. tatarinowii water extract (1, 10, and 100 mg/kg) two hours before the treadmill exercise. Caffeine was used as the positive control drug. A. tatarinowii prolonged the time to exhaustion by treadmill exercise in a dose-dependent way. Notably, A. tatarinowii at 100 mg/kg was just as effective as caffeine (10 mg/kg) in prolonging the time to exhaustion during the treadmill exercise. By preventing the exercise-induced decrease in 5-HT1B mRNA and protein expression in the dorsal raphe, A. tatarinowii was able to increase exercise endurance. It could also attenuate the exercise-induced increase in 5-HT synthesis, the TPH2 mRNA and protein expression, and other effects. Moreover, the effects of A. tatarinowii were comparable to those of caffeine . These findings support the traditional medical application of A. tatarinowii and point to its potential therapeutic value as an antifatigue drug. 5.8. Antifungal Properties Fungal infections can result in many diseases, including dermatosis with skin infections and fungal enteritis with acute or chronic infections of deep tissues, causing significant morbidity and mortality in susceptible populations. Candida spp. are common opportunistic fungal pathogens, among which Candida albicans is the most common infectious fungal agent . C. albicans is a normal human intestinal, oral cavity, and vaginal microflora constituent. It can cause infections ranging from easily treatable superficial infections to life-threatening invasive infections . The ethanol extract of A. tatarinowii was shown to possess antifungal activities in vivo and in vitro . Its fungicidal efficiency was evaluated in vivo, with mice randomly divided into four groups. In the first group, mice were pricked with a needle in their abdomens and orally fed PBS as the KB-negative control group. The other three groups of mice were infected intraperitoneally with 5 × 10 5 CFU of log-phase C. albicans . After two days, mice of groups 2–4 were orally fed with the ethanol extract of A. tatarinowii , fluconazole (positive drug control group), or PBS (negative control group) (8 mg/kg) once every day for seven days. After seven days, the ethanol extract of A. tatarinowii significantly reduced the fungal burden in the spleen, liver, and kidney compared to fluconazole. These results suggest that ethanol extract of A. tatarinowii can be used to treat deep C. albicans infections . Additionally, a sterile filter paper disk impregnated with ethanol extract of A. tatarinowii was placed on an agar plate, inoculated with a C. albicans suspension, and incubated under aerobic conditions for 24 h. The diameters of inhibition zones were then measured and recorded. A. tatarinowii resulted in an inhibition zone of 9.9 ± 0.5 mm against C. albicans , compared with 7 mm in the control group. Further, the MIC and MFC values of A. tatarinowii against C. albicans were 51.2 and 102.4 μg/mL. A. tatarinowii showed significantly higher potency against C. albicans than the two positive control drugs, fluconazole and itraconazole, at 51.2 μg/mL . In summary, the ethanol extract of A. tatarinowii has superior antifungal activity in vivo and in vitro . These results could contribute to reducing antibiotic consumption for the treatment of fungal infections, thereby helping to reduce the emergence of antibiotic resistance. They further promote the safe and effective use of A. tatarinowii for traditional and modern medical applications. Depression, under the increasing pressure of social activities, has gradually become one of the most common psychiatric disorders. It severely limits psychosocial functioning and quality of life. At the same time, it is becoming a heavy economic burden to society and families . Studies have shown that the water extract of A. tatarinowii can be effective against depression. Experiments were carried out using the forced swimming test (FST), tail suspension test (TST), and locomotor activity (LA) in mice. The mice were acclimated in a quiet laboratory for 60 min and then placed in water alone for 6 min. The mice were suspended from the tail end with tape at about 2 cm from the tail tip so that the mice were suspended 15 cm from the ground. Their movement within the next 30 min was recorded using a high-definition digital camera. The immobility time of mice in the above conditions was recorded. The results confirmed that the A. tatarinowii water extracts significantly decreased mice immobility time but did not alter the mice’s locomotor activity. At the same time, the serotonin transporter (SERT) activity was significantly increased at a dose of 100 μg/mL of the A. tatarinowii water extract. Moreover, the petroleum ether extract of A. tatarinowii also significantly increased SERT activity at a dose of 1.56 μg/mL. In contrast, the water extract after petroleum ether processing significantly inhibited SERT activity at 50–100 μg/mL. Thus, A. tatarinowii could regulate SERT activities in a bidirectional manner, potentially exerting its antidepressant properties . In addition, α-asarone and β-asarone, the main components of essential oil (EO) from the rhizome of A. tatarinowii , were found to exhibit antidepressant effects. The same experiment was carried out in mice, showing that at a 5, 10, and 20 mg/kg dose of α-asarone and β-asarone, the immobility time of mice was significantly reduced ( p > 0.01). The antidepressant, imipramine, was the positive control at a dose of 15 mg/kg. Notably, α-asarone significantly reduced the immobility time at doses of 10 and 20 mg/kg ( p > 0.05 and p > 0.01) compared with the control. Furthermore, the immobility time was also decreased by β-asarone at a dose of 20 mg/kg ( p > 0.05). The mean immobility times after α-asarone and β-asarone administration were as follows: α-asarone (5, 10, and 20 mg/kg) 205.1 ± 19, 178 ± 15, and 159 ± 17 s, β-asarone (5, 10, and 20 mg/kg) 223 ± 23, 198 ± 18, and 179 ± 18 s. These results indicate dose-dependent antidepressive-like activities of α-asarone and β-asarone . In addition, to evaluate the influence of the A. tatarinowii β-asarone on depressive-like behavior induced by the chronic unpredictable mild stress (CUMS) model, the CUMS rat model of depression was used. During 28 straight days at a volume of 0.01 g/mL, β-asarone (25 mg/kg/day) or an equivalent amount of saline served as the control for rats exposed to CUMS. When compared to CUMS-exposed rats, the time spent motionless was considerably decreased by 29% after being administered β-asarone ( p < 0.05). Moreover, the Sucrose Preference Test (SPT) revealed that sucrose preference was 45% lower in CUMS-exposed rats as compared with non-stressed control rats. Additionally, β-asarone in A. tatarinowii was shown to promote hippocampal neuronal neurogenesis in CUMS-exposed rats, significantly increasing the CREB and BDNF mRNA levels. Furthermore, this research also showed that adult neurogenesis plays a role in the antidepressant-like behavioral outcomes of β-asarone, indicating that β-asarone from A. tatarinowii is a prospective option for the treatment of depression . In conclusion, A. tatarinowii extracts can have a potent antidepressant effect, providing an important natural medicine option for treating depression. Epilepsy is a neurological disease caused by abnormal neuron discharge in the brain. Its onset often leads to temporary brain dysfunction, accompanied by fainting, convulsions, and other pathological reactions, affecting the normal life of many patients . Studies have shown that A. tatarinowii extract has antiepileptic effects . The maximal electroshock (MES), pentylenetetrazol (PTZ) maximal seizure, and prolonged PTZ kindling models were used to test the extract’s antiepileptic properties. Mice with persistent convulsions with tonic hindlimb extension were randomly divided into different groups. Electric stimulation was given 45 min after intraperitoneal administration of the drug or normal saline (NS), and each group’s convulsive rate was recorded. PTZ at 100 mg/kg was injected intraperitoneally 45 min after the drug or NS administration. Convulsive and mortality rates, as well as seizure latency, were recorded. The results indicated that both the decoction (at a dose of 10–20 g/kg) and volatile oil (at 1.25 g/kg) of A. tatarinowii significantly decreased the epileptic rate in the MES model. The A. tatarinowii decoction was effective in the PTZ model, with decreased epileptic and mortality rates. In the dosage range studied, the A. tatarinowii volatile oil was unable to prevent seizures, although a dose of 1.25 g/kg was observed to lengthen seizure latency and reduce mortality. The long-term PTZ kindling model was established in male Sprague Dawley (SD) rats. In the PTZ kindling model, γ—aminobutyric acid (GABA) immunohistochemical reaction (IR) (GABA-IR) neurons decreased significantly compared with the normal group. After therapy with the decoction and volatile oil, the severity of the seizures dramatically diminished in the treated groups. As compared to PTZ kindling controls, more GABA-IR neurons were discovered. Morphological examination also indicated that GABA-IR neuron loss was less severe in the drug-treated groups. All in all, both the decoction and volatile oil extracted from A. tatarinowii were shown to possess antiepileptic properties. The volatile oil was less effective for PTZ-induced epilepsies. Both extracts could prevent epileptic episodes, as well as epilepsy-related GABAergic neuron damage in the brain in the prolonged PTZ kindling model . These results provide a scientific basis for the clinical antiepileptic application of A. tatarinowii and benefit the development and production of novel antiepileptic drugs. The typical clinical manifestations of convulsive seizures are sudden loss of consciousness and sudden generalized or localized, tonic or clonic facial and limb muscle convulsions. Prolonged convulsions can cause hyperthermia, hypoxic brain damage, cerebral edema, and even cerebral hernia, which can be life-threatening . A. tatarinowii lignans, especially eudesmin, have shown significant anticonvulsant effects on mice. MES- and PTZ-induced seizures in male mice were used to evaluate the anticonvulsant activities of eudesmin. Mice were pretreated with intraperitoneal injections of eudesmin (5, 10, and 20 mg/kg), while NS (20 kg/mL) was used as the blank control group. Mice from the MES model group were intraperitoneally injected with phenytoin (20 mg/kg) again, while the PTZ model group was injected with diazepam (4 mg/kg). After 30 min, the MES model group was given an electric shock, and the PTZ model group was subcutaneously injected with PTZ (90 mg/kg). The results showed that eudesmin exhibited significant anticonvulsant effects at the 5, 10, and 20 mg/kg doses. In addition, no convulsion or death was observed in the mice treated with the positive control drugs phenytoin 20 mg/kg and diazepam 4 mg/kg. Finally, the eudesmin mechanism of action was investigated by determining the glutamic acid (Glu) and gamma-aminobutyric acid (GABA) content in epileptic mice and glutamate decarboxylase 65 (GAD65), GABAA, Bcl-2, and caspase-3 gene expression in the brain of chronic epileptic rats. The MES and PTZ test results revealed that eudesmin isolated from A. tatarinowii possesses significant anticonvulsant effects. Furthermore, after eudesmin treatment, the GABA content increased, whereas the Glu content decreased, and the ratio of Glu/GABA decreased. Moreover, GAD65, GABAA, and Bcl-2 were up-regulated after treatment with eudesmin, whereas caspase-3 was down-regulated. In summary, the anticonvulsant effect of eudesmin isolated from A. tatarinowii may be associated with the up-regulation of GABAA and GAD65 expression and neuron anti-apoptosis in the brain . Another study found that the anticonvulsant effect against the pain models in mice was observed when an A. tatarinowii methanol extract was administered orally at 100 and 200 mg/kg doses. The anticonvulsant effect was studied through the PTZ-induced seizures method. The results suggest that the activity of GABA might potentiate the anticonvulsant effects . In summary, these findings may provide novel directions or insights into treating convulsions using TCM, such as A. tatarinowii. One of the most prevalent mental diseases and the primary contributor to psychosocial dysfunction is anxiety. This disorder causes high costs in terms of healthcare use, disability, loss of productivity, and patient quality of life . A frequent comorbidity of chronic pain is anxiety illness. Those who experience chronic pain are more likely to develop anxiety problems, according to earlier research. Tian et al. discovered that A. tatarinowii extract has potential antianxiety properties. Previous studies have shown that anxiety-like behavior could be induced in mice with persistent inflammatory pain. First, to induce chronic inflammatory pain, a single dose of complete Freund’s adjuvant (CFA) (50% of 10 μL CFA) was injected into the plantar surface of the left hind paw. Mice exhibited significant anxiety-like behavior two weeks after the CFA injection . The mice were placed in a central square device, allowing free movement for 5 min. The number of entries and time spent in each treatment arm were recorded. Mice were placed in the box’s center and allowed to explore freely for 15 min. A decrease in the time spent and the number of entries in the open arms in the elevated plus maze test (EPMT) revealed the anxiety-related behavioral phenotype as well as a decrease in the percentage of time spent in central areas in the open field test (OFT). Administration of α-asarone (2 and 20 mg/kg) for one week (from day 8 to day 14 after CFA injection) inhibited the anxiety-like behavior in a dose-dependent manner without affecting locomotor activity. This was achieved by regulating the balance between GABAergic and glutamatergic transmission in the basolateral (BLA), achieving partially inhibited chronic pain-induced anxiety-like behaviors in mice . On the other hand, it has been suggested that GABAergic inhibition is essential for the modulation and maintenance of excitation/inhibition balance. GABAA receptors play the most important role in GABAergic inhibition. Clinically, some anxiolytic drugs exert their effects by binding with the GABAA receptors . The above investigations will serve as a guide for more in-depth clinical uses of A. tatarinowii for the treatment of anxiety. At present, there are many protective mechanisms for neurological disorders, and oxidative stress in the neuronal cell has been proposed to play a crucial role in disease progression . The use of A. tatarinowii and its primary components, α-asarone and β-asarone, in treating neurological illnesses, particularly in neuroprotection, has been supported by a number of lines of evidence . Test-butyl hydroperoxide (tBHP)-induced rat primary astrocytes were used to evaluate the neuroprotective properties of the volatile oil and asarone from A. tatarinowii . Primary cultured rat astrocytes were plated and pretreated with different medications for 48 h. Then, the cultures were treated with tBHP for 3 h. Cultured rat astrocytes were pretreated with α-asarone, β-asarone, or the A. tatarinowii volatile oil for 48 h. The A. tatarinowii representative constituents exhibited promising protective effects on the cultures. The administration of tBHP in the cultures led to the induction of oxidative stress and cell death, with the application of tBHP considerably lowering cell viability in a dose-dependent manner. The application of these A. tatarinowii representative constituents protected against cell death induced by the tBHP challenge. The tBHP-induced cell death in the cultured astrocytes was considerably decreased after a dose-dependent pretreatment. The A. tatarinowii representative constituents did not show cytotoxicity nor a proliferating effect on the cultures in all the concentrations (0.5 to 15 μg/mL) applied. In addition, α-asarone and β-asarone (3, 10, and 30 mg/kg) have demonstrated antioxidant effects in several animal seizure models . They perform a crucial protective function in maintaining normal levels of superoxide dismutase, lipid peroxidation, catalase, and glutathione-peroxidase in various stressed-out areas of rat brains. This suggests that they play a neuroprotective role through an antioxidant pathway . Moreover, the β-asarone of A. tatarinowii exhibited neuroprotective effects against spatial memory impairment and synaptogenesis in the chronic lead (Pb)-exposed rats. Both SD developmental rat pups and adult rats were used in the study. Rat pups were exposed to Pb throughout the lactation period, and β-asarone (10 and 40 mg/kg) was given intraperitoneally from postnatal day 14 to 21. In addition, the adult rats were exposed to Pb from the embryo stage to 11 weeks old, and β-asarone (2.5, 10, and 40 mg/kg) was given during the period from 9 to 11 weeks old. The Morris water maze test and Golgi–Cox staining method were used to assess spatial memory ability and synaptogenesis. Rats were anesthetized with CO 2 and quickly decapitated. The brains were longitudinally cut into two halves. One hemisphere was processed for morphological staining, and the other hemisphere was used to examine specific protein expression. It should be noted that A. tatarinowii constituents can pass through the blood–brain barrier quickly . It effectively attenuated the Pb-induced reduction of spine density in hippocampal CA1 and dentate gyrus areas in a dose-dependent manner both in developmental and adult rats. At the same time, the Pb-induced impairments of learning and memory were partially rescued. In addition, it resulted in the up-regulation of NR2B, Arc, and Wnt7a protein expression, as well as an increase in the mRNA levels of Arc/Arg3.1 and Wnt7a . In conclusion, the neuroprotective properties of A. tatarinowii offer an intriguing treatment strategy for a variety of neurological disorders. AD is a degenerative disease of the central nervous system primarily characterized by the progressive loss of cognition and memory. AD has several pathological hallmarks, including extracellular amyloid plaque formation, intracellular neurofibrillary tangles, and neuronal loss . The most important feature of AD is the gradual, irreversible cognitive ability loss through amyloid β (Aβ) plaque formation and of neurofibrillary tangles composed of tau protein . Previous studies have shown that this TCM has ameliorative and protective properties against neurodegenerative diseases, such as Parkinson’s disease and AD, hypoxic–ischemic encephalopathy, and cerebrovascular diseases . β-asarone, the main A. tatarinowii constituent, plays an important role in the central nervous system. Wang et al. established the AD cell model, culturing PC12 cells in vitro , and Aβ 1–42 was then added into the medium at different concentrations and time points. As the concentration of Aβ 1–42 and time increased, the PC12 cell viability decreased in a dose-dependent manner; at the same time, cytotoxicity and LDH increased. Moreover, senescent cells clearly increased in cells treated with Aβ 1–42 . After establishing a stable AD cell model, they investigated the effects of gradient concentrations of β-asarone (12, 24, 36, 72, and 144 μM) or donepezil (10, 20, and 40 μM). The β-asarone protective effect on cell proliferation was dose-dependent; the low-dose group demonstrated a better protective effect than the high-dose group. Subsequently, 24, 36, and 72 μM of β-asarone and 9.6 μM of donepezil were chosen as the ideal concentrations, respectively. Compared with model cells, β-asarone and donepezil both improved cell proliferation and decreased cell damage . At the same time, they also decreased the cell senescence rate. In conclusion, the study demonstrated that the β-asarone in A. tatarinowii can inhibit Aβ, which has a significant therapeutic effect against toxic protein deposition . Another study used adult male Wistar rats to examine the effects of β-asarone on neurodegeneration brought on by intrahippocampal injection of Aβ. The Alzheimer’s disease model was established, and then the rats were treated with β-asarone (12.5, 25, and 50 mg/kg). Rats were randomly divided into groups and were bilaterally injected with Aβ. Thirty days before Aβ administration, an intragastric tube was used to administer β-asarone for fifty days, every day. Once the rats were sacrificed, the hippocampal homogenate’s oxidative stress parameters, superoxide dismutase (SOD), and glutathione peroxidase (GPX) activity were assessed. The results showed that β-asarone at doses of 25 and 50 mg/kg significantly increased the levels of antioxidant enzymes, including SOD and GPX. Moreover, β-asarone significantly decreased cell loss in the cerebral cortex and hippocampus . These findings suggest that A. tatarinowii and its active constituent β-asarone have potential therapeutic effects against Alzheimer’s disease, which could be useful for the development of new drugs. Fatigue may be defined as the inability to maintain the expected muscle strength, leading to reduced performance during prolonged exercise. However, the cause is usually not muscle fatigue but an increase in serotonin or 5-hydroxytryptamine (5-HT) concentration in the brain during prolonged exercise . A. tatarinowii is an ancient TCM tonic nourishment that can be used as an antifatigue medicine. The influence of A. tatarinowii on endurance exercise was determined by the fatigue time of adult male rats during a treadmill exercise. Rats were injected with A. tatarinowii water extract (1, 10, and 100 mg/kg) two hours before the treadmill exercise. Caffeine was used as the positive control drug. A. tatarinowii prolonged the time to exhaustion by treadmill exercise in a dose-dependent way. Notably, A. tatarinowii at 100 mg/kg was just as effective as caffeine (10 mg/kg) in prolonging the time to exhaustion during the treadmill exercise. By preventing the exercise-induced decrease in 5-HT1B mRNA and protein expression in the dorsal raphe, A. tatarinowii was able to increase exercise endurance. It could also attenuate the exercise-induced increase in 5-HT synthesis, the TPH2 mRNA and protein expression, and other effects. Moreover, the effects of A. tatarinowii were comparable to those of caffeine . These findings support the traditional medical application of A. tatarinowii and point to its potential therapeutic value as an antifatigue drug. Fungal infections can result in many diseases, including dermatosis with skin infections and fungal enteritis with acute or chronic infections of deep tissues, causing significant morbidity and mortality in susceptible populations. Candida spp. are common opportunistic fungal pathogens, among which Candida albicans is the most common infectious fungal agent . C. albicans is a normal human intestinal, oral cavity, and vaginal microflora constituent. It can cause infections ranging from easily treatable superficial infections to life-threatening invasive infections . The ethanol extract of A. tatarinowii was shown to possess antifungal activities in vivo and in vitro . Its fungicidal efficiency was evaluated in vivo, with mice randomly divided into four groups. In the first group, mice were pricked with a needle in their abdomens and orally fed PBS as the KB-negative control group. The other three groups of mice were infected intraperitoneally with 5 × 10 5 CFU of log-phase C. albicans . After two days, mice of groups 2–4 were orally fed with the ethanol extract of A. tatarinowii , fluconazole (positive drug control group), or PBS (negative control group) (8 mg/kg) once every day for seven days. After seven days, the ethanol extract of A. tatarinowii significantly reduced the fungal burden in the spleen, liver, and kidney compared to fluconazole. These results suggest that ethanol extract of A. tatarinowii can be used to treat deep C. albicans infections . Additionally, a sterile filter paper disk impregnated with ethanol extract of A. tatarinowii was placed on an agar plate, inoculated with a C. albicans suspension, and incubated under aerobic conditions for 24 h. The diameters of inhibition zones were then measured and recorded. A. tatarinowii resulted in an inhibition zone of 9.9 ± 0.5 mm against C. albicans , compared with 7 mm in the control group. Further, the MIC and MFC values of A. tatarinowii against C. albicans were 51.2 and 102.4 μg/mL. A. tatarinowii showed significantly higher potency against C. albicans than the two positive control drugs, fluconazole and itraconazole, at 51.2 μg/mL . In summary, the ethanol extract of A. tatarinowii has superior antifungal activity in vivo and in vitro . These results could contribute to reducing antibiotic consumption for the treatment of fungal infections, thereby helping to reduce the emergence of antibiotic resistance. They further promote the safe and effective use of A. tatarinowii for traditional and modern medical applications. This review provided the scientific foundation for future research on A. tatarinowii and the development of better therapeutic agents using the natural medicinal plant. At the same time, according to the traditional literature and contemporary evidence, the present research status of A. tatarinowii was critically reviewed. Nowadays, A. tatarinowii is widely used in the treatment of brain diseases and nervous system diseases and has achieved satisfactory therapeutic effects . A. tatarinowii can treat brain diseases, such as epilepsy, anxiety, and depression, by regulating neurotransmitter levels. It can also improve blood circulation in the brain to alleviate neurological diseases, such as AD. To date, over 160 compounds have been isolated and identified from A. tatarinowii . It is expected that more active ingredients will be identified and characterized in future research. On the other hand, pharmacological studies published in the literature with in vitro and in vivo assays largely corroborate its wide medicinal use. These studies indicated that both the extracts and active constituents of A. tatarinowii possess a wide range of pharmacological activities. These modern pharmacological studies supported most traditional uses of A. tatarinowii as an indispensable TCM. Although significant work has been conducted on A. tatarinowii , some scientific gaps still need to be explored. Firstly, the reported studies have shown that the main chemical components of A. tatarinowii are phenylpropanoids. At the same time, there are relatively few other chemical constituents extracted and isolated from A. tatarinowii . More chemical constituents must be identified to explore the relationship between bioactive constituents and pharmacological effects in depth. More advanced instruments to separate and identify rare compounds in A. tatarinowii should be utilized to study their pharmacological activity. The active components of the aboveground parts of A. tatarinowii , such as stems and leaves, should be studied to contribute to the rational utilization of the plant’s resources and to identify the concentration of active compounds in the different plant tissues. Secondly, the research on the medicinal parts of A. tatarinowii is not comprehensive enough. Due to the highly variable secondary metabolism in plants, the chemical components and pharmacological effects of the different medicinal parts of A. tatarinowii plants are also very different. A. tatarinowii showed good anti-AD properties. Due to the aging society, the morbidity and prevalence rate of senile diseases such as AD and PD are growing at an accelerated pace. Therefore, it is urgent to study a new and novel drug for treating AD. The active ingredients of A. tatarinowii come from different tissues of the plant. Further pharmacological studies should be conducted on different chemical components of rhizomes and/or any other parts of A. tatarinowii to provide a sufficient scientific basis and in-depth research on the function and mechanism of the identified active ingredients. We expect this will be the key direction of future research. Thirdly, systematic data on pharmacokinetics and clinical studies of A. tatarinowii are limited, and there are few studies on target organ toxicity. We should conduct more clinical studies to evaluate possible therapeutic effects and investigate the side effects and toxicity of A. tatarinowii . The toxic effect of asarone in A. tatarinowii may limit its therapeutic effect. Toxicological studies have shown that α-asarone and β-asarone in A. tatarinowii can cause hepatomas, which may have mutagenic, genotoxic, and teratogenic effects. It has been reported that β-asarone is more toxic than α-asarone. In a study involving the human body, several consumers experienced persistent vomiting due to long-term intake of A. tatarinowii containing high concentrations of asarone. In addition, asarone also showed cytotoxic and genotoxic effects on HepG2 cells. Due to the potential toxic effects of asarone, in particular β-asarone, the European Council has limited the content of β-asarone in alcoholic beverages and condiments to 1 mg/kg and in other foods and beverages to 0.1 mg/kg. Based on the existing literature, further dose-dependent in vivo studies are needed to confirm the mutagenicity, genotoxicity, and teratogenicity associated with α-asarone and β-asarone. In addition, it is speculated that the epoxide metabolites of α-asarone and β-asarone may be the cause of these toxicities. Importantly, considering the toxicity of α-asarone and β-asarone, the clinical use of these compounds carries certain risks. On the other hand, other compounds such as sesquiterpene Acorusin E and indole alkaloids in A. tatarinowii have also been reported to have potential toxicity. Studies have shown that high doses of Acorusin E in A. tatarinowii may inhibit the central nervous system. Secondly, long-term or high-dose intake of indole alkaloids in A. tatarinowii may have some adverse effects on the human body, causing nausea, vomiting, dizziness, diarrhea, and other symptoms. In addition, indole alkaloids may also have effects on the cardiovascular system, such as arrhythmia and blood pressure changes . Therefore, it is necessary to be cautious in determining the human administration regimen of A. tatarinowii to avoid toxicity and protect human health. Further research may focus on the pharmacodynamic material relationship, pharmacokinetics, clinical research, and toxicological evaluation of A. tatarinowii . At the same time, A. tatarinowii has potential as a nutritional supplement that promotes health. As people are increasingly conscious of their well-being, there is a growing demand for edible Chinese medicines that offer health benefits. Thus, further studies should be conducted on A. tatarinowii health products to explore their potential for future development. The premise of in-depth development and utilization of natural plant resources may be evaluating and controlling their quality. However, there are still some shortcomings in the quality control of A. tatarinowii . Nowadays, A. tatarinowii on the market is easy to confuse with Anemone altaica Fisch. Fortunately, they belong to different families of plants or are easy to distinguish. In addition, since the TCM composition and pharmacological effects are usually complex, for their quality control, single components and multiple components may be utilized to assess the quality of a specific TCM, especially the chemical components related to its efficacy. The study of the pharmacodynamic material basis of A. tatarinowii mostly focuses on the study of its volatile components. According to the latest edition of the pharmacopeia (2020), the volatile oil content in the chemical composition of A. tatarinowii should not be less than 1.0% (mL/g), and the volatile oil in the Chinese herbal pieces should not be less than 0.7% (mL/g) . However, the volatile oil components of A. tatarinowii are mixtures and unstable. With further in-depth research on A. tatarinowii , certain unique components of A. tatarinowii, such as phenylpropanoids and lignans, can be selected as its quality markers . This will provide a solid foundation for scientifically developing and utilizing more A. tatarinowii plant resources. This will also help to protect people’s health and safety better. Therefore, it is necessary to develop new and effective analytical methods and techniques to identify multiple components to achieve more comprehensive quality control of A. tatarinowii . In summary, A. tatarinowii is an important medicinal plant and a source of phytochemicals with extensive pharmacological activities and high application value in all respects. However, further comprehensive and in-depth clinical studies are required to determine the safety and availability of A. tatarinowii for clinical utility. Until now, many compounds from A. tatarinowii have been found, but further research needs be conducted to provide a more thorough characterization. In the future, the structure–activity relationship and mechanistic action of isolated compounds should be studied to explore their potency and drug-like properties. The present paper systematically reviews the botany, traditional uses, phytochemistry, and pharmacology of A. tatarinowii . We aimed to provide the groundwork for further research on its mechanism of action and the development of improved therapeutic agents using A. tatarinowii in the future. Furthermore, we hope this review highlights the importance of A. tatarinowii and provides useful directions for the future development of this natural medicinal plant. |
Banff 2019 Meeting Report: Molecular diagnostics in solid organ transplantation–Consensus for the Banff Human Organ Transplant (B‐HOT) gene panel and open source multicenter validation | bd25df73-89af-40e6-b731-be0118d2e89b | 7496585 | Pathology[mh] | INTRODUCTION The XV Banff Conference for Allograft Pathology was held on September 23‐27, 2019, in Pittsburgh,Pennsylvania. One main topic, continuing a theme from two previous Banff meetings, was to include applications of molecular techniques for transplant biopsies and to articulate a roadmap for the clinical adoption of molecular transplant diagnostics for allograft biopsies. This meeting report summarizes the progress made by the Banff Molecular Diagnostics Working Group (MDWG) and the resulting next steps from the 2019 conference. CHALLENGES IN MOLECULAR TRANSPLANT DIAGNOSTICS The MDWG identified several challenges in the clinical application of molecular diagnostics. Different assays that measure different sets of genes validated for slightly different clinical contexts create a major analytical challenge. Enrolling patients into multicenter molecular diagnostic trials becomes problematic if local molecular diagnostic tests and risk stratification are done by noncomparable assays. The lack of a diagnostic gold standard for clinical validation of new molecular diagnostics requires multicenter standardization and independent validation in prospective randomized trials. Clinical and pathologic indications for molecular testing need to be defined and validated. Molecular tests must be cost effective to increase diagnostic utility beyond histopathology. For useful molecular diagnostics turnaround time needs to match immediate clinical needs. The integration of molecular tests with other diagnostic and clinical information requires standardization to make diagnosis and risk stratification comparable between centers. Industry partnerships are needed to advance the field, but transparency and appropriate disclosure of potential conflicts of interest are paramount. The MDWG believes that the present report shows a pathway that can address many of these issues. EVOLUTION OF MOLECULAR TRANSPLANT DIAGNOSTICS Over the past 20 years, we estimate that more than 4000 organ transplant biopsies have been studied by whole transcriptome microarrays. These have been conducted independently by several research groups, covering transplant biopsies of kidneys , , , , and, to a lesser extent, other organs. , , , , , Different analytical approaches addressing relevant research questions from these data have been made available and reproduced by several research groups and transplant centers, covering a broad spectrum of phenotypes and patient demographics. These studies led to potential diagnostic applications as well as major novel mechanistic insights with changes to the Banff classification, for example, the adoption of C4d‐negative antibody‐mediated rejection (ABMR) and chronic‐active T cell–mediated rejection (TCMR) as new diagnostic categories. , , Using transcriptome arrays the molecular phenotype in renal allografts correlates well with relevant rejection clinical entities and phenotypes. , In liver transplantation, microarray studies confirmed that liver biopsies with TCMR share very similar transcriptional phenotypes with those in renal allograft biopsies. , Transcriptional similarities are also present in heart and lung allograft biopsies. , , , These publications show that groups of genes within certain molecular pathways are statistically significantly associated with specific Banff histological lesions, rejection phenotypes, and Banff diagnostic categories. Transcript analysis also reveals potentially important underlying heterogeneities not perceived by pathology alone within diagnostic groups. In 2013 molecular diagnostics were added as an aspirational goal to the Banff classification. The molecular quantification of endothelial cell associated transcripts and classifier‐based prediction of donor specific antibody‐mediated tissue injury were adopted as diagnostic features/lesions equivalent to C4d for the diagnosis of ABMR. This was noted to be a forward‐looking proposal at the time, because there was no consensus around which endothelial genes should be quantified and no independent multi‐institutional validation for any diagnostic classifier or gene set. The main impetus in 2013 to adopt a molecular diagnostic option into the classification, despite these limitations, was to set the future direction for the Banff classification and to promote collaborative and multi‐institutional, open source efforts to advance the field by validating, standardizing, and making molecular transplant diagnostics accessible to the broad transplant community. This is a foundational value of the Banff consortium. At the 2015 meeting, the Banff MDWG recommended the creation of molecular consensus gene sets as classifiers derived from the overlap between published and reproduced gene lists that associate with the main clinical phenotypes of TCMR and ABMR. Similar roadmaps and processes for clinical adoption have been reviewed extensively and proposed by other key opinion leaders in the field. , , , Collaborative multicenter studies were proposed to close identified knowledge gaps and enable practical molecular diagnostic incorporation into diagnostic classifications. The 2017 Banff meeting identified an initial validated, consensus gene list with potential specific indications for molecular testing. Importantly presented at this meeting was a new technology, Nanostring, which uses robust multiplex transcript quantitation from formalin‐fixed, paraffin‐embedded (FFPE) biopsies. The compelling advantage of NanoString is that it performs transcriptional analysis on routine histological samples allowing correlation of both histologic with molecular phenotypes on the same tissue. CURRENT STATE OF MOLECULAR TRANSPLANT DIAGNOSTICS Most of the published research studies for molecular testing on biopsies has been performed using microarrays on an extra biopsy core stored in RNAlater Stabilization Solution. The pioneering work by Halloran and colleagues was the basis of a commercial test (Molecular Microscope MMDx) now offered by One Lambda Inc. , , , These insightful, prospective studies showed strong associations of transcript patterns with the histological Banff lesions and diagnosis but also identified discrepancies. These discrepancies require further investigation to reveal the optimal integration of histology and molecular biopsy features that are informative of outcome and response to therapy. No prospective randomized outcome trial using microarray assays as the end point has been conducted, in part because of the technical challenges and the long follow‐up required. Although microarray analysis is the most established method for biopsies, alternative approaches, less invasive than a biopsy, are attractive and under investigation, such as urine and blood transcript analysis. Recently, more practical technologies based on FFPE biopsy analysis are now available, in particular the NanoString nCounter system (NanoString Technologies, Seattle, WA). Several NanoString publications using FFPE transplant specimens identify similar transcript associations with the molecular and histologic phenotypes as those reported in microarray studies. , , , , , , , , , , , , , , Among the advantages of NanoString are (1) a separate core processed at the time of biopsy is not required; (2) transcripts are assessed in the same sample analyzed by light microscopy; and (3) large retrospective and longitudinal analyses of archived samples can be readily performed in the setting of multicenter studies, which will enable retrospective randomization with long‐term survival end points available (Table ). Over 1000 publications have reported its application and value. The NanoString system yields comparable results between FFPE and fresh frozen samples, with a higher sensitivity than that of microarrays and about equal to reverse transcription polymerase chain reaction (RT‐PCR). , , This technology in one assay uses color‐coded molecular barcodes that can hybridize directly up to 800 different targets with highly reproducibility. NanoString thereby closes a gap between genome‐wide expression (ie, microarrays and RNA sequencing as whole transcriptome discovery platforms) and mRNA expression profiling of a single target (ie, RT‐PCR). But unlike quantitative RT‐PCR, the NanoString system does not require enzymes and uses a single reaction per sample regardless of the level of multiplexing. Thus, it is simpler for the user and requires less sample per experiment for multiplex experiments, for example, pathway analysis, assessment of biomarker panels, or assessment of custom‐made gene sets. The NanoString system is approved for clinical diagnostics and paired with user‐friendly analytical software, thus representing a simple, relatively fast (24‐hour turnaround time), automated platform that is well poised for integration into the routine diagnostic workflows in existing pathology laboratories. Synthetic DNA standard oligonucleotides, corresponding to each target probe in the panel, allow normalization of expression results between different reagent batches, platforms, and users, This permits standardization of diagnostic thresholds across multiple laboratories, a major challenge using microarrays and RNA sequencing. A major disadvantage of the NanoString approach is the need to predefine the gene panel and the restriction to 800 probes, making it better for follow‐up studies once the discovery phase with microarrays has winnowed the possibilities to the most informative transcripts. The other disadvantages, shared with microarrays and RNASeq, is the loss of anatomic localization and the need for a biopsy. GENERATION OF A BANFF HUMAN ORGAN TRANSPLANT (B‐HOT) PANEL The B‐HOT panel includes the validated genes found informative from major peer reviewed microarray and NanoString studies on kidney, heart, lung, and liver allograft biopsies, identified by the MDWG through literature review. A list of the genes with corresponding key publications is given in the Data . In detail, candidate genes were identified using the key words “transplantation,” “kidney, “heart, ” “lung, ” ‘liver, ” “gene expression, ” “molecule, ” and “transcripts. ” Mining these publications for genes listed as significantly associated with any study variable revealed 2521 publications indexed in PubMed concerning more than 4000 genes. After redundant and duplicate genes were removed, the list contained 1749 genes. Then the MDWG members identified overlap between these genes and genes described in the peer‐reviewed literature , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , as being strongly associated with relevant clinical phenotypes and identified 1050 genes to be considered for inclusion. In the next step, a list including all genes with consensus expert opinion were selected and for which all Hugo duplicates were then combined, leaving 670 unique genes. We initiated discussions with NanoString and learned they would be willing to make our panel widely available. However, their commercial panels typically have 770 genes, so they provided suggestions for addition genes to delineate relevant cellular pathways and cell types that have been used in other panels. Using an independent data‐driven process, NanoString Technologies Inc recommended additional genes within relevant molecular pathways related to the 670 genes that were most informative by their Ingenuity Pathways. The final B‐HOT panel included 758 genes covering the most pertinent genes from the core pathways and processes related to host responses to rejection of transplanted tissue, tolerance, drug‐induced toxicity, transplantation‐associated viral infections (BK polyomavirus, cytomegalovirus, Epstein‐Barr virus) plus 12 internal reference genes for quality control and normalization (Figures and , Table ).Through that approach the B‐HOT gene panel was defined, further engineered, and made commercially available ( https://www.NanoString.com/products/gene‐expression‐panels/gene‐expression‐panels‐overview/human‐organ‐transplant‐panel ). The pathways added to the list are given in Figure and in more detail in the Table . The panel probes were also designed to cover different organ types for transplantation and for sequence homology with nonhuman primates to facilitate preclinical research applications. The panel's broad coverage of inflammatory, adaptive, and innate immune systems; signaling; and endothelial transcripts will likely be largely applicable across organ types but with some expected organ specific variation. Furthermore, parenchymal transcripts will often be organ specific and many have been included (see Table ). We anticipate that continued discovery of other informative transcripts not included in the B‐HOT panel will occur. To provide flexibility, up to 30 custom genes can be added to the B‐HOT panel by an investigator. Although the panel has been commercialized for the nCounter platform, the gene list is not proprietary and probes based on the gene list can be designed to run on any transcript analytical platform. NEXT STEPS: MULTICENTER ANALYTICAL AND CLINICAL VALIDATION The Banff MDWG formed a voluntary, growing, and open international consortium, independent of commercial sponsorship, to develop future steps for validation, analyses, and database sharing. The focus of the next 2 years will be validation of the panel and discovery of the optimal algorithms and gene sets. This will be enabled by (1) the B‐HOT panel and its comprehensive probe standards for comparison between laboratories, batches, and runs; (2) a shared database containing clinical, laboratory, pathological and transcript data; and (3) access to comprehensive sophisticated bioinformatics. The next steps will be to document the analytical validity across laboratories and then determine the clinical validity. The clinical validity will be assessed by analyzing B‐HOT transcripts in 1000 or more clinical biopsies (as of this report the consortium has run the B‐HOT panel on over 600 samples). These results along with standardized clinical and pathologic information will be entered in a shared database, which will be interrogated to discover the most useful algorithms for clinical applications. Analytical validation for regulatory approval must document accuracy, precision, analytical sensitivity (reproducibility, coefficient of variance), reportable ranges, reference interval values, and analytical specificity. Calibration and control procedures must be determined, and the laboratory must be enrolled in external proficiency testing programs. Clinical validation is the next step. Even an assay with perfect analytical validity does not automatically imply association between the test result and a relevant clinical outcome or action. This requires access to relevant patient populations’ material of adequately powered sample size to evaluate assay performance in a real‐world clinical setting. Accordingly, clinical utility of an assay needs to be established by providing evidence of improved, measurable clinical outcome or benefit that is directly related to the use of the test, that is, proof that the test adds significant value to patient care. This also needs to take into consideration how the assay is interpreted, reported, and applied in the context of clinical patient management. Ideally, proper evaluation of an assay's clinical utility requires prospective randomized control trials. The B‐HOT panel will undergo all of these validation steps. In the next 2 years retrospective, well‐annotated cohorts will be analyzed for analytical and clinical validation. The MDWG is aligning joint efforts using available NanoString systems at participating centers for studying a broad spectrum of archived and well‐annotated transplant biopsies. To centralize the resulting multicenter molecular data from archived transplant biopsies together with the related clinical and outcome data, algorithms, and tools for analysis (including explorative analytics, machine learning‐based diagnostic approaches/classifiers, and risk prediction tools) with remote access by users across the world, a data integration platform (DIP) will be built (Figure ). Participating centers will be able to upload routinely collected transplant‐related patient data in an anonymized and uniform fashion. A participating investigator will then be able to use all data in the DIP. Currently underway is the development of a consensus data template representing the variables and units to be included in the DIP. The NanoString data files also include important analytical parameters (quality control measures, background subtractions, normalization values) in addition to the individual gene expression values, which will also be part of the DIP to allow for standardization across laboratories and thus multicenter analytical validation of any diagnostic assays. The output of this effort is expected to be a robust well‐characterized gene set (presumably a subset of the B‐HOT panel or additional genes) and analytic methodology for interpretation, which will be presented at a subsequent Banff meeting and published. We expect to see correlations with histologic diagnosis (including interpretations not revealed by routine pathology analysis), ongoing immunosuppressive therapy, prediction of outcome, and response to treatment. We (and others, we hope) will follow this by prospective, controlled clinical trials to fully define clinical utility. As a first evaluation, after the Banff meeting, a member of the MDWG, Neal Smith, performed an in silico assessment of the B‐HOT panel genes using the archived Genomic Spatial Event databases from Halloran's group , , that contains 764 kidney biopsy samples with microarray data and diagnostic classification as TCMR, chronic‐active ABMR, mixed, acute kidney injury, no rejection, and normal. Briefly, 3 bioinformatics methods were used to see if they could identify the 6 diagnostic groups from the transcripts: (1) supervised, using diagnostic and pathogenesis based transcripts sets of Halloran; (2) semisupervised, using Nanostring pathways (Data ) plus CIBERSORT cells types; and (3) unsupervised principal component analysis. Results confirmed the correlation of expected gene sets in each analysis with the 6 diagnostic categories (Smith, manuscript in preparation). A description of the initial B‐HOT results in kidney transplants to be presented at the 2020 American Transplant Conference reveals both expected and novel correlations with pathologic categories. The B‐HOT panel will be commercially available for research use only. Whether B‐HOT leads to a clinically indicated laboratory developed test remains to be seen. If it does, it will probably be a simplified panel. In the future, the international, open source, multicenter Banff DIP can serve as a reference point for generating a molecular diagnostic “gold‐standard” in transplantation, similar to the Banff histology lesions and diagnoses agreed upon in 1991. As the Banff consensus rules for histology underwent refinement over the last 28 years as new knowledge emerged, any molecular “consensus” will also need to undergo constant refinement and, no doubt further, technological innovation. Only through integration with clinical decision‐making and end points in clinical trials can the true clinical utility of molecular diagnostics be demonstrated. The authors of this manuscript have conflicts of interest to disclose as described by the American Journal of Transplantation . Michael Mengel received honoraria from Novartis, CSL Behring, Vitaeris. Mark Haas received consulting fees from Shire ViroPharma, AstraZeneca, Novartis, and CareDx, and honoraria from CareDx. Robert Colvin is a consultant for Shire ViroPharma, CSL Behring, Alexion and eGenesis. Candice Roufosse has received consulting fees from Achillion and UCB. Ivy Rosales is a consultant for eGenesis. Enver Akalin received honorarium and research grant support from CareDx. Marian Clahsen‐van Groningen received grant support from Astellas Pharma (paid to the Erasmus MC). A. Jake Demetris receives research support from Q2 Solutions and is a member of an Adjudication Committee for Novartis. None of these conflicts are relevant to this article. The other authors have no conflicts of interest to disclose. None of the authors has a financial interest in NanoString. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. |
Association between local spatial accessibility of dental care services and dental care quality | af3ee2e5-4040-49a7-9013-8bb10983f29e | 8600821 | Dental[mh] | Oral care is an important public health issue. In most countries, especially in developing countries, there are not enough dental resources. Even in developed countries, the dental-to-population ratios have inequalities in different regions, and this is especially a concern among deprived communities, certain ethnic minorities, and disabled individuals . For example, the density of dentists in 2019 based on American Dental Association Health Policy Institute data varied by state. The highest density was 104 dentists per 100,000 population in the district of Columbia, and the lowest was 40.97 in Alabama . Heterogeneity of dental resources has been widely found, with differences between rural and urban areas and across countries. Similarly, Taiwan’s medical resources are distributed unevenly; most are in high-population-density and urban areas and less are in remote areas such as mountainous and hilly regions, which account for over two-thirds of the nation’s land area . Inconvenient traffic transportation, inadequate medical equipment and insufficient medical personnel in remote areas cause low medical accessibility . In the eastern region of Taiwan, Hualien city, located on flatlands, is the most densely populated area in Hualien county, and has more medical resources than other townships. According to 2018 Hualien county statistics, the ratio of dentists per 10,000 population was 9.91 in Hualien city and only 0.62 in Xiulin township, a mountain indigenous township . The report also showed that most medical resources are concentrated on the plains, and there is a lack of resources in mountainous townships and coastal areas. There are several factors affecting dentists’ choice of location for their practice and causing uneven distribution of dental resources. First, variation in both the awareness of oral health and knowledge of the importance of dental care cause different degrees of demand for dental services. Second, the ability to pay for services is different, especially for the poor, minorities, uninsured people and people with relatively poor health . Third, if dentists practice in remote areas, it may increase their workload and difficulty in recruiting staff . Uneven distribution of dental resources affects the timing of receiving dental treatment and transportation time to dental facilities. For example, people in remote areas of Hualien county spend an average of 16 min to arrive at the nearest medical institution (standard error: 33.3 min), and people in the villages of Hualien county spend an average of 7 min (standard error: 7.6 min) . More people in remote areas expressed that seeking medical service was inconvenient . In a study exploring the effects of distance to dentists on children’s dental service usage, increased distance of 3.3 miles reduced having comprehensive oral exams by about 6% . Moreover, unevenness of medical resources influences residents’ health status and induces health disparities. In remote areas, it is difficult to accumulate health capital due to resource accessibility, transportation costs and travel time . Many medical accessibility definitions have been proposed, among which Penchansky and Thomas divided accessibility into five domains, including availability, accessibility, accommodation, acceptability and affordability. The first two are related to spatial factors, which are the type and quantity of medical resources within a specific space and the convenience of transportation including transportation time, distance and cost. Others are related to demographic characteristics, healthcare needs, socioeconomic status and cultural differences. Many methods for measuring potential resource accessibility have been used, including calculating the nearest or average distance, dentist-to-population ratio, and the two-step floating catchment area (2SFCA) method . Luo and Wang proposed the 2SFCA method in 2003 and used two catchments to evaluate resource usage . This method deals with the limitation of searching for medical resources only within administrative boundaries, because people may seek medical services across boundaries within a manageable distance. Previous studies have explored dental resources distribution by dentist-to-population ratio . To our knowledge, few studies have applied the 2SFCA method to analyze access to dentists. Moreover, caries prevention , periodontal care and tooth restoration longevity may be used as markers of quality in dentistry. No prior research has explored whether dental care quality differs between areas with adequate versus deficient dental resources. The aim of this study was to use 2SFCA to explore dental resource accessibility, the spatiotemporal distribution of dental care quality, and the association between resource-deficient areas and dental care quality .
Data resources Mid-year population data at the village level from 2012 to 2019 were downloaded from socio-economic databases maintained by the Ministry of the Interior, Taiwan ( https://segis.moi.gov.tw/STAT/Web/Portal/STAT_PortalHome.aspx ). Medical institutions and personnel statistical data obtained from an open data platform in Taiwan ( https://data.gov.tw/ ) were used to geocode the location of the dentists’ practice addresses. A caries experience index (decayed, missing, and filled teeth, DMFT index) was obtained from an investigation on the oral hygiene and status of children and adolescents six to 18 years old in Taiwan between 2009 and 2011 . The index was used as an indicator of oral status in each county. The caries experience index is the sum of the total number of caries, teeth extracted due to caries, and teeth filled. Three quality indexes including dental filling preservation rate (within 2 years), calculus removal rate (13 years old or older) and fluoride service rate (under 6 years old) were captured from the National Health Insurance open data platform ( https://data.nhi.gov.tw/Index.aspx ) between 2012 and 2018 and the first to third quarters in 2019. According to an official quality index definition and value for inference , the dental filling preservation rate (within 2 years) is the proportion of not repeating filling of the same tooth in the same dental facility in 2 years for a specific period. When dental fillings remain intact for more than 2 years, it is likely to be partly due to the choice of filling materials and correct and skilled operation . The calculus removal rate (13 years old or older) is the proportion of 13-year-old or older patients receiving full mouth cleaning with ultrasonic scaling for a specific period. The calculus removal rate reflects the dentists performing periodontal disease care and regular full-mouth scaling . The fluoride service rate (under 6 years old) is the proportion of performing oral preventive and care services for a specific period. Children receive dental facility or community tour service once every 6 months by using national health insurance. Children from low-income households, indigenous and remote areas or those with physical and mental disabilities can receive fluoride service every 3 months. The fluoride service rate reflects parents’ attitude and cognition, children’s cooperation, and willingness of the dentist practice. Fluoride service can prevent primary tooth decay and make up for unskilled tooth brushing by children . The urbanization degree of 359 townships in Taiwan is classified into seven types, including highly urban, moderately urban, emerging, general, aging, agriculture town and remote township, as proposed by Liu et al. . Travel time to the closest provider In previous studies, the average weighted medical service distance was 10 km in highly urban, moderately urban and emerging towns in Taiwan . Overall, the average weighted medical service distance was 17.68 km. Considering that the average road speed limit is 60 km/h , we set 10 min as the threshold to evaluate the spatial accessibility. Dental resource accessibility analysis: two-step floating catchment area In the first step, we set a 10-min catchment area around each dental facility using OpenStreetMap as a base map, identified all the population within each catchment, and calculated supply-to-demand ratios for each dental facility with QGIS 3.4.7 and ORS Tools (Version 1.2.3) . In the second step, we summed supply-to-demand ratios in each catchment around the geographical centroid of each village. The sum of supply-to-demand ratios for each village was its accessibility score. The data sources mentioned above are listed in the Additional file . Provider to population ratios It has been suggested that one dentist serves 2000 people per year, and areas with one dentist for 4000 people or more per year are defined as dental-resource-deficient areas . After converting the above dentist service quantity to spatial accessibility, we see that a person can make 0.0005 dentist service trips and 0.00025 dentist service trips per year in normal and dental-resource-deficient areas respectively. Statistical analysis We visualized the dental resources accessibility at the village level and three dental care quality indexes at the township level, and defined deficient townships based on two accessibility scores, 0.0005 and 0.00025. The temporal trends of the three dental care quality indexes were plotted by box plot and also stratified by the urbanization degree at the township level. Local indicators of spatial association (LISA) were applied to measure spatial dependence and evaluate localized spatial clusters of dental resources and three dental care quality indexes using a QGIS Spatial Autocorrelation Map . Because of adjacency spatial dependency, a spatial error model with rook contiguity was used to explore the association between dental resource accessibility and dental care quality after adjusting for the DMFT index at the county level in 2012. All analyses used QGIS 3.4.7, GeoDa (subversion 1.14.0), SAS (version 9.4) and RStudio (Version 1.0.153), and all statistical tests were two-sided with a significance level of 0.05.
Mid-year population data at the village level from 2012 to 2019 were downloaded from socio-economic databases maintained by the Ministry of the Interior, Taiwan ( https://segis.moi.gov.tw/STAT/Web/Portal/STAT_PortalHome.aspx ). Medical institutions and personnel statistical data obtained from an open data platform in Taiwan ( https://data.gov.tw/ ) were used to geocode the location of the dentists’ practice addresses. A caries experience index (decayed, missing, and filled teeth, DMFT index) was obtained from an investigation on the oral hygiene and status of children and adolescents six to 18 years old in Taiwan between 2009 and 2011 . The index was used as an indicator of oral status in each county. The caries experience index is the sum of the total number of caries, teeth extracted due to caries, and teeth filled. Three quality indexes including dental filling preservation rate (within 2 years), calculus removal rate (13 years old or older) and fluoride service rate (under 6 years old) were captured from the National Health Insurance open data platform ( https://data.nhi.gov.tw/Index.aspx ) between 2012 and 2018 and the first to third quarters in 2019. According to an official quality index definition and value for inference , the dental filling preservation rate (within 2 years) is the proportion of not repeating filling of the same tooth in the same dental facility in 2 years for a specific period. When dental fillings remain intact for more than 2 years, it is likely to be partly due to the choice of filling materials and correct and skilled operation . The calculus removal rate (13 years old or older) is the proportion of 13-year-old or older patients receiving full mouth cleaning with ultrasonic scaling for a specific period. The calculus removal rate reflects the dentists performing periodontal disease care and regular full-mouth scaling . The fluoride service rate (under 6 years old) is the proportion of performing oral preventive and care services for a specific period. Children receive dental facility or community tour service once every 6 months by using national health insurance. Children from low-income households, indigenous and remote areas or those with physical and mental disabilities can receive fluoride service every 3 months. The fluoride service rate reflects parents’ attitude and cognition, children’s cooperation, and willingness of the dentist practice. Fluoride service can prevent primary tooth decay and make up for unskilled tooth brushing by children . The urbanization degree of 359 townships in Taiwan is classified into seven types, including highly urban, moderately urban, emerging, general, aging, agriculture town and remote township, as proposed by Liu et al. .
In previous studies, the average weighted medical service distance was 10 km in highly urban, moderately urban and emerging towns in Taiwan . Overall, the average weighted medical service distance was 17.68 km. Considering that the average road speed limit is 60 km/h , we set 10 min as the threshold to evaluate the spatial accessibility.
In the first step, we set a 10-min catchment area around each dental facility using OpenStreetMap as a base map, identified all the population within each catchment, and calculated supply-to-demand ratios for each dental facility with QGIS 3.4.7 and ORS Tools (Version 1.2.3) . In the second step, we summed supply-to-demand ratios in each catchment around the geographical centroid of each village. The sum of supply-to-demand ratios for each village was its accessibility score. The data sources mentioned above are listed in the Additional file .
It has been suggested that one dentist serves 2000 people per year, and areas with one dentist for 4000 people or more per year are defined as dental-resource-deficient areas . After converting the above dentist service quantity to spatial accessibility, we see that a person can make 0.0005 dentist service trips and 0.00025 dentist service trips per year in normal and dental-resource-deficient areas respectively.
We visualized the dental resources accessibility at the village level and three dental care quality indexes at the township level, and defined deficient townships based on two accessibility scores, 0.0005 and 0.00025. The temporal trends of the three dental care quality indexes were plotted by box plot and also stratified by the urbanization degree at the township level. Local indicators of spatial association (LISA) were applied to measure spatial dependence and evaluate localized spatial clusters of dental resources and three dental care quality indexes using a QGIS Spatial Autocorrelation Map . Because of adjacency spatial dependency, a spatial error model with rook contiguity was used to explore the association between dental resource accessibility and dental care quality after adjusting for the DMFT index at the county level in 2012. All analyses used QGIS 3.4.7, GeoDa (subversion 1.14.0), SAS (version 9.4) and RStudio (Version 1.0.153), and all statistical tests were two-sided with a significance level of 0.05.
This study involved 7604 villages on the main island of Taiwan. The villages located on the western coast, and in eastern Taiwan and the mountainous areas had low accessibility, shown in blue (Fig. a). The red areas indicate the places with sufficient resources, most of which were concentrated in metropolitan areas such as Taipei City, New Taipei City, Taichung City, Tainan City and Kaohsiung City. Corresponding to the level of urbanization of each township, resources were concentrated in the west, especially in the western metropolitan areas, and the areas with low accessibility of dental service were mostly in aging, agricultural and remote towns (Table ). The ratios of the population to the dentists were also inversely correlated with the spatial accessibility. LISA found spatial clusters, which revealed hot spots (high–high), defined as areas with a lot of dental resources whose neighbors have the same phenomenon. These hot spots were concentrated in the western metropolitan areas, and the cold spots were scattered around the western coast, the east and the surrounding mountains (Fig. a). The thresholds of accessibility scores were 0.0005 and 0.00025 (Fig. b) at the township level, respectively. In other words, the dentist-to-population ratios were 1:2000 and 1:4000, and the former cutoff point covered more deficient areas. In the 352 towns, dental-resource-deficient areas accounted for 4.5% (n = 16) under the 0.00025 threshold and were concentrated in the mountainous areas and the east. Villages were divided into four groups by quartiles, with a fifth group being those completely lacking dental resources (Table ). 267 villages had no dentist within 10 min’ driving distance and contained 250,906 persons (accounting for 1.08% of the total population). 1834 villages with low accessibility (0 < R ≦ 0.00851) included 3,006,980 people (accounting for 12.89% of the total population). The areas with the second lowest accessibility (0.00851 < R ≦ 0.01433) included 1840 villages, with 4,469,234 people (19.15% of the total population). The slightly higher accessibility (0.01433 < R ≦ 0.02077) covered 1831 villages and included 6,849,317 people (accounting for 29.35% of the total population). In addition, there were 1832 villages with high accessibility (0.02077 < R) including population of 8,756,947 (maximum percentage of total population: 37.53%). Low proportions of fluoride service (for children under 6 years old) were concentrated on the northeast coast and sporadic areas of the central western plains, especially in areas where the urbanization levels were aging, agricultural and remote townships. The hot zones of spatial clusters were concentrated in the north, southwest and east, while the cold zones were in the northeast coast, and on the western plain with its ageing, agricultural and remote townships, and the southern coast (Fig. a). The proportion of calculus removal (13-year-olds or older) was higher on the sporadic western plains and in the east, and lower in the sporadic middle part of the west, southeast and mountainous areas. The hot zones were in the northeast and western plains, especially in the metropolitan areas, and the cold zones were concentrated in the middle and southern parts of mountainous areas and the northern coast (Fig. b). The proportion of dental filling preservation (within 2 years) accounted for more than 95% of filled teeth in all counties. The places with lower refilling rates were in the north and central parts of Taiwan. The hot zones of spatial autocorrelation distribution were in the north and middle parts of the west, and the cold zones were in the east and the sporadic regions of the south (Fig. c). Performing fluoride service (for children under 6 years old) increased year by year from 2012 to 2019, and the median value in 2019 was 42.86% (interquartile range, IQR = 39.91). The rate of calculus removal (13 years old or older) and dental filling preservation rate (within 2 years) had little difference over time. The former had a median index of 54.52% in 2019 (IQR = 16.25%), and the latter had a median index of 99.90% in 2019 (IQR = 0.33%) (Fig. ). Fluoride service (under 6 years old) increased year by year from 2012 to 2019 in highly urban, moderately urban, emerging and general towns. But in aging, agricultural and remote townships the fluoride implementation rate fluctuated with time (Fig. ). The rate of calculus removal (13 years old or older) and dental filling preservation rate (within 2 years) had no particular change over time for different urbanization levels, except for the aging towns, which showed a slight fluctuation (Figs. , ). The rates of fluoride service (under 6 years old) and calculus removal (13 years old or older) in general, aging, agricultural and remote townships were lower than those in highly urban, moderately urban and emerging towns. The dental filling preservation rate (within 2 years) was more than 95% across different urbanization levels, and the difference in each urbanization level was small. In the spatial error model, regarding the fluoride service (for those under 6 years old), the dental service accessibility (coefficient = 7.17E−05, p value = 0.002) and the caries experience index (coefficient = −3.73, p value ≤ 0.0001) were significant. The model interpretation power (R-square) was 0.665, with spatial dependence ( p value = 0.023). Regarding calculus removal rate, the dental service accessibility (coefficient = 1.10E−04, p value = 0.004) was significant, and the model's explanatory power was 0.345, but there was no spatial dependence ( p value = 0.158). Regarding the dental filling preservation rate (within 2 years), the dental service accessibility (coefficient = −3.01E−07, p value = 0.679) and the caries experience index (coefficient = −0.0008, p value = 0.972) were not significant, but there was spatial dependence ( p value = 0.045). The model's explanatory power was 0.278 (Table ).
In the traditional approach, the dentist-to-population ratio was calculated by fixed administrative boundaries and couldn’t consider spatial heterogeneity. Our study used the road network and 2SFCA to compute the accessibility of dental resources while overcoming the difficulty of cross-boundary accessibility estimation. In addition, the usage of dental facility addresses was more accurate to reflect the supply of dental resources. For example, medical services are more likely to concentrate in the busy section of district, and the dentist-to-population ratio can’t represent this feature. We used spatial autocorrelation analysis to reveal clusters, helping us understand dental resource distribution at the village level. The results can help government to target insufficient resources areas, provide corresponding dental resources, effectively establish and integrate a reasonable system, and reduce health inequality [ , , ]. Lower accessibility of dental resources and a lower dental care quality index were mostly associated with remote, agricultural or aging towns with spatial clustering. Even distribution of the dental resources can elevate the usage of dental service in remote areas. In a cross-sectional study, which used Washington State Medicaid Program data in 2012, the proportion of Medicaid-enrolled children who utilized preventive dental care significantly increased by 1.67 percent as the ratio of pediatric dentists per 10,000 children in a county increased, after adjusting both for regionality and for the age of access to a baby and child dental program which was a special Medicaid access program to improve the oral health of those under age 6 years . One study which enrolled children between 2000 and 2009 from Iowa Medicaid found that increased distance to the nearest dentist was associated with a decrease in comprehensive exams . Generally speaking, urban areas are more likely to have sufficient resources and high-quality service. In one study identifying the dentally underserved geographic areas in the US, dentally underserved areas had significantly lower population densities regardless of urbanization level . Dental care quality indexes have mostly risen or remained steady over time, and the indexes were relatively high in highly urban areas. There were some dental care quality indexes associated with accessibility such as rates of fluoride service (for those under 6 years old) and calculus removal (13 years old or older). The dental care quality as evaluated by a standard criterion allowed observation of the historical trends, comparison with other institutions in different regions, and an understanding of which types of quality needed to be improved. In this study, dental care quality indexes were calculated by health insurance claims data to represent the implementation of different treatments and preventive care in the different dental facilities. The health insurance claims data had expert review on medical care quality and expenses by the National Health Insurance Administration. There also exist other methods for measuring dental care quality. The Dental Quality Alliance, established by the American Dental Association, has developed standard and verifiable measurement , including oral care usage, oral care quality and cost to enhance oral health. Righolt et al. established a definition for quality of oral healthcare which comprises seven domains—patient safety, effectiveness, efficiency, patient centeredness, equitability, timeliness, and access to care . This quality measurement, with its more comprehensive definition, can be used for routine feedback of information on the quality and outcome of oral health care, and to promote quality improvement in oral health care . Preventive care of fluoride application for children under 6 years old should be performed once every 6 months. In remote areas where the population density is lower than one-fifth of the average population density, fluoride services can be conducted twice every 6 months. Fluoride community tour services are often performed in remote areas. For example, National Yang-Ming University Hospital in Taiwan regularly goes to remote areas in Nan'ao or Datong Township in Yilan County in northeastern Taiwan to offer fluoride application and caries prevention. Therefore, for these reasons, some remote areas have a high percentage of implementing preventive services. There are several methods to improve accessibility in dental-resource-deficient areas. First, financial incentives of low interest rates for loan repayment or tax breaks can be used for attracting dental facilities located in dental-resource-deficient areas. Improving quality of life to attract dentists to practice in rural areas may also help balance the urban–rural skew. Second, increasing the demand by educating the underserved population on the need to maintain oral health attracts dentists to provide care in underserved areas . Due to varying dentist working hours and specific services provided, the establishment of transparent service information may help residents search for the appropriate dental service. Third, implementing universal enrollment health insurance can help balance the geographic distribution of health providers, as confirmed in a previous study, in which implementing National Health Insurance improved the equality of dentist geographic distribution after controlling for the natural growth by the time trend in Taiwan . Moreover, cost-effective mobile and portable dental services can be made available in resource-scarce or naturally isolated areas to solve the disparity in accessibility . In terms of the research limitations of this study, first, the actual dentist practice time such as full time and part time was not considered. If a dental facility is closed when a patient needs treatment, the accessibility is reduced. Second, if a dentist is a specialist such as an orthodontist, she or he may not perform other treatment, and the accessibility of basic care will be overestimated. Third, the dental care quality index reflects the preventive and curative treatment performance, and other domains of dental care quality are not included in the national health insurance claims data. Furthermore, the dental filling preservation rate (within 2 years) cannot reflect a situation in which the same person has the same tooth filled in different dental facilities within 2 years, so the quality index value may be slightly higher.
In conclusion, regular monitoring of dental services accessibility can help policymakers and health services providers reallocate dental resources and balance resource distribution by encouraging dentists to practice in remote areas and to provide mobile dental health care.
Additional file 1: The summary of variables collected for dental resource accessibility analysis.
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Resveratrol-decreased hyperalgesia mediated by the P2X | 5d287887-f83c-4683-8880-557a013063fa | 5453631 | Physiology[mh] | Chronic pain is a common symptom in human immunodeficiency virus (HIV)-1 infection/acquired immunodeficiency syndrome (AIDS) patients. – The quality of life of HIV-1/AIDS patients with chronic pain is significantly decreased. To ascertain the pathogenic mechanism of HIV-associated pain, it is pivotal to identify the causative HIV-1 agents. Glycoprotein 120 (gp120) can cause axonal injury of sensory neurons in culture. , Gp120 is an HIV-1 protein that induces pain behaviors when introduced into animal models. , – Pain may arise from the direct effects of HIV on the peripheral nervous system. , The dorsal root ganglion (DRG) afferent fibers are distributed to both central and peripheral terminals and they transmit noxious stimuli from the periphery to the central nervous system. , Gp120 appears to bind to the surface of rat DRG neurons and may be causative factors in the generation of neuropathic pain in HIV-1-infected patients. , The HIV-1 gp120 level was significantly higher in “pain-positive” HIV-1 patients. , Therefore, preventing and treating HIV-1 gp120-associated neuropathic pain has become a heavily researched subject. Resveratrol (RES) is a natural polyphenolic compound found in peanuts, mulberries, grapes, and red wine. , RES exhibits anti-inflammatory and anti-nociceptive effects. – Adenosine triphosphate (ATP) is a signaling molecule in neuropathic and inflammatory pain. – Extracellular ATP can activate the ionotrophic P2X receptors in primary afferent fibers. – The P2X 7 receptor is involved in the induction and maintenance of neuropathic and inflammatory pain. , , The interaction between HIV-1 gp120 and macrophages stimulates increased ATP release and P2X receptors activated by ATP are required for HIV entry into macrophages. , ATP signaling via the P2X 7 receptor is related to the regulation of inflammatory responses during acute viral infection. The blocking of purinergic receptors results in a significant reduction in the HIV replication in macrophages. Therefore, the P2X 7 receptor may be involved in HIV-associated neuropathic pain. In this study, we investigated the effect of RES on gp120-induced neuropathic pain mediated by the P2X 7 receptor in rat DRGs.
Animals and surgical methods Adult (200–250 g) male Sprague–Dawley (SD) rats were used in all experiments and housed with an alternating 12-h light/dark cycle. They were provided with food and water ad libitum. The use of the animals was reviewed and approved by the Animal Care and Use Committee of Medical College of Nanchang University. The experiments were conducted under the guidelines of the NIH in the US regarding the care and use of animals for experimental procedures. The rats were randomly divided into the following three groups (with six rats in each group): the HIV-gp120 group (gp120 group); HIV-gp120 rats treated with RES group (gp120 + RES group); and sham operation group (sham group). A previously described technique was used for the perineural HIV-gp120 administration. Briefly, under 10% chloral hydrate anesthesia (3 ml/kg, i.p., supplemented as necessary) and aseptic surgical conditions, the left sciatic nerve of the SD rats was exposed in the popliteal fossa without damaging the nerve construction. A 2 × 6 mm strip of oxidized regenerated cellulose was previously soaked in 250 µl of a 0.1% rat serum albumin saline solution containing 200 ng of gp120 (Sigma) or 0.1% rat serum albumin in saline for the sham surgery. A 3–4 mm length of the sciatic nerve that was proximal to the trifurcation was wrapped loosely with the soaked cellulose, did not cause nerve constriction, and was left in situ. The incision was closed with 4/0 sutures. Beginning at 24 h after surgery, the rats in the gp120 + RES group were intraperitoneally treated with RES (30 mg/kg) daily for 14 days. Rats in the sham and gp120 groups were intraperitoneally injected with the same volume of normal saline. Measurement of the mechanical withdrawal threshold Determination of the mechanical withdrawal threshold (MWT) was performed at 9:00–12:00 using a BME-404 electronic mechanical stimulator (Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Tianjin, China). The main technical parameters of this equipment were as follows: end face diameter of the test needle, 0.6 mm; pressure measurement range, 0.1–50 g; and pressure measurement resolution, 0.05 g. An organic glass box (22 × 22 × 12 cm) was placed on the sieve of the metal frame. The rat was placed into the box for 30 min of adaptation. The left hind paws were touched with the test needle until escaping behavior was observed. The pressure value was automatically recorded. The measurement was conducted five times for each rat (interval, ≥5 min), and the mean value was calculated as the MWT for this measurement. , , RNA extraction and Real-time-PCR The rats in three groups were anesthetized using 10% chloral hydrate (3 ml/kg, i.p.). The L4–6 DRGs were isolated immediately and flushed with ice-cold phosphate-buffered saline (PBS). The total RNA samples were prepared from the L4–6 DRGs of each group using the TRIzol Total RNA Reagent (Beijing Tiangen Biotech Co.). cDNA synthesis was performed with 2 µg of total RNA using a RevertAid™ H Minus First Strand cDNA Synthesis Kit (Fermentas, Burlington, Ontario, Canada). The primers were designed with Primer Express 3.0 software (Applied Biosystems), and the sequences were as follows: P2X 7 , forward 5’-CTTCGGCGTGCGTTTTG-3’, and reverse 5’-AGGACAGGGTGGATCCAATG-3’ as well as β-actin, forward 5’- TAAAGACCTCTATGCCAACACAGT-3’, and reverse 5’-CACGATGGAGGGGCCGGACTCATC-3’. Quantitative PCR was performed using the SYBR® Green MasterMix in an ABI PRISM® 7500 Sequence Detection System (Applied Biosystems, Inc.: Foster City, CA). The quantification of gene expression was performed using the ΔΔCT calculation with CT as the threshold cycle. The relative levels of target genes, normalized to the sample with the lowest CT, are given as 2 −ΔΔCT . β-actin was used to be internal control in the three groups. The relative expression levels of mRNA in the three groups were normalized to β-actin. Western blot analysis The animals were anesthetized and tissue collection was performed as described above, except that the tissues were snap-frozen in tubes on dry ice during collection. Briefly, on the 14th day after the operation, the animals were anesthetized with 10% chloral hydrate and L4-6 DRGs were isolated immediately and rinsed in ice-cold PBS. The ganglia were homogenized by mechanical disruption in lysis buffer containing the following: 50 mM Tris-Cl, pH 8.0, 150 mM NaCl, 0.1% sodium dodecyl sulfate (SDS), 1% Nonidet P-40, 0.02% sodium deoxycholate, 100 µg/mL phenylmethylsulfonyl fluoride, and 1 µg/mL Aprotinin. The cells were incubated on ice for 30 min. The homogenates were then centrifuged at 12,000 r/min for 10 min and the supernatants were collected. The quantity of total proteins in the supernatants was determined using the Lowry method. After dilution with loading buffer (250 mM Tris-Cl, 200 mM Dithiothreitol, 10% SDS, 0.5% Bromophenol Blue, and 50% Glycerol) and heating to 95℃ for 5 min, samples containing equal protein levels (20 µg) were separated by 10% SDS–polyacrylamide gel electrophoresis with a Bio-Rad system. The proteins were then transferred onto polyvinylidene difluoride membranes by electrophoretic transfer using the same system. The membrane was blocked with 5% bovine serum albumin (BSA) for anti-p-ERK1/2 and anti-ERK1/2 in 25 mM tris-buffered saline, pH 7.2, plus 0.05% Tween 20 (TBST) for 2 h at room temperature, which was followed by incubation with a rabbit anti-P2X 7 (1:800 dilutions, Abcam, USA), rabbit anti-TNFα-receptor (R), rabbit anti-IL-1β and rabbit anti IL-10 (1:500 dilutions, Abcam, USA), rabbit anti-p-ERK1/2 (Thr202/Tyr204) (1:1000, Cell signaling technology, 9101), rabbit anti-ERK1/2 (1:1000, Cell signaling technology, 9102), and mouse monoclonal anti-β-actin antibody (1:800 dilutions, Beijing Zhongshan Biotech Co., China) at 4℃ overnight. The membranes were washed three times with TBST and incubated (1 h, room temperature) with a horseradish peroxidase-conjugated secondary antibody (goat anti-rabbit IgG (1:2000), goat anti-mouse IgG (1:2000), Beijing Zhongshan Biotech Co.) in blocking buffer. After another wash cycle, the labeled proteins were visualized by enhanced chemiluminescence on a high-performance film (Shanghai Pufei Biotech Co.). The chemiluminescent signals were collected on an autoradiography film, and the band intensity was quantified using Image Pro Plus software. The relative band intensity of the target proteins was normalized against the intensity of the respective β-actin internal control. Double immunofluorescence The DRGs isolated from rats in the three groups, six rats in each group, were washed with PBS. The DRGs were dissected immediately and fixed in 4% paraformaldehyde for 24 h at room temperature. Then, they were transferred to 20% sucrose for dehydration at 4℃ overnight. The tissues were sectioned at 10 µm using a cryostat and placed onto glass slides that were coated with poly-d-lysine for storage in the refrigerator at −20℃. After washing with PBS three times, the preparations were preincubated with 10% normal goat serum (Jackson ImmunoResearch Inc., West Grove PA, USA) for 40 min in a moist chamber at 37 ° C. The sections were then incubated with chicken anti-GFAP (1:1000 dilutions; Abcam, USA) and rabbit anti-P2X 7 (1:200 dilutions; Abcam, USA), which were diluted in PBS, overnight at 4 ° C. After three rinses in PBS, the sections were then incubated with fluorescent goat anti-chicken fluorescein isothiocyanate (FITC) and goat anti-rabbit tetramethylrhodamine isothiocyanate (TRITC) secondary antibodies (1:200 dilutions for both secondary antibodies; Jackson ImmunoResearch, PA, USA) in the dark at 37 ° C for 40 min. The prepared sections were washed three times in PBS before they were mounted in glycerol and cover slipped. After these steps, the sections were examined using fluorescence microscopy. Image-Pro Plus 6.0 image analysis software (Media Cybernetics Inc.) was used to quantify the co-localization of GFAP and P2X 7 . To specify the immunoreactivity of GFAP and P2X 7 , normal goat serum and PBS were used as negative controls in place of the primary antibodies. HEK 293 cell culture and transfection HEK 293 cells were grown in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum, 1% penicillin, and streptomycin at 37℃ in a humidified atmosphere containing 5% CO 2 . Cells were transiently transfected with the human pcDNA3.0-EGFP-P2X 7 plasmid using Lipofectamine 2000 reagent (Invitrogen) according to the manufacturer’s instructions. The Genbank accession number is NM_019256.1. The hP2X7R plasmid was purchased from Shanghai Generay Biotech Co., Ltd. When HEK293 cells were 70%–80% confluent, cell culture media was replaced with OptiMEM 2 h before transfection. The transfection media were prepared as follows: (a) 4 µg DNA was diluted into a 250 µl final volume of OptiMEM, (b) 10 µl Lipofectimine2000 was diluted into a 250 µl final volume of OptiMEM, and (c) the Lipofectimine-containing solution was mixed with the plasmid-containing solutions, which was incubated at room temperature (RT) for 20 min. Subsequently, 500 µl of cDNA/lipofectamine solution was added to each well. Cells were incubated for 6 h at 37℃ in 5% CO 2 . After incubation, the cells were washed in MEM containing 10% FBS and incubated for 24–48 h. The green fluorescent protein (GFP) fluorescence was assessed as a reporter for the efficiency of transfection. Whole-cell patch clamp recordings were performed one to two days after transfection. Electrophysiological recordings The electrophysiological recording was performed using a patch/whole cell clamp amplifier (Axopatch 200B). The micropipette was filled with internal solution (in mM) containing KCl 140, MgCl 2 2, HEPES 10, EGTA 11, and ATP 5. The osmolarity was adjusted to 340 mOsmol/kg with sucrose and pH was adjusted to 7.4 with KOH. The external solution (in mM) contained NaCl 150, KCl 5, CaCl 2 2.5, MgCl 2 1, HEPES 10, and D-glucose 10. Its osmolarity was adjusted to 340 mOsm with sucrose and pH was adjusted to 7.4 with NaOH. The resistance of recording electrodes was in the range of 1–4 MΩ; 3 MΩ was the best. A small patch of membrane underneath the pipette tip was aspirated to form a seal (1–10 GΩ). Then, a more negative pressure was applied to rupture it and establish a whole-cell mode. The holding potential was set at –60 mV. The drugs were dissolved in an external solution and delivered by gravity flow from an array of tubules (500 µm O.D. and 200 µm I.D.) connected to a series of independent reservoirs. The distance from the tubule mouth to the examined cell was approximately 100 µm. Rapid solution exchange was achieved by horizontally shifting the tubules with a micromanipulator. Statistical analysis The data were analyzed using SPSS 20 software. The numerical values were reported as the mean ± SEM. Statistical significance was determined by one-way analysis of variance followed by the Fisher’s post hoc test for multiple comparisons. A p-value < 0.05 was considered statistically significant.
Adult (200–250 g) male Sprague–Dawley (SD) rats were used in all experiments and housed with an alternating 12-h light/dark cycle. They were provided with food and water ad libitum. The use of the animals was reviewed and approved by the Animal Care and Use Committee of Medical College of Nanchang University. The experiments were conducted under the guidelines of the NIH in the US regarding the care and use of animals for experimental procedures. The rats were randomly divided into the following three groups (with six rats in each group): the HIV-gp120 group (gp120 group); HIV-gp120 rats treated with RES group (gp120 + RES group); and sham operation group (sham group). A previously described technique was used for the perineural HIV-gp120 administration. Briefly, under 10% chloral hydrate anesthesia (3 ml/kg, i.p., supplemented as necessary) and aseptic surgical conditions, the left sciatic nerve of the SD rats was exposed in the popliteal fossa without damaging the nerve construction. A 2 × 6 mm strip of oxidized regenerated cellulose was previously soaked in 250 µl of a 0.1% rat serum albumin saline solution containing 200 ng of gp120 (Sigma) or 0.1% rat serum albumin in saline for the sham surgery. A 3–4 mm length of the sciatic nerve that was proximal to the trifurcation was wrapped loosely with the soaked cellulose, did not cause nerve constriction, and was left in situ. The incision was closed with 4/0 sutures. Beginning at 24 h after surgery, the rats in the gp120 + RES group were intraperitoneally treated with RES (30 mg/kg) daily for 14 days. Rats in the sham and gp120 groups were intraperitoneally injected with the same volume of normal saline.
Determination of the mechanical withdrawal threshold (MWT) was performed at 9:00–12:00 using a BME-404 electronic mechanical stimulator (Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Tianjin, China). The main technical parameters of this equipment were as follows: end face diameter of the test needle, 0.6 mm; pressure measurement range, 0.1–50 g; and pressure measurement resolution, 0.05 g. An organic glass box (22 × 22 × 12 cm) was placed on the sieve of the metal frame. The rat was placed into the box for 30 min of adaptation. The left hind paws were touched with the test needle until escaping behavior was observed. The pressure value was automatically recorded. The measurement was conducted five times for each rat (interval, ≥5 min), and the mean value was calculated as the MWT for this measurement. , ,
The rats in three groups were anesthetized using 10% chloral hydrate (3 ml/kg, i.p.). The L4–6 DRGs were isolated immediately and flushed with ice-cold phosphate-buffered saline (PBS). The total RNA samples were prepared from the L4–6 DRGs of each group using the TRIzol Total RNA Reagent (Beijing Tiangen Biotech Co.). cDNA synthesis was performed with 2 µg of total RNA using a RevertAid™ H Minus First Strand cDNA Synthesis Kit (Fermentas, Burlington, Ontario, Canada). The primers were designed with Primer Express 3.0 software (Applied Biosystems), and the sequences were as follows: P2X 7 , forward 5’-CTTCGGCGTGCGTTTTG-3’, and reverse 5’-AGGACAGGGTGGATCCAATG-3’ as well as β-actin, forward 5’- TAAAGACCTCTATGCCAACACAGT-3’, and reverse 5’-CACGATGGAGGGGCCGGACTCATC-3’. Quantitative PCR was performed using the SYBR® Green MasterMix in an ABI PRISM® 7500 Sequence Detection System (Applied Biosystems, Inc.: Foster City, CA). The quantification of gene expression was performed using the ΔΔCT calculation with CT as the threshold cycle. The relative levels of target genes, normalized to the sample with the lowest CT, are given as 2 −ΔΔCT . β-actin was used to be internal control in the three groups. The relative expression levels of mRNA in the three groups were normalized to β-actin.
The animals were anesthetized and tissue collection was performed as described above, except that the tissues were snap-frozen in tubes on dry ice during collection. Briefly, on the 14th day after the operation, the animals were anesthetized with 10% chloral hydrate and L4-6 DRGs were isolated immediately and rinsed in ice-cold PBS. The ganglia were homogenized by mechanical disruption in lysis buffer containing the following: 50 mM Tris-Cl, pH 8.0, 150 mM NaCl, 0.1% sodium dodecyl sulfate (SDS), 1% Nonidet P-40, 0.02% sodium deoxycholate, 100 µg/mL phenylmethylsulfonyl fluoride, and 1 µg/mL Aprotinin. The cells were incubated on ice for 30 min. The homogenates were then centrifuged at 12,000 r/min for 10 min and the supernatants were collected. The quantity of total proteins in the supernatants was determined using the Lowry method. After dilution with loading buffer (250 mM Tris-Cl, 200 mM Dithiothreitol, 10% SDS, 0.5% Bromophenol Blue, and 50% Glycerol) and heating to 95℃ for 5 min, samples containing equal protein levels (20 µg) were separated by 10% SDS–polyacrylamide gel electrophoresis with a Bio-Rad system. The proteins were then transferred onto polyvinylidene difluoride membranes by electrophoretic transfer using the same system. The membrane was blocked with 5% bovine serum albumin (BSA) for anti-p-ERK1/2 and anti-ERK1/2 in 25 mM tris-buffered saline, pH 7.2, plus 0.05% Tween 20 (TBST) for 2 h at room temperature, which was followed by incubation with a rabbit anti-P2X 7 (1:800 dilutions, Abcam, USA), rabbit anti-TNFα-receptor (R), rabbit anti-IL-1β and rabbit anti IL-10 (1:500 dilutions, Abcam, USA), rabbit anti-p-ERK1/2 (Thr202/Tyr204) (1:1000, Cell signaling technology, 9101), rabbit anti-ERK1/2 (1:1000, Cell signaling technology, 9102), and mouse monoclonal anti-β-actin antibody (1:800 dilutions, Beijing Zhongshan Biotech Co., China) at 4℃ overnight. The membranes were washed three times with TBST and incubated (1 h, room temperature) with a horseradish peroxidase-conjugated secondary antibody (goat anti-rabbit IgG (1:2000), goat anti-mouse IgG (1:2000), Beijing Zhongshan Biotech Co.) in blocking buffer. After another wash cycle, the labeled proteins were visualized by enhanced chemiluminescence on a high-performance film (Shanghai Pufei Biotech Co.). The chemiluminescent signals were collected on an autoradiography film, and the band intensity was quantified using Image Pro Plus software. The relative band intensity of the target proteins was normalized against the intensity of the respective β-actin internal control.
The DRGs isolated from rats in the three groups, six rats in each group, were washed with PBS. The DRGs were dissected immediately and fixed in 4% paraformaldehyde for 24 h at room temperature. Then, they were transferred to 20% sucrose for dehydration at 4℃ overnight. The tissues were sectioned at 10 µm using a cryostat and placed onto glass slides that were coated with poly-d-lysine for storage in the refrigerator at −20℃. After washing with PBS three times, the preparations were preincubated with 10% normal goat serum (Jackson ImmunoResearch Inc., West Grove PA, USA) for 40 min in a moist chamber at 37 ° C. The sections were then incubated with chicken anti-GFAP (1:1000 dilutions; Abcam, USA) and rabbit anti-P2X 7 (1:200 dilutions; Abcam, USA), which were diluted in PBS, overnight at 4 ° C. After three rinses in PBS, the sections were then incubated with fluorescent goat anti-chicken fluorescein isothiocyanate (FITC) and goat anti-rabbit tetramethylrhodamine isothiocyanate (TRITC) secondary antibodies (1:200 dilutions for both secondary antibodies; Jackson ImmunoResearch, PA, USA) in the dark at 37 ° C for 40 min. The prepared sections were washed three times in PBS before they were mounted in glycerol and cover slipped. After these steps, the sections were examined using fluorescence microscopy. Image-Pro Plus 6.0 image analysis software (Media Cybernetics Inc.) was used to quantify the co-localization of GFAP and P2X 7 . To specify the immunoreactivity of GFAP and P2X 7 , normal goat serum and PBS were used as negative controls in place of the primary antibodies.
HEK 293 cells were grown in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum, 1% penicillin, and streptomycin at 37℃ in a humidified atmosphere containing 5% CO 2 . Cells were transiently transfected with the human pcDNA3.0-EGFP-P2X 7 plasmid using Lipofectamine 2000 reagent (Invitrogen) according to the manufacturer’s instructions. The Genbank accession number is NM_019256.1. The hP2X7R plasmid was purchased from Shanghai Generay Biotech Co., Ltd. When HEK293 cells were 70%–80% confluent, cell culture media was replaced with OptiMEM 2 h before transfection. The transfection media were prepared as follows: (a) 4 µg DNA was diluted into a 250 µl final volume of OptiMEM, (b) 10 µl Lipofectimine2000 was diluted into a 250 µl final volume of OptiMEM, and (c) the Lipofectimine-containing solution was mixed with the plasmid-containing solutions, which was incubated at room temperature (RT) for 20 min. Subsequently, 500 µl of cDNA/lipofectamine solution was added to each well. Cells were incubated for 6 h at 37℃ in 5% CO 2 . After incubation, the cells were washed in MEM containing 10% FBS and incubated for 24–48 h. The green fluorescent protein (GFP) fluorescence was assessed as a reporter for the efficiency of transfection. Whole-cell patch clamp recordings were performed one to two days after transfection.
The electrophysiological recording was performed using a patch/whole cell clamp amplifier (Axopatch 200B). The micropipette was filled with internal solution (in mM) containing KCl 140, MgCl 2 2, HEPES 10, EGTA 11, and ATP 5. The osmolarity was adjusted to 340 mOsmol/kg with sucrose and pH was adjusted to 7.4 with KOH. The external solution (in mM) contained NaCl 150, KCl 5, CaCl 2 2.5, MgCl 2 1, HEPES 10, and D-glucose 10. Its osmolarity was adjusted to 340 mOsm with sucrose and pH was adjusted to 7.4 with NaOH. The resistance of recording electrodes was in the range of 1–4 MΩ; 3 MΩ was the best. A small patch of membrane underneath the pipette tip was aspirated to form a seal (1–10 GΩ). Then, a more negative pressure was applied to rupture it and establish a whole-cell mode. The holding potential was set at –60 mV. The drugs were dissolved in an external solution and delivered by gravity flow from an array of tubules (500 µm O.D. and 200 µm I.D.) connected to a series of independent reservoirs. The distance from the tubule mouth to the examined cell was approximately 100 µm. Rapid solution exchange was achieved by horizontally shifting the tubules with a micromanipulator.
The data were analyzed using SPSS 20 software. The numerical values were reported as the mean ± SEM. Statistical significance was determined by one-way analysis of variance followed by the Fisher’s post hoc test for multiple comparisons. A p-value < 0.05 was considered statistically significant.
Effects of RES on hyperalgesia in gp120-treated rats Mechanical hyperalgesia was tested with a mechanical stimulator. There was no difference in the MWT between the gp120 and sham groups before the operation (p > 0.05). At 4 to 14 days after the operation, the MWT in the gp120 group was lower than the sham group (p < 0.05) and there was a significant difference from days 7 to 14 (p < 0.01). The MWT in the gp120 + RES group was higher than the gp120 group from days 4 to 14 (p < 0.05), and there was a significant difference from days 12 to 14 (p < 0.01) ( ). Effects of RES on the expression of the P2X 7 mRNA and protein in the DRG of the gp120-treated rats The expression of the P2X 7 mRNA in the DRG was measured by RT-PCR. The relative levels of the P2X 7 mRNA in the gp120 group were significantly increased compared to the sham group (p < 0.01). The expression levels of the P2X 7 mRNA in the gp120 + RES group were significantly decreased compared to the gp120 group (p < 0.01) ( ). The expression levels of the P2X 7 protein in the DRG were analyzed by Western blot analysis. Using image analysis, the P2X 7 protein expression (normalized to each β-actin in the internal control) in the gp120 group was significantly enhanced compared to the sham group (p < 0.01). The relative levels of the P2X 7 protein expression in the gp120 + RES group were lower than the gp120 group (p < 0.01) ( ). Effects of RES on the co-localization of P2X 7 and GFAP by double immunofluorescence in the DRGs of the gp120-treated rats The co-localization of the P2X 7 receptor and GFAP (a marker of SGCs) was measured by double immunofluorescence. The upregulated expression of GFAP was a typical characteristic of active SGCs. The immunofluorescence results showed that the P2X 7 receptor and GFAP were co-localized in the DRG SGCs. The co-localization of the P2X 7 receptor and GFAP in the gp120 group exhibited more intense staining than the sham group. The co-localization of the P2X 7 receptor and GFAP in the gp120 + RES group was significantly decreased compared to the gp120 group ( ). Effects of RES on the expression of TNFα-R, IL-1β, and IL-10 proteins in the DRG of gp120-treated rats The expression levels of TNFα-R, IL-1β, and IL-10 proteins in the DRG were analyzed by Western blot analysis. Using image analysis, the values for the TNFα-R and IL-1β protein expression levels (normalized to each β-actin internal control) in the gp120 group were significantly augmented compared to the sham group (p < 0.01). The relative values of the TNFα-R and IL-1β protein expression levels in the gp120 + RES group were lower than the gp120 group (p < 0.01) ( ). The IL-10 protein expression levels in the gp120 group were decreased compared to the sham group (p < 0.01). The IL-10 protein expression levels in the gp120 + RES group were increased compared to the gp120 group (p < 0.01) ( ). Effects of RES on the ERK1/2 and p-ERK1/2 expression levels in the DRG of gp120-treated rats The phosphorylation and activation of ERK1/2 are involved in inflammatory pain. The ERK1/2 and p-ERK1/2 expression levels in the DRG were analyzed by Western blot analysis. The integrated optical density (IOD) ratio of p-ERK1/2 to ERK1/2 was higher in the gp120 group than in the sham group (p < 0.01, n = 6 for each group).The results indicated that the role of extracellular signal-regulated protein kinase (ERK) phosphorylation in the DRG is related to the P2X 7 receptor-mediated hyperalgesia in the gp120-treated rats. In addition, we examined whether the administration of RES was able to affect the phosphorylation of ERK in the gp120 group DRG. The IOD ratio of p-ERK1/2 to ERK1/2 in the gp120 + RES group was significantly lower than the gp120 group (p < 0.01, n = 6 for each group) ( ). These results suggest that the RES effects on the P2X 7 receptor-mediated hyperalgesia may help decrease the ERK1/2 phosphorylation and activation in the DRG of the gp120-treated rats. Depressive effects of RES on ATP-induced current in HEK293 cells expressing the hP2X7 receptor The ATP-activated currents in HEK293 cells transfected with pEGFP-hP2X 7 plasmid were recorded by whole cell patch clamping. The ATP-activated currents in HEK293 cells can be inhibited by RES ( ). The concentration dependence of ATP on the peak amplitude of current responses by the P2X 7 receptor in the absence (closed symbols) and presence of RES (100 µM) (open symbols) (p < 0.05, n = 8–10) was showed in (b).
Mechanical hyperalgesia was tested with a mechanical stimulator. There was no difference in the MWT between the gp120 and sham groups before the operation (p > 0.05). At 4 to 14 days after the operation, the MWT in the gp120 group was lower than the sham group (p < 0.05) and there was a significant difference from days 7 to 14 (p < 0.01). The MWT in the gp120 + RES group was higher than the gp120 group from days 4 to 14 (p < 0.05), and there was a significant difference from days 12 to 14 (p < 0.01) ( ).
7 mRNA and protein in the DRG of the gp120-treated rats The expression of the P2X 7 mRNA in the DRG was measured by RT-PCR. The relative levels of the P2X 7 mRNA in the gp120 group were significantly increased compared to the sham group (p < 0.01). The expression levels of the P2X 7 mRNA in the gp120 + RES group were significantly decreased compared to the gp120 group (p < 0.01) ( ). The expression levels of the P2X 7 protein in the DRG were analyzed by Western blot analysis. Using image analysis, the P2X 7 protein expression (normalized to each β-actin in the internal control) in the gp120 group was significantly enhanced compared to the sham group (p < 0.01). The relative levels of the P2X 7 protein expression in the gp120 + RES group were lower than the gp120 group (p < 0.01) ( ).
7 and GFAP by double immunofluorescence in the DRGs of the gp120-treated rats The co-localization of the P2X 7 receptor and GFAP (a marker of SGCs) was measured by double immunofluorescence. The upregulated expression of GFAP was a typical characteristic of active SGCs. The immunofluorescence results showed that the P2X 7 receptor and GFAP were co-localized in the DRG SGCs. The co-localization of the P2X 7 receptor and GFAP in the gp120 group exhibited more intense staining than the sham group. The co-localization of the P2X 7 receptor and GFAP in the gp120 + RES group was significantly decreased compared to the gp120 group ( ).
The expression levels of TNFα-R, IL-1β, and IL-10 proteins in the DRG were analyzed by Western blot analysis. Using image analysis, the values for the TNFα-R and IL-1β protein expression levels (normalized to each β-actin internal control) in the gp120 group were significantly augmented compared to the sham group (p < 0.01). The relative values of the TNFα-R and IL-1β protein expression levels in the gp120 + RES group were lower than the gp120 group (p < 0.01) ( ). The IL-10 protein expression levels in the gp120 group were decreased compared to the sham group (p < 0.01). The IL-10 protein expression levels in the gp120 + RES group were increased compared to the gp120 group (p < 0.01) ( ).
The phosphorylation and activation of ERK1/2 are involved in inflammatory pain. The ERK1/2 and p-ERK1/2 expression levels in the DRG were analyzed by Western blot analysis. The integrated optical density (IOD) ratio of p-ERK1/2 to ERK1/2 was higher in the gp120 group than in the sham group (p < 0.01, n = 6 for each group).The results indicated that the role of extracellular signal-regulated protein kinase (ERK) phosphorylation in the DRG is related to the P2X 7 receptor-mediated hyperalgesia in the gp120-treated rats. In addition, we examined whether the administration of RES was able to affect the phosphorylation of ERK in the gp120 group DRG. The IOD ratio of p-ERK1/2 to ERK1/2 in the gp120 + RES group was significantly lower than the gp120 group (p < 0.01, n = 6 for each group) ( ). These results suggest that the RES effects on the P2X 7 receptor-mediated hyperalgesia may help decrease the ERK1/2 phosphorylation and activation in the DRG of the gp120-treated rats.
The ATP-activated currents in HEK293 cells transfected with pEGFP-hP2X 7 plasmid were recorded by whole cell patch clamping. The ATP-activated currents in HEK293 cells can be inhibited by RES ( ). The concentration dependence of ATP on the peak amplitude of current responses by the P2X 7 receptor in the absence (closed symbols) and presence of RES (100 µM) (open symbols) (p < 0.05, n = 8–10) was showed in (b).
Elucidation of how HIV-1 infection causes chronic pain is essential for developing effective therapy. HIV-1 gp120, as a potential pathogenically relevant factor, is involved in neuropathic pain. , , Our data showed that the MWT in the peripheral gp120-treated rats was decreased compared to the sham rats, which was consistent with previous reports. , , The DRG can transmit pain signals from the periphery to the central nervous system. , The P2X 7 receptor in the DRG is related to inflammatory and neuropathic pain. , , , Our study demonstrated that the P2X 7 mRNA and protein levels in the HIV-1 gp120-treated rats were significantly enhanced compared with those in the sham rats. The increased P2X 7 receptor in the DRG may be involved in HIV-associated neuropathic pain. After treatment with RES, the P2X 7 receptor mRNA and protein levels were decreased. Meanwhile, the MWT in the gp120 + RES group was higher than that in the gp120 group. Our results indicated that RES might decrease the upregulated expression of the P2X 7 receptor and inhibit the transmission of nociceptive signaling. This effect may eventually alleviate the HIV-associated pain behavior in the gp120 group rats. The SGCs enwrap the neuronal soma in the DRG. Double immunohistochemical staining showed that co-localization of the P2X 7 receptor and GFAP in the DRG in the gp120-treatment rats was increased. GFAP is a marker of SGCs. Our data indicated that the expression of the P2X 7 receptor in the DRG SGCs was increased. The GFAP upregulation in the DRG SGCs of gp120 treatment rats indicates the activation of SGCs. , The activation of SGCs can release cytokines and thus augment neuronal excitation. , The results showed that the TNFα-R and IL-1β protein levels in the gp120 group were significantly increased compared to the sham group, and the IL-10 protein levels (anti-inflammatory factor) in the gp120 group were decreased compared to the sham group. RES inhibited the increased expression levels of P2X 7 and GFAP in the DRG SGCs. After the gp120 rats were treated with RES, the relative TNFα-R and IL-1β protein levels were lower than the gp120 rats and the IL-10 protein levels were increased compared to the gp120 rats. RES may inhibit the upregulated P2X 7 and GFAP levels in the DRG and decrease the activation of SGCs. RES may then reduce the release of cytokines. Inflammatory factors can increase the activation of the P2X 7 receptor, aggravating the neuropathic damage. , Anti-inflammatory effects could decrease the nociceptive signal of the aggravated DRG neuronal excitation. RES has anti-inflammatory effects. – Our results suggested that RES relieved the HIV-associated pain behavior in the gp120 rats by influencing the P2X 7 receptor in the DRG SGCs. P2X receptor-mediated pain transmission is related to ERK signaling. ERK pathway activation participates in the sensitized primary afferents in pain transmission. , ERK1/2 phosphorylation generates the activation form of ERK1/2. Our data revealed that the IOD ratio of p-ERK1/2 to ERK1/2 was higher in the gp120 group than the sham group. The role of ERK phosphorylation in the DRG may be involved in the P2X 7 receptor-mediated hyperalgesia in the gp120-treated rats. After the administration of RES, the IOD ratio of p-ERK1/2 to ERK1/2 in the gp120 + RES group was significantly decreased compared with that in the gp120 group. RES may decrease the phosphorylation of ERK1/2 in the DRG of the gp120-treated rats, relieving the P2X 7 receptor-mediated hyperalgesia. To identify whether RES can specially act on the P2X 7 receptor, HEK293 cells that were transfected with the P2X 7 plasmid were evaluated. RES significantly inhibited the ATP-activated currents in the HEK293 cells that were transfected with P2X 7 plasmid. These data confirmed that RES relieved the HIV-associated pain behavior in the gp120 rats by acting on the P2X 7 receptor. The electrophysiological data supported the phenomenon, RES treatment relieved the HIV-associated pain behavior relating to downregulation of the P2X 7 receptor expression. In conclusion, the gp120 protein treatment enhanced the expression the P2X 7 receptor in DRG SGCs. The upregulated P2X 7 and GFAP levels in the DRG indicated the activation of SGCs. The activation of SGCs increased the release of inflammatory cytokines (IL-1β and TNF-α) and decreased the release of anti-inflammatory cytokine (IL-10). IL-1β and TNF-α could increase the sensitization of neurons in the DRG, resulting in gp120-induced neuropathic pain behavior. RES dampened the release of inflammatory cytokines, enhanced the release of an anti-inflammatory cytokine, and reduced the upregulation of the P2X 7 receptor. Inhibition of the P2X 7 receptor in DRG SGCs may decrease the sensitization of neurons in the DRG of the gp120-treated rats. Therefore, RES relieved the mechanical hyperalgesia in the gp120-treated rats relating to inhibition of the P2X 7 receptor in DRG SGCs.
Bing Wu performed experiments and wrote the manuscript. Bing Wu, Yucheng Ma, Zhihua Yi, Shuangmei Liu, Shenqiang Rao, Lifang Zou, Shouyu Wang, Yun Xue, Tianyu Jia, Shanhong Zhao, Lin Li, Huilong Yuan, and Liran Shi performed the experiments. Bing Wu and Shuangmei Liu performed the electrophysiological experiments. Shandong Liang designed the study, supervised the work, wrote, and revised the manuscript. All authors read and approved the final manuscript.
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Mandibular Fractures in Edentulous Patients with Bone Atrophy and Osseointegrated Dental Implants: Therapeutic Management in a Case Series | 336c065e-3e6c-4134-b89f-b1f5b500290a | 11596129 | Dentistry[mh] | Mandibular atrophy is a consequence of tooth loss. Over time, edentulous bone decreases in height and also frequently in width. The remaining bone is characterized as being mostly cortical and less medullary. In addition, its periosteal vascular supply is partially diminished, and its endosteal vascularization may be severely compromised by the osseous tissue atrophy (the inferior alveolar artery can be found underneath the mucosa). The greatest degree of atrophy is usually located in the mandibular body . Patients with mandibular atrophy can benefit from dental implant treatment. Subsequent to dental implant placement, one of the possible prosthetic solutions could be the use of implant-retained overdentures, with a success rate ranging from 80% to 100% . Despite the high rate of osseointegration of the implants and the good functioning of overdentures, complications may arise. Infections, improper implant placement, bleeding, or mandibular fractures should be kept in mind when treating these patients. The incidence of mandibular fractures, in this specific situation, is very low (0.05–0.2%) , and few cases have been reported in the literature. The etiology of the fracture is usually due to trauma or peri-implantitis, and their consequences can be severe , including osteomyelitis, paresthesias/dysesthesias, pseudoarthrosis, and long-term nutritional problems . The initial suspected diagnosis should be clinical, based on an accurate physical examination. It is important to highlight that bone fragment mobility may not be clear due to the splinting effect of the overdenture bar or the overdenture itself. Therefore, clinical examination should always be supported by imaging studies, ideally orthopantomography (OPG) and multiplanar computed tomography (CT). The treatment of this type of fracture can be complex, and there are several different therapeutic alternatives, such as conservative management with a soft diet, splinting supported by implant-retained overdentures, or open reduction and internal fixation with or without combining the use of bone grafts . Whether to choose one therapeutic option or the other depends primarily on the characteristics of the fracture, the possible associated peri-implantitis and the patient’s medical condition. In general, surgical treatment with an extraoral approach and rigid fixation is recommended, as it is a load-bearing situation where the osteosynthesis material must withstand all the biomechanical requirements of the fracture. In some cases, open reduction and internal fixation (ORIF) may be achieved by preserving dental implants if there is no indication for its removal, such as in cases where the cause of the fracture is peri-implantitis, or where there is implant mobility . The main objective of this research is to describe the management of these types of fractures in a case series of edentulous patients with mandibular atrophy and implant-retained overdentures, as well as to discuss possible etiologies and treatment options.
A retrospective observational study of a case series was designed for the period from January 2010 to December 2023. The research was conducted in two different centers by the Oral and Maxillofacial Surgery Departments of Gregorio Marañón University Hospital (HGUGM) and La Paz University Hospital (HULP) in Madrid. A specific informed consent form was designed. This study is endorsed by the ethics committee of the Gregorio Marañón University Hospital. 2.1. Inclusion and Exclusion Criteria The study included patients who met all the following criteria: Edentulous patients with atrophic bone treated with dental implants and implant-retained overdentures. Adult patients (over 18 years old). Patients with a clinical diagnosis of mandibular fracture supported by imaging evidence. Minimum clinical follow-up of one year. Patients who met any of the following criteria were excluded from the study: Patients who have undergone previous surgeries that could have altered mandibular anatomy. Pathological mandibular fractures secondary to tumoral pathology. Patients with psychiatric disorders. Patients whose medical records did not include the study variables. Refusal to sign the informed consent. Patients with signs of parafunctional habits (bruxism). The sources of information used to identify potential candidates for the research are as follows: Surgical reports from the Oral and Maxillofacial Surgery Department of HGUGM and HULP. Medical records from HGUGM and HULP. Radiological image archives from HGUGM and HULP. 2.2. Study Variables The data collection notebook is an Excel table. The variables for which information was collected are as follows: sex, age, smoking habit, personal medical condition, history of radiation therapy in the head and neck area, diagnostic imaging test, fracture focus location, type of fracture line, reason for consultation, etiology, treatment (conservative vs. surgical), surgical approach, type of internal fixation, use of bone grafts, length of hospital stay, complications, and follow-up duration. A descriptive statistical analysis was performed. 2.3. Limitation of the Research The primary limitations of the study are its retrospective design and the small sample size.
The study included patients who met all the following criteria: Edentulous patients with atrophic bone treated with dental implants and implant-retained overdentures. Adult patients (over 18 years old). Patients with a clinical diagnosis of mandibular fracture supported by imaging evidence. Minimum clinical follow-up of one year. Patients who met any of the following criteria were excluded from the study: Patients who have undergone previous surgeries that could have altered mandibular anatomy. Pathological mandibular fractures secondary to tumoral pathology. Patients with psychiatric disorders. Patients whose medical records did not include the study variables. Refusal to sign the informed consent. Patients with signs of parafunctional habits (bruxism). The sources of information used to identify potential candidates for the research are as follows: Surgical reports from the Oral and Maxillofacial Surgery Department of HGUGM and HULP. Medical records from HGUGM and HULP. Radiological image archives from HGUGM and HULP.
The data collection notebook is an Excel table. The variables for which information was collected are as follows: sex, age, smoking habit, personal medical condition, history of radiation therapy in the head and neck area, diagnostic imaging test, fracture focus location, type of fracture line, reason for consultation, etiology, treatment (conservative vs. surgical), surgical approach, type of internal fixation, use of bone grafts, length of hospital stay, complications, and follow-up duration. A descriptive statistical analysis was performed.
The primary limitations of the study are its retrospective design and the small sample size.
The total number of patients who met the inclusion/exclusion criteria was six. All patients included in the study were female. The mean age was 76.33 years old. None of the patients were smokers; two patients (33.33%) had a history of osteoporosis treated with bisphosphonates; however, none of them had received radiation therapy in the head and neck area. The reason for consultation in all cases was mandibular pain and inflammation. Hypoesthesia was present in one patient. The imaging diagnostic tests used were OPG and CT, except for one case in which only OPG was used. The fracture focus was left parasymphysis in two patients, the left mandibular body in three patients, and one bifocal fracture (left body and right ramus). Fracture lines were simple in five patients (83.33%). The most frequent cause of fracture was peri-implantitis in three patients (50%); mandibular trauma in one patient (16.67%), and bisphosphonate-related osteonecrosis in two patients (33.33%). Among the patients with peri-implantitis, it is noteworthy that in one case, the fracture occurred at the moment of screwing the overdenture bar to the osseointegrated implant . Surgical treatment (open reduction and internal fixation) was performed in five patients (83.33%). A combined intraoral and cervical approach was used in two patients (40%), only a cervical approach in two patients (40%), and only an intraoral approach in the other patient (16.66%). Conservative treatment was employed in a 94-year-old patient with multiple pathologies who presented with a double mandibular fracture with non-displaced foci. Internal fixation was performed using load-bearing principles. A 2.5 mm thick mandibular locking plate with a 2.4 mm screw diameter was used in three patients (50%), a combination of 2.0 mm thick mandibular locking plate with 2 mm screw diameter and 1.0 mm thick mandibular plate with 2 mm screw diameter was used in one patient (16.66%); and a 2.0 mm thick mandibular locking plate with 2 mm screw diameter combined with a titanium mesh in another patient (16.66%). Implant removal was necessary in two patients (33.33%) . Additionally, in two patients (33.33%), autologous grafts obtained from the iliac crest and mandibular ramus were used, respectively . In one patient (16.66%), a non-autologous bone graft was used. The average length of hospital stay was 4 days. The complication rate was 50% (three patients), with complications including delayed consolidation without interfragmentary mobility, hypoesthesia of the inferior alveolar nerve, and bone sequestration with granuloma formation, which was treated with antibiotic therapy. The follow-up period had a mean duration of 34 months. At the end of the follow-up period, all patients reported no pain. 3.1. Case 1 A non-smoker 70-year-old woman with a personal history of mitral valve disease consulted for pain and left paramandibular swelling. The patient denied any previous trauma. She had no history of radiation therapy in the head and neck area and had not received bisphosphonate treatment. On physical examination, the patient had a complete edentulism with associated mandibular atrophy and carried a three-dental-implant-retained overdenture. No open mandibular fracture lines or interfragmentary mobility were observed. After performing an OPG and CT scan, she was diagnosed with a left mandibular body fracture due to peri-implantitis ( and ). Based on the CT images, a 3D biomodel was created in the 3D Printing Unit (UPAM3D) of HGUGM. A 2.5 mm thick mandibular locking plate with a 2.4 mm screw diameter was preshaped on the 3D mandibular model before surgery . Under general anesthesia and nasotracheal intubation, a cervical approach was used to identify the fracture and to perform an open reduction and internal rigid fixation with the previous prebended plate. Additionally, a non-autologous bone graft was used . Two implants affected by peri-implantitis were removed during the same surgical procedure, while the other implant was left in place to prevent further damage to the bone and its vascularization. During the immediate postoperative period, the patient had no medical events and was discharged on the first postoperative day. After 33 months, there were no clinical signs of complications, the fracture focus had consolidated , and the patient refused any kind of pre-prosthetic surgical intervention. For esthetic reasons, the patient carries one implant-retained overdenture . 3.2. Case 2 A 94-year-old woman with a medical history of heart failure who was a non-smoker and had no history of radiation therapy in the head and neck area consulted for mandibular pain following trauma after an accidental fall. The patient denied having received bisphosphonate treatment. Physical examination revealed an edentulism and a mandibular atrophy. The patient carried a two-implant-retained overdenture as a dental prosthesis. No fracture lines or bone interfragmentary mobility were appreciated. The patient refers hypoesthesia of the left inferior alveolar nerve. The OPG image revealed a bifocal atrophic mandibular fracture (right mandibular ramus and left body) . Despite having two fracture foci, no important displacement was observed, and there was no pathological mobility between bone fragments. The patient refused surgery, so conservative treatment was carried out with a soft diet for 8 weeks. After close clinical follow-up for more than one year, it became evident that there was no important bone displacement or late complications , and the patient was able to return to wearing her overdenture.
A non-smoker 70-year-old woman with a personal history of mitral valve disease consulted for pain and left paramandibular swelling. The patient denied any previous trauma. She had no history of radiation therapy in the head and neck area and had not received bisphosphonate treatment. On physical examination, the patient had a complete edentulism with associated mandibular atrophy and carried a three-dental-implant-retained overdenture. No open mandibular fracture lines or interfragmentary mobility were observed. After performing an OPG and CT scan, she was diagnosed with a left mandibular body fracture due to peri-implantitis ( and ). Based on the CT images, a 3D biomodel was created in the 3D Printing Unit (UPAM3D) of HGUGM. A 2.5 mm thick mandibular locking plate with a 2.4 mm screw diameter was preshaped on the 3D mandibular model before surgery . Under general anesthesia and nasotracheal intubation, a cervical approach was used to identify the fracture and to perform an open reduction and internal rigid fixation with the previous prebended plate. Additionally, a non-autologous bone graft was used . Two implants affected by peri-implantitis were removed during the same surgical procedure, while the other implant was left in place to prevent further damage to the bone and its vascularization. During the immediate postoperative period, the patient had no medical events and was discharged on the first postoperative day. After 33 months, there were no clinical signs of complications, the fracture focus had consolidated , and the patient refused any kind of pre-prosthetic surgical intervention. For esthetic reasons, the patient carries one implant-retained overdenture .
A 94-year-old woman with a medical history of heart failure who was a non-smoker and had no history of radiation therapy in the head and neck area consulted for mandibular pain following trauma after an accidental fall. The patient denied having received bisphosphonate treatment. Physical examination revealed an edentulism and a mandibular atrophy. The patient carried a two-implant-retained overdenture as a dental prosthesis. No fracture lines or bone interfragmentary mobility were appreciated. The patient refers hypoesthesia of the left inferior alveolar nerve. The OPG image revealed a bifocal atrophic mandibular fracture (right mandibular ramus and left body) . Despite having two fracture foci, no important displacement was observed, and there was no pathological mobility between bone fragments. The patient refused surgery, so conservative treatment was carried out with a soft diet for 8 weeks. After close clinical follow-up for more than one year, it became evident that there was no important bone displacement or late complications , and the patient was able to return to wearing her overdenture.
Edentulism causes the jawbone to atrophy, resulting in severe esthetic and functional consequences for chewing, management of the food bolus, and speech. Implant placement and retained overdentures help edentulous patients but do not prevent the progression of bone resorption, especially in the posterior area of the jaw. Therefore, in the event of infections, peri-implantitis, or trauma, the chances of suffering a mandibular fracture are higher . Fractures of atrophic mandibles in patients carrying dental implants are rare, with an incidence reported in the literature ranging from 0.05% to 0.2% . They are more common in women aged between 30 and 78 years old . Some risk factors may include osteoporosis , previous radiation therapy in the head and neck area, use of anti-resorptive treatment, and smoking . When considering the management of these fractures, it must be kept in mind that the alveolar process and the mandibular basal bone have been reduced , vascularization is impaired, and the bone morphology is predominantly cortical . It seems that the placement of implants in these situations may result in an area of increased jaw weakness. Therefore, functional forces alone could cause a mandibular fracture without the need for trauma , and the more implants are placed, the greater the risk of mandibular fracture . It is reasonable to understand that the surgical treatment of these patients also carries a higher risk of complications. The treatment of these fractures can be a challenge for maxillofacial surgeons. There are different therapeutic options that are generally selected based on the characteristics of the involved fracture and the patient’s conditions. According to AO Foundation (Arbeitsgemeinschaft für Osteosynthesefragen) principles, they usually require surgical treatment with ORIF using rigid fixation plates due to the “load-bearing” situation, which implies that the osteosynthesis material must support the entire mandibular load . The use of rigid versus semi-rigid fixation is a controversial issue well described in the literature. The rationale for using mini plates is that they require less periosteal stripping and thus less blood disruption, allowing for primary reduction and stability. However, the use of this type of plate is not always feasible in atrophic mandibles. Ellis et al. report that at least 10 mm of bone height is necessary to be able to accommodate two mini-plates. Even when this height is sufficient to fit two plates, the resulting stability is still lower than that observed in non-atrophic or dentate mandibles due to the fact that stability is directly influenced by the distance between plates . It is also important not to forget that mini plates can be more susceptible to fractures . Vajgel et al. highlighted the need to establish safety limits for the fixation plates due to the variation in masticatory forces. Their research demonstrated that the application of forces of 102 N and 154 N to 1.0 mm and 1.5 mm plates, respectively, resulted in permanent deformation. In contrast, the 2.0 mm and 2.5 mm plates were deformed by higher forces, specifically 194 N and 260 N. Biomechanical studies indicate that a reduction in the vertical dimension of the mandible, particularly when the bone height at the fracture site is less than 10 mm, leads to a proportional decrease in resistance to bone fragment displacement. The absence of structural support in atrophic mandibles creates a scenario similar to a continuity defect. The result is that the bone along the fracture line does not bear any occlusal load, and most of the force is transferred to the plate. The development of locking systems has improved the treatment of these fractures, as the plate does not need to be in close contact with the underlying bone in all areas, and the vascularization is less compromised . The cervical approach is the most commonly used because it allows good bone exposure, permits the verification of a correct reduction of the fragments, and insets the appropriate osteosynthesis material. Another advantage of this approach in this type of fracture is having a better control of the inferior alveolar nerve. However, it has disadvantages such as the risk of facial nerve damage, development of cervical hematomas, infections, orocervical fistula, hypertrophic scars, and the exposure of osteosynthesis plates. ORIF can also be performed through an intraoral approach, communicating the oral cavity with the fracture site and osteosynthesis plates, thus increasing the risk of infection. However, there is no evidence confirming the superiority of one approach over another for atrophic mandibular fractures in patients with implants and overdentures . Therefore, the choice of approach should also be based on each surgeon’s experience . There is no convincing evidence that the use of bone grafting is necessary in the treatment of atrophic edentulous mandibular fractures. The use of bone grafting in these specific situations is useful to facilitate bone union, provide fracture stability and increase bone volume in order to prevent pathological fractures and improve prosthetic rehabilitation . Autologous or non-autologous bone grafts can be employed in regions where there are significant bone defects or in clinical scenarios characterized by reduced healing capacity. On one hand, autologous grafts, particularly those harvested from the iliac crest, are frequently favoured due to their superior capacity to promote neovascularization. This biological process is crucial, as it enhances graft integration and survival at the recipient site, thereby facilitating better healing outcomes. Additionally, autologous grafts contain vital growth factors that contribute to the regenerative process, making them a reliable choice for complex cases. On the other hand, non-autologous grafts may be selected for their relative availability and the reduced morbidity associated with donor sites. It is important to highlight that the integration of non-autologous grafts may be less predictable, and their biological behaviour may not replicate that of autologous grafts. The preference between autologous and non-autologous grafts is influenced by a variety of clinical and practical factors, such as the extent of the bone defect, the patient’s general condition, and the surgeon’s familiarity with specific materials and techniques. Joshep E. et al. report that, despite the traditional view that the use of bone grafting is essential to enhance osteogenesis, their findings suggest that the use of large reconstruction plates may be sufficient to achieve adequate ossification without the need for grafting. This perspective challenges established paradigms and indicates that, with appropriate surgical techniques and materials, effective results can be achieved even in cases traditionally considered complex . Luhr et al. achieved excellent results with open reduction and internal fixation with bone plates without the routine addition of bone grafts . In certain circumstances, like non-displaced simple fractures without interfragmentary mobility, patients with significant comorbidities who are not candidates for surgical treatment, or patients unwilling to undergo surgery, conservative treatment may be a valid option. A soft diet and/or closed reduction with external fixation using the patient’s overdenture , or wires between the remaining implants can help to obtain proper healing of the fracture. New technologies allow for more predictable and precise procedures. The use of biomodels, pre-adapted plates, and personal–specific implants facilitates more detailed and personalized surgical planning. These innovations significantly reduce surgical time by enabling faster and more accurate plate adaptation. As a result, a decrease in the length of hospital stay can be observed.
Mandibular fractures in edentulous patients carrying implant-retained overdentures are a very rare condition. Consequently, there is no highly scientific consensus regarding their treatment. In most cases, surgical treatment is preferred and requires the use of rigid fixation plates. Occasionally, bone grafting may be necessary. Clinical features of the patient, the type of fracture, and the surgeon’s experience should be considered to select an appropriate treatment option.
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Dermatology mycology diagnostics in Ireland: National deficits identified in 2022 that are relevant internationally | 74f7b2de-6b84-41f7-983f-e9fbe855fecf | 10107536 | Microbiology[mh] | INTRODUCTION Dermatophyte infections are among the most common global diseases, affecting 25% of the world's population, with asymptomatic carriage in 30%–70% of adults. Moreover, in the last two decades, there has been a dramatic increase in their incidence, due to a range of factors including socioeconomic problems, international travel, immigration from tropical countries and contact with animals, particularly pets. The clinical features of dermatophytosis may be mistaken for a wide range of other dermatological diseases including bacterial folliculitis, psoriasis and eczema. Many localised uncomplicated fungal skin infections in healthy individuals can be treated effectively by community pharmacists and general practitioners, however, access to accurate pathogen identification is important in moderate to severe disease, complicated or recalcitrant disease; in order to direct treatment appropriately. For example, in tinea capitis, treatment is often commenced based on clinical diagnosis; however, the choice of oral antifungal agent is dependent on the suspected species and subsequent pathogen identification; also, guidelines recommend that the definitive end point for adequate treatment must be the mycological cure, rather than clinical response. Infections with anthropophilic species such as Trichophyton violaceum or Trichophyton soudanense have shown a good response to terbinafine, yet zoophilic pathogens such as Microsporum canis have better cure rates with the use of griseofulvin or itraconazole. , Historically there has been a preponderance of zoophilic dermatophytes in our region, but a recent epidemiological study demonstrated a shift in prevalence to predominantly anthropophilic species over a 20‐year period. In the latter period of this study, mycology testing of skin, hair and nail samples was outsourced, and access was curtailed for patients in primary care settings. Conventional mycological diagnostic methods are time‐consuming, and when faced with staff shortages in 2016, mycology testing was outsourced to a referral laboratory. Thereafter, requests for fungal testing of skin, hair and nail samples were restricted to consultant dermatologists and other practitioners with specialist training, reducing the number of tests performed. The shortage of medical laboratory scientists is neither a recent phenomenon nor is it simply a local problem for our laboratory; calls to action to address the shortage began in the 1980s, , and even prior to the COVID‐19 pandemic it was recognised that the number of new medical laboratorians entering the workforce was not keeping up with future demand. In a National survey of the United States of America in 2018, vacancy rates in laboratories were ‘considerably higher’ than a similar survey in 2016, and Microbiology Departments were amongst the worst affected with vacancy rates over 10%. At the time of writing, in our Microbiology Department we have a vacancy rate of 21%, and this has been an on‐going issue for many years. In the scientific literature, there is an abundance of guidance , , , and recommendations , , , , , , , , , , , for the diagnosis of dermatomycoses and onychomycoses. However, little is known of the degree to which laboratories have adopted new technologies such as molecular identification tests and antifungal susceptibility testing of dermatophytes. Ireland has no national mycology reference laboratory and fungal skin, hair or nail infections are not notifiable diseases, so there is no oversight or co‐ordinated approaches to diagnosis and surveillance of these pathogens or their susceptibility to anti‐fungal agents. The aim of this study is to perform an evaluation of the dermatological mycology diagnostic service of our hospital and the other hospitals of Ireland, in comparison to similar services internationally, and recognised best practice.
METHODS 2.1 Ethics statement This study was approved by the Research Ethics Committee of University Limerick Hospital Group, Limerick, Ireland. 2.2 Setting The Department of Clinical Microbiology at University Hospital Limerick (UHL) provides a centralised microbiology service for six acute hospital sites of the region's hospital group, University of Limerick Hospitals' Group (ULHG). This service is provided to public and private healthcare facilities in the region including general practice, for a population of circa 400,000 people. Of note, there are no electronic patient records in this group of hospitals. Previous related research from our institution includes fungal bloodstream infections in our ICU patients, an epidemiological analysis of dermatomycoses and onychomycoses in our region over a period spanning 20 years, and several reports of multi‐resistant organisms detected in our hospitals, many of which resulted in outbreaks. , 2.3 Data and Analysis All mycology laboratory test counts from January 2001 to December 2021 were extracted from the Laboratory Information Management System (LIMS, iLab, Dedalus Healthcare, Italy), to provide an historical context to recent trends in the numbers of tests performed. For the period 2011–2021, a data extract of dermatology clinic attendance figures for the hospital was performed from the patient management system (iPMS, Dedalus Healthcare, Italy). Figures for the five‐year periods prior to and following July 2016 (when the change to testing methodology was implemented) were recorded. Similarly, a keyword search term count was performed of the patient clinical letters database (Filemaker Pro, Claris International) held at the dermatology clinic. The keywords ‘fungal’, ‘tinea’ and ‘onychomycosis’ were searched for in the letters of correspondence sent to general practitioners. The count of letters containing these keywords allowed a crude comparison to be made of the number of patients with these conditions seen in the periods before and after access to diagnostics was restricted. A survey was performed in all of the 28 public hospital Microbiology laboratories of Ireland to determine how many of those laboratories performed in‐house mycology testing of skin, nail and hair samples, and which of them routinely performed polymerase chain reaction (PCR) and/or susceptibility testing of dermatophytes and non‐dermatophyte moulds. The respondents were invited to supply test count data if they wished. This survey took the form of an e‐mail request in January 2022 and subsequent follow‐up of non‐responders. The pharmaceutical suppliers of the main dermatological anti‐fungal agents were contacted by e‐mail in January 2022, with follow‐up e‐mails for non‐responders. The companies were asked for details of the number of their unit sales per product for the Irish state and/or for the Mid‐West region of Ireland, especially data from 2011 to 2021 where possible. The companies were Brown and Burk IR Limited, GlaxoSmithKline Consumer Healthcare (Ireland) Limited, Novartis Ireland Limited, Viatris Global Healthcare T/A Mylan Limited, Johnson & Johnson Limited and Janssen Sciences Ireland. Data were analysed using Microsoft Excel.
Ethics statement This study was approved by the Research Ethics Committee of University Limerick Hospital Group, Limerick, Ireland.
Setting The Department of Clinical Microbiology at University Hospital Limerick (UHL) provides a centralised microbiology service for six acute hospital sites of the region's hospital group, University of Limerick Hospitals' Group (ULHG). This service is provided to public and private healthcare facilities in the region including general practice, for a population of circa 400,000 people. Of note, there are no electronic patient records in this group of hospitals. Previous related research from our institution includes fungal bloodstream infections in our ICU patients, an epidemiological analysis of dermatomycoses and onychomycoses in our region over a period spanning 20 years, and several reports of multi‐resistant organisms detected in our hospitals, many of which resulted in outbreaks. ,
Data and Analysis All mycology laboratory test counts from January 2001 to December 2021 were extracted from the Laboratory Information Management System (LIMS, iLab, Dedalus Healthcare, Italy), to provide an historical context to recent trends in the numbers of tests performed. For the period 2011–2021, a data extract of dermatology clinic attendance figures for the hospital was performed from the patient management system (iPMS, Dedalus Healthcare, Italy). Figures for the five‐year periods prior to and following July 2016 (when the change to testing methodology was implemented) were recorded. Similarly, a keyword search term count was performed of the patient clinical letters database (Filemaker Pro, Claris International) held at the dermatology clinic. The keywords ‘fungal’, ‘tinea’ and ‘onychomycosis’ were searched for in the letters of correspondence sent to general practitioners. The count of letters containing these keywords allowed a crude comparison to be made of the number of patients with these conditions seen in the periods before and after access to diagnostics was restricted. A survey was performed in all of the 28 public hospital Microbiology laboratories of Ireland to determine how many of those laboratories performed in‐house mycology testing of skin, nail and hair samples, and which of them routinely performed polymerase chain reaction (PCR) and/or susceptibility testing of dermatophytes and non‐dermatophyte moulds. The respondents were invited to supply test count data if they wished. This survey took the form of an e‐mail request in January 2022 and subsequent follow‐up of non‐responders. The pharmaceutical suppliers of the main dermatological anti‐fungal agents were contacted by e‐mail in January 2022, with follow‐up e‐mails for non‐responders. The companies were asked for details of the number of their unit sales per product for the Irish state and/or for the Mid‐West region of Ireland, especially data from 2011 to 2021 where possible. The companies were Brown and Burk IR Limited, GlaxoSmithKline Consumer Healthcare (Ireland) Limited, Novartis Ireland Limited, Viatris Global Healthcare T/A Mylan Limited, Johnson & Johnson Limited and Janssen Sciences Ireland. Data were analysed using Microsoft Excel.
RESULTS For the five‐year period 2011–2015, the median number of skin, hair and nail specimens for mycology analysis received in our laboratory from general practitioners (GPs) was 855 specimens per annum. For the corresponding period following the restriction of access to this service (2017–2021), the median test count was 35 specimens per annum (i.e., a 96% reduction). The positivity rate (microscopy and/or culture) of these samples increased from 36.5% to 40% across these two periods. The dermatology clinic of our hospital showed an increase from 54 specimens per annum to 117 specimens per annum (117% increase) for the same two time periods and a reduction in the positivity rate from 30% to 27%. See Figure for a chart of specimen requests per requesting location. Total dermatology clinic attendance figures showed a similar increase over the two time periods. The median annual attendance for the clinic in the pre‐curtailment period was 2320 and the corresponding figure post‐curtailment was 4570 attendances (97% increase). This increase was weighted more heavily in favour of paediatric patients (140% increase) rather than adult patients (94% increase). See Figure for a chart of annual attendance figures at the clinic. The results for the count of letters from the patient letters database of the dermatology clinic with matches for the specific search terms ‘fungal’, ‘tinea’ and ‘onychomycosis’ also showed an increase. The total number of letters per annum in the pre‐curtailment period was 65 letters (21 ‘fungal’, 39 ‘tinea’ and 5 ‘onychomycosis’), and there were 127 letters per annum (29, 83 and 15, respectively) in the post‐curtailment period – a 95% increase. See Figure for the number of matches for patient letters containing the search terms ‘fungal’, ‘tinea’ and ‘onychomycosis’, as well as the total number of patient letters recorded per annum in the clinic. In January to March 2022, a survey of the Microbiology laboratories of the public health service system (Health Services Executive) hospitals in the Republic of Ireland revealed that 10 of the twenty‐eight laboratories continue to perform in‐house fungal testing of skin, hair and nail samples. See Figure for a chart of the results of this survey. Nine laboratories refer their specimens to laboratories in larger hospitals in their region, often as part of a hub‐and‐spoke service that applies to many of the more specialised microbiology tests. Nine other laboratories refer their samples to a private reference facility for testing. Our laboratory was the only one of the six large (>600 beds) hospitals which did not provide in‐house testing of these samples. Medium‐sized hospitals were defined for this study as those accommodating 300–600 beds, and small hospitals were those with <300 beds. The bed capacity provides only a very rough estimate of the testing throughput of the laboratories; much of the testing workload comes from community healthcare facilities and general practice, which can vary widely for each hospital depending on their location. The laboratories were also asked whether they had curtailed access to their fungal testing of skin, hair and nails, and were invited to supply test count data. Two hospitals supplied 10 years of test count figures, one from the south of the country (‘Hospital B’) and one from the east of the country (‘Hospital C’), neither of which has had to restrict access to mycology diagnostic services, see Figure for details. Some laboratories reported that they did not provide microscopy results for some of their users (usually general practitioners), but access to fungal culture testing was only restricted by two laboratories (including ours). The second laboratory introduced this measure as a result of the surge in workload due to the Covid‐19 testing. In a follow‐up question to the above survey, the respondents were asked whether they had in‐house capability for either susceptibility testing or PCR testing of dermatophytes. One of the respondents had validated a PCR system but had not yet brought it into routine use, and two other hospitals had trials of systems in progress. As such, at the time of the survey there were no hospitals in Ireland with a dermatophyte PCR system available for routine use. None of the respondents had a susceptibility testing system in use, and since there is no national reference lab facility in Ireland, isolates would need to be sent to the United Kingdom for susceptibility testing if required. In February 2022, the following pharmaceutical companies were contacted for sales data (11 years of data if possible) on their dermatological anti‐fungal products, and their responses are included below: Brown and Burk IR Limited (oral griseofulvin): No response. GlaxoSmithKline Consumer Healthcare (Ireland) Limited (topical terbinafine): No data available. Novartis Ireland Limited (oral terbinafine): Data for 2017–2021 supplied. Viatris Global Healthcare T/A Mylan Limited (oral terbinafine): Data for 2018–2021 supplied. Johnson & Johnson (Ireland) Limited (topical miconazole, topical clotrimazole, topical ketoconazole, topical terbinafine): Data for 2017–2021 supplied. Janssen Sciences Ireland (topical miconazole and hydrocortisone): Data for 2017–2021 supplied. No data prior to 2017 were available, but the data provided for the period 2017–2021 (excluding Nailderm tablets) showed a 12.5% increase in product sales. The data for 2018–2021 (including Nailderm tablets) showed an 11% increase in product sales. Figure provides a chart of the volume of sales for each of the above products.
LIMITATIONS Local pharmacy sales data were not available for the study. The Primary Care Reimbursement Service (PCRS) was contacted for antifungal reimbursement claims data. No data were available by the time the study concluded.
DISCUSSION The incidence of fungal skin infections is increasing at an alarming rate worldwide. Increased incidence was demonstrated in our region by surrogate measures that were examined in this study: Anti‐fungal sales data and dermatology clinic records of confirmed or suspected infections both show double‐digit increases in the last 5 years. Furthermore, the twenty‐year records of test requests of skin, hair and nail samples show year‐on‐year increases right up to the point when access to testing was curtailed. It is evident from our patient letter counts (see Figure ) that patients with fungal‐related disorders represent a very small proportion of cases seen at our dermatology clinics, suggesting the main burden of disease and treatment management is in the community setting by general practitioners and pharmacists with curtailed access to appropriate mycological investigations. Reports of outbreaks involving dermatophytes are commonplace in the scientific literature; a PubMed search for ‘tinea’ and ‘outbreak’ for 2012–2021 provides 767 results. Tinea unguium or onychomycosis was the most common body site mentioned in the study title (50.3% of those with a site stated in the title, 172/342), followed by tinea capitis (27.8%, n = 95), tinea versicolor/corporis (7.9%, n = 27) tinea pedis (7.3%, n = 25) and tinea faciei (2.3%, n = 8). Where a geographical region is mentioned in the title ( n = 423), regions in Asia were the most common (24.8%, n = 105), followed by Africa (24.3%, n = 103), Europe (20.8%, n = 88), the Middle East (13/7%, n = 58), North and South America (4.7% and 10.2%, respectively) and Oceania (1.4%, n = 6). No recent reports of outbreaks are available from Ireland, although a study from Dublin in 2006 described a disproportionate (85.5%) number of patients of African extraction among their paediatric tinea capitis patients. Fungal outbreaks are not unknown on this island however; in 1948, a cluster of 368 tinea capitis cases were detected. Despite this, dermatophyte infections are not listed as a notifiable disease in this country, so there is no obligation to report them. A considerable shift in the epidemiology of dermatophytes has been demonstrated in our region in the last 20 years, with an increasing proportion of anthropophilic species detected from both skin or hair samples and from nail samples, and this has been mirrored in many other countries. , , , The migration of people, children in particular, during wartime has been linked with an increase in dermatomycoses. This has been reported in the former Yugoslavia during the war that took place there in the 1990s, and was previously reported after the second world war, when dermatomycoses spread epidemically. At the time of writing, more than 14 million people have fled Ukraine due to the war taking place there, many of them women and children. It is important now more than ever that dermatomycoses are monitored and identified to prevent large outbreaks from occurring. The results of this study demonstrated a dramatic reduction in the processing of specimens for fungal analysis from GPs after curtailment of mycology diagnostic services. The corresponding increase in dermatology clinic samples did not fill the gap left by this drop in community specimens, which could be explained in part by patients being treated for fungal infection without appropriate diagnostic confirmation, or being left untreated because of the lack of access to diagnostics. Clinical papers , , and dermatology guidelines unanimously call for laboratory confirmation of fungal infection before oral treatment of onychomycosis is started. Clinical findings, nail disease pattern and mycological investigations are important in the treatment of onychomycosis (fungal nail disease); in particular topical treatments are most effective in superficial onychomycosis but often ineffective in subungual or dystrophic onychomycosis with prolonged courses of systemic antifungals required to eradicate infection. Additionally, diagnosis of onychomycosis can be challenging, with similar clinical features seen in non‐dermatophyte nail infections, and non‐infectious conditions such as psoriasis, chronic trauma, lichen planus and nail bed malignancies. Antifungal medications are known to have multiple potential side effects and drug interactions, so prolonged courses in the absence of dermatophyte confirmation is not advised. Mycological identification not only supports diagnosis, it influences antifungal therapy choice and in select cases provides susceptibility information for recalcitrant infections. , Despite the recommendations for microbiological confirmation, investment in fungal diagnostics in this country has been poor. Just 10 of the twenty‐eight laboratories surveyed had in‐house mycology testing capabilities for skin, hair and nail samples, and none reported access to in‐house PCR or susceptibility testing of dermatophytes. Antifungal resistance has been called a ‘global public health threat’. , This is exemplified in India where terbinafine resistant T . indotineae are highly prevalent, and terbinafine resistance in dermatophytes has also been reported in Iran, Japan, Denmark, Belgium, Finland, Switzerland, Germany, the United States, Canada, Bahrain and Brazil. Terbinafine resistance is especially concerning because alternative therapeutic options to treat dermatophytoses are limited. Antifungal resistance is also probably underestimated, since many countries, including our own, have not been performing susceptibility testing. Susceptibility testing of dermatophytes isolated from recalcitrant infections is imperative, , , , so access to this capability should be a priority for our diagnostic services. This would be most readily achieved by the creation of a mycology reference lab for the country, a resource that no national health service should be without. For such testing, current practice in our institution is the transfer of samples overseas to The Mycology Reference Laboratory in Bristol, United Kingdom. This further compounds costs to the health service and delays timely diagnosis. MALDI‐TOF MS (matrix‐assisted laser desorption/ionisation time‐of‐flight mass spectrometry) instrumentation has been reported to be capable of identifying dermatophytes, , although not yet to the same level of accuracy achieved by conventional methods. The availability of these instruments in most modern microbiology laboratories may mean that in the future the identification of fungal pathogens may not need to be a laborious and subjective methodology, and should make it easier for smaller laboratories to implement mycology testing without the specialised knowledge and experience required to identify fungi visually (macroscopically and microscopically). Nucleic acid amplification tests have replaced many of the conventional diagnostic techniques of the microbiology laboratory, and mycology testing is no exception. The poor sensitivity of microscopy and culture, particularly after the onset of empirical treatment and the long turnaround time for culture results give PCR testing a distinct advantage over traditional methods. There is an abundance of published research available evaluating dermatophyte PCR systems, but consensus has yet to be achieved on their applicability. The earliest publications , described PCR as a supplement to culture for assisting organism identification; later publications give a more prominent role to PCR but still suggest that classical methods ‘are still warranted for training purposes and when encountering specific diagnostic problems’. More recently however we see a publication suggesting that PCR can ‘replace microscopy and culture for routine dermatophyte diagnosis’, but another author regarding the same PCR platform says that direct microscopy ‘remains relevant’ for these specimens. The Netherlands National Healthcare Institute report a higher predictive value for the PCR test over direct microscopy and culture, and they recommend that it should therefore replace traditional diagnostics in routine care. Many in‐house PCR systems have been developed, some even achieving ISO 15189 accreditation, but the most straightforward process for introducing a PCR system is via a ‘CE‐IVD’ marked commercial kit; some commercial kits are available that have not been fully evaluated (‘research use only’), these should not be used for routine diagnosis. There are four ‘CE‐IVD’ marked dermatomycosis PCR platforms from three manufacturers available for use in Ireland currently: ‘Dermagenius® 2.0’ and ‘Dermagenius® 3.0’ (Pathonostics®), ‘EUROArray Dermatomycosis’ (EUROImmun) and ‘Dermatophytes and Other Fungi 12‐Well’ (AusDiagnostics). All four platforms have been described previously. , , , , , , , , See Table for a summary of the dermatological fungal isolates captured by each of these kits, and a full list of targets is available in the Appendix . Details are also available in the Appendix for another kit which is currently marked ‘Research Use Only’: ‘Novaplex tm Dermatophyte Assay’ (Seegene). Other studies have shown that the widespread use of over‐the‐counter antifungals may be promoting resistance, most notably to the azole drugs, which can mean that oropharyngeal, vaginal or even systemic yeast infections may need to be treated with less desirable alternatives such as amphotericin B with possible complications and renal toxicity. The increased use of immunosuppressive therapy means that invasive fungal infections are an emerging problem worldwide, and the incidence of azole resistance is increasing. , Our data show significant use of topical azole creams and powders in this country; over 700,000units purchased by a population of 5 million people in 2021. Dermatological mycology testing has not been prioritised in many laboratories around the world, including our own, yet there is growing international evidence of increased incidence of infections and resistance to anti‐fungal agents. In Ireland, we have a growing population and increasing immigration, yet the testing capacity of our laboratories are being curtailed, susceptibility testing of dermatophytes is not being performed and new technologies have not been adopted. Furthermore, there is suboptimal epidemiological tracking of organisms and their antifungal susceptibilities, and there is no national oversight. Dermatological fungal infections are commonly misconceived as a cosmetic problem, but left untreated they can cause pain, physical impairment, increased risk of infections such as cellulitis and osteomyelitis in immunocompromised or diabetic patients, and a significant negative impact on quality of life. Recently, the WHO published a list of fungal priority pathogens causing systemic invasive infections, in this report, they suggest that future reports will include those causing dermatomycoses, highlighting the economic and health impact of the same. This study serves to highlight the need for improvement of current national practices in dermatological mycology testing, and proposes practical steps toward improving them.
JP: Conceptualisation (equal); Writing–original draft (lead); Data curation (lead); Methodology (lead); Writing–review and editing (equal). EP: Conceptualisation (equal); Writing–original draft (supporting); Writing–review and editing (equal); SR: Writing–original draft (supporting); Writing–review and editing (equal). SF: Conceptualisation (equal); Writing–original draft (supporting); Writing–review and editing (equal). NOC: Conceptualisation (equal); Writing–original draft (supporting); Writing–review and editing (equal). CPD: Conceptualisation (equal); Writing–original draft (supporting); Writing–review and editing (equal).
This study was performed as part of a PhD program for the lead author (JP). Funding for the PhD was provided by University Hospital Limerick and the Corresponding Author at the University of Limerick.
The authors certify that they have no affiliations with or involvement in any organisation or entity with any financial interest, or non‐financial interest in the subject matter or materials discussed in this manuscript that would constitute a conflict of interest.
All the authors have revised the manuscript critically and have approved the final draft.
Appendix S1 Click here for additional data file.
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Level of PAX5 in differential diagnosis of non-Hodgkin's lymphoma | c849027c-3383-4121-a312-28874c905bd2 | 5080925 | Pathology[mh] | This study was conducted in the Institute of Medical Sciences, Banaras Hindu University, Varanasi, India, during February 2009 to January 2012. The study protocol was approved by the institutional ethics committee. Immunohistochemical analysis and TUNEL (Terminal deoxynucleotidyl transferase dUTP nick end labelling) assay : Majority of the biopsy samples were obtained by excision of cervical lymph nodes whereas some of them were obtained from auxiliary lymph node excision. Biopsy samples of 65 patients with confirmed NHL were collected. Samples were fixed with 4 per cent formaldehyde overnight and then embedded in paraffin wax. Serial (5 μm thick) sections were de-paraffinized and re-hydrated in alcohol downgrade series. The sections were fully hydrated for 30 min and stained with haematoxylin followed by differentiation in acid water. The sections were dehydrated in upgrade alcohol serries and stained with eosin for histological evaluation. For immunohistochemical analysis, sections were rehydrated by alcohol downgrade series and then in running water. Antigen retrieval was done in 0.1 per cent trypsin for 10 min and blocked with 1 per cent bovine serum albumin (BSA) followed by treatment of primary antibody at 1:200 dilutions for 4-6 h or overnight at 4°C. The sections were washed with phosphate buffered saline (PBS) and incubated with horseradish peroxidase (HRP) conjugated secondary antibody as per protocol of super sensitive polymer-HRP IHC detection system (BioGenex, USA). In this study primary antibodies anti-cABL, anti-CD19, anti-CD3, anti-Ras, anti-Raf (Abcam, UK), anti-PAX5, and anti-p53 (Santacruz Biotech, USA) were used. TUNEL assay was performed for the detection of apoptotic bodies in NHL biopsy sections, using Apo-Brdu-IHC™ In Situ DNA Fragmentation Assay Kit (BioVision, Inc, USA). Analysis of expression pattern of markers by reverse transcriptase polymerase chain reaction (RT-PCR) : Total RNA was extracted from biopsy samples of NHL patients by PureLink RNA Mini kit (Life technologies, USA) using manufacturer's protocol. One microgram of total RNA was reverse transcribed in 20 μl reaction mixture using oligo-dT primer according to the protocol for first strand cDNA synthesis kit (Fermentas, USA). The resulting cDNA was used as a template for PCR. All reactions were done in triplicate. The expression levels of PAX5 , ZAP70 , CD19 , Ras , Raf , MAPK , p53 and HIF-1-alpha (hypoxia inducible factor -1α subunit) were studied with the gene specific sets of primers and normalized against β- actin internal control gene . The gene specific primers used here were self designed and validated. Protein expression pattern by Western blotting : The extract of biopsy samples was prepared in Tris-Cl 0.1M, p H 7.2, containing protease inhibitor. 50 μg protein was resolved on 10 per cent denaturing poly-acrylamide gel using standard method . The polypeptide pattern was immobilized on polyvinylidene difluoride (PVDF) membrane, and probed with primary antibodies, anti-CD19, anti-CD3 (Abcam), anti-PAX5, and anti-p53 (Santacrutz Biotech., USA) after blocking with 5 per cent non-fat milk in PBS. Detection was done with electrochemiluminescence (ECL)-system (supersignal west pico chemiluminescent substrate, Thermo Scientific, USA) with HRP-conjugated secondary antibody. β-actin (Sigma - Aldrich, Inc., USA) was used as the reference protein for constitutive expression. Lactate dehydrogenase (LDH) specific staining : Native polyacrylamide gel (8.0%) electrophoresis was performed to analyze LDH isoforms and enzyme activity of lymph nodes from NHL patients. Gels were stained for LDH specific activity as described earlier .
Of the 65 patients, 43 (66%) were diagnosed as NHL and classified into different types of NHL according to the WHO classification . Of the 43 NHL patients, 20 (46.5%) showed T-cell type NHL and 23 patients (53.5%) showed B-cell type NHL. Of the 23 B-cell type NHL, eight patients showed high grade large cell B-cell type NHL, seven showed mature B-cell type NHL, five showed intermediate B-cell type NHL, and one patient showed follicular type B-cell NHL . The case histories of patients, their diagnosis and immunophenotypic analysis of their biopsy samples showed variable penetrance and expressivity of NHL. One patient having intestinal lymphoma but no tumour cells in lymph nodes showed preserved architecture with germinal centre (Fig. - ). Patient P1 presented with diffuse superficial and deep lymphadenopathy showed effacement of the architecture by the monotonous population of atypical lymphoid cells with opened up nuclei (Fig. - ). Lymph node from lymphoma patient P2 showed loose clusters of cells and necrosis in whole tissue (Fig. - ). The lymph nodes of patients showed immunoreactive cells for PAX5 (77%), CABL (66%), CD19 (77%), CD3 (77%), Raf (88%), Ras (100%), and p53 (100%) (Fig. - ). To observe the effect of progression of NHL on the apoptosis, TUNEL assay was performed with the sections of biopsy samples of NHL patients. shows a representative micrograph of TUNEL positive cells. Levels of transcripts of PAX5, CD19, ZAP70, p53, HIF1A, MAPK, Ras and Raf in NHL patients : The levels of transcripts of PAX5 and associated markers CD19 , ZAP70 , p53 , HIF1A , MAPK , Ras and Raf were found altered in NHL patients . The PAX5 expression could only be observed in patient P2, whereas MAPK and Raf were detected only in patients P2 and P3. The other candidates ( CD19 , ZAP70 , p53 , Ras and HIF1A ) showed variable expression in different patients. CD19 and ZAP70 were relatively higher in P2 and P3 than in P1 and P4 patients. The p53 and HIF1A showed higher expression in patient P2 than patients P1, P3 and P4 . The expression patterns of PAX5 (25%) and associated markers CD19 (100%), ZAP70 (100%), p53 (75%), HIF1A (100%), MAPK (50%), Ras (75%) and Raf (50%) were variable. The Western blot analysis of patient samples showed presence of PAX5 (66%), CD3 (33%), CD19 (66%), and all patients showed presence of p53 . Modulation of LDH isoforms : The results of enzyme-specific staining of LDH of NHL patients showed modulation of LDH isoforms . Patient P1 showed three isoforms of LDH i.e. , LDH4, LDH3, and LDH2 while the patient 2 (P2) showed four isoforms of LDH including LDH5, LDH4, LDH3, and LDH2. The reactive or control lymph node showed only three isoforms of LDH including LDH3, LDH4, and LDH5 at detectable level . The activities of LDH isoforms LDH3, LDH4 and LDH5 were higher in P2 while that of LDH2 was higher in P1. While some of them showed all the five LDH isoforms (LDH1, LDH2, LDH3, LDH4 and LDH5), LDH2 and LDH3 were absent in P15. LDH4 was absent in P12, P14 and P15. LDH5 was absent in P12, P14 and P19 .
The NHL covers about 90 per cent of diagnosed lymphomas that affect lymph nodes, spleen, bone marrow and other organs of immune system . Distinction between histologically similar tumours is often critical as therapeutic options often differ . The expression of PAX5, and CD19 was detectable in a few cases by both immunohistochemistry and Western blot analysis. Since PAX5 also regulates expression of p53 in haematopoietic cells, it was interesting to observe presence of p53 in lymph nodes of lymphoma bearing patients. It is known that overexpression of wild type p53 induces cells to express cytoplasmic immunoglobulin heavy chain and a B-cell specific antigen . Co-expression of both T- and B-cell markers was in agreement with expression patterns of neoplastic T-cells showing positive signals for CD3, CD4, CD5, CD8, CD45, and CD20 and negative signals for other B-cell markers such as CD79a and PAX5 . Some specific type of B-cell lymphomas show negative staining for CD20 while some T-cell lymphomas show positive staining for CD20 . It is suggested that although CD markers are specific to particular cell types but in neoplastic conditions their expression becomes non-specific . The expression of B- and T-cell markers may not be aberrant but indicative of an antigenic phenotype present on small population of cells. The expression of PAX5, CD19 and CD3 in these cases recapitulated the conditional Pax5 deletion in mice that allowed mature B-cell from peripheral lymphoid organs to dedifferentiate in vivo back to uncommitted progenitors in the bone marrow, which rescued T lymphopoiesis in the thymus of T cell deficient mice . The Pax5 and its isoforms are well known for normal B-cell development and differential modulation of Pax5 is suggested in case of malignancies . The expression of PAX5 in immunohistochemistry and Western blot suggested its promising role in B-cell specific NHL. However, the co-expression of PAX5, CD19, p53, Ras and Raf indicates involvement of Ras-Raf mediated pathway influenced by PAX5 . The LDH activity was elevated because glucose was used as main energy source through glycolysis. Kimura et al have reported a relationship between expression of CD19 and level of LDH in B-cell lymphoma that may be associated with energy transduction and redox-sensitive factor, PAX5. The modulation of activity of LDH isoforms in lymphoma may be due to induced hypoxic condition. The elevated activity of LDH5, LDH4 and LDH3 could be due to differences in the rate of synthesis, degradation or excretion of the enzymes in lymphoma. A tumour-induced cachexia and metabolic inefficiency is also presumed . In conclusion, the analysis of cell types and immunoreactivity showed various types of cells including lymphocytes and medullar sinuses. The variable immunoreactivity of markers in patients indicated mixed type of lymphoma. The expression levels of PAX5 , CD19 , CD3 , p53 , Ras , Raf , ZAP70 , HIFIA , and MAPK indicated involvement of Ras-Raf mediated pathway influenced by PAX5. The modulation of activity of LDH isoforms (LDH2) may be due to induced hypoxic condition. Almost all patients were p53 positive but variable TUNEL positivity indicated p53 independent apoptosis. The patients with NHL may be tested for molecular markers and differential diagnosis with PAX5, CD19 and ZAP70 to decide appropriate therapy of NHL.
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High intensity perturbations induce an abrupt shift in soil microbial state | a264d6b6-bd0f-42f6-ac28-959e926342d5 | 10690886 | Microbiology[mh] | Natural ecosystems are constantly exposed to natural fluctuations in environmental conditions and under such conditions they retain a stable equilibrium state, or quasi-stable state, characterised by minor fluctuations in community composition and function . However, human-induced perturbations, including those related to climate change, can destabilise this dynamic equilibrium and potentially trigger a cascade of events that may lead to an abrupt change . This is particularly relevant in a warmer world, where the speed of soil drying is increasingly higher and multiple combined climate change factors interact . Abrupt transitions occur when an ecosystem surpasses a certain threshold, which can have important consequences for ecosystem functioning . Numerous studies have demonstrated the existence of abrupt changes in aquatic ecosystems , terrestrial plant communities , and the human gut microbiome in response to perturbations . However, abrupt transitions in soil microbial communities have so far received little attention , despite their fundamental role in terrestrial ecosystems, driving key processes of organic matter decomposition, nutrient cycling, and carbon and nutrient storage , which regulate ecosystem productivity. As such, abrupt shifts in soil microbial communities in response to perturbations may have significant implications for soil functioning, with consequences for ecosystem services, such as food production and climate regulation . Soil microbial communities are increasingly challenged by perturbations associated with human-induced environment change, including intense “pulse” perturbations caused by climate extremes (e.g., droughts, heat waves and floods), which are predicted to increase in frequency and intensity with ongoing climate change . Microbial communities can withstand such pulse perturbations in different ways. In this context, resistance is defined as the degree to which microbial community attributes change in the face of a perturbation, and resilience as the rate at which they recover from it . Thus, if the attributes (i.e., structure and function) of a microbial community stay stable following a perturbation, it is considered resistant , whereas if its attributes change, but it recovers to its original configuration over time, it is considered resilient . Additionally, if the ecosystem processes remain stable whereas microbial community composition changes, this points to functional redundancy within the microbial community . However, evidence is mounting that different microbial groups vary in their resistance and resilience to drought [ – ], and while intense droughts can de-stabilise soil bacterial networks, potentially rendering them more vulnerable to subsequent drought, soil fungal networks appear to be more resistant . Frequent, recurring droughts can also lead to soil microbial communities becoming more resistant to drought [ – ], although repeated dry-wet cycles can induce shifts in the functional state of agricultural soils, measured as soil respiration . Similarly, high intensity drought has been shown to cause abrupt shifts in peatland moisture characteristics and plant-fungal interactions , although evidence of thresholds beyond which soil microbial communities have no resilience to drought, leading to abrupt shifts in their taxonomic and functional attributes, is lacking. Here, we experimentally tested whether increases in the intensity and frequency of drought pulses can trigger an abrupt and persistent shift in the structural and functional attributes of natural grassland soil microbial communities. We also tested for the existence of a drought intensity and/or frequency threshold after which the soil microbial community shifts to a functionally and structurally different state. Moreover, we tested whether the bacterial and fungal communities showed any adaptation in their growth characteristics to the drying/rewetting cycle. To achieve this, we carried out an incubation experiment whereby we imposed a matrix of drought frequency and intensity treatments on a natural grassland soil. Microbial responses were assessed with a broad range of taxonomic and functional attributes of microbial communities over an extended period of time after returning soils to their original moisture condition. This enabled us to test for abrupt shifts in soil microbial communities that persisted under the same environmental conditions after the end of the perturbation. We hypothesised that soil microbial communities exposed to more intense and frequent droughts will show a lower resistance and resilience than those subject to milder, less frequent droughts. We also hypothesised that this lower resistance and resilience of microbial communities to more intense, frequent droughts will induce a shift in microbial taxonomic and functional state.
Soil collection and experimental design A pot experiment was designed to test the effects of drought intensity and frequency (3 levels each, full factorial including a well-watered control, Fig. ), on the microbial communities of a natural grassland soil. Soil was collected from Selside, Yorkshire Dales (54.17 N, 2.34 W), from four independent plots (replicates). These plots correspond to the control plots in the experiment detailed elsewhere . The soils are part of the Malham Series of Eutric Endoleptic Cambisols; a clayey brown earth . Chemical characteristics of the soil are shown in Table . The sampled soil was sieved and divided into pots. Pots were incubated at 18 °C, 30% air relative humidity, and kept at 65% water holding capacity (WHC), which correspond to ~40% volumetric water content. After 3 weeks of stabilisation, drought treatments were applied by reducing watering, reaching three selected drought intensity levels. A mild drought treatment (40% WHC, 23% volumetric water content) corresponded to average values of soil moisture during summer (June–August), an intermediate drought level (23% WHC, 14% volumetric water content) corresponded to common summer drought events (once every 4 years), and a high intensity drought level (11% WHC, 7% volumetric water content) corresponded to a once in a century drought in the studied ecosystem. Additional details can be found in SI methods. The drying period lasted for 2 weeks followed by 2 weeks of recovery, when pots were slowly rewetted to optimum moisture (65% WHC). All soils dried out at the very similar pace (Fig. ). Drought was repeated up to 3 times depending on the drought frequency treatment. Control pots were always kept at 65% WHC (Fig. ). Immediately after the last drought cycle, samples were collected to evaluate the resistance of the system. We consider the perturbation to be the entire drying/rewetting cycle, and thus, to evaluate the resistance we harvested the pots once the perturbation had ended (when all pots recovered to the same WHC, 11 days after the start of the rewetting, Fig. ). Additionally, pots were harvested over time, to evaluate the resilience of the system in the long term (1, 3, and 6 months after drought, Fig. ), which covers the length of the typical growing season for the study site where soil was collected in the Yorkshire Dales (Met Office UK). During this whole period, pots were kept at optimum soil moisture (65% WHC). 40 extra pots were harvested 1 month after drought to evaluate the adaptation of microbial growth characteristics to drought. Total number of pots: 200. Microbial community structure Soil samples were collected in Eppendorf tubes (approx. 0.25 g) and frozen at -80 °C immediately after sampling. DNA was extracted in frozen samples, without thawing, with PowerSoil DNA isolation Kit (Qiagen, Germany). DNA was sent to Macrogen sequencing service (Macrogen Inc., Korea), for sequencing on a MiSeq v3 (Illumina). Fungal diversity was evaluated by ITS2 sequencing, using the primer pair 5.8S-Fun and ITS4-Fun . Bacterial diversity was evaluated by 16 S rRNA gene V3-V4 sequencing, with primers Bakt_341F and Bakt_805R . Microbial community analysis was not done in samples from the 3 months after drought time point. Alongside the samples, three extraction blanks were included and a mock community sample for each primer pair: 19 strains genomic DNA even mix from Bakker lab for fungi , and MSA-1000 10 strain even mix genomic material for bacteria from the American Type Culture Collection (ATCC, Manassas, US). Sequences were analysed using the DADA2 pipeline . Taxonomic identification was performed by IDTAXA taxonomic classification method in DECIPHER package using UNITE 7.2 reference database for fungi and SILVA release 138 database for bacteria. See SI methods for full details. After filtering, de-noising and refining steps, final databases contained 2760 amplicon sequence variants (ASVs) and 4,316,693 reads for fungi, and 7313 ASVs and 2,383,395 reads for bacteria. Mean sampling depth was 36,275 reads in fungi and 19,937 reads in bacteria. Soil functionality Soil functionality was assessed by measuring soil enzymatic activities and different soil nutrient pools, as indicators, among others, of soil organic matter decomposition capacity, nutrient cycling capacity, soil fertility, available stocks of energy for microbial process, and soil carbon and nutrient storage capacity . β -glucosidase (GLC), cellobiohydrolase (CBH), xylosidase (XYL), N -acetylglucosaminidase (NAG), and acid phosphatase (PHO) were measured photometrically using p NP-linked substrate analogues . Urease (URE) was evaluated by the production of ammonium after urea addition to soils, following the optimised high throughput method . Phenoloxidase (POX) and peroxidase (PER) activities were measured photometrically by the oxidation of L -DOPA . See SI methods for full details. All enzymes were measured in fresh soil, kept at 4 °C, within five days from harvest. Different nutrient pools were measured by means of soil extractions with different extracting solutions depending on the nutrient and the pool of interest . Dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) were evaluated in water extracts and plant available nitrogen (ammonium and nitrate) were evaluated in 1 M KCl extracts. Plant available P was extracted with 2.5% acetic acid solution and total organic P (TOP) was estimated by evaluation of available phosphate before and after sample ignition at 550 °C for 4 h, and extracted with 0.5 M H 2 SO 4 . Microbial biomass nutrients were measured using fumigation–extraction techniques. Microbial C and N were measured after fumigation with CHCl 3 and extraction with 0.5 M K 2 SO 4 . Microbial P was estimated by fumigation with hexanol and extraction with anion-exchange membranes . Microbial C, N, and P were calculated as the difference in C, N, and P between fumigated and un-fumigated samples, and they were converted to microbial biomass using k EC factor of 0.35 for C , k EN factor of 0.54 for N , and k EP factor of 0.40 for P . Microbial P was further corrected by sorption percentage using spiked samples. After extraction, N pools were measured in AA3 HR Auto Analyser (Seal Analytical, UK) while C pools were measured in 5000 A TOC-L analyser (Shimadzu, Japan). P pools were detected by molybdate colorimetry in a CLARIOstar plate reader (BMG Labtech, Germany). All soil nutrients were measured in fresh soil (except organic P), kept at 4 °C, within two weeks from harvest, including extraction and measurement of extracts. Nutrients were evaluated in duplicates, and reported values are the mean of those two analytical replicates. See SI methods for full details. Microbial functional adaptation to drying/rewetting cycles Microbial adaptation to a subsequent dry-wet cycle was assessed using a two-tiered approach. First, the moisture dependence of microbial growth and respiration were assessed. To do so, soils were air dried under a ventilator until they reached constant weight. During the drying down, to assess how microbial functions were inhibited by lack of moisture, soils were subsampled every 2–3 h, and gravimetric water content, microbial growth and respiration were measured. Microbial growth rates were measured by radioisotope incorporation . For bacterial growth, the rate of protein production was estimated using 3 H-leucine incorporation into bacteria following homogenisation/centrifugation with modifications as described previously . Fungal growth rates were assessed by tracing 14 C-acetate incorporation into the fungal-specific lipid ergosterol . To measure soil respiration, 1.0 g of soil was weighed into 20 ml glass vials, which were purged with pressurised air, sealed with crimp caps and incubated. CO 2 production was measured using a gas chromatograph equipped with a methaniser and a flame-ionisation detector. A logistic model was then fitted to the inhibition curves describing the relationship between microbial growth or respiration rates and moisture , and microbial tolerance to drought was estimated using IC 10 values (moisture level at which the microbial function is inhibited by 10%), with lower values of IC 10 indicating higher drought tolerance. Second, air dried soils were rewetted to 60% WHC in order to evaluate microbial responses to rewetting. After rewetting, microbial growth rates, along with respiration, were measured with a high temporal resolution of approximately 6 h for a week (more frequent at the beginning and every 24 h afterwards, 12 time points in total), as previously described. Cumulative bacterial growth, fungal growth, and respiration during 1 week after rewetting was calculated. Furthermore, in all soils, bacterial growth exhibited a lag period of no growth before the growth rates started increasing exponentially, which has been previously observed . These growth response patterns were therefore modelled using a Gompertz curve, which was then used to calculate the lag periods before the increase in growth rate . Statistical analyses All statistical analyses were done in R v4.0 . To evaluate microbial community structure, we investigated alpha diversity, ordination analyses, proportion of different taxa and functional guilds, and indicator species analysis. Resistance and resilience of soil functions were evaluated with a linear regression analysis between the value of the variable under drought and time after drought. The value of the intercept was used as a resistance index (RS), and the value of the slope as a resilience index (RL). Soil functional data (soil extracellular enzymes and nutrient pools) were analysed with a non-metric multidimensional scaling (NMDS) ordination analysis. Multifunctionality index was calculated with all the soil enzymatic activities, which represent the organic matter decomposition capacity of soils. The effects of drought intensity and frequency on all variables were analysed by linear mixed effect models (LME) with drought intensity and frequency as fixed factors and soil replicate as random factor. See SI methods for full details.
A pot experiment was designed to test the effects of drought intensity and frequency (3 levels each, full factorial including a well-watered control, Fig. ), on the microbial communities of a natural grassland soil. Soil was collected from Selside, Yorkshire Dales (54.17 N, 2.34 W), from four independent plots (replicates). These plots correspond to the control plots in the experiment detailed elsewhere . The soils are part of the Malham Series of Eutric Endoleptic Cambisols; a clayey brown earth . Chemical characteristics of the soil are shown in Table . The sampled soil was sieved and divided into pots. Pots were incubated at 18 °C, 30% air relative humidity, and kept at 65% water holding capacity (WHC), which correspond to ~40% volumetric water content. After 3 weeks of stabilisation, drought treatments were applied by reducing watering, reaching three selected drought intensity levels. A mild drought treatment (40% WHC, 23% volumetric water content) corresponded to average values of soil moisture during summer (June–August), an intermediate drought level (23% WHC, 14% volumetric water content) corresponded to common summer drought events (once every 4 years), and a high intensity drought level (11% WHC, 7% volumetric water content) corresponded to a once in a century drought in the studied ecosystem. Additional details can be found in SI methods. The drying period lasted for 2 weeks followed by 2 weeks of recovery, when pots were slowly rewetted to optimum moisture (65% WHC). All soils dried out at the very similar pace (Fig. ). Drought was repeated up to 3 times depending on the drought frequency treatment. Control pots were always kept at 65% WHC (Fig. ). Immediately after the last drought cycle, samples were collected to evaluate the resistance of the system. We consider the perturbation to be the entire drying/rewetting cycle, and thus, to evaluate the resistance we harvested the pots once the perturbation had ended (when all pots recovered to the same WHC, 11 days after the start of the rewetting, Fig. ). Additionally, pots were harvested over time, to evaluate the resilience of the system in the long term (1, 3, and 6 months after drought, Fig. ), which covers the length of the typical growing season for the study site where soil was collected in the Yorkshire Dales (Met Office UK). During this whole period, pots were kept at optimum soil moisture (65% WHC). 40 extra pots were harvested 1 month after drought to evaluate the adaptation of microbial growth characteristics to drought. Total number of pots: 200.
Soil samples were collected in Eppendorf tubes (approx. 0.25 g) and frozen at -80 °C immediately after sampling. DNA was extracted in frozen samples, without thawing, with PowerSoil DNA isolation Kit (Qiagen, Germany). DNA was sent to Macrogen sequencing service (Macrogen Inc., Korea), for sequencing on a MiSeq v3 (Illumina). Fungal diversity was evaluated by ITS2 sequencing, using the primer pair 5.8S-Fun and ITS4-Fun . Bacterial diversity was evaluated by 16 S rRNA gene V3-V4 sequencing, with primers Bakt_341F and Bakt_805R . Microbial community analysis was not done in samples from the 3 months after drought time point. Alongside the samples, three extraction blanks were included and a mock community sample for each primer pair: 19 strains genomic DNA even mix from Bakker lab for fungi , and MSA-1000 10 strain even mix genomic material for bacteria from the American Type Culture Collection (ATCC, Manassas, US). Sequences were analysed using the DADA2 pipeline . Taxonomic identification was performed by IDTAXA taxonomic classification method in DECIPHER package using UNITE 7.2 reference database for fungi and SILVA release 138 database for bacteria. See SI methods for full details. After filtering, de-noising and refining steps, final databases contained 2760 amplicon sequence variants (ASVs) and 4,316,693 reads for fungi, and 7313 ASVs and 2,383,395 reads for bacteria. Mean sampling depth was 36,275 reads in fungi and 19,937 reads in bacteria.
Soil functionality was assessed by measuring soil enzymatic activities and different soil nutrient pools, as indicators, among others, of soil organic matter decomposition capacity, nutrient cycling capacity, soil fertility, available stocks of energy for microbial process, and soil carbon and nutrient storage capacity . β -glucosidase (GLC), cellobiohydrolase (CBH), xylosidase (XYL), N -acetylglucosaminidase (NAG), and acid phosphatase (PHO) were measured photometrically using p NP-linked substrate analogues . Urease (URE) was evaluated by the production of ammonium after urea addition to soils, following the optimised high throughput method . Phenoloxidase (POX) and peroxidase (PER) activities were measured photometrically by the oxidation of L -DOPA . See SI methods for full details. All enzymes were measured in fresh soil, kept at 4 °C, within five days from harvest. Different nutrient pools were measured by means of soil extractions with different extracting solutions depending on the nutrient and the pool of interest . Dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) were evaluated in water extracts and plant available nitrogen (ammonium and nitrate) were evaluated in 1 M KCl extracts. Plant available P was extracted with 2.5% acetic acid solution and total organic P (TOP) was estimated by evaluation of available phosphate before and after sample ignition at 550 °C for 4 h, and extracted with 0.5 M H 2 SO 4 . Microbial biomass nutrients were measured using fumigation–extraction techniques. Microbial C and N were measured after fumigation with CHCl 3 and extraction with 0.5 M K 2 SO 4 . Microbial P was estimated by fumigation with hexanol and extraction with anion-exchange membranes . Microbial C, N, and P were calculated as the difference in C, N, and P between fumigated and un-fumigated samples, and they were converted to microbial biomass using k EC factor of 0.35 for C , k EN factor of 0.54 for N , and k EP factor of 0.40 for P . Microbial P was further corrected by sorption percentage using spiked samples. After extraction, N pools were measured in AA3 HR Auto Analyser (Seal Analytical, UK) while C pools were measured in 5000 A TOC-L analyser (Shimadzu, Japan). P pools were detected by molybdate colorimetry in a CLARIOstar plate reader (BMG Labtech, Germany). All soil nutrients were measured in fresh soil (except organic P), kept at 4 °C, within two weeks from harvest, including extraction and measurement of extracts. Nutrients were evaluated in duplicates, and reported values are the mean of those two analytical replicates. See SI methods for full details.
Microbial adaptation to a subsequent dry-wet cycle was assessed using a two-tiered approach. First, the moisture dependence of microbial growth and respiration were assessed. To do so, soils were air dried under a ventilator until they reached constant weight. During the drying down, to assess how microbial functions were inhibited by lack of moisture, soils were subsampled every 2–3 h, and gravimetric water content, microbial growth and respiration were measured. Microbial growth rates were measured by radioisotope incorporation . For bacterial growth, the rate of protein production was estimated using 3 H-leucine incorporation into bacteria following homogenisation/centrifugation with modifications as described previously . Fungal growth rates were assessed by tracing 14 C-acetate incorporation into the fungal-specific lipid ergosterol . To measure soil respiration, 1.0 g of soil was weighed into 20 ml glass vials, which were purged with pressurised air, sealed with crimp caps and incubated. CO 2 production was measured using a gas chromatograph equipped with a methaniser and a flame-ionisation detector. A logistic model was then fitted to the inhibition curves describing the relationship between microbial growth or respiration rates and moisture , and microbial tolerance to drought was estimated using IC 10 values (moisture level at which the microbial function is inhibited by 10%), with lower values of IC 10 indicating higher drought tolerance. Second, air dried soils were rewetted to 60% WHC in order to evaluate microbial responses to rewetting. After rewetting, microbial growth rates, along with respiration, were measured with a high temporal resolution of approximately 6 h for a week (more frequent at the beginning and every 24 h afterwards, 12 time points in total), as previously described. Cumulative bacterial growth, fungal growth, and respiration during 1 week after rewetting was calculated. Furthermore, in all soils, bacterial growth exhibited a lag period of no growth before the growth rates started increasing exponentially, which has been previously observed . These growth response patterns were therefore modelled using a Gompertz curve, which was then used to calculate the lag periods before the increase in growth rate .
All statistical analyses were done in R v4.0 . To evaluate microbial community structure, we investigated alpha diversity, ordination analyses, proportion of different taxa and functional guilds, and indicator species analysis. Resistance and resilience of soil functions were evaluated with a linear regression analysis between the value of the variable under drought and time after drought. The value of the intercept was used as a resistance index (RS), and the value of the slope as a resilience index (RL). Soil functional data (soil extracellular enzymes and nutrient pools) were analysed with a non-metric multidimensional scaling (NMDS) ordination analysis. Multifunctionality index was calculated with all the soil enzymatic activities, which represent the organic matter decomposition capacity of soils. The effects of drought intensity and frequency on all variables were analysed by linear mixed effect models (LME) with drought intensity and frequency as fixed factors and soil replicate as random factor. See SI methods for full details.
Changes in microbial community structure Our data show that intense drought (~11% WHC), simulating a once in a century drought event in England, had a profound and long-lasting impact on soil microbial community structure and diversity, despite environmental conditions being returned to their original state (optimum moisture, 65% WHC). Six months after the end of the high intensity drought, bacterial diversity (Fig. ) was still reduced, while fungal Shannon diversity was significantly higher than in the non-droughted control treatment (Fig. ), despite no effects on fungal species richness being detected (Fig. ). Bacterial and fungal community structures were strongly affected by drought (Fig. , Fig. ) and changes in microbial community structures observed after drought were exacerbated with time. This is exemplified in the proportion of variance in community structure explained by drought intensity (Fig. ), which increased after 6 months compared to immediately after drought, particularly under the most intense drought treatment. However, bacterial communities in soils subjected to intermediate intensity drought which simulated drought events in England occurring every 4 years, partially recovered (Fig. ), with less variance explained by drought treatments after 6 months than after drought, i.e., they were more similar to the control treatments after 6 months than at the end of the perturbation. Mild drought, which simulated common drought events occurring annually in England, had no detectable impact on microbial community structure. Drought frequency also significantly affected bacterial and fungal community structures (Fig. ), with communities of those soils exposed to more frequent drought pulses being more distinct from the non-droughted control soils than those subject to fewer drought events. The proportion of different bacterial taxa observed in the soil communities was mainly affected by drought intensity and time, with some minor effects of drought frequency (Table ). Bacterial phyla Proteobacteria , Actinobacteriota , and Firmicutes increased in relative abundance with drought intensity, while taxa affiliated with Acidobacteriota , Bacteroidota , and Myxococcota decreased (Fig. ). There was a clear shift in the bacterial community, persistent through time, from a community co-dominated by Acidobacteriota and Proteobacteria taxa in the control towards one dominated by Proteobacteria under high intensity drought. At family level, particularly significant were the increases in ASVs affiliated with Xanthobacteraceae , Chthoniobacteraceae , Rhodanobacteraceae , and a transient increase in Oxalobacteraceae after drought (Fig. ), and the decrease in the relative abundance of Solibacteraceae and Pedosphaeraceae with drought intensity (Fig. ). Seventy-five of the 86 indicator genera identified for bacteria in our database (Fig. ) were indicators for all of the groups except the high intensity drought, i.e. their abundance was significantly reduced under intense drought. Only the genera Edaphobacter, Paenibacillus, Streptomyces, Sphingomonas , and an unassigned genus in the family Intrasporangiaceae were more abundant under intense drought than the rest of the treatments, and the genera Tumebacillus , and two unassigned genera in the families Microbacteriaceae and Micrococcaceae were more abundant under intense and intermediate drought. The relative abundance of main fungal phyla was mostly affected by drought intensity and time (Fig. , Table ). We observed an increase in Ascomycota and a decrease in Mortierellomycota . In particular, we observed an increase in relative abundance of taxa affiliated with Piskurozymaceae , Helotiales , Trimorphomycetaceae , and Nectriaceae , and a substantial decrease of Mortierellaceae and Clavariaceae , the two most abundant fungal families (Fig. ), which are both typical soil saprotrophs. In agreement with this, we observed a significant decrease with drought treatments in the relative abundance of fungal taxa considered as saprotrophs (Fig. ). Fungal indicator genera (Fig. ) were mostly identified for the control + mild + intermediate drought group (17 out of 20), with no genus indicator for the most intense drought. Bacterial diversity and community structure were correlated with a decrease in soil pH at the last sampling point (Fig. ), which was associated with increased nitrate ion concentrations at this sampling time (Fig. ). Fungal diversity was only marginally affected by soil pH (Fig. ). Changes in microbial community function After the end of drought, when soils were rewetted to the level of the control, seven of the eight extracellular enzyme activities evaluated were significantly reduced by drought intensity and/or frequency, displaying a low resistance to drought (Fig. , Fig. , Table ). Phenoloxidase (POX) activity was slightly reduced by all drought treatments compared to the control, with no significant effect of drought intensity or frequency levels (Fig. , Fig. ). Only the activity of peroxidase (PER) was not affected by drought (only a marginal effect of drought frequency) (Fig. ). The effects of drought intensity on soil enzymes were still detectable after six months (Fig. ), with very little or no resilience, or even a stronger reduction of their activity than immediately after drought (phosphatase) (Fig. ). Soil nutrients were highly affected by drought, particularly available ammonium and dissolved organic carbon (DOC), with a significant increase due to drought intensity and frequency and an interaction between them: the more intense the drought, the bigger the effect of drought frequency on their concentration (Fig. , Fig. , Table ). On the other hand, soil nitrate concentrations were reduced with most drought treatments compared to the control, showing a low resistance (Fig. ). After six months, this big ammonium and DOC flush had mostly disappeared and in turn, nitrate levels significantly increased (Fig. , Fig. ). Drought had no significant effect on the resistance and resilience indexes of available phosphate (Fig. ), but there was a significant increase in available phosphate in the most intense and frequent drought treatment when evaluating the raw data after drought, instead of the calculated indexes (Fig. ). Microbial biomass C, N, and P were reduced by increasing drought intensity (Fig. ), and this effect was still detected after 6 months of returning soils to moisture levels of the control, with microbial P in intense drought treatments showing a stronger decrease with time (Fig. , Fig. , Table ). Taken together, we observed that soils exposed to the most intense drought were in a significantly different functional state than the control soils even 6 months after the end of the perturbation (Fig. ). Microbial functional adaptation to drying/rewetting cycles Drought intensity had a legacy effect resulting in shorter lag times and higher cumulative bacterial growth (Fig. ) after rewetting, while cumulative fungal growth and cumulative respiration (Fig. ) significantly decreased with previous drought intensity. Fungi were more resistant to low moisture than bacteria, as shown by the lower IC 10 (moisture level at which growth rate is reduced by 10%), but this was not significantly affected by previous drought treatments (Fig. ). Respiration showed reduced resistance to drought with previous drought intensity (Fig. ).
Our data show that intense drought (~11% WHC), simulating a once in a century drought event in England, had a profound and long-lasting impact on soil microbial community structure and diversity, despite environmental conditions being returned to their original state (optimum moisture, 65% WHC). Six months after the end of the high intensity drought, bacterial diversity (Fig. ) was still reduced, while fungal Shannon diversity was significantly higher than in the non-droughted control treatment (Fig. ), despite no effects on fungal species richness being detected (Fig. ). Bacterial and fungal community structures were strongly affected by drought (Fig. , Fig. ) and changes in microbial community structures observed after drought were exacerbated with time. This is exemplified in the proportion of variance in community structure explained by drought intensity (Fig. ), which increased after 6 months compared to immediately after drought, particularly under the most intense drought treatment. However, bacterial communities in soils subjected to intermediate intensity drought which simulated drought events in England occurring every 4 years, partially recovered (Fig. ), with less variance explained by drought treatments after 6 months than after drought, i.e., they were more similar to the control treatments after 6 months than at the end of the perturbation. Mild drought, which simulated common drought events occurring annually in England, had no detectable impact on microbial community structure. Drought frequency also significantly affected bacterial and fungal community structures (Fig. ), with communities of those soils exposed to more frequent drought pulses being more distinct from the non-droughted control soils than those subject to fewer drought events. The proportion of different bacterial taxa observed in the soil communities was mainly affected by drought intensity and time, with some minor effects of drought frequency (Table ). Bacterial phyla Proteobacteria , Actinobacteriota , and Firmicutes increased in relative abundance with drought intensity, while taxa affiliated with Acidobacteriota , Bacteroidota , and Myxococcota decreased (Fig. ). There was a clear shift in the bacterial community, persistent through time, from a community co-dominated by Acidobacteriota and Proteobacteria taxa in the control towards one dominated by Proteobacteria under high intensity drought. At family level, particularly significant were the increases in ASVs affiliated with Xanthobacteraceae , Chthoniobacteraceae , Rhodanobacteraceae , and a transient increase in Oxalobacteraceae after drought (Fig. ), and the decrease in the relative abundance of Solibacteraceae and Pedosphaeraceae with drought intensity (Fig. ). Seventy-five of the 86 indicator genera identified for bacteria in our database (Fig. ) were indicators for all of the groups except the high intensity drought, i.e. their abundance was significantly reduced under intense drought. Only the genera Edaphobacter, Paenibacillus, Streptomyces, Sphingomonas , and an unassigned genus in the family Intrasporangiaceae were more abundant under intense drought than the rest of the treatments, and the genera Tumebacillus , and two unassigned genera in the families Microbacteriaceae and Micrococcaceae were more abundant under intense and intermediate drought. The relative abundance of main fungal phyla was mostly affected by drought intensity and time (Fig. , Table ). We observed an increase in Ascomycota and a decrease in Mortierellomycota . In particular, we observed an increase in relative abundance of taxa affiliated with Piskurozymaceae , Helotiales , Trimorphomycetaceae , and Nectriaceae , and a substantial decrease of Mortierellaceae and Clavariaceae , the two most abundant fungal families (Fig. ), which are both typical soil saprotrophs. In agreement with this, we observed a significant decrease with drought treatments in the relative abundance of fungal taxa considered as saprotrophs (Fig. ). Fungal indicator genera (Fig. ) were mostly identified for the control + mild + intermediate drought group (17 out of 20), with no genus indicator for the most intense drought. Bacterial diversity and community structure were correlated with a decrease in soil pH at the last sampling point (Fig. ), which was associated with increased nitrate ion concentrations at this sampling time (Fig. ). Fungal diversity was only marginally affected by soil pH (Fig. ).
After the end of drought, when soils were rewetted to the level of the control, seven of the eight extracellular enzyme activities evaluated were significantly reduced by drought intensity and/or frequency, displaying a low resistance to drought (Fig. , Fig. , Table ). Phenoloxidase (POX) activity was slightly reduced by all drought treatments compared to the control, with no significant effect of drought intensity or frequency levels (Fig. , Fig. ). Only the activity of peroxidase (PER) was not affected by drought (only a marginal effect of drought frequency) (Fig. ). The effects of drought intensity on soil enzymes were still detectable after six months (Fig. ), with very little or no resilience, or even a stronger reduction of their activity than immediately after drought (phosphatase) (Fig. ). Soil nutrients were highly affected by drought, particularly available ammonium and dissolved organic carbon (DOC), with a significant increase due to drought intensity and frequency and an interaction between them: the more intense the drought, the bigger the effect of drought frequency on their concentration (Fig. , Fig. , Table ). On the other hand, soil nitrate concentrations were reduced with most drought treatments compared to the control, showing a low resistance (Fig. ). After six months, this big ammonium and DOC flush had mostly disappeared and in turn, nitrate levels significantly increased (Fig. , Fig. ). Drought had no significant effect on the resistance and resilience indexes of available phosphate (Fig. ), but there was a significant increase in available phosphate in the most intense and frequent drought treatment when evaluating the raw data after drought, instead of the calculated indexes (Fig. ). Microbial biomass C, N, and P were reduced by increasing drought intensity (Fig. ), and this effect was still detected after 6 months of returning soils to moisture levels of the control, with microbial P in intense drought treatments showing a stronger decrease with time (Fig. , Fig. , Table ). Taken together, we observed that soils exposed to the most intense drought were in a significantly different functional state than the control soils even 6 months after the end of the perturbation (Fig. ).
Drought intensity had a legacy effect resulting in shorter lag times and higher cumulative bacterial growth (Fig. ) after rewetting, while cumulative fungal growth and cumulative respiration (Fig. ) significantly decreased with previous drought intensity. Fungi were more resistant to low moisture than bacteria, as shown by the lower IC 10 (moisture level at which growth rate is reduced by 10%), but this was not significantly affected by previous drought treatments (Fig. ). Respiration showed reduced resistance to drought with previous drought intensity (Fig. ).
Our findings demonstrate that soil microbial communities are generally resistant to, and recover rapidly from, mild, infrequent droughts. However, we demonstrate a lack of resilience to high intensity drought, which triggers an abrupt and persistent shift in the soil microbial community to one of reduced structural complexity and impaired functioning. We also discovered that the functional characteristics of soil microbial communities can react to drought exposure, with exposure to high intensity drought inducing an enhanced ability of bacteria to recover growth rates following subsequent drought. Bacterial and fungal communities were strongly and persistently modified by high intensity drought, with clear changes in diversity and community structure that persisted despite returning soils to their original moisture conditions. Consistent with previous studies, high intensity drought caused a reduction in bacterial diversity, which is indicative of reduced community resistance . Moreover, under high intensity drought, bacterial communities shifted from being co-dominated by Acidobacteriota and Proteobacteria to being dominated by Proteobacteria , with persistent increases in Actinobacteriota and Firmicutes , and a decrease in Bacteroidetes and Myxococcota . This community shift is consistent with previous reports on the drought tolerance of Proteobacteria , Actinobacteria , and Firmicutes , and drought sensitivity of Acidobacteria and Bacteroidetes . In contrast to bacteria, we observed an increase in fungal diversity under high intensity drought. This fungal community change was not associated with a change in species richness, but with an increase in evenness due to reduced abundances of the two dominant fungal taxa, Mortierellaceae and Clavariaceae , typical soil saprotrophs. These two families have been previously identified as drought sensitive and their decrease could be related to persistent changes in nutrient availability elicited by drought. Fungi are generally considered to be more resistant to drought than bacteria and several studies demonstrate a lack of drought effect on fungal communities . In contrast, we observed a clear shift in the fungal community, which was still evident 6 months after returning droughted soils to their original, pre-drought moisture content. In our experiment, changes in community structure and the reduction in bacterial diversity were partially related to a decrease in soil pH, as previously demonstrated at a global and local scale . However, fungal diversity was only marginally related to soil pH, also in agreement with the literature . Microbial community shifts in response to high intensity drought were also associated with persistent changes in microbial functioning. Extracellular enzymes are not produced by a wide diversity of soil organisms , and, therefore, they do not reflect the whole soil community functionally. Additionally, part of the activity observed will come from stabilised enzymes within the soil matrix and not new enzymes produced by viable microbial cells . Nevertheless, we observed a significant correlation between community composition and combined enzymatic activity in our experiment (Fig. ). High intensity drought effects on soil enzymes were still detectable after six months with very little or no recovery, manifesting a very low resilience and a persistent reduction of soil functional capacity, or functional regime shift. A reduction in soil enzymatic capacity with drought has been frequently reported , probably associated with microbial death and thus reduced enzyme production and reduced substrate diffusion that limits enzyme activity . Enzymatic activities can also reflect the nutritional status of the microbial community and the existence of any particular nutrient limitation, as microbes invest in enzymes that minimise energy and nutrient costs and maximise benefits . In agreement with this, enzyme activities were negatively correlated with available N and P (Fig. ). The lack of recovery of enzymatic capacity over time, even though soil nutrient returned to their original levels after rewetting, could be explained by consistently low microbial biomass 6 months after high intensity drought (Fig. ). Increases in nutrient availability immediately after rewetting dry soils are likely explained by the death of microorganisms and increased availability of organic compounds . The fact that nitrate levels in our experiment significantly increased over time after rewetting, could be related to a high nitrification activity, where the highly abundant ammonium was transformed into nitrate . Decreases in microbial biomass due to drought, as observed here under high intensity drought, have been widely reported , although some authors observed an increase in microbial biomass under drought . The observed constant decline of microbial biomass P over time since rewetting could be related to reduced phosphatase activity (Fig. ). This agrees with the study of Dijkstra and collaborators which showed a strong reduction in P uptake by soil microbes during drought. However, a decrease in microbial biomass over time in bare soils is expected, as there is no additional C input from plants into the system. As well as clear changes in soil microbial community structure and function elicited by drought, we also observed legacy effects of drought and adaptation of growth responses of bacterial and fungal communities when facing a further drying/rewetting cycle. The observed shorter lag times and higher cumulative growth for bacteria, in soils with a legacy of intense drought, are indicative of a faster recolonisation ability . An increased and faster bacterial growth in soils with a history of drought could be a competitive adaptive strategy in soils exposed to frequent drought events . However, this could also be linked to changes in soil chemistry associated with the legacy of the different drought treatments. Although most of the nutrients released just after drought were already consumed at the time of the growth rate measurements (one month after drought), some were still elevated compared to control soils (Fig. ), which could support bacterial growth. On the other hand, the reduced cumulative fungal growth could underpin the reduced abundance of the two dominant fungal families. This result contrasts with other studies where fungal growth was not affected by drought history . However, the fungal growth capacity in our study could have also been constrained by the high bacterial growth in the soils . These effects on microbial growth were not dependent on the microbial biomass of soils before drying/rewetting (Fig. ). Cumulative respiration after rewetting seems to be driven by fungi, as it follows approximately the same pattern as cumulative fungal growth. This contrasts with some recent observations, where respiration was mostly driven by bacterial growth . Alternatively, this decrease in cumulative respiration with previous drought intensity could be also related to resource availability. Previous high intensity drought led to a strong increase of DOC, which was mostly used one month after drought (Fig. ), and this likely depleted the soil carbon available to fuel a respiration peak after the additional drying/rewetting cycle. Reduced carbon availability in soils after drought has been previously reported , as well as less intense respiration peaks after repeated drying/rewetting cycles . Our results indicate that there are legacy effects of drought on soil microbial communities, matching recent studies. For example, pre-exposure to drought has been demonstrated to increase bacterial resistance and resilience to subsequent droughts, although others have reported the opposite pattern, with previous drought reducing stability and diversity of microbial communities in the long term . We observed an increased recolonisation capacity of bacteria, albeit a lower tolerance to reduced soil moisture, while fungi showed a potential increased resistance to drought but with less cumulative growth upon rewetting. Thus, in this study system, there appears to be a trade-off between growth after rewetting, which can be interpreted as resilience, and resistance to low moisture. These strategy changes could be the result of a shift in the relative abundance of different taxa within the community or due to changes in individual taxa’s physiology or traits (evolution). In any case, the response of fast re-coloniser bacterial taxa appears to shape bacterial communities after drought, as they occupy niches left vacant after drought, conditioning community assembly afterwards . As discussed above, our findings provide experimental evidence that high intensity soil drying prevented microbial community resilience upon rewetting. Moreover, we observed a clear threshold of drought intensity level corresponding to a 30-year recurrent drought event in England (15% WHC, 9% volumetric water content; Fig. ). Below this moisture level, soil microbial communities were markedly and persistently restructured with impaired functioning, and they failed to recover over a period of 6 months, despite returning moisture levels to those of the control. The existence of this threshold is further supported by a previous study that demonstrated that below a threshold of 14% WHC, the growth pattern of bacteria upon rewetting changed significantly . To further evaluate the abrupt and persistent microbial shifts in our experiment, we mapped microbial community composition and function with multivariate analysis, as it is a useful tool to visualise stability landscapes and regime shifts . We observed a clear pattern in both community structure and function of soil microbial communities where soils subjected to intense drought occupy a distinct space separated from the control, which could potentially be interpreted as an alternative state of the system (Fig. ). Moreover, our experiment met most of the recognised criteria for detecting an alternative state . First, we demonstrated the existence of two different microbial communities given the same environmental condition (i.e., at optimum soil moisture during the period after drought). Second, different intensities of drought, or the scale of pulse perturbation, were found to have contrasting effects on soil microbial communities, with mild and intermediate drought intensities showing reversible effects, but persistent changes in response to high intensity drought. Third, our experiment was conducted over an extended period of time, representing the typical length of the growing season in northern England, where the soil samples were collected. While it is unlikely that the identified microbial shifts are “stable”, we demonstrate that microbial communities subject to high intensity drought shift towards a different state that is distinct from its original one and from the non-droughted control soils. We therefore propose that the detected microbial shifts may reflect an alternative “transient” state or simply an alternative state.
Our findings demonstrate experimentally that while microbial communities can buffer mild, infrequent droughts, increasing the intensity and frequency of drought decreases soil microbial community resistance and resilience, and triggers an abrupt shift in soil microbial state. Moreover, we show that this abrupt shift in microbial state occurs at a threshold of <15% WHC - corresponding to a 30-year recurrent drought event in England - and is characterised by a pronounced and persistent reduction in microbial functional capacity, modified taxonomical composition of reduced complexity, and bacterial communities with a composition of functional traits that enable rapid recolonisation. Based on these finding, we propose that the detected microbial shifts may be indicative of an alternative microbial state after intense drought. However, caution is needed on extrapolating results from this laboratory study to real world settings and future studies are necessary to consider the role of extrinsic factors that might modify the vulnerability of soil microbial communities to perturbation-induced transitions to alternative states, such as the presence of plants, which can help the system recover after drought , or differences in nutrient availability and other soil abiotic properties . Additionally, further experiments with longer time-scales and under settings closer to those found in the field are needed to better understand the responses of soil microbial communities to drought intensity and frequency, and how they vary under different climatic and edaphic conditions. Nevertheless, our results provide novel experimental evidence of a decreasing resistance and resilience of soil microbial communities as drought intensity increases, and identify a threshold for an abrupt and persistent shift in soil microbial state driven by high intensity drought, with potentially deleterious consequences for soil health.
Supplementary information
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Síndrome do Bloqueio de Ramo Esquerdo Doloroso em Paciente Encaminhada para Estudo Eletrofisiológico: Um Relato de Caso | 165d9de3-eae2-480c-8682-0862cc1cb7f1 | 8149111 | Physiology[mh] | O desenvolvimento de dor precordial associada ao bloqueio de ramo esquerdo (BRE) intermitente na ausência de doença arterial coronariana tem sido descrito na literatura como síndrome do bloqueio de ramo esquerdo doloroso. O mecanismo responsável pela dor precordial é desconhecido, mas a principal hipótese atualmente está relacionada à dissincronia cardíaca aguda. Nessa síndrome, o BRE ocorre quando a duração do ciclo é igual ou inferior ao período refratário do ramo esquerdo, principalmente durante o esforço físico. A dor torácica na síndrome do BRE doloroso pode variar entre um leve desconforto a uma condição incapacitante. Esse relato descreve uma paciente com BRE frequência-dependente típico associado com dor torácica, encaminhada ao estudo eletrofisiológico (EEF) sem evidências de arritmias.
Paciente do sexo feminino, 41 anos, com histórico de hipertensão controlada e dois anos de palpitações associadas com dor torácica desencadeada por esforço mínimo durante atividades cotidianas, que persistia por até 2 horas. A dor torácica foi descrita como uma sensação de pressão, que irradiava para o braço esquerdo, associada a náusea e dispneia. Os episódios foram caracterizados por início súbito, sem pródromos, com melhora espontânea. Inicialmente, a paciente foi tratada com atenolol 25 mg (duas vezes ao dia), com alívio parcial dos sintomas. Não havia histórico familiar de síncope inexplicada ou morte cardíaca súbita. O exame físico foi normal. O ECG de 12 derivações durante a crise revelou taquicardia de complexo alargado com bloqueio de ramo esquerdo completo (BRE), eixo inferior e onda P compatível com ritmo sinusal. Mesmo assim, a paciente foi referia ao EEF, que não mostrou substratos arritmogênicos. Entretanto, no início da estimulação atrial contínua a 600 ms, foi observado um BRE frequência dependente. Imediatamente após o BRE, a paciente, que não havia sido mantida sedada, começou a se queixar dos mesmos sintomas já descritos. O BRE persistiu por alguns minutos e desapareceu espontaneamente, concomitantemente com o alívio da dor. O ECG é apresentado na . Trata-se de um BRE de 3º grau típico, com duração do complexo QRS de 138 ms, eixo superior e onda P sinusal. O ECG basal de 12 derivações estava normal . O monitoramento por Holter de 24 horas revelou que a FC basal variou entre 56 e 116 bpm durante as atividades cotidianas, sem evidência de BRE. Tanto a ecocardiografia transtorácica quanto a ressonância magnética cardíaca mostraram função sistólica normal sem doença miocárdica ou valvar. Todas as câmaras cardíacas estavam com tamanho normal. Um teste de esforço revelou o desenvolvimento de bloqueio de ramo esquerdo associado com a dor torácica. A angiotomografia descartou doença arterial coronariana e defeitos de perfusão do miocárdio com diripidamol. Atualmente, a paciente está recebendo atenolol 50 mg (duas vezes ao dia) e não houve recorrências de palpitações ou dor precordial no acompanhamento de seis meses.
Em 1946, foi publicado o primeiro relato de bloqueio de ramo esquerdo intermitente relacionado a esforços. O paciente apresentava palpitações e sensação de dor no precórdio durante as crises. Entretanto, a angiocoronariografia não foi realizada devido à tecnologia disponível naquela época. Em 1976, Vieweg et al., relataram o primeiro caso de bloqueio de ramo esquerdo associado com angina de esforço, com evidências angiográficas de artérias coronárias normais. Embora tenha sido feito um diagnóstico de angina, foram observadas características atípicas: início e fim abruptos da dor, concomitantemente ao BRE e após o seu desaparecimento, respectivamente. Em 1982, Virtanen et al., conduziram um estudo com 7 pacientes portadores de bloqueio de ramo esquerdo recente e dor precordial durante o teste de esforço, todos com angiocoronariografias normais. Nesse estudo, foi avaliado o padrão da dor apresentada pelos pacientes. Em todos os casos, a dor foi considerada atípica por conta do início e fim abruptos. Posteriormente, novos casos foram relatados, e a essa condição deu-se o nome de síndrome do bloqueio de ramo esquerdo doloroso. Os mecanismos da síndrome do BRE doloroso são pouco claros. A possibilidade de isquemia de demanda resultante de lesões ou espasmos coronários foi inicialmente considerada uma possível causa para essa síndrome, mas logo essa suposição se mostrou incorreta. O início/fim imediatos da dor são incompatíveis com isquemia. A nitroglicerina se mostrou ineficaz e, às vezes, induziu o BRE devido à taquicardia. Muitas vezes, o resultado do exame de imagem nuclear era negativo e o vasoespasmo também havia sido descartado. , A melhor teoria até agora é a proposta por Virtanen et al., que, por meio da avaliação de ventriculografias, especulou que a dor poderia ser induzida pelo movimento sistólico anormal do septo. A presença do eixo inferior em uma série de casos de maneira uniforme fez com que os autores presumissem a existência de um padrão de contratilidade específico. Shvlikin et al., propuseram critérios para o diagnóstico da síndrome do BRE doloroso . De forma semelhante à onda T da memória cardíaca de pacientes com marcapasso, o BRE crônica apresenta ondas T de menor amplitude do que a BRE aguda. Em estudo prospectivo, uma relação S/T < 2,5 em derivações precordiais se mostrou eficaz (100% sensibilidade e 89% especificidade) para distinguir entre o BRE de início recente ou crônico, um dos itens dos critérios propostos na . A paciente a qual se refere este artigo foi encaminhada ao EEF por conta de uma hipótese equívoca de taquicardia supraventricular com aberrância. Durante o estudo, com a estimulação atrial contínua, tivemos a oportunidade de registrar o momento exato do bloqueio de ramo esquerdo e a imediata queixa sobre a mesma dor previamente referida pela paciente como sendo crônica. Ao traçarmos uma comparação com os critérios propostos por Schvilkin et al., verificamos que nosso caso se encaixa em todos os critérios, com a exceção de um: o “critério do eixo inferior”. Entretanto, outras publicações também mostraram um complexo QRS superior. , A relação S/T foi igual a 1,33 em V2 , compatível com um BRE de início agudo. A paciente apresentou início abrupto de dor, conforme registrado pelos membros da nossa equipe no laboratório de eletrofisiologia. O desaparecimento dos sintomas ocorreu imediatamente após o desaparecimento do BRE. O ECG basal de 12 derivações estava normal. Um teste de esforço descartou a isquemia miocárdica e a angiotomografia revelou artérias coronárias normais. Tanto a ecocardiografia quanto a ressonância cardíaca estavam normais, com exceção das causas secundárias da angina.
Relatamos um caso de BRE doloroso de uma paciente encaminhada ao EEF. O início abrupto da dor assim que o bloqueio do ramo esquerdo ocorre é incompatível com a isquemia. Além disso, a paciente foi submetida a exames que descartaram o comprometimento coronário e miocárdico. A melhor hipótese para a fisiopatologia dessa síndrome é a dissincronia dolorosa do coração resultante do BRE de início agudo. Até onde sabemos, este é o primeiro relato de caso sobre essa síndrome em uma revista médica brasileira.
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Potential antigenic targets used in immunological tests for diagnosis of tegumentary leishmaniasis: A systematic review | b7f1ecd9-fa8e-4dea-b226-ca19a7adca27 | 8158869 | Histology[mh] | Tegumentary Leishmaniasis (TL) is a neglected tropical disease caused by different species of the genus Leishmania (Kinetoplastea: Trypanosomatidae), transmitted to vertebrate hosts by sand flies (Diptera: Psychodidae) . TL is considered an emergent and re-emergent disease, since a worrisome increase in its incidence has been reported . On a the global scale, the number of new autochthonous TL cases reported annually to the World Health Organization (WHO) increased from 71,486 to 251,553 during 1998 to 2018 . Several factors are involved with the spread of TL, such as human migration from rural to urban areas, conflicts and wars, disturbances in microenvironments due to climate change and human intervention and deterioration of socioeconomic conditions in endemic countries . TL comprises a broad spectrum of clinical manifestations ranging from single or multiple ulcerative skin lesions (cutaneous leishmaniasis—CL), to diffuse (diffuse leishmaniasis-DL) and mucosal (mucosal leishmaniasis—ML) lesions, with the last two being typical in the Americas. TL is associated with physical deformities and psychological alterations, affecting the health and wellness of the patient . The range of clinical manifestations can hinder rapid and accurate diagnoses, a key step to initiate treatment promptly and control the disease. Although several advances, TL-diagnosis remains based on the triad of epidemiological background, clinical signs and laboratory diagnosis, including direct and histopathological examination of skin biopsy and molecular detection of Leishmania DNA. Despite high specificity, low sensitivities have been described for direct and histopathological examination, especially in New World countries, where chronic cases and ML are frequent [ – ]. Molecular techniques are complex, expensive, still without a standardized protocol for routine use and are restricted to reference and research centers. Therefore, these limitations make the TL-diagnosis scenario restricted, particularly in resource limited settings [ – ]. In this sense, immunological tests may present remarkable advantages for TL-diagnosis, due to the use of less invasive sampling compared to skin biopsy and their potential to be automated, quantitative and used as point-of-care tests. The anti- Leishmania delayed-type hypersensitivity reaction, known as the Montenegro skin test (MST), has been the most used immunological test for CL-diagnosis in Brazil, even though it presents significant limitations such as positive results associated with previous leishmaniasis or asymptomatic infections . Nonetheless, the production of the MST antigen was discontinued in Brazil, hampering even more CL-diagnosis in the country . Other immunological tests, mainly Enzyme-Linked Immunosorbent Assay (ELISA), have presenting promising results in the Americas and beyond . Several studies using soluble Leishmania antigen (SLA) in ELISA for TL-diagnosis, have presented variable sensitivity especially due to antigen preparation and antigenic differences among Leishmania isolates and species. Moreover, reduced specificity due to the cross-reactivity with other infectious diseases has been frequently reported [ – ]. Since CL-patients commonly produce low levels of anti- Leishmania antibodies, there is growing interest in high sensitivity antigens for immunological tests. Different methodologies have been employed, such as bioinformatics tools [ – ], cDNA expression library , phage display , immunoproteomic approach [ , – ] and isolation and purification of glycoconjugates to identify potential antigens. Furthermore, immunological tools have already been used to detect Leishmania antigens using monoclonal and polyclonal antibodies by immunochromatographic test (ICT) or immunohistochemistry (IHC), such as the CL Detect Rapid Test (InBios International Inc., Seattle, WA, USA), which detects peroxidoxin from Leishmania and has been used especially in Old World countries, with limited sensitivity . In this sense, we consider immunnodiagosis as potential tools to increase the access and improve TL-diagnosis. Although systematic reviews have been conducted on some aspects of this form of diagnosis, it is essential to identify potential antigenic targets that have been evaluated as TL-immunodiagnostic, point out knowledge gaps that still remain and encourage other studies to allow its application in clinical practice . In this way, we performed a worldwide systematic review to identify potential antigenic targets, with reported sensitivity and specificity, used as TL-immunodiagnostic.
Protocol and registration The review protocol was registered in the International Prospective Record of Systematic Reviews (PROSPERO: CRD42020213311) and was developed based on the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy . This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) ( ) . Information sources and study selection Structured searches were conducted in the following databases: MEDLINE, Virtual Health Library, Embase and Cochrane. A comprehensive list of key terms including tegumentary leishmaniasis and its different clinical forms AND immunological diagnosis or targets (antigens and antibodies) AND techniques or outcomes (sensitivity and specificity), was constructed in MEDLINE ( ). Similar searches were adapted to each database. Complementary searches were performed by analysis of reference lists of selected articles. Searches were performed on 23 rd March 2020, without restriction of publication date. Inclusion and exclusion criteria Original research articles reporting on the performance (sensitivity and specificity) of immunological tests based on the detection of antibodies or antigens using purified or recombinant proteins, synthetic peptides or polyclonal or monoclonal antibodies for diagnosis of human-TL, CL or ML were included. Exclusion criteria were: evaluation of serological tests based on SLA; only non-human samples were tested (e.g. canine samples); both sensitivity and specificity of the immunological tests were not presented or were impossible to be calculated; less than five samples were tested; the absence of information about the reference test and a non-specific Leishmania antigen was used. Selection process For each database, all publications were retrieved and duplicate citations were excluded by EndNote software . Based on the inclusion and exclusion criteria, two independent reviewers analyzed each publication by title and abstract using Rayyan software . Articles with no reason for rejection were included for full text reading. All discrepancies were solved by consensus after discussion. Selected studies were read in full to confirm their eligibility, to extract data or to exclude if exclusion criteria were identified during this step. Data extraction Data were independently extracted by two researchers (MLF and FDR) directly from full-length articles and were checked by a third researcher (EO). In case of disagreements, the final decision was reached by consensus. In this study, data were extracted and a 2x2 contingency table set up for immunological tests, containing the true positives, false positives, true negatives and false negatives. Furthermore, the following items were extracted: origin of the participants; the immunological test used; antigen or antibody types; Leishmania species and reference standard test used for disease confirmation. The phase of development of each study was classified according to Leeflang & Allerberger (2019) . Study quality assessment The quality of the studies was assessed using the second version of Quality Assessment of Studies of Diagnostic Accuracy Approach (QUADAS-2) . This tool allows a more transparent rating of risk of bias for studies included in systematic reviews on diagnostic accuracy. Data synthesis The performance of antigenic targets was presented in four groups according immunological tests and clinical form: 1) ELISA for TL; 2) ELISA for CL; 3) Other immunological tests for CL and 4) ELISA for ML. The performance outcomes for each antigen or antibody were sensitivity (probability of a positive test among cases or disease confirmed individuals) and specificity (probability of a negative test among controls or individuals without disease). Forest plots showing sensitivity and specificity values of all antigens, including 95% confidence intervals (CI) and Summary Receiver Operating Characteristic (SROC) curves were created using RevMan 5.3. Several studies considered a set of results for the same antigen (e.g. different cut-off points were available or different non-case groups were used in the analysis, such as healthy patients and those with other diseases). If possible, these results were grouped and only one sensitivity rate and one specificity rate including all evaluated patients. When impossible, we chose to present data that reflect the best field conditions (e.g. non-case group of patients with other diseases) or the better performance (e.g. cut-off point with best performance).
The review protocol was registered in the International Prospective Record of Systematic Reviews (PROSPERO: CRD42020213311) and was developed based on the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy . This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) ( ) .
Structured searches were conducted in the following databases: MEDLINE, Virtual Health Library, Embase and Cochrane. A comprehensive list of key terms including tegumentary leishmaniasis and its different clinical forms AND immunological diagnosis or targets (antigens and antibodies) AND techniques or outcomes (sensitivity and specificity), was constructed in MEDLINE ( ). Similar searches were adapted to each database. Complementary searches were performed by analysis of reference lists of selected articles. Searches were performed on 23 rd March 2020, without restriction of publication date.
Original research articles reporting on the performance (sensitivity and specificity) of immunological tests based on the detection of antibodies or antigens using purified or recombinant proteins, synthetic peptides or polyclonal or monoclonal antibodies for diagnosis of human-TL, CL or ML were included. Exclusion criteria were: evaluation of serological tests based on SLA; only non-human samples were tested (e.g. canine samples); both sensitivity and specificity of the immunological tests were not presented or were impossible to be calculated; less than five samples were tested; the absence of information about the reference test and a non-specific Leishmania antigen was used.
For each database, all publications were retrieved and duplicate citations were excluded by EndNote software . Based on the inclusion and exclusion criteria, two independent reviewers analyzed each publication by title and abstract using Rayyan software . Articles with no reason for rejection were included for full text reading. All discrepancies were solved by consensus after discussion. Selected studies were read in full to confirm their eligibility, to extract data or to exclude if exclusion criteria were identified during this step.
Data were independently extracted by two researchers (MLF and FDR) directly from full-length articles and were checked by a third researcher (EO). In case of disagreements, the final decision was reached by consensus. In this study, data were extracted and a 2x2 contingency table set up for immunological tests, containing the true positives, false positives, true negatives and false negatives. Furthermore, the following items were extracted: origin of the participants; the immunological test used; antigen or antibody types; Leishmania species and reference standard test used for disease confirmation. The phase of development of each study was classified according to Leeflang & Allerberger (2019) .
The quality of the studies was assessed using the second version of Quality Assessment of Studies of Diagnostic Accuracy Approach (QUADAS-2) . This tool allows a more transparent rating of risk of bias for studies included in systematic reviews on diagnostic accuracy.
The performance of antigenic targets was presented in four groups according immunological tests and clinical form: 1) ELISA for TL; 2) ELISA for CL; 3) Other immunological tests for CL and 4) ELISA for ML. The performance outcomes for each antigen or antibody were sensitivity (probability of a positive test among cases or disease confirmed individuals) and specificity (probability of a negative test among controls or individuals without disease). Forest plots showing sensitivity and specificity values of all antigens, including 95% confidence intervals (CI) and Summary Receiver Operating Characteristic (SROC) curves were created using RevMan 5.3. Several studies considered a set of results for the same antigen (e.g. different cut-off points were available or different non-case groups were used in the analysis, such as healthy patients and those with other diseases). If possible, these results were grouped and only one sensitivity rate and one specificity rate including all evaluated patients. When impossible, we chose to present data that reflect the best field conditions (e.g. non-case group of patients with other diseases) or the better performance (e.g. cut-off point with best performance).
Literature search A total of 1642 articles from four databases were initially identified. Of this total, 261 were excluded due to duplicity (the same study was found in different databases). The title and abstract of each of the 1381 articles were checked and 139 were selected for full text reading. Finally, 98 articles presented exclusion criteria and so 38 were included ( ). Descriptive analysis of included studies The characteristics of all included studies are presented in . In several studies, test performance was analyzed according to the clinical form (CL and ML) or globally (TL). In 19 studies, the antigenic targets were evaluated for TL-diagnosis, in 21 for CL and in 9 for ML. Sample size ranged from 26 to 500 patients. A total of three different immunological tests using purified or recombinant proteins, synthetic peptides or polyclonal or monoclonal antibodies were reported: ELISA, ICT and IHC. Different reference standard tests were used to confirm leishmaniasis cases. Thirty-one studies (81.6%) considered at least one parasitological method as a reference standard test, such as microscopy examination or in vitro culture for isolation of the parasite. On the other hand, seven studies (18.4%) considered some immunological or molecular tests as a reference standard. A total of 89.5% (34 out of 38) of the studies was classified as phase I (proof-of-concept), and the remaining 10.5% (4 out of 38) was classified as phase III. ELISA for TL diagnosis Nineteen studies used ELISA to evaluate the performance of a total of 56 antigens for TL-diagnosis, without specification of the clinical form (CL or ML). These studies evaluated 38 recombinant proteins, 14 synthetic peptides and 4 purified proteins. Forty-seven antigens were evaluated in studies that considered at least one parasitological method, such as microscopy examination or in vitro culture isolation of the parasite, as a reference standard test. The number of TL-patients ranged from 20 to 219 and the number of non-TL patients ranged from 8 to 281. The highest performance (100% of sensitivity and specificity) was reported for four recombinant proteins (cytochrome c oxidase; hypothetical protein XP_003886492.1; putative IgE histamine releasing factor; tryparedoxin peroxidase) and four synthetic peptides (A10, B7, C12 and H7) selected by the phage display technique [ , , , ]. Nine other antigens were evaluated in studies that considered at least one immunological method as a reference standard test. For these antigens the sensitivity ranged from 39.8% to 76.9% and the specificity from 53.4% to 97%. The forest plots for sensitivity and specificity of ELISA considering parasitological methods and other tests as reference standard tests for TL-diagnosis are presented in ; more details about each evaluated antigen are available in . ELISA for CL diagnosis Seventeen studies used ELISA to evaluate the performance of 44 antigens for CL-diagnosis, which comprised 20 recombinant proteins, 13 synthetic peptides and 11 purified proteins. The performance of 35 antigens was evaluated considering at least one parasitological method as a reference standard test. Among these, the sample size for studies of CL-patients ranged from 12 to 74 and for non-CL-patients from 10 to 177. Peroxidoxin was the only antigen presenting 100% sensitivity and specificity . Nine antigens were evaluated considering at least one immunological test as a reference standard. Overall, HSP83 presented the highest performance (100% sensitivity and specificity) ( , ). Other immunological tests for CL diagnosis The performance of ICT and IHC using different monoclonal and/or polyclonal antibodies is presented in and detailed in . Four studies evaluated the CL Detect Rapid Test (InBios International Inc., Seattle, WA, USA) in different countries. The sensitivity ranged from 35.6 to 67.6 and the specificity was higher than 80%. For IHC, two monoclonal antibodies were employed to detect antigens in fixed skin fragments. The highest performance was reported for IS22B4/XLVI5B8 mAbs, with 96% and 100% sensitivity and specificity, respectively . ELISA for ML results Nine studies used ELISA to evaluate the performance of 23 antigens for ML-diagnosis, which comprised 19 recombinant proteins, three synthetic peptides and one purified protein. The sample size from ML-patients in these studies ranged from 14 to 53 and from non-ML-patients from 20 to 92. At least one parasitological method was used as a reference standard test for the evaluation of sixteen antigens. The highest performance was obtained for Hypothetical protein XP_001467126.1, with 100% sensitivity and 98% specificity . Seven antigens were evaluated in studies considering at least one immunological test as a reference standard. As noted for CL-diagnosis, 100% sensitivity and specificity were reported for HSP83 . The performance of these antigens is presented in and more details are available in . The SROC curves with the antigen performances for the diagnostic of different clinical forms, using parasitological or other tests (such as ELISA and MST) as a reference standard, are presented in . The antigens tended to have greater accuracy in studies that have used the parasitological methods as reference standard tests, regardless of TL-clinical manifestation. Quadas-2 based quality assessment Quality assessment of the study according to risk of bias and concern with applicability (low, high and unclear) is shown in . Of the 38 studies assessed, 21 had high risk of bias in patient selection. The risk was unclear for the index test in 34 studies and for flow and timing in 30 studies. Nineteen studies had high concerns regarding applicability of patient selection criteria.
A total of 1642 articles from four databases were initially identified. Of this total, 261 were excluded due to duplicity (the same study was found in different databases). The title and abstract of each of the 1381 articles were checked and 139 were selected for full text reading. Finally, 98 articles presented exclusion criteria and so 38 were included ( ).
The characteristics of all included studies are presented in . In several studies, test performance was analyzed according to the clinical form (CL and ML) or globally (TL). In 19 studies, the antigenic targets were evaluated for TL-diagnosis, in 21 for CL and in 9 for ML. Sample size ranged from 26 to 500 patients. A total of three different immunological tests using purified or recombinant proteins, synthetic peptides or polyclonal or monoclonal antibodies were reported: ELISA, ICT and IHC. Different reference standard tests were used to confirm leishmaniasis cases. Thirty-one studies (81.6%) considered at least one parasitological method as a reference standard test, such as microscopy examination or in vitro culture for isolation of the parasite. On the other hand, seven studies (18.4%) considered some immunological or molecular tests as a reference standard. A total of 89.5% (34 out of 38) of the studies was classified as phase I (proof-of-concept), and the remaining 10.5% (4 out of 38) was classified as phase III.
Nineteen studies used ELISA to evaluate the performance of a total of 56 antigens for TL-diagnosis, without specification of the clinical form (CL or ML). These studies evaluated 38 recombinant proteins, 14 synthetic peptides and 4 purified proteins. Forty-seven antigens were evaluated in studies that considered at least one parasitological method, such as microscopy examination or in vitro culture isolation of the parasite, as a reference standard test. The number of TL-patients ranged from 20 to 219 and the number of non-TL patients ranged from 8 to 281. The highest performance (100% of sensitivity and specificity) was reported for four recombinant proteins (cytochrome c oxidase; hypothetical protein XP_003886492.1; putative IgE histamine releasing factor; tryparedoxin peroxidase) and four synthetic peptides (A10, B7, C12 and H7) selected by the phage display technique [ , , , ]. Nine other antigens were evaluated in studies that considered at least one immunological method as a reference standard test. For these antigens the sensitivity ranged from 39.8% to 76.9% and the specificity from 53.4% to 97%. The forest plots for sensitivity and specificity of ELISA considering parasitological methods and other tests as reference standard tests for TL-diagnosis are presented in ; more details about each evaluated antigen are available in .
Seventeen studies used ELISA to evaluate the performance of 44 antigens for CL-diagnosis, which comprised 20 recombinant proteins, 13 synthetic peptides and 11 purified proteins. The performance of 35 antigens was evaluated considering at least one parasitological method as a reference standard test. Among these, the sample size for studies of CL-patients ranged from 12 to 74 and for non-CL-patients from 10 to 177. Peroxidoxin was the only antigen presenting 100% sensitivity and specificity . Nine antigens were evaluated considering at least one immunological test as a reference standard. Overall, HSP83 presented the highest performance (100% sensitivity and specificity) ( , ).
The performance of ICT and IHC using different monoclonal and/or polyclonal antibodies is presented in and detailed in . Four studies evaluated the CL Detect Rapid Test (InBios International Inc., Seattle, WA, USA) in different countries. The sensitivity ranged from 35.6 to 67.6 and the specificity was higher than 80%. For IHC, two monoclonal antibodies were employed to detect antigens in fixed skin fragments. The highest performance was reported for IS22B4/XLVI5B8 mAbs, with 96% and 100% sensitivity and specificity, respectively .
Nine studies used ELISA to evaluate the performance of 23 antigens for ML-diagnosis, which comprised 19 recombinant proteins, three synthetic peptides and one purified protein. The sample size from ML-patients in these studies ranged from 14 to 53 and from non-ML-patients from 20 to 92. At least one parasitological method was used as a reference standard test for the evaluation of sixteen antigens. The highest performance was obtained for Hypothetical protein XP_001467126.1, with 100% sensitivity and 98% specificity . Seven antigens were evaluated in studies considering at least one immunological test as a reference standard. As noted for CL-diagnosis, 100% sensitivity and specificity were reported for HSP83 . The performance of these antigens is presented in and more details are available in . The SROC curves with the antigen performances for the diagnostic of different clinical forms, using parasitological or other tests (such as ELISA and MST) as a reference standard, are presented in . The antigens tended to have greater accuracy in studies that have used the parasitological methods as reference standard tests, regardless of TL-clinical manifestation.
Quality assessment of the study according to risk of bias and concern with applicability (low, high and unclear) is shown in . Of the 38 studies assessed, 21 had high risk of bias in patient selection. The risk was unclear for the index test in 34 studies and for flow and timing in 30 studies. Nineteen studies had high concerns regarding applicability of patient selection criteria.
TL is considered a multifactorial disease, responsible for psychological and social impacts due to scars and mutilating lesions generating stigma and self-deprecation in affected patients . Improvements in healthcare access and laboratory diagnosis are needed to overcome the impacts of this disease and should be encouraged . According to WHO’s Special Programme for Research and Training in Tropical Diseases (TDR), the ideal test must be affordable, sensitive, specific, user-friendly, rapid, equipment-free and delivered to end-users (ASSURED) . Immunological tests may fill these criteria since they are usually easy to perform, accessible and require minimally invasive sample collection. Therefore, the identification of sensitive and specific antigenic targets seems to be a promising step toward the improvement of TL-diagnosis. The studies analyzed here were conducted from 1996 to 2019, however, almost 50% of them were conducted in the last five years, mostly in Brazil or another country in the Americas. The increase in the number of studies is coincident with the interruption of the production of MST antigen in Brazil in 2015, which extinguished the simple and rapid immunodiagnostic for TL . This fact may have boosted research aimed at finding new diagnostic tools. Parasitological diagnosis was considered a reference standard test in 89.5% of the studies. Despite this technique being highly specific for TL-diagnosis, its sensitivity is limited and inversely correlated with disease duration . However, no test seems to present sufficiently high sensitivity and specificity to be used as a gold standard test. We observed a tendency for index tests to be more accurate if parasitological tests were used as a reference standard than other reference test such as MST and histopathology ( ). Polymerase chain reaction (PCR) was used as a reference standard test in 18 studies, generally in association with parasitological diagnosis. Overall, PCR appears to be a more suitable reference test, however, a standard protocol is urgently needed and encouraged, since distinct extraction methods, protocols and molecular targets have been used overtime . The ability to accurately identify TL-patients is essential for a diagnostic test, in view of the range of clinical forms, disease severity and treatment toxicity. Several studies have included patients with Chagas disease as non-TL cases, however, despite phylogenetic proximity, the inclusion of patients with clinical signs that do not resemble TL is at least questionable. For tests with diagnostic purposes, a better sample panel needs to be encouraged, including diseases such as sporotrichosis, paracoccidioidomycosis, hanseniasis, vasculitis, syphilis and other dermal or mucosal diseases, that represent confounding factors in clinical practice. Despite the distinct profiles in immune response usually reported for each clinical form of TL, some antigens presented high values of sensitivity, even for CL-patients. In general, higher levels of antibodies have been reported for ML-patients compared to CL-patients, the latter being characterized by a moderate Th1 immune response . In this way, it seems that problems related to antibody detection in CL-patients may be reduced by using sensitive targets and well-standardized procedures . Some antigenic targets were evaluated for TL-diagnosis without distinction of clinical form and, consequently, immune response profile. We believe that the accuracy of these antigenic targets may be improperly estimated in these specific cases. This systematic literature review found 79 different antigens, comprising 40 recombinant proteins, 24 synthetic peptides and 15 purified proteins. The identification and more refined selection of protein targets using recombinant proteins or synthetic peptides allows the development of more standardized techniques due to the possibility of generating the purest inputs. Some protein-families have been widely evaluated as antigenic targets for TL-immunodiagnosis, such as heat shock proteins (HSPs), histones and peroxiredoxins, with promising results. HSPs represent a highly conserved family of intracellular proteins of varying molecular weights in prokaryotic and eukaryotic cells, including cytosolic, mitochondrial, nuclear and endoplasmic reticulum resident proteins. They act as a chaperon in peptide folding and in the translocation of proteins to organelles, the prevention of protein aggregation, and the stabilization and degradation of proteins . HSPs have usually been identified by amino acid sequence homology and molecular weight, with HSP70 and HSP83 being the most abundant . These proteins are constitutively expressed throughout the life cycle of Leishmania , increasing expression in the vertebrate host due to variation in temperature and pH . The recombinant proteins HSP70 and HSP83, and the synthetic peptides extracted from those proteins, have been widely evaluated for TL-diagnosis [ , , , , , ]. The performance of these targets seems to be promising, with HSP83 presenting sensitivity of over 90% and high specificity with few cross reactions [ , , ]. Histones are conserved proteins bound to DNA establishing chromatin structure in eukaryotes. Several biological functions have been described for histones during Leishmania infection in susceptible hosts. Core nucleosomal Leishmania histones have been proposed as prominent intracellular pathoantigens, since immunological responses against histones seem to be involved in the pathological mechanisms of visceral leishmaniasis (VL) . In this way, this protein family has been extensively employed in ELISA for both human and canine VL [ – ]. The presence of antibodies against rH2B of L . peruviana , rH1 of L . braziliensis and rH2A, rH2B, rH3 and rH4 of L . infantum have been detected in sera from CL or ML patients. CARMELO et al. (2002) demonstrated that the antibody against histone H1 was specific for the parasite without cross reaction with human histones. However, moderate cross reactivity has been observed in a sample panel composed of Systemic Lupus Erythematosus (SLE) and Chagas disease [ , , ]. Peroxidoxin, also known as thiol-specific antioxidant protein, as well as tryparedoxin peroxidase, are peroxiredoxins, an antioxidant enzyme family [ – ]. This protein family has been described in a wide variety of organisms and several biological functions have been reported for Leishmania parasites, such as virulence factor and protection against reactive oxygen and nitrogen species . In this manner, they are directly associated with cell proliferation, senescence, apoptosis, and circadian rhythms . These proteins have been described in the secretome of L . braziliensis and the antigenicity of tryparedoxin peroxidase has also been evaluated for both human and canine VL-diagnosis [ – ]. Peroxidoxin is the protein target identified by the CL Detect Rapid Test (InBios International Inc.) for CL-diagnosis. Variable performance has been reported for this ICT, according to endemic region and, consequently, the Leishmania species involved, with better results for infections caused by L . tropica , with sensitivity ranging 65.4–73% and specificity 92–100% . This test, however, has not been evaluated in Brazil. Other recombinant proteins, such as cytochrome c oxidase, putative IgE histamine releasing factor, prohibitin, eukaryotic initiation factor 5a, cathepsin L-like peptide and small myristoylated protein-3, as well as hypothetical proteins, were evaluated in preliminary studies demonstrating potential as candidates for TL-immunodiagnosis, and so more studies are desirable [ , , , ]. Some promising synthetic peptides have been identified and employed in ELISA. The use of small fragments containing potent antigenic determinants is able to minimize non-specific reactions. LINK et al. (2017) identified three peptides by phage display, probably from GP63 glycoprotein, and presented 79% sensitivity in ELISA . COSTA et al. (2016) found high performance for three clones (A10, C12 and H7) in discriminating TL-patients from patients with other diseases and healthy individuals (100% sensitivity and specificity) . However, these short linear peptides may have some drawbacks, such as limited passive adsorption on polystyrene titration plates (ELISA-standard procedure), inability to identify serum antibodies that recognize conformational epitopes and problems considering reproducibility due to variation in inter-assay reactivity producing different batches . Despite the advantages, the absence of post-translational modifications of bacterially-expressed and chemically synthesized proteins comprises an important limitation for the employment of this biotechnology for immunodiagnosis. In this way, purified proteins can represent significant advantages, especially regarding immunoreactivity. This review found iron-superoxide dismutase to be a purified protein with interesting results, with more than 80% sensitivity for CL or ML diagnosis. However, being purified proteins, sensitivity and specificity may vary according to the type, source, and purity of the antigen used . Three polyclonal and monoclonal antibodies were evaluated for detecting Leishmania antigen by ICT and IHC [ , , , , , ]. The phase III studies included were ICT tests, that is, prospective studies in which the index and reference test were performed simultaneously in patients with clinical suspicion [ , , , ]. This is a commercial test that, despite its low sensitivity, has been useful in some localities due to the simple realization and high specificity, reducing the number of CL patients referred for diagnosis confirmation. High performance was observed in phase I studies for species-specific monoclonal antibody (IS2-2B4—A11/ XLVI-5B8-B3) employed in IHC, with 96% sensitivity and 100% specificity . More robust studies using monoclonal or polyclonal antibodies for TL-diagnosis need to be encouraged evaluating the performance in clinical practice. The strength of the present literature review is that it employed a comprehensive search strategy with four databases. One of the meaningful limitations may be the limited number of studies evaluating the same protein target, and so results need to be interpreted with caution. For this reason, a meta-analysis was not performed here. Additionally, it is important to consider that the risk of bias for many of the included studies was unclear and/or was high for some of the evaluated parameters: “Patient selection”, “Flow and Timing” and "Index test". Here, we identified a large number of antigenic targets that could help clinical diagnosis. However, the high number of proof-of-concept and phase I studies highlights the need to move forward with more refined and mainly prospective studies including patients with clinical suspicion of TL from different endemic regions and the most sensitive reference standard tests, to evaluate the diagnostic accuracy of antigenic targets reported in clinical practice.
S1 Fig Terms used in MEDLINE search. (TIF) Click here for additional data file. S1 Table PRISMA checklist. (DOCX) Click here for additional data file. S2 Table Antigenic targets used in ELISA for diagnosis of tegumentary leishmaniasis. (DOCX) Click here for additional data file. S3 Table Antigenic targets used in ELISA for diagnosis of cutaneous leishmaniasis. (DOCX) Click here for additional data file. S4 Table Antigenic targets for diagnosis of cutaneous leishmaniasis by other tests. (DOCX) Click here for additional data file. S5 Table Antigenic targets used in ELISA for diagnosis of mucosal leishmaniasis. (DOCX) Click here for additional data file.
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Assessing disintegration effectiveness: A thorough evaluation using the SeDeM-ODT expert system for doxylamine succinate orodispersible formulation | bd0c8e2f-a8be-40ae-a63d-428206c7632d | 11407626 | Pharmacology[mh] | In the past, extensive experimental work was required to optimize the powder blend’s flow, compressibility, and disintegration behavior; this increased the time and cost of formulation development. There is always a need for such pre-formulation tools that can elucidate the behavior of the powder/powder blend, guide the selection of excipients, and speed up the formulation development process. The SeDeM-ODT expert system is one such tool that has assisted formulators and researchers in examining the critical quality attributes of the powder/powder blend, affecting the quality features of the orodispersible tablet (ODT) formulations. As a pre-formulation technique, the expert system is applied to characterize powder substances based on various parameters related to flow, compressibility, and disintegration behavior. The physical profile of the powder substance is developed, suggesting its suitability for direct compression and buccodispersibility . Initially, the SeDeM expert system was used to characterize powder substances based on their rheological characteristics and compressibility. The SeDeM expert system could only provide an estimate of the suitability of the powder substance for direct compression . With development, the SeDeM-ODT expert system was created, a modified version of the SeDeM expert system. The modified assessment tool could simultaneously evaluate the powder substances for rheological characteristics, compressibility, and disintegration behavior . The older version of the SeDeM had twelve parameters divided into five indices. In contrast, the incorporation of the sixth index of disgregability resulted in the new and refined version of the SeDeM system, known as the SeDeM-ODT expert system. The new tool has three additional parameters that enhance the capacity of the expert system to characterize disintegration behavior . Overall, the parameters included in the SeDeM-ODT expert system are bulk density, tapped density, inter-particle porosity, Carr’s index, cohesion index, Hausner ratio, angle of repose, powder flow, loss on drying, hygroscopicity, particle size lower than 50 μm, homogeneity index, effervescence, disintegration with disc, and disintegration without disc . What differentiates the SeDeM-ODT expert system from the older version is the ability of the new tool to link the suitability of the pharmaceutical ingredient for direct compression and orodispersibility (buccodispersibility). The expert system for ODT formulations is based on Quality by Design (QbD) ICH Q8 guidelines and efficiently assesses the critical quality attributes of the final product . The development of an orodispersible tablet (ODT) formulation has ameliorated patient compliance and adherence among the various drug delivery technologies. Furthermore, ODTs offer many advantages, including improved bioavailability compared to immediate release tablets and capsules, increased stability compared to liquid formulations, and rapid onset of action. These attributes render them superior to conventional oral formulations like immediate release tablets, capsules, and oral liquids, particularly in certain patient types and conditions (such as pediatric and geriatric populations, psychologically unfit, and physiologically and neurologically impaired patients) . An ODT refers to a kind of medication that is designed to be disintegrated in the mouth. The Food and Drug Administration (FDA) considers ODT a solid preparation administered orally and disintegrating inside the oral cavity. Moreover, based on the United States pharmacopeial testing method for disintegration, the FDA states an in vitro disintegration time of 30 s or less for ODTs . European Pharmacopeia recommends that the orodispersible tablets disintegrate within 3 min before swallowing . Once in the mouth, the formulation quickly releases the active pharmaceutical ingredient (API), resulting in a fine suspension or solution in the saliva. Orodispersible tablets enhance patient compliance by being quickly ingested without chewing or drinking water. Additionally, they ensure precise dosing compared to liquid medication forms . Doxylamine Succinate is a multifaceted medication recognized for its various pharmacological effects. Chemically, Doxylamine, categorized as Ethanolamine, competitively binds with the H 1 receptors, resulting in antagonism. These histaminic receptors are situated in multiple locations, including the uterus, gastrointestinal tract, bronchial muscles, large blood vessels, etc. The sedating effect of the drug is linked to its action on the central and peripheral receptors. Doxylamine Succinate is primarily utilized for the short-term treatment of insomnia because of its sedative properties. Moreover, owing to its antiemetic action, it is also included in the formulations prepared for morning sickness, a condition specifically associated with pregnant women . Due to signal transmission inhibition to the vomiting center in the medulla oblongata, nausea and vomiting are antagonized . The presence of superdisintegrants is responsible for the rapid disintegration of orodispersible tablets . Superdisintegrants belong to the class of excipients that promote the breakage of a compressed tablet matrix into fine particles once the dosage form is in contact with the aqueous media. These specialized agents perform this process of mechanical disintegration through various mechanisms, including wicking and swelling, which primarily affect tablet disintegration. Additionally, other methods, such as heat of wetting, deformation recovery, particle repulsion theory, and gas evolution, may contribute to the disintegration of particulate tablets . The dissolution process of tablets containing sparingly soluble drug substances is typically hindered by the poor wettability of the tablet, resulting in slow liquid penetration into the tablet matrix. Hence, an increased disintegration time causes delayed release of the drug. Incorporating disintegrants resolves this problem . Disintegrating agents could be of natural or synthetic origin . This study focused on utilizing the SeDeM-ODT expert system to evaluate the effectiveness of the superdisintegrants in producing a quicker disintegration effect. The evaluation will ultimately assist in selecting an appropriate superdisintegrant for the orodispersible formulation of Doxylamine Succinate. 2.1. Materials Doxylamine Succinate (USP-NF: Doxylamine Succinate) was purchased from Harika Drugs Private Limited (Hyderabad, India). Povidone K30 (BP, PhEur, USP-NF: Povidone) was purchased from Boai NKY Pharmaceuticals Limited (Jiaozuo, China), Crospovidone (BP, PhEur, USP-NF: Crospovidone) was purchased from Jiaozuo Zhongwei Special Products Pharmaceutical Co. Limited (Jiaozuo, China), Guar Gum (USP-NF: Guar Gum) was purchased from Liberty Natural Products (Oregon, OR, USA), Avicel PH 102 (BP, USP-NF: Microcrystalline Cellulose) was purchased from Sigachi Industries Limited (Hyderabad, India), Sodium Saccharin (BP, PhEur, USP-NF: Saccharin) was purchased from Shanghai Shinesino Biotechnology Co. Limited (Shangai, China), Mannitol (BP, PhEur, USP-NF: Mannitol) was purchased from Hunan Jiudian Hongyang Pharmaceutical Co. Limited (Changsha, China), Aerosil (USP-NF: Colloidal Silicon Dioxide) was purchased from Hubei Huifu Nanomaterial Co. Limited (Yichang, China), and the remaining three excipients, i.e., Sodium Starch glycolate (BP, PhEur, USP-NF: Sodium Starch Glycolate), Croscarmellose Sodium (BP, PhEur, USP-NF: Croscarmellose Sodium), and Magnesium Stearate (BP, PhEur, USP-NF: Magnesium Stearate) were purchased from Vasa Pharmachem Private Limited (Ahmedabad, India). All the ingredients were pharmaceutical grade. 2.2. Characterization of excipients and active using SeDeM-ODT expert system The suitability of the powder blend for undergoing direct compression and conversion into an orodispersible formulation was assessed through the SeDeM-ODT expert system. This suitability determination was based on specific indices, including dimension, compressibility, flowability, stability, dosage, and disgregability, which were determined through the tool. Each index consisted of some parameters; overall, 15 parameters were evaluated through experimental work and mathematical equations. The parameter values obtained via the SeDeM-ODT expert system were converted into radii using appropriate factors. lists all the details of the SeDeM-ODT expert system, including the indices and parameters, acceptable ranges (values), and the conversion factors applied to obtain the desired radius value for each parameter of the tool . Some parameters were determined empirically following the stated methodology, while others were derived from the experimental values of other parameters. Various compendial methods described in the European and United States Pharmacopeia were employed for the experimental work . The Supplementary Materials details the testing procedures and the mathematical formulae used for the parameters. All tests were performed in triplicate to reduce the chances of variation . The SeDeM-ODT expert system determined the index of good compressibility and buccodispersibility (IGCB) for the candidates (excipients) selected to prepare the formulation. An IGCB value ≥ 5 signifies that the excipient could undergo direct compression, and the resulting tablet will have favorable buccodispersible qualities . 2.3. Characterization of active (Drug) using SeDeM expert system The active (drug) ingredient, i.e., Doxylamine Succinate, was evaluated with the SeDeM expert system for its appropriateness for direct compression. The tool was similar to the SeDeM-ODT expert system except for the disgregability index, i.e., the parameters of effervescence, disintegration with the disc, and disintegration without the disc were not part of the SeDeM expert system. Determination of the remaining 12 parameters, conversion of the parameter values into their respective radius, and finally, calculation of the IGC value gave an estimate of the active principle (drug) for its suitability to be directly compressed. An IGC value ≥ 5 suggests that Doxylamine Succinate has the potential to be compressed by the direct compression method. The active drug ingredient was also confirmed for its orodispersible characteristic by subjecting it to three additional parameters of the SeDeM-ODT expert system. The standard for acceptance was similar to the criteria described above for the excipients. 2.4. Construction of radar diagrams for the active (Drug) and the excipients The radii values obtained for each excipient and the active (drug) ingredient (Doxylamine Succinate) were used to construct the radar graphs. The radar diagrams were constructed using Microsoft Excel (version 365). The polygonal area covered in each radar diagram of the excipient indicated its suitability for direct compression and the buccodispersible characteristics of the respective ingredient. In contrast, the radar diagram of Doxylamine Succinate only highlighted its capability to be directly compressed, as the SeDeM expert system was used to evaluate the drug. The radar graphs for the excipients were constructed using 15 parameters of the SeDeM-ODT expert system, whereas 12 parameters assessed for the active moiety (drug) through the SeDeM expert system were utilized to build the radar diagram for Doxylamine Succinate. 2.5. Formulae for calculating Parameter Index (IP), Parameter Profile Index (IPP), Index of Good Compressibility (IGC), Index of Good Compressibility and Buccodispersibility (IGCB) There are different indices included in the SeDeM-ODT expert system. The use of SeDeM-ODT involves determining various parameters, highlighted in , and then utilizing these parameters to evaluate different indices, which finally helps identify the compressibility and buccodispersibility characteristics of excipients. These indices include parameter index, parameter profile index, index of good compressibility, and index of good compressibility and buccodispersibility. The complete details of these indices are mentioned in . 2.6. Formulation development of doxylamine succinate ODTs The orodispersible tablet formulation of Doxylamine Succinate was developed using a central composite design (CCD) approach with Design Expert® software (version 13). To enhance the robustness and reliability in the optimization process, rotatable CCD was applied with five center points with α value of 1.41421. Multiple center points in the CCD are particularly significant as they augment the ability to investigate the experimental error and the adequacy of the model to represent the responses within the testing region. The design proposed 52 formulations with varying percentages of independent variables. The direct compression method was utilized for the compression of the orodispersible formulation. The direct compression process involves mixing the formulation ingredients to form a powder blend and then directly compressing the blend. The compression of the tablets was performed on an eccentric single punch machine (Korsch, Berlin, Germany). The target weight was set to 125 mg on the tablet press. Within the permitted ranges, the formulation included the active drug ingredient (Doxylamine Succinate) and the excipients. Multiple literature sources confirmed the recommended quantities . Superdisintegrants of natural (Guar Gum) and synthetic (Crospovidone, Sodium Starch Glycolate, and Croscarmellose Sodium) origin were utilized to enhance the disintegration of the formulation. The disintegrating agent and the binder (Povidone) acted as factors (independent variables). Friability, hardness, wetting time, water absorption ratio, and in vitro disintegration were the responses (dependent variables) evaluated as a result of the variation of independent variables. Doxylamine Succinate was mixed with all the excipients, except Aerosil, in a mortar and pestle. Once combined, Aerosil was added, and the complete blend was mixed in a polybag for 5 min. The mode of adding the glidants (e.g., Aerosil) in a formulation affects the surface of solid powdered particles. This effect is not only limited to processing performance but also greatly affects the quality features of the finished product. By coating the solid particle surfaces, particularly the bonding sites, the interparticulate bonding is affected, which has a crucial impact on the tabletabilty of the pharmaceutical formulation . Hence, Aerosil was added and mixed in last after combining the remaining ingredients. The incorporation of Aerosil lastly minimized the interference of Aerosil with bonding, which is crucial for compressibility and compactibility. 2.7. Pre-compression tests The powder blends were evaluated for pre-compression parameters, including determining bulk density, tapped density, Carr’s index, Hausner’s ratio, and angle of repose. The tests were performed as per the pharmacopoeial specifications. 2.8. Evaluation of compressed tablets The formulated orodispersible Doxylamine Succinate tablets were examined for various characteristics to confirm the performance of the SeDeM-ODT expert system. These assessment parameters included hardness, thickness, diameter, weight variation, friability, water absorption ratio, wetting time, and in vitro disintegration time. 2.8.1. Hardness The hardness represents the tensile strength of the tablet formulation. The hardness of tablets is linked with the physical deformation of the particles in the blend, the role of the binder in the formulation, and the compressional force applied during the compression of the powder blend. Ten tablets from each formulation were randomly selected. Hardness was determined using the Erweka Hardness tester (Fujiwara Seisukusho Corporation, Wakayama, Japan). The crushing strength of the tablet was determined by placing the tablet diametrically on the lower anvil and applying pressure. The values were recorded in Newtons (N) . 2.8.2. Thickness and diameter Ten tablets from each batch (F1–F52) were selected at random. The thickness and diameter were determined using a vernier caliper (Seiko, Shanghai, China) . 2.8.3. Friability Removal of fine particles from the surface of the tablets results in a change in the weight of the tablets, as indicated by the value of the friability. Roche friabilator (Basel, Switzerland) was used to find the friability test on the sample of ten tablets of each formulation. A pre-weighed, dedusted sample of tablets was placed inside the friabilator. After 100 rotations, the tablets were weighed again. The difference in weight represented friability. The acceptable limit for weight loss is less than 1%. Friability was calculated using the following formula : % F r i a b i l i t y = I n i t i a l W e i g h t − F i n a l W e i g h t I n i t i a l W e i g h t × 100 2.8.4. Wetting time and water absorption ratio The method utilized by Bi et al. was employed to determine the wetting time and the water absorption ratio. A piece of tissue paper was folded twice and placed in a small petri dish containing 6 mL of water. The tablet was placed on the tissue paper, and the time the wetting process took to complete was recorded. The weight of the tablet was determined once the wetting was complete . The water absorption ratio (R) was determined using the following mathematical formula : W a t e r A b s o r p t i o n R a t i o = W a − W b W b × 100 where W a = weight of the tablet after absorption and W b = weight of the tablet before absorption. 2.8.5. In vitro disintegration An Erweka disintegration tester (Erweka ZT-2, Langen, Germany) was used to evaluate the disintegration time of the tablet samples. Six tablets from each formulation were selected randomly and assessed against the compendial requirements. The disintegration test was performed by placing one tablet in each tube, and the assembly was suspended into a 1000 mL beaker containing distilled water maintained at 37 ± 2°C . The European Pharmacopeia mentions that ODTs must disintegrate within 3 min . Doxylamine Succinate (USP-NF: Doxylamine Succinate) was purchased from Harika Drugs Private Limited (Hyderabad, India). Povidone K30 (BP, PhEur, USP-NF: Povidone) was purchased from Boai NKY Pharmaceuticals Limited (Jiaozuo, China), Crospovidone (BP, PhEur, USP-NF: Crospovidone) was purchased from Jiaozuo Zhongwei Special Products Pharmaceutical Co. Limited (Jiaozuo, China), Guar Gum (USP-NF: Guar Gum) was purchased from Liberty Natural Products (Oregon, OR, USA), Avicel PH 102 (BP, USP-NF: Microcrystalline Cellulose) was purchased from Sigachi Industries Limited (Hyderabad, India), Sodium Saccharin (BP, PhEur, USP-NF: Saccharin) was purchased from Shanghai Shinesino Biotechnology Co. Limited (Shangai, China), Mannitol (BP, PhEur, USP-NF: Mannitol) was purchased from Hunan Jiudian Hongyang Pharmaceutical Co. Limited (Changsha, China), Aerosil (USP-NF: Colloidal Silicon Dioxide) was purchased from Hubei Huifu Nanomaterial Co. Limited (Yichang, China), and the remaining three excipients, i.e., Sodium Starch glycolate (BP, PhEur, USP-NF: Sodium Starch Glycolate), Croscarmellose Sodium (BP, PhEur, USP-NF: Croscarmellose Sodium), and Magnesium Stearate (BP, PhEur, USP-NF: Magnesium Stearate) were purchased from Vasa Pharmachem Private Limited (Ahmedabad, India). All the ingredients were pharmaceutical grade. The suitability of the powder blend for undergoing direct compression and conversion into an orodispersible formulation was assessed through the SeDeM-ODT expert system. This suitability determination was based on specific indices, including dimension, compressibility, flowability, stability, dosage, and disgregability, which were determined through the tool. Each index consisted of some parameters; overall, 15 parameters were evaluated through experimental work and mathematical equations. The parameter values obtained via the SeDeM-ODT expert system were converted into radii using appropriate factors. lists all the details of the SeDeM-ODT expert system, including the indices and parameters, acceptable ranges (values), and the conversion factors applied to obtain the desired radius value for each parameter of the tool . Some parameters were determined empirically following the stated methodology, while others were derived from the experimental values of other parameters. Various compendial methods described in the European and United States Pharmacopeia were employed for the experimental work . The Supplementary Materials details the testing procedures and the mathematical formulae used for the parameters. All tests were performed in triplicate to reduce the chances of variation . The SeDeM-ODT expert system determined the index of good compressibility and buccodispersibility (IGCB) for the candidates (excipients) selected to prepare the formulation. An IGCB value ≥ 5 signifies that the excipient could undergo direct compression, and the resulting tablet will have favorable buccodispersible qualities . The active (drug) ingredient, i.e., Doxylamine Succinate, was evaluated with the SeDeM expert system for its appropriateness for direct compression. The tool was similar to the SeDeM-ODT expert system except for the disgregability index, i.e., the parameters of effervescence, disintegration with the disc, and disintegration without the disc were not part of the SeDeM expert system. Determination of the remaining 12 parameters, conversion of the parameter values into their respective radius, and finally, calculation of the IGC value gave an estimate of the active principle (drug) for its suitability to be directly compressed. An IGC value ≥ 5 suggests that Doxylamine Succinate has the potential to be compressed by the direct compression method. The active drug ingredient was also confirmed for its orodispersible characteristic by subjecting it to three additional parameters of the SeDeM-ODT expert system. The standard for acceptance was similar to the criteria described above for the excipients. The radii values obtained for each excipient and the active (drug) ingredient (Doxylamine Succinate) were used to construct the radar graphs. The radar diagrams were constructed using Microsoft Excel (version 365). The polygonal area covered in each radar diagram of the excipient indicated its suitability for direct compression and the buccodispersible characteristics of the respective ingredient. In contrast, the radar diagram of Doxylamine Succinate only highlighted its capability to be directly compressed, as the SeDeM expert system was used to evaluate the drug. The radar graphs for the excipients were constructed using 15 parameters of the SeDeM-ODT expert system, whereas 12 parameters assessed for the active moiety (drug) through the SeDeM expert system were utilized to build the radar diagram for Doxylamine Succinate. There are different indices included in the SeDeM-ODT expert system. The use of SeDeM-ODT involves determining various parameters, highlighted in , and then utilizing these parameters to evaluate different indices, which finally helps identify the compressibility and buccodispersibility characteristics of excipients. These indices include parameter index, parameter profile index, index of good compressibility, and index of good compressibility and buccodispersibility. The complete details of these indices are mentioned in . The orodispersible tablet formulation of Doxylamine Succinate was developed using a central composite design (CCD) approach with Design Expert® software (version 13). To enhance the robustness and reliability in the optimization process, rotatable CCD was applied with five center points with α value of 1.41421. Multiple center points in the CCD are particularly significant as they augment the ability to investigate the experimental error and the adequacy of the model to represent the responses within the testing region. The design proposed 52 formulations with varying percentages of independent variables. The direct compression method was utilized for the compression of the orodispersible formulation. The direct compression process involves mixing the formulation ingredients to form a powder blend and then directly compressing the blend. The compression of the tablets was performed on an eccentric single punch machine (Korsch, Berlin, Germany). The target weight was set to 125 mg on the tablet press. Within the permitted ranges, the formulation included the active drug ingredient (Doxylamine Succinate) and the excipients. Multiple literature sources confirmed the recommended quantities . Superdisintegrants of natural (Guar Gum) and synthetic (Crospovidone, Sodium Starch Glycolate, and Croscarmellose Sodium) origin were utilized to enhance the disintegration of the formulation. The disintegrating agent and the binder (Povidone) acted as factors (independent variables). Friability, hardness, wetting time, water absorption ratio, and in vitro disintegration were the responses (dependent variables) evaluated as a result of the variation of independent variables. Doxylamine Succinate was mixed with all the excipients, except Aerosil, in a mortar and pestle. Once combined, Aerosil was added, and the complete blend was mixed in a polybag for 5 min. The mode of adding the glidants (e.g., Aerosil) in a formulation affects the surface of solid powdered particles. This effect is not only limited to processing performance but also greatly affects the quality features of the finished product. By coating the solid particle surfaces, particularly the bonding sites, the interparticulate bonding is affected, which has a crucial impact on the tabletabilty of the pharmaceutical formulation . Hence, Aerosil was added and mixed in last after combining the remaining ingredients. The incorporation of Aerosil lastly minimized the interference of Aerosil with bonding, which is crucial for compressibility and compactibility. The powder blends were evaluated for pre-compression parameters, including determining bulk density, tapped density, Carr’s index, Hausner’s ratio, and angle of repose. The tests were performed as per the pharmacopoeial specifications. The formulated orodispersible Doxylamine Succinate tablets were examined for various characteristics to confirm the performance of the SeDeM-ODT expert system. These assessment parameters included hardness, thickness, diameter, weight variation, friability, water absorption ratio, wetting time, and in vitro disintegration time. 2.8.1. Hardness The hardness represents the tensile strength of the tablet formulation. The hardness of tablets is linked with the physical deformation of the particles in the blend, the role of the binder in the formulation, and the compressional force applied during the compression of the powder blend. Ten tablets from each formulation were randomly selected. Hardness was determined using the Erweka Hardness tester (Fujiwara Seisukusho Corporation, Wakayama, Japan). The crushing strength of the tablet was determined by placing the tablet diametrically on the lower anvil and applying pressure. The values were recorded in Newtons (N) . 2.8.2. Thickness and diameter Ten tablets from each batch (F1–F52) were selected at random. The thickness and diameter were determined using a vernier caliper (Seiko, Shanghai, China) . 2.8.3. Friability Removal of fine particles from the surface of the tablets results in a change in the weight of the tablets, as indicated by the value of the friability. Roche friabilator (Basel, Switzerland) was used to find the friability test on the sample of ten tablets of each formulation. A pre-weighed, dedusted sample of tablets was placed inside the friabilator. After 100 rotations, the tablets were weighed again. The difference in weight represented friability. The acceptable limit for weight loss is less than 1%. Friability was calculated using the following formula : % F r i a b i l i t y = I n i t i a l W e i g h t − F i n a l W e i g h t I n i t i a l W e i g h t × 100 2.8.4. Wetting time and water absorption ratio The method utilized by Bi et al. was employed to determine the wetting time and the water absorption ratio. A piece of tissue paper was folded twice and placed in a small petri dish containing 6 mL of water. The tablet was placed on the tissue paper, and the time the wetting process took to complete was recorded. The weight of the tablet was determined once the wetting was complete . The water absorption ratio (R) was determined using the following mathematical formula : W a t e r A b s o r p t i o n R a t i o = W a − W b W b × 100 where W a = weight of the tablet after absorption and W b = weight of the tablet before absorption. 2.8.5. In vitro disintegration An Erweka disintegration tester (Erweka ZT-2, Langen, Germany) was used to evaluate the disintegration time of the tablet samples. Six tablets from each formulation were selected randomly and assessed against the compendial requirements. The disintegration test was performed by placing one tablet in each tube, and the assembly was suspended into a 1000 mL beaker containing distilled water maintained at 37 ± 2°C . The European Pharmacopeia mentions that ODTs must disintegrate within 3 min . The hardness represents the tensile strength of the tablet formulation. The hardness of tablets is linked with the physical deformation of the particles in the blend, the role of the binder in the formulation, and the compressional force applied during the compression of the powder blend. Ten tablets from each formulation were randomly selected. Hardness was determined using the Erweka Hardness tester (Fujiwara Seisukusho Corporation, Wakayama, Japan). The crushing strength of the tablet was determined by placing the tablet diametrically on the lower anvil and applying pressure. The values were recorded in Newtons (N) . Ten tablets from each batch (F1–F52) were selected at random. The thickness and diameter were determined using a vernier caliper (Seiko, Shanghai, China) . Removal of fine particles from the surface of the tablets results in a change in the weight of the tablets, as indicated by the value of the friability. Roche friabilator (Basel, Switzerland) was used to find the friability test on the sample of ten tablets of each formulation. A pre-weighed, dedusted sample of tablets was placed inside the friabilator. After 100 rotations, the tablets were weighed again. The difference in weight represented friability. The acceptable limit for weight loss is less than 1%. Friability was calculated using the following formula : % F r i a b i l i t y = I n i t i a l W e i g h t − F i n a l W e i g h t I n i t i a l W e i g h t × 100 The method utilized by Bi et al. was employed to determine the wetting time and the water absorption ratio. A piece of tissue paper was folded twice and placed in a small petri dish containing 6 mL of water. The tablet was placed on the tissue paper, and the time the wetting process took to complete was recorded. The weight of the tablet was determined once the wetting was complete . The water absorption ratio (R) was determined using the following mathematical formula : W a t e r A b s o r p t i o n R a t i o = W a − W b W b × 100 where W a = weight of the tablet after absorption and W b = weight of the tablet before absorption. An Erweka disintegration tester (Erweka ZT-2, Langen, Germany) was used to evaluate the disintegration time of the tablet samples. Six tablets from each formulation were selected randomly and assessed against the compendial requirements. The disintegration test was performed by placing one tablet in each tube, and the assembly was suspended into a 1000 mL beaker containing distilled water maintained at 37 ± 2°C . The European Pharmacopeia mentions that ODTs must disintegrate within 3 min . 3.1. SeDeM-Based characterization of ingredients The study used the SeDeM-ODT expert system to assess the compressibility and buccodispersibility of various excipients, including superdisintegrants (natural and synthetic superdisintegrants), Mannitol, Sodium Saccharin, and Microcrystalline Cellulose. The tool mainly focused on assessing superdisintegrants to identify and select the most appropriate superdisintegrant for the orodispersible formulation. The SeDeM-ODT expert system’s evaluation framework incorporated 15 parameters, which are outlined in . The parameters were determined using a combination of calculative and experimental procedures, as highlighted in and Supplementary Materials. The quantitative data collected for each ingredient enabled the determination of the parameter index (IP), parameter profile index (IPP), and the index of good compressibility and buccodispersibility (IGCB), as shown in . The numerical values obtained from all the parameters were converted into their respective radii using particular mathematical factors detailed in to enable a thorough study. The radii were graphically represented using radar charts, as seen in . Using the IGCB values and the polygonal area depicted in radar graphs for the excipients, this analytical method helped to characterize the studied ingredients thoroughly. The results outlined in revealed that among the four types of disintegrating agents, Crospovidone has the highest IGCB value (IGCB = 6.396). In contrast, Croscarmellose Sodium, Sodium Starch Glycolate, and Guar Gum had IGCB values of 5.137, 5.346, and 5.327, respectively. Although Doxylamine Succinate was cleared for the compressibility criteria once it gave the value of IGC ≥ 5, its lower disgregability characteristic made the therapeutic agent inappropriate for an orodispersible formulation. Hence, adding a suitable superdisintegrant in an appropriate quantity helped improve the orodispersibility of the therapeutic moiety. 3.2. Formulation development and assessment of disintegration effectiveness Direct compression of CCD proposed formulations produced tablets, each weighing 125 mg and consisting of 20% API (Doxylamine Succinate). The blends were subjected to a pre-compression examination. The examination included determining bulk density, tapped density, Carr’s index, Hausner’s ratio, and angle of repose. As shown in , all the powder blends (F1–F52) showed excellent flow characteristics, as the average value of the angle of repose ranged from 26.990° to 30.044° , whereas formulations F1–F26 exhibited better compressibility owing to lower Carr’s index values in contrast to higher values for formulations F27–F52. The compressed formulations were assessed for various parameters, as shown in . The determination of post-compression parameters helped identify an optimized formulation that fulfills the requirements of an orodispersible formulation. Moreover, these tests also helped in assessing the performance of the disintegrants, which gave a comparison among the four different superdisintegrants used in the study. Formulation containing Guar Gum (F40–F52) as a disintegrating agent resulted in tablets of the lowest hardness ( x ¯ = 2.69 kg/cm2, S.D. = 0.09). Orodispersible formulations containing Crospovidone (F1–F13) produced tablets with an average hardness of 3.43 kg/cm2 ± 0.131, which was the highest hardness recorded among other formulations consisting of Guar Gum, Croscarmellose Sodium, or Sodium Starch Glycolate as the superdisintegrants. The F7 formulation, containing Crospovidone as a superdisintegrant, was identified as an optimized formulation, showing the lowest disintegration time of 27 s with the water absorption ratio and wetting time of 101.50 and 9.89 s, respectively. The study used the SeDeM-ODT expert system to assess the compressibility and buccodispersibility of various excipients, including superdisintegrants (natural and synthetic superdisintegrants), Mannitol, Sodium Saccharin, and Microcrystalline Cellulose. The tool mainly focused on assessing superdisintegrants to identify and select the most appropriate superdisintegrant for the orodispersible formulation. The SeDeM-ODT expert system’s evaluation framework incorporated 15 parameters, which are outlined in . The parameters were determined using a combination of calculative and experimental procedures, as highlighted in and Supplementary Materials. The quantitative data collected for each ingredient enabled the determination of the parameter index (IP), parameter profile index (IPP), and the index of good compressibility and buccodispersibility (IGCB), as shown in . The numerical values obtained from all the parameters were converted into their respective radii using particular mathematical factors detailed in to enable a thorough study. The radii were graphically represented using radar charts, as seen in . Using the IGCB values and the polygonal area depicted in radar graphs for the excipients, this analytical method helped to characterize the studied ingredients thoroughly. The results outlined in revealed that among the four types of disintegrating agents, Crospovidone has the highest IGCB value (IGCB = 6.396). In contrast, Croscarmellose Sodium, Sodium Starch Glycolate, and Guar Gum had IGCB values of 5.137, 5.346, and 5.327, respectively. Although Doxylamine Succinate was cleared for the compressibility criteria once it gave the value of IGC ≥ 5, its lower disgregability characteristic made the therapeutic agent inappropriate for an orodispersible formulation. Hence, adding a suitable superdisintegrant in an appropriate quantity helped improve the orodispersibility of the therapeutic moiety. Direct compression of CCD proposed formulations produced tablets, each weighing 125 mg and consisting of 20% API (Doxylamine Succinate). The blends were subjected to a pre-compression examination. The examination included determining bulk density, tapped density, Carr’s index, Hausner’s ratio, and angle of repose. As shown in , all the powder blends (F1–F52) showed excellent flow characteristics, as the average value of the angle of repose ranged from 26.990° to 30.044° , whereas formulations F1–F26 exhibited better compressibility owing to lower Carr’s index values in contrast to higher values for formulations F27–F52. The compressed formulations were assessed for various parameters, as shown in . The determination of post-compression parameters helped identify an optimized formulation that fulfills the requirements of an orodispersible formulation. Moreover, these tests also helped in assessing the performance of the disintegrants, which gave a comparison among the four different superdisintegrants used in the study. Formulation containing Guar Gum (F40–F52) as a disintegrating agent resulted in tablets of the lowest hardness ( x ¯ = 2.69 kg/cm2, S.D. = 0.09). Orodispersible formulations containing Crospovidone (F1–F13) produced tablets with an average hardness of 3.43 kg/cm2 ± 0.131, which was the highest hardness recorded among other formulations consisting of Guar Gum, Croscarmellose Sodium, or Sodium Starch Glycolate as the superdisintegrants. The F7 formulation, containing Crospovidone as a superdisintegrant, was identified as an optimized formulation, showing the lowest disintegration time of 27 s with the water absorption ratio and wetting time of 101.50 and 9.89 s, respectively. The SeDeM-ODT expert system is an advancement of the SeDeM expert system for developing orodispersible tablets (ODTs). This research utilized this methodology due to its systematic and quantitative approach in evaluating the suitability of the pharmaceutical ingredients for direct compression. Various literature has identified that the SeDeM-ODT expert system helps reduce the number of extra, repetitive laboratory tests since it provides insights into a powder mixture’s rheological and compactable properties for producing conventional tablets through direct compression. Additionally, it offers information that deepens the understanding of formulation design . The SeDeM expert system assessed the compressibility characteristics of Doxylamine Succinate. The index of good compressibility (IGC) obtained through the tool proved the compression characteristic and appropriateness of the active pharmaceutical ingredient (API), i.e., the drug, for direct compression. An IGC value greater than 5, as in the case of Doxylamine Succinate, represented the suitability of the material to be directly compressed. The active drug ingredient did not produce satisfactory results for buccodispersibility when subjected to the SeDeM-ODT expert system. Characterizing the API through the SeDeM-ODT expert system was not essential, as the active drug principle is usually considered deficient in the disgregability parameter, which improves by adding disintegrating agents . Superdisintegrants were subjected to SeDeM-ODT expert system tests to evaluate their compressibility and buccodispersibility features. Various micromeritic properties obtained for different experimentally determined and calculated values were converted into radii values. These radii values were transformed into radar diagrams. The radar graphs depicted the polygonal diagrams that illustrated the micromeritic properties of the formulation ingredients. The radar graph would be the circumscribed regular polygon if all the radii values were equal to 10. The polygon is termed a dodecagon in the case of Doxylamine Succinate (a drug), and a pentadecagon, in the case of the excipients. The polygonal area of the radar diagram of the drug, constructed using the SeDeM expert system, represented the suitability of the Doxylamine Succinate to undergo direct compression. In contrast, the polygonal area of the radar charts for superdisintegrants, obtained through applying the SeDeM-ODT expert system, showed their appropriateness for conversion into an ODT by direct compression. A larger polygonal area represents the more outstanding suitability of the formulation ingredient . The radar plots constructed using data obtained from the SeDeM-ODT expert system proved the suitability of Crospovidone in an ODT formulation, as it had the largest shaded polygonal area among the four superdisintegrants. The determination of the IGCB value further supported and ranked Crospovidone on top (IGCB = 6.396) among the remaining three superdisintegrants, i.e., Sodium Starch Glycolate (IGCB = 5.346), Croscarmellose Sodium (IGCB = 5.137) and Guar Gum (IGCB = 5.237). These findings were in line with the findings of Rao, Sapate and Sonawane , in which Crospovidone had the highest IGCB value (5.75) among Sodium Starch Glycolate and Croscarmellose Sodium used in formulation development. Hence, Crospovidone demonstrated ideal dimensional properties, including optimal compressibility, good flowability, required lubricity, and outstanding disgregability. What differed from the mentioned study was the researcher’s finding that Sodium Starch Glycolate has an IGCB value of less than five, representing its lack of buccodispersibility. In contrast, Glycolys® (a brand of Sodium Starch Glycolate) gave an IGCB value above 5 when evaluated through SeDeM-ODT expert system tests by Aguilar-Díaz, García-Montoya, Suñe-Negre, Pérez-Lozano, Miñarro and Ticó . The findings of Aguilar-Díaz, García-Montoya, Suñe-Negre, Pérez-Lozano, Miñarro and Ticó complied with our study, proving its good buccodispersible characteristic. The evaluation of flowability and compressibility for the prepared powdered blends (F1–F52) judged the effect of the added disintegrant in the formulation. Appropriate flowability was observed for all the formulations, with the angle of repose values ranging from 26.97° to 32.01°. Formulations containing Crospovidone (F1–F14) had the angle of repose values on the lower side of the range, consistent with the research work of Puttewar, Kshirsagar, Chandewar and Chikhale for Doxylamine and Pyridoxine combined formulation. Furthermore, a change of disintegrant in formulations (F1–F52) showed a shift in compressibility behavior, as exhibited by the compressibility index (Carr’s Index) value. The average value of 12.895% ± 0.537 not only resembled the findings of previous research but also supported the current SeDeM-ODT expert system findings, which marked Crospovidone to have the best compressibility and flowability characteristics among the other superdisintegrants under investigation. Various post-compression parameters evaluated for the compressed Doxylamine Succinate tablets endorsed the results of the SeDeM-ODT expert system and confirmed the tool’s effectiveness for evaluating the disintegrants. Wetting time and water absorption ratio values were used to compare the formulations, which differed due to varying concentrations of Povidone and the type and concentration of superdisintegrants. The average wetting time and water absorption ratio for formulations F1–F13 were 10.695 s ± 0.50 and 101.519 ± 0.250, respectively. These values made the formulations containing Crospovidone (F1–F13) superior to the others (F14–F52). Among the synthetic superdisintegrants, the wetting time of Crospovidone formulations was the lowest, followed by Croscarmellose Sodium and Sodium Starch Glycolate formulations. The wetting time of the natural disintegrant, Guar Gum (F40–F52), was comparable with the Sodium Starch Glycolate formulations. The results for synthetic superdisintegrants closely resembled the findings of Puttewar, Kshirsagar, Chandewar and Chikhale , particularly regarding sequence and wetting time values. Moreover, the formulations of Crospovidone in our study exhibited a higher water absorption ratio, consistent with the research outcomes of Puttewar, Kshirsagar, Chandewar and Chikhale . Lower wetting time and a higher water absorption ratio mark Crospovidone as a suitable superdisintegrant for an orodispersible formulation. Past investigations have compared the disintegration performance of superdisintegrants in various formulations. Comparing the current results with past scientific studies revealed that Crospovidone exhibits quicker disintegration compared to Croscarmellose Sodium and Sodium Starch Glycolate. Yousaf, et al. concluded that adding Crospovidone to Stevia tablets resulted in a faster disintegration time than Croscarmellose Sodium and Sodium Starch Glycolate. Dubey, et al. found that Ibuprofen mouth dissolving tablets with Crospovidone disintegrated faster and released Ibuprofen more quickly than those with Croscarmellose Sodium. The disintegration time for the orodispersible formulations containing Guar Gum was between 60 and 61 s. This time was higher than the disintegration time reported in the literature . The research findings suggested the F7 formulation (containing Crospovidone) as an optimized formulation. The formulation exhibited the shortest disintegration time, the lowest wetting time, and the highest water absorption ratio. The formulation showed appropriate hardness and an acceptable friability. The findings affirmed the appropriateness of the SeDeM-ODT expert system in assessing the ingredients and assured the tool’s strength in selecting the correct ingredients that produce promising results. The SeDeM-ODT expert system significantly improves the efficiency and predictability of orodispersible tablet (ODT) formulation processes, making a crucial contribution to pharmaceutical technology by aiding in the creation of more efficient and accessible drug delivery systems. The current research witnessed the expert system tool’s efficiency in identifying each excipient’s performance, particularly the superdisintegrants. The assessment tool assessed the suitability of each disintegrant and identified Crospovidone as producing quicker disintegration of the Doxylamine Succinate orodispersible formulation in comparison with other synthetic (Croscarmellose Sodium and Sodium Starch Glycolate) and natural (Guar Gum) disintegrating agents. S1 File SeDeM-ODT expert system. Details (method and formula), of 15 parameters included in the expert system are mentioned in the supplementary material. (DOCX) |
Root colonization by beneficial rhizobacteria | 81f5c38f-7353-4c02-85c2-093294c00e07 | 10786197 | Microbiology[mh] | The significance of plant- and animal-associated microbiomes to their hosts has been well recognized for decades (Mendes et al. ). Microbes inhabiting the rhizosphere are critical determinants of plant growth and health. Beneficial rhizobacteria show great potential in agricultural production since they offer a variety of beneficial functions for plants, such as promoting plant growth and enhancing plant abiotic stress tolerance by secreting phytohormones and some specific signaling molecules and protecting host plants by inducing systemic resistance and direct antagonism with soil-borne pathogens (Pieterse et al. ). These beneficial bacteria can generally be used in agriculture as biofertilizers or microbial agents and are essential in green agricultural production. Rhizosphere colonization is one of the most important features of rhizobacteria that determines their survival and propagation, which are prerequisites for versatile bacteria to exert their beneficial functions on host plants (Mendes et al. ). The rhizosphere includes plant roots and the surrounding soil influenced by root exudates (Dessaux et al. ), therefore, bacteria surviving and forming firmly community in rhizosphere soil, on rhizoplane and in root endosphere were all defined as the term “rhizosphere colonization” (Fig. ). They can selectively colonize distinctively on primary root or lateral root, on spatial axis of the root, inside root, or root surface. Rhizobacteria colonize the plant root in a highly heterogeneous manner, covering 10%–40% of the root surface (Danhorn and Fuqua ), and some endophytic bacteria can also live inside root tissue. Since the colonization process of symbiotic bacteria, which reside in living plant cells or is surrounded by a membrane compartment (Reinhold-Hurek and Hurek ), has been thoroughly reviewed (Roy et al. , Soyano et al. , Yang et al. , González-Guerrero et al. , Jain et al. , Rahmat et al. , Xu and Wang ), this review only focuses on the root colonization of nonsymbiotic beneficial rhizobacteria. Plants are the major players in the rhizosphere and they affect bacterial colonization. Plants secrete 11%–40% of photosynthesis products into the rhizosphere as root exudates (Zhalnina et al. , Du et al. ), which cause the rhizosphere to be a highly active site for microbial colonization than bulk soil. Undoubtedly, the colonization of beneficial rhizobacteria is largely impacted by the abundance and composition of root exudates. Root exudates can be divided into the low molecular weight and high molecular weight compounds. Low molecular weight compounds include sugars, organic acids, amino acids, alcohols, volatile compounds, and some secondary metabolites. The high molecular weight compounds are less diverse but yield a higher mass % of root exudates, and those compounds are mostly polysaccharides and proteins (Chagas et al. ). Although the rhizosphere is rich in carbon resources for bacterial growth, it is generally accepted that plants are able to expel unfavorable bacteria through the plant immune system, which is also a crucial factor that determines bacterial colonization in the rhizosphere (Shu et al. ). The concept of plant immunity has been well-established in interactions with pathogens and symbiotic microbes. Recently, the importance of plant immunity in modulating nonsymbiotic rhizobacteria colonization has been fully recognized (Shu et al. ). Additionally, a “cry-for-help” theory proposed that a stressed plant can recruit beneficial bacteria to colonize the rhizosphere (Lebeis et al. , Rolfe et al. ). All these factors influence the rhizosphere colonization of the nonsymbiotic beneficial bacteria. The biology of root colonization by rhizobacteria has advanced in recent years. Rhizosphere colonization is a complex process involving several steps that depend on bacterial lifestyles. They can colonize in rhizosphere soil, on rhizoplane, or endophytically based on some of these steps (Fig. ). In general, rhizobacteria colonize the root in a sequential process that begins with rhizosphere chemotaxis, root attachment, sometimes followed by rhizoplane biofilm formation or endophytic colonization for some strains. Bacterial chemotactic motility involves a conserved intracellular signal transduction pathway and varied signal sensors and drives the selection of initial sites for attachment and colonization site migration, which vary depending on the strain and plant species (Sampedro et al. , Li et al. ). After moving to the rhizosphere, some bacterial strains need to stop moving and adhere to the root surface, which is defined as root attachment (Knights et al. ). During this period, bacteria must exert their role to overcome the plant immune response for further colonization. Rapid proliferation using root exudates as the main carbon resources is one of most important process for colonization. Some of the rhizobacteria formed biofilm on the rhizoplane in a multispecies manner (Beauregard et al. ). During this period, bacteria have to compete for some scarce elements in the rhizosphere to support proliferation and biofilm formation (Liu et al. ). Additionally, some endophytes begin penetrating into plant tissue during life on the root surface (Dudeja et al. , Mushtaq et al. ). In general, these processes involve complicated lifestyle transformation and intracellular signal transduction that are influenced by plants and the environment. However, the current understanding of bacterial colonization in the rhizosphere is scattered, especially for beneficial nonsymbiotic rhizobacteria. In this review, we will summarize the knowledge on the rhizosphere colonization of nonsymbiotic beneficial bacteria along with the sequential process and conclude the underlying regulatory molecular mechanism, the important bacterial genes involved in the processes, and the influencing factors. We will also review the advances in “cry-for-help” theory. The difference in colonization processes and the plant‒microbe interactions that determine colonization between nonsymbiotic bacteria will be compared with that of symbiotic/pathogenic bacteria. Finally, we propose several artificial strategies to enhance the colonization of beneficial rhizobacteria, which would benefit the application of beneficial rhizobacteria in agriculture. The scope of this review is comprehensively summarizing the rhizosphere colonization processes of the nonsymbiotic bacteria to promote the application of beneficial rhizobacteria in agriculture.
Chemotaxis is a motility-based ability of microbes to sense chemical gradients and direct their movement either up the gradient toward the source (attraction) or down the gradient away from the source (repulsion). Motility and chemotaxis of vegetative bacterial cells are essential for rhizosphere colonization, as well as for establishing primary bacteria–root interactions (Feng et al. ). Root exudates activate chemosensory pathways and cause motile bacteria to move toward the root. Rhizobacterial motility can be achieved by various mechanisms, including flagellar swimming, swarming, twitching, and gliding motility (Kearns ). Bacterial swimming is achieved by rotating flagella to generate a force that moves the cell forward (Sampedro et al. ). Swarming is a multicellular movement over a solid surface that is driven by a raft-like flagellar complex from the community (Kearns ). Twitching is a motility based on the extension–tethering–retraction–extension of type IV pili (Sampedro et al. ). Gliding motility is a definition of cells moving smoothly along their long axis in the absence of any visible organelle (Mignot ). Chemotaxis and motility then drive the selection of the initial contact site on the root. The success of these processes determines the root colonization efficiency. It is evident that either inactivation of chemosensory activity by knocking out all the chemotaxis receptors or blocking motility by deleting the genes responsible for synthesizing flagellin in a rhizobacterium led to a 100-fold decrease in root colonization efficiency (Feng et al. , Tzipilevich et al. ). Chemotaxis process and signaling Chemotaxis intracellular signaling is conserved in many bacterial species. Bacterial chemotaxis toward root exudates is initiated by the perception of chemoeffectors in root exudates by bacterial transmembrane chemotaxis receptors, which are specifically termed methyl-accepting chemotaxis proteins (MCPs) (Feng et al. ). Generally, chemotaxis receptor proteins always exist in a ternary complex with the CheA histidine kinase and the coupling protein CheW. Chemotaxis receptors are transmembrane proteins that constitute a highly varied ligand-binding domain (LBD) in the extracellular space for signal sensing, an intracellular highly conserved methyl-accepting (MA) domain for adaptation, which is the standard criterion for the annotation of proteins as MCPs (Sampedro et al. ). The MCPs selectively recognize and bind to specific ligands, such as root exudates, resulting in molecular signals that transduce across the cellular membrane. This transduction subsequently modulates the autophosphorylation rate of the histidine kinase CheA in a CheW-dependent manner (Lacal et al. ). CheA and CheY constitute a two-component system. The phosphorylation of CheA affects the transphosphorylation of the CheY response regulator. Phosphorylated CheY binds to motor proteins that are responsible for driving various kinds of motility in different bacteria. In addition, the turnover of methylation and demethylation of the MA domain of the MCPs was deployed as an adaptation system, and methylation increased while demethylation decreased the autophosphorylation activity of CheA (Sampedro et al. ). This whole signaling pathway is extremely well-conserved in many bacteria, including Escherichia coli, Bacillus spp. and Pseudomonas spp. The variety of MCPs with different LBDs determines the molecules to be sensed by the bacteria (Sanchis-López et al. ). In rhizobacteria, an expansive array of MCPs and their corresponding ligands have been identified, with notable examples found in species such as Pseudomonas putida, Bacillus velezensis , and Sinorhizobium meliloti . Allard-Massicotte et al. ( ) demonstrated that root colonization of Bacillus subtilis involves multiple chemotaxis receptors. An efficient colonizer in the rhizosphere should respond to a broad range of compounds in root exudates. For example, the colonization of P. putida KT2440 and B. velezensis SQR9 was regulated by various compounds in root exudates (Ortega et al. , Feng et al. ). Notably, Pseudomonas spp. exhibit chemotactic responses to an impressive repertoire of over 140 compounds, thereby setting them as exemplary models for elucidating the structure‒function relationships between MCPs (Sampedro et al. ). A comprehensive analysis revealed that P. putida KT2440 harbors as many as 27 distinct MCPs (Corral-Lugo et al. ), each specific to detect a myriad of signaling molecules, including polyamines, amino acids, fatty acids, sugars, and many secondary metabolites. Bacillus velezensis SQR9 is endowed with eight unique MCPs, explicitly enumerated as McpA, McpB, McpC, McpR, TlpA, TlpB, YfmS, and HemAT (Liu et al. ). However, the functions of homologous MCPs can be different between strains. For example, McpA in B. velezensis SQR9 orchestrates chemoattraction to a wide range of 20 ligands, including organic acids, sugars, and amino acids (Feng et al. ). Its homologs in B. subtilis NCIB 3610 are predominantly predisposed to sugar ligands, specifically glucose and α-methylglucoside (Allard-Massicotte et al. ). Through rigorous molecular investigations coupled with site-directed mutagenesis experiments, it has been elucidated that McpA in strain SQR9 boasts a broad ligand-sensing capacity arising from its capability to harness both the distal and proximal membrane regions of its LBD. (Feng et al. ). Root-secreted glucose can act as a chemoattractant to many beneficial rhizobacteria (Feng et al. , Sánchez-Gil et al. ). Cucumber root-secreted d -galactose serves as a ligand of McpA in strain SQR9 to enhance chemotaxis (Liu et al. ). Compounds that act as chemoeffectors in root exudates are mainly low molecular weight compounds, such as organic acids, amino acids, sugars, sugar alcohols, and flavonoids. Some of these compounds also act as repellents. Detailed MCPs and their sensed root exudate compounds have been summarized by Feng et al. ( ). In addition to acting as a chemoeffector attracting bacteria, a range of compounds in root exudates enhance the motility of rhizobacteria. Root-secreted sucrose activates the bacterial production of extracellular polymeric levan, which in turn regulates the flagellar synthesis of B. subtilis , and B. subtilis cannot effectively colonize roots of Arabidopsis mutants that are deficient in root sucrose secretion (Tian et al. ). Interestingly, Bacillus -produced surfactin, an antibiotic essential for bacterial motility and thus rhizosphere colonization, is also promoted by other root exudates, such as polysaccharides (Debois et al. , Hoff et al. ). Recent studies revealed that root-secreted inositol can act as a signaling molecule to stimulate swimming motility in Pseudomonas via inositol-induced repression of DksA, a transcriptional regulator involved in inhibiting swimming motility and thus chemotaxis to the rhizosphere (Vílchez et al. , O’Banion et al. , Sánchez-Gil et al. ). The Arabidopsis root-secreted flavonoids attract Aeromonas sp. H1 by upregulating transcripts of flagellum biogenesis and inhibiting fumarate reduction for smooth swims (He et al. ). Notably, the diffusion range of root exudates is inherently limited, leading to reduced concentrations at greater distances from the root. In light of emerging theories on bacterial chemotaxis, there appears to be a sophisticated relay of chemotactic signals between distinct bacterial cells (Cremer et al. , Insall et al. ). Although they have not identified the signaling molecules secreted by the bacteria yet (Cremer et al. ), it supports that bacterial self-generated chemotactic signals might be essential in facilitating movement to the rhizosphere. Besides by sensing self-produced signal, bacterial chemotaxis may also be achieved through microbe–microbe interactions (Tian et al. ), sometimes even by attraction to the exudates of root-associated fungi (Jiang et al. , Mesny et al. ). To encapsulate this dynamic, microbes near the roots will sense root-secreted chemotactic signals and secrete chemotactic cues from their locus. This results in the establishment of a secondary chemotactic signal gradient, effectively drawing in more bacterial cells and mediating bacterial advancement toward the roots. Colonization site selection and migration Bacterial chemotaxis and motility determine colonization site selection and migration. The colonization sites can differ between bacteria, even between phylogenetically close strains (Fan et al. , Gao et al. , Tovi et al. , O’Neal et al. ). It can be expected that sites with high exudation are possible colonization hotspots for the whole community because the high concentration of root exudates would attract bacteria (Darrah , Marschner et al. ). Root hairs promote plants to allocate more carbon to root exudates (Holz et al. ), but it is generally agreed that the exudation rates are high in the elongation zone just behind the root tips rather than in the mature root zones. The colonization site is temporally changed along the root axis or between different root branches during the colonizing life cycle (Trivedi et al. ). The long-term colonization site may be different from the initial contact site. For instance, Bacillus megaterium NCT-2 cells were mostly distributed in the epidermis of the root elongation zone of maize at 3 days postinoculation (dpi), while colonization was observed along the meristematic zone, elongation zone, and root hair region at 11 dpi (Chu et al. ). First, bacterial chemotaxis and motility contribute decisively to the selection of the initial site for colonization. O’Neal et al. ( ) found that the Azospirillum brasilense mutant lacking the major chemoreceptors that are responsible for root exudate chemotaxis is impaired in preferentially accumulating on rhizoplane and inside tissue of maturation and elongation zones. The factors influencing bacterial chemotaxis and motility for selecting root colonization sites are complex, including the diversity and concentration of each component in root exudates at different sites and the immune response of different cell types and some locally secreted antimicrobial compounds (Fröschel et al. , Verbon et al. ). For example, reactive oxygen species (ROS) produced by roots also act as repellents to drive bacterial repulsion from the wheat root tip for initial colonization (O’Neal et al. ). Second, in addition to having a decisive role in the initial contact site, bacterial chemotaxis and motility also drive colonization site migration after root surface attachment. Root cell development changes the root exudation site, and bacterial migration could follow the changed root exudation sites, which are dynamically moving, following the expansion of the root system (Zboralski and Filion ). The migration of bacterial colonization site on roots after initial colonization can also result from evasion of immune-activating sites. Spatiotemporal root immune responses during microbial colonization are an important factor that determines the bacterial colonization site (Tsai et al. ). Liu et al. ( ) suggested that the ΔmorA mutant of Pseudomonas is a poor rhizosphere colonizer due to its inability to move from the initial site of colonization after triggering plant immune responses, indicating that migration along the root may occur to evade plant defense after initial colonization. Overall, there is no doubt that bacterial chemotaxis and motility determine the site preferences for colonization in different root zones. However, most of the current research measuring rhizosphere colonization is mainly based on overall quantitative measurements, while measurements of colonization in different root zones are lacking, which will lead to many objectively existing differences in colonization being ignored or some differences in colonization being misinterpreted. The key problem for this status is the difficulty in measuring bacterial colonization within distinct root zones. Most current studies regarding colonization sites are based on microscopic observations, including fluorescence-, GUS- and FISH-based methods (Cao et al. ). These strategies can well-reflect in situ bacterial colonization, but they are not as accurate as traditional plate counting methods in quantification. Moreover, due to the limitation of displaying only partial root zones under the microscope, it can sometimes be influenced by subjective bias.
Chemotaxis intracellular signaling is conserved in many bacterial species. Bacterial chemotaxis toward root exudates is initiated by the perception of chemoeffectors in root exudates by bacterial transmembrane chemotaxis receptors, which are specifically termed methyl-accepting chemotaxis proteins (MCPs) (Feng et al. ). Generally, chemotaxis receptor proteins always exist in a ternary complex with the CheA histidine kinase and the coupling protein CheW. Chemotaxis receptors are transmembrane proteins that constitute a highly varied ligand-binding domain (LBD) in the extracellular space for signal sensing, an intracellular highly conserved methyl-accepting (MA) domain for adaptation, which is the standard criterion for the annotation of proteins as MCPs (Sampedro et al. ). The MCPs selectively recognize and bind to specific ligands, such as root exudates, resulting in molecular signals that transduce across the cellular membrane. This transduction subsequently modulates the autophosphorylation rate of the histidine kinase CheA in a CheW-dependent manner (Lacal et al. ). CheA and CheY constitute a two-component system. The phosphorylation of CheA affects the transphosphorylation of the CheY response regulator. Phosphorylated CheY binds to motor proteins that are responsible for driving various kinds of motility in different bacteria. In addition, the turnover of methylation and demethylation of the MA domain of the MCPs was deployed as an adaptation system, and methylation increased while demethylation decreased the autophosphorylation activity of CheA (Sampedro et al. ). This whole signaling pathway is extremely well-conserved in many bacteria, including Escherichia coli, Bacillus spp. and Pseudomonas spp. The variety of MCPs with different LBDs determines the molecules to be sensed by the bacteria (Sanchis-López et al. ). In rhizobacteria, an expansive array of MCPs and their corresponding ligands have been identified, with notable examples found in species such as Pseudomonas putida, Bacillus velezensis , and Sinorhizobium meliloti . Allard-Massicotte et al. ( ) demonstrated that root colonization of Bacillus subtilis involves multiple chemotaxis receptors. An efficient colonizer in the rhizosphere should respond to a broad range of compounds in root exudates. For example, the colonization of P. putida KT2440 and B. velezensis SQR9 was regulated by various compounds in root exudates (Ortega et al. , Feng et al. ). Notably, Pseudomonas spp. exhibit chemotactic responses to an impressive repertoire of over 140 compounds, thereby setting them as exemplary models for elucidating the structure‒function relationships between MCPs (Sampedro et al. ). A comprehensive analysis revealed that P. putida KT2440 harbors as many as 27 distinct MCPs (Corral-Lugo et al. ), each specific to detect a myriad of signaling molecules, including polyamines, amino acids, fatty acids, sugars, and many secondary metabolites. Bacillus velezensis SQR9 is endowed with eight unique MCPs, explicitly enumerated as McpA, McpB, McpC, McpR, TlpA, TlpB, YfmS, and HemAT (Liu et al. ). However, the functions of homologous MCPs can be different between strains. For example, McpA in B. velezensis SQR9 orchestrates chemoattraction to a wide range of 20 ligands, including organic acids, sugars, and amino acids (Feng et al. ). Its homologs in B. subtilis NCIB 3610 are predominantly predisposed to sugar ligands, specifically glucose and α-methylglucoside (Allard-Massicotte et al. ). Through rigorous molecular investigations coupled with site-directed mutagenesis experiments, it has been elucidated that McpA in strain SQR9 boasts a broad ligand-sensing capacity arising from its capability to harness both the distal and proximal membrane regions of its LBD. (Feng et al. ). Root-secreted glucose can act as a chemoattractant to many beneficial rhizobacteria (Feng et al. , Sánchez-Gil et al. ). Cucumber root-secreted d -galactose serves as a ligand of McpA in strain SQR9 to enhance chemotaxis (Liu et al. ). Compounds that act as chemoeffectors in root exudates are mainly low molecular weight compounds, such as organic acids, amino acids, sugars, sugar alcohols, and flavonoids. Some of these compounds also act as repellents. Detailed MCPs and their sensed root exudate compounds have been summarized by Feng et al. ( ). In addition to acting as a chemoeffector attracting bacteria, a range of compounds in root exudates enhance the motility of rhizobacteria. Root-secreted sucrose activates the bacterial production of extracellular polymeric levan, which in turn regulates the flagellar synthesis of B. subtilis , and B. subtilis cannot effectively colonize roots of Arabidopsis mutants that are deficient in root sucrose secretion (Tian et al. ). Interestingly, Bacillus -produced surfactin, an antibiotic essential for bacterial motility and thus rhizosphere colonization, is also promoted by other root exudates, such as polysaccharides (Debois et al. , Hoff et al. ). Recent studies revealed that root-secreted inositol can act as a signaling molecule to stimulate swimming motility in Pseudomonas via inositol-induced repression of DksA, a transcriptional regulator involved in inhibiting swimming motility and thus chemotaxis to the rhizosphere (Vílchez et al. , O’Banion et al. , Sánchez-Gil et al. ). The Arabidopsis root-secreted flavonoids attract Aeromonas sp. H1 by upregulating transcripts of flagellum biogenesis and inhibiting fumarate reduction for smooth swims (He et al. ). Notably, the diffusion range of root exudates is inherently limited, leading to reduced concentrations at greater distances from the root. In light of emerging theories on bacterial chemotaxis, there appears to be a sophisticated relay of chemotactic signals between distinct bacterial cells (Cremer et al. , Insall et al. ). Although they have not identified the signaling molecules secreted by the bacteria yet (Cremer et al. ), it supports that bacterial self-generated chemotactic signals might be essential in facilitating movement to the rhizosphere. Besides by sensing self-produced signal, bacterial chemotaxis may also be achieved through microbe–microbe interactions (Tian et al. ), sometimes even by attraction to the exudates of root-associated fungi (Jiang et al. , Mesny et al. ). To encapsulate this dynamic, microbes near the roots will sense root-secreted chemotactic signals and secrete chemotactic cues from their locus. This results in the establishment of a secondary chemotactic signal gradient, effectively drawing in more bacterial cells and mediating bacterial advancement toward the roots.
Bacterial chemotaxis and motility determine colonization site selection and migration. The colonization sites can differ between bacteria, even between phylogenetically close strains (Fan et al. , Gao et al. , Tovi et al. , O’Neal et al. ). It can be expected that sites with high exudation are possible colonization hotspots for the whole community because the high concentration of root exudates would attract bacteria (Darrah , Marschner et al. ). Root hairs promote plants to allocate more carbon to root exudates (Holz et al. ), but it is generally agreed that the exudation rates are high in the elongation zone just behind the root tips rather than in the mature root zones. The colonization site is temporally changed along the root axis or between different root branches during the colonizing life cycle (Trivedi et al. ). The long-term colonization site may be different from the initial contact site. For instance, Bacillus megaterium NCT-2 cells were mostly distributed in the epidermis of the root elongation zone of maize at 3 days postinoculation (dpi), while colonization was observed along the meristematic zone, elongation zone, and root hair region at 11 dpi (Chu et al. ). First, bacterial chemotaxis and motility contribute decisively to the selection of the initial site for colonization. O’Neal et al. ( ) found that the Azospirillum brasilense mutant lacking the major chemoreceptors that are responsible for root exudate chemotaxis is impaired in preferentially accumulating on rhizoplane and inside tissue of maturation and elongation zones. The factors influencing bacterial chemotaxis and motility for selecting root colonization sites are complex, including the diversity and concentration of each component in root exudates at different sites and the immune response of different cell types and some locally secreted antimicrobial compounds (Fröschel et al. , Verbon et al. ). For example, reactive oxygen species (ROS) produced by roots also act as repellents to drive bacterial repulsion from the wheat root tip for initial colonization (O’Neal et al. ). Second, in addition to having a decisive role in the initial contact site, bacterial chemotaxis and motility also drive colonization site migration after root surface attachment. Root cell development changes the root exudation site, and bacterial migration could follow the changed root exudation sites, which are dynamically moving, following the expansion of the root system (Zboralski and Filion ). The migration of bacterial colonization site on roots after initial colonization can also result from evasion of immune-activating sites. Spatiotemporal root immune responses during microbial colonization are an important factor that determines the bacterial colonization site (Tsai et al. ). Liu et al. ( ) suggested that the ΔmorA mutant of Pseudomonas is a poor rhizosphere colonizer due to its inability to move from the initial site of colonization after triggering plant immune responses, indicating that migration along the root may occur to evade plant defense after initial colonization. Overall, there is no doubt that bacterial chemotaxis and motility determine the site preferences for colonization in different root zones. However, most of the current research measuring rhizosphere colonization is mainly based on overall quantitative measurements, while measurements of colonization in different root zones are lacking, which will lead to many objectively existing differences in colonization being ignored or some differences in colonization being misinterpreted. The key problem for this status is the difficulty in measuring bacterial colonization within distinct root zones. Most current studies regarding colonization sites are based on microscopic observations, including fluorescence-, GUS- and FISH-based methods (Cao et al. ). These strategies can well-reflect in situ bacterial colonization, but they are not as accurate as traditional plate counting methods in quantification. Moreover, due to the limitation of displaying only partial root zones under the microscope, it can sometimes be influenced by subjective bias.
Root surface colonization begins immediately after chemotaxis toward root, with successful adhesion to the root being the critical step for rhizoplane and endophytic colonization. In brief, bacteria need to stop moving and bind to the root surface, in which a transformation of lifestyle processes controlled by complex signal transduction is involved. Comprehensive studies on representative rhizobacteria, including Pseudomonas, Bacillus, Bradyrhizobium, Azospirillum, Agrobacterium , and Salmonella , have unveiled the molecular intricacies of root attachment. It has been established that agriculturally important microbial species share a biphasic model for root attachment (Wheatley and Poole , Knights et al. ). In most cases, this biphasic model involves two steps: initial attachment occurs when rhizobacteria are reversibly bound to a root surface, followed by secondary attachment that results in their irreversible attachment (Knights et al. ). The current knowledge on root attachment based on these two steps will be reviewed here. In addition, upon attachment to the root surface, plant immunity functions as an important factor influencing bacterial colonization, which will also be discussed for the strategies bacteria deployed to address plant immunity. Root surface attachment process Reversible initial attachment In general, initial attachment is weak, reversible, and nonspecific, allowing single cells to attach to the root surface. Compared to later-stage secondary attachment, the initial attachment is relatively poorly characterized. Numerous physiochemical and electrostatic forces influence the initial interactions between the surface molecules of the root and bacterial cell envelope, including van der Waals forces, electrostatic forces, and hydrophobic interactions. To overcome these repulsive forces, rhizobacteria use adhesive pili (T-pili), flagella, the polar flagellum, and fimbriae to overcome the electrostatic repulsion that occurs between negatively charged cell envelopes and root surfaces (Berne et al. , Knights et al. ). For instance, the flagella-deficient mutant of A. brasilense is unable to adhere to wheat or maize roots. Moreover, the polar flagella purified from A. brasilense bind to wheat roots directly (Rossi et al. ). In addition to this universal force of attachment, rhizobacteria can exhibit numerous species-specific mechanisms for attachment and colonization. The major membrane porin, outer membrane proteins, and polysaccharides are considered to play a role in root adhesion during the early stages of root establishment (Berne et al. ). An outer membrane porin F (OprF) from Pseudomonas shows adhesive properties toward the roots of cucumbers and tomatoes. It was found that OprF-deficient mutants of P. fluorescens are significantly less capable of loosely adhering to roots than wild-type plants, which indicates that OprF plays an important role in primary attachment (Alvarez Crespo and Valverde ). Although OprF in Pseudomonas appears to play a role in initial attachment, its molecular mechanism remains unclear. Irreversible secondary attachment In the following stages of initial bacterial attachment, only a small percentage of rhizobacteria switch to a stronger, more specific binding mode and generate extracellular fibrils that facilitate bacterial accumulation and aggregation, called secondary attachment (Wheatley and Poole ). A range of species-specific strategies are employed by rhizobacteria for secondary attachment. Pseudomonas spp. secrete a Ca 2+ -binding protein, LapA, via ATP-binding cassette transporters. This protein loosely associates with bacterial surfaces, facilitating interactions with the root surface (Hinsa et al. ). LapA of P. putida is also necessary for attachment to abiotic surfaces and to plant seeds (Espinosa-Urgel et al. ). Notably, P. fluorescens mutants lacking LapA exhibit diminished initial attachment to abiotic surfaces and compromised biofilm formation abilities. The O-antigenic chains of Pseudomonas spp. lipopolysaccharides have also been linked to root attachment in crops such as tomatoes and potatoes (Spiers and Rainey ). Zhao et al. ( ) demonstrated that collagen-like proteins of B. velezensis FZB42 are critical for root attachment. Recently, Huang et al. ( ) demonstrated that the wall teichoic acid, flagellar protein FliD, and YhaN (a putative ABC transporter) of B. velezensis SQR9 function as adhesins on both cucumber root surfaces and abiotic surfaces and are involved in rhizosphere colonization (Huang et al. ). Cyclic di-AMP, a common bacterial second messenger, influences the formation of biofilms and plant root attachments in B. subtilis (Townsley et al. ). These investigations underscore that root attachment mechanisms are pivotal for successful rhizosphere colonization by bacteria. Interaction with plant immunity Plant immunity is one of the barriers that rhizobacteria must overcome during attachment to the root surface. The first process depends on recognizing highly conserved microbe-associated molecular patterns (MAMPs), including flg22, chitin, peptidoglycan, and lipopolysaccharide, by pattern recognition receptors (PRRs) and activating pattern-triggered immunity (PTI), which forms a primary defense against microbial colonization. The second layer of plant immunity is referred to as effector-triggered immunity. Plants have evolved nucleotide binding and oligomerization domain-like receptors, which sense microbial effectors either directly or through effector-induced modifications of host structures (Wang et al. ). H + /Ca 2+ ion fluxes and bursts of ROS are two typical cellular responses occurring within minutes after immune signaling responses. Other responses include triggering downstream defense-related gene activation, defense hormone regulation, callose deposition, camalexin biosynthesis, and antimicrobial compound accumulation. This local immune response is always accompanied by growth inhibition as a result of the growth-defense trade-off (Liu et al. ). In addition to triggering the local immune response, beneficial rhizobacteria can also elicit the induction of systemic resistance (ISR) (Pieterse et al. ). Evidence show that at least the PTI is engaged and influences root colonization by beneficial rhizobacteria (Yu et al. ). A recent study demonstrated that the Arabidopsis root bacterial community is involved in PTI regulation, and a group of robust, taxonomically diverse PTI-inhibiting strains that are efficient root colonizers were identified (Teixeira et al. ). In addition to facilitating the colonization of PTI-regulating bacteria themselves, both individual strains and synthetic consortia that regulate PTI can increase the ability of other beneficial bacteria to colonize roots (Ma et al. , Teixeira et al. ). This suggests that the interaction with plant immunity highly influences the root colonization of beneficial rhizobacteria. Suppressing the root immune response Increasing evidence demonstrates that beneficial rhizobacteria can avoid being detected by root receptors that elicit immune responses, which are negative for bacterial colonization and plant growth. One aspect is the variation in the MAMPs, which is evidenced by the variation in flg22, one of the well-studied MAMPs. Colaianni et al. ( ) showed that most of the flg22 peptide variants from beneficial bacteria failed to activate PRR FLS2 (64%) and did not significantly inhibit plant host growth (80%), suggesting no activation of an energy-costly immune response. This kind of flg22 peptide variant altered PTI signaling output by interfering with coreceptor enlistment and by another, unidentified mechanism that triggered the typical ROS response, resulting in modulation of plant immunity (Colaianni et al. ). This finding suggests that beneficial rhizobacteria may avoid eliciting the root immune response by deploying flagella with low immunogenic sequences to facilitate rhizosphere colonization. The advantages of a low-immune-response-eliciting flagellin also drive the evolution of bacterial flagellar sequences with a trade-off of motility (Parys et al. ). In addition, there are beneficial rhizobacteria that possess immunogenic MAMPs that are very similar to those of pathogens. They have, therefore, evolved the ability to evade PRR recognition by inhibiting the interaction of their MAMP with PRRs, including through modification of the MAMP epitope, inhibition of the biosynthesis of MAMP-containing molecules, or alteration of microbial cell wall compositions (Yu et al. ). In contrast to the phytopathogen Pseudomonas syringae , which suppresses the root immune response by producing the low molecular weight phytotoxin COR, the beneficial rhizobacterium Pseudomonas suppresses the flg22-triggered immune response without producing COR (Millet et al. ). Instead, Yu et al. ( ) demonstrated that Pseudomonas capeferrum WCS358 reduces the rhizosphere pH by producing gluconic acid and its derivative 2-keto gluconic acid, therefore inhibiting the flg22-binding activity of FLS2, which requires a neutral pH environment. The inhibition of FLS2 activity further suppresses the flg22-mediated oxidative burst and root immunity, thereby facilitating colonization (Yu et al. ). Similarly, the beneficial B. subtilis FB17 can suppress flg22-induced early root immune responses in Arabidopsis by releasing an unidentified low molecular weight compound, which controls the JA signaling components JAR1, JIN1, and MYC2 (Lakshmanan et al. ). This suggests that beneficial rhizobacteria actively interfere with plant immune signaling by delivering immune-suppressive compounds. However, current knowledge on suppressing PTI is mainly aimed at flg22, and more efforts aimed at other MAMPs on a large scale should be made to reveal immune suppression by beneficial rhizobacteria during colonization. Tolerance of root immune response Once plant immunity is activated, some beneficial rhizobacteria can also utilize strategies to address the activated immune response. The root cell-type-specific transcriptome in response to a beneficial rhizobacterium Pseudomonas simiae WCS417 revealed a spatial difference in immune activation of root hairs, cortex and endodermal barrier during colonization of this strain, suggesting that a spatial selection of the colonization site would benefit immune response evasion (Verbon et al. ). A genome-wide screen in rhizosphere Pseudomonas identified two genes, morA and spuC, that are essential in rhizosphere colonization, and the authors speculated that these two genes may confer the bacterium an ability to disperse from the initial site of colonization after triggering plant immune responses (Liu et al. ). This case proposed a potential bacterial strategy that evades root immunity through spatial mitigation of the colonization site. In addition to spatial evasion, higher tolerance is another strategy to address the activated root immune response, such as the ROS burst. Recently, Song et al. ( ) demonstrated that ROS in roots regulate the levels of rhizosphere beneficial Pseudomonas . The auxin produced by the beneficial bacterium B. velezensis FZB42 is essential for root colonization by antagonizing ROS produced as part of the receptor EFR-triggered immune response (Tzipilevich et al. ). Moreover, ROS induce auxin synthesis in B. velezensis FZB42 (Tzipilevich et al. ). The beneficial rhizobacterium B. velezensis SQR9 possesses a specific two-component regulatory system (TCS), ResDE, to tolerate the ROS produced during the flg22-triggered root immune response, which promotes rhizosphere colonization of this strain (Zhang et al. ). However, it is still unclear whether the suppression of PTI in roots by beneficial rhizobacteria increases the risk of root infection by soil-borne pathogens. From the results reported by Ma et al. ( ), it seems that suppression of root PTI by beneficial rhizobacteria renders plants more susceptible to opportunistic Pseudomonas pathogens. Moreover, beneficial rhizobacteria can stimulate ISR, but the plant immune system actively or passively overlooks colonization by beneficial rhizobacteria during interactions. Whether this resistance impacts the colonization of nonsymbiotic beneficial rhizobacteria and its relationship with local plant immunity is unclear.
Reversible initial attachment In general, initial attachment is weak, reversible, and nonspecific, allowing single cells to attach to the root surface. Compared to later-stage secondary attachment, the initial attachment is relatively poorly characterized. Numerous physiochemical and electrostatic forces influence the initial interactions between the surface molecules of the root and bacterial cell envelope, including van der Waals forces, electrostatic forces, and hydrophobic interactions. To overcome these repulsive forces, rhizobacteria use adhesive pili (T-pili), flagella, the polar flagellum, and fimbriae to overcome the electrostatic repulsion that occurs between negatively charged cell envelopes and root surfaces (Berne et al. , Knights et al. ). For instance, the flagella-deficient mutant of A. brasilense is unable to adhere to wheat or maize roots. Moreover, the polar flagella purified from A. brasilense bind to wheat roots directly (Rossi et al. ). In addition to this universal force of attachment, rhizobacteria can exhibit numerous species-specific mechanisms for attachment and colonization. The major membrane porin, outer membrane proteins, and polysaccharides are considered to play a role in root adhesion during the early stages of root establishment (Berne et al. ). An outer membrane porin F (OprF) from Pseudomonas shows adhesive properties toward the roots of cucumbers and tomatoes. It was found that OprF-deficient mutants of P. fluorescens are significantly less capable of loosely adhering to roots than wild-type plants, which indicates that OprF plays an important role in primary attachment (Alvarez Crespo and Valverde ). Although OprF in Pseudomonas appears to play a role in initial attachment, its molecular mechanism remains unclear. Irreversible secondary attachment In the following stages of initial bacterial attachment, only a small percentage of rhizobacteria switch to a stronger, more specific binding mode and generate extracellular fibrils that facilitate bacterial accumulation and aggregation, called secondary attachment (Wheatley and Poole ). A range of species-specific strategies are employed by rhizobacteria for secondary attachment. Pseudomonas spp. secrete a Ca 2+ -binding protein, LapA, via ATP-binding cassette transporters. This protein loosely associates with bacterial surfaces, facilitating interactions with the root surface (Hinsa et al. ). LapA of P. putida is also necessary for attachment to abiotic surfaces and to plant seeds (Espinosa-Urgel et al. ). Notably, P. fluorescens mutants lacking LapA exhibit diminished initial attachment to abiotic surfaces and compromised biofilm formation abilities. The O-antigenic chains of Pseudomonas spp. lipopolysaccharides have also been linked to root attachment in crops such as tomatoes and potatoes (Spiers and Rainey ). Zhao et al. ( ) demonstrated that collagen-like proteins of B. velezensis FZB42 are critical for root attachment. Recently, Huang et al. ( ) demonstrated that the wall teichoic acid, flagellar protein FliD, and YhaN (a putative ABC transporter) of B. velezensis SQR9 function as adhesins on both cucumber root surfaces and abiotic surfaces and are involved in rhizosphere colonization (Huang et al. ). Cyclic di-AMP, a common bacterial second messenger, influences the formation of biofilms and plant root attachments in B. subtilis (Townsley et al. ). These investigations underscore that root attachment mechanisms are pivotal for successful rhizosphere colonization by bacteria.
In general, initial attachment is weak, reversible, and nonspecific, allowing single cells to attach to the root surface. Compared to later-stage secondary attachment, the initial attachment is relatively poorly characterized. Numerous physiochemical and electrostatic forces influence the initial interactions between the surface molecules of the root and bacterial cell envelope, including van der Waals forces, electrostatic forces, and hydrophobic interactions. To overcome these repulsive forces, rhizobacteria use adhesive pili (T-pili), flagella, the polar flagellum, and fimbriae to overcome the electrostatic repulsion that occurs between negatively charged cell envelopes and root surfaces (Berne et al. , Knights et al. ). For instance, the flagella-deficient mutant of A. brasilense is unable to adhere to wheat or maize roots. Moreover, the polar flagella purified from A. brasilense bind to wheat roots directly (Rossi et al. ). In addition to this universal force of attachment, rhizobacteria can exhibit numerous species-specific mechanisms for attachment and colonization. The major membrane porin, outer membrane proteins, and polysaccharides are considered to play a role in root adhesion during the early stages of root establishment (Berne et al. ). An outer membrane porin F (OprF) from Pseudomonas shows adhesive properties toward the roots of cucumbers and tomatoes. It was found that OprF-deficient mutants of P. fluorescens are significantly less capable of loosely adhering to roots than wild-type plants, which indicates that OprF plays an important role in primary attachment (Alvarez Crespo and Valverde ). Although OprF in Pseudomonas appears to play a role in initial attachment, its molecular mechanism remains unclear.
In the following stages of initial bacterial attachment, only a small percentage of rhizobacteria switch to a stronger, more specific binding mode and generate extracellular fibrils that facilitate bacterial accumulation and aggregation, called secondary attachment (Wheatley and Poole ). A range of species-specific strategies are employed by rhizobacteria for secondary attachment. Pseudomonas spp. secrete a Ca 2+ -binding protein, LapA, via ATP-binding cassette transporters. This protein loosely associates with bacterial surfaces, facilitating interactions with the root surface (Hinsa et al. ). LapA of P. putida is also necessary for attachment to abiotic surfaces and to plant seeds (Espinosa-Urgel et al. ). Notably, P. fluorescens mutants lacking LapA exhibit diminished initial attachment to abiotic surfaces and compromised biofilm formation abilities. The O-antigenic chains of Pseudomonas spp. lipopolysaccharides have also been linked to root attachment in crops such as tomatoes and potatoes (Spiers and Rainey ). Zhao et al. ( ) demonstrated that collagen-like proteins of B. velezensis FZB42 are critical for root attachment. Recently, Huang et al. ( ) demonstrated that the wall teichoic acid, flagellar protein FliD, and YhaN (a putative ABC transporter) of B. velezensis SQR9 function as adhesins on both cucumber root surfaces and abiotic surfaces and are involved in rhizosphere colonization (Huang et al. ). Cyclic di-AMP, a common bacterial second messenger, influences the formation of biofilms and plant root attachments in B. subtilis (Townsley et al. ). These investigations underscore that root attachment mechanisms are pivotal for successful rhizosphere colonization by bacteria.
Plant immunity is one of the barriers that rhizobacteria must overcome during attachment to the root surface. The first process depends on recognizing highly conserved microbe-associated molecular patterns (MAMPs), including flg22, chitin, peptidoglycan, and lipopolysaccharide, by pattern recognition receptors (PRRs) and activating pattern-triggered immunity (PTI), which forms a primary defense against microbial colonization. The second layer of plant immunity is referred to as effector-triggered immunity. Plants have evolved nucleotide binding and oligomerization domain-like receptors, which sense microbial effectors either directly or through effector-induced modifications of host structures (Wang et al. ). H + /Ca 2+ ion fluxes and bursts of ROS are two typical cellular responses occurring within minutes after immune signaling responses. Other responses include triggering downstream defense-related gene activation, defense hormone regulation, callose deposition, camalexin biosynthesis, and antimicrobial compound accumulation. This local immune response is always accompanied by growth inhibition as a result of the growth-defense trade-off (Liu et al. ). In addition to triggering the local immune response, beneficial rhizobacteria can also elicit the induction of systemic resistance (ISR) (Pieterse et al. ). Evidence show that at least the PTI is engaged and influences root colonization by beneficial rhizobacteria (Yu et al. ). A recent study demonstrated that the Arabidopsis root bacterial community is involved in PTI regulation, and a group of robust, taxonomically diverse PTI-inhibiting strains that are efficient root colonizers were identified (Teixeira et al. ). In addition to facilitating the colonization of PTI-regulating bacteria themselves, both individual strains and synthetic consortia that regulate PTI can increase the ability of other beneficial bacteria to colonize roots (Ma et al. , Teixeira et al. ). This suggests that the interaction with plant immunity highly influences the root colonization of beneficial rhizobacteria. Suppressing the root immune response Increasing evidence demonstrates that beneficial rhizobacteria can avoid being detected by root receptors that elicit immune responses, which are negative for bacterial colonization and plant growth. One aspect is the variation in the MAMPs, which is evidenced by the variation in flg22, one of the well-studied MAMPs. Colaianni et al. ( ) showed that most of the flg22 peptide variants from beneficial bacteria failed to activate PRR FLS2 (64%) and did not significantly inhibit plant host growth (80%), suggesting no activation of an energy-costly immune response. This kind of flg22 peptide variant altered PTI signaling output by interfering with coreceptor enlistment and by another, unidentified mechanism that triggered the typical ROS response, resulting in modulation of plant immunity (Colaianni et al. ). This finding suggests that beneficial rhizobacteria may avoid eliciting the root immune response by deploying flagella with low immunogenic sequences to facilitate rhizosphere colonization. The advantages of a low-immune-response-eliciting flagellin also drive the evolution of bacterial flagellar sequences with a trade-off of motility (Parys et al. ). In addition, there are beneficial rhizobacteria that possess immunogenic MAMPs that are very similar to those of pathogens. They have, therefore, evolved the ability to evade PRR recognition by inhibiting the interaction of their MAMP with PRRs, including through modification of the MAMP epitope, inhibition of the biosynthesis of MAMP-containing molecules, or alteration of microbial cell wall compositions (Yu et al. ). In contrast to the phytopathogen Pseudomonas syringae , which suppresses the root immune response by producing the low molecular weight phytotoxin COR, the beneficial rhizobacterium Pseudomonas suppresses the flg22-triggered immune response without producing COR (Millet et al. ). Instead, Yu et al. ( ) demonstrated that Pseudomonas capeferrum WCS358 reduces the rhizosphere pH by producing gluconic acid and its derivative 2-keto gluconic acid, therefore inhibiting the flg22-binding activity of FLS2, which requires a neutral pH environment. The inhibition of FLS2 activity further suppresses the flg22-mediated oxidative burst and root immunity, thereby facilitating colonization (Yu et al. ). Similarly, the beneficial B. subtilis FB17 can suppress flg22-induced early root immune responses in Arabidopsis by releasing an unidentified low molecular weight compound, which controls the JA signaling components JAR1, JIN1, and MYC2 (Lakshmanan et al. ). This suggests that beneficial rhizobacteria actively interfere with plant immune signaling by delivering immune-suppressive compounds. However, current knowledge on suppressing PTI is mainly aimed at flg22, and more efforts aimed at other MAMPs on a large scale should be made to reveal immune suppression by beneficial rhizobacteria during colonization. Tolerance of root immune response Once plant immunity is activated, some beneficial rhizobacteria can also utilize strategies to address the activated immune response. The root cell-type-specific transcriptome in response to a beneficial rhizobacterium Pseudomonas simiae WCS417 revealed a spatial difference in immune activation of root hairs, cortex and endodermal barrier during colonization of this strain, suggesting that a spatial selection of the colonization site would benefit immune response evasion (Verbon et al. ). A genome-wide screen in rhizosphere Pseudomonas identified two genes, morA and spuC, that are essential in rhizosphere colonization, and the authors speculated that these two genes may confer the bacterium an ability to disperse from the initial site of colonization after triggering plant immune responses (Liu et al. ). This case proposed a potential bacterial strategy that evades root immunity through spatial mitigation of the colonization site. In addition to spatial evasion, higher tolerance is another strategy to address the activated root immune response, such as the ROS burst. Recently, Song et al. ( ) demonstrated that ROS in roots regulate the levels of rhizosphere beneficial Pseudomonas . The auxin produced by the beneficial bacterium B. velezensis FZB42 is essential for root colonization by antagonizing ROS produced as part of the receptor EFR-triggered immune response (Tzipilevich et al. ). Moreover, ROS induce auxin synthesis in B. velezensis FZB42 (Tzipilevich et al. ). The beneficial rhizobacterium B. velezensis SQR9 possesses a specific two-component regulatory system (TCS), ResDE, to tolerate the ROS produced during the flg22-triggered root immune response, which promotes rhizosphere colonization of this strain (Zhang et al. ). However, it is still unclear whether the suppression of PTI in roots by beneficial rhizobacteria increases the risk of root infection by soil-borne pathogens. From the results reported by Ma et al. ( ), it seems that suppression of root PTI by beneficial rhizobacteria renders plants more susceptible to opportunistic Pseudomonas pathogens. Moreover, beneficial rhizobacteria can stimulate ISR, but the plant immune system actively or passively overlooks colonization by beneficial rhizobacteria during interactions. Whether this resistance impacts the colonization of nonsymbiotic beneficial rhizobacteria and its relationship with local plant immunity is unclear.
Increasing evidence demonstrates that beneficial rhizobacteria can avoid being detected by root receptors that elicit immune responses, which are negative for bacterial colonization and plant growth. One aspect is the variation in the MAMPs, which is evidenced by the variation in flg22, one of the well-studied MAMPs. Colaianni et al. ( ) showed that most of the flg22 peptide variants from beneficial bacteria failed to activate PRR FLS2 (64%) and did not significantly inhibit plant host growth (80%), suggesting no activation of an energy-costly immune response. This kind of flg22 peptide variant altered PTI signaling output by interfering with coreceptor enlistment and by another, unidentified mechanism that triggered the typical ROS response, resulting in modulation of plant immunity (Colaianni et al. ). This finding suggests that beneficial rhizobacteria may avoid eliciting the root immune response by deploying flagella with low immunogenic sequences to facilitate rhizosphere colonization. The advantages of a low-immune-response-eliciting flagellin also drive the evolution of bacterial flagellar sequences with a trade-off of motility (Parys et al. ). In addition, there are beneficial rhizobacteria that possess immunogenic MAMPs that are very similar to those of pathogens. They have, therefore, evolved the ability to evade PRR recognition by inhibiting the interaction of their MAMP with PRRs, including through modification of the MAMP epitope, inhibition of the biosynthesis of MAMP-containing molecules, or alteration of microbial cell wall compositions (Yu et al. ). In contrast to the phytopathogen Pseudomonas syringae , which suppresses the root immune response by producing the low molecular weight phytotoxin COR, the beneficial rhizobacterium Pseudomonas suppresses the flg22-triggered immune response without producing COR (Millet et al. ). Instead, Yu et al. ( ) demonstrated that Pseudomonas capeferrum WCS358 reduces the rhizosphere pH by producing gluconic acid and its derivative 2-keto gluconic acid, therefore inhibiting the flg22-binding activity of FLS2, which requires a neutral pH environment. The inhibition of FLS2 activity further suppresses the flg22-mediated oxidative burst and root immunity, thereby facilitating colonization (Yu et al. ). Similarly, the beneficial B. subtilis FB17 can suppress flg22-induced early root immune responses in Arabidopsis by releasing an unidentified low molecular weight compound, which controls the JA signaling components JAR1, JIN1, and MYC2 (Lakshmanan et al. ). This suggests that beneficial rhizobacteria actively interfere with plant immune signaling by delivering immune-suppressive compounds. However, current knowledge on suppressing PTI is mainly aimed at flg22, and more efforts aimed at other MAMPs on a large scale should be made to reveal immune suppression by beneficial rhizobacteria during colonization.
Once plant immunity is activated, some beneficial rhizobacteria can also utilize strategies to address the activated immune response. The root cell-type-specific transcriptome in response to a beneficial rhizobacterium Pseudomonas simiae WCS417 revealed a spatial difference in immune activation of root hairs, cortex and endodermal barrier during colonization of this strain, suggesting that a spatial selection of the colonization site would benefit immune response evasion (Verbon et al. ). A genome-wide screen in rhizosphere Pseudomonas identified two genes, morA and spuC, that are essential in rhizosphere colonization, and the authors speculated that these two genes may confer the bacterium an ability to disperse from the initial site of colonization after triggering plant immune responses (Liu et al. ). This case proposed a potential bacterial strategy that evades root immunity through spatial mitigation of the colonization site. In addition to spatial evasion, higher tolerance is another strategy to address the activated root immune response, such as the ROS burst. Recently, Song et al. ( ) demonstrated that ROS in roots regulate the levels of rhizosphere beneficial Pseudomonas . The auxin produced by the beneficial bacterium B. velezensis FZB42 is essential for root colonization by antagonizing ROS produced as part of the receptor EFR-triggered immune response (Tzipilevich et al. ). Moreover, ROS induce auxin synthesis in B. velezensis FZB42 (Tzipilevich et al. ). The beneficial rhizobacterium B. velezensis SQR9 possesses a specific two-component regulatory system (TCS), ResDE, to tolerate the ROS produced during the flg22-triggered root immune response, which promotes rhizosphere colonization of this strain (Zhang et al. ). However, it is still unclear whether the suppression of PTI in roots by beneficial rhizobacteria increases the risk of root infection by soil-borne pathogens. From the results reported by Ma et al. ( ), it seems that suppression of root PTI by beneficial rhizobacteria renders plants more susceptible to opportunistic Pseudomonas pathogens. Moreover, beneficial rhizobacteria can stimulate ISR, but the plant immune system actively or passively overlooks colonization by beneficial rhizobacteria during interactions. Whether this resistance impacts the colonization of nonsymbiotic beneficial rhizobacteria and its relationship with local plant immunity is unclear.
In the rhizosphere, bacterial growth using root exudates as carbon resources is an important factor influencing root colonization. In addition to carbon resources, some scarce elements, such as phosphorus and iron, are also factors limiting the colonization of bacteria. Many bacterial species have evolved fascinating strategies to compete for scarce elements. Moreover, biofilm formation is an important process for many rhizoplane-colonizing bacterial species, motile flagellated bacterial cells differentiate into matrix-producing cells, which stop agglutinating, begin and form extracellular matrix surrounding chains (Karygianni et al. ). The biofilm matrix binds cells and imparts many key features to the biofilm, and therefore rhizosphere colonization (Flemming et al. ). The biofilms in rhizosphere are generally formed by bacteria from multispecies, and the matrix provides a spatial structure and multiple levels of protection for the community within biofilm. Bacterial growth using root exudates Bacterial growth and nutrition are the most important factors influencing bacterial colonization in the rhizosphere (López et al. ), and root exudate compounds can serve as nutrients that support bacterial colonization. The ability to utilize nutrients in root exudates is critical for rhizobacteria to occupy rhizosphere niches. Sugars and organic acids constitute a large fraction of exudates and are the major carbon sources for rhizobacteria (Sasse et al. , Korenblum et al. ); some root-sourced VOCs, such as terpenes, can also act as nutrient sources (Schulz-Bohm et al. ). Plant root exudate nutrients can selectively promote the colonization of specific bacteria (Wang et al. ). For instance, Huang et al. ( ) discovered that the specialized triterpenes thalianin, thalianyl fatty acid esters, and arabidin in root exudates of Arabidopsis modulate the root microbiota by enhancing or inhibiting specific bacterial growth. Rhizobacteria that can selectively metabolize certain triterpenes as carbon sources for growth have more efficient rhizosphere colonization. The root-secreted compound 1-aminocyclopropane-1-carboxylic acid (ACC), which is the precursor of ethylene, can be used only by bacteria with ACC deaminase. These bacteria can degrade ACC as a nitrogen source, giving them a significant advantage in rhizosphere colonization (Li et al. ). Recently, several publications demonstrated that plant secreted inositol as a nutrient is important for regulating rhizobacteria colonization (O’Banion et al. ), and a conserved inositol metabolism cluster in root Pseudomonas contributes to the competition for nutrients in the rhizosphere (Sánchez-Gil et al. ). In addition to the direct effect, compounds in root exudates can be degraded by specific bacteria, and the resulting metabolites will promote colonization by other bacteria. This kind of effect is expected to greatly participate in modulating root colonization by beneficial rhizobacteria (Sasse et al. ). Some broad-spectrum antimicrobial substances in root exudates also impact the colonization of beneficial rhizobacteria by serving as carbon resources. Many plant secondary metabolites and small peptides exert variable antimicrobial activity (Chagas et al. ) and function as bioprotectants against pathogens. However, some of these compounds have selective antimicrobial activity and can act as carbon resources for certain beneficial rhizobacteria. Rhizobacteria that can metabolize root-secreted antimicrobial substances will have higher rhizosphere colonization efficiency and succeed in root colonization. The root-secreted toxic compounds camalexin and benzoxazinoids, which are signatures of the root immune response, also promoted colonization by beneficial Pseudomonas (Hu et al. , Koprivova et al. ). Many VOCs produced by roots can serve as antimicrobial compounds, such as terpenes and terpenoids, to inhibit pathogen growth, and interestingly, they can also promote specific beneficial rhizobacterial growth (Chagas et al. , Schulz-Bohm et al. ). In addition, aromatic compounds released by roots also mediate defense mechanisms against pathogens and attract some microbes by serving as carbon sources (Lattanzio et al. ). Indeed, Lebeis et al. ( ) demonstrated that salicylic acid, an aromatic signaling molecule responsible for many kind of plant defense response, can be used by some beneficial bacterial strains as a growth signal or as a carbon source. Some specific transporters from either plants or bacteria have been suggested to be involved in the process of bacterial acquisition of root secreted carbon resource and contribute to the bacterial colonization in rhizosphere. Plants have developed active mechanisms for root exudation. Numerous studies have established that specific transporters located on the plasma membrane of root may be responsible for recruiting beneficial bacteria (Hennion et al. , Vives-Peris et al. ). The plant transporter ALMT1 plays a role in exudation of the malate and the gamma-aminobutyric acid (GABA), which is one of the major carbon resources for rhizobacteria (Lakshmanan et al. , , Kamran et al. ). Arabidopsis amino acid transporter, LHT1, modulates P. simiae metabolism in the rhizosphere, which influence its colonization efficiency (Agorsor et al. ). Bacterial also deploy a range of transporters to acquire the root exudates. Using a combination of comparative genomics and exometabolomics, Zhalnina et al. ( ) revealed that the uptake of root-secreted carbon resources by specific transporters of rhizobacteria determines their colonization, and a bacterium with an uptake transporter of the highly abundant nutritional compounds of root exudates will be highly advantageous in rhizosphere colonization. They also found that the uptake of certain substances is highly variable among rhizobacteria (Zhalnina et al. ). Under controlled conditions, Lin et al. ( ) demonstrated that knockout of the ptsG gene encoding the main glucose transporter in Bacillus cereus C1 L led to a sharp decrease in root colonization, suggesting the importance of bacterial transporter of root secreted carbon resources in bacterial colonization. Biofilm formation The formation of a biofilm is a way to maintain a critical cell mass in a specific location that is sufficient to initiate beneficial interactions with host plants (Flemming and Wuertz ). Biofilms increase resistance to certain environmental stresses as well as antimicrobial tolerance, protection from protozoan predation, consortia metabolism, or the opportunity for horizontal gene transfer (Arnaouteli et al. ). The biofilm matrix consists of extracellular polymeric substances, including polysaccharides, proteins, amyloids, lipids, and extracellular DNA, as well as membrane vesicles and humic-like refractories (Flemming et al. ). Global transcription factors in biofilm formation Mature biofilm formation generally indicates successful rhizosphere colonization. Rhizobacterial biofilm formation on the root surface is a highly regulated process, as each species has its own molecular mechanism for responding to environmental cues (Trivedi et al. ). The cessation of movement and initiation of biofilm formation by beneficial rhizobacteria are typically governed by one or several global transcriptional regulators within the bacterium. Consequently, these two cellular decisions are always coupled. When cells opt to transition into a biofilm state, the gene transcription associated with motility and chemotaxis is simultaneously downregulated. For example, biofilm formation by beneficial Bacillus in rhizosphere is governed by two global transcription factors, Spo0A and DegU (Arnaouteli et al. , Kobayashi and Ikemoto ). DegU controls both motility and biofilm formation by different phosphorylation levels (Kobayashi and Ikemoto ). Spo0A also controls sporulation and biofilm formation by different phosphorylation levels (Xu et al. ). Pseudomonas deploys different oligomerization of the global transcriptional regulator FleQ to adjudge the decision of motility and biofilm formation (Nie et al. ). Deficiency of these global transcriptional regulators in bacteria always leads to sharply reduced rhizosphere colonization (Xu et al. , , Emonet et al. ), suggesting the critical role of lifestyle transitions in rhizosphere colonization. Such a mechanism will prevent the contradictory coactivation of biofilm formation and motility during rhizosphere colonization. The global transcriptional regulators that direct the shift from bacterial motility to biofilm formation respond to environmental cues, such as root exudates (Ivanova et al. ). This sensory mechanism is generally mediated by cell surface receptors such as histidine kinases, notably KinD in Bacillus (Liu et al. ). Upon perceiving specific rhizosphere signals, these receptors communicate with global regulatory factors in various ways depending on bacterial variations (Arnaouteli et al. , Nie et al. , Wang et al. ), prompting cells to initiate biofilm formation on root surfaces. Certain plant polysaccharides, the major components of the plant cell wall, were also shown to enhance the biofilm of B. subtilis by acting as signals for controlling the phosphorylation level of the master regulator Spo0A and as carbon resources for producing the matrix exopolysaccharide (Beauregard et al. ). Interestingly, some signaling molecules induce both biofilm formation and trigger chemotaxis in beneficial rhizobacteria, such as cucumber root-secreted d -galactose, which could be induced by B. velezensis SQR9, serving as a signal for enhancing chemotaxis and biofilm formation of strain SQR9 in a McpA-dependent manner (Liu et al. ). The organic acids in the root exudates of peanut, including citric, malic, and oxalic acids, promoted bacterial biofilm formation of the beneficial rhizobacterium Burkholderia pyrrocinia strain P10 in rhizosphere (Han et al. ). In addition, the flavones in rice root exudates enhance biofilm formation of the nitrogen-fixing bacterium Gluconacetobacter diazotrophicus , and biofilm formation in turn recruits diazotrophic bacteria in the rhizosphere (Yan et al. ). While these are distinct processes in rhizosphere colonization, it can be expected that bacteria might exhibit differential responses to different concentrations of the same signaling molecule. Thus, a molecule could stimulate chemotaxis at greater distances from roots but favor biofilm formation on the root surface. Such dose-dependent signaling is very common in biofilm and chemotaxis regulation among rhizobacteria. Effect of self-produced secondary metabolites on biofilm formation Rhizosphere microorganisms can produce many secondary metabolites, which also impact biofilm formation. Root-secreted sucrose activates the bacterial production of extracellular polymeric levan, which in turn regulates the synthesis of surfactin and hyperflagellation of the bacterium (Tian et al. ). Interestingly, by causing potassium leakage, surfactin was demonstrated to be an essential signaling molecule in the establishment of biofilms and root colonization in B. subtilis NCIB3610 (Lopez et al. ). It has also been shown that another lipopeptide antibiotic, bacillomycin D, contributes to biofilm formation by facilitating iron acquisition. In B. velezensis SQR9, bacillomycin D specifically promotes transcription of the iron ABC transporter FeuABC by binding to its transcription factor, called Btr (Xu et al. ). Additionally, using a novel branched-chain fatty acid, bacillunoic acid, allows B. velezensis SQR9 to utilize a novel branched-chain fatty acid called bacillunoic acid to establish a policing system for punishing cheaters within the biofilm community and to improve the community’s fitness in a variety of conditions, including the root colonization process (Huang et al. ). Importantly, numerous studies have observed that siderophores play an important role in rhizobacterial biofilm formation of Bacillus spp. and Pseudomonas spp. siderophore-defective mutants in different PGPR strains fail to form biofilms and are unable to competitively colonize plant roots (Pizarro-Tobías et al. , Qin et al. , Singh et al. ). Owing to the complexity of secondary metabolites in the rhizosphere, there are numerous secondary metabolites that affect the interaction between plants and rhizobacteria, which needs to be investigated further. Multispecies biofilm in the rhizosphere It has been recognized that multispecies biofilms, rather than single-species biofilms, are the most dominant bacterial lifestyle naturally found in the rhizosphere, a consortium of bacterial isolates may form stronger biofilm on rhizoplane thus an enhanced colonization can be expected (Burmølle et al. , Sadiq et al. ). There have been numerous recent studies that provide insight into the synergistic effects of multispecies biofilms in rhizosphere soil, resulting in beneficial properties for plants. For example, a four-species biofilm consortium exhibited higher biomass than single species, as well as increased tolerance to environmental stress (Ren et al. , Yang et al. ). In one particular instance, a consortium of five rhizosphere native bacterial isolates forms synergistic biofilms in vitro and colonizes a larger area on the root than the individual strains (Santhanam et al. , ). Inoculation of cucumber rhizosphere with B. velezensis could increase the colonization of resident plant-beneficial Pseudomonas stutzeri through synergic biofilm formation (Sun et al. ). Furthermore, a study demonstrated that a three-species combination composed of Xanthomonas, Stenotrophomonas , and Microbacterium spp. showed increasing biofilm production compared to their individual members and thus increasing beneficial function on Arabidopsis (Berendsen et al. ). Competition for scarce elements for growth and biofilm formation Because of the large number of organisms in the rhizosphere, there are inevitable wars for limited elements, especially for the relatively scarce nutrient elements that are essential for rhizobacterial colonization, such as phosphorus, iron, zinc, and manganese (Dennis et al. , Tsai and Schmidt ). Here, the scarce element nutrient is defined as the limited amount of this element in the rhizosphere becomes a limiting factor for bacterial growth and biofilm formation. In addition, plants also need these elements for growth, leading to fierce competition for phosphorus and iron in the rhizosphere. Phosphorus generally reacts with calcium and magnesium in alkaline soils or with aluminum and iron in acidic soils to be fixed, which is difficult to absorb and utilize, resulting in a low level of phosphorus availability for bacteria (Earth System Science Data Discussions ). Rapid root absorption and poor mobility often lead to phosphorus depletion in the rhizosphere (Ceulemans et al. , Sakuraba et al. ). Soil phosphorus is divided into inorganic P (P i ) and organic P (P o ); inorganic phosphorus mainly exists in the form of phosphate, and organic P is an insoluble complex formed with organic monoesters, diesters, and inositol phosphates (Turner , Liu et al. ). To cope with such situations, a range of beneficial rhizobacteria secrete different phosphatases to dissolve organic phosphorus in soil and utilize the unique phosphorus transport system for uptake and utilization (Fitriatin et al. ). The general phosphorus solubilization and uptake system in rhizobacteria consists of four categories of genes, including the phosphorus regulatory transcription factor pho and the TCS phoB/phoR, transport system genes such as pit, pstA, pstB, and ugpQ, the inorganic phosphorus solubilization genes gcd, ppa, and ppx, and organic phosphate mineralization genes such as phoA and phoD (Wu et al. ). The phosphorus regulatory transcription regulator pho and the downstream TCS, which are conserved in most bacterial species, are essential in activating phosphorus solubilization and uptake genes in response to a low phosphorus environment. Activation of pho generally induces the expression of a series of downstream reactions to secrete phosphatases and organic acids, therefore mineralizing insoluble organic phosphates (Hulett ). In recent years, it has been reported that the constitutive phosphatase (PafA) activity expressed by Flavobacteria in the rhizosphere is stronger than that of Pseudomonas , which enables Flavobacteria to occupy unique phosphorus clearance sites in the rhizosphere and enhance the ability of phosphorus acquisition (Lidbury et al. ), making the Flavobacteria successful colonizers of the phosphorus solubilizing niche in the rhizosphere. Iron is an indispensable element that participates in many important biological metabolic processes; in particular, bacterial biofilm formation requires sufficient iron (Qin et al. , Xu et al. ). The total iron in soil is abundant, estimated to be 20–40 g/kg (Bowles ); however, most iron is present in insoluble iron oxide precipitates or insoluble high-valence forms. Iron availability is extremely low in neutral and alkaline soils (Moreno-Jiménez et al. ). Moreover, plant roots also deploy a strategy that takes up iron and withholds excess iron in vacuoles to restrict pathogen virulence. Therefore, soluble iron is extremely scarce for bacteria in the rhizosphere (Trapet et al. ). To increase their competitiveness for iron nutrition in the rhizosphere, most rhizobacteria produce siderophores to chelate ferric iron for colonization in rhizosphere (Stringlis et al. ). Bacterial siderophores can be hijacked by other bacteria to compete for iron (Gu et al. ). In addition to competition for soil iron by siderophores, iron competition between rhizobacteria and plants is also a canonical battle field (Xing et al. ). It has been recently found that beneficial rhizobacteria also trade with iron resources during bacterial colonization. Bacillus velezensis SQR9 deploys the type VII secretion system to export YukE, which inserts into the plant root cell membrane to cause iron leakage to facilitate the iron nutrition and rhizosphere colonization of this strain (Liu et al. ).
Bacterial growth and nutrition are the most important factors influencing bacterial colonization in the rhizosphere (López et al. ), and root exudate compounds can serve as nutrients that support bacterial colonization. The ability to utilize nutrients in root exudates is critical for rhizobacteria to occupy rhizosphere niches. Sugars and organic acids constitute a large fraction of exudates and are the major carbon sources for rhizobacteria (Sasse et al. , Korenblum et al. ); some root-sourced VOCs, such as terpenes, can also act as nutrient sources (Schulz-Bohm et al. ). Plant root exudate nutrients can selectively promote the colonization of specific bacteria (Wang et al. ). For instance, Huang et al. ( ) discovered that the specialized triterpenes thalianin, thalianyl fatty acid esters, and arabidin in root exudates of Arabidopsis modulate the root microbiota by enhancing or inhibiting specific bacterial growth. Rhizobacteria that can selectively metabolize certain triterpenes as carbon sources for growth have more efficient rhizosphere colonization. The root-secreted compound 1-aminocyclopropane-1-carboxylic acid (ACC), which is the precursor of ethylene, can be used only by bacteria with ACC deaminase. These bacteria can degrade ACC as a nitrogen source, giving them a significant advantage in rhizosphere colonization (Li et al. ). Recently, several publications demonstrated that plant secreted inositol as a nutrient is important for regulating rhizobacteria colonization (O’Banion et al. ), and a conserved inositol metabolism cluster in root Pseudomonas contributes to the competition for nutrients in the rhizosphere (Sánchez-Gil et al. ). In addition to the direct effect, compounds in root exudates can be degraded by specific bacteria, and the resulting metabolites will promote colonization by other bacteria. This kind of effect is expected to greatly participate in modulating root colonization by beneficial rhizobacteria (Sasse et al. ). Some broad-spectrum antimicrobial substances in root exudates also impact the colonization of beneficial rhizobacteria by serving as carbon resources. Many plant secondary metabolites and small peptides exert variable antimicrobial activity (Chagas et al. ) and function as bioprotectants against pathogens. However, some of these compounds have selective antimicrobial activity and can act as carbon resources for certain beneficial rhizobacteria. Rhizobacteria that can metabolize root-secreted antimicrobial substances will have higher rhizosphere colonization efficiency and succeed in root colonization. The root-secreted toxic compounds camalexin and benzoxazinoids, which are signatures of the root immune response, also promoted colonization by beneficial Pseudomonas (Hu et al. , Koprivova et al. ). Many VOCs produced by roots can serve as antimicrobial compounds, such as terpenes and terpenoids, to inhibit pathogen growth, and interestingly, they can also promote specific beneficial rhizobacterial growth (Chagas et al. , Schulz-Bohm et al. ). In addition, aromatic compounds released by roots also mediate defense mechanisms against pathogens and attract some microbes by serving as carbon sources (Lattanzio et al. ). Indeed, Lebeis et al. ( ) demonstrated that salicylic acid, an aromatic signaling molecule responsible for many kind of plant defense response, can be used by some beneficial bacterial strains as a growth signal or as a carbon source. Some specific transporters from either plants or bacteria have been suggested to be involved in the process of bacterial acquisition of root secreted carbon resource and contribute to the bacterial colonization in rhizosphere. Plants have developed active mechanisms for root exudation. Numerous studies have established that specific transporters located on the plasma membrane of root may be responsible for recruiting beneficial bacteria (Hennion et al. , Vives-Peris et al. ). The plant transporter ALMT1 plays a role in exudation of the malate and the gamma-aminobutyric acid (GABA), which is one of the major carbon resources for rhizobacteria (Lakshmanan et al. , , Kamran et al. ). Arabidopsis amino acid transporter, LHT1, modulates P. simiae metabolism in the rhizosphere, which influence its colonization efficiency (Agorsor et al. ). Bacterial also deploy a range of transporters to acquire the root exudates. Using a combination of comparative genomics and exometabolomics, Zhalnina et al. ( ) revealed that the uptake of root-secreted carbon resources by specific transporters of rhizobacteria determines their colonization, and a bacterium with an uptake transporter of the highly abundant nutritional compounds of root exudates will be highly advantageous in rhizosphere colonization. They also found that the uptake of certain substances is highly variable among rhizobacteria (Zhalnina et al. ). Under controlled conditions, Lin et al. ( ) demonstrated that knockout of the ptsG gene encoding the main glucose transporter in Bacillus cereus C1 L led to a sharp decrease in root colonization, suggesting the importance of bacterial transporter of root secreted carbon resources in bacterial colonization.
The formation of a biofilm is a way to maintain a critical cell mass in a specific location that is sufficient to initiate beneficial interactions with host plants (Flemming and Wuertz ). Biofilms increase resistance to certain environmental stresses as well as antimicrobial tolerance, protection from protozoan predation, consortia metabolism, or the opportunity for horizontal gene transfer (Arnaouteli et al. ). The biofilm matrix consists of extracellular polymeric substances, including polysaccharides, proteins, amyloids, lipids, and extracellular DNA, as well as membrane vesicles and humic-like refractories (Flemming et al. ). Global transcription factors in biofilm formation Mature biofilm formation generally indicates successful rhizosphere colonization. Rhizobacterial biofilm formation on the root surface is a highly regulated process, as each species has its own molecular mechanism for responding to environmental cues (Trivedi et al. ). The cessation of movement and initiation of biofilm formation by beneficial rhizobacteria are typically governed by one or several global transcriptional regulators within the bacterium. Consequently, these two cellular decisions are always coupled. When cells opt to transition into a biofilm state, the gene transcription associated with motility and chemotaxis is simultaneously downregulated. For example, biofilm formation by beneficial Bacillus in rhizosphere is governed by two global transcription factors, Spo0A and DegU (Arnaouteli et al. , Kobayashi and Ikemoto ). DegU controls both motility and biofilm formation by different phosphorylation levels (Kobayashi and Ikemoto ). Spo0A also controls sporulation and biofilm formation by different phosphorylation levels (Xu et al. ). Pseudomonas deploys different oligomerization of the global transcriptional regulator FleQ to adjudge the decision of motility and biofilm formation (Nie et al. ). Deficiency of these global transcriptional regulators in bacteria always leads to sharply reduced rhizosphere colonization (Xu et al. , , Emonet et al. ), suggesting the critical role of lifestyle transitions in rhizosphere colonization. Such a mechanism will prevent the contradictory coactivation of biofilm formation and motility during rhizosphere colonization. The global transcriptional regulators that direct the shift from bacterial motility to biofilm formation respond to environmental cues, such as root exudates (Ivanova et al. ). This sensory mechanism is generally mediated by cell surface receptors such as histidine kinases, notably KinD in Bacillus (Liu et al. ). Upon perceiving specific rhizosphere signals, these receptors communicate with global regulatory factors in various ways depending on bacterial variations (Arnaouteli et al. , Nie et al. , Wang et al. ), prompting cells to initiate biofilm formation on root surfaces. Certain plant polysaccharides, the major components of the plant cell wall, were also shown to enhance the biofilm of B. subtilis by acting as signals for controlling the phosphorylation level of the master regulator Spo0A and as carbon resources for producing the matrix exopolysaccharide (Beauregard et al. ). Interestingly, some signaling molecules induce both biofilm formation and trigger chemotaxis in beneficial rhizobacteria, such as cucumber root-secreted d -galactose, which could be induced by B. velezensis SQR9, serving as a signal for enhancing chemotaxis and biofilm formation of strain SQR9 in a McpA-dependent manner (Liu et al. ). The organic acids in the root exudates of peanut, including citric, malic, and oxalic acids, promoted bacterial biofilm formation of the beneficial rhizobacterium Burkholderia pyrrocinia strain P10 in rhizosphere (Han et al. ). In addition, the flavones in rice root exudates enhance biofilm formation of the nitrogen-fixing bacterium Gluconacetobacter diazotrophicus , and biofilm formation in turn recruits diazotrophic bacteria in the rhizosphere (Yan et al. ). While these are distinct processes in rhizosphere colonization, it can be expected that bacteria might exhibit differential responses to different concentrations of the same signaling molecule. Thus, a molecule could stimulate chemotaxis at greater distances from roots but favor biofilm formation on the root surface. Such dose-dependent signaling is very common in biofilm and chemotaxis regulation among rhizobacteria. Effect of self-produced secondary metabolites on biofilm formation Rhizosphere microorganisms can produce many secondary metabolites, which also impact biofilm formation. Root-secreted sucrose activates the bacterial production of extracellular polymeric levan, which in turn regulates the synthesis of surfactin and hyperflagellation of the bacterium (Tian et al. ). Interestingly, by causing potassium leakage, surfactin was demonstrated to be an essential signaling molecule in the establishment of biofilms and root colonization in B. subtilis NCIB3610 (Lopez et al. ). It has also been shown that another lipopeptide antibiotic, bacillomycin D, contributes to biofilm formation by facilitating iron acquisition. In B. velezensis SQR9, bacillomycin D specifically promotes transcription of the iron ABC transporter FeuABC by binding to its transcription factor, called Btr (Xu et al. ). Additionally, using a novel branched-chain fatty acid, bacillunoic acid, allows B. velezensis SQR9 to utilize a novel branched-chain fatty acid called bacillunoic acid to establish a policing system for punishing cheaters within the biofilm community and to improve the community’s fitness in a variety of conditions, including the root colonization process (Huang et al. ). Importantly, numerous studies have observed that siderophores play an important role in rhizobacterial biofilm formation of Bacillus spp. and Pseudomonas spp. siderophore-defective mutants in different PGPR strains fail to form biofilms and are unable to competitively colonize plant roots (Pizarro-Tobías et al. , Qin et al. , Singh et al. ). Owing to the complexity of secondary metabolites in the rhizosphere, there are numerous secondary metabolites that affect the interaction between plants and rhizobacteria, which needs to be investigated further. Multispecies biofilm in the rhizosphere It has been recognized that multispecies biofilms, rather than single-species biofilms, are the most dominant bacterial lifestyle naturally found in the rhizosphere, a consortium of bacterial isolates may form stronger biofilm on rhizoplane thus an enhanced colonization can be expected (Burmølle et al. , Sadiq et al. ). There have been numerous recent studies that provide insight into the synergistic effects of multispecies biofilms in rhizosphere soil, resulting in beneficial properties for plants. For example, a four-species biofilm consortium exhibited higher biomass than single species, as well as increased tolerance to environmental stress (Ren et al. , Yang et al. ). In one particular instance, a consortium of five rhizosphere native bacterial isolates forms synergistic biofilms in vitro and colonizes a larger area on the root than the individual strains (Santhanam et al. , ). Inoculation of cucumber rhizosphere with B. velezensis could increase the colonization of resident plant-beneficial Pseudomonas stutzeri through synergic biofilm formation (Sun et al. ). Furthermore, a study demonstrated that a three-species combination composed of Xanthomonas, Stenotrophomonas , and Microbacterium spp. showed increasing biofilm production compared to their individual members and thus increasing beneficial function on Arabidopsis (Berendsen et al. ).
Mature biofilm formation generally indicates successful rhizosphere colonization. Rhizobacterial biofilm formation on the root surface is a highly regulated process, as each species has its own molecular mechanism for responding to environmental cues (Trivedi et al. ). The cessation of movement and initiation of biofilm formation by beneficial rhizobacteria are typically governed by one or several global transcriptional regulators within the bacterium. Consequently, these two cellular decisions are always coupled. When cells opt to transition into a biofilm state, the gene transcription associated with motility and chemotaxis is simultaneously downregulated. For example, biofilm formation by beneficial Bacillus in rhizosphere is governed by two global transcription factors, Spo0A and DegU (Arnaouteli et al. , Kobayashi and Ikemoto ). DegU controls both motility and biofilm formation by different phosphorylation levels (Kobayashi and Ikemoto ). Spo0A also controls sporulation and biofilm formation by different phosphorylation levels (Xu et al. ). Pseudomonas deploys different oligomerization of the global transcriptional regulator FleQ to adjudge the decision of motility and biofilm formation (Nie et al. ). Deficiency of these global transcriptional regulators in bacteria always leads to sharply reduced rhizosphere colonization (Xu et al. , , Emonet et al. ), suggesting the critical role of lifestyle transitions in rhizosphere colonization. Such a mechanism will prevent the contradictory coactivation of biofilm formation and motility during rhizosphere colonization. The global transcriptional regulators that direct the shift from bacterial motility to biofilm formation respond to environmental cues, such as root exudates (Ivanova et al. ). This sensory mechanism is generally mediated by cell surface receptors such as histidine kinases, notably KinD in Bacillus (Liu et al. ). Upon perceiving specific rhizosphere signals, these receptors communicate with global regulatory factors in various ways depending on bacterial variations (Arnaouteli et al. , Nie et al. , Wang et al. ), prompting cells to initiate biofilm formation on root surfaces. Certain plant polysaccharides, the major components of the plant cell wall, were also shown to enhance the biofilm of B. subtilis by acting as signals for controlling the phosphorylation level of the master regulator Spo0A and as carbon resources for producing the matrix exopolysaccharide (Beauregard et al. ). Interestingly, some signaling molecules induce both biofilm formation and trigger chemotaxis in beneficial rhizobacteria, such as cucumber root-secreted d -galactose, which could be induced by B. velezensis SQR9, serving as a signal for enhancing chemotaxis and biofilm formation of strain SQR9 in a McpA-dependent manner (Liu et al. ). The organic acids in the root exudates of peanut, including citric, malic, and oxalic acids, promoted bacterial biofilm formation of the beneficial rhizobacterium Burkholderia pyrrocinia strain P10 in rhizosphere (Han et al. ). In addition, the flavones in rice root exudates enhance biofilm formation of the nitrogen-fixing bacterium Gluconacetobacter diazotrophicus , and biofilm formation in turn recruits diazotrophic bacteria in the rhizosphere (Yan et al. ). While these are distinct processes in rhizosphere colonization, it can be expected that bacteria might exhibit differential responses to different concentrations of the same signaling molecule. Thus, a molecule could stimulate chemotaxis at greater distances from roots but favor biofilm formation on the root surface. Such dose-dependent signaling is very common in biofilm and chemotaxis regulation among rhizobacteria.
Rhizosphere microorganisms can produce many secondary metabolites, which also impact biofilm formation. Root-secreted sucrose activates the bacterial production of extracellular polymeric levan, which in turn regulates the synthesis of surfactin and hyperflagellation of the bacterium (Tian et al. ). Interestingly, by causing potassium leakage, surfactin was demonstrated to be an essential signaling molecule in the establishment of biofilms and root colonization in B. subtilis NCIB3610 (Lopez et al. ). It has also been shown that another lipopeptide antibiotic, bacillomycin D, contributes to biofilm formation by facilitating iron acquisition. In B. velezensis SQR9, bacillomycin D specifically promotes transcription of the iron ABC transporter FeuABC by binding to its transcription factor, called Btr (Xu et al. ). Additionally, using a novel branched-chain fatty acid, bacillunoic acid, allows B. velezensis SQR9 to utilize a novel branched-chain fatty acid called bacillunoic acid to establish a policing system for punishing cheaters within the biofilm community and to improve the community’s fitness in a variety of conditions, including the root colonization process (Huang et al. ). Importantly, numerous studies have observed that siderophores play an important role in rhizobacterial biofilm formation of Bacillus spp. and Pseudomonas spp. siderophore-defective mutants in different PGPR strains fail to form biofilms and are unable to competitively colonize plant roots (Pizarro-Tobías et al. , Qin et al. , Singh et al. ). Owing to the complexity of secondary metabolites in the rhizosphere, there are numerous secondary metabolites that affect the interaction between plants and rhizobacteria, which needs to be investigated further.
It has been recognized that multispecies biofilms, rather than single-species biofilms, are the most dominant bacterial lifestyle naturally found in the rhizosphere, a consortium of bacterial isolates may form stronger biofilm on rhizoplane thus an enhanced colonization can be expected (Burmølle et al. , Sadiq et al. ). There have been numerous recent studies that provide insight into the synergistic effects of multispecies biofilms in rhizosphere soil, resulting in beneficial properties for plants. For example, a four-species biofilm consortium exhibited higher biomass than single species, as well as increased tolerance to environmental stress (Ren et al. , Yang et al. ). In one particular instance, a consortium of five rhizosphere native bacterial isolates forms synergistic biofilms in vitro and colonizes a larger area on the root than the individual strains (Santhanam et al. , ). Inoculation of cucumber rhizosphere with B. velezensis could increase the colonization of resident plant-beneficial Pseudomonas stutzeri through synergic biofilm formation (Sun et al. ). Furthermore, a study demonstrated that a three-species combination composed of Xanthomonas, Stenotrophomonas , and Microbacterium spp. showed increasing biofilm production compared to their individual members and thus increasing beneficial function on Arabidopsis (Berendsen et al. ).
Because of the large number of organisms in the rhizosphere, there are inevitable wars for limited elements, especially for the relatively scarce nutrient elements that are essential for rhizobacterial colonization, such as phosphorus, iron, zinc, and manganese (Dennis et al. , Tsai and Schmidt ). Here, the scarce element nutrient is defined as the limited amount of this element in the rhizosphere becomes a limiting factor for bacterial growth and biofilm formation. In addition, plants also need these elements for growth, leading to fierce competition for phosphorus and iron in the rhizosphere. Phosphorus generally reacts with calcium and magnesium in alkaline soils or with aluminum and iron in acidic soils to be fixed, which is difficult to absorb and utilize, resulting in a low level of phosphorus availability for bacteria (Earth System Science Data Discussions ). Rapid root absorption and poor mobility often lead to phosphorus depletion in the rhizosphere (Ceulemans et al. , Sakuraba et al. ). Soil phosphorus is divided into inorganic P (P i ) and organic P (P o ); inorganic phosphorus mainly exists in the form of phosphate, and organic P is an insoluble complex formed with organic monoesters, diesters, and inositol phosphates (Turner , Liu et al. ). To cope with such situations, a range of beneficial rhizobacteria secrete different phosphatases to dissolve organic phosphorus in soil and utilize the unique phosphorus transport system for uptake and utilization (Fitriatin et al. ). The general phosphorus solubilization and uptake system in rhizobacteria consists of four categories of genes, including the phosphorus regulatory transcription factor pho and the TCS phoB/phoR, transport system genes such as pit, pstA, pstB, and ugpQ, the inorganic phosphorus solubilization genes gcd, ppa, and ppx, and organic phosphate mineralization genes such as phoA and phoD (Wu et al. ). The phosphorus regulatory transcription regulator pho and the downstream TCS, which are conserved in most bacterial species, are essential in activating phosphorus solubilization and uptake genes in response to a low phosphorus environment. Activation of pho generally induces the expression of a series of downstream reactions to secrete phosphatases and organic acids, therefore mineralizing insoluble organic phosphates (Hulett ). In recent years, it has been reported that the constitutive phosphatase (PafA) activity expressed by Flavobacteria in the rhizosphere is stronger than that of Pseudomonas , which enables Flavobacteria to occupy unique phosphorus clearance sites in the rhizosphere and enhance the ability of phosphorus acquisition (Lidbury et al. ), making the Flavobacteria successful colonizers of the phosphorus solubilizing niche in the rhizosphere. Iron is an indispensable element that participates in many important biological metabolic processes; in particular, bacterial biofilm formation requires sufficient iron (Qin et al. , Xu et al. ). The total iron in soil is abundant, estimated to be 20–40 g/kg (Bowles ); however, most iron is present in insoluble iron oxide precipitates or insoluble high-valence forms. Iron availability is extremely low in neutral and alkaline soils (Moreno-Jiménez et al. ). Moreover, plant roots also deploy a strategy that takes up iron and withholds excess iron in vacuoles to restrict pathogen virulence. Therefore, soluble iron is extremely scarce for bacteria in the rhizosphere (Trapet et al. ). To increase their competitiveness for iron nutrition in the rhizosphere, most rhizobacteria produce siderophores to chelate ferric iron for colonization in rhizosphere (Stringlis et al. ). Bacterial siderophores can be hijacked by other bacteria to compete for iron (Gu et al. ). In addition to competition for soil iron by siderophores, iron competition between rhizobacteria and plants is also a canonical battle field (Xing et al. ). It has been recently found that beneficial rhizobacteria also trade with iron resources during bacterial colonization. Bacillus velezensis SQR9 deploys the type VII secretion system to export YukE, which inserts into the plant root cell membrane to cause iron leakage to facilitate the iron nutrition and rhizosphere colonization of this strain (Liu et al. ).
Endophytic bacteria colonize the host tissue. Some endophytes can colonize roots from vertical transmission and have been reviewed on vertical transmission (Frank et al. , Guo et al. , Soluch et al. ). Here, we focus on the endophytic process after root attachment of the bacteria. The intercellular colonization process has been demonstrated with several model endophytes, such as Azoarcus spp., Paraburkholderia phytofirman , and Klebsiella spp. (Reinhold-Hurek et al. , Turner et al. ). The key process is penetration into plant tissue (Hallmann ). The infection site selection and the bacterial features involved in lifestyle of root colonization are the key points here. Infection site The infection sites of rhizosphere endophytes are selective. It has been reported that many microorganisms enter plant root tissue by the following three putative pathways: the root tip in the elongation and differentiation zone, the points where lateral roots emerge, and the axils of emerging or developed lateral roots (Reinhold-Hurek and Hurek , James , Mushtaq et al. ). James et al. ( ) deployed a GUS-marked strain of the endophyte Herbaspirillum seropedicae , a nitrogen-fixing bacterium, to study the rhizosphere colonization site in rice. This bacterium is most abundant on coleoptiles, lateral roots, and at the junctions of the major and lateral roots in the initial step (James et al. , Balsanelli et al. ). It enters roots via cracks at the points of lateral root emergence and subsequently colonizes the intercellular spaces of roots (James et al. ). Histochemical analysis of seedlings of maize, sorghum, wheat, and rice grown in vermiculite showed that strain H. seropedicae LR15 colonized inner tissues. In the early steps of the endophytic association, H. seropedicae colonized intercellular spaces of the root cortex; it then occupied the vascular tissue. Colonization was also observed in the external mucilaginous root material at 8 dpi (Roncato-Maccari et al. ). Bacillus megaterium NCT-2 could penetrate into maize roots through the root tip in the elongation and differentiation zone (Chu et al. ). Compant et al. ( ) labeled Burkholderia sp. PsJN with GFP and observed the bacterial cells enriched in high numbers at the sites of lateral root emergence. Growing evidence support the idea that the endophytic colonization site is highly restricted by plant, such as by the plant immunity, the suberin, the casparian strip, and some antimicrobial metabolites in root tissues (Philippe et al. , Durr et al. , Fröschel et al. , Kashyap et al. , Verbon et al. ). Specific features of bacterial endophytes It seems that the decision of endophytic colonization can be distinct even between bacterial strains with close phylogenetic relationships. For instance, two efficient avocado root tip colonizers, P. alcaligenes AVO73 and P. pseudoalcaligenes AVO110, display distinct colonization sites; the latter colonizes root wounds and intercellular spaces between root epidermal cells, while the former colonizes only the root surface (Pliego et al. ). It is generally agreed that the factors influencing bacterial endophytism are complex and varied. Chen et al. ( ) explored the transcriptome profile of rice upon infection by two endophyte isolates, Azoarcus olearius BH72 and Azospirillum sp. B510 and found that plants respond quite differently to these two endophytes, suggesting a large variation in molecular interactions during endophytic colonization. But knowledge on the bacterial genetic features that responsible for penetration into root tissue and intercellular lifestyle is still very limited. Cell wall degradation is expected to be a fundamental skill of endophytic bacteria, even if they do not need to enter the intracellular space. The secretion of cell wall-degrading enzymes, mainly pectinases and cellulases, is known to be involved in bacterial penetration into plant tissue (Compant et al. ). A mutant of A. olearius BH72 devoid of endoglucanase activity had a decreased ability to colonize rice (Reinhold-Hurek et al. ). Rat et al. ( ) tested 197 endophytic bacteria of medicinal plant Alkanna tinctoria and found strains expressing cell-wall degrading enzymatic activities might have strong plant growth-promoting activity due to their ability to colonize plant. A unique respiratory type of metabolism may be essential for an endophyte because the carbon resources and the oxygen in plant tissue are quite different from those in the rhizoplane and soil. For example, the well-studied endophyte A. olearius BH72 has a strictly respiratory type of metabolism and cannot utilize common carbohydrates (Krause et al. ). A highly adaptive respiratory type can be expected to be essential for root endophytic life of bacteria. Unique motility may function in evading plant tissue. Böhm et al. ( ) demonstrated that a type IV pili-dependent twitching motility, but not the type-pili itself, mediated the endophyte A. olearius BH72 invasion of and establishment inside the plant. The interaction with plant immunity is expected to be a major trait for the adaptive lifestyle of endophytes. It has been shown that a plant-beneficial endophyte generally elicits a weaker immune response than pathogens. Moreover, Deng et al. ( ) demonstrated that an endophyte B. subtilis strain could evade plant defense by producing subtilomycin to mask self-produced flg22. Activation of the immune response or other stress responses is always accompanied by oxidative bursts, which lead to osmotic stress in endophytes, so it can be expected that a successful endophyte also harbors ROS tolerance to address the plant immune response and the ROS produced by plants under stressful conditions. Alquéres et al. ( ) found that the endophyte G. diazotrophicus PAL5 showed increased expression of genes encoding ROS-detoxifying enzymes during colonization in rice roots. In conclusion, knowledge on the molecular mechanism underlying the endophytic lifestyle is still lacking. First, although the feasible and independent solutions for endophyte isolation have been demonstrated, a standardized and unbiased method is urgently needed. A comprehensive genomic comparison will help to determine whether there is a common trait in the genome of bacterial endophytes. To identify genes involved in the endophytic lifestyle rather than contributing to the colonizing process before entering plant tissue using mutational experiments, comparing colonization both on the root surface and in root tissue is necessary. In addition, it could also be that endophytism is transient and opportunistic rather than a strict lifestyle.
The infection sites of rhizosphere endophytes are selective. It has been reported that many microorganisms enter plant root tissue by the following three putative pathways: the root tip in the elongation and differentiation zone, the points where lateral roots emerge, and the axils of emerging or developed lateral roots (Reinhold-Hurek and Hurek , James , Mushtaq et al. ). James et al. ( ) deployed a GUS-marked strain of the endophyte Herbaspirillum seropedicae , a nitrogen-fixing bacterium, to study the rhizosphere colonization site in rice. This bacterium is most abundant on coleoptiles, lateral roots, and at the junctions of the major and lateral roots in the initial step (James et al. , Balsanelli et al. ). It enters roots via cracks at the points of lateral root emergence and subsequently colonizes the intercellular spaces of roots (James et al. ). Histochemical analysis of seedlings of maize, sorghum, wheat, and rice grown in vermiculite showed that strain H. seropedicae LR15 colonized inner tissues. In the early steps of the endophytic association, H. seropedicae colonized intercellular spaces of the root cortex; it then occupied the vascular tissue. Colonization was also observed in the external mucilaginous root material at 8 dpi (Roncato-Maccari et al. ). Bacillus megaterium NCT-2 could penetrate into maize roots through the root tip in the elongation and differentiation zone (Chu et al. ). Compant et al. ( ) labeled Burkholderia sp. PsJN with GFP and observed the bacterial cells enriched in high numbers at the sites of lateral root emergence. Growing evidence support the idea that the endophytic colonization site is highly restricted by plant, such as by the plant immunity, the suberin, the casparian strip, and some antimicrobial metabolites in root tissues (Philippe et al. , Durr et al. , Fröschel et al. , Kashyap et al. , Verbon et al. ).
It seems that the decision of endophytic colonization can be distinct even between bacterial strains with close phylogenetic relationships. For instance, two efficient avocado root tip colonizers, P. alcaligenes AVO73 and P. pseudoalcaligenes AVO110, display distinct colonization sites; the latter colonizes root wounds and intercellular spaces between root epidermal cells, while the former colonizes only the root surface (Pliego et al. ). It is generally agreed that the factors influencing bacterial endophytism are complex and varied. Chen et al. ( ) explored the transcriptome profile of rice upon infection by two endophyte isolates, Azoarcus olearius BH72 and Azospirillum sp. B510 and found that plants respond quite differently to these two endophytes, suggesting a large variation in molecular interactions during endophytic colonization. But knowledge on the bacterial genetic features that responsible for penetration into root tissue and intercellular lifestyle is still very limited. Cell wall degradation is expected to be a fundamental skill of endophytic bacteria, even if they do not need to enter the intracellular space. The secretion of cell wall-degrading enzymes, mainly pectinases and cellulases, is known to be involved in bacterial penetration into plant tissue (Compant et al. ). A mutant of A. olearius BH72 devoid of endoglucanase activity had a decreased ability to colonize rice (Reinhold-Hurek et al. ). Rat et al. ( ) tested 197 endophytic bacteria of medicinal plant Alkanna tinctoria and found strains expressing cell-wall degrading enzymatic activities might have strong plant growth-promoting activity due to their ability to colonize plant. A unique respiratory type of metabolism may be essential for an endophyte because the carbon resources and the oxygen in plant tissue are quite different from those in the rhizoplane and soil. For example, the well-studied endophyte A. olearius BH72 has a strictly respiratory type of metabolism and cannot utilize common carbohydrates (Krause et al. ). A highly adaptive respiratory type can be expected to be essential for root endophytic life of bacteria. Unique motility may function in evading plant tissue. Böhm et al. ( ) demonstrated that a type IV pili-dependent twitching motility, but not the type-pili itself, mediated the endophyte A. olearius BH72 invasion of and establishment inside the plant. The interaction with plant immunity is expected to be a major trait for the adaptive lifestyle of endophytes. It has been shown that a plant-beneficial endophyte generally elicits a weaker immune response than pathogens. Moreover, Deng et al. ( ) demonstrated that an endophyte B. subtilis strain could evade plant defense by producing subtilomycin to mask self-produced flg22. Activation of the immune response or other stress responses is always accompanied by oxidative bursts, which lead to osmotic stress in endophytes, so it can be expected that a successful endophyte also harbors ROS tolerance to address the plant immune response and the ROS produced by plants under stressful conditions. Alquéres et al. ( ) found that the endophyte G. diazotrophicus PAL5 showed increased expression of genes encoding ROS-detoxifying enzymes during colonization in rice roots. In conclusion, knowledge on the molecular mechanism underlying the endophytic lifestyle is still lacking. First, although the feasible and independent solutions for endophyte isolation have been demonstrated, a standardized and unbiased method is urgently needed. A comprehensive genomic comparison will help to determine whether there is a common trait in the genome of bacterial endophytes. To identify genes involved in the endophytic lifestyle rather than contributing to the colonizing process before entering plant tissue using mutational experiments, comparing colonization both on the root surface and in root tissue is necessary. In addition, it could also be that endophytism is transient and opportunistic rather than a strict lifestyle.
Several papers demonstrated that stressed plants recruit beneficial bacteria to colonize the root, thereby facilitating the stress-induced opposite effect on plant growth and health (Berendsen et al. , Yuan et al. , Santoyo , Xie et al. , Wen et al. ). It is a noteworthy factor that influences bacterial colonization. One of the well-known strategies is the “cry for help” hypothesis, which explains the long-term disease suppressive soil feedback to foliar pathogen attack. The underlying mechanism still remain to be demonstrated (Wang and Song ). Although the current understanding of the cross-talk between root exudation, the root immune system, and the “cry for help” response is limited, it can be expected or confirmed that they may be linked internally. Rolfe et al. ( ) proposed three stages for this plant disease-induced long-term response: root immune responses to attackers, stress-induced changes in root exudation of antimicrobials and signaling chemicals, and impacts of root exudates on the rhizosphere microbiome. In addition, evidence has shown that root exudation from abiotic stressed plants also promotes colonization of beneficial rhizobacteria, which function to relieve the stress response of the plant. This stress-induced host selection would highly influence the colonization of beneficial rhizobacteria by changing the immune response and root exudation. Biotic stress triggered “cry for help” response Rudrappa et al. ( ) were the first to provide experimental evidence that aboveground disease alters root exudation of a primary root metabolite, l -malic acid, resulting in increased root colonization by a beneficial rhizobacterial strain. The authors propose that P. syringae pathovar tomato DC3000 ( Pst DC3000) infection of Arabidopsis leaves induces root secretion of l -malic acid, which acts as a specific signal for chemotaxis and colonization of the biocontrol bacterium B. subtilis FB17 in the rhizosphere (Rudrappa et al. ). A follow-up study demonstrated that either MAMPs, such as flg22, or the pathogen-derived phytotoxin COR are necessary to induce plants to secrete l -malic acid to promote colonization by B. subtilis FB17 (Lakshmanan et al. ). However, the mechanism that triggers the colonization promotion response is unclear. Regulation of the immune system upon perception of foliar pathogens was thought to contribute to influencing root microbiome composition (Lebeis et al. ). Foliar attack by pathogens or insects can influence belowground direct and indirect plant defense responses (Bezemer and Van Dam ), but the root immune system needs to differentiate between beneficial and pathogenic microbes and mount appropriate, yet diametrically opposed, colonization-enabling or defense responses. However, COR, as a mimic of JA-Ile, was proposed to suppress SA signaling and the flg22-triggered immune response (Li et al. , Melotto et al. ), since both flg22 and COR could trigger the colonization promotion response. It is ambiguous how the immune response in aboveground tissue is involved in promoting root colonization by Bacillus . It is hypothesized that some defense signaling activated upon infection by pathogen may be positive for beneficial rhizobacterial colonization. Indeed, Yang et al. ( ) found that the SA signaling pathway is essential for eliciting plants to promote root colonization of some biocontrol bacteria for bacterial wilt disease. Another important case comes from the interaction between Fusarium and plants. Liu et al. ( ) used a split-root system to show that inoculation of part of the cucumber root system with Fusarium changes numerous root exudates and promotes colonization of the beneficial rhizobacterium B. velezensis SQR9 in distal roots, which was linked to increased exudation of tryptophan, a biofilm formation stimulator of strain SQR9. This finding was also corroborated by a comics study by Wen et al. ( ), who found that Fusarium -infected cucumber also attracted Sphingomonas in addition to Bacillus for root colonization by stimulating the genes involved in motility and chemotaxis (Wen et al. ). Similarly, Schulz-Bohm et al. ( ) found that upon infection with the fungal pathogen Fusarium culmorum, Carex arenaria changed the blend of root-secreted VOCs that promote the colonization of specific bacteria with antifungal properties. Root exudates from Fusarium -infected maize also stimulate root colonization of B. amyloliquefaciens OR2-30 by stimulating chemotaxis and motility (Xie et al. ). In wheat, Fusarium infection leads to higher root colonization of Stenotrophomonas rhizophila SR80, a dominant beneficial bacterium that induces strong disease resistance by boosting plant defense in aboveground plant parts (Liu et al. ). Upon infection by phytopathogens, plant roots release several antimicrobial compounds, but little is known about their effects on root colonization by beneficial rhizobacteria. One interesting field of how these antimicrobial compounds contribute to the “cry for help” response and affect beneficial bacterial colonization is studies on the rhizosphere function of coumarin. Coumarin is a class of phenolic secondary metabolites synthesized by Arabidopsis that can stimulate biofilm formation of B. subtilis (Korenblum et al. ). Stringlis et al. ( ) revealed that coumarin scopoletin selectively inhibits the soil-borne fungal pathogens Fusarium oxysporum and Verticillium dahliae , while growth-promoting and resistance-inducing Pseudomonas are highly tolerant to scopoletin. Vismans et al. ( ) found that foliar infection of Arabidopsis thaliana by the biotrophic downy mildew pathogen Hyaloperonospora arabidopsidis recruits beneficial bacteria that can enhance plant resistance, while it is evident that the coumarin biosynthesis genes MYB72 and F6’H1 in Arabidopsis are essential for recruiting beneficial bacterial colonization upon infection. These findings draw the outline of a fascinating “cry for help” response. Abiotic stress triggered “cry for help” response The colonization of beneficial rhizobacteria on roots can also be activated by plants under abiotic stress. For instance, rice during and after drought recruits beneficial Streptomyces to colonize the root endosphere (Santos-Medellín et al. ). Drought typically decreases the root exudation of plants, but drought-stressed trees have increased root exudation of phenolic acid compounds and quinate to recruit beneficial Bacillus and Pseudomonas for colonization (Oppenheimer-Shaanan et al. ). Root secretion of flavonoids, which is often elevated in plants under abiotic stress, may also be involved in promoting colonization upon stress production. Arabidopsis roots under dehydration stress increased flavonoid accumulation within 15 min. The flavonoid naringenin enhances root colonization of Aeromonas sp. H1, which is identified as a plant beneficial bacterium capable of enhancing plant resistance to dehydration through transcriptional enhancement of bacterial motility and colonization (He et al. ). Hou et al. ( ) demonstrated that Arabidopsis under low photosynthesis drives the recruitment of specific rhizobacteria with beneficial effects. Plants under salt stress employ a species-specific strategy to promote colonization by beneficial bacteria in the rhizosphere. Root exudates from the salt-stressed coastal halophyte Limonium sinense promote the growth, chemotaxis and finally root colonization of the bacterium B. flexus KLBMP 4941 (Li et al. ). An interesting example is coumarins, besides mediating the pathogen-infection-triggered “cry for help” response, coumarins have also demonstrated to be secreted by A. thaliana upon iron-deficiency stress to recruit beneficial bacteria (Harbort et al. ). Besides the specific molecules, stress-induced plant hormones are essential for plants to recruit beneficial bacteria. Indeed, Chen et al. ( ) found that peanut root could sense the cyanide stress produced by neighboring cassava plants and produce ethylene to recruit beneficial bacteria to adjust to the stressful environment.
Rudrappa et al. ( ) were the first to provide experimental evidence that aboveground disease alters root exudation of a primary root metabolite, l -malic acid, resulting in increased root colonization by a beneficial rhizobacterial strain. The authors propose that P. syringae pathovar tomato DC3000 ( Pst DC3000) infection of Arabidopsis leaves induces root secretion of l -malic acid, which acts as a specific signal for chemotaxis and colonization of the biocontrol bacterium B. subtilis FB17 in the rhizosphere (Rudrappa et al. ). A follow-up study demonstrated that either MAMPs, such as flg22, or the pathogen-derived phytotoxin COR are necessary to induce plants to secrete l -malic acid to promote colonization by B. subtilis FB17 (Lakshmanan et al. ). However, the mechanism that triggers the colonization promotion response is unclear. Regulation of the immune system upon perception of foliar pathogens was thought to contribute to influencing root microbiome composition (Lebeis et al. ). Foliar attack by pathogens or insects can influence belowground direct and indirect plant defense responses (Bezemer and Van Dam ), but the root immune system needs to differentiate between beneficial and pathogenic microbes and mount appropriate, yet diametrically opposed, colonization-enabling or defense responses. However, COR, as a mimic of JA-Ile, was proposed to suppress SA signaling and the flg22-triggered immune response (Li et al. , Melotto et al. ), since both flg22 and COR could trigger the colonization promotion response. It is ambiguous how the immune response in aboveground tissue is involved in promoting root colonization by Bacillus . It is hypothesized that some defense signaling activated upon infection by pathogen may be positive for beneficial rhizobacterial colonization. Indeed, Yang et al. ( ) found that the SA signaling pathway is essential for eliciting plants to promote root colonization of some biocontrol bacteria for bacterial wilt disease. Another important case comes from the interaction between Fusarium and plants. Liu et al. ( ) used a split-root system to show that inoculation of part of the cucumber root system with Fusarium changes numerous root exudates and promotes colonization of the beneficial rhizobacterium B. velezensis SQR9 in distal roots, which was linked to increased exudation of tryptophan, a biofilm formation stimulator of strain SQR9. This finding was also corroborated by a comics study by Wen et al. ( ), who found that Fusarium -infected cucumber also attracted Sphingomonas in addition to Bacillus for root colonization by stimulating the genes involved in motility and chemotaxis (Wen et al. ). Similarly, Schulz-Bohm et al. ( ) found that upon infection with the fungal pathogen Fusarium culmorum, Carex arenaria changed the blend of root-secreted VOCs that promote the colonization of specific bacteria with antifungal properties. Root exudates from Fusarium -infected maize also stimulate root colonization of B. amyloliquefaciens OR2-30 by stimulating chemotaxis and motility (Xie et al. ). In wheat, Fusarium infection leads to higher root colonization of Stenotrophomonas rhizophila SR80, a dominant beneficial bacterium that induces strong disease resistance by boosting plant defense in aboveground plant parts (Liu et al. ). Upon infection by phytopathogens, plant roots release several antimicrobial compounds, but little is known about their effects on root colonization by beneficial rhizobacteria. One interesting field of how these antimicrobial compounds contribute to the “cry for help” response and affect beneficial bacterial colonization is studies on the rhizosphere function of coumarin. Coumarin is a class of phenolic secondary metabolites synthesized by Arabidopsis that can stimulate biofilm formation of B. subtilis (Korenblum et al. ). Stringlis et al. ( ) revealed that coumarin scopoletin selectively inhibits the soil-borne fungal pathogens Fusarium oxysporum and Verticillium dahliae , while growth-promoting and resistance-inducing Pseudomonas are highly tolerant to scopoletin. Vismans et al. ( ) found that foliar infection of Arabidopsis thaliana by the biotrophic downy mildew pathogen Hyaloperonospora arabidopsidis recruits beneficial bacteria that can enhance plant resistance, while it is evident that the coumarin biosynthesis genes MYB72 and F6’H1 in Arabidopsis are essential for recruiting beneficial bacterial colonization upon infection. These findings draw the outline of a fascinating “cry for help” response.
The colonization of beneficial rhizobacteria on roots can also be activated by plants under abiotic stress. For instance, rice during and after drought recruits beneficial Streptomyces to colonize the root endosphere (Santos-Medellín et al. ). Drought typically decreases the root exudation of plants, but drought-stressed trees have increased root exudation of phenolic acid compounds and quinate to recruit beneficial Bacillus and Pseudomonas for colonization (Oppenheimer-Shaanan et al. ). Root secretion of flavonoids, which is often elevated in plants under abiotic stress, may also be involved in promoting colonization upon stress production. Arabidopsis roots under dehydration stress increased flavonoid accumulation within 15 min. The flavonoid naringenin enhances root colonization of Aeromonas sp. H1, which is identified as a plant beneficial bacterium capable of enhancing plant resistance to dehydration through transcriptional enhancement of bacterial motility and colonization (He et al. ). Hou et al. ( ) demonstrated that Arabidopsis under low photosynthesis drives the recruitment of specific rhizobacteria with beneficial effects. Plants under salt stress employ a species-specific strategy to promote colonization by beneficial bacteria in the rhizosphere. Root exudates from the salt-stressed coastal halophyte Limonium sinense promote the growth, chemotaxis and finally root colonization of the bacterium B. flexus KLBMP 4941 (Li et al. ). An interesting example is coumarins, besides mediating the pathogen-infection-triggered “cry for help” response, coumarins have also demonstrated to be secreted by A. thaliana upon iron-deficiency stress to recruit beneficial bacteria (Harbort et al. ). Besides the specific molecules, stress-induced plant hormones are essential for plants to recruit beneficial bacteria. Indeed, Chen et al. ( ) found that peanut root could sense the cyanide stress produced by neighboring cassava plants and produce ethylene to recruit beneficial bacteria to adjust to the stressful environment.
Pathogenic, symbiotic, and nonsymbiotic rhizobacteria represent three groups of root colonizers that are tightly associated with plant. But the comparison of the difference of their colonization mechanisms in rhizosphere is lack. The rhizosphere chemotaxis and root attachment of these bacterial groups are similar, which are mainly by sensing root secreted signals, moving toward rhizosphere, and adhering to root surface, although the signals or cellular molecular pathway involved may different. The colonization process for pathogenic/symbiotic bacteria and the nonsymbiotic beneficial bacteria differed mainly in their specific lifestyles. Most nonsymbiotic rhizobacteria colonize the rhizoplane as a community, some endophytes colonize the intercellular spaces of the root at a controlled low density (Lugtenberg and Kamilova ). However, symbiotic bacteria colonize roots intracellularly and sometimes they induce root to develop specific organs, which allow their high populations in root (Tang et al. ). Pathogenic bacteria infect root tissues and always grow to a very high density, which is needed for expression of virulence factors (von Bodman et al. ). The different lifestyles lead to difference of host specificity, nutrition and metabolism and strategies against plant immunity during colonization in the rhizosphere (Fig. ). Host specificity Generally, a nonsymbiotic beneficial rhizobacterium can colonize a broad range of host plants. For example, B. velezensis SQR9 was isolated from the rhizosphere of cucumber and can colonize Arabidopsis , maize and rice efficiently (Liu et al. , Cao et al. ). Pseudomonas simiae WCS417 was isolated from the rhizosphere of wheat and induced systemic resistance in Arabidopsis , tomato, and many other plant species, suggesting efficient colonization of these plant species (Berendsen et al. ). The endophytes A. olearius BH72 was isolated from Kallar grass ( Leptochloa fusca L. Kunth), while it also endophytically colonized rice (Hurek and Reinhold-Hurek ). However, relatively strict host selection is observed for symbiotic and pathogenic bacteria. Isolates belonging to Rhizobiaceae only infect legumes as a very specific host. One rhizobium strain can not colonize different cultivars from the same host plant species. This opinion is highly supported by the results from Dong et al. ( ), who found that the legume Medicago truncatula possesses an SHR–SCR stem cell program in cortical cells to specifically interact with rhizobia for nodulation. Pathogenic bacteria also have strict host selection. For example, one strain from P. syringae generally has a very limited host plant species and even a few cultivars from a single plant species, based on which the basis of the pathogenic P. syringae can be grouped into pathovars (Xin and He ). The narrow host spectrum for symbiotic and pathogenic bacteria is generally due to their host selection genes, and the presence or absence of these genes determines the infection of a specific host. For example, a common concept of the presence of pathogenic bacteria and symbiotic strains is called avirulent genes, which enable specific nonhost plants to specifically prevent the infection of that strain. These avirulent genes typically mediate immune recognition by nonhost plants (Yang et al. ). In contrast, there are currently no reported host selection genes in nonsymbiotic beneficial rhizobacteria. But nonsymbiotic rhizobacteria do have a host preference, which suggest the existence of specific genes determines the colonization of these bacteria (Wippel et al. ). Even though, here is currently a tendency to believe that such bacteria use lower amplification rates in association with host plant in exchange for a wider host range. Nutrition and metabolism Lifestyle determines the metabolism of the bacteria. Due to the intracellular life of symbiotic bacteria, their metabolism and carbon resources are largely dependent on their host cells, and therefore, they generally have a more specific metabolites exchange with the host. Intracellular colonization is established and partially controlled by plant genes. For example, rhizobia mainly use the carbohydrates of host plants as carbon resources and feed plants with ammonia during root nodule symbiosis (Yang et al. ). Moreover, the respiratory type and redox potential of symbiotic bacteria are highly influenced by the host plant (Yu et al. ). Specific metabolism was also observed in the well-studied Agrobacteria strategy, during which pathogenic Agrobacterium hijacks plant cells by injecting a part of the DNA sequence from the Ti plasmid to produce opines as dedicated carbon resources for Agrobacterium itself (Lang et al. , González-Mula et al. , Matveeva and Otten ). The plant pathogen Ralstonia solanacearum is also able to manipulate plant metabolism to produce GABA to support bacterial nutrition during colonization (Xian et al. ). The nutrition and metabolism of most nonsymbiotic rhizobacteria are not strictly dependent on the host. They mainly use a broad range of organic compounds in root exudates for colonization (Badri and Vivanco ). In contrast to the specific carbon resources for bacteria during nodulation or infection, due to the much higher diversity of bacteria than intercellular and intracellular spaces, the bacteria colonizing the root surface should have a broader carbon source utilization spectrum to compete for nutrients in root exudates (Mataigne et al. ). The diversity of the bacteria in the rhizosphere led them to share the various compounds of the root exudates (Yang et al. , ). Moreover, most nonsymbiotic rhizobacteria can degrade and use the soil-derived carbon resources. Plant immunity evading strategy The lifestyle of pathogenic, symbiotic, and nonsymbiotic bacteria is largely distinctive, leading a quite different strategy to interact with plant immunity. Due to the intracellular lifestyle of symbiotic bacteria, activation of the plant immune response is believed to be harmful to the interaction (Feng et al. ). Most pathogenic bacteria infect root tissue in a high density, eliciting a stressful and PAMP-rich environment; when pathogens do not have immune-blocking strategies, strong PTI and sharply reduced colonization can be expected (Wei et al. ). Nonsymbiotic bacteria generally colonize the rhizosphere at a relatively lower density, but ROS accumulation or establishment of immune response within roots has a weaker influence to the colonization of nonsymbiotic bacteria than to the pathogenic and symbiotic bacteria (Buschart et al. , Zhang et al. ). This may rely on the different concentrations of antibacterial compounds, such as ROS, in root cells, intercellular spaces, and rhizoplane. The difference has been evident by several studies that blocking the plant immune response evading mechanism in bacteria has a much stronger impact on colonization of rhizobia and pathogenic bacteria than that of nonsymbiotic beneficial bacteria (Liang et al. , Wei et al. , Deng et al. , Pfeilmeier et al. , Yu et al. , Zhang et al. ). To fit their unique lifestyles, pathogenic, symbiotic, and nonsymbiotic bacteria deployed different strategies to evade plant immunity. Pathogenic and symbiotic bacteria possess highly immunogenic MAMPs. Although many MAMPs from nonsymbiotic rhizobacteria have been identified, current researches suggest those MAMPs elicit a weaker response than that derived from pathogens, which is shown by a lower elicitation of defense gene transcription, a lower oxidative burst, and a higher concentration needed for seedling growth inhibition (Colaianni et al. , Zhang et al. ). For example, Colaianni et al. ( ) demonstrated that the flg22 variant from beneficial Bacillus can not trigger seedling growth inhibition when applied to a final concentration of 10 nM, a concentration the flg22 variant from Pst DC3000 did. However, pathogens use unique secretion system to interfere the PTI therefore establishing disease (Shu et al. ). For example, both pathogenic P. syringae and R. solanacearum deliver effectors into plant cells through the type III secretion system to interfere with the plant immune response for efficient colonization (Yuan et al. , Yu et al. ). The nodulation out proteins secreted by symbiotic bacteria have been reported to suppress PTI (Xin et al. ). Both symbiotic and pathogenic bacteria show specific interactions with the plant immune system, such as R genes. For rhizobia, it has also been demonstrated that R genes in legumes control the host specificity of rhizobium symbiosis. But different with pathogen, balanced regulation of innate immunity is required for rhizobial infection and symbiosis (Cao et al. , Yang et al. ). In contrast, nonsymbiotic rhizobacteria regulate the plant immune response in general as reviewed in the section “Interaction with plant immunity”, rather than through specific interactions as that of pathogenic bacteria and have never been shown to interact with R genes in plants.
Generally, a nonsymbiotic beneficial rhizobacterium can colonize a broad range of host plants. For example, B. velezensis SQR9 was isolated from the rhizosphere of cucumber and can colonize Arabidopsis , maize and rice efficiently (Liu et al. , Cao et al. ). Pseudomonas simiae WCS417 was isolated from the rhizosphere of wheat and induced systemic resistance in Arabidopsis , tomato, and many other plant species, suggesting efficient colonization of these plant species (Berendsen et al. ). The endophytes A. olearius BH72 was isolated from Kallar grass ( Leptochloa fusca L. Kunth), while it also endophytically colonized rice (Hurek and Reinhold-Hurek ). However, relatively strict host selection is observed for symbiotic and pathogenic bacteria. Isolates belonging to Rhizobiaceae only infect legumes as a very specific host. One rhizobium strain can not colonize different cultivars from the same host plant species. This opinion is highly supported by the results from Dong et al. ( ), who found that the legume Medicago truncatula possesses an SHR–SCR stem cell program in cortical cells to specifically interact with rhizobia for nodulation. Pathogenic bacteria also have strict host selection. For example, one strain from P. syringae generally has a very limited host plant species and even a few cultivars from a single plant species, based on which the basis of the pathogenic P. syringae can be grouped into pathovars (Xin and He ). The narrow host spectrum for symbiotic and pathogenic bacteria is generally due to their host selection genes, and the presence or absence of these genes determines the infection of a specific host. For example, a common concept of the presence of pathogenic bacteria and symbiotic strains is called avirulent genes, which enable specific nonhost plants to specifically prevent the infection of that strain. These avirulent genes typically mediate immune recognition by nonhost plants (Yang et al. ). In contrast, there are currently no reported host selection genes in nonsymbiotic beneficial rhizobacteria. But nonsymbiotic rhizobacteria do have a host preference, which suggest the existence of specific genes determines the colonization of these bacteria (Wippel et al. ). Even though, here is currently a tendency to believe that such bacteria use lower amplification rates in association with host plant in exchange for a wider host range.
Lifestyle determines the metabolism of the bacteria. Due to the intracellular life of symbiotic bacteria, their metabolism and carbon resources are largely dependent on their host cells, and therefore, they generally have a more specific metabolites exchange with the host. Intracellular colonization is established and partially controlled by plant genes. For example, rhizobia mainly use the carbohydrates of host plants as carbon resources and feed plants with ammonia during root nodule symbiosis (Yang et al. ). Moreover, the respiratory type and redox potential of symbiotic bacteria are highly influenced by the host plant (Yu et al. ). Specific metabolism was also observed in the well-studied Agrobacteria strategy, during which pathogenic Agrobacterium hijacks plant cells by injecting a part of the DNA sequence from the Ti plasmid to produce opines as dedicated carbon resources for Agrobacterium itself (Lang et al. , González-Mula et al. , Matveeva and Otten ). The plant pathogen Ralstonia solanacearum is also able to manipulate plant metabolism to produce GABA to support bacterial nutrition during colonization (Xian et al. ). The nutrition and metabolism of most nonsymbiotic rhizobacteria are not strictly dependent on the host. They mainly use a broad range of organic compounds in root exudates for colonization (Badri and Vivanco ). In contrast to the specific carbon resources for bacteria during nodulation or infection, due to the much higher diversity of bacteria than intercellular and intracellular spaces, the bacteria colonizing the root surface should have a broader carbon source utilization spectrum to compete for nutrients in root exudates (Mataigne et al. ). The diversity of the bacteria in the rhizosphere led them to share the various compounds of the root exudates (Yang et al. , ). Moreover, most nonsymbiotic rhizobacteria can degrade and use the soil-derived carbon resources.
The lifestyle of pathogenic, symbiotic, and nonsymbiotic bacteria is largely distinctive, leading a quite different strategy to interact with plant immunity. Due to the intracellular lifestyle of symbiotic bacteria, activation of the plant immune response is believed to be harmful to the interaction (Feng et al. ). Most pathogenic bacteria infect root tissue in a high density, eliciting a stressful and PAMP-rich environment; when pathogens do not have immune-blocking strategies, strong PTI and sharply reduced colonization can be expected (Wei et al. ). Nonsymbiotic bacteria generally colonize the rhizosphere at a relatively lower density, but ROS accumulation or establishment of immune response within roots has a weaker influence to the colonization of nonsymbiotic bacteria than to the pathogenic and symbiotic bacteria (Buschart et al. , Zhang et al. ). This may rely on the different concentrations of antibacterial compounds, such as ROS, in root cells, intercellular spaces, and rhizoplane. The difference has been evident by several studies that blocking the plant immune response evading mechanism in bacteria has a much stronger impact on colonization of rhizobia and pathogenic bacteria than that of nonsymbiotic beneficial bacteria (Liang et al. , Wei et al. , Deng et al. , Pfeilmeier et al. , Yu et al. , Zhang et al. ). To fit their unique lifestyles, pathogenic, symbiotic, and nonsymbiotic bacteria deployed different strategies to evade plant immunity. Pathogenic and symbiotic bacteria possess highly immunogenic MAMPs. Although many MAMPs from nonsymbiotic rhizobacteria have been identified, current researches suggest those MAMPs elicit a weaker response than that derived from pathogens, which is shown by a lower elicitation of defense gene transcription, a lower oxidative burst, and a higher concentration needed for seedling growth inhibition (Colaianni et al. , Zhang et al. ). For example, Colaianni et al. ( ) demonstrated that the flg22 variant from beneficial Bacillus can not trigger seedling growth inhibition when applied to a final concentration of 10 nM, a concentration the flg22 variant from Pst DC3000 did. However, pathogens use unique secretion system to interfere the PTI therefore establishing disease (Shu et al. ). For example, both pathogenic P. syringae and R. solanacearum deliver effectors into plant cells through the type III secretion system to interfere with the plant immune response for efficient colonization (Yuan et al. , Yu et al. ). The nodulation out proteins secreted by symbiotic bacteria have been reported to suppress PTI (Xin et al. ). Both symbiotic and pathogenic bacteria show specific interactions with the plant immune system, such as R genes. For rhizobia, it has also been demonstrated that R genes in legumes control the host specificity of rhizobium symbiosis. But different with pathogen, balanced regulation of innate immunity is required for rhizobial infection and symbiosis (Cao et al. , Yang et al. ). In contrast, nonsymbiotic rhizobacteria regulate the plant immune response in general as reviewed in the section “Interaction with plant immunity”, rather than through specific interactions as that of pathogenic bacteria and have never been shown to interact with R genes in plants.
The field application of beneficial rhizobacteria is an effective practice for sustainable agriculture, the efficient root colonization of these bacteria is critical for the performance of their beneficial functions. Hence, it is important to develop strategies to enhance the root colonization of beneficial rhizobacteria. This review proposes three strategies, which include the addition of colonization-enhancing substrates, bacterial genetic modulation, and evolution of beneficial rhizobacteria (Fig. ). It can be expected that the application of some compounds in root exudates or microbial metabolites may serve as root colonization stimulators given that many studies have demonstrated the role of these compounds in modulating the root colonization of beneficial rhizobacteria. For example, the application of organic acids, such as malic acids, citric acid, and fumaric acid, can enhance root colonization of the beneficial strains Hansschlegelia zhihuaiae, B. velezensis SQR9, and B. pyrrocini (Zhang et al. , , , , Feng et al. , Han et al. ). Therefore, soil amendments can be used to promote beneficial bacterial colonization. Genetic engineering of beneficial rhizobacteria to respond to specific root exudate compounds is another strategy to enhance colonization. Xu et al. ( ) developed a xylose-inducible degQ genetically engineered strain of B. velezensis SQR9, which can use root secreted xylose as a signal to regulate the phosphorylation level of DegU and then promoted its ability to form biofilm on the root surface. Compared to the wild-type strain, the genetically engineered strain showed greater root colonization ability and biocontrol efficacy in cucumber and tomato (Xu et al. ). Singh et al. ( ) engineered the beneficial bacterium A. brasilense Sp7 with enhanced d -glucose utilization ability and showed significantly increased root colonization in rice compared with the wild-type strain. One imaginative strategy for improving root colonization ability of beneficial rhizobacteria is coevolution of the strain with the target plant to get the evolved strain, which is termed as targeted domestication. It is known that natural genetic mutations, such as random point mutation and horizontal gene transfer, drive the evolution of bacteria, for example, phage infection drive the evolution of bacterial resistance to phage (Hussain et al. ). Therefore, if a bacterial strain was inoculated to the rhizosphere, isolated and reinoculated again, then, after rounds of repeating, the genetic mutations in the evolved bacterial genome that benefit its life in rhizosphere will accumulate due to the survival of the fittest theory. It can be inferred that artificial domestication of bacterial strains within the rhizosphere under monoassociation conditions may accelerate evolution and drive the direction to a better rhizosphere colonizer. Indeed, Blake et al. ( ) found that B. subtilis NCIB 3610 differentiated into three different colony morphologies after experimental evolution within the Arabidopsis rhizosphere and that a mixture of the three morphotypes colonized the rhizosphere better than each colony alone. Li et al. ( ) repeatedly inoculated Pseudomonas protegens CHA0 in the rhizosphere of A. thaliana cultivated in sandy soil for six growth cycles, and they detected 35 mutations within 28 genes in the genome of the evolved isolates. Among them, mutations affecting global regulators, bacterial cell surface structure, and motility accumulated in parallel across multiple evolved strains (Li et al. ). Moreover, the relationship between bacteria and plants has evolved from antagonism to mutualistic cooperation, which is manifested in a stronger ability to utilize rhizosphere exudates and a stronger tolerance to antibacterial substances secreted by plants (Li et al. ). However, the entire trait correlation networks of P. protegens CHA0 are recombined after adaptive evolution, showing the loss of stress resistance modules and the linking of those modules that enhance ability after evolution (Li et al. ). Compared with the solid substrate environment, domestication within the Arabidopsis rhizosphere under a hydroponic environment places more emphasis on the mobility and recolonization ability of strains (Nordgaard et al. ). Rotating croplands provide a more complex ecological environment for bacteria. In an evolutionary experimental study, the evolutionary strains in alternate host environments had a higher degree of parallel evolution at the gene level (Hu et al. ). Adaptive mutations in B. subtilis NCIB 3610 occurred earlier in the presence of Pseudomonas in the rhizosphere, suggesting that a competitive environment accelerates this capacity change (Pomerleau et al. ). In conclusion, evolution experiments can be used as an important means to breed beneficial rhizobacteria with improved root colonization and agricultural application. However, this evolution-based domestication is also risky because a slight environmental difference may lead to a butterfly effect on the resultant strains’ features. Moreover, domestication of the bacteria in a simplified environment would weaken the bacterial ability in other environments, such as stress tolerance (Li et al. , , ).
The importance of rhizobacteria in plant growth, development, and health has been well recognized. Recent studies have revealed many fascinating models that describe complex interactions between rhizobacteria and plant and soil environments. However, compared with the soil-borne pathogenic and symbiotic bacteria of rhizobia, the root colonization of beneficial rhizobacteria has not been comprehensively concluded. Here, we summarized the root colonization of rhizobacteria into several steps. We also compared the difference in the colonization process of those nonsymbiotic beneficial rhizobacteria with symbiotic and pathogenic bacteria. Finally, we discussed the efforts made to improve the root colonization of beneficial rhizobacteria, which will facilitate their agricultural application. The nonsymbiotic rhizobacteria represent the plant-associated bacteria with the largest abundance and diversity in the rhizosphere. The mechanism of root colonization of nonsymbiotic bacteria is significantly different from that of symbiotic and pathogenic bacteria. The colonization of any nonsymbiotic strain can not reach the abundance level as that of symbiotic or pathogenic bacteria. The symbiotic and pathogenic bacteria colonize the inside root tissues with very high abundance, while most nonsymbiotic beneficial rhizobacteria colonize the root surface or inside root tissue with a low abundance. The differences in colonization site and abundance suggest that the nonsymbiotic rhizobacteria have different root–bacteria interaction mechanisms. In particular, how do plants recognize nonsymbiotic beneficial rhizobacteria and allow colonization? The rhizosphere environment is rich in other organisms, including fungi, protozoans, viruses, and other bacteria. Moreover, the microbiome in the rhizosphere is dominated by nonplant factors and varies largely depending on environmental factors, such as soil type, temperature, and humidity. Based on these concerns, the root colonization study of beneficial rhizobacteria in more natural conditions and under the holistic view of the rhizosphere microbiome and even the multitrophic interaction level will provide an in-depth understanding of the process and mechanisms in the future. Benefiting from the development of sequencing technology, many studies have made great efforts to use bioinformatic methods to analyze the rhizosphere microbiome. Finally, the study of rhizobacterial root colonization aims to improve the agricultural application efficiency of biofertilizers, which are mostly isolated from beneficial rhizobacteria. Therefore, our future study of rhizobacterial root colonization should pay more attention to the development of products or biotechnologies based on the process and mechanism understanding to improve the field application effect of beneficial rhizobacteria. More efforts to develop a new generation of biofertilizers that enhance beneficial rhizobacterial colonization should be made to promote the sustainable development of agriculture.
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DIAMONDS—a diabetes self-management intervention for people with severe mental illness: protocol for an individually randomised controlled multicentre trial | 3091cb02-8578-4bec-bd91-5b508dae72ef | 11956296 | Patient Education as Topic[mh] | People with severe mental illness (SMI; ie, long-term mental illnesses such as schizophrenia, schizoaffective disorder, bipolar disorder and severe depression) experience higher rates of physical illness than the general population. Their life expectancy is 15–20 years shorter mainly due to comorbid physical illnesses. Accessing clinically and cost-effective healthcare for individuals with a combination of mental and physical illness is recognised as challenging. The symptoms and the pharmacological treatments of SMI and physical illness can negatively interact, leading to higher illness and treatment burden compared with the general population. The resulting health inequalities are especially apparent when SMI is comorbid with diabetes. Type 2 diabetes mellitus (T2DM) is two to three times more common in people with SMI than in the general population and is associated with poorer outcomes than those seen in individuals with diabetes alone. Supporting self-management in diabetes, in common with other long-term conditions (LTCs), is fundamental to improving clinical outcomes, as most diabetes care falls to self-management. Self-management refers to the skills, practices and behaviours that a person engages in to protect and promote their health. Diabetes self-management activities include improving diet; physical activity; smoking cessation; monitoring blood glucose levels; preventing complications and treatment adherence. ‘Self-management education’ is key to supporting self-management. In England, diabetes self-management education and support programmes are recommended for recently diagnosed persons and their family members or supporters. Such programmes typically include educational and behavioural elements to increase knowledge, skills and capacity for self-management. Self-management education programmes for the general population with diabetes have been found to be clinically and cost-effective. For people with SMI and diabetes, self-management support is rarely offered (although reliable data on this are difficult to obtain). Moreover, the effectiveness of diabetes self-management programmes for this population is largely unknown as research typically excludes them. SMI is characterised by disturbances of thought, perception, affect and motivation, which influence self-efficacy, literacy, lifestyle, behaviour and family life. Diabetes self-management programmes designed for the general population do not address these important barriers, and programmes specifically for people with SMI do not currently exist. The STEPWISE trial tested a group structured lifestyle education programme to support weight reduction in people with schizophrenia. While the intervention was neither clinically nor cost-effective, the STEPWISE trial aimed to overcome the unacceptable health inequalities among people with SMI and highlighted the challenges of improving physical health in people with schizophrenia.
The DIAMONDS randomised controlled trial (RCT) aims to investigate the clinical and cost-effectiveness of a self-management intervention for people with SMI and T2DM compared with usual care. We will conduct an economic evaluation to assess the cost-effectiveness of the DIAMONDS intervention and a process evaluation that will address questions about whether the intervention was delivered as intended and how outcomes were determined. An intervention fidelity assessment will also be undertaken. This paper describes the trial protocol. Primary outcome The primary outcome is the adjusted difference in glycated haemoglobin (HbA1c) between the groups at 12 months postrandomisation. To avoid the inadvertent introduction of differences in measurements of HbA1c through the use of several local laboratories, one central United Kingdom Accreditation Service registered laboratory will be used for all blood sample analyses. Blood samples will be sent to the laboratory from the participating sites. The laboratory will return test results (recorded as mmol/mol and %) to the study team at the University of York (UoY). Secondary outcomes Secondary outcomes were selected to allow for a broad clinical and psychosocial profile as well as to cover domains of the core outcome set for trials evaluating such interventions in this population. Outcomes include measures of physical health (total cholesterol, haemoglobin, body mass index, waist circumference, blood pressure, smoking status and urinary albumin to creatinine ratio), physical activity (recorded with an accelerometer and participant self-report), mental health, diabetes measures, quality of life, health resource use and mechanisms of action (MoA). Full details of the outcome measures can be found in .
The primary outcome is the adjusted difference in glycated haemoglobin (HbA1c) between the groups at 12 months postrandomisation. To avoid the inadvertent introduction of differences in measurements of HbA1c through the use of several local laboratories, one central United Kingdom Accreditation Service registered laboratory will be used for all blood sample analyses. Blood samples will be sent to the laboratory from the participating sites. The laboratory will return test results (recorded as mmol/mol and %) to the study team at the University of York (UoY).
Secondary outcomes were selected to allow for a broad clinical and psychosocial profile as well as to cover domains of the core outcome set for trials evaluating such interventions in this population. Outcomes include measures of physical health (total cholesterol, haemoglobin, body mass index, waist circumference, blood pressure, smoking status and urinary albumin to creatinine ratio), physical activity (recorded with an accelerometer and participant self-report), mental health, diabetes measures, quality of life, health resource use and mechanisms of action (MoA). Full details of the outcome measures can be found in .
This protocol is reported in line with the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) checklist. See for a copy of the completed checklist. Trial design The DIAMONDS trial is a multicentre, two-armed, parallel, individual RCT with embedded process and economic evaluations. The trial includes a 12 month internal pilot phase to assess recruitment assumptions and optimise trial processes (full details of the pilot phase can be found in ). Participants will be followed up for one year with outcome assessments conducted at six and 12 months post-randomisation. The overall study is planned to start in September 2022 and finish in September 2025. Recruitment is planned to start in December 2022 and finish in September 2024. Setting and recruitment The study setting will include National Health Service (NHS) mental health trusts, general practices acting as Participant Identification Centres (PICs) and third sector organisations providing support to individuals with SMI and/or diabetes across England. Participants from previous studies who have provided consent will also be contacted, and individuals will be able to self-refer into the trial. An up-to-date list of recruiting sites is available on the DIAMONDS website ( https://www.diamondscollaboration.org.uk/ ). Participants will be recruited using methods successfully deployed in the DIAMONDS feasibility study, using a staged consent procedure. All participant-facing documents were produced in collaboration with DIAMONDS Voice ( https://www.diamondscollaboration.org.uk/diamonds-voice ), the service user and carer group that has been an integral part of the DIAMONDS programme for several years. Participants will be recruited from these sources and settings: NHS mental health trusts Authorised research and development (R&D) staff at participating secondary care sites will run searches in databases and screen community mental health team (CMHT) caseloads for potentially eligible patients using the eligibility criteria outlined below. There may also be direct referrals from consultants/CMHTs or through discharge meetings conducted with inpatient wards. Potential participants will receive a study information pack containing an invitation letter and a short patient information sheet (PIS) and will have the chance to discuss any questions they have with the research team (in person or over the phone). Following this, they will receive the full PIS. These potential participants will be contacted a few days later to arrange a face-to-face meeting with the research team, where there will be a further opportunity to ask questions relating to the study. If the individual wants to take part in the trial, they will be asked to give written informed consent (see for a copy of the consent form). GP database screenin g General practices will be asked to consult their SMI and LTC quality and outcomes framework registers to screen for potentially eligible patients using the inclusion criteria outlined below. General practitioners (GPs) at participating practices will check the lists produced by the database search to confirm eligibility. They will also approach potential participants at their annual health checks. Eligible patients will initially receive study information documents from their practice, usually via mailout to their home address. Where staff capacity allows, PIC sites will follow this up with a phone call. Consent-to-contact (CTC) will be obtained from interested patients, either via return of a CTC form or verbally during the follow-up phone call and passed on to appropriate research teams at mental health trusts who will then follow the same recruitment process as described above. Identification of potential participants from existing research cohorts Individuals who have previously taken part in related research projects conducted within our research group at UoY and who have given permission to be approached about future opportunities to participate in research will be contacted. Individuals identified via this route will receive the study information documents and will return a CTC form if interested. This CTC form will be passed on to the research teams at the mental health trusts and follow the process described above. Recruitment from third sector and service user groups We will work with relevant local third sector organisations and service user groups. Individuals who are interested in taking part in the trial will be directed to the person in the organisation/service supporting the trial, or the DIAMONDS study team. They will be provided with a short PIS and asked to complete and return a CTC form. The recruitment process will continue as previously described. Eligibility criteria Participants must (1) be aged 18 years or older and living in the community; (2) have any of the following SMI diagnoses: schizophrenia, bipolar disorder, schizoaffective disorder, psychosis, severe depression and (3) have T2DM. The diagnosis of SMI and T2DM must be confirmed by a clinician or be stated in the patient medical records. People will be excluded if they: (1) have cognitive impairments that would preclude the individual from participation in the trial and engagement with the intervention; (2) have gestational diabetes; (3) have type 1 diabetes; (4) have other types of secondary diabetes; (5) lack capacity to consent to participate in the trial as defined by the 2005 Mental Health Capacity Act or (6) are currently in an inpatient stay in an acute or mental health hospital. Patient pathway illustrates the participant pathway through the trial. Assignment of groups Eligible and consenting participants will be randomised on a 1:1 basis to the DIAMONDS intervention or usual care using computer-generated permuted blocks of randomly varying size. York Trials Unit (YTU) will provide a central web-based randomisation service for R&D teams at sites to use when assigning participant allocations. Participants will then be informed of their allocation during their baseline visit or shortly following. Blinding Efforts will be made to ensure R&D staff responsible for data collection remain blinded to treatment allocation. Should a participant inadvertently reveal their allocation to an outcome assessor, or the assessor becomes unblinded for any reason, this will be recorded in the outcome assessment case report form (CRF) at the relevant time. Designated R&D staff will be tasked with randomising participants and coordinating the handover of participants in the intervention group to a DIAMONDS Coach. Due to the nature of the comparison between the DIAMONDS intervention and treatment as usual, neither participants themselves nor the intervention facilitators (DIAMONDS Coaches) will be blinded. The trial statisticians and health economists will not be blinded. The DIAMONDS Programme Manager and Trial coordinators will remain unblinded and will not be involved in the analysis of data. The DIAMONDS intervention The DIAMONDS intervention was co-designed with service users, carers, members of the service user and carer group DIAMONDS Voice and healthcare professionals and is a tailored self-management support intervention to help people with T2DM and SMI self-manage diabetes through: Increasing knowledge and skills for diabetes self-management. Providing support to increase their physical activity levels and make healthier food choices. Identifying and addressing sleep difficulties, barriers to taking medications and other key problem areas as identified by the participant with support from their Coach, a healthcare professional who has been trained in the delivery of the DIAMONDS intervention. Supporting participants to manage their diabetes within the context of fluctuating and low mood. The acceptability of the intervention to participants and DIAMONDS Coaches was confirmed in the DIAMONDS feasibility study. Prior to the start of the RCT, we refined the intervention in line with findings from the feasibility study, which will be reported elsewhere (DIAMONDS Feasibility Study, ISRCTN15328700). A brief summary of the findings can be found ( https://www.hra.nhs.uk/planning-and-improving-research/application-summaries/research-summaries/diamonds-feasibility-study-v10/ ). The intervention will be delivered by a DIAMONDS Coach over a period of 6 months, using a combination of individual sessions and daily use of a paper-based workbook (the ‘DIAMONDS Workbook’) which can be supported by daily use of a digital app (‘Change One Thing’; optional) (see and details below). If the participant wishes to stop receiving the intervention before the end of the six months, the Coach will still support participants to set longer term goals and action plans for self-management and help them to access appropriate support to implement these, as is done for participants who complete the six month intervention period. Participants will be able to continue engaging with intervention content after follow-up data are collected through continued use of the app and/or workbook. Other reasons for the discontinuation of the intervention would be the death of the participant or if they remain an inpatient that takes them beyond the six month mark. Participants in the intervention will be permitted to continue with current care alongside the intervention. Control group Participants in the control group will access usual care for people with SMI and diabetes. This will include primary care health checks for SMI and diabetes along with community-based mental healthcare through CMHTs. Participants in the control group will be eligible to self-enrol in existing programmes. Participants randomised to the control group will be signposted to these services immediately following randomisation. Data collection and management Data will be collected at baseline, six and 12 months post-randomisation during appointments with the R&D teams at participating sites taking place either on Trust premises or at the participant’s home. The blood samples for the primary (HbA1c) and secondary (haemoglobin and cholesterol) outcomes will be collected by an appropriately trained member of staff and will be sent to a central laboratory for analysis. The other secondary outcomes will be collected through paper-based CRFs which will be returned to YTU and then scanned using specialist software. The data will be checked against the hard copy of the CRF, error checked and validation checks run against the database. Queries will be raised with the site if discrepancies are identified during validation or on receipt. All training for completing CRFs will be conducted during site set-up and will be recorded on a delegation and training log. There will be a range of centralised monitoring activities (eg, eligibility, consent and safety checks) undertaken as well as being in regular contact with sites to discuss any issues encountered. The full data collection timetable is outlined in . To gain objective measures of physical activity in addition to self-report questionnaire data, participants will be asked to wear a wrist-worn accelerometer (GENEActiv, Activinsights, Kimbolton, UK) for seven days at baseline and six months follow-up. Accelerometer data will not be collected during the 12 month follow-up due to previously reported decreased adherence levels following six months. The devices are blinded, that is, participants will not be able to see or interact with their data during the wear period. Each participant will be offered a £10 high street gift voucher at their baseline, six and 12 months appointments. Confidentiality and data protection Each participant will be allocated a unique trial identification number. This number will be used to identify participants throughout the study. Data will be held according to the General Data Protection Regulations and the UK Policy Framework for Health and Social Care. Anonymised trial data will be securely archived by the UoY for a minimum of 10 years. Personal data of participants will be stored for up to three years after the study has ended for the purpose of disseminating study findings. Full details of the data protection regulations are outlined in . Patient and public involvement (PPI) During development and throughout the trial, we have been collaborating with DIAMONDS Voice, a service-user and carer group dedicated to supporting this work. The group consists of adults with SMI as well as family carers. DIAMONDS Voice members have contributed critically to the intervention content as well as the development of the intervention materials (app and workbook). For this RCT, they reviewed all participant-facing documentation, including consent forms, invitation letters and questionnaires, and were consulted about the acceptability of taking blood and undertaking measurements of their physical health. They continue to advise on recruitment strategies and will support recruitment within their own networks as appropriate and feasible. Members of DIAMONDS Voice will also be involved in the dissemination of trial findings and wider knowledge exchange activities. Sample size and statistical analysis Sample size The sample size calculation was based on detecting a clinically meaningful difference of 5.5 mmol/mol (0.5%) in HbA1c at 12 months. This difference was selected based on data from trials of diabetes self-management in the general diabetes population and National Institute for Health and Care Excellence (NICE) guideline on T2DM management. For approximately 90% power, at the 5% significance level, assuming an average cluster size of 10–12 participants per DIAMONDS Coach with an intraclass correlation of 0.02 in the intervention group and adjusting for 20% attrition, it was estimated that 450 participants need to be randomised, with 225 per group. Owing to slower than anticipated recruitment, we discussed options to revise the target sample size with the Programme Steering Committee (PSC) in February 2024. With the approval of the PSC, we amended the sample size by including an adjustment for the correlation between baseline and 12 months HbA1c (0.3) to reflect the repeated measures analysis model planned for the primary analysis. This led to a reduction in target sample size to 380 participants; statistical power at 88% is retained and all other assumptions remain the same. Statistical analysis Full analyses will be detailed in a statistical analysis plan (SAP), which will be finalised and made available before the end of data collection. Statistical analyses will be on an intention to treat basis and statistical significance will be at the 5% level (unless otherwise stated in the SAP). Analyses will be conducted in the latest available version of Stata or similar statistical software. Baseline characteristics will be reported descriptively by treatment group. Continuous data will be summarised as means, SD, medians and ranges and categorical data will be summarised as frequencies and percentages. Data will be visually inspected and any imbalance reported. No interim analyses will be conducted. Primary outcome HbA1c at 12 months post-randomisation will be analysed using a mixed-effects regression analysis, with HbA1c values at six and 12 months follow-up as the dependent variables. Baseline HbA1c values, randomised treatment group, time, and a treatment group-by-time interaction, as well as other important baseline covariates will be included as fixed effects, and the DIAMONDS Coach who delivered the intervention will be included as a random effect, nested within treatment group. Sensitivity analyses The amount of missing data will be reported for each randomised group, and we will also compare the baseline characteristics of participants who are included in the primary analysis to ensure that any missing data have not produced any imbalance in the groups in important covariates. The amount of missing data will be mitigated by including all data in the primary analysis model, which allows the inclusion of any patient with complete baseline data and valid outcome data at one or more follow-up points. Complier Average Causal Effect (CACE) analyses will be performed for the primary outcome to assess the impact of compliance with the intervention on treatment estimates. Subgroup analyses A subgroup analysis will be performed to explore any differential treatment effects for different levels of HbA1c at baseline. We will also conduct exploratory subgroup analysis by ethnicity and by insulin use status. The results of any subgroup analysis will be treated cautiously, detailed in advance in the SAP and include hypothesised direction of effect, in line with best practice. Secondary outcomes Secondary outcomes relating to participants’ physical health, mental health and diabetes measures will be analysed using mixed-effects regression analysis for continuous outcomes and logistic mixed models for categorical outcomes. Models will include assessments at all available time-points and will provide an overall treatment effect over 12 months, as well as estimates at individual time-points (six and 12 months), reported as estimates and 95% CIs. Accelerometer data will be collected at baseline and six months post-randomisation. Data will be analysed using the R-package GGIR, which performs signal processing of the raw data, including auto-calibration, detection of abnormal values, detection of non-wear and calculation of the average magnitude of dynamic acceleration (Euclidean norm minus one g (ENMO)). Descriptive statistics for accelerometer data will be reported for each treatment group at each time point (baseline and six months) and differences between treatment groups will be reported, adjusted for baseline. Process evaluation The process evaluation will draw on a mixed-methods approach, harnessing data from both qualitative and quantitative sources to address questions about whether the intervention was delivered as intended (ie, fidelity) and how outcomes were produced (ie, MoAs). Additionally, the process evaluation will aim to identify contextual and service-level barriers and enablers to post-trial implementation and scale-up, including whether the intervention can support self-management of other LTCs in people with SMI. Drawing on best practice methodology for process evaluations, we will identify and assess key dimensions related to what intervention activity and content was delivered and how. Intervention fidelity observations In accordance with the guidance set out by Bellg (2004), the Intervention Fidelity (IF) framework for the DIAMONDS RCT will measure: (1) adherence (whether the content of the intervention sessions was delivered as it was designed); (2) quality of delivery of intervention sessions (use of Behaviour Change Techniques and the manner/behaviour in which the Coach delivers the programme); (3) duration (mean, SD and range) of intervention sessions and (4) dose (number of sessions delivered). This IF framework was determined and refined through discussions with the research team at the Leicester Diabetes Centre (LDC) and University of Leicester (UoL), the study team and findings from the feasibility study. IF will be achieved by training observers to observe the sessions. For each observation, the trained observers will complete a checklist supported by an IF coding manual which will be developed by the LDC/UoL team. The development process will include drafting the checklist and IF coding manual, testing them by carrying out inter-rater reliability and refining them until the level of agreement is reached. Quantitative approach: data collection and analysis Quantitative data will be extracted from Coach session logs, the Change One Thing app content management system, and the IF assessments to descriptively summarise: Number of sessions delivered: mean, SD; session length. Date of sessions (to derive session frequency). Mode of delivery (videocall, phone, in person): frequencies/percentages. List of intervention content areas with number (%) of participants who discussed each content area Average duration a participant stayed with the same action plan/content area Average number of intervention content areas covered during the total intervention period and in both the workbook and/or Change One Thing app. Qualitative evaluation: recruitment, data collection and analysis The research team at UoY will conduct semi-structured interviews/focus groups with participants, carers and DIAMONDS Coaches to determine engagement and satisfaction with the intervention. Interviews/focus groups will last approximately 45 min. The recruitment, data collection, and analysis for each of these cohorts are outlined below. Participants A sample of participants (20–25) will be approached by the research staff at the trusts on completion of the intervention and asked to provide written or verbal consent to take part in these 1–1 interviews. We aim to invite participants with a range of ages, genders, baseline health outcomes, comorbidities, levels of engagement with the workbook/app and levels of intervention completeness to inform sampling. These interviews/focus groups will explore participants’ experiences of intervention delivery and receipt, and any behavioural changes made to support their physical health and well-being. Carers The research staff at the trusts will be asked to identify, contact and recruit 20–25 carers for participation in the interviews. They will obtain either written or verbal consent. Only carers of service-users participating in the DIAMONDS RCT will be eligible. Once carers have given consent to the research team at the study site and permissions are in place to share contact details, this information will be passed on to the study team at UoY who will be responsible for arranging and conducting the interviews. Similar to the participant interviews, these will last approximately 45 min. For the purpose of this study, carers are defined as unpaid carers who are not subject to working regulations and provide support to a dependent person who they have a social relationship with, such as a spouse, other relative, neighbour, friend or other non-kin. Coaches On completion of their intervention sessions, all Coaches will be invited to take part in interviews/focus groups. Coach interviews are expected to last 30 min and will explore questions around the DIAMONDS Coach training, delivering the intervention, engagement with Coach support and barriers and enablers to implementing the intervention in existing health and care services. All interviews/focus groups will be digitally recorded (with participant consent), anonymised and transcribed, with the transcripts forming the data for analysis. An initial thematic analysis will be conducted using a framework method. An initial coding framework will be developed, and transcripts checked against the framework to ensure that there are no significant omissions. Codes will be examined across individual transcripts as well as across the entire data set and allocated to the framework. Using aspects of the constant comparison method of analysis, broader categories using linking codes will be developed across the transcripts. Further analysis will be guided by the MoA framework that extends the Theoretical Domains Framework (TDF). The TDF offers a robust theoretical basis for understanding implementation problems and has previously been used to frame the focus of a process evaluation of a behaviour change intervention. Integrated analysis A triangulation protocol will be used to explore opportunities to further integrate the quantitative and qualitative data. The sources of data will include IF assessments about adherence and quality of intervention delivery; patient participant and informal caregiver interview data about experiences of intervention receipt and Coach interviews/focus group data about experiences of intervention delivery. Key findings will be compared (in pairs) across the data sets using a convergence coding matrix. For each qualitative theme, we will investigate whether we can identify analogues in the quantitative data. We will then categorise the relationship between findings from the qualitative and quantitative data according to four categories: agreement (convergence in the data), partial agreement (complementary findings but limited overlap), silence (no overlap between quantitative and qualitative data) and dissonance (disagreement between data sets). Economic evaluation The health economic analysis will take the form of a within-trial cost-utility analysis using an NHS and personal social services perspective as recommended by NICE guidance undertaken over a 12 month period. Additional details of the economic evaluation can be found in . Adverse event reporting, harms and participant withdrawals Adverse events An adverse event (AE) is any unexpected effect or untoward clinical event affecting the participant (ie, any unfavourable and unintended sign, symptom or disease). It can be directly related, possibly related or completely unrelated to the intervention. Any AEs or serious adverse events (SAEs) will be recorded by the R&D team at sites using specific AE/SAE forms. The reporting period will be from study entry to the last follow-up visit, and all events related to the DIAMONDS intervention will be recorded. All SAEs are to be reported to the Chief Investigator and will be reviewed by a clinician independent of the DIAMONDS study team. All SAEs will be reported to the Sponsor and Research Ethics Committee (REC) in line with their guidelines. Ongoing review of AEs will take place during the Programme Management Team and PSC meetings. Suicide and self-harm risk management We have developed a suicide risk protocol for the monitoring of suicide and self-harm risk during all encounters with study participants. Where any risk to participants, due to expressed thoughts of self-harm or suicide is encountered, a risk assessment will be conducted. Prior to conducting the risk assessment, the participant will be advised that if there is a concern of risk of harm to themselves or others, concerns will need to be passed on to another party, such as their GP or clinical care team. Duty of care We will use YTU standard operating procedures to support researchers to report to GPs or responsible services instances where there are concerns about the health of the participant. Normal NHS indemnity procedures will apply as participants are recruited from NHS sites. The Sponsor (UoY) will also provide standard public liability insurance to meet the potential legal liability of the sponsor for harm to participants arising from the design and management of the research. Researcher safety and lone working We will use the YTU standard operating procedures/UoY Department of Health Sciences policy for fieldwork and lone working. All researchers tasked with fieldwork will undertake lone worker training and conduct a risk assessment with their line manager about the specific tasks to be carried out. Participant withdrawals Participants will be able to withdraw from the trial at any point without having to provide a reason and without it affecting their usual care or any benefits to which they are entitled. If a participant decides to withdraw, their quality of care will not be compromised. The participant’s clinical team will also be able to withdraw participants if they lose capacity or become unfit to continue. There are three categories of withdrawal: withdrawal from follow-ups, withdrawal from intervention (ie, withdrawal from engaging with Coaches and workbook) or full withdrawal. Where withdrawal is from intervention only, follow-up data will continue to be collected from the participant. Data provided by participants who decide to withdraw will be retained for analysis up until the point of withdrawal. Trial oversight A Trial Management Group will monitor the day-to-day management of the trial. An independent PSC will have oversight of the trial and, due to the low-risk nature of this trial, it will also undertake the role of the Data Monitoring Committee. Ethics and dissemination The study received ethical approval by the West of Scotland 3 (22/WS/0117). It is registered with the ISRCTN (ISRCTN22275538) and CPMS (53712). Since the approval of the trial there have been three modifications to the protocol. The current protocol is version 1.3 (07.02.2024). We aim to publish the findings of the main study in peer reviewed, academic and professional journals to ensure that clinicians and academics have prompt access to our findings. We will produce a summary of the results that can be distributed to all trial participants and other relevant stakeholders (e.g. commissioners, third sector organisations) and will use social media channels, websites, and knowledge exchange events to communicate our findings beyond academic audiences. A publication policy has been agreed by the research team
The DIAMONDS trial is a multicentre, two-armed, parallel, individual RCT with embedded process and economic evaluations. The trial includes a 12 month internal pilot phase to assess recruitment assumptions and optimise trial processes (full details of the pilot phase can be found in ). Participants will be followed up for one year with outcome assessments conducted at six and 12 months post-randomisation. The overall study is planned to start in September 2022 and finish in September 2025. Recruitment is planned to start in December 2022 and finish in September 2024.
The study setting will include National Health Service (NHS) mental health trusts, general practices acting as Participant Identification Centres (PICs) and third sector organisations providing support to individuals with SMI and/or diabetes across England. Participants from previous studies who have provided consent will also be contacted, and individuals will be able to self-refer into the trial. An up-to-date list of recruiting sites is available on the DIAMONDS website ( https://www.diamondscollaboration.org.uk/ ). Participants will be recruited using methods successfully deployed in the DIAMONDS feasibility study, using a staged consent procedure. All participant-facing documents were produced in collaboration with DIAMONDS Voice ( https://www.diamondscollaboration.org.uk/diamonds-voice ), the service user and carer group that has been an integral part of the DIAMONDS programme for several years. Participants will be recruited from these sources and settings: NHS mental health trusts Authorised research and development (R&D) staff at participating secondary care sites will run searches in databases and screen community mental health team (CMHT) caseloads for potentially eligible patients using the eligibility criteria outlined below. There may also be direct referrals from consultants/CMHTs or through discharge meetings conducted with inpatient wards. Potential participants will receive a study information pack containing an invitation letter and a short patient information sheet (PIS) and will have the chance to discuss any questions they have with the research team (in person or over the phone). Following this, they will receive the full PIS. These potential participants will be contacted a few days later to arrange a face-to-face meeting with the research team, where there will be a further opportunity to ask questions relating to the study. If the individual wants to take part in the trial, they will be asked to give written informed consent (see for a copy of the consent form). GP database screenin g General practices will be asked to consult their SMI and LTC quality and outcomes framework registers to screen for potentially eligible patients using the inclusion criteria outlined below. General practitioners (GPs) at participating practices will check the lists produced by the database search to confirm eligibility. They will also approach potential participants at their annual health checks. Eligible patients will initially receive study information documents from their practice, usually via mailout to their home address. Where staff capacity allows, PIC sites will follow this up with a phone call. Consent-to-contact (CTC) will be obtained from interested patients, either via return of a CTC form or verbally during the follow-up phone call and passed on to appropriate research teams at mental health trusts who will then follow the same recruitment process as described above. Identification of potential participants from existing research cohorts Individuals who have previously taken part in related research projects conducted within our research group at UoY and who have given permission to be approached about future opportunities to participate in research will be contacted. Individuals identified via this route will receive the study information documents and will return a CTC form if interested. This CTC form will be passed on to the research teams at the mental health trusts and follow the process described above. Recruitment from third sector and service user groups We will work with relevant local third sector organisations and service user groups. Individuals who are interested in taking part in the trial will be directed to the person in the organisation/service supporting the trial, or the DIAMONDS study team. They will be provided with a short PIS and asked to complete and return a CTC form. The recruitment process will continue as previously described.
Authorised research and development (R&D) staff at participating secondary care sites will run searches in databases and screen community mental health team (CMHT) caseloads for potentially eligible patients using the eligibility criteria outlined below. There may also be direct referrals from consultants/CMHTs or through discharge meetings conducted with inpatient wards. Potential participants will receive a study information pack containing an invitation letter and a short patient information sheet (PIS) and will have the chance to discuss any questions they have with the research team (in person or over the phone). Following this, they will receive the full PIS. These potential participants will be contacted a few days later to arrange a face-to-face meeting with the research team, where there will be a further opportunity to ask questions relating to the study. If the individual wants to take part in the trial, they will be asked to give written informed consent (see for a copy of the consent form).
g General practices will be asked to consult their SMI and LTC quality and outcomes framework registers to screen for potentially eligible patients using the inclusion criteria outlined below. General practitioners (GPs) at participating practices will check the lists produced by the database search to confirm eligibility. They will also approach potential participants at their annual health checks. Eligible patients will initially receive study information documents from their practice, usually via mailout to their home address. Where staff capacity allows, PIC sites will follow this up with a phone call. Consent-to-contact (CTC) will be obtained from interested patients, either via return of a CTC form or verbally during the follow-up phone call and passed on to appropriate research teams at mental health trusts who will then follow the same recruitment process as described above.
Individuals who have previously taken part in related research projects conducted within our research group at UoY and who have given permission to be approached about future opportunities to participate in research will be contacted. Individuals identified via this route will receive the study information documents and will return a CTC form if interested. This CTC form will be passed on to the research teams at the mental health trusts and follow the process described above.
We will work with relevant local third sector organisations and service user groups. Individuals who are interested in taking part in the trial will be directed to the person in the organisation/service supporting the trial, or the DIAMONDS study team. They will be provided with a short PIS and asked to complete and return a CTC form. The recruitment process will continue as previously described.
Participants must (1) be aged 18 years or older and living in the community; (2) have any of the following SMI diagnoses: schizophrenia, bipolar disorder, schizoaffective disorder, psychosis, severe depression and (3) have T2DM. The diagnosis of SMI and T2DM must be confirmed by a clinician or be stated in the patient medical records. People will be excluded if they: (1) have cognitive impairments that would preclude the individual from participation in the trial and engagement with the intervention; (2) have gestational diabetes; (3) have type 1 diabetes; (4) have other types of secondary diabetes; (5) lack capacity to consent to participate in the trial as defined by the 2005 Mental Health Capacity Act or (6) are currently in an inpatient stay in an acute or mental health hospital.
illustrates the participant pathway through the trial.
Eligible and consenting participants will be randomised on a 1:1 basis to the DIAMONDS intervention or usual care using computer-generated permuted blocks of randomly varying size. York Trials Unit (YTU) will provide a central web-based randomisation service for R&D teams at sites to use when assigning participant allocations. Participants will then be informed of their allocation during their baseline visit or shortly following.
Efforts will be made to ensure R&D staff responsible for data collection remain blinded to treatment allocation. Should a participant inadvertently reveal their allocation to an outcome assessor, or the assessor becomes unblinded for any reason, this will be recorded in the outcome assessment case report form (CRF) at the relevant time. Designated R&D staff will be tasked with randomising participants and coordinating the handover of participants in the intervention group to a DIAMONDS Coach. Due to the nature of the comparison between the DIAMONDS intervention and treatment as usual, neither participants themselves nor the intervention facilitators (DIAMONDS Coaches) will be blinded. The trial statisticians and health economists will not be blinded. The DIAMONDS Programme Manager and Trial coordinators will remain unblinded and will not be involved in the analysis of data.
The DIAMONDS intervention was co-designed with service users, carers, members of the service user and carer group DIAMONDS Voice and healthcare professionals and is a tailored self-management support intervention to help people with T2DM and SMI self-manage diabetes through: Increasing knowledge and skills for diabetes self-management. Providing support to increase their physical activity levels and make healthier food choices. Identifying and addressing sleep difficulties, barriers to taking medications and other key problem areas as identified by the participant with support from their Coach, a healthcare professional who has been trained in the delivery of the DIAMONDS intervention. Supporting participants to manage their diabetes within the context of fluctuating and low mood. The acceptability of the intervention to participants and DIAMONDS Coaches was confirmed in the DIAMONDS feasibility study. Prior to the start of the RCT, we refined the intervention in line with findings from the feasibility study, which will be reported elsewhere (DIAMONDS Feasibility Study, ISRCTN15328700). A brief summary of the findings can be found ( https://www.hra.nhs.uk/planning-and-improving-research/application-summaries/research-summaries/diamonds-feasibility-study-v10/ ). The intervention will be delivered by a DIAMONDS Coach over a period of 6 months, using a combination of individual sessions and daily use of a paper-based workbook (the ‘DIAMONDS Workbook’) which can be supported by daily use of a digital app (‘Change One Thing’; optional) (see and details below). If the participant wishes to stop receiving the intervention before the end of the six months, the Coach will still support participants to set longer term goals and action plans for self-management and help them to access appropriate support to implement these, as is done for participants who complete the six month intervention period. Participants will be able to continue engaging with intervention content after follow-up data are collected through continued use of the app and/or workbook. Other reasons for the discontinuation of the intervention would be the death of the participant or if they remain an inpatient that takes them beyond the six month mark. Participants in the intervention will be permitted to continue with current care alongside the intervention.
Participants in the control group will access usual care for people with SMI and diabetes. This will include primary care health checks for SMI and diabetes along with community-based mental healthcare through CMHTs. Participants in the control group will be eligible to self-enrol in existing programmes. Participants randomised to the control group will be signposted to these services immediately following randomisation.
Data will be collected at baseline, six and 12 months post-randomisation during appointments with the R&D teams at participating sites taking place either on Trust premises or at the participant’s home. The blood samples for the primary (HbA1c) and secondary (haemoglobin and cholesterol) outcomes will be collected by an appropriately trained member of staff and will be sent to a central laboratory for analysis. The other secondary outcomes will be collected through paper-based CRFs which will be returned to YTU and then scanned using specialist software. The data will be checked against the hard copy of the CRF, error checked and validation checks run against the database. Queries will be raised with the site if discrepancies are identified during validation or on receipt. All training for completing CRFs will be conducted during site set-up and will be recorded on a delegation and training log. There will be a range of centralised monitoring activities (eg, eligibility, consent and safety checks) undertaken as well as being in regular contact with sites to discuss any issues encountered. The full data collection timetable is outlined in . To gain objective measures of physical activity in addition to self-report questionnaire data, participants will be asked to wear a wrist-worn accelerometer (GENEActiv, Activinsights, Kimbolton, UK) for seven days at baseline and six months follow-up. Accelerometer data will not be collected during the 12 month follow-up due to previously reported decreased adherence levels following six months. The devices are blinded, that is, participants will not be able to see or interact with their data during the wear period. Each participant will be offered a £10 high street gift voucher at their baseline, six and 12 months appointments. Confidentiality and data protection Each participant will be allocated a unique trial identification number. This number will be used to identify participants throughout the study. Data will be held according to the General Data Protection Regulations and the UK Policy Framework for Health and Social Care. Anonymised trial data will be securely archived by the UoY for a minimum of 10 years. Personal data of participants will be stored for up to three years after the study has ended for the purpose of disseminating study findings. Full details of the data protection regulations are outlined in .
Each participant will be allocated a unique trial identification number. This number will be used to identify participants throughout the study. Data will be held according to the General Data Protection Regulations and the UK Policy Framework for Health and Social Care. Anonymised trial data will be securely archived by the UoY for a minimum of 10 years. Personal data of participants will be stored for up to three years after the study has ended for the purpose of disseminating study findings. Full details of the data protection regulations are outlined in .
During development and throughout the trial, we have been collaborating with DIAMONDS Voice, a service-user and carer group dedicated to supporting this work. The group consists of adults with SMI as well as family carers. DIAMONDS Voice members have contributed critically to the intervention content as well as the development of the intervention materials (app and workbook). For this RCT, they reviewed all participant-facing documentation, including consent forms, invitation letters and questionnaires, and were consulted about the acceptability of taking blood and undertaking measurements of their physical health. They continue to advise on recruitment strategies and will support recruitment within their own networks as appropriate and feasible. Members of DIAMONDS Voice will also be involved in the dissemination of trial findings and wider knowledge exchange activities.
Sample size The sample size calculation was based on detecting a clinically meaningful difference of 5.5 mmol/mol (0.5%) in HbA1c at 12 months. This difference was selected based on data from trials of diabetes self-management in the general diabetes population and National Institute for Health and Care Excellence (NICE) guideline on T2DM management. For approximately 90% power, at the 5% significance level, assuming an average cluster size of 10–12 participants per DIAMONDS Coach with an intraclass correlation of 0.02 in the intervention group and adjusting for 20% attrition, it was estimated that 450 participants need to be randomised, with 225 per group. Owing to slower than anticipated recruitment, we discussed options to revise the target sample size with the Programme Steering Committee (PSC) in February 2024. With the approval of the PSC, we amended the sample size by including an adjustment for the correlation between baseline and 12 months HbA1c (0.3) to reflect the repeated measures analysis model planned for the primary analysis. This led to a reduction in target sample size to 380 participants; statistical power at 88% is retained and all other assumptions remain the same. Statistical analysis Full analyses will be detailed in a statistical analysis plan (SAP), which will be finalised and made available before the end of data collection. Statistical analyses will be on an intention to treat basis and statistical significance will be at the 5% level (unless otherwise stated in the SAP). Analyses will be conducted in the latest available version of Stata or similar statistical software. Baseline characteristics will be reported descriptively by treatment group. Continuous data will be summarised as means, SD, medians and ranges and categorical data will be summarised as frequencies and percentages. Data will be visually inspected and any imbalance reported. No interim analyses will be conducted. Primary outcome HbA1c at 12 months post-randomisation will be analysed using a mixed-effects regression analysis, with HbA1c values at six and 12 months follow-up as the dependent variables. Baseline HbA1c values, randomised treatment group, time, and a treatment group-by-time interaction, as well as other important baseline covariates will be included as fixed effects, and the DIAMONDS Coach who delivered the intervention will be included as a random effect, nested within treatment group. Sensitivity analyses The amount of missing data will be reported for each randomised group, and we will also compare the baseline characteristics of participants who are included in the primary analysis to ensure that any missing data have not produced any imbalance in the groups in important covariates. The amount of missing data will be mitigated by including all data in the primary analysis model, which allows the inclusion of any patient with complete baseline data and valid outcome data at one or more follow-up points. Complier Average Causal Effect (CACE) analyses will be performed for the primary outcome to assess the impact of compliance with the intervention on treatment estimates. Subgroup analyses A subgroup analysis will be performed to explore any differential treatment effects for different levels of HbA1c at baseline. We will also conduct exploratory subgroup analysis by ethnicity and by insulin use status. The results of any subgroup analysis will be treated cautiously, detailed in advance in the SAP and include hypothesised direction of effect, in line with best practice. Secondary outcomes Secondary outcomes relating to participants’ physical health, mental health and diabetes measures will be analysed using mixed-effects regression analysis for continuous outcomes and logistic mixed models for categorical outcomes. Models will include assessments at all available time-points and will provide an overall treatment effect over 12 months, as well as estimates at individual time-points (six and 12 months), reported as estimates and 95% CIs. Accelerometer data will be collected at baseline and six months post-randomisation. Data will be analysed using the R-package GGIR, which performs signal processing of the raw data, including auto-calibration, detection of abnormal values, detection of non-wear and calculation of the average magnitude of dynamic acceleration (Euclidean norm minus one g (ENMO)). Descriptive statistics for accelerometer data will be reported for each treatment group at each time point (baseline and six months) and differences between treatment groups will be reported, adjusted for baseline.
The sample size calculation was based on detecting a clinically meaningful difference of 5.5 mmol/mol (0.5%) in HbA1c at 12 months. This difference was selected based on data from trials of diabetes self-management in the general diabetes population and National Institute for Health and Care Excellence (NICE) guideline on T2DM management. For approximately 90% power, at the 5% significance level, assuming an average cluster size of 10–12 participants per DIAMONDS Coach with an intraclass correlation of 0.02 in the intervention group and adjusting for 20% attrition, it was estimated that 450 participants need to be randomised, with 225 per group. Owing to slower than anticipated recruitment, we discussed options to revise the target sample size with the Programme Steering Committee (PSC) in February 2024. With the approval of the PSC, we amended the sample size by including an adjustment for the correlation between baseline and 12 months HbA1c (0.3) to reflect the repeated measures analysis model planned for the primary analysis. This led to a reduction in target sample size to 380 participants; statistical power at 88% is retained and all other assumptions remain the same.
Full analyses will be detailed in a statistical analysis plan (SAP), which will be finalised and made available before the end of data collection. Statistical analyses will be on an intention to treat basis and statistical significance will be at the 5% level (unless otherwise stated in the SAP). Analyses will be conducted in the latest available version of Stata or similar statistical software. Baseline characteristics will be reported descriptively by treatment group. Continuous data will be summarised as means, SD, medians and ranges and categorical data will be summarised as frequencies and percentages. Data will be visually inspected and any imbalance reported. No interim analyses will be conducted. Primary outcome HbA1c at 12 months post-randomisation will be analysed using a mixed-effects regression analysis, with HbA1c values at six and 12 months follow-up as the dependent variables. Baseline HbA1c values, randomised treatment group, time, and a treatment group-by-time interaction, as well as other important baseline covariates will be included as fixed effects, and the DIAMONDS Coach who delivered the intervention will be included as a random effect, nested within treatment group. Sensitivity analyses The amount of missing data will be reported for each randomised group, and we will also compare the baseline characteristics of participants who are included in the primary analysis to ensure that any missing data have not produced any imbalance in the groups in important covariates. The amount of missing data will be mitigated by including all data in the primary analysis model, which allows the inclusion of any patient with complete baseline data and valid outcome data at one or more follow-up points. Complier Average Causal Effect (CACE) analyses will be performed for the primary outcome to assess the impact of compliance with the intervention on treatment estimates. Subgroup analyses A subgroup analysis will be performed to explore any differential treatment effects for different levels of HbA1c at baseline. We will also conduct exploratory subgroup analysis by ethnicity and by insulin use status. The results of any subgroup analysis will be treated cautiously, detailed in advance in the SAP and include hypothesised direction of effect, in line with best practice. Secondary outcomes Secondary outcomes relating to participants’ physical health, mental health and diabetes measures will be analysed using mixed-effects regression analysis for continuous outcomes and logistic mixed models for categorical outcomes. Models will include assessments at all available time-points and will provide an overall treatment effect over 12 months, as well as estimates at individual time-points (six and 12 months), reported as estimates and 95% CIs. Accelerometer data will be collected at baseline and six months post-randomisation. Data will be analysed using the R-package GGIR, which performs signal processing of the raw data, including auto-calibration, detection of abnormal values, detection of non-wear and calculation of the average magnitude of dynamic acceleration (Euclidean norm minus one g (ENMO)). Descriptive statistics for accelerometer data will be reported for each treatment group at each time point (baseline and six months) and differences between treatment groups will be reported, adjusted for baseline.
HbA1c at 12 months post-randomisation will be analysed using a mixed-effects regression analysis, with HbA1c values at six and 12 months follow-up as the dependent variables. Baseline HbA1c values, randomised treatment group, time, and a treatment group-by-time interaction, as well as other important baseline covariates will be included as fixed effects, and the DIAMONDS Coach who delivered the intervention will be included as a random effect, nested within treatment group.
The amount of missing data will be reported for each randomised group, and we will also compare the baseline characteristics of participants who are included in the primary analysis to ensure that any missing data have not produced any imbalance in the groups in important covariates. The amount of missing data will be mitigated by including all data in the primary analysis model, which allows the inclusion of any patient with complete baseline data and valid outcome data at one or more follow-up points. Complier Average Causal Effect (CACE) analyses will be performed for the primary outcome to assess the impact of compliance with the intervention on treatment estimates.
A subgroup analysis will be performed to explore any differential treatment effects for different levels of HbA1c at baseline. We will also conduct exploratory subgroup analysis by ethnicity and by insulin use status. The results of any subgroup analysis will be treated cautiously, detailed in advance in the SAP and include hypothesised direction of effect, in line with best practice.
Secondary outcomes relating to participants’ physical health, mental health and diabetes measures will be analysed using mixed-effects regression analysis for continuous outcomes and logistic mixed models for categorical outcomes. Models will include assessments at all available time-points and will provide an overall treatment effect over 12 months, as well as estimates at individual time-points (six and 12 months), reported as estimates and 95% CIs. Accelerometer data will be collected at baseline and six months post-randomisation. Data will be analysed using the R-package GGIR, which performs signal processing of the raw data, including auto-calibration, detection of abnormal values, detection of non-wear and calculation of the average magnitude of dynamic acceleration (Euclidean norm minus one g (ENMO)). Descriptive statistics for accelerometer data will be reported for each treatment group at each time point (baseline and six months) and differences between treatment groups will be reported, adjusted for baseline.
The process evaluation will draw on a mixed-methods approach, harnessing data from both qualitative and quantitative sources to address questions about whether the intervention was delivered as intended (ie, fidelity) and how outcomes were produced (ie, MoAs). Additionally, the process evaluation will aim to identify contextual and service-level barriers and enablers to post-trial implementation and scale-up, including whether the intervention can support self-management of other LTCs in people with SMI. Drawing on best practice methodology for process evaluations, we will identify and assess key dimensions related to what intervention activity and content was delivered and how. Intervention fidelity observations In accordance with the guidance set out by Bellg (2004), the Intervention Fidelity (IF) framework for the DIAMONDS RCT will measure: (1) adherence (whether the content of the intervention sessions was delivered as it was designed); (2) quality of delivery of intervention sessions (use of Behaviour Change Techniques and the manner/behaviour in which the Coach delivers the programme); (3) duration (mean, SD and range) of intervention sessions and (4) dose (number of sessions delivered). This IF framework was determined and refined through discussions with the research team at the Leicester Diabetes Centre (LDC) and University of Leicester (UoL), the study team and findings from the feasibility study. IF will be achieved by training observers to observe the sessions. For each observation, the trained observers will complete a checklist supported by an IF coding manual which will be developed by the LDC/UoL team. The development process will include drafting the checklist and IF coding manual, testing them by carrying out inter-rater reliability and refining them until the level of agreement is reached. Quantitative approach: data collection and analysis Quantitative data will be extracted from Coach session logs, the Change One Thing app content management system, and the IF assessments to descriptively summarise: Number of sessions delivered: mean, SD; session length. Date of sessions (to derive session frequency). Mode of delivery (videocall, phone, in person): frequencies/percentages. List of intervention content areas with number (%) of participants who discussed each content area Average duration a participant stayed with the same action plan/content area Average number of intervention content areas covered during the total intervention period and in both the workbook and/or Change One Thing app. Qualitative evaluation: recruitment, data collection and analysis The research team at UoY will conduct semi-structured interviews/focus groups with participants, carers and DIAMONDS Coaches to determine engagement and satisfaction with the intervention. Interviews/focus groups will last approximately 45 min. The recruitment, data collection, and analysis for each of these cohorts are outlined below. Participants A sample of participants (20–25) will be approached by the research staff at the trusts on completion of the intervention and asked to provide written or verbal consent to take part in these 1–1 interviews. We aim to invite participants with a range of ages, genders, baseline health outcomes, comorbidities, levels of engagement with the workbook/app and levels of intervention completeness to inform sampling. These interviews/focus groups will explore participants’ experiences of intervention delivery and receipt, and any behavioural changes made to support their physical health and well-being. Carers The research staff at the trusts will be asked to identify, contact and recruit 20–25 carers for participation in the interviews. They will obtain either written or verbal consent. Only carers of service-users participating in the DIAMONDS RCT will be eligible. Once carers have given consent to the research team at the study site and permissions are in place to share contact details, this information will be passed on to the study team at UoY who will be responsible for arranging and conducting the interviews. Similar to the participant interviews, these will last approximately 45 min. For the purpose of this study, carers are defined as unpaid carers who are not subject to working regulations and provide support to a dependent person who they have a social relationship with, such as a spouse, other relative, neighbour, friend or other non-kin. Coaches On completion of their intervention sessions, all Coaches will be invited to take part in interviews/focus groups. Coach interviews are expected to last 30 min and will explore questions around the DIAMONDS Coach training, delivering the intervention, engagement with Coach support and barriers and enablers to implementing the intervention in existing health and care services. All interviews/focus groups will be digitally recorded (with participant consent), anonymised and transcribed, with the transcripts forming the data for analysis. An initial thematic analysis will be conducted using a framework method. An initial coding framework will be developed, and transcripts checked against the framework to ensure that there are no significant omissions. Codes will be examined across individual transcripts as well as across the entire data set and allocated to the framework. Using aspects of the constant comparison method of analysis, broader categories using linking codes will be developed across the transcripts. Further analysis will be guided by the MoA framework that extends the Theoretical Domains Framework (TDF). The TDF offers a robust theoretical basis for understanding implementation problems and has previously been used to frame the focus of a process evaluation of a behaviour change intervention.
In accordance with the guidance set out by Bellg (2004), the Intervention Fidelity (IF) framework for the DIAMONDS RCT will measure: (1) adherence (whether the content of the intervention sessions was delivered as it was designed); (2) quality of delivery of intervention sessions (use of Behaviour Change Techniques and the manner/behaviour in which the Coach delivers the programme); (3) duration (mean, SD and range) of intervention sessions and (4) dose (number of sessions delivered). This IF framework was determined and refined through discussions with the research team at the Leicester Diabetes Centre (LDC) and University of Leicester (UoL), the study team and findings from the feasibility study. IF will be achieved by training observers to observe the sessions. For each observation, the trained observers will complete a checklist supported by an IF coding manual which will be developed by the LDC/UoL team. The development process will include drafting the checklist and IF coding manual, testing them by carrying out inter-rater reliability and refining them until the level of agreement is reached.
Quantitative data will be extracted from Coach session logs, the Change One Thing app content management system, and the IF assessments to descriptively summarise: Number of sessions delivered: mean, SD; session length. Date of sessions (to derive session frequency). Mode of delivery (videocall, phone, in person): frequencies/percentages. List of intervention content areas with number (%) of participants who discussed each content area Average duration a participant stayed with the same action plan/content area Average number of intervention content areas covered during the total intervention period and in both the workbook and/or Change One Thing app.
The research team at UoY will conduct semi-structured interviews/focus groups with participants, carers and DIAMONDS Coaches to determine engagement and satisfaction with the intervention. Interviews/focus groups will last approximately 45 min. The recruitment, data collection, and analysis for each of these cohorts are outlined below. Participants A sample of participants (20–25) will be approached by the research staff at the trusts on completion of the intervention and asked to provide written or verbal consent to take part in these 1–1 interviews. We aim to invite participants with a range of ages, genders, baseline health outcomes, comorbidities, levels of engagement with the workbook/app and levels of intervention completeness to inform sampling. These interviews/focus groups will explore participants’ experiences of intervention delivery and receipt, and any behavioural changes made to support their physical health and well-being. Carers The research staff at the trusts will be asked to identify, contact and recruit 20–25 carers for participation in the interviews. They will obtain either written or verbal consent. Only carers of service-users participating in the DIAMONDS RCT will be eligible. Once carers have given consent to the research team at the study site and permissions are in place to share contact details, this information will be passed on to the study team at UoY who will be responsible for arranging and conducting the interviews. Similar to the participant interviews, these will last approximately 45 min. For the purpose of this study, carers are defined as unpaid carers who are not subject to working regulations and provide support to a dependent person who they have a social relationship with, such as a spouse, other relative, neighbour, friend or other non-kin. Coaches On completion of their intervention sessions, all Coaches will be invited to take part in interviews/focus groups. Coach interviews are expected to last 30 min and will explore questions around the DIAMONDS Coach training, delivering the intervention, engagement with Coach support and barriers and enablers to implementing the intervention in existing health and care services. All interviews/focus groups will be digitally recorded (with participant consent), anonymised and transcribed, with the transcripts forming the data for analysis. An initial thematic analysis will be conducted using a framework method. An initial coding framework will be developed, and transcripts checked against the framework to ensure that there are no significant omissions. Codes will be examined across individual transcripts as well as across the entire data set and allocated to the framework. Using aspects of the constant comparison method of analysis, broader categories using linking codes will be developed across the transcripts. Further analysis will be guided by the MoA framework that extends the Theoretical Domains Framework (TDF). The TDF offers a robust theoretical basis for understanding implementation problems and has previously been used to frame the focus of a process evaluation of a behaviour change intervention.
A sample of participants (20–25) will be approached by the research staff at the trusts on completion of the intervention and asked to provide written or verbal consent to take part in these 1–1 interviews. We aim to invite participants with a range of ages, genders, baseline health outcomes, comorbidities, levels of engagement with the workbook/app and levels of intervention completeness to inform sampling. These interviews/focus groups will explore participants’ experiences of intervention delivery and receipt, and any behavioural changes made to support their physical health and well-being.
The research staff at the trusts will be asked to identify, contact and recruit 20–25 carers for participation in the interviews. They will obtain either written or verbal consent. Only carers of service-users participating in the DIAMONDS RCT will be eligible. Once carers have given consent to the research team at the study site and permissions are in place to share contact details, this information will be passed on to the study team at UoY who will be responsible for arranging and conducting the interviews. Similar to the participant interviews, these will last approximately 45 min. For the purpose of this study, carers are defined as unpaid carers who are not subject to working regulations and provide support to a dependent person who they have a social relationship with, such as a spouse, other relative, neighbour, friend or other non-kin.
On completion of their intervention sessions, all Coaches will be invited to take part in interviews/focus groups. Coach interviews are expected to last 30 min and will explore questions around the DIAMONDS Coach training, delivering the intervention, engagement with Coach support and barriers and enablers to implementing the intervention in existing health and care services. All interviews/focus groups will be digitally recorded (with participant consent), anonymised and transcribed, with the transcripts forming the data for analysis. An initial thematic analysis will be conducted using a framework method. An initial coding framework will be developed, and transcripts checked against the framework to ensure that there are no significant omissions. Codes will be examined across individual transcripts as well as across the entire data set and allocated to the framework. Using aspects of the constant comparison method of analysis, broader categories using linking codes will be developed across the transcripts. Further analysis will be guided by the MoA framework that extends the Theoretical Domains Framework (TDF). The TDF offers a robust theoretical basis for understanding implementation problems and has previously been used to frame the focus of a process evaluation of a behaviour change intervention.
A triangulation protocol will be used to explore opportunities to further integrate the quantitative and qualitative data. The sources of data will include IF assessments about adherence and quality of intervention delivery; patient participant and informal caregiver interview data about experiences of intervention receipt and Coach interviews/focus group data about experiences of intervention delivery. Key findings will be compared (in pairs) across the data sets using a convergence coding matrix. For each qualitative theme, we will investigate whether we can identify analogues in the quantitative data. We will then categorise the relationship between findings from the qualitative and quantitative data according to four categories: agreement (convergence in the data), partial agreement (complementary findings but limited overlap), silence (no overlap between quantitative and qualitative data) and dissonance (disagreement between data sets).
The health economic analysis will take the form of a within-trial cost-utility analysis using an NHS and personal social services perspective as recommended by NICE guidance undertaken over a 12 month period. Additional details of the economic evaluation can be found in .
Adverse events An adverse event (AE) is any unexpected effect or untoward clinical event affecting the participant (ie, any unfavourable and unintended sign, symptom or disease). It can be directly related, possibly related or completely unrelated to the intervention. Any AEs or serious adverse events (SAEs) will be recorded by the R&D team at sites using specific AE/SAE forms. The reporting period will be from study entry to the last follow-up visit, and all events related to the DIAMONDS intervention will be recorded. All SAEs are to be reported to the Chief Investigator and will be reviewed by a clinician independent of the DIAMONDS study team. All SAEs will be reported to the Sponsor and Research Ethics Committee (REC) in line with their guidelines. Ongoing review of AEs will take place during the Programme Management Team and PSC meetings. Suicide and self-harm risk management We have developed a suicide risk protocol for the monitoring of suicide and self-harm risk during all encounters with study participants. Where any risk to participants, due to expressed thoughts of self-harm or suicide is encountered, a risk assessment will be conducted. Prior to conducting the risk assessment, the participant will be advised that if there is a concern of risk of harm to themselves or others, concerns will need to be passed on to another party, such as their GP or clinical care team. Duty of care We will use YTU standard operating procedures to support researchers to report to GPs or responsible services instances where there are concerns about the health of the participant. Normal NHS indemnity procedures will apply as participants are recruited from NHS sites. The Sponsor (UoY) will also provide standard public liability insurance to meet the potential legal liability of the sponsor for harm to participants arising from the design and management of the research. Researcher safety and lone working We will use the YTU standard operating procedures/UoY Department of Health Sciences policy for fieldwork and lone working. All researchers tasked with fieldwork will undertake lone worker training and conduct a risk assessment with their line manager about the specific tasks to be carried out. Participant withdrawals Participants will be able to withdraw from the trial at any point without having to provide a reason and without it affecting their usual care or any benefits to which they are entitled. If a participant decides to withdraw, their quality of care will not be compromised. The participant’s clinical team will also be able to withdraw participants if they lose capacity or become unfit to continue. There are three categories of withdrawal: withdrawal from follow-ups, withdrawal from intervention (ie, withdrawal from engaging with Coaches and workbook) or full withdrawal. Where withdrawal is from intervention only, follow-up data will continue to be collected from the participant. Data provided by participants who decide to withdraw will be retained for analysis up until the point of withdrawal.
An adverse event (AE) is any unexpected effect or untoward clinical event affecting the participant (ie, any unfavourable and unintended sign, symptom or disease). It can be directly related, possibly related or completely unrelated to the intervention. Any AEs or serious adverse events (SAEs) will be recorded by the R&D team at sites using specific AE/SAE forms. The reporting period will be from study entry to the last follow-up visit, and all events related to the DIAMONDS intervention will be recorded. All SAEs are to be reported to the Chief Investigator and will be reviewed by a clinician independent of the DIAMONDS study team. All SAEs will be reported to the Sponsor and Research Ethics Committee (REC) in line with their guidelines. Ongoing review of AEs will take place during the Programme Management Team and PSC meetings.
We have developed a suicide risk protocol for the monitoring of suicide and self-harm risk during all encounters with study participants. Where any risk to participants, due to expressed thoughts of self-harm or suicide is encountered, a risk assessment will be conducted. Prior to conducting the risk assessment, the participant will be advised that if there is a concern of risk of harm to themselves or others, concerns will need to be passed on to another party, such as their GP or clinical care team.
We will use YTU standard operating procedures to support researchers to report to GPs or responsible services instances where there are concerns about the health of the participant. Normal NHS indemnity procedures will apply as participants are recruited from NHS sites. The Sponsor (UoY) will also provide standard public liability insurance to meet the potential legal liability of the sponsor for harm to participants arising from the design and management of the research.
We will use the YTU standard operating procedures/UoY Department of Health Sciences policy for fieldwork and lone working. All researchers tasked with fieldwork will undertake lone worker training and conduct a risk assessment with their line manager about the specific tasks to be carried out.
Participants will be able to withdraw from the trial at any point without having to provide a reason and without it affecting their usual care or any benefits to which they are entitled. If a participant decides to withdraw, their quality of care will not be compromised. The participant’s clinical team will also be able to withdraw participants if they lose capacity or become unfit to continue. There are three categories of withdrawal: withdrawal from follow-ups, withdrawal from intervention (ie, withdrawal from engaging with Coaches and workbook) or full withdrawal. Where withdrawal is from intervention only, follow-up data will continue to be collected from the participant. Data provided by participants who decide to withdraw will be retained for analysis up until the point of withdrawal.
A Trial Management Group will monitor the day-to-day management of the trial. An independent PSC will have oversight of the trial and, due to the low-risk nature of this trial, it will also undertake the role of the Data Monitoring Committee.
The study received ethical approval by the West of Scotland 3 (22/WS/0117). It is registered with the ISRCTN (ISRCTN22275538) and CPMS (53712). Since the approval of the trial there have been three modifications to the protocol. The current protocol is version 1.3 (07.02.2024). We aim to publish the findings of the main study in peer reviewed, academic and professional journals to ensure that clinicians and academics have prompt access to our findings. We will produce a summary of the results that can be distributed to all trial participants and other relevant stakeholders (e.g. commissioners, third sector organisations) and will use social media channels, websites, and knowledge exchange events to communicate our findings beyond academic audiences. A publication policy has been agreed by the research team
10.1136/bmjopen-2024-090295 online supplemental file 1
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FERTILITY CARE IN LOW AND MIDDLE INCOME COUNTRIES: Embryologists’ practices of care in IVF-clinics in sub-Saharan Africa | 51e84f3a-f42e-4e0e-a795-f41406e15aa7 | 11792113 | Anatomy[mh] | Embryologists are vital to in vitro fertilization (IVF) success, yet there is relatively little literature on the nature of their work. The authors of one editorial suggest that ‘the embryologist has always been considered a highly skilled “artisan of life”, extensively trained to master sensitive microscale procedures where the margin for error is close to zero’, and note their various roles other than technical . A summary of the ‘modern’ embryologists’ work suggests that they undertake a multiplicity of tasks – not only as technical experts but also as managers, researchers, collaborators, scholars, communicators and mentors . The importance of one or another role may depend on their specific position and experience, but ‘embryologists’ efficacy behind the scenes reflects positively on the success of the fertility clinic’ . Hence, although invisible and ‘behind the scenes’ , the work of embryologists is intense, collaborative and stressful. One study of embryologists found that 59% of UK and 62% of US embryologists reported high ‘burnout’, stress and occupational challenges . Little is known about the roles and experiences of embryologists in IVF clinics in the global south. Some anthropologists have reported on embryologists’ transnational mobility, as embryology was – and still is – a scarce expertise in many places in the global south, while the demand for IVF is constantly growing . showed how, in Uganda and Ghana, these ‘transnational arrangements affect the local appropriation of laboratory procedures, protocols, and practices in various way’ (p. 69), and delved into the relationship between clinicians and embryologists, where the latter – referred to as ‘biologists’ in the Mexican context – felt not ‘as much taken into account as much as they should’ (p. 39). Efforts to define the role, status and training needs of embryologists are ongoing . In looking at the role of embryologists in ensuring quality care, Kathryn Go describes them as ‘the most valuable and critical asset of an assisted reproduction technique laboratory’ and notes that ‘through their hands, safe conduct of patients’ gametes and embryos is achieved’ . She highlights the combination of technical skills – ‘the craft’ of embryology – with various administrative or regulatory compliance activities and lists a long range of responsibilities within clinics. These include the preparation and quality testing of materials and labware; preparation of gametes for transfers; cryopreservation and thawing procedures; embryo transfers; sperm manipulation, preparation and storage; training of new embryologists; biopsies; and retrospective data analysis. In addition, they are responsible for the maintenance of the laboratory, including instruments, equipment, supplies and temperature; record-keeping of all treatment cycles; education of clinical staff and patients about procedures; compliance work with accreditation authorities; and reporting of clinical data . Above all, embryologists carry a unique responsibility for the ‘moral objects’ of human embryos demanding meticulous attention and risk avoidance in their work. At any point, they can succeed or fail through technical mishap, neglect or carelessness. The care-work and emotional labour undertaken by embryologists – to care for embryos, oocytes and sperm, and patients – is highlighted in a study in New Zealand on the work of ‘biological scientists’ in human embryology and assisted reproduction. In this study, the tasks of medical scientists and embryologists are divided into a five-fold ‘object of care’: clients, reproductive material, the scientific and bureaucratic system that underpinned their work, the quality of the team dynamics and each scientist’s own internal state or ‘fitness to work’ . In New Zealand, these scientists were strongly encouraged to make personal contact with their clients to convey results and explain procedures, rather than to work anonymously in a remote laboratory with decontextualized reproductive material ; this explains their engagement with and commitment to care for patients in the first place. Furthermore, the emphasis on the other four objects of care was related to the idea that they were working with ‘precious’ material, referring in particular to oocytes and embryos; mistakes with such irreplaceable material were simply not an option . Other than taking care of these materials, embryologists took care of the scientific and bureaucratic processes underpinning the practice of the clinic, laboratory team dynamics and their own internal state of mind. They also undertook many aspects of the emotional labour considered important to high-quality patient-centred care: counselling patients, conveying bad news, trying to impart hope and managing ‘difficult’ patients . In this article, we likewise consider the work of embryologists through the lens of care, building upon and expanding the understandings of the work of embryologists as care-work. However, in a slightly different approach to the above categorization , we suggest care is enacted and co-produced through the interaction of people and things, an approach used in science and technology studies and material semiotics . This approach considers how people and material objects shape each other through relationships, which gain meaning as they are situated in practices and vary in different contexts. Instead of only describing how embryologists care, we consider how embryologists and the practices of their work enact care and are mutually shaped in the process. This allows us to consider how tasks, technologies and people – patients and other staff – together enact care within an IVF clinic. The approach, captured in ethnographic descriptions of IVF clinics, highlights the ontological choreography of multiple actors and technologies in the provision of care . Across sub-Saharan Africa (SSA), there is a shortage and maldistribution of IVF clinics. It is estimated that 1500 assisted reproduction cycles per million infertile people are required in SSA to meet present needs, but in 2020, only 87 cycles per million took place . The International Federation of Fertility Societies identified some 210 clinics in SSA, the majority in South Africa (40), Nigeria (96), Ghana (18) and Kenya (11) . Almost all clinics offering IVF in SSA are private clinics, and as a result, ARTs are not affordable for most people experiencing fertility problems in these countries . Only a few initiatives of publicly funded IVF in SSA countries (Nigeria, Mali and Uganda) have been reported ; in South Africa, only three public academic clinics offer a limited number of subsidized IVF cycles . Expanding IVF care across the continent is difficult, given the limited number of clinical and laboratory staff with the necessary expertise. In particular, there exist a shortage of embryologists, challenges in providing training for them and difficulties in retaining experienced staff due to a ‘brain drain’ to other countries. Training options for embryologists differ across countries. In South Africa, stringent selection and training for embryologists is observed (A Whittaker & T Gerrits, personal communication). Medical biological scientists can enrol in any of 12 different training programmes (such as genetic counselling, medical physics or microbiology) at seven different universities with medical faculties or can train at any one of six SANAS (Health Professions Council of South Africa)-accredited medical institutes or diagnostic laboratories. However, reproductive biology training is provided at only two institutions. Medical scientists with a four-year degree in science may enrol in a 24-month prescribed evidence-based internship in reproductive biology at one of two authorized academic ART laboratories (under the auspices of the Medical and Dental Board). Clinical technologists complete a two-year training in basic sciences at one of three universities of technology, then specialize in reproductive biology at various authorized ART laboratories. Certification of Independent Practice by the Health Professions Council of South Africa as a clinical embryologist is needed to practise as an embryologist. Overall, at the time the study took place, the numbers of people training were small; within public institutions, there were only nine new biological scientists being trained in reproductive biology at two hospitals (Steve Biko Hospital and Tygerberg Hospital) connected, respectively, with the University of Pretoria and the University of Stellenbosch (A Whittaker & T Gerrits, personal communication). In this article, we draw on our work on the emerging IVF industry in SSA, during which we observed the multiple tasks and work of embryologists that supplement their laboratory-technical tasks. Below, we first present the motivations of embryologists in SSA. We show their high level of engagement and commitment, noting the diversity of their roles and tasks . As we illustrate, the roles of embryologists are complex and may include work not undertaken in some other settings around the world. In the clinics we observed and in other interviews, embryologists were highly valued by fertility specialists and considered crucial members of the care team for patients and regularly consulted for their expertise. Care-work enacted by embryologists in SSA includes human reproductive materials, patients, running the laboratory, the profession and data. We argue that this care-work, in concert with their technologies, is crucial to achieve the main goal of clinics in providing effective and (high) quality infertility care. Finally, we explore aspects of care-work relevant to infertility care within SSA. We describe aspects of the work of embryologists not mentioned in the previous literature, including fundraising by embryologists and their roles in establishing ‘first’ clinics, mobile work as ‘fly-in fly-out’ (FIFO) staff, combined professional backgrounds and advocacy work where there may be little or no government financial support for IVF, nor legislation or professional guidelines in place. We draw on qualitative fieldwork and interviews conducted as part of a large ethnographic study on the emerging IVF industry in SSA. The qualitative methodology fitted the exploratory aims of the broader study and enabled us to combine different means of data collection, such as semi-structured interviews (SSIs), observations and conversations. In this ethnographic study, we interviewed 117 informants (including patients, clinicians, embryologists, nurses, counsellors and donors) from January 2022 to February 2023. This included key informants from across SSA (mainly South Africa, but also Uganda, Mozambique, Namibia, Tanzania, Ethiopia, Cameroon, Zambia and Ghana) and observations during visits to three public and six private clinics in South Africa – Pretoria, Johannesburg, Mbombela and Cape Town (in September and October 2022). In this article, we draw on SSIs with 11 embryologists who work or previously worked in fertility clinics in South Africa, Namibia, Ethiopia, Uganda, Zimbabwe, Kenya and Zambia. Thirteen embryologists were approached for an interview, of whom 11 agreed, one declined, and one did not respond. The conduct of SSIs is a valid way to gain insights into people’s accounts – their views and experiences . Informants were recruited through direct approaches to fertility clinics and personal networks of the study team. As hardly anything is known about the role of embryologists in SSA and no database exists, we opted for a combination of convenience and maximum variation sampling, attempting to include embryologists working in different contexts, positions and clinics to explore their different views and experiences . We spoke with six male and five female embryologists, all working in different clinics; nine of them (had) worked in private clinics and three in public clinics; their work experience varied substantially, from around 40 years to a couple of years. The SSIs, using a SSI-guide (presented in the Appendix, see section on given at the end of the article.), lasted on average approximately one hour and were conducted in person during visits to clinics or via Zoom throughout 2022 and 2023. All participants gave signed informed consent. Participants were asked to describe their work and comment on their motivation to do this work and its challenges, describe their roles and tasks in the clinic, reflect on what they felt might improve access to ARTs in SSA and consider the future of IVF in the region. For the current article, we used insights gained about their motivation and variety in roles (see also ). All interviews except one were recorded and transcribed (in one case, when the informant declined to be tape-recorded, notes were taken manually). One interviewee asked for the interview guide before the interview took place and answered the questions in written form; this document was shared with the researchers during the interview. Interviews were thematically coded (inductively) by the two first authors and then compared across the sample to note similar and contrasting opinions. As is common practice in social science, we provided all participants with pseudonyms (rather than numbers) to emphasize their personhood. Given that the community of embryologists is very small, we have not provided further data on the background and ages of informants to protect their anonymity. Ethical clearance was granted by Monash University (MUHREC 27166), the University of the Witwatersrand (M210546) and participating clinics. All names in this article are pseudonyms. Motivations to work in embryology In all conversations, we asked embryologists what got them involved and what drives them to stay in the IVF industry. Their strong motivation and commitment stood out despite the long hours, as embryologist Anje (South Africa) expressed: You know I must be honest with you, there were many times that I really wanted to get out of it because in the beginning it’s long hours, it is irregular hours. In the days when we started out we would have aspirated in the morning and then in vitro culture the eggs and strictly 4 o’clock in the afternoon – you were not allowed to do fertilisation before 4 o’clock. So that being a Monday, a Saturday, or a Sunday, 7 days a week. That is how we used to work. So the hours were very difficult for me but then at that time it just so happened that every time that I wanted to get away or do something else my road just got deeper and deeper into this’… as much as I at times tried to get out of it my roads always lead into deeper things, more, yeah, and that’s why I’m still here. When asking our embryology informants working in SSA IVF clinics to describe what their jobs entail and what an average day looks like, many first emphasized that ‘no day is the same’, given the enormous diversity of their tasks. In attempting to describe a ‘typical day’, one embryologist in an academic training clinic in South Africa explained in a written description: Started work at 06:30 h with mail over breakfast and pre-reading intern reports, followed by evaluation of embryos progress in the embryoscope at 07:00 h; conducted morning meetings to discuss previous procedures, current embryo development and the day’s ART tasks; then undertook administration and in-person talks with interns at 08:00 h; followed by tasks related to the work program including dealing with financials/disposables/equipment/repairs at 11:00 h. At 12:00 h had to troubleshoot a lab event and problem-solve, then had lunch [during which time processed more emails]. By 02:00 h undertook some research work as well as professional association activities and database entry. Went home at 04:50 h and then at 06:00 h was involved in an African Federation Fertility Society – Webinar. For many embryologists, the variety of their work is the attraction. Octavia (South Africa), who is involved in andrology and embryology, emphasized that this is what motivated her. She described it as ‘fascinating’: That is why I say I am actually in a very nice position here because I am an embryologist by registration, I still do embryology, I do what I love, I love working with sperm. And then also, I mean, the shipments and the donor sperm and I mean – when I started doing this I never thought I would choose a donor for a patient. These multiple daily tasks and responsibilities were described as rewarding by all our informants, though also extremely challenging, given the extended hours of work each day and over weekends. Most described good relationships with the fertility specialists and other clinical staff, recognition of their importance to the workings of the clinic and autonomy in their scientific work (reinforced in our interviews with fertility specialists). Finding a good balance between clinic care-work and domestic care-work at home with family was a topic that some embryologists struggled with, especially women who often had the double burden of gendered housework and family responsibilities in addition to paid work. The combination of laboratory practice with research added to their satisfaction in working in a field in which new technologies and research questions were continuously introduced, but this competed with the attention they wanted to give to their own family: Ja, so for me it is difficult. Sometimes I get to work and I think ‘I’m done, I can’t be a mom and do this and have a husband that has a difficult job.’ But then I love the research side, and then there is just a new research question or this new thing popping up – and there are so many questions in this field! So from a research perspective, it is an amazing field to be in. (Octavia) Another embryologist underlined the importance of research, yet regretted they only had limited time for that. Some embryologists had a personal motivation for their involvement, such as seeing close relatives or friends suffer from infertility or not being able to conceive themselves. The latter was the case for embryologist Sam (Zimbabwe): ‘I mean I'm more than motivated, you know … that my child is an IVF baby and that’s why I was motivated, yeah; so I mean I couldn’t get any bigger motivation’. Octavia’s own experience of motherhood increased her motivation to continue working in the field: ‘And then I had my own child and for me it changed there … I realised this is what people want and this is why they are there’. For Billy, a family connection to the IVF industry in Uganda inspired him to gain an advanced degree qualification in embryology. In addition, a number of embryologists undertake various forms of advocacy work, such as with government policies and institutions to improve funding for infertility treatment, to ease barriers to the importation of equipment and medication, or to improve access for patients. Embryologists were highly motivated because of their pioneering role in introducing fertility care in their country, as embryologist Erik (Ethiopia) explained: ‘The government, they didn’t give it any attention, the health professionals didn’t know about it too’. He noted the social stigma experienced by infertile people in Ethiopia, especially women, who he said had little recourse to biomedical treatment; here, polygamy, witchcraft or holy water were used to overcome infertility, and ‘women becoming nuns in convents and divorce’. In addition to working in embryology, Erik had become a fundraiser for a public infertility unit and saw himself as an advocate whose mission was ‘opening the eyes’ of health professionals and policymakers to the burden of infertility. Sam was the only embryologist who mentioned that his involvement in embryology was partly financially motivated, although the profession attracts a relatively high salary, especially in the private sector, this also makes retention of embryologists in the public sector difficult. Erik, for example, referred to the different salary levels for expert IVF staff in the public sector in Ethiopia: ‘I think gynecologists were paid, like US $2000, and the embryologists, it’s like, not more than US $500 in a month, which is big money, actually’. Some embryologists intimated that they had moved into the private sector because of better conditions, pay and experience, contributing to shortages of embryologists in the public sector of SSA countries. Caring for reproductive materials The primary role of embryologists, recognized in the laboratory, is the responsibility for human reproductive materials. As noted above, the sense of care derives from the clinical work – the work of making a baby – and the work in preserving the materials of potential human beings through handling, testing, vitrifying, transporting and thawing with care. There is enormous responsibility invested in the embryologist; at any point, they can succeed or fail through technical mishap, neglect or carelessness. The laboratory work must be precise, documented and double-checked, all under time pressures. There is great emphasis on the efficient use of laboratory materials and time due to the demand for cost-efficiency and specific biological chronology – time periods required for fertilization, embryo development and transfers. Several embryologists emphasized that they handle human embryos, which are – according to one interviewee – ‘not objects’. One argued that embryologists need to take care not to become disassociated from the embryo and to be aware of the special status of the embryos in the work they do. She illustrated this by recalling an event early in her career, when she had grown several embryos for one patient, and the clinician-in-charge had asked her to throw away three of those. She bluntly refused to do so – they were ‘perfectly good embryos’. While recognizing the preciousness of the materials was common among embryologists, one strongly distinguished between the preciousness of different materials involved in IVF. When talking about shipping materials and the risks involved, Octavia differentiated between sperm, eggs and embryos: So what we used to do a few years back, the clinics give patients a flask, a thermos flask, and you fill it with [a medium] and you put your sperm or eggs in there and you travel it up and down. So with sperm I am fine with patients to do that, but now with eggs and embryos it is starting to get a bit risky. So [a shipping company] is close by and I always tell patients to contact them and let them bring their shipper and we pack the shipper or they pack the shipper – it is at an additional cost, I know, but at least we know it is safe; the shipper is upright. And I mean sperm is one thing, but if your embryo, that’s your last embryo and now you are walking around with it in a flask! The technologies themselves figure in this care, as the ‘flask’ is not considered ‘safe enough’ for oocytes. Having appropriate, up-to-date, clean equipment, materials and space is paramount, and it is with pride that embryologists displayed to us their newest equipment, impeccable systems of record-keeping, effective systems for identifying material, checklists and workspaces. The technologies are both symbolically and pragmatically extensions of embryology care – they are the exclusive domain of the embryologist and the means through which material is tested, counted, fertilized and stored and through which vigilance and protection are enacted. In recognition of the preciousness of the materials they are working with, some embryologists also referred to their dependence on higher powers, beyond technology, to be successful . Praying at crucial moments, such as trying to find a healthy spermatozoon in a testicular biopsy or during ICSI fertilization, can be considered a practice of care undertaken in hope to increase the chance of success. For Sam, treatment failures were the most difficult of all: ‘Especially in the first year or two, you know it was really difficult when you failed, either you failed to fertilize the eggs or the embryos end – virtually no pregnancy’. Although he now feels he is experienced enough that he is capable of resolving most situations that confront him, he continues to call on God and says His support is still ‘dearly needed’. Enacting care with patients Embryologists may be thought of as technicians working in laboratory settings – dressed in white coats, wearing hair caps and gloves for hygienic purposes, distanced from the people they are working with and whose gametes they are handling with care. This does not reflect the situation of the embryologists we spoke with, who were all involved in emotional labour as part of their jobs, which was also observed by . All of those interviewed directly interacted with and cared for their patients outside the laboratory, and this seemed to be an essential and rewarding part of their job. These interactions differed depending on the kind and size of the clinic(s) in which they worked, their particular professional background, including training additional to embryology, and the position they held in the clinic. All were involved in informing and communicating with patients, such as explaining the procedures involved in IVF and the results of various treatment steps (for example, the number of ova retrieved or embryos fertilized). One embryologist (Anje, South Africa), also trained as a psychologist, underlined the importance of providing this information as a way for their patients to gain familiarity and a sense of control: I think, you know I try to just, I try to involve them as much as I can so that in the end they will realise that I cannot guarantee them a baby, but I can guarantee them that I will walk the road with them. And I think having the first interview, … I have about half and an hour interview with them explaining to them what we’re going to do, how they can expect to feel, what they can expect in terms of feedback, when they should be coming back, what we’re going to do with the embryo transfer, what will happen to their remaining embryos and in my way I try to familiarise them with very unfamiliar circumstances, and also try to at least put them in control in a situation where they don’t have control over anything … In such work, embryologists navigated the different backgrounds and knowledge bases of patients. Anje, for example, had put efforts into learning the basics of Portuguese to enable her to communicate directly with patients coming from Mozambique. Billy explained that at their clinic in Uganda, staff adapted their explanations of complex fertility issues to ensure comprehension: The patients first of all, I mean it’s varied. You have the highly educated ones who come to you after they have done all their research on the internet or whatever and then you have those who have no idea what they are even doing. So our way was really to break it down to them at their level. You know I explained the concept of a seed and the soil, why does the seed germinate and others don’t germinate… This is what you are going to go into, this is what you should expect and these are the success rates. If you are not successful we can do this again. These are your options. So we used to have very good dialogues and we would discuss options, you know. Some of the interviewed embryologists were responsible for sharing bad news, such as the failure of fertilization or poor-quality embryos. Anje compared support practices in universities in the early days of IVF – when social work and psychologists were involved in the IVF clinic – with more contemporary practices in private clinics, where things are ‘much speeded up’, with less time for counselling. Sometimes, negative results were left to secretarial staff to convey over the phone. She felt communication by the embryologist was one means to better support people: (The patients) become so anxious as to (say things like) ‘yesterday you said I had nine eggs, now today you say only five have been fertilized, now tomorrow only three are developing, what is happening? Will I – you know we can’t do anything about the stress that these people are under, or we can’t take it away. It’s part of the whole thing, but you can definitely limit the period that they have to cope with it on a daily basis but by at least talking to them, explaining to them what the real situation is. In clinics offering donor material and surrogacy, some embryologists were involved in educating patients with little knowledge of these practices, as Billy explained: If somebody really was post-menopausal, you know there was no point in wasting time selling them what you don’t have (IVF with her own eggs), but we freely talked about the concept of egg donation, egg sharing, surrogacy, but breaking it in a way that they could digest. For instance, somebody would say ‘Hey, but if another woman carries my baby then that’s not my baby’, and then we explain the genetics but at the level that they understand. A few of the embryologists we interviewed were also involved in donor selection, leading to extended interactions with patients. For example, Octavia was responsible for finding appropriate sperm donors (from an external donor bank), which she then presented as potential candidates to intended parents. In her experience, some intended parents were able to choose straight away; others continued to ponder about who would be the best donor, with lengthy conversations with Octavia: It is a huge responsibility, but I do look at it very scientifically. I never help a patient choose a donor if they say they have no selection criteria. So you need to give me three or four selection criteria, we need to have something, so I try and approach it as scientifically as possible with as little emotional connection to it as possible. Embryologists are also heavily involved in clinic policies and ethical considerations surrounding the use of third-party material. In South Africa, sperm donation is allowed to be anonymous, but elsewhere in SSA countries where our informants worked, little or no regulation existed. This means that clinics determine the ethical considerations and conditions under which third-party material is used (cf. ). For example, in Zimbabwe, although third-party donation is currently anonymous at their clinic, embryologist Sam is concerned that in the future, direct-to-consumer DNA testing may result in donor-conceived children tracing their family background: ‘I am worried for 20 years to come or so’. For that reason, to be able to care for such requests in the future, he keeps track of donors’ names and other details. At the time of the interview, this was a handwritten file; subsequently, a digital donor record system was installed at the clinic. Providing information on the procedures around shipping donor gametes and embryos is another task of one South Africa-based embryologist, although the actual shipping is organized by companies that provide specialized IVF courier services. This also involves direct communication with patients, to explain the options and procedures. Although the clinic is not legally responsible for these courier tasks and the risks involved, such as the materials not being carried properly and therefore arriving damaged, Octavia had to have conversations with patients about this. Caring for the clinic Due to the paucity of infertility clinics across the SSA region, several embryologists were involved in work as ‘pioneers’ lobbying for funding and investment to build ‘first’ clinics (both public and private), getting them running and offering a variety of treatments (including egg and sperm donation), or expanding to other countries. We consider this as ‘caring for the clinic’. This was time-consuming work that was additional to actual laboratory work – caring for ‘precious’ materials – and caring for patients. Setting up a clinic involves several steps: budgeting; finding investors or engaging in some form of crowdfunding; finding a proper building and adapting it to fit the requirements of an IVF clinic and laboratory; recruiting and training staff; purchasing equipment and arranging permissions for its import; getting medication approved, ordered and stored; guaranteeing backup of medication; logistics to ensure adequate supplies of culture medium; and so forth. In these steps, embryologists were confronted with various hurdles and challenges. One embryologist had undertaken such work in several countries and was often called in to troubleshoot laboratories with poor success rates to try to identify and fix the problem. Convincing other people, either policymakers in the public health service sector or private investors, to support the establishment of a clinic was the first hurdle they had to take. International professional contacts – experts they met during training abroad or at international conferences – were important for this. Erik, for example, collaborated with an Ethiopian university to convince some government officials and university professors to establish a public IVF clinic in a wing of an existing hospital. In the absence of financial support from the government, he then facilitated liaison with a US university clinic, which led to support for the IVF clinic for a period of five years. To staff the clinic, three gynaecologists working in the hospital and interested in infertility were recruited and sent to Taiwan for short IVF training courses and to Egypt for on-the-job training; embryologists were sent to India for a six-week course. Erik then assisted with getting approval for medication and culture media, all newly introduced products in Ethiopia, which had to be approved by the Ethiopian Drug Administration. The bureaucratic hurdles in getting approvals were manifold; at the time of the interview (October 2022), they were still in process. The public IVF clinic started functioning in 2021, more than two years after Erik proposed the clinic. Meanwhile, Erik had found another investor – a private company – prepared to invest in a private IVF clinic in Tigray Province. This company uses money from private investors who want to invest in health, led by a UK citizen originally from Ethiopia who understood the problem. With this investor, Erik was able to convince the government hospital in Tigray Province to build a new storey on top of the existing women’s hospital – ‘they preferred it not to be a solo IVF clinic, because it’s like, people don’t like it, it will be like, discriminatory’. Due to hostilities in the province, this clinic was not used when this interview was conducted – ‘it’s sitting there. Everything is there, the equipment. It’s idle now’. So, while Erik spent much time in setting up IVF clinics in Ethiopia, he has returned to a third country to work as an embryologist. Other embryologists reflected on similar challenges in setting up and expanding IVF clinics in SSA. Billy, who has lived and worked for a long time in Uganda as an embryologist, well remembers the efforts it took to get IVF introduced and the system working. Over the years, he invested time and effort in organizing IVF logistics. He arranged to purchase equipment, second-hand, from a European IVF centre that was closing, and had to convince the government that this was not just ‘the West dumping their used stuff’. Some large scientific equipment suppliers did not yet have agencies/offices in SSA, and they even had to buy instruments like a small microscope in Dubai, which was the nearest agency. Billy mentions that they were quite privileged from the start, ‘despite only purchasing and importing culture media, really buying a small quantity of stock for a limited number of patients’. He noted the support he received from ‘friends from Brussels who kind of lobbied for us’, which enabled them to establish relationships when going to conferences and allowed them to buy smaller quantities: ‘And, when their numbers were increasing over time (the companies) started taking us more seriously and they could ship (larger quantities)’. Getting equipment and other products into the harbour is one thing; getting them to pass customs duties is another: When they (government officials) don’t know these kinds of things, equipment and all, they tend to classify them as they want that attracts a whole huge duty. So it took us some kind of diplomacy dealing with key stakeholders in the ministries of health, and some government officials, some of whom had been our patients, to lobby. So once those kinds of people did speak on our behalf, yeah for some countries especially Uganda we had the favour of having a lot of the duties on some of these things lifted. So that helped us. Other embryologists had similar stories of their work setting up clinics, lobbying for funds, approaching investors and negotiating with government agencies. These roles are far beyond those typically associated with embryologists but indicate the crucial roles they play in advocating for the expansion of infertility services across SSA. Transnational mobilities: care-work across borders The shortage of expertise in embryology in many countries in SSA leads to the movement of clinicians and embryologists to provide services on rotation across the region, ‘flying-in flying-out’ (FIFO) across countries – and even continents – to deliver their lab services in short periods of time, often on a monthly or bimonthly basis . This transnational mobility – of patients and staff, gametes and embryos, lab equipment, materials and medication – complicates the functioning of the clinic and laboratory and further extends the care-work of embryologists across borders. This mobile FIFO work involves travel on a regular basis to other ‘satellite’ clinics or laboratories to deliver laboratory services in countries without embryology staff. This affects the work of embryologists, leading to an increase in ‘batching’, a practice that involves the control and manipulation of women patients’ hormonal cycles so that egg retrieval, fertilization of eggs with sperm and embryo transfer can take place for a cohort of patients within a discrete time period of a few days, making efficient use of the presence of embryologists. Embryologist Billy, for example, has worked on a regular circuit traversing satellite clinics in Uganda, Tanzania and Zambia. The organization of work is influenced by the scarcity/availability of certain expertise –in particular embryologists – and the need for time, material and cost efficiencies. For the embryologist, such work is intensive. Peter, for instance, noted the intensity of his workload during periods working in a satellite clinic in Namibia and elsewhere outside South Africa when he is the only one in the laboratory, ‘so I do everything. Instead of there being two or three people helping there is only one person’. Caring for the profession Dedication to the profession was evident in our interviews, in particular the need for further training in the region and professional development opportunities for embryologists who may be quite isolated in disparate countries. Concerns about recognizing embryology as an important specialization were expressed in our interviews as well. For example, in South Africa, the country has only two full professors in embryology; there is no professional society for embryologists (though a Special Interest Group for embryologists exists in SASREG (Southern African Society of Reproductive Medicine and Gynaecological Endoscopy)); the capacity for training embryologists in clinics is limited; and legally, the term ‘embryologist’ is not defined or protected. One embryologist mentioned their involvement in training as a key source of personal satisfaction and motivation: (I) encourage independent evidence based-scientific thinking and life-competencies. So that interns carry on a philosophy of strong self-worth, develop their own capabilities, based on experiences and knowledge where to get answers if in doubt. Trainees in medical embryology are carefully selected. As one trainer noted, embryologists must be able to carefully handle the precious materials they are going to work with, and not everyone has this capacity. Our interviewees noted that approximately 15 applicants apply annually in South Africa to be trained in medical embryology, usually coming from biological science backgrounds, but of these, only three are accepted due to the limited capacity to train more. The applicants have to spend a day in a lab to watch the realities of the work involved. The embryologists and medical scientists with whom they work during that day will then score the applicant on a number of qualities, before the applicant is invited for an interview. At the interview, we were informed that their motivation for training and the work is an important topic. Once trained, most embryologists are in such demand that they are lost to public health systems and usually find work in the private sector. Several experienced embryologists in our sample had emigrated for further training opportunities and experience and also, in some cases, to permanently live and work overseas. As a result, across SSA, clinics complained about the difficulties in attracting and retaining embryologists and other medical science staff. In all conversations, we asked embryologists what got them involved and what drives them to stay in the IVF industry. Their strong motivation and commitment stood out despite the long hours, as embryologist Anje (South Africa) expressed: You know I must be honest with you, there were many times that I really wanted to get out of it because in the beginning it’s long hours, it is irregular hours. In the days when we started out we would have aspirated in the morning and then in vitro culture the eggs and strictly 4 o’clock in the afternoon – you were not allowed to do fertilisation before 4 o’clock. So that being a Monday, a Saturday, or a Sunday, 7 days a week. That is how we used to work. So the hours were very difficult for me but then at that time it just so happened that every time that I wanted to get away or do something else my road just got deeper and deeper into this’… as much as I at times tried to get out of it my roads always lead into deeper things, more, yeah, and that’s why I’m still here. When asking our embryology informants working in SSA IVF clinics to describe what their jobs entail and what an average day looks like, many first emphasized that ‘no day is the same’, given the enormous diversity of their tasks. In attempting to describe a ‘typical day’, one embryologist in an academic training clinic in South Africa explained in a written description: Started work at 06:30 h with mail over breakfast and pre-reading intern reports, followed by evaluation of embryos progress in the embryoscope at 07:00 h; conducted morning meetings to discuss previous procedures, current embryo development and the day’s ART tasks; then undertook administration and in-person talks with interns at 08:00 h; followed by tasks related to the work program including dealing with financials/disposables/equipment/repairs at 11:00 h. At 12:00 h had to troubleshoot a lab event and problem-solve, then had lunch [during which time processed more emails]. By 02:00 h undertook some research work as well as professional association activities and database entry. Went home at 04:50 h and then at 06:00 h was involved in an African Federation Fertility Society – Webinar. For many embryologists, the variety of their work is the attraction. Octavia (South Africa), who is involved in andrology and embryology, emphasized that this is what motivated her. She described it as ‘fascinating’: That is why I say I am actually in a very nice position here because I am an embryologist by registration, I still do embryology, I do what I love, I love working with sperm. And then also, I mean, the shipments and the donor sperm and I mean – when I started doing this I never thought I would choose a donor for a patient. These multiple daily tasks and responsibilities were described as rewarding by all our informants, though also extremely challenging, given the extended hours of work each day and over weekends. Most described good relationships with the fertility specialists and other clinical staff, recognition of their importance to the workings of the clinic and autonomy in their scientific work (reinforced in our interviews with fertility specialists). Finding a good balance between clinic care-work and domestic care-work at home with family was a topic that some embryologists struggled with, especially women who often had the double burden of gendered housework and family responsibilities in addition to paid work. The combination of laboratory practice with research added to their satisfaction in working in a field in which new technologies and research questions were continuously introduced, but this competed with the attention they wanted to give to their own family: Ja, so for me it is difficult. Sometimes I get to work and I think ‘I’m done, I can’t be a mom and do this and have a husband that has a difficult job.’ But then I love the research side, and then there is just a new research question or this new thing popping up – and there are so many questions in this field! So from a research perspective, it is an amazing field to be in. (Octavia) Another embryologist underlined the importance of research, yet regretted they only had limited time for that. Some embryologists had a personal motivation for their involvement, such as seeing close relatives or friends suffer from infertility or not being able to conceive themselves. The latter was the case for embryologist Sam (Zimbabwe): ‘I mean I'm more than motivated, you know … that my child is an IVF baby and that’s why I was motivated, yeah; so I mean I couldn’t get any bigger motivation’. Octavia’s own experience of motherhood increased her motivation to continue working in the field: ‘And then I had my own child and for me it changed there … I realised this is what people want and this is why they are there’. For Billy, a family connection to the IVF industry in Uganda inspired him to gain an advanced degree qualification in embryology. In addition, a number of embryologists undertake various forms of advocacy work, such as with government policies and institutions to improve funding for infertility treatment, to ease barriers to the importation of equipment and medication, or to improve access for patients. Embryologists were highly motivated because of their pioneering role in introducing fertility care in their country, as embryologist Erik (Ethiopia) explained: ‘The government, they didn’t give it any attention, the health professionals didn’t know about it too’. He noted the social stigma experienced by infertile people in Ethiopia, especially women, who he said had little recourse to biomedical treatment; here, polygamy, witchcraft or holy water were used to overcome infertility, and ‘women becoming nuns in convents and divorce’. In addition to working in embryology, Erik had become a fundraiser for a public infertility unit and saw himself as an advocate whose mission was ‘opening the eyes’ of health professionals and policymakers to the burden of infertility. Sam was the only embryologist who mentioned that his involvement in embryology was partly financially motivated, although the profession attracts a relatively high salary, especially in the private sector, this also makes retention of embryologists in the public sector difficult. Erik, for example, referred to the different salary levels for expert IVF staff in the public sector in Ethiopia: ‘I think gynecologists were paid, like US $2000, and the embryologists, it’s like, not more than US $500 in a month, which is big money, actually’. Some embryologists intimated that they had moved into the private sector because of better conditions, pay and experience, contributing to shortages of embryologists in the public sector of SSA countries. The primary role of embryologists, recognized in the laboratory, is the responsibility for human reproductive materials. As noted above, the sense of care derives from the clinical work – the work of making a baby – and the work in preserving the materials of potential human beings through handling, testing, vitrifying, transporting and thawing with care. There is enormous responsibility invested in the embryologist; at any point, they can succeed or fail through technical mishap, neglect or carelessness. The laboratory work must be precise, documented and double-checked, all under time pressures. There is great emphasis on the efficient use of laboratory materials and time due to the demand for cost-efficiency and specific biological chronology – time periods required for fertilization, embryo development and transfers. Several embryologists emphasized that they handle human embryos, which are – according to one interviewee – ‘not objects’. One argued that embryologists need to take care not to become disassociated from the embryo and to be aware of the special status of the embryos in the work they do. She illustrated this by recalling an event early in her career, when she had grown several embryos for one patient, and the clinician-in-charge had asked her to throw away three of those. She bluntly refused to do so – they were ‘perfectly good embryos’. While recognizing the preciousness of the materials was common among embryologists, one strongly distinguished between the preciousness of different materials involved in IVF. When talking about shipping materials and the risks involved, Octavia differentiated between sperm, eggs and embryos: So what we used to do a few years back, the clinics give patients a flask, a thermos flask, and you fill it with [a medium] and you put your sperm or eggs in there and you travel it up and down. So with sperm I am fine with patients to do that, but now with eggs and embryos it is starting to get a bit risky. So [a shipping company] is close by and I always tell patients to contact them and let them bring their shipper and we pack the shipper or they pack the shipper – it is at an additional cost, I know, but at least we know it is safe; the shipper is upright. And I mean sperm is one thing, but if your embryo, that’s your last embryo and now you are walking around with it in a flask! The technologies themselves figure in this care, as the ‘flask’ is not considered ‘safe enough’ for oocytes. Having appropriate, up-to-date, clean equipment, materials and space is paramount, and it is with pride that embryologists displayed to us their newest equipment, impeccable systems of record-keeping, effective systems for identifying material, checklists and workspaces. The technologies are both symbolically and pragmatically extensions of embryology care – they are the exclusive domain of the embryologist and the means through which material is tested, counted, fertilized and stored and through which vigilance and protection are enacted. In recognition of the preciousness of the materials they are working with, some embryologists also referred to their dependence on higher powers, beyond technology, to be successful . Praying at crucial moments, such as trying to find a healthy spermatozoon in a testicular biopsy or during ICSI fertilization, can be considered a practice of care undertaken in hope to increase the chance of success. For Sam, treatment failures were the most difficult of all: ‘Especially in the first year or two, you know it was really difficult when you failed, either you failed to fertilize the eggs or the embryos end – virtually no pregnancy’. Although he now feels he is experienced enough that he is capable of resolving most situations that confront him, he continues to call on God and says His support is still ‘dearly needed’. Embryologists may be thought of as technicians working in laboratory settings – dressed in white coats, wearing hair caps and gloves for hygienic purposes, distanced from the people they are working with and whose gametes they are handling with care. This does not reflect the situation of the embryologists we spoke with, who were all involved in emotional labour as part of their jobs, which was also observed by . All of those interviewed directly interacted with and cared for their patients outside the laboratory, and this seemed to be an essential and rewarding part of their job. These interactions differed depending on the kind and size of the clinic(s) in which they worked, their particular professional background, including training additional to embryology, and the position they held in the clinic. All were involved in informing and communicating with patients, such as explaining the procedures involved in IVF and the results of various treatment steps (for example, the number of ova retrieved or embryos fertilized). One embryologist (Anje, South Africa), also trained as a psychologist, underlined the importance of providing this information as a way for their patients to gain familiarity and a sense of control: I think, you know I try to just, I try to involve them as much as I can so that in the end they will realise that I cannot guarantee them a baby, but I can guarantee them that I will walk the road with them. And I think having the first interview, … I have about half and an hour interview with them explaining to them what we’re going to do, how they can expect to feel, what they can expect in terms of feedback, when they should be coming back, what we’re going to do with the embryo transfer, what will happen to their remaining embryos and in my way I try to familiarise them with very unfamiliar circumstances, and also try to at least put them in control in a situation where they don’t have control over anything … In such work, embryologists navigated the different backgrounds and knowledge bases of patients. Anje, for example, had put efforts into learning the basics of Portuguese to enable her to communicate directly with patients coming from Mozambique. Billy explained that at their clinic in Uganda, staff adapted their explanations of complex fertility issues to ensure comprehension: The patients first of all, I mean it’s varied. You have the highly educated ones who come to you after they have done all their research on the internet or whatever and then you have those who have no idea what they are even doing. So our way was really to break it down to them at their level. You know I explained the concept of a seed and the soil, why does the seed germinate and others don’t germinate… This is what you are going to go into, this is what you should expect and these are the success rates. If you are not successful we can do this again. These are your options. So we used to have very good dialogues and we would discuss options, you know. Some of the interviewed embryologists were responsible for sharing bad news, such as the failure of fertilization or poor-quality embryos. Anje compared support practices in universities in the early days of IVF – when social work and psychologists were involved in the IVF clinic – with more contemporary practices in private clinics, where things are ‘much speeded up’, with less time for counselling. Sometimes, negative results were left to secretarial staff to convey over the phone. She felt communication by the embryologist was one means to better support people: (The patients) become so anxious as to (say things like) ‘yesterday you said I had nine eggs, now today you say only five have been fertilized, now tomorrow only three are developing, what is happening? Will I – you know we can’t do anything about the stress that these people are under, or we can’t take it away. It’s part of the whole thing, but you can definitely limit the period that they have to cope with it on a daily basis but by at least talking to them, explaining to them what the real situation is. In clinics offering donor material and surrogacy, some embryologists were involved in educating patients with little knowledge of these practices, as Billy explained: If somebody really was post-menopausal, you know there was no point in wasting time selling them what you don’t have (IVF with her own eggs), but we freely talked about the concept of egg donation, egg sharing, surrogacy, but breaking it in a way that they could digest. For instance, somebody would say ‘Hey, but if another woman carries my baby then that’s not my baby’, and then we explain the genetics but at the level that they understand. A few of the embryologists we interviewed were also involved in donor selection, leading to extended interactions with patients. For example, Octavia was responsible for finding appropriate sperm donors (from an external donor bank), which she then presented as potential candidates to intended parents. In her experience, some intended parents were able to choose straight away; others continued to ponder about who would be the best donor, with lengthy conversations with Octavia: It is a huge responsibility, but I do look at it very scientifically. I never help a patient choose a donor if they say they have no selection criteria. So you need to give me three or four selection criteria, we need to have something, so I try and approach it as scientifically as possible with as little emotional connection to it as possible. Embryologists are also heavily involved in clinic policies and ethical considerations surrounding the use of third-party material. In South Africa, sperm donation is allowed to be anonymous, but elsewhere in SSA countries where our informants worked, little or no regulation existed. This means that clinics determine the ethical considerations and conditions under which third-party material is used (cf. ). For example, in Zimbabwe, although third-party donation is currently anonymous at their clinic, embryologist Sam is concerned that in the future, direct-to-consumer DNA testing may result in donor-conceived children tracing their family background: ‘I am worried for 20 years to come or so’. For that reason, to be able to care for such requests in the future, he keeps track of donors’ names and other details. At the time of the interview, this was a handwritten file; subsequently, a digital donor record system was installed at the clinic. Providing information on the procedures around shipping donor gametes and embryos is another task of one South Africa-based embryologist, although the actual shipping is organized by companies that provide specialized IVF courier services. This also involves direct communication with patients, to explain the options and procedures. Although the clinic is not legally responsible for these courier tasks and the risks involved, such as the materials not being carried properly and therefore arriving damaged, Octavia had to have conversations with patients about this. Due to the paucity of infertility clinics across the SSA region, several embryologists were involved in work as ‘pioneers’ lobbying for funding and investment to build ‘first’ clinics (both public and private), getting them running and offering a variety of treatments (including egg and sperm donation), or expanding to other countries. We consider this as ‘caring for the clinic’. This was time-consuming work that was additional to actual laboratory work – caring for ‘precious’ materials – and caring for patients. Setting up a clinic involves several steps: budgeting; finding investors or engaging in some form of crowdfunding; finding a proper building and adapting it to fit the requirements of an IVF clinic and laboratory; recruiting and training staff; purchasing equipment and arranging permissions for its import; getting medication approved, ordered and stored; guaranteeing backup of medication; logistics to ensure adequate supplies of culture medium; and so forth. In these steps, embryologists were confronted with various hurdles and challenges. One embryologist had undertaken such work in several countries and was often called in to troubleshoot laboratories with poor success rates to try to identify and fix the problem. Convincing other people, either policymakers in the public health service sector or private investors, to support the establishment of a clinic was the first hurdle they had to take. International professional contacts – experts they met during training abroad or at international conferences – were important for this. Erik, for example, collaborated with an Ethiopian university to convince some government officials and university professors to establish a public IVF clinic in a wing of an existing hospital. In the absence of financial support from the government, he then facilitated liaison with a US university clinic, which led to support for the IVF clinic for a period of five years. To staff the clinic, three gynaecologists working in the hospital and interested in infertility were recruited and sent to Taiwan for short IVF training courses and to Egypt for on-the-job training; embryologists were sent to India for a six-week course. Erik then assisted with getting approval for medication and culture media, all newly introduced products in Ethiopia, which had to be approved by the Ethiopian Drug Administration. The bureaucratic hurdles in getting approvals were manifold; at the time of the interview (October 2022), they were still in process. The public IVF clinic started functioning in 2021, more than two years after Erik proposed the clinic. Meanwhile, Erik had found another investor – a private company – prepared to invest in a private IVF clinic in Tigray Province. This company uses money from private investors who want to invest in health, led by a UK citizen originally from Ethiopia who understood the problem. With this investor, Erik was able to convince the government hospital in Tigray Province to build a new storey on top of the existing women’s hospital – ‘they preferred it not to be a solo IVF clinic, because it’s like, people don’t like it, it will be like, discriminatory’. Due to hostilities in the province, this clinic was not used when this interview was conducted – ‘it’s sitting there. Everything is there, the equipment. It’s idle now’. So, while Erik spent much time in setting up IVF clinics in Ethiopia, he has returned to a third country to work as an embryologist. Other embryologists reflected on similar challenges in setting up and expanding IVF clinics in SSA. Billy, who has lived and worked for a long time in Uganda as an embryologist, well remembers the efforts it took to get IVF introduced and the system working. Over the years, he invested time and effort in organizing IVF logistics. He arranged to purchase equipment, second-hand, from a European IVF centre that was closing, and had to convince the government that this was not just ‘the West dumping their used stuff’. Some large scientific equipment suppliers did not yet have agencies/offices in SSA, and they even had to buy instruments like a small microscope in Dubai, which was the nearest agency. Billy mentions that they were quite privileged from the start, ‘despite only purchasing and importing culture media, really buying a small quantity of stock for a limited number of patients’. He noted the support he received from ‘friends from Brussels who kind of lobbied for us’, which enabled them to establish relationships when going to conferences and allowed them to buy smaller quantities: ‘And, when their numbers were increasing over time (the companies) started taking us more seriously and they could ship (larger quantities)’. Getting equipment and other products into the harbour is one thing; getting them to pass customs duties is another: When they (government officials) don’t know these kinds of things, equipment and all, they tend to classify them as they want that attracts a whole huge duty. So it took us some kind of diplomacy dealing with key stakeholders in the ministries of health, and some government officials, some of whom had been our patients, to lobby. So once those kinds of people did speak on our behalf, yeah for some countries especially Uganda we had the favour of having a lot of the duties on some of these things lifted. So that helped us. Other embryologists had similar stories of their work setting up clinics, lobbying for funds, approaching investors and negotiating with government agencies. These roles are far beyond those typically associated with embryologists but indicate the crucial roles they play in advocating for the expansion of infertility services across SSA. The shortage of expertise in embryology in many countries in SSA leads to the movement of clinicians and embryologists to provide services on rotation across the region, ‘flying-in flying-out’ (FIFO) across countries – and even continents – to deliver their lab services in short periods of time, often on a monthly or bimonthly basis . This transnational mobility – of patients and staff, gametes and embryos, lab equipment, materials and medication – complicates the functioning of the clinic and laboratory and further extends the care-work of embryologists across borders. This mobile FIFO work involves travel on a regular basis to other ‘satellite’ clinics or laboratories to deliver laboratory services in countries without embryology staff. This affects the work of embryologists, leading to an increase in ‘batching’, a practice that involves the control and manipulation of women patients’ hormonal cycles so that egg retrieval, fertilization of eggs with sperm and embryo transfer can take place for a cohort of patients within a discrete time period of a few days, making efficient use of the presence of embryologists. Embryologist Billy, for example, has worked on a regular circuit traversing satellite clinics in Uganda, Tanzania and Zambia. The organization of work is influenced by the scarcity/availability of certain expertise –in particular embryologists – and the need for time, material and cost efficiencies. For the embryologist, such work is intensive. Peter, for instance, noted the intensity of his workload during periods working in a satellite clinic in Namibia and elsewhere outside South Africa when he is the only one in the laboratory, ‘so I do everything. Instead of there being two or three people helping there is only one person’. Dedication to the profession was evident in our interviews, in particular the need for further training in the region and professional development opportunities for embryologists who may be quite isolated in disparate countries. Concerns about recognizing embryology as an important specialization were expressed in our interviews as well. For example, in South Africa, the country has only two full professors in embryology; there is no professional society for embryologists (though a Special Interest Group for embryologists exists in SASREG (Southern African Society of Reproductive Medicine and Gynaecological Endoscopy)); the capacity for training embryologists in clinics is limited; and legally, the term ‘embryologist’ is not defined or protected. One embryologist mentioned their involvement in training as a key source of personal satisfaction and motivation: (I) encourage independent evidence based-scientific thinking and life-competencies. So that interns carry on a philosophy of strong self-worth, develop their own capabilities, based on experiences and knowledge where to get answers if in doubt. Trainees in medical embryology are carefully selected. As one trainer noted, embryologists must be able to carefully handle the precious materials they are going to work with, and not everyone has this capacity. Our interviewees noted that approximately 15 applicants apply annually in South Africa to be trained in medical embryology, usually coming from biological science backgrounds, but of these, only three are accepted due to the limited capacity to train more. The applicants have to spend a day in a lab to watch the realities of the work involved. The embryologists and medical scientists with whom they work during that day will then score the applicant on a number of qualities, before the applicant is invited for an interview. At the interview, we were informed that their motivation for training and the work is an important topic. Once trained, most embryologists are in such demand that they are lost to public health systems and usually find work in the private sector. Several experienced embryologists in our sample had emigrated for further training opportunities and experience and also, in some cases, to permanently live and work overseas. As a result, across SSA, clinics complained about the difficulties in attracting and retaining embryologists and other medical science staff. While working in the IVF laboratory – performing laboratory technical tasks – may be thought of as the embryologists’ primary task, in our study, all embryologists combined various forms of work beyond what is usually considered their conventional ‘role’. This is partly due to the context in which they work. Our exploration of the work of embryologists highlights the importance of context in shaping their practices, interactions and expectations. The shortage of embryologists, the lack of ‘corporate’ multi-centre IVF clinics in South Africa and the region (as may be the case in the US), the paucity or lack of trained counsellors in clinics, the mobilities in IVF staff and patients characteristic in the region and the need to set up ‘first’ clinics in many countries all mean that embryologists’ work extends beyond the technical. Within SSA, their roles often involve tasks beyond what might be expected of an embryologist in a laboratory in the US or Europe. The shortage of embryologists, other clinical staff and counsellors affects practices in SSA clinics, and accordingly, embryologists we interviewed undertook entrepreneurial tasks, advocacy, training, development of regulations and mentoring and patient counselling, on top of laboratory work. Clearly, this varied with the size of the clinic and its stage of development (for example, fundraising was only done by embryologists initiating a clinic). This combination of tasks makes for a dynamic and fulfilling career for those we interviewed but also stretches their capacities. It raises the question of whether their deployment across this range of tasks contributes to the scarcity of embryologists in SSA. We conceive of the work of embryologists as forms of care-work and suggest that care is enacted (and experienced) in IVF clinics through the sum of tasks, technologies, patients and other staff, which together enact care. This not only suggests the importance of care as a fundamental outcome of the work of all staff and technologies but also suggests the importance of the context, expectations and reception of care. This is a different approach to the traditional view of care in IVF clinics, which tends to view it as part of a job description of a particular staff member and assumes that quality care follows their actions alone. Our approach breaks down divisions between ‘technical’ and ‘clinical’ staff and recognizes the various ways in which care is enacted: towards gametes and embryos, clinics and technologies, the profession, patients and, in SSA, the broader goals of providing access to infertility treatment to patients who need IVF. The embryologists we interviewed were all involved in various forms of emotional labour and care with patients; they took pride in this and saw this as part of ensuring quality patient care . We were initially surprised by this, and this also contrasted with the experience of one embryologist who had worked in the US, where they had no contact with patients. Embryologists we interviewed saw themselves not only as technically adroit but also as responsible for creating families. They found that patient contact motivated their careful handling of the ‘precious’ human reproductive materials with which they worked. However, some of the interviewed embryologists are undertaking tasks, such as counselling or donor selection, for which they are not necessarily trained (although it should be mentioned that one of the interviewees combined specializations – in embryology and psychology – which justified this combination of roles). IVF clinics are strongly recommended to follow internationally accepted guidelines for IVF counselling and the use of donor material and donor selection, as provided by ESHRE and other professional organizations, which include the training of specialists in these fields ( https://www.eshre.eu/Guidelines-and-Legal ). In the Global North, the changing work of embryologists is a subject under discussion. This has been prompted by the advent of automated AI and microfluidics, which will change the technical roles of the embryologist away from manual manipulation and towards more data capture, management and analysis . However, in other ways, our study suggests that the caring role of embryologists with the advent of new technologies may be increased, requiring vigilance over AI decisions and increased need for informed communication with patients. Recognition of the deep engagement of embryologists in enacting care and contributing to successful IVF in their clinics is essential. In Global South countries such as those in SSA, the context in which embryology is practised poses differing challenges. Given the shortage of embryologists in SSA, their deployment across a range of tasks contributes to the scarcity of embryological work. In SSA countries, access to affordable and effective IVF is required, and there is a pressing need to train more embryologists to cater to the growing need for and use of medically assisted reproductive technologies. Furthermore, models and technologies of low-cost IVF all require the human resources of trained embryologists to ensure quality care and efficacy. If access to IVF is to be achieved in the region, then more embryologists need to be trained and retained. A major limitation of this study is that only 11 embryologists who are or have been working in SSA have been interviewed, not covering all SSA countries where IVF clinics exist. However, as this study/article is intended to explore the variety of embryologists’ roles and the various forms of enactment of care – and not intending to make generalizations and/or judgements about the functioning of the embryologists in these clinics – this is not considered to be a major problem. The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the work reported. This work was supported by the Australian government through an Australian Research Council https://doi.org/10.13039/501100000923 Discovery Project Grant (DP 200101270). TG and AW conceived the study, conducted the interviews, analysed and interpreted the data and authored the article. LM analysed and interpreted the data and co-authored and edited the article. |
Metabolomic profiles in serum uncover novel biomarkers in children with Williams–Beuren syndrome | 44290ed1-f6e0-4e7e-98be-5a0ac3b9cdeb | 11923248 | Biochemistry[mh] | Williams–Beuren syndrome (WBS, OMIM-194050) is a rare genetic disorder characterized by multisystemic manifestations resulting from a heterozygous loss of contiguous 26–28 genes on chromosome 7, typically occurring de novo . The prevalence of WBS is approximately 1:7500 live births . Individuals with WBS exhibit distinctive facial dysmorphisms, cardiovascular anomalies, growth retardation, mild-to-moderate intellectual disability, and a heightened sociability. Patients with WBS also frequently experience medical problems in the gastrointestinal tract and urinary system, such as feeding difficulties, inguinal hernia, diarrhea, and hypercalciuria. Cardiovascular risk factors, including hypertension, impaired glucose tolerance, hyperlipidemia, and high intima-media thickness, are commonly observed in children with Williams syndrome, contributing to an increased likelihood of developing cardiovascular diseases in adulthood . These manifestations necessitate ongoing management and are currently a primary focus of clinical care. The pathophysiology of WBS beyond developmental issues in the cardiovascular and neurological systems remains poorly understood, yet it plays a critical role in the manifestation of clinical phenotypes and treatment of WBS. Individuals with WBS frequently experience endocrine and metabolic complications such as disrupted glucose metabolism and diabetes, elevated cholesterol levels and obesity, thyroid dysfunction, hypercalcemia, and premature onset of puberty. Metabolic disturbances are implicated in the manifestation of functional declines, including cognitive impairment and increased risk of cardiovascular disease, which is a leading cause of mortality in individuals with WBS , . The prevalence of metabolic disturbances in WBS is notable, with reports of mild thyroid hypoplasia in around 70% of children and impaired glucose tolerance in up to 75% of adults . Additionally, hyperbilirubinemia is observed in 18.3% of WBS patients and is linked to subclinical hypotriglyceridemia and hypothyroidism . Metabolism and endocrine characteristics play a significant role in the pathophysiology of developmental issues associated with WBS. Nevertheless, there is a scarcity of information regarding the metabolomic profiles of children with WBS. Examination of metabolomic disruptions in WBS may offer insights into the etiology of the disease and the evolution of clinical phenotypes, as well as aid in disease monitoring and treatment. The objective of this study was to analyze the global metabolomic changes and associated metabolic pathways in individuals with WBS using untargeted serum metabolomics profiling via Ultra Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS/MS) within a case–control framework.
Study population We recruited 25 children diagnosed with WBS who visited the Department of Child Health Care in Children’s Hospital, Zhejiang University School of Medicine between January 2020 to May 2023. Eligibility criteria were as follows: age under 18 years; and with the presence of microdeletion at 7q11.23 of the genome or the presence of clinical symptoms according to the Lowery score . Patients with insufficient medical information regarding pregnancy and birth, or clinical records were excluded from the study, as were patients with elastin (ELN) deletion only, and patients whose legal representatives did not give informed consent. The diagnosis of WBS was confirmed by genetic testing, either fluorescence in situ hybridization (FISH) or chromosomal microarray, in 21/25 subjects; the diagnosis was clinically established by experienced senior clinicians in the remaining subjects , . One-to-one age and sex matched healthy controls (N = 25) were matched from the Health Management Center in the same hospital. The study was approved by the Ethics Committee of the Children’s Hospital of Zhejiang University School of Medicine (No. 2019-IRB-122). All legal representatives of the participants in the present analysis provided written informed consent for participation. The study was conducted in accordance with the Helsinki Declaration. Assessment of WBS-related phenotypes Anthropometric measurements were measured by trained staff. Detailed WBS-related phenotypes, medical history questionnaire, maternal prenatal history, and genetic test results were retrieved from medical records . The guardians of WBS children were interviewed for information on demographics and family history. Metabolomics profiling Sample preparation Participants arrived in the morning after an 8-h fast and underwent blood sampling. Serum samples were stored at − 80 °C. Before seqnencing, samples were thawed at 4 °C and vortex-mixed. 100 μL aliquot of each serum sample was mixed with 400 μL methanol. The mixture was vortex-mixed and centrifuged at 12,000 rpm for 10 min at 4 °C. The supernatant was transferred and evaporated to dryness using a centrifugal vacuum evaporator. The dried sample was dissolved in 150 μL methanol–water (80: 20, v/v) containing internal standard (2-chlorol-phenylalanine, 4 ppm) and then was filtered by 0.22 µm membrane and transferred to a vial for UPLC-MS analysis. The quality control (QC) samples were prepared by mixing 20 μL of each sample supernatant and following the same steps. UPLC-MS/MS methodology Untargeted serum metabolomics were profiled with a UPLC-MS/MS system consisting of a Vanquish UPLC System (Thermo Fisher Scientific, USA) coupled with Q Exactive HF-X mass spectrometer (Thermo Fisher Scientific, USA), and operated in positive and negative polarity modes. Samples were injected 2 μL into a UPLC BEH Amide column (2.1 mm × 100 mm, 1.7 μm). In ESI positive ion mode (ESI+), the mobile phase was consisted of eluent A (0.1% formic acid in water) and eluent B (0.1% formic acid in acetonitrile). In ESI negative ion mode (ESI-), the mobile phases were consisted of eluent A (5 mM ammonium formate in water) and eluent B (acetonitrile). Simultaneous MS1 and MS/MS (Full MS-ddMS2 mode, data-dependent MS/MS) acquisition were used. The raw data were firstly converted to mzXML format by MSConvert in ProteoWizard software package (v3.0.8789) and processed using XCMS for feature detection, retention time correction and alignment. The metabolites were identified by accuracy mass (< 30 ppm) and MS/MS data which were matched with HMDB ( http://www.hmdb.ca ), massbank ( http://www.massbank.jp ), LipidMaps ( http://www.lipidmaps.org ), mzcloud ( https://www.mzcloud.org ) and KEGG ( http://www.genome.jp/kegg ) – . The robust LOESS signal correction (QC-RLSC) was applied for data normalization to correct for any systematic bias. After normalization, only ion peaks with relative standard deviations (RSDs) less than 30% in QC were kept to ensure proper metabolite identification. Quality control QC samples were plotted together with samples on the PCA plot based on level one metabolome (Supplementary Figure ). Closely clustered QC samples indicate good repeatability. Concentrations have to be reported for more than 25% of the samples, otherwise, the metabolite is excluded from the statistical evaluation. Statistical analysis Data were expressed as mean ± standard deviation (SD) or median and interquartile range (IQE). T-test or Mann–Whitney U test were used to compare the two groups for normally distributed or non-normally distributed variables, respectively. Chi-square test was performed to compare count variables between groups. A two-sided p value < 0.05 was considered statistically significant. All analyses were conducted using R Studio (version 4.1.2). Z-scores of metabolites were calculated and used in analyses. Multivariable analysis was performed to evaluate the overall difference of metabolome between WBS and controls. Metabolomics data underwent scaling by adaptive conversion before multivariate analysis. Two different multivariate statistical analysis models, unsupervised and supervised, were applied to discriminate the groups (PCA; PLS-DA; OPLS-DA) by R ropls (v1.22.0) package . Variable Importance in Projection (VIP) derived from the OPLS-DA model was used to describe the contribution of metabolites to the model which evaluates the influence and ability to distinguish the two groups. A VIP > 1 for the first principal component of the OPLS-DA model was considered meaningful for group differentiation. To identify characteristic metabolome features that differentiate WBS children from health controls, t-test was performed to identify differences in mean levels of ions or metabolites in WBS and controls. P value < 0.05 and VIP value > 1 were used to screen differentially abundant ions or metabolites. For the top differentially abundant metabolites, the ROC curve and AUC were computed using the predicted probabilities from the logistic regression model with group of participants (WBS or controls) as the outcome and the metabolites as the predictor. The pROC R package (version 1.18.5) was employed to generate the ROC curve and calculate the AUC. Model performance was assessed by comparing to a baseline classifier (AUC = 0.5). After scaling of metabolite matrix using pheatmap R package, heatmap was plotted with clustering for samples and differentially abundant metabolites. Spearman’s correlation coefficients were calculated and tested among metabolites that are differentially abundant in WBS compared to control groups. Correlations patterns were compared between the two groups. Differential metabolites were subjected to pathway analysis by MetaboAnalyst , which combines results from powerful pathway enrichment analysis with the pathway topology analysis. Enrichment analysis was based on the hypergeometric distribution test. Topological analysis based on pointwise centrality degree method was performed to assess whether a given gene or metabolite plays an important role in a biological response based on its position in the pathway. The identified metabolites in metabolomics were then mapped to the KEGG pathway for biological interpretation of higher-level systemic functions. The metabolites and corresponding pathways were visualized using the KEGG Mapper tool. The impact value and p values of pathways were visualized. The top influenced pathways and metabolites were visualized in the network plot. To identify potential metabolites relating to WBS phenotypes, the associations between differentially abundant metabolites and phenotypes were assessed in linear or logistic regression models adjusting for age and sex. Differentially abundant metabolites were compared to those reported for other diseases in MetaboAnalyst 5.0 as an exploration of shared molecular links and pathophysiology .
We recruited 25 children diagnosed with WBS who visited the Department of Child Health Care in Children’s Hospital, Zhejiang University School of Medicine between January 2020 to May 2023. Eligibility criteria were as follows: age under 18 years; and with the presence of microdeletion at 7q11.23 of the genome or the presence of clinical symptoms according to the Lowery score . Patients with insufficient medical information regarding pregnancy and birth, or clinical records were excluded from the study, as were patients with elastin (ELN) deletion only, and patients whose legal representatives did not give informed consent. The diagnosis of WBS was confirmed by genetic testing, either fluorescence in situ hybridization (FISH) or chromosomal microarray, in 21/25 subjects; the diagnosis was clinically established by experienced senior clinicians in the remaining subjects , . One-to-one age and sex matched healthy controls (N = 25) were matched from the Health Management Center in the same hospital. The study was approved by the Ethics Committee of the Children’s Hospital of Zhejiang University School of Medicine (No. 2019-IRB-122). All legal representatives of the participants in the present analysis provided written informed consent for participation. The study was conducted in accordance with the Helsinki Declaration.
Anthropometric measurements were measured by trained staff. Detailed WBS-related phenotypes, medical history questionnaire, maternal prenatal history, and genetic test results were retrieved from medical records . The guardians of WBS children were interviewed for information on demographics and family history.
Sample preparation Participants arrived in the morning after an 8-h fast and underwent blood sampling. Serum samples were stored at − 80 °C. Before seqnencing, samples were thawed at 4 °C and vortex-mixed. 100 μL aliquot of each serum sample was mixed with 400 μL methanol. The mixture was vortex-mixed and centrifuged at 12,000 rpm for 10 min at 4 °C. The supernatant was transferred and evaporated to dryness using a centrifugal vacuum evaporator. The dried sample was dissolved in 150 μL methanol–water (80: 20, v/v) containing internal standard (2-chlorol-phenylalanine, 4 ppm) and then was filtered by 0.22 µm membrane and transferred to a vial for UPLC-MS analysis. The quality control (QC) samples were prepared by mixing 20 μL of each sample supernatant and following the same steps. UPLC-MS/MS methodology Untargeted serum metabolomics were profiled with a UPLC-MS/MS system consisting of a Vanquish UPLC System (Thermo Fisher Scientific, USA) coupled with Q Exactive HF-X mass spectrometer (Thermo Fisher Scientific, USA), and operated in positive and negative polarity modes. Samples were injected 2 μL into a UPLC BEH Amide column (2.1 mm × 100 mm, 1.7 μm). In ESI positive ion mode (ESI+), the mobile phase was consisted of eluent A (0.1% formic acid in water) and eluent B (0.1% formic acid in acetonitrile). In ESI negative ion mode (ESI-), the mobile phases were consisted of eluent A (5 mM ammonium formate in water) and eluent B (acetonitrile). Simultaneous MS1 and MS/MS (Full MS-ddMS2 mode, data-dependent MS/MS) acquisition were used. The raw data were firstly converted to mzXML format by MSConvert in ProteoWizard software package (v3.0.8789) and processed using XCMS for feature detection, retention time correction and alignment. The metabolites were identified by accuracy mass (< 30 ppm) and MS/MS data which were matched with HMDB ( http://www.hmdb.ca ), massbank ( http://www.massbank.jp ), LipidMaps ( http://www.lipidmaps.org ), mzcloud ( https://www.mzcloud.org ) and KEGG ( http://www.genome.jp/kegg ) – . The robust LOESS signal correction (QC-RLSC) was applied for data normalization to correct for any systematic bias. After normalization, only ion peaks with relative standard deviations (RSDs) less than 30% in QC were kept to ensure proper metabolite identification. Quality control QC samples were plotted together with samples on the PCA plot based on level one metabolome (Supplementary Figure ). Closely clustered QC samples indicate good repeatability. Concentrations have to be reported for more than 25% of the samples, otherwise, the metabolite is excluded from the statistical evaluation.
Participants arrived in the morning after an 8-h fast and underwent blood sampling. Serum samples were stored at − 80 °C. Before seqnencing, samples were thawed at 4 °C and vortex-mixed. 100 μL aliquot of each serum sample was mixed with 400 μL methanol. The mixture was vortex-mixed and centrifuged at 12,000 rpm for 10 min at 4 °C. The supernatant was transferred and evaporated to dryness using a centrifugal vacuum evaporator. The dried sample was dissolved in 150 μL methanol–water (80: 20, v/v) containing internal standard (2-chlorol-phenylalanine, 4 ppm) and then was filtered by 0.22 µm membrane and transferred to a vial for UPLC-MS analysis. The quality control (QC) samples were prepared by mixing 20 μL of each sample supernatant and following the same steps.
Untargeted serum metabolomics were profiled with a UPLC-MS/MS system consisting of a Vanquish UPLC System (Thermo Fisher Scientific, USA) coupled with Q Exactive HF-X mass spectrometer (Thermo Fisher Scientific, USA), and operated in positive and negative polarity modes. Samples were injected 2 μL into a UPLC BEH Amide column (2.1 mm × 100 mm, 1.7 μm). In ESI positive ion mode (ESI+), the mobile phase was consisted of eluent A (0.1% formic acid in water) and eluent B (0.1% formic acid in acetonitrile). In ESI negative ion mode (ESI-), the mobile phases were consisted of eluent A (5 mM ammonium formate in water) and eluent B (acetonitrile). Simultaneous MS1 and MS/MS (Full MS-ddMS2 mode, data-dependent MS/MS) acquisition were used. The raw data were firstly converted to mzXML format by MSConvert in ProteoWizard software package (v3.0.8789) and processed using XCMS for feature detection, retention time correction and alignment. The metabolites were identified by accuracy mass (< 30 ppm) and MS/MS data which were matched with HMDB ( http://www.hmdb.ca ), massbank ( http://www.massbank.jp ), LipidMaps ( http://www.lipidmaps.org ), mzcloud ( https://www.mzcloud.org ) and KEGG ( http://www.genome.jp/kegg ) – . The robust LOESS signal correction (QC-RLSC) was applied for data normalization to correct for any systematic bias. After normalization, only ion peaks with relative standard deviations (RSDs) less than 30% in QC were kept to ensure proper metabolite identification.
QC samples were plotted together with samples on the PCA plot based on level one metabolome (Supplementary Figure ). Closely clustered QC samples indicate good repeatability. Concentrations have to be reported for more than 25% of the samples, otherwise, the metabolite is excluded from the statistical evaluation.
Data were expressed as mean ± standard deviation (SD) or median and interquartile range (IQE). T-test or Mann–Whitney U test were used to compare the two groups for normally distributed or non-normally distributed variables, respectively. Chi-square test was performed to compare count variables between groups. A two-sided p value < 0.05 was considered statistically significant. All analyses were conducted using R Studio (version 4.1.2). Z-scores of metabolites were calculated and used in analyses. Multivariable analysis was performed to evaluate the overall difference of metabolome between WBS and controls. Metabolomics data underwent scaling by adaptive conversion before multivariate analysis. Two different multivariate statistical analysis models, unsupervised and supervised, were applied to discriminate the groups (PCA; PLS-DA; OPLS-DA) by R ropls (v1.22.0) package . Variable Importance in Projection (VIP) derived from the OPLS-DA model was used to describe the contribution of metabolites to the model which evaluates the influence and ability to distinguish the two groups. A VIP > 1 for the first principal component of the OPLS-DA model was considered meaningful for group differentiation. To identify characteristic metabolome features that differentiate WBS children from health controls, t-test was performed to identify differences in mean levels of ions or metabolites in WBS and controls. P value < 0.05 and VIP value > 1 were used to screen differentially abundant ions or metabolites. For the top differentially abundant metabolites, the ROC curve and AUC were computed using the predicted probabilities from the logistic regression model with group of participants (WBS or controls) as the outcome and the metabolites as the predictor. The pROC R package (version 1.18.5) was employed to generate the ROC curve and calculate the AUC. Model performance was assessed by comparing to a baseline classifier (AUC = 0.5). After scaling of metabolite matrix using pheatmap R package, heatmap was plotted with clustering for samples and differentially abundant metabolites. Spearman’s correlation coefficients were calculated and tested among metabolites that are differentially abundant in WBS compared to control groups. Correlations patterns were compared between the two groups. Differential metabolites were subjected to pathway analysis by MetaboAnalyst , which combines results from powerful pathway enrichment analysis with the pathway topology analysis. Enrichment analysis was based on the hypergeometric distribution test. Topological analysis based on pointwise centrality degree method was performed to assess whether a given gene or metabolite plays an important role in a biological response based on its position in the pathway. The identified metabolites in metabolomics were then mapped to the KEGG pathway for biological interpretation of higher-level systemic functions. The metabolites and corresponding pathways were visualized using the KEGG Mapper tool. The impact value and p values of pathways were visualized. The top influenced pathways and metabolites were visualized in the network plot. To identify potential metabolites relating to WBS phenotypes, the associations between differentially abundant metabolites and phenotypes were assessed in linear or logistic regression models adjusting for age and sex. Differentially abundant metabolites were compared to those reported for other diseases in MetaboAnalyst 5.0 as an exploration of shared molecular links and pathophysiology .
Descriptives of patients and controls A total of 25 children diagnosed with WBS were included in the current study. The mean age was 5.0 years (SD: 2.6 years), ranging from 1.1 to 10.4 years old. 40% were female. Table presents the general and clinical characteristics of the WBS children. Of them, 22 (88%) children experienced developmental delay, 23 (92%) had congenital heart disease, and 18 (72%) had indirect inguinal hernia. Supravalvular aortic stenosis and peripheral pulmonic stenosis were also prevalent in 20 (80%) and 18 (72%) children, respectively. UPLC-MS detected 20,600 signals in positive ion mode and 12,775 in negative ion mode. A total of 465 metabolites were assigned putatively by matching retention time and available tandem MS information with reference databases. These metabolites belong mainly to carboxylic acids and derivatives, fatty acyls, benzene, and substituted derivatives, steroids and steroid derivatives, and organooxygen compounds. Metabolite difference between WBS patients and healthy controls Multivariate analysis of serum metabolomics Hierarchical clustering in the heatmap of ion signals reveals a clear separation between WBS cohort and controls. Group-specific patterns of signals are also present among participants of the two groups (Supplementary Figure ). Children with WBS and controls clustered distinctly in the OPLS-DA plot, with individuals of each group clustering closely (Fig. ) along PC1. Volcano plot showed that the levels of a large panel of metabolic signals in WBS differed significantly from controls (p < 0.05, Fig. C). Differentially abundant analysis Among the 20,600 signals detected by LC–MS in positive ion mode, 7111 were differentially abundant (5229 elevated and 1882 decreased) in WBS compared to controls ( p < 0.05, VIP > 1.0). In negative ion mode, 4093 out of 12,775 signals were different in WBS compared to controls (2177 elevated and 1916 decreased). A total of 169 putative metabolites were differentially abundant in WBS patients compared to the controls ( P < 0.05 and VIP > 1), with 105 increased and 64 decreased (Supplementary Table ). Table list the top differentially abundant metabolites with a FC > 2 or < 0.5 and a VIP > 1. Differentially abundant metabolites are visualized in Fig. A Heatmap of differentially abundant metabolites in children with WBS and controls; (B) OPLS-DA plot of differentially abundant metabolites in the two groups; (C) Volcano plot shows fold changes and p-values of significantly different metabolites between groups). The groups of metabolites altered in WBS included organic acids, glucogenic amino acids, bile acids and among others. As depicted in the heatmap, the top 10 metabolites with concentrations in WBS less than 50% of controls (FC ≤ 0.5) were 5-hydroxyindoleacetic acid, 9,10-dihydroxystearate, deoxyribose 5-phosphate, trimethoprim, indole glycerol phosphate, quadrone, 17a-estradiol, arachidic acid, lithocholic acid, and docosahexaenoic acid. The top 10 metabolites with concentrations more than 2 folds in WBS (FC ≥ 2) were palmitoleic acid, taurocholic acid, l -kynurenine, adenosine 5′-phosphate disodium, mannitol, homogentisate, creatinine, thymidine, (R)-4-hydroxymandelate, gentisic acid. Among these metabolites, palmitoleic acid, 17a-estradiol, deoxyribose 5-phosphate, l -kynurenine, indole glycerol phosphate, adenosine 5′-phosphate disodium, taurocholic acid, 9,10-dihydroxystearate, and gentisic acid had a VIP > 2 from OPLS-DA in distinguishing WBS children and the controls. We also provided the receiver operating characteristic (ROC) curves and area under the curve (AUC) for these metabolites in Supplementary Figures and . The major classes of differentially abundant metabolites include carboxylic acids and derivatives, benzene and substituted derivatives, fatty acyls, organooxygen compounds, and steroids and steroid derivatives. Figure depicts the classes of differentially abundant metabolites and Fig. shows distributions of top differentially abundant metabolites in WBS children. KEGG pathway enrichment analysis The differentially abundant metabolites were mapped to KEGG pathways. Significantly ( p < 0.05) enriched pathways include (ranging from large to small p -value) nicotine addiction, cholesterol metabolism, arginine biosynthesis, retrograde endocannabinoid signaling, ovarian steroidogenesis, cocaine addiction, phenylalanine metabolism, histidine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, central carbon metabolism in cancer, protein digestion and absorption, aminoacyl-tRNA biosynthesis, neuroactive ligand–receptor interaction, ABC transporters, glycine, serine and threonine metabolism (Table ). Some of the suggestive ( p < 0.1 but p > 0.05) enriched pathways include glutamatergic synapse, GABAergic synapse, linoleic acid metabolism, cerebellar long-term depression, taurine and hypotaurine metabolism, primary bile acid biosynthesis, mineral absorption, pentose phosphate pathway. Supplementary Table shows the full list of pathway enrichment analysis results. Enriched KEGG pathways and their respective disturbed metabolites in WBS were visualized together in the network visualization plot (Fig. ), revealing a centered place of altered levels of amino acids among enriched metabolic pathways, especially a decreased l -isoleucine and l -histidine, an elevated l -glutamic acid, l -glutamine, l -aspartic acid, l -phenylalanine, and l -threonine, connecting multiple enriched pathways. The disturbance of selected KEGG pathways is visualized in Supplementary Figure . Correlation between differentially abundant metabolites Many of the differentially abundant metabolites were intercorrelated and the correlation pattern in WBS was disrupted as compared to controls (Supplementary Figure , correlation plots for differentially abundant metabolites in controls (A) and WBS children (B)). In WBS children, for instance, 17-hydroxyprogesterone, 13E-11a-hydroxy-9,15-dioxoprost-13-enoic acid, pergolide, and sphingosine-1-phosphate, became positively correlated with multiple metabolites. N -acetylserotonin was inversely correlated with several metabolites in WBS instead of being positively correlated in controls. Metabolites phenotype associations To investigate if circulating metabolites were related to phenotypes of WBS, we regressed the 465 metabolites over 25 phenotypes after adjusting for age and sex. A total of 222 associations from 125 metabolites were identified ( p < 0.05), but no association survived FDR multiple testing correction. An overview of the presence of WBS-related phenotypes in WBS children is visualized in the heatmap (Supplementary Figure ). Metabolites associated with the phenotypes are listed in Supplementary Table . Short stature, gene deletion size, indirect inguinal hernia, a history of neonatal jaundice, and PPS were associated with most metabolite alterations. Larger gene deletion sizes were in general associated with lower levels of several metabolites. Higher levels of trimethoprim, ergothioneine, salicyluric acid, and lower taurine were associated with hypercalcemia. Lower anhalamine, mannitol, l -glutamine, tryptophanol, creatine, propionylcarnitine, isopyridoxal, cortisone, carbosulfan, aspartame, indole-3-acetate, 4-quinolinecarboxylic acid, and higher indoleglycerol phosphate, kyotorphin, pelargonic acid, acetylcholine, beta-leucine were associated with larger head circumference. However, birth weight, birth height, pregnancy week, SGA, SVAS, and SVPS did not show much correlation. For exploring purpose, we checked in the MetaboAnalyst Online platform the similarity of differentially abundant metabolites with those reported for other diseases. The enriched metabolite sets share a higher similarity with those reported for dicarboxylic aminoaciduria, nicotinamide adenine dinucleotide deficiency, celiac disease, galactosemia type 1, schizophrenia, Alzheimer’s disease, autism, etc. Further, we explored the enriched KEGG pathways of metabolites associated with gene deletion sizes and short stature (Supplementary Figure ).
A total of 25 children diagnosed with WBS were included in the current study. The mean age was 5.0 years (SD: 2.6 years), ranging from 1.1 to 10.4 years old. 40% were female. Table presents the general and clinical characteristics of the WBS children. Of them, 22 (88%) children experienced developmental delay, 23 (92%) had congenital heart disease, and 18 (72%) had indirect inguinal hernia. Supravalvular aortic stenosis and peripheral pulmonic stenosis were also prevalent in 20 (80%) and 18 (72%) children, respectively. UPLC-MS detected 20,600 signals in positive ion mode and 12,775 in negative ion mode. A total of 465 metabolites were assigned putatively by matching retention time and available tandem MS information with reference databases. These metabolites belong mainly to carboxylic acids and derivatives, fatty acyls, benzene, and substituted derivatives, steroids and steroid derivatives, and organooxygen compounds.
Multivariate analysis of serum metabolomics Hierarchical clustering in the heatmap of ion signals reveals a clear separation between WBS cohort and controls. Group-specific patterns of signals are also present among participants of the two groups (Supplementary Figure ). Children with WBS and controls clustered distinctly in the OPLS-DA plot, with individuals of each group clustering closely (Fig. ) along PC1. Volcano plot showed that the levels of a large panel of metabolic signals in WBS differed significantly from controls (p < 0.05, Fig. C). Differentially abundant analysis Among the 20,600 signals detected by LC–MS in positive ion mode, 7111 were differentially abundant (5229 elevated and 1882 decreased) in WBS compared to controls ( p < 0.05, VIP > 1.0). In negative ion mode, 4093 out of 12,775 signals were different in WBS compared to controls (2177 elevated and 1916 decreased). A total of 169 putative metabolites were differentially abundant in WBS patients compared to the controls ( P < 0.05 and VIP > 1), with 105 increased and 64 decreased (Supplementary Table ). Table list the top differentially abundant metabolites with a FC > 2 or < 0.5 and a VIP > 1. Differentially abundant metabolites are visualized in Fig. A Heatmap of differentially abundant metabolites in children with WBS and controls; (B) OPLS-DA plot of differentially abundant metabolites in the two groups; (C) Volcano plot shows fold changes and p-values of significantly different metabolites between groups). The groups of metabolites altered in WBS included organic acids, glucogenic amino acids, bile acids and among others. As depicted in the heatmap, the top 10 metabolites with concentrations in WBS less than 50% of controls (FC ≤ 0.5) were 5-hydroxyindoleacetic acid, 9,10-dihydroxystearate, deoxyribose 5-phosphate, trimethoprim, indole glycerol phosphate, quadrone, 17a-estradiol, arachidic acid, lithocholic acid, and docosahexaenoic acid. The top 10 metabolites with concentrations more than 2 folds in WBS (FC ≥ 2) were palmitoleic acid, taurocholic acid, l -kynurenine, adenosine 5′-phosphate disodium, mannitol, homogentisate, creatinine, thymidine, (R)-4-hydroxymandelate, gentisic acid. Among these metabolites, palmitoleic acid, 17a-estradiol, deoxyribose 5-phosphate, l -kynurenine, indole glycerol phosphate, adenosine 5′-phosphate disodium, taurocholic acid, 9,10-dihydroxystearate, and gentisic acid had a VIP > 2 from OPLS-DA in distinguishing WBS children and the controls. We also provided the receiver operating characteristic (ROC) curves and area under the curve (AUC) for these metabolites in Supplementary Figures and . The major classes of differentially abundant metabolites include carboxylic acids and derivatives, benzene and substituted derivatives, fatty acyls, organooxygen compounds, and steroids and steroid derivatives. Figure depicts the classes of differentially abundant metabolites and Fig. shows distributions of top differentially abundant metabolites in WBS children.
Hierarchical clustering in the heatmap of ion signals reveals a clear separation between WBS cohort and controls. Group-specific patterns of signals are also present among participants of the two groups (Supplementary Figure ). Children with WBS and controls clustered distinctly in the OPLS-DA plot, with individuals of each group clustering closely (Fig. ) along PC1. Volcano plot showed that the levels of a large panel of metabolic signals in WBS differed significantly from controls (p < 0.05, Fig. C).
Among the 20,600 signals detected by LC–MS in positive ion mode, 7111 were differentially abundant (5229 elevated and 1882 decreased) in WBS compared to controls ( p < 0.05, VIP > 1.0). In negative ion mode, 4093 out of 12,775 signals were different in WBS compared to controls (2177 elevated and 1916 decreased). A total of 169 putative metabolites were differentially abundant in WBS patients compared to the controls ( P < 0.05 and VIP > 1), with 105 increased and 64 decreased (Supplementary Table ). Table list the top differentially abundant metabolites with a FC > 2 or < 0.5 and a VIP > 1. Differentially abundant metabolites are visualized in Fig. A Heatmap of differentially abundant metabolites in children with WBS and controls; (B) OPLS-DA plot of differentially abundant metabolites in the two groups; (C) Volcano plot shows fold changes and p-values of significantly different metabolites between groups). The groups of metabolites altered in WBS included organic acids, glucogenic amino acids, bile acids and among others. As depicted in the heatmap, the top 10 metabolites with concentrations in WBS less than 50% of controls (FC ≤ 0.5) were 5-hydroxyindoleacetic acid, 9,10-dihydroxystearate, deoxyribose 5-phosphate, trimethoprim, indole glycerol phosphate, quadrone, 17a-estradiol, arachidic acid, lithocholic acid, and docosahexaenoic acid. The top 10 metabolites with concentrations more than 2 folds in WBS (FC ≥ 2) were palmitoleic acid, taurocholic acid, l -kynurenine, adenosine 5′-phosphate disodium, mannitol, homogentisate, creatinine, thymidine, (R)-4-hydroxymandelate, gentisic acid. Among these metabolites, palmitoleic acid, 17a-estradiol, deoxyribose 5-phosphate, l -kynurenine, indole glycerol phosphate, adenosine 5′-phosphate disodium, taurocholic acid, 9,10-dihydroxystearate, and gentisic acid had a VIP > 2 from OPLS-DA in distinguishing WBS children and the controls. We also provided the receiver operating characteristic (ROC) curves and area under the curve (AUC) for these metabolites in Supplementary Figures and . The major classes of differentially abundant metabolites include carboxylic acids and derivatives, benzene and substituted derivatives, fatty acyls, organooxygen compounds, and steroids and steroid derivatives. Figure depicts the classes of differentially abundant metabolites and Fig. shows distributions of top differentially abundant metabolites in WBS children.
The differentially abundant metabolites were mapped to KEGG pathways. Significantly ( p < 0.05) enriched pathways include (ranging from large to small p -value) nicotine addiction, cholesterol metabolism, arginine biosynthesis, retrograde endocannabinoid signaling, ovarian steroidogenesis, cocaine addiction, phenylalanine metabolism, histidine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, central carbon metabolism in cancer, protein digestion and absorption, aminoacyl-tRNA biosynthesis, neuroactive ligand–receptor interaction, ABC transporters, glycine, serine and threonine metabolism (Table ). Some of the suggestive ( p < 0.1 but p > 0.05) enriched pathways include glutamatergic synapse, GABAergic synapse, linoleic acid metabolism, cerebellar long-term depression, taurine and hypotaurine metabolism, primary bile acid biosynthesis, mineral absorption, pentose phosphate pathway. Supplementary Table shows the full list of pathway enrichment analysis results. Enriched KEGG pathways and their respective disturbed metabolites in WBS were visualized together in the network visualization plot (Fig. ), revealing a centered place of altered levels of amino acids among enriched metabolic pathways, especially a decreased l -isoleucine and l -histidine, an elevated l -glutamic acid, l -glutamine, l -aspartic acid, l -phenylalanine, and l -threonine, connecting multiple enriched pathways. The disturbance of selected KEGG pathways is visualized in Supplementary Figure .
Many of the differentially abundant metabolites were intercorrelated and the correlation pattern in WBS was disrupted as compared to controls (Supplementary Figure , correlation plots for differentially abundant metabolites in controls (A) and WBS children (B)). In WBS children, for instance, 17-hydroxyprogesterone, 13E-11a-hydroxy-9,15-dioxoprost-13-enoic acid, pergolide, and sphingosine-1-phosphate, became positively correlated with multiple metabolites. N -acetylserotonin was inversely correlated with several metabolites in WBS instead of being positively correlated in controls.
To investigate if circulating metabolites were related to phenotypes of WBS, we regressed the 465 metabolites over 25 phenotypes after adjusting for age and sex. A total of 222 associations from 125 metabolites were identified ( p < 0.05), but no association survived FDR multiple testing correction. An overview of the presence of WBS-related phenotypes in WBS children is visualized in the heatmap (Supplementary Figure ). Metabolites associated with the phenotypes are listed in Supplementary Table . Short stature, gene deletion size, indirect inguinal hernia, a history of neonatal jaundice, and PPS were associated with most metabolite alterations. Larger gene deletion sizes were in general associated with lower levels of several metabolites. Higher levels of trimethoprim, ergothioneine, salicyluric acid, and lower taurine were associated with hypercalcemia. Lower anhalamine, mannitol, l -glutamine, tryptophanol, creatine, propionylcarnitine, isopyridoxal, cortisone, carbosulfan, aspartame, indole-3-acetate, 4-quinolinecarboxylic acid, and higher indoleglycerol phosphate, kyotorphin, pelargonic acid, acetylcholine, beta-leucine were associated with larger head circumference. However, birth weight, birth height, pregnancy week, SGA, SVAS, and SVPS did not show much correlation. For exploring purpose, we checked in the MetaboAnalyst Online platform the similarity of differentially abundant metabolites with those reported for other diseases. The enriched metabolite sets share a higher similarity with those reported for dicarboxylic aminoaciduria, nicotinamide adenine dinucleotide deficiency, celiac disease, galactosemia type 1, schizophrenia, Alzheimer’s disease, autism, etc. Further, we explored the enriched KEGG pathways of metabolites associated with gene deletion sizes and short stature (Supplementary Figure ).
Through the utilization of a comprehensive, untargeted metabolomics methodology, the present investigation demonstrated a distinct differentiation in the circulating metabolome between individuals with WBS and healthy individuals. A total of 465 compounds were characterized based on their retention time and tandem mass spectrometry data, with 169 exhibiting differential abundance in individuals with WBS. The perturbed metabolites were found to be enriched in various pathways associated with crucial neurological functions, including retrograde endocannabinoid signaling, phenylalanine metabolism, nicotine and cocaine addiction, and bile acids metabolism. These findings suggest potential implications for the pathophysiological alterations observed in individuals with WBS. In our analysis, a significant number of metabolites and their correlations were found to be disrupted in children with WBS compared to healthy controls. Despite being measured in blood, many of these disturbed metabolites were associated with the metabolism of neurotransmitters. Specifically, shared metabolites for these pathways included L-glutamic acid, l -glutamine, l -phenylalanine, l -aspartic acid, l -threonine, l -histidine, and l -isoleucine. These findings not only suggest potential underlying pathophysiological mechanisms but also present new opportunities for disease management. For instance, we detected disruptions in N , N -dimethylglycine and d -glycerate levels, which were linked to decreased phosphoserine phosphatase activity in a patient with Williams–Beuren syndrome. Supplementation with serine and glycine was found to be advantageous in this case . 5-Hydroxyindoleacetic acid (5-HIAA), the main metabolite of serotonin, was among the top decreased metabolites among WBS children. Lower urinary or circulating 5-HIAA was found in depression, migraines, and autism spectrum disorders previously and low cerebral spinal fluid (CSF) levels were associated with anxiety and aggression and were found in WBS . The primary source of circulating serotonin is the intestine, with additional synthesis occurring in the brain from L-tryptophan. This neurotransmitter plays a crucial role in modulating various physiological processes including learning, memory, sleep, mood, attention, fear and appetite regulation, , as well as gastrointestinal motility and vasoconstriction. Decreased levels of serotonin have been associated with conditions such as depression, anxiety, obsessive–compulsive disorder, sleep disturbances, and gastrointestinal issues. , . The dysregulation of serotonin synaptic activities in the brain has been implicated in both WBS and autism, as evidenced by mouse models . Consistent with our findings, a decrease in serotonergic axon density has been observed in postmortem brains of individuals with WBS compared to neurotypical brains . Serotonin metabolism has been suggested to play a role in the social phenotypes of WBS and peripheral arterial stenosis . Additionally, a decreased density of serotonin transporter, responsible for removing serotonin from the synaptic cleft to the presynaptic terminal, has been observed in the amygdala of infants with WBS . Consistent with this finding, adjusting serotonin levels may be advantageous in addressing neurological symptoms, as indicated by the effectiveness of selective serotonin reuptake inhibitors in individuals with WBS . Our study further supports the potential utility of medications that target the serotonin system, such as antidepressants, anxiolytics, and antiemetics, in managing psychiatric symptoms in individuals with WBS . In contrast, mouse models of WBS exhibited elevated levels of serotonin metabolite 5-HIAA and increased 5-HT1A currents in various brain regions, which are known to influence anxiety-like behaviors , . The potential disparity between peripheral and cerebral serotonin metabolite levels requires further investigation, but these findings underscore the dysregulation of serotonin metabolism in the neurological aspects of WBS. In addition to its known functions, serotonin may also impact glucose metabolism , and contribute to vascular abnormalities in WBS . In individuals with WBS, levels of the neurotoxic metabolite l -kynurenine, derived from l -tryptophan, were found to be significantly elevated compared to serotonin levels . This suggests a deviation in tryptophan metabolism from serotonin towards the kynurenine pathway, which has been associated with neurodegenerative disorders . This metabolic shift may be influenced by oxidative stress and inflammation, and has been linked to the development of type 2 diabetes , cardiovascular diseases, cognitive deficits, and depression , . Psychological stressors, as well as kynurenine itself, have the potential to activate the aryl hydrocarbon receptor and stimulate the production of kynurenine . These findings suggest that restoring equilibrium in tryptophan metabolism, particularly in the serotonin and l -kynurenine pathways, could be advantageous in addressing mood disorders associated with WBS. Increased levels of l -glutamic acid and arachidic acid, as well as decreased levels of trehalose 6-phosphate and 2-arachidonoylglycerol, were enriched in the retrograde endocannabinoid signaling pathway, which has been implicated in Williams syndrome . The endocannabinoid system is integral to various physiological processes, including brain development, anxiety regulation, stress response, pain perception, memory formation, appetite control, digestion, sleep regulation, inflammation modulation, and cardiovascular health , . Elevated levels of endogenous cannabinoids have been associated with anxiety disorders, which may contribute to the heightened prevalence of anxiety in individuals with WBS. Modulation of the cannabinoid pathway in WBS mouse models has shown promising results in enhancing social and cognitive behaviors, as well as improving cardiovascular function . A higher level of arachidic acid, a polyunsaturated fatty acid, was linked to inflammation , but it also supports the performance of brain function . The alteration of metabolites we observed in WBS may contribute to anxiety and other cognitive and cardiovascular issues in WBS, suggesting potential treatment avenues. The taurocholic acid level of WBS children was eight times higher than that of controls. Other derivatives of primary bile acid metabolism including taurine, and glycocholic acid were also elevated, indicating active bile acid biosynthesis in WBS. Circulating bile acids are considered mediators linking the gut, liver, and brain, and have been linked to Pakinson’s disease related depression , Alzheimer’s disease , , diabetes, obesity , and liver injury , . Taurine plays an important role in modulating calcium homeostasis and vitamin D absorption , and is relevant for cardiac disease , and bone health . In line with this, a lower taurine level was associated with hypercalcemia in our WBS cohort. Additionally, the gut microbiota plays a role in the synthesis of secondary bile acids, and the composition of the microbiota can be influenced by the host’s bile acid metabolism . For example, individuals with irritable bowel disease have been found to exhibit elevated levels of fecal primary bile acids, which are positively associated with symptoms, while levels of secondary bile acids are reduced . In our investigation, we observed a decrease in the secondary bile acid lithocholic acid in WBS. This dysregulation in bile acid metabolism may contribute to the common gastrointestinal symptoms experienced by WBS patients . This is further supported by a recent study which documented reduced taurine and hypotaurine metabolism through analysis of gut microbiota proteome . Additionally, while biliary hypoplasia, a factor in bile acid transfer, was not previously recognized as a characteristic of WBS, it has been documented in a patient with neonatal cholestatic jaundice . Given the high incidence of cholestatic jaundice in our WBS cohort, vigilant monitoring of biliary development is warranted. Variations in additional metabolites may also serve as indicators of the pathophysiological mechanisms underlying WBS. Specifically, children with WBS exhibited notably elevated levels of creatinine, suggesting an increased susceptibility to chronic kidney disease . Furthermore, heightened levels of sphingosine-1-phosphate, a key modulator of vascular and immune functions, were observed. The increase in palmitoleic acid levels may be indicative of enhanced hepatic lipogenesis. Metabolites associated with steroid hormone biosynthesis exhibit variations between the groups, indicating potential phenotypic implications such as precocious puberty warranting consideration in WBS . The elevated presence of N-acetylglucosamine may serve as a compensatory mechanism by inhibiting elastase activity, a notable feature in WBS attributed to the deletion of the elastin gene. The metabolic profile of individuals with WBS was compared to that of individuals with other diseases. Similarities were identified with celiac disease, which has a co-occurrence rate of over 4% with WBS , . Additionally, similarities were noted with schizophrenia, Alzheimer’s disease, and autism, as alterations in neurotransmitters were found to be shared among these conditions, supported by gene expression data . Future research could explore common molecular pathways that contribute to the phenotypes of these conditions. Furthermore, metabolites, which are downstream of pathological changes, may be influenced by genetic variations or alterations in gut microbial metabolic activities. Till now, no genes deleted in WBS were directly linked to metabolic processes, and future studies are warranted to uncover underlying genetic architecture. The WBS gut microbiota was revealed to show altered microbial metabolism implicated in our study, such as alanine, aspartate, and glutamate metabolism . The strengths of our study lie in the untargeted metabolome profiling of individuals with WBS and healthy controls, which revealed metabolites from diverse families and pathways not previously examined in the context of WBS. Furthermore, the study predominantly focused on young children with WBS, enabling the identification of metabolic alterations during early developmental stages. The results illuminate metabolomic changes that may be advantageous for the management and early intervention of WBS, as well as enhance comprehension of the molecular underpinnings of neuro-endocrinological symptoms, which may have greater significance for neurological development in comparison to adults. There are several limitations inherent in the present study. The present study is subject to limitations regarding sample size, with 25 participants per group and a predominantly male composition. While we implemented age and gender matching between the WBS group and healthy controls to mitigate selection bias, the restricted sample size may limit the generalizability of findings, particularly regarding gender-specific effects. This sample size determination aligns with exploratory research paradigms in rare disease studies, yet future investigations would benefit from expanded cohorts incorporating more balanced gender representation and diverse demographic characteristics to enhance statistical power and external validity. Furthermore, in order to explore the relationship and causality among metabolite disturbances, phenotypes, and genotypes, a larger study sample size with a longitudinal design would be necessary. However, increasing the sample size for a rare disease may present challenges. The extent to which serum metabolome measures accurately reflect metabolic status in the central nervous system and other tissues remains inadequately elucidated. Further research is necessary to determine the potential relationship between these biochemical alterations and physiological functions, particularly within the central nervous system. Additionally, the current methodology was unable to ascertain the absolute metabolite concentration, thus hindering the interpretation against normal ranges. Moreover, the influence of dietary factors and gut microbial metabolic activities, which could impact circulating metabolites, were not considered in the present study. Last but not the least, we had to acknowledge that certain metabolites may not be exclusively specific to WBS patients. Urinary organic acid analysis indicates that patients with other inborn metabolic defects (e.g., amino acid metabolism disorders or fatty acid oxidation abnormalities) may excrete similar metabolites. For instance, elevated specific organic acids in urine are also observed in methylmalonic acidemia and propionic acidemia patients, which may overlap with the metabolic profile of WBS. To enhance the identification of disease-specific biomarkers, we recommend genetic testing (e.g., verification of chromosome 7q11.23 deletion) or targeted metabolomic analysis.
In conclusion, our research has identified unique metabolomic profiles in children with Williams–Beuren syndrome compared to healthy controls, even at a young age. These findings suggest significant subclinical metabolic changes that may have implications for neuroendocrinological development. These alterations appear to be associated with imbalances in metabolite production and consumption, potentially stemming from dysregulation of key enzymes. However, further investigation is needed to fully elucidate the underlying regulatory mechanisms. Future studies with larger sample sizes and long-term follow-ups can determine if metabolite differences can predict the onset of related symptoms for early intervention.
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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Comprehensive use of cardiopulmonary exercise testing in pediatrics | fed26e63-caff-415b-8bca-d54cb127c365 | 10227478 | Pediatrics[mh] | The cardiopulmonary exercise test (CPET) allows the possibility to appoint the pathophysiological limitations of exercise and also the significance of functional impairment. It began to be use as a “gold standard” to evaluate the result of surgical, medical and rehabilitative treatment on cardiopulmonary function and to investigate the integrated physiological reactions to exercise in paediatric medicine. It is widely use in paediatric patients and adults and significantly improved the understanding of cardiopulmonary development in children and adolescents . A large number of research tools are used in clinical practice to assess physical fitness. These tools have a lot of advantages and disadvantages . Cardiopulmonary exercise test has become an chief clinical non-invasive tool to assess and predict the capacity of exercise in patients with heart failure and in different cardiac conditions. It supplies estimation of the exercise responses, affecting the cardiovascular, pulmonary, skeletal muscle, metabolism and the cellular system, which are not well reflected in individual organ systems by measuring function . Cardiopulmonary exercise test carry physiological parameters at rest and during progressive exercise. It determines the ability to produce energy at metabolically relevant time points as anaerobic threshold and the body’s cardiorespiratory fitness . Resting pulmonary and cardiac function cannot reliably estimate physical performance and functional capacity . Energetic human capacity is the most significant factor that sets the limits of physical capacity . The cardiopulmonary exercise test allows to assess body’s response during sub and maximal exercise. Mainly measurements include gas exchange parameters such as: oxygen consumption, carbon dioxide production, minute ventilation, ECG monitoring, blood pressure and pulse oximetry . In the latest years of CPET exploitation, the test has been appreciably identified by medical interest and as a physiological bases of different variables, which were before unknown and by accentuation proof for a multivariable approach. Most of problems with ventilation and its control were taken into consideration . An obstacle in performing the CPET test was mostly described as the financial barrier. Hospitals and institutions trying to initiate the action mentioned lack of funding as the most common reason for not being able to test .
We performed a literature search at Google Scholar, PubMed, Science Direct, available literature from the book from 2006 to 2019 and internet sources. The bibliography search was reviewed and performed using selected keywords. This study is based on analysis of literature about cardiopulmonary exercise test and cardiorespiratory fitness.
Physical effort requires coordinated actions of physiological mechanisms related to the functioning of the nervous system, circulatory system, respiratory system and internal function to cover the escalated energy demand of working muscles . Features which condition physical performance are: efficiency of aerobic muscle supply and activation of biochemical processes determining the use of oxygen energy sources, removal of catabolite, efficiency of thermoregulation and size and efficiency of energy substrates use. Considering on the subject about efficiency, we can not forget about the tolerance of fatigue changes during CPET test, which it can affect: aversion to effort or fear of effort. It can also occur pain, dyspnoea, palpitation, or excessive sweating . In the study of children and adolescents, we must also consider the race of subjects. Studies conducted on Caucasian race in the United Kingdom have shown that, English children have higher cardiovascular fitness than Indian children . Social, religious, linguistic and cultural traditions exclude involvement in physical activity, therefore their ability and approach to sport or recreation may be different from other children . The surveys on male and female have shown that in swimmers of age from 9 to 20 years from West Bengal, had importantly lower than norm value of VO 2max , than international athletes, which practiced endurance type of sport, however they had significantly higher VO 2max parameter than sedentary girls of West Bengal . Cardiorespiratory fitness, is a solid parameter to estimate the capacity of the cardiovascular system to overcome extended physical work. It has been depicted to be the most dominant predictor of death rate and morbidity, besides of classical cardiovascular disease, risk factors such as cholesterol, smoking cigarettes, hypertension, and diabetes mellitus type 1 (T1DM) and diabetes mellitus type 2 (T2DM) . In recent years, studies have documented the health benefits of regular physical activity. Nowadays it is highly appreciated that higher cardiorespiratory fitness and physical activity standards are beneficial for the diseases prophylaxis and prevention . Physical activity is essential for human health in every period of life, and it gains special value during the time of the fastest and most intense development, i.e. childhood . It has a positive effect on dealing with civilization diseases such as diabetes type 2 (T2DM), improves bone health, reduces the incidence of cancer, reduces signs of disability and extends life . Cardiopulmonary exercise test variables The aim of spirometry is the continuous survey of respiration (spirography) and respiratory gas metabolism . The tests are performed on a treadmill, cycle-ergometer or outdoor. Portable Ergospirometers are very often used to study physiological ventilation variables in field tests . There are 2 basic types of ergospirometers. The first one is an ergospirometer with a mixing chamber. The principle of its operation, is that during breathing, samples of exhaled gas are taken and collected in a reservoir (chamber), where they are mixed. The size of a single sample is proportional to the current tidal volume (VT). In every constant period of time, measurements are made of the gas composition in the chamber, which is a mixture of taken samples. Measurements of average O 2 and CO 2 concentrations are obtained, e.g. another set of measurement data every 10 seconds. The action of the second one is based on continuous sampling of breathing air with a constant gas sample volume. In this method, measurements of O 2 and CO 2 concentrations require the use of fast gas analysers, usually with a response time of less than 120 ms. In addition, synchronization of the flow, O 2 and CO 2 concentrations is required due to delays in the sample drain and in the gas sensor itself. Measurements of temporary O 2 and CO 2 concentrations, are obtained after each breath. The advantage of the “breath-by-breath” type ergospirometers compared to devices with a mixing chamber is the high accuracy of the measurement regardless of changing environmental conditions, because the concentration of O 2 and CO 2 is measured both during the inspiration and exhalation phases . The major results are schedule in the following order: maximal oxygen uptake (VO2max/peak), carbon dioxide emission (VCO 2 ), ventilatory threshold (VT), minute ventilation (VE), ventilatory equivalents for oxygen (VE/VO 2 ) and carbon dioxide (VE/VCO 2 ), respiratory exchange ratio (RER/R, VCO 2 /VO 2 ), heart rate (HR), saturation (SatO 2 ), ECG, blood pressure (BP) The most important parameter examined in the assessment of physical fitness is VO 2max , which we describe as the maximum integrated capacity of the pulmonary system, cardiovascular system and muscular system to uptake, transport and utilize O 2 . Through the value of the oxygen uptake kinetic reaction its survey is complex by the large “inter-breath” change in oxygen uptake in children during the test. It cuts the reliance in which kinetic variables can be asses and necessitates the measurement of variety identic transitions . VO2peak is highest speed attained at the end of the test . Ventilatory threshold is described as a the level at which, sudden growth in blood lactate is noticed. Output of lactic acid in the muscle rise curvilinear with increasing work load . We also pay attention to the carbon dioxide that it is the sum of exhaled CO 2 by a examined patient is an act of the substrate and metabolic rate utilized in oxidative metabolism. The sum of exhaled CO 2 by a examined patient is an act of the substrate and metabolic rate utilized in oxidative metabolism. The amount of carbo-dioxide exhaled in oxidative metabolism for each litre of oxygen consumed is named (RER/R) the respiratory exchange ratio . This parameter nearing to 0.7 if the dominant fuel is fat to 1.0 if the prevalent fuel is carbohydrate. During dynamic exercise, the heart rate (HR) increases in order to respond to higher oxygen demand. It is accompanied by an increase in the stroke volume of the heart, which reaches its maximum value already at 30–50% VO 2max . Enhanced work of the heart causes an augmentation in blood flow mainly in working skeletal muscles, heart and skin at the expense of a decrease in flow through the kidneys, liver and visceral organs. During physical effort, the body increases its oxygen demand, so the lung ventilation process potentiates. After beginning of training, there is an increase in VE (minute ventilation), the breathing cycle speeds up and gets deeper. The rapid increase in VE lasts a few seconds after initiation of activity, then this trend slows down until it reaches a level of stabilization. The transition phase occurs when you stop exercising operations. In the case of intense effort, the VE value enhance constantly, the steady state phase does not occur. During low intensity exercise, VE increases proportionally to VO 2 until it reaches 50–75% VO 2max . Parameters related to cardiopulmonary exercise test were divided into this, which characterize circulatory system, lung ventilation, metabolic changes and those which are enters into gas exchange in the lungs . Contraindications and savouireship Each patient should receive instructions and basic information on how the laboratory equipment works and what the test procedure consists of. The patient should avoid eating meals, smoking cigarettes and drinking alcohol at least 2 hours before the test. Patient should wear comfortable clothing and footwear. It should also be also follow the history of medications and perform resting supine ECG to identify individual for whom the test could be contraindicated or should be performed with special safety features . The basis that we can modify is the protocol with increasing linear load. It is able to choose Ramp or stepwise protocol. During the measurement process, the child should achieve a constant speed of 60 to 80 rpm. The load is gradually increased, depending on the chosen linear protocol. It is set to 1 W/1 kg of body weight as the basic load and increase the resistance every 10 seconds by 1 W. The load is heightened by increasing the resistance of the cycle-ergometer pedals. After reaching the desired parameters or when indicators to stop the examination appear, the doctor or paramedic decides to finish the survey. The test can also be interrupted at any time at the patient’s request or when disturbing symptoms appear. After the effort, a rest phase follows, then the patient is disconnected from the device and the electrodes are peeled off and discarded. The duration of the test lasts from 30 to 60 minutes . We increase the effort load to: Obtain the maximum rhythm frequency (220-age), occurrence of symptoms indicating need to end the test (maximum stress test limited by symptoms), achieving 85% of the maximum frequency rhythm (submaximal exercise test) . Absolute contraindications and exclusion criteria for children and adolescents are described in detail by American Heart Association (AHA). We can include among them: disagreement of person being examined/guardian, severe respiratory failure, congestive heart failure, active rheumatic fever with carditis, significant aortic stenosis, significant mitral valve stenosis, uncontrolled cardiac arrhythmias causing clinical symptoms or disadvantaging hemodynamics, severe arterial hypertension (systolic pressure & gt: 200 mm Hg and/or diastolic pressure & gt: 120 mm Hg), hypertrophic cardiomyopathy with former cases of collapse, diabetic children hypoglycaemia, hypoglycaemia above 250 mg/dl, severe disorders of other organs which may impact on the course of the effort or increase under their influence (e.g. infection, kidney failure, thyrotoxicosis), lower extremity phlebitis, physical disability which may prevent to perform safe and adequate test, mental disability preventing cooperation . However, some children, adolescents and adults noticed discomfort with the mouthpiece, facemask, or with nose clip. Consequently, all these inconvenience, should be reported before starting the CPET test. They serve to show the need for versatile initial patient assessment, and precise monitoring during the survey . Cardiopulmonary exercise test should be interpreted and controlled by a consultant with an experience in conducting the cardiopulmonary exercise testing. Furthermore, the individual performing the CPET test should be experienced in working on cardiopulmonary tests like also interpreting the outcomes . However, despite their precision and reproducibility, cardiopulmonary exercise testing physicians (cardiologists, pulmonologists, and physiologists) must be well trained to avoid misinterpretation pitfalls and above all, highly experienced in clinical practice and pathological conditions .
The aim of spirometry is the continuous survey of respiration (spirography) and respiratory gas metabolism . The tests are performed on a treadmill, cycle-ergometer or outdoor. Portable Ergospirometers are very often used to study physiological ventilation variables in field tests . There are 2 basic types of ergospirometers. The first one is an ergospirometer with a mixing chamber. The principle of its operation, is that during breathing, samples of exhaled gas are taken and collected in a reservoir (chamber), where they are mixed. The size of a single sample is proportional to the current tidal volume (VT). In every constant period of time, measurements are made of the gas composition in the chamber, which is a mixture of taken samples. Measurements of average O 2 and CO 2 concentrations are obtained, e.g. another set of measurement data every 10 seconds. The action of the second one is based on continuous sampling of breathing air with a constant gas sample volume. In this method, measurements of O 2 and CO 2 concentrations require the use of fast gas analysers, usually with a response time of less than 120 ms. In addition, synchronization of the flow, O 2 and CO 2 concentrations is required due to delays in the sample drain and in the gas sensor itself. Measurements of temporary O 2 and CO 2 concentrations, are obtained after each breath. The advantage of the “breath-by-breath” type ergospirometers compared to devices with a mixing chamber is the high accuracy of the measurement regardless of changing environmental conditions, because the concentration of O 2 and CO 2 is measured both during the inspiration and exhalation phases . The major results are schedule in the following order: maximal oxygen uptake (VO2max/peak), carbon dioxide emission (VCO 2 ), ventilatory threshold (VT), minute ventilation (VE), ventilatory equivalents for oxygen (VE/VO 2 ) and carbon dioxide (VE/VCO 2 ), respiratory exchange ratio (RER/R, VCO 2 /VO 2 ), heart rate (HR), saturation (SatO 2 ), ECG, blood pressure (BP) The most important parameter examined in the assessment of physical fitness is VO 2max , which we describe as the maximum integrated capacity of the pulmonary system, cardiovascular system and muscular system to uptake, transport and utilize O 2 . Through the value of the oxygen uptake kinetic reaction its survey is complex by the large “inter-breath” change in oxygen uptake in children during the test. It cuts the reliance in which kinetic variables can be asses and necessitates the measurement of variety identic transitions . VO2peak is highest speed attained at the end of the test . Ventilatory threshold is described as a the level at which, sudden growth in blood lactate is noticed. Output of lactic acid in the muscle rise curvilinear with increasing work load . We also pay attention to the carbon dioxide that it is the sum of exhaled CO 2 by a examined patient is an act of the substrate and metabolic rate utilized in oxidative metabolism. The sum of exhaled CO 2 by a examined patient is an act of the substrate and metabolic rate utilized in oxidative metabolism. The amount of carbo-dioxide exhaled in oxidative metabolism for each litre of oxygen consumed is named (RER/R) the respiratory exchange ratio . This parameter nearing to 0.7 if the dominant fuel is fat to 1.0 if the prevalent fuel is carbohydrate. During dynamic exercise, the heart rate (HR) increases in order to respond to higher oxygen demand. It is accompanied by an increase in the stroke volume of the heart, which reaches its maximum value already at 30–50% VO 2max . Enhanced work of the heart causes an augmentation in blood flow mainly in working skeletal muscles, heart and skin at the expense of a decrease in flow through the kidneys, liver and visceral organs. During physical effort, the body increases its oxygen demand, so the lung ventilation process potentiates. After beginning of training, there is an increase in VE (minute ventilation), the breathing cycle speeds up and gets deeper. The rapid increase in VE lasts a few seconds after initiation of activity, then this trend slows down until it reaches a level of stabilization. The transition phase occurs when you stop exercising operations. In the case of intense effort, the VE value enhance constantly, the steady state phase does not occur. During low intensity exercise, VE increases proportionally to VO 2 until it reaches 50–75% VO 2max . Parameters related to cardiopulmonary exercise test were divided into this, which characterize circulatory system, lung ventilation, metabolic changes and those which are enters into gas exchange in the lungs .
Each patient should receive instructions and basic information on how the laboratory equipment works and what the test procedure consists of. The patient should avoid eating meals, smoking cigarettes and drinking alcohol at least 2 hours before the test. Patient should wear comfortable clothing and footwear. It should also be also follow the history of medications and perform resting supine ECG to identify individual for whom the test could be contraindicated or should be performed with special safety features . The basis that we can modify is the protocol with increasing linear load. It is able to choose Ramp or stepwise protocol. During the measurement process, the child should achieve a constant speed of 60 to 80 rpm. The load is gradually increased, depending on the chosen linear protocol. It is set to 1 W/1 kg of body weight as the basic load and increase the resistance every 10 seconds by 1 W. The load is heightened by increasing the resistance of the cycle-ergometer pedals. After reaching the desired parameters or when indicators to stop the examination appear, the doctor or paramedic decides to finish the survey. The test can also be interrupted at any time at the patient’s request or when disturbing symptoms appear. After the effort, a rest phase follows, then the patient is disconnected from the device and the electrodes are peeled off and discarded. The duration of the test lasts from 30 to 60 minutes . We increase the effort load to: Obtain the maximum rhythm frequency (220-age), occurrence of symptoms indicating need to end the test (maximum stress test limited by symptoms), achieving 85% of the maximum frequency rhythm (submaximal exercise test) . Absolute contraindications and exclusion criteria for children and adolescents are described in detail by American Heart Association (AHA). We can include among them: disagreement of person being examined/guardian, severe respiratory failure, congestive heart failure, active rheumatic fever with carditis, significant aortic stenosis, significant mitral valve stenosis, uncontrolled cardiac arrhythmias causing clinical symptoms or disadvantaging hemodynamics, severe arterial hypertension (systolic pressure & gt: 200 mm Hg and/or diastolic pressure & gt: 120 mm Hg), hypertrophic cardiomyopathy with former cases of collapse, diabetic children hypoglycaemia, hypoglycaemia above 250 mg/dl, severe disorders of other organs which may impact on the course of the effort or increase under their influence (e.g. infection, kidney failure, thyrotoxicosis), lower extremity phlebitis, physical disability which may prevent to perform safe and adequate test, mental disability preventing cooperation . However, some children, adolescents and adults noticed discomfort with the mouthpiece, facemask, or with nose clip. Consequently, all these inconvenience, should be reported before starting the CPET test. They serve to show the need for versatile initial patient assessment, and precise monitoring during the survey . Cardiopulmonary exercise test should be interpreted and controlled by a consultant with an experience in conducting the cardiopulmonary exercise testing. Furthermore, the individual performing the CPET test should be experienced in working on cardiopulmonary tests like also interpreting the outcomes . However, despite their precision and reproducibility, cardiopulmonary exercise testing physicians (cardiologists, pulmonologists, and physiologists) must be well trained to avoid misinterpretation pitfalls and above all, highly experienced in clinical practice and pathological conditions .
Cardiopulmonary exercise test in clinical praxis is very useful and has potential indication for use in assessing the functional capacity of young people with moderate to severe valvular defects to evaluate for possible surgical intervention and to determine whether early fatigue is due to defect or deconditioning . Cardiopulmonary exercise test contains estimation of tolerance and intolerance during exercise, rating of patients with cardiovascular like: (heart failure, transplantation, cardiac rehabilitation, and exercise individualization) and respiratory diseases as: (chronic obstructive pulmonary disease (COPD), cystic fibrosis, interstitial lung diseases, pulmonary vascular disease and exercise-induced bronchospasm) and different clinical applicabilities like exercise rehabilitation, preoperative risk evaluation and exercise prescription to overall health improvement . The cardiopulmonary exercise test with survey of metabolic parameters, such as peak myocardial oxygen consumption and also exercise ventilation, may help in the clinical assessment of hypertrophic cardiomyopathy (HCM) patients in their functional capacity . Measurements of gas exchange are taking place more and more often in sports medicine. . It is a useful tool for assessing limitations during daily activities, that have a physiological basis on individual with chronic organ failure Cardiopulmonary exercise test is one of the most important diagnostic methods used in cardiology and sports medicine. Measurements, including gas exchange parameters during exercise, are characterized by a high prognostic value in patients not only with heart failure, but also with respiratory diseases . It would seems that it is impossible to perform a test on people with mucoviscoidosis. With the right approach and load dosing, Urquhart and Vendrusculo conducted a study on a group of 4 children from the age of 14 to 15. The measurement of performance and efficiency in cooperation with the musculoskeletal system and the cardiovascular system provided by CPET test adds more information to individualize exercise programmes for patients with highest risk suffering on cystic fibrosis . Also in patients with chronic obstructive pulmonary disease (COPD), VO2max/peak is the best indicator of aerobic fitness, as long as patients are able to exercise more than their limits . In studies conducted by Hunt et al . cardiorespiratory fitness on children was measured by FitnessGram assessment protocol. This is a good comparative method to the cardiopulmo-nary exercise test, because of the cost and the possibility of conducting it in the field. FitnesGram is usually use to estimate cardiorespiratory fitness and improve health and physical activity in children and adolescents .
Measurement of expiratory gas exchange during the test, physical activity is a repeatable and objective method, which enables accurate measurement of functional capacity. In this way, it is possible to detect the causes of reduced tolerance of effort, to notice the severity of many diseases, to monitor the effects of treatment and rehabilitation, but also to confirm the complete health and ability to exercise intensively.
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Evaluating Whether Radiofrequency Irradiation Attenuated UV-B-Induced Skin Pigmentation by Increasing Melanosomal Autophagy and Decreasing Melanin Synthesis | a8a9533c-c95d-4121-90c5-306530ad7c36 | 8509725 | Anatomy[mh] | Melanin is a nitrogen-containing pigment made from the melanin precursor L-tyrosine and is deposited in melanosomes, which are subcellular lysosome-like organelles . Both keratinocytes and melanocytes are involved in melanogenesis in the skin: melanocytes produce the melanin and deliver it to the keratinocytes for skin protection . Human skin color is determined by the balance between melanin synthesis and degradation . Microenvironment alterations caused by ultraviolet (UV) radiation, free radicals, and inflammation change this balance, and such changes eventually result in either skin depigmentation or hyperpigmentation . Melanogenesis is initiated by UV via the melanocortin-1 receptor . By binding the α-melanocyte-stimulating hormone (α-MSH) to MC1R, the melanocyte-inducing transcription factor (MITF) is activated and increases tyrosinase, which is a rate-limiting enzyme of melanogenesis . Autophagy is a vital cellular catabolic system for maintaining tissue homeostasis that eliminates aggregated or misfolded proteins and dysfunctional organelles . Autophagy is also involved in melanosome degradation. Melanosomes are degraded by autophagy after being transferred from melanocytes to keratinocytes . Moreover, melanosomes accumulated in melanocytes due to disrupted transport are also degraded by autophagy . Solar UV upregulates the mammalian target of the rapamycin complex (mTORC), which inhibits unc-51-like autophagy-inhibiting kinase (ULK) 1 and decreases the complex formation of ULK1 with autophagy-related protein (ATG) 13 and the 200 kDa family-interacting protein (FIP200), thereby decreasing autophagy . The activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) as an upstream target of mTORC1 inhibits autophagy [ , , ]. Furthermore, the canonical NF-κB pathway is activated by pro-inflammatory pathways like the tumor necrosis factor (TNF) receptors, Toll-like receptors (TLR), and antigen receptors . TNF has been shown to induce NF-κB activation, thereby decreasing autophagy in various cancer cells such as Ewing’s sarcoma, breast, and leukemia cancer cell lines. Conversely, the downregulation of NF-κB reactivates the autophagy process . TLR4, an upstream target of NF-κB, is also known to dysregulate mTORC-dependent autophagy . UV-B increases the production of various inflammatory molecules such as interleukin (IL)-1α, IL-1β, IL-6, IL-8, and TNF-α in keratinocytes [ , , ]. UV-B-irradiated keratinocytes also secrete high-mobility group box 1 (HMGB1), which is a ligand of TLR4 . These proteins are associated with post-inflammatory hyperpigmentation, which results from the overproduction or irregular dispersion of melanin . Radiofrequency (RF) irradiation has been shown to decrease IL-6, IL-8, and HMGB1 expression in UV-B-irradiated keratinocytes , as well as the expressions of NF-κB, TNF-α, and TLR4 in the UV-B-irradiated animal model, thereby decreasing keratinocyte proliferation and pigment accumulation . RF could decrease skin pigmentation by modulating skin inflammation through the downregulation of various pro-inflammatory signals like NF-κB, TNF-α, and TLR4. It is well known that UV-B irradiation increases various inflammatory cytokines and increases NF-κB, which eventually decreases melanosomal autophagy and increases skin pigmentation. Even though it is known that RF could decrease skin pigmentation, research concerning the mechanism of how skin pigmentation could be decreased by RF has mainly been focused on modulating inflammation. We thought it could be possible that RF decreases skin pigmentation by decreasing skin inflammation, which eventually leads to an increase in melanosomal autophagy. We hypothesized that RF downregulates TNF-α and TLR4, thereby downregulating NF-κB, and decreasing mTOR expression to restore melanosomal autophagy. In this study, we investigated the effects of RF irradiation on autophagy and skin pigmentation in the UV-B radiation animal model.
2.1. RF Decreased the Expressions of TNFR, TLR4, and NF-κB First, we evaluated whether RF irradiation decreased the expressions of TNFR, TLR4, and NF-κB in the UV-B-irradiated human primary epidermal keratinocytes (HEKn cells). The expressions of TNFR, TLR4, and NF-κB were significantly increased by UV-B radiation in HEKn cells, whereas RF irradiation significantly decreased them at 24 h after RF irradiation ( A–D). Statistical differences of all factors among the control, UV-B, and UV-B/RF groups were compared at the end of the experiment (28 days after RF irradiation). The changes of all factors by time points after RF irradiation were evaluated at 1, 7, and 28 days after RF irradiation, since we wanted to evaluate how long the RF effect continued. The statistical difference among time points was also compared ( E). TNFR expression in UV-B-irradiated skin was significantly higher than those in the control and UV-B/RF groups. In the UV-B/RF group, TNFR expression was highest at 1 day after RF but decreased with time ( F,G). The expressions of TLR4 and NF-κb were significantly increased by UV-B irradiation and were significantly higher than those in the control and UV-B/RF groups. In the UV-B/RF group, the expressions of TLR4 and NF-κb were highest at 1 day after RF irradiation but decreased with time ( H–K). 2.2. RF Decreased mTOR Expression and Induced the Expression of Autophagy Initiation Factors in UV-B-Irradiated Skin The expression ratio of pmTOR to mTOR was significantly higher in the skins of the UV-B group than those in the control and UV-B/RF groups ( A,B). In the UV-B/RF group, the ratio of pmTOR to mTOR was highest at 1 day after RF but also decreased with time ( A–C). The expressions of autophagy initiation factors, such as FIP200, ULK1, ULK2, ATG13, and ATG101, were significantly lower in the UV-B group than in the control and UV-B/RF groups. In the UV-B/RF group, the expressions did not differ significantly among the time points after RF ( D–M). 2.3. RF Increased Melanosomal Autophagy and Degradation Beclin 1 expression was significantly lower in the UV-B 28 days group than those in the control 28 days and UV-B/RF 28 days groups. In the UV-B/RF group, the expression of Beclin 1 was highest at 1 day after RF ( A–C). The expression ratio of precursors of microtubule-associated protein light chain 3 (LC3)-like proteins to LC3-II in the UV-B group was significantly lower than that in the control 28 days group and the UV-B/RF 28 days group. In the UV-B/RF group, the expression ratio of LC3-I to LC3-II was highest at 1 day after RF ( A,D,E). Melanosomal degradation by autophagy was evaluated by counting the number of melanin-containing autophagosomes in the transmission electron microscopy (TEM). Melanin-containing autophagosomes were not observed in the control and UV-B-irradiated groups. Such autophagosomes observed from 1 day after RF irradiation disappeared at 28 days after RF irradiation. The number of melanin-containing autophagosomes was highest at 1 day after RF irradiation ( F,G). 2.4. RF Decreased Skin Pigmentation The areas of black spots in the skin of the UV-B group were significantly greater than those in the control and UV-B/RF groups 28 days after RF irradiation. In the UV-B/RF group, the areas of black spots were significantly largest at 1 day after RF ( A; upper panel, C). Fontana–Masson staining showed that melanin deposition in the UV-B group was significantly higher than those in the control and UV-B/RF groups. In the UV-B/RF group, melanin deposition was significantly highest at 1 day after RF ( A; lower panel, D,E). We also evaluated changes of melanin synthesis by RF with α-MSH-treated human epidermal melanocytes (HEMn) (F). The expression of MC1R and MITF were significantly increased by treating α-MSH, however those were significantly decreased by RF ( G,H). Melanin content that was evaluated with a melanin assay was significantly increased by treating α-MSH, however it was decreased by RF ( I). Images from TEM also showed that α-MSH increased melanin in the HEMn and melanin was decreased by RF ( J).
First, we evaluated whether RF irradiation decreased the expressions of TNFR, TLR4, and NF-κB in the UV-B-irradiated human primary epidermal keratinocytes (HEKn cells). The expressions of TNFR, TLR4, and NF-κB were significantly increased by UV-B radiation in HEKn cells, whereas RF irradiation significantly decreased them at 24 h after RF irradiation ( A–D). Statistical differences of all factors among the control, UV-B, and UV-B/RF groups were compared at the end of the experiment (28 days after RF irradiation). The changes of all factors by time points after RF irradiation were evaluated at 1, 7, and 28 days after RF irradiation, since we wanted to evaluate how long the RF effect continued. The statistical difference among time points was also compared ( E). TNFR expression in UV-B-irradiated skin was significantly higher than those in the control and UV-B/RF groups. In the UV-B/RF group, TNFR expression was highest at 1 day after RF but decreased with time ( F,G). The expressions of TLR4 and NF-κb were significantly increased by UV-B irradiation and were significantly higher than those in the control and UV-B/RF groups. In the UV-B/RF group, the expressions of TLR4 and NF-κb were highest at 1 day after RF irradiation but decreased with time ( H–K).
The expression ratio of pmTOR to mTOR was significantly higher in the skins of the UV-B group than those in the control and UV-B/RF groups ( A,B). In the UV-B/RF group, the ratio of pmTOR to mTOR was highest at 1 day after RF but also decreased with time ( A–C). The expressions of autophagy initiation factors, such as FIP200, ULK1, ULK2, ATG13, and ATG101, were significantly lower in the UV-B group than in the control and UV-B/RF groups. In the UV-B/RF group, the expressions did not differ significantly among the time points after RF ( D–M).
Beclin 1 expression was significantly lower in the UV-B 28 days group than those in the control 28 days and UV-B/RF 28 days groups. In the UV-B/RF group, the expression of Beclin 1 was highest at 1 day after RF ( A–C). The expression ratio of precursors of microtubule-associated protein light chain 3 (LC3)-like proteins to LC3-II in the UV-B group was significantly lower than that in the control 28 days group and the UV-B/RF 28 days group. In the UV-B/RF group, the expression ratio of LC3-I to LC3-II was highest at 1 day after RF ( A,D,E). Melanosomal degradation by autophagy was evaluated by counting the number of melanin-containing autophagosomes in the transmission electron microscopy (TEM). Melanin-containing autophagosomes were not observed in the control and UV-B-irradiated groups. Such autophagosomes observed from 1 day after RF irradiation disappeared at 28 days after RF irradiation. The number of melanin-containing autophagosomes was highest at 1 day after RF irradiation ( F,G).
The areas of black spots in the skin of the UV-B group were significantly greater than those in the control and UV-B/RF groups 28 days after RF irradiation. In the UV-B/RF group, the areas of black spots were significantly largest at 1 day after RF ( A; upper panel, C). Fontana–Masson staining showed that melanin deposition in the UV-B group was significantly higher than those in the control and UV-B/RF groups. In the UV-B/RF group, melanin deposition was significantly highest at 1 day after RF ( A; lower panel, D,E). We also evaluated changes of melanin synthesis by RF with α-MSH-treated human epidermal melanocytes (HEMn) (F). The expression of MC1R and MITF were significantly increased by treating α-MSH, however those were significantly decreased by RF ( G,H). Melanin content that was evaluated with a melanin assay was significantly increased by treating α-MSH, however it was decreased by RF ( I). Images from TEM also showed that α-MSH increased melanin in the HEMn and melanin was decreased by RF ( J).
Even though melanin protects the skin against UV radiation , excessive accumulation of melanin leads to hyperpigmentation-related disorders like melasma or freckles, which cause cosmetic problems . Autophagy helps determine skin color by modulating melanosome degradation in keratinocytes . Autophagic activity is related to the degree of skin pigmentation wherein keratinocytes in lighter skin are more able to degrading melanosomes than keratinocytes in darker skin . A previous study showed that LC3B expression and autophagy were more decreased in melanocytes of melasma lesions than in unaffected areas of the skin . NF-κB is activated by UV radiation . The expressions of TNF-α and TLR4 are also increased by UV radiation [ , , , ], both of which downregulate autophagy by activating NF-κB [ , , ]. In our study, we evaluated whether RF irradiation reduced skin pigmentation by restoring autophagy, which was decreased by UV-B radiation. We found that RF irradiation downregulated the expressions of TNFR, TLR4, and NF-κB, thereby increasing autophagic activity, an effect that was observed up to 28 days after RF irradiation. Autophagy is initiated by the generation of double membrane-bound autophagosomes. In the autophagic process, autophagosomes form autolysosomes by merging with lysosomes . Various stresses activate AMP-activated protein kinase (AMPK) and inhibit the mTOR, which consequently initiates autophagy by upregulating the FIP200, ULK 1, ATG13, and ATG101 . After the initiation of autophagy, phagophore nucleation follows, which involves various proteins like ATG6 (Beclin 1), ATG14, and vacuolar protein sorting-associated protein 15 (Vps15) . The next stage of nucleation is phagophore elongation. During elongation, precursors of LC3-like proteins are cleaved to produce LC3-II. By conjugation with phosphatidylethanolamine, the cytosolic form of LC-I becomes LC-II, which is an autophagosome-bound form . LC3-II enhances targeted degradation of aggregated proteins or injured cellular organelles by interacting with adaptor proteins, such as p62 . Thus, LC3-II is frequently used to measure autophagic flux . Various cellular stress signals lead to the activation of mTORC1, which is an upstream target of the autophagy core machinery and the inactivation of which initiates autophagy . mTORC1 inhibition activates ULK1/2 kinase activity, and then ULK1 and ULK2 phosphorylate ATG13 and FIP200, which are essential subunits of the ULK1/2 kinase complex [ , , ]. In our study, pmTOR expression was increased by UV-B radiation and conversely decreased by RF radiation. Our findings suggest that RF irradiation promotes autophagy by inactivating mTOR, which otherwise inhibits autophagy and autophagic flux. We also evaluated whether RF irradiation contributed to melanosome removal by autophagy on TEM and found that an increase in the melanin-containing autophagosomes was observed from 1 day to 7 days after RF irradiation. Melanin deposition in the skin was increased by UV-B but decreased by RF radiation. Increased skin melanin accumulation is resulted from decreased melanin removal and increased melanin synthesis. Thus, we also evaluated whether changes of melanin synthesis by RF might also involve decreasing melanogenesis, and which possible mechanism might decrease inflammatory signal pathways such as TNF by RF. For evaluating exact mechanisms for decreasing melanogenesis by RF, further study is needed. Various treatments have been suggested to reduce melanin accumulation, such as the use of hypopigmentation agents, which include tyrosinase inhibitors such as hydroquinone and arbutin, which block melanogenesis . However, such agents are not very effective and cause irritation . Natural products such as marliolide or ursolic acid have been found effective in reducing melanin deposition by increasing autophagy . These studies showed that increasing autophagic activity led to melanin degradation and thus decreased skin pigmentation. Our study showed that RF irradiation decreased skin pigmentation by increasing autophagy in skin in the UV-B-irradiated mouse model. RF irradiation decreased the expressions of TLR4 and TNFR, which in turn decreased mTOR activity, thereby increasing autophagic activity. Since we did not use knock-out animal models, it is hard to show which signal pathways were definitive ones to modulate autophagy by RF. To evaluate the exact mechanism of decreasing skin pigmentation by RF, future studies with knock-out animal models are needed. Moreover, this is a preclinical study which is too early to apply directly to humans. Nevertheless, our results showed RF leads to increased autophagy which is associated with reduced melanin accumulation in the animal model. Our findings suggest that RF irradiation is a promising method of decreasing skin pigmentation by modulating autophagy.
4.1. In Vitro Model and RF Irradiation Human primary epidermal keratinocytes (HEKn; American Type Culture Collection, ATCC, Manassas, VA, USA) were maintained with a keratinocyte growth kit (ATCC, Manassas, VA, USA). For establishing the in vitro model in HEKn, the cells were exposed to UV-B (200 mJ/cm 2 ) for 5 min, irradiated with RF (POTENZA, Jeisys Medical Inc., Seoul, Korea; 2 MHz, 10 W, 100 ms), and incubated for 24 h ( A). Human primary epidermal melanocytes (HEMn; ATCC, Manassas, VA, USA) were grown in Dermal Cell Basal Medium (ATCC, Manassas, VA, USA) with a melanocyte growth kit (ATCC, Manassas, VA, USA). For establishing the in vitro model in HEMn, the cells were treated with 200 nM α-MSH (Sigma Aldrich, St. Louis, MO, USA) and kept in an incubator at 37 °C in an atmosphere of 5% CO 2 for 24 h. Then, the cells were irradiated with RF, and incubated for 48 h ( F). 4.2. Measurement of Melanin Content in Cells To assess melanin content in HEMn, the cells were seeded at 1 × 10 4 cells/well in 96-well plates and incubated for 24 h. After applying α-MSH and RF, the cells were harvested by centrifugation at 12,000× g for 20 min and dissolved in 100 μL of 10% dimethyl sulfoxide (DMSO) and 1N NaOH solution for 20 min at 95 °C. Absorbance at 490 nm was measured with a microplate reader (Molecular Devices). 4.3. In Vivo Model and RF Irradiation Five-week-old male HRM-2 mice (20–25 g) were obtained from Central Lab Animal Inc. (Seoul, Korea) and cared to adapt for 2 weeks. The mice were housed in cages under a controlled temperature (23 °C) with a 12 h light/dark cycle and free access to food and water. After the adaptation period, the mice were randomly divided into five groups as follows: (1) control (no exposure to UV-B and no irradiated RF), (2) UV-B (exposure to UV-B at 200 mJ/cm 2 ), (3) UV-B/RF 1d (exposure to UV-B/irradiated RF; sampling proceeds 1 day after RF irradiation), (4) UV-B/RF 7d (exposure to UV-B/irradiated RF; sampling proceeds 7 days after RF irradiation), (5) UV-B/RF 28d (exposure to UV-B/irradiated RF; sampling proceeds 28 days after RF irradiation). The mice were exposed to UV-B for 5 min once every 2 days for 10 days and then for 5 min every day for the next 3 days (total of 13 days) . Subsequently, the mice were irradiated to RF (2 MHz, 10 W for 100 ms) and then exposed to UV-B every 2 days for 28 days. The skin tissues of mice were harvested after 1 day, 7 days and 28 days of RF irradiation ( E). This study was approved by the Center of Animal Care and Use ethical board of Gachon University (Approval Number LCDI-2020-0115) and executed in accordance with the Institutional Animal Care and Use Committee. 4.4. RF Irradiation System The irradiation system (POTENZA, Jeisys Medical Inc., Seoul, Korea) used for this study was a bipolar pulse-type electrode array radiofrequency device. An impedance matching system was used to determine the compensation value by automatically measuring impedance, and RF was applied using a 16 ea (4 × 4) needle tip. RF was administered at 2 MHz using pulse-type, bipolar, alternating current oscillations in the animal experiment. Single pulse-type bipolar RF devices were used in the animal experiment and comprised an on-time pulse duration of 100 ms at a power density of 10 W/pulse. The invasive microneedle for RF application had a length of 13.6 mm, a diameter of 250 mm, and a needle-to-needle distance of 1.3 mm, and irradiation and treatment were performed with a disposable tip of 10 mm × 10mm consisting of 16 electrodes. The tip was approved by NAMSA (Northwood, OH, USA) after biological compatibility testing. 4.5. Sample Preparation 4.5.1. Extraction of RNA and cDNA Synthesis The cells and frozen skin tissues were ground using liquid nitrogen and homogenized by the RNAiso Plus reagent (Takara, Shiga, Japan) according to the manufacturer’s instructions. The extracted RNA was quantified by the NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and was converted to cDNA using a PrimeScript 1 ST strand cDNA Synthesis Kit (Takara, Shiga, Japan) for quantitative real-time polymerase chain reaction (qRT-PCR). 4.5.2. Paraffin-Embedded Tissue Sectioning The skin tissues that were fixed by 4% paraformaldehyde (Sigma-Aldrich, St. Louis, MO, USA) were washed for 30 min for embedding. Skin paraffin blocks made using a tissue processor (Thermo Fisher Scientific, Waltham, MA, USA) were sectioned at 7-µm using a microtome (Leica, Wetzlar, Germany), and cooked at 37°C overnight to keep them attached to the slides. The sectioned slides were passed through xylene and four concentrations of ethanol (100%, 95%, 80%, and 70%) to deparaffinate them for staining. 4.5.3. Isolation of Protein The frozen skin tissues were ground using liquid nitrogen and homogenized by the RIPA buffer (EzRIPA, ATTO, Tokyo, Japan) with proteinase and phosphatase inhibitors. The homogenized skin tissues were sonicated and then centrifuged at 14,000× g for 15 min at 4 °C After centrifugation, the isolated protein (supernatant liquids) was aliquoted and quantified by a bicinchoninic acid assay kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA). 4.6. Quantitative Real-Time Polymerase Chain Reaction The qRT-PCR mixed a reagent containing the SYBR Green reagent (Takara), 1 µg of synthesized cDNA template, and a 10 pmol primer ( ), which were dispensed into 384-well multi-plates, and then analyzed by the CFX386 Touch Real-Time PCR System (Bio-Rad, Hercules, CA, USA). 4.7. 3,3-Diaminobenzidine Staining for Immunohistochemistry Use The sectioned skin tissue slides were incubated in 3% hydrogen peroxide in methanol for 30 min at room temperature to block endogenous peroxidase. The tissue slides were washed using a phosphate-buffered saline (PBS) and then incubated with mTOR antibodies (1:400; LSBio, Seattle, WA, USA) and pmTOR antibodies (1:50; Santa Cruz Biotechnology Inc., Dallas, TX, USA) in normal serum for 24 h at 4 °C. The slides were rinsed with PBS and incubated with a biotinylated secondary antibody using the ABC kit (Vector Laboratories Inc., Burlingame, CA, USA) for 2 h at room temperature. After washing with PBS, the tissue slides were developed using 3,3 ′ -diaminobenzidine (Sigma-Aldrich) for 15 min to confirm the brown signal. To identify nuclei, tissue slides were stained in hematoxylin solution for 1 min, then mounted with dibutylphthalate polystyrene xylene mounting solution (Sigma-Aldrich). Images of the stained tissues were taken under an optical microscope (Olympus Optical Co., Tokyo, Japan) and analyzed using ImageJ software (NIH, Bethesda, MD, USA). 4.8. Western Blotting Equal amounts of isolated skin proteins were separated on 8–12% polyacrylamide gels and transferred to polyvinylidene fluoride membranes (Millipore, Burlington, MA, USA) by a power station (ATTO, Osaka, Japan). After blocking using 5% skim milk and washing with Tris-buffered saline with 0.1% Tween 20 (TTBS), the membranes were incubated with Beclin 1 antibodies (1:2000; Bioss, Woburn, MA, USA), LC3 (1:500; Bioss) and β-actin (1:1000; Cell Signaling, Danvers, MA, USA) for 12 h at 4 °C and then washed with TTBS. The membranes were then incubated with a secondary antibody (Vector Laboratories, Burlingame, CA, USA) and rinsed with TTBS. Subsequently, an enhanced chemiluminescence detection reagent (GE Healthcare, Chicago, IL, USA) was used to visualize the immunoreactive proteins on the membrane. 4.9. Transmission Electron Microscopy Specimens were fixed for 12 h in 2% glutaraldehyde/2% paraformaldehyde in 0.1 M phosphate buffer (pH 7.4) and washed in 0.1 M phosphate buffer, post-fixed with 1% OsO 4 in 0.1 M phosphate buffer for 2 h, dehydrated with an ascending ethanol series (50%, 60%, 70%, 80%, 90%, 95%, 100%, and 100%) for 10 min each, and infiltrated with propylene oxide for 10 min. The fixed samples were embedded using a Poly/Bed 812 kit (Polysciences, Warrington, PA, USA) and polymerized in an electron microscope oven (DOSAKA, Katsumi, Japan) at 65 °C for 12 h. The block was equipped with a diamond knife in the ultramicrotome, cut into 200 nm sections, and stained with toluidine blue for optical microscopy. The region of interest was then cut into 80 nm sections using the ultramicrotome, placed on copper grids, double stained with 3% uranyl acetate for 30 min and 3% lead citrate for 7 min, and observed under a TEM (JEOL, Tokyo, Japan) equipped with a Megaview III CCD camera (Soft Imaging System-Germany) at an acceleration voltage of 80 kV. 4.10. Fontana–Masson Staining The skin tissues were incubated in Fontana ammoniacal silver solution (ScyTek, West Logan, UT, USA) overnight at room temperature, subsequently rinsed three times with distilled water, and then incubated in hypo solution for 3 min. Afterwards, the tissues were washed in distilled water, counterstained with neutral red stain for 5 min, washed in distilled water, dehydrated in absolute alcohol, and mounted for observation. 4.11. Statistical Analysis We performed a Kruskal–Wallis test for comparisons of three groups, followed by a Mann–Whitney U test as a post hoc test. This study was validated using an unpaired t -test. All results are presented as mean ± standard deviation, and the statistical significance was displayed: *, vs. control (HEKn or HEMn) or control 28 days (skin); $, vs. UV-B (HEKn) or α-MSH (HEMn) or UV-B 28 days (skin); †, vs. UV-B/RF 1 day (skin). All statistical analyses were performed using SPSS version 22 (IBM Corporation; Armonk, NY, USA).
Human primary epidermal keratinocytes (HEKn; American Type Culture Collection, ATCC, Manassas, VA, USA) were maintained with a keratinocyte growth kit (ATCC, Manassas, VA, USA). For establishing the in vitro model in HEKn, the cells were exposed to UV-B (200 mJ/cm 2 ) for 5 min, irradiated with RF (POTENZA, Jeisys Medical Inc., Seoul, Korea; 2 MHz, 10 W, 100 ms), and incubated for 24 h ( A). Human primary epidermal melanocytes (HEMn; ATCC, Manassas, VA, USA) were grown in Dermal Cell Basal Medium (ATCC, Manassas, VA, USA) with a melanocyte growth kit (ATCC, Manassas, VA, USA). For establishing the in vitro model in HEMn, the cells were treated with 200 nM α-MSH (Sigma Aldrich, St. Louis, MO, USA) and kept in an incubator at 37 °C in an atmosphere of 5% CO 2 for 24 h. Then, the cells were irradiated with RF, and incubated for 48 h ( F).
To assess melanin content in HEMn, the cells were seeded at 1 × 10 4 cells/well in 96-well plates and incubated for 24 h. After applying α-MSH and RF, the cells were harvested by centrifugation at 12,000× g for 20 min and dissolved in 100 μL of 10% dimethyl sulfoxide (DMSO) and 1N NaOH solution for 20 min at 95 °C. Absorbance at 490 nm was measured with a microplate reader (Molecular Devices).
Five-week-old male HRM-2 mice (20–25 g) were obtained from Central Lab Animal Inc. (Seoul, Korea) and cared to adapt for 2 weeks. The mice were housed in cages under a controlled temperature (23 °C) with a 12 h light/dark cycle and free access to food and water. After the adaptation period, the mice were randomly divided into five groups as follows: (1) control (no exposure to UV-B and no irradiated RF), (2) UV-B (exposure to UV-B at 200 mJ/cm 2 ), (3) UV-B/RF 1d (exposure to UV-B/irradiated RF; sampling proceeds 1 day after RF irradiation), (4) UV-B/RF 7d (exposure to UV-B/irradiated RF; sampling proceeds 7 days after RF irradiation), (5) UV-B/RF 28d (exposure to UV-B/irradiated RF; sampling proceeds 28 days after RF irradiation). The mice were exposed to UV-B for 5 min once every 2 days for 10 days and then for 5 min every day for the next 3 days (total of 13 days) . Subsequently, the mice were irradiated to RF (2 MHz, 10 W for 100 ms) and then exposed to UV-B every 2 days for 28 days. The skin tissues of mice were harvested after 1 day, 7 days and 28 days of RF irradiation ( E). This study was approved by the Center of Animal Care and Use ethical board of Gachon University (Approval Number LCDI-2020-0115) and executed in accordance with the Institutional Animal Care and Use Committee.
The irradiation system (POTENZA, Jeisys Medical Inc., Seoul, Korea) used for this study was a bipolar pulse-type electrode array radiofrequency device. An impedance matching system was used to determine the compensation value by automatically measuring impedance, and RF was applied using a 16 ea (4 × 4) needle tip. RF was administered at 2 MHz using pulse-type, bipolar, alternating current oscillations in the animal experiment. Single pulse-type bipolar RF devices were used in the animal experiment and comprised an on-time pulse duration of 100 ms at a power density of 10 W/pulse. The invasive microneedle for RF application had a length of 13.6 mm, a diameter of 250 mm, and a needle-to-needle distance of 1.3 mm, and irradiation and treatment were performed with a disposable tip of 10 mm × 10mm consisting of 16 electrodes. The tip was approved by NAMSA (Northwood, OH, USA) after biological compatibility testing.
4.5.1. Extraction of RNA and cDNA Synthesis The cells and frozen skin tissues were ground using liquid nitrogen and homogenized by the RNAiso Plus reagent (Takara, Shiga, Japan) according to the manufacturer’s instructions. The extracted RNA was quantified by the NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and was converted to cDNA using a PrimeScript 1 ST strand cDNA Synthesis Kit (Takara, Shiga, Japan) for quantitative real-time polymerase chain reaction (qRT-PCR). 4.5.2. Paraffin-Embedded Tissue Sectioning The skin tissues that were fixed by 4% paraformaldehyde (Sigma-Aldrich, St. Louis, MO, USA) were washed for 30 min for embedding. Skin paraffin blocks made using a tissue processor (Thermo Fisher Scientific, Waltham, MA, USA) were sectioned at 7-µm using a microtome (Leica, Wetzlar, Germany), and cooked at 37°C overnight to keep them attached to the slides. The sectioned slides were passed through xylene and four concentrations of ethanol (100%, 95%, 80%, and 70%) to deparaffinate them for staining. 4.5.3. Isolation of Protein The frozen skin tissues were ground using liquid nitrogen and homogenized by the RIPA buffer (EzRIPA, ATTO, Tokyo, Japan) with proteinase and phosphatase inhibitors. The homogenized skin tissues were sonicated and then centrifuged at 14,000× g for 15 min at 4 °C After centrifugation, the isolated protein (supernatant liquids) was aliquoted and quantified by a bicinchoninic acid assay kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA).
The cells and frozen skin tissues were ground using liquid nitrogen and homogenized by the RNAiso Plus reagent (Takara, Shiga, Japan) according to the manufacturer’s instructions. The extracted RNA was quantified by the NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and was converted to cDNA using a PrimeScript 1 ST strand cDNA Synthesis Kit (Takara, Shiga, Japan) for quantitative real-time polymerase chain reaction (qRT-PCR).
The skin tissues that were fixed by 4% paraformaldehyde (Sigma-Aldrich, St. Louis, MO, USA) were washed for 30 min for embedding. Skin paraffin blocks made using a tissue processor (Thermo Fisher Scientific, Waltham, MA, USA) were sectioned at 7-µm using a microtome (Leica, Wetzlar, Germany), and cooked at 37°C overnight to keep them attached to the slides. The sectioned slides were passed through xylene and four concentrations of ethanol (100%, 95%, 80%, and 70%) to deparaffinate them for staining.
The frozen skin tissues were ground using liquid nitrogen and homogenized by the RIPA buffer (EzRIPA, ATTO, Tokyo, Japan) with proteinase and phosphatase inhibitors. The homogenized skin tissues were sonicated and then centrifuged at 14,000× g for 15 min at 4 °C After centrifugation, the isolated protein (supernatant liquids) was aliquoted and quantified by a bicinchoninic acid assay kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA).
The qRT-PCR mixed a reagent containing the SYBR Green reagent (Takara), 1 µg of synthesized cDNA template, and a 10 pmol primer ( ), which were dispensed into 384-well multi-plates, and then analyzed by the CFX386 Touch Real-Time PCR System (Bio-Rad, Hercules, CA, USA).
The sectioned skin tissue slides were incubated in 3% hydrogen peroxide in methanol for 30 min at room temperature to block endogenous peroxidase. The tissue slides were washed using a phosphate-buffered saline (PBS) and then incubated with mTOR antibodies (1:400; LSBio, Seattle, WA, USA) and pmTOR antibodies (1:50; Santa Cruz Biotechnology Inc., Dallas, TX, USA) in normal serum for 24 h at 4 °C. The slides were rinsed with PBS and incubated with a biotinylated secondary antibody using the ABC kit (Vector Laboratories Inc., Burlingame, CA, USA) for 2 h at room temperature. After washing with PBS, the tissue slides were developed using 3,3 ′ -diaminobenzidine (Sigma-Aldrich) for 15 min to confirm the brown signal. To identify nuclei, tissue slides were stained in hematoxylin solution for 1 min, then mounted with dibutylphthalate polystyrene xylene mounting solution (Sigma-Aldrich). Images of the stained tissues were taken under an optical microscope (Olympus Optical Co., Tokyo, Japan) and analyzed using ImageJ software (NIH, Bethesda, MD, USA).
Equal amounts of isolated skin proteins were separated on 8–12% polyacrylamide gels and transferred to polyvinylidene fluoride membranes (Millipore, Burlington, MA, USA) by a power station (ATTO, Osaka, Japan). After blocking using 5% skim milk and washing with Tris-buffered saline with 0.1% Tween 20 (TTBS), the membranes were incubated with Beclin 1 antibodies (1:2000; Bioss, Woburn, MA, USA), LC3 (1:500; Bioss) and β-actin (1:1000; Cell Signaling, Danvers, MA, USA) for 12 h at 4 °C and then washed with TTBS. The membranes were then incubated with a secondary antibody (Vector Laboratories, Burlingame, CA, USA) and rinsed with TTBS. Subsequently, an enhanced chemiluminescence detection reagent (GE Healthcare, Chicago, IL, USA) was used to visualize the immunoreactive proteins on the membrane.
Specimens were fixed for 12 h in 2% glutaraldehyde/2% paraformaldehyde in 0.1 M phosphate buffer (pH 7.4) and washed in 0.1 M phosphate buffer, post-fixed with 1% OsO 4 in 0.1 M phosphate buffer for 2 h, dehydrated with an ascending ethanol series (50%, 60%, 70%, 80%, 90%, 95%, 100%, and 100%) for 10 min each, and infiltrated with propylene oxide for 10 min. The fixed samples were embedded using a Poly/Bed 812 kit (Polysciences, Warrington, PA, USA) and polymerized in an electron microscope oven (DOSAKA, Katsumi, Japan) at 65 °C for 12 h. The block was equipped with a diamond knife in the ultramicrotome, cut into 200 nm sections, and stained with toluidine blue for optical microscopy. The region of interest was then cut into 80 nm sections using the ultramicrotome, placed on copper grids, double stained with 3% uranyl acetate for 30 min and 3% lead citrate for 7 min, and observed under a TEM (JEOL, Tokyo, Japan) equipped with a Megaview III CCD camera (Soft Imaging System-Germany) at an acceleration voltage of 80 kV.
The skin tissues were incubated in Fontana ammoniacal silver solution (ScyTek, West Logan, UT, USA) overnight at room temperature, subsequently rinsed three times with distilled water, and then incubated in hypo solution for 3 min. Afterwards, the tissues were washed in distilled water, counterstained with neutral red stain for 5 min, washed in distilled water, dehydrated in absolute alcohol, and mounted for observation.
We performed a Kruskal–Wallis test for comparisons of three groups, followed by a Mann–Whitney U test as a post hoc test. This study was validated using an unpaired t -test. All results are presented as mean ± standard deviation, and the statistical significance was displayed: *, vs. control (HEKn or HEMn) or control 28 days (skin); $, vs. UV-B (HEKn) or α-MSH (HEMn) or UV-B 28 days (skin); †, vs. UV-B/RF 1 day (skin). All statistical analyses were performed using SPSS version 22 (IBM Corporation; Armonk, NY, USA).
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Bovine Leukemia Virus and Human Breast Cancer: A Review of Clinical and Molecular Evidence | c5d00690-565a-43e0-8ce4-be848449672c | 11946124 | Pathologic Processes[mh] | Breast cancer (BC) is the most commonly diagnosed malignancy among women globally and the leading cause of cancer-related death in this population . In the United States alone, an estimated 310,720 new cases and 42,250 deaths from BC among women were reported for 2024 . Notably, the highest BC incidence rates occur in regions such as Australia/New Zealand, Northern America, Northern Europe, and Western Europe, where the rates are nearly three times higher compared to those in Eastern Africa, South-Central Asia, and Middle Africa . In general, the differences in BC incidence rates among countries and ethnicities are associated with differences in the exposure level to risk factors and the implementation and/or access to primary prevention programs . A variety of reproductive and lifestyle risk factors have been associated with BC development, including, but not limited to, age at menarche and menopause, number of children, breastfeeding, use of hormonal therapy, obesity, genetic mutations, family history, and unhealthy food habits . Furthermore, the potential relation of some viruses like mouse mammary tumor virus (MMTV), Epstein-Barr virus (EBV), human papillomavirus (HPV), and human cytomegalovirus (HCMV) to BC development has also been proposed [ , , , , ]. In addition, a potential association between viral co-infections and BC development was previously suggested . However, it is well accepted that breast carcinogenesis is most related to a combination of environmental, genetic, and lifestyle risk factors . Particularly, the potential association of BC development and the intake of animal products have been addressed in numerous studies [ , , ]. For instance, bovine meat and dairy products could contain high levels of saturated fats , xenoestrogens, growth factors , and endocrine disruptors such as heterocyclic amines found in processed or cooked red meat , all of which may contribute to BC development and progression . Despite these findings, the causal relationship between dietary factors and BC remains unclear. Interestingly, the presence of the bovine leukemia virus (BLV) DNA in bovine milk and meat for human consumption has been reported [ , , ]. BLV is a deltaretrovirus that naturally infects cattle, zebu, and buffalo . BLV is the causative agent of enzootic bovine leucosis (EBL), characterized by persistent B-cell lymphocytosis and lymphoma development . In addition, BLV is able to infect a broad variety of cells, including bovine mammary epithelial cells . Recently, a meta-analysis conducted by Bushi et al. (2024), including 48 studies and 101,120 cattle samples, reported a global prevalence of BLV at 26.8% (95% CI: 20.0–33.0) . The occurrence of anti-BLV antibodies was demonstrated in human females [ , , ], which supports previous exposure to the virus. Moreover, BLV DNA was detected in blood samples from human females , which was also genetically related to the virus-infected cattle in the same geographical area and time period . Furthermore, an association between the increased consumption of dairy products by females and the risk of BLV infection was reported , suggesting that bovine products could be a route for zoonotic BLV infection in humans. Given the high consumption of dairy products in certain regions, BLV exposure may have public health implications. While its role in human disease remains uncertain, potential transmission through dairy consumption warrants further investigation to assess associated risks and preventive measures. In this regard, the presence of BLV has been frequently detected in breast tissue samples, and it has also been related to an increased risk of BC development [ , , ]. Notably, the presence of BLV was demonstrated in initial benign breast tissues and in the posterior BC specimens from the same patients . However, the relationship between BLV and BC remains highly controversial due to inconsistencies in the available data. While some studies report a strong association, others fail to find significant differences in BLV prevalence between BC cases and controls. These discrepancies may be attributed to variations in detection methodologies, sample sizes, and study designs. Differences in BLV DNA target regions, geographic variations in viral strains, and potential confounding factors further complicate the interpretation of findings. This review provides a comprehensive analysis of the current clinical evidence linking BLV infection to human BC development. Additionally, it explores the potential mechanisms by which BLV enters breast epithelial cells and examines its contribution to BC initiation and progression.
BLV is a diploid single-stranded RNA that belongs to the Retroviridae family and Deltaretrovirus genus . This virus is closely related to the human T-cell leukemia virus type 1 (HTLV-1), both of which are characterized by their ability to infect lymphocytes and integrate their genetic material into the host genome—a process known as establishing the proviral state—which is an essential hallmark of retroviral replication . The BLV genome comprises an 8714-nucleotide sequence, enclosed by an icosahedral nucleocapsid surrounded by a double-layered lipid membrane structure derived from the host cell during viral budding . This genome encodes structural proteins, viral enzymes, regulatory proteins, and accessory proteins. It is flanked by two identical long terminal repeat (LTR) sequences, the 5′ LTR and 3′ LTR, which regulate viral gene expression and replication ( ). The 5′ LTR contains promoter elements that drive the activity of RNA polymerase II (RNAPII), which transcribes BLV protein-coding genes. These include the structural genes ( gag , pro , pol , and env ), regulatory genes ( tax and rex ), and accessory genes ( R3 and G4 ), all of which are essential for the virus lifecycle . The gag gene encodes three non-glycosylated and structural proteins: the nucleocapsid protein (p12), the matrix protein (p15), and the other nucleocapsid protein (p24), which form the viral core . The pro gene encodes the viral protease (p14), which cleaves gag and gag-pol polyproteins during virion maturation, a process critical for the release of infectious particles . However, the pol gene encodes two essential enzymes: reverse transcriptase (RT), which converts viral RNA into double-stranded proviral DNA, and integrase (INT), which facilitates the integration of this DNA into the host genome . The env gene encodes two glycosylated envelope proteins, glycoprotein (gp)51 (surface) and gp30 (transmembrane). The gp51 protein mediates virus–host cell fusion, while gp30 is involved in signal transduction pathways and stabilizing gp51 . Notably, the env gene exhibits genetic polymorphism, with eleven distinct BLV genotypes identified through gp51 sequencing and phylogenetic studies. These genotypes are distributed differently across the globe, reflecting the evolutionary adaptation of BLV and geographical spread [ , , , , ]. Located between the env gene and the 3′ LTR, the pX region encodes key regulatory proteins (Tax and Rex) and accessory proteins (R3 and G4) . Tax functions as a transcriptional activator, stimulating LTR activity and driving viral gene expression while playing a critical role in BLV-induced tumorigenesis and lymphoproliferative disorders [ , , ]. Likewise, Rex is involved in post-transcriptional regulation, ensuring the efficient export of unspliced viral RNA from the nucleus and supporting the synthesis of structural proteins . Meanwhile, the accessory proteins R3 and G4 play critical roles in maintaining high viral loads during persistent infections, with G4 also associated with oncogenic activity, further highlighting its role in BLV pathogenesis . Another unique feature of the BLV genome is a region located between the env and R3 genes, which encode ten viral microRNAs (miRNAs) under the control of RNA polymerase III . These miRNAs are involved in various biological processes, including immune modulation, cell signaling, apoptosis, and tumorigenesis . These small RNA molecules contribute to immune evasion and viral persistence by downregulating host antiviral responses. Some of BLV-encoded miRNAs share sequence identity with human miRNAs, suggesting a potential overlap in the target molecules of both viral and human miRNAs. For instance, it was found that miR-B2-5p displays a common seed overlap with human miR-943 . The overexpression of miR-943 was evidenced in the stem population of primary human mammalian epithelial cells (HMECs), and it was also upregulated in cells when the tumor suppressor p53 was knocked down . Moreover, miR-943 is negatively correlated with the gene expression of Ataxia-telangiectasia mutated (ATM) and breast cancer gene 1 (BRCA1) in BC, which suggests its potential involvement in the repair of DNA double-strand breaks . Furthermore, it was found that BLV-miR-B4–3p also has a matching seed sequence with the human miR-29a . The miR-29a targets SUV420H2 and downregulates the trimethylation of the histone H4K20, inducing the epithelial-to-mesenchymal transition (EMT), migration, and invasion of BC cells . These facts together may suggest a possible oncogenic role of BLV miRNAs in human breast cells. In the BLV lifecycle, a defining step is the integration of the virus as a provirus into the genomic DNA of peripheral blood cells, establishing a persistent infection in the host . The retroviral lifecycle can be divided into two phases: the early phase and the late phase. The early phase includes viral entry, reverse transcription, and proviral integration. Viral envelope proteins mediate entry by interacting with specific host cell receptors. Inside the cell, viral RNA is reverse transcribed into DNA, which is then integrated into the host genome by the viral integrase enzyme, while the late phase involves the transcription and translation of viral RNA, assembly of new virions, and their release through budding . Both phases require coordinated interplay between viral and host factors . For example, the processing of viral proteins relies not only on the viral protease but also on host proteases, highlighting the viral dependence on host cellular machinery . Efficient transcription of the BLV proviral genome is driven by the viral transcriptional activator Tax, which works in tandem with host factors to regulate viral gene expression . Additionally, the LTR interacts with host transcription factors to fine-tune viral replication, demonstrating the intricate relationship between the virus and its host. This complex lifecycle and genetic makeup allow BLV to evade immune responses, persist in host populations, and contribute to oncogenesis, making it a significant concern for animal health and a useful model for studying retroviral biology. BLV can also infect and replicate in cells from non-bovine animal species (e.g., lamb, canine, feline, murine, and human cells) . However, the ability of BLV to infect non-bovine cells depends on diverse factors, such as the competence and response of the host immune system, the presence of viral receptors on the cell surface, and the capacity of BLV to hijack and customize the host cell machinery for replication . For example, the expression of BLV precursor and mature proteins was also reported in COS-1 cells (African green monkey kidney cells) and FLK cells (fetal lamb kidney cells) transfected with wild-type proviral DNA . Notably, it was demonstrated that the expression of gPr72Env, Pr70Gag, and pr45Gag precursor proteins as well as gp51, gp30, and p24 mature proteins was detected in the lysates of 293T human cells transfected with an infectious BLV clone. Moreover, the production and secretion of BLV viral particles by 293T-transfected cells was verified . These facts together may suggest similarities in the BLV lifecycle across cells from different animal species, including human cells.
The BLV is an enzootic retrovirus that naturally infects cattle, zebu, and buffalo , causing B-cell lymphomas in 1–5% of infected cattle . In addition, BLV can be experimentally transmitted to other species, including goats , sheep , chickens , rabbits , and rats , which provide evidence concerning the capacity of BLV to cross species barriers. Remarkably, in humans, the presence of BLV has been detected in breast and lung tissues, as well as in blood cells . In cattle, BLV is detected in biological fluids such as blood, colostrum, and milk, which are considered potential sources for viral transmission . BLV can be transmitted horizontally through iatrogenic procedures permitting blood or fluid transfer like rectal palpation using contaminated sleeves, injections with reused needles, or animal-to-animal contact through nasal excretions or saliva . Vertical transmission occurs from BLV-infected dams to calves mainly through the consumption of infected colostrum or milk . BLV DNA was detected in 38.9% of the milk samples and in 32.1% of the meat samples obtained from BLV-positive cows . Similarly, the BLV proviral gag segment was found in 48.0% of the milk samples and in 50.0% of the meat samples for human consumption . Moreover, the ex vivo infectivity of milk cells from BLV-infected cattle was previously demonstrated , which suggests that milk and meat consumption could be a route for BLV infection in humans. On the other hand, BLV DNA was detected in 33/95 (34.7%) samples of leukocytes and platelets (buffy coat cells) from the blood from human females using PCR and DNA sequencing . Similarly, BLV DNA was found in 16.5% (33/200) of blood samples from women without BC . Interestingly, Canova et al. reported a genetic relationship between the BLV DNA sequences found in the blood from virus-infected cattle and in women’s breast tissue in the same geographical area and time period . Additionally, Buehring et al. detected antibodies against BLV capsid protein (p24) in 191/257 (74.3%) samples of the analyzed human sera. The distribution for the three antibody isotypes tested was as follows: IgG = 101/257 (39.3%), IgM = 80/257 (31.1%), and IgA = 96/256 (37.5%) . However, the same authors reported no significant correlation between the occurrence of anti-BLV p24 antibodies and the presence of BLV DNA in the blood samples . However, de Quadros et al. reported the presence of anti-BLV antibodies in 4.1% of the tested human serum samples . The presence of anti-BLV antibodies in human sera provides evidence of previous exposure to the virus, although others have reported the lack of BLV antibodies in human serum samples . Overall, the evidence suggests that uncooked or partially cooked meat and unpasteurized milk derived from BLV-infected cattle could be a potential source of a zoonotic infection to humans. In this regard, a statistically significant association was reported between an increased consumption of dairy products by females and the risk of BLV infection (OR = 2.4, CI 95%: 1.063–5.527; p = 0.035), although no relation with meat consumption was obtained in this study . Remarkably, it was suggested that another oncogenic virus in humans (high-risk HPV) could reach the breast tissue through circulation (blood or lymphatic systems) in patients with HPV-positive cervical cancer . A hypothetical scheme regarding the potential routes for BLV infection in human breast tissues through infected milk and meat consumption is shown in . Other hypotheses for BLV entry to humans, such as direct contact with infected animals or through vaccine production processes that involve the use of BLV-contaminated fetal bovine sera, have also been proposed . As occurs in cattle-to-cattle transmission, the lack of protection when handling infected animals, blood/tissue exposure, or inadequate safety protocols could theoretically be alternative routes for the transmission of BLV to humans . Despite these potential risks, there are no confirmed reports of BLV transmitting infection in humans in this way. However, the detection of BLV in human blood cells may suggest a potential route of transmission to other individuals via the blood . Further investigations are required to elucidate the routes by which BLV reaches human tissues.
BLV shows a preferential tropism for B lymphocytes, but it was demonstrated that BLV in vivo also targets other leukocytes such as monocytes, granulocytes, and CD8+ T lymphocytes . Moreover, BLV is able to infect a broad variety of cells, such as canine, feline, and murine cells, and also bovine mammary epithelial cells . Furthermore, the capacity of BLV to infect a variety of human cells of different origins, such as embryonic kidney (293T) , cervical carcinoma (HeLa) , glioblastoma (U-118 MG), ovarian teratocarcinoma (PA-1) , and breast adenocarcinoma (MCF-7) , was demonstrated. Particularly, evidence suggests the tropism of BLV towards human breast epithelial cells, based on the fact that these epithelial cells express viral proteins after BLV infection [ , , ]. Overall evidence suggests that the cellular receptors involved in BLV entry could be broadly expressed rather than restricted to a specific cell type. It was reported that BLV is able to infect the human WI-38 cells (lung fibroblast cells) in vitro. However, WI-38 cells released only small amounts of the viral particles despite remaining infected, as measured by the expression of BLV antigen and the syncytia formation assay . This assay evaluates the capacity of retroviruses to induce fusion between infected and uninfected cells, leading to the creation of multinucleated cells, known as syncytia. The syncytia formation assay is commonly used to monitor BLV infection in vitro . Also, it demonstrated the capacity of BLV to infect human glioblastoma, neuroblastoma, and ovarian teratocarcinoma cells . Interestingly, some human cell lines were susceptible to BLV infection, including MCF-102A (non-malignant) and MCF-7 (adenocarcinoma) breast cells. But, only MCF-7 cells were able to sustain BLV infection and also showed syncytia formation and multinucleated cells . The high-affinity cationic amino acid transporter 1 (CAT1), also known as solute carrier family 7 member 1 (SLC7A1), is a transmembrane protein primarily responsible for the uptake of cationic amino acids into cells. This protein plays a critical role in cellular metabolism, growth, and immune response by regulating the availability of essential amino acids required for protein synthesis and other metabolic pathways . SLC7A1 is considered a potential entry receptor for BLV into human epithelial cells. In fact, HeLa (human cervical carcinoma cells) and 293T (human embryonic kidney cells) expressing SLC7A1 formed syncytia in culture after inoculation with BLV . Moreover, the knockdown of SLC7A1 using specific siRNAs significantly decreased both the binding between SLC7A1 and BLV Env protein and the BLV infection of CC81-GREMG cells . In addition, overexpression of SLC7A1 was able to enhance the susceptibility of the same cells to BLV infection . These facts together permit the consideration of the potential role of SLC7A1 in BLV binding and infection. Interestingly, the levels of SLC7A1 mRNA were significantly increased in BC tissues compared to normal breast samples ( p < 0.01) . According to the TCGA database , SLC7A1 expression was also higher in BC tissues and metastasis compared to normal breast tissues ( ). These facts together could suggest that increased levels of SLC7A1 make BC cells more susceptible to BLV infection ( ). Moreover, it was demonstrated that the overexpression of SLC7A1 confers survival advantages and apoptosis resistance in MCF-7 and T47D BC cells . The adaptor-related protein complex 3 subunit delta 1 (AP3D1) is a critical component of the adaptor protein complex-3 (AP-3), which is involved in intracellular protein trafficking . This complex facilitates the sorting and transport of cargo proteins from the trans-Golgi network to lysosomes and other endosomal compartments . The AP3D1 protein has also been proposed as a potential receptor for BLV in humans, sharing 88% of identity compared to the bovine receptor . In fact, it was reported that HEp-2 human cancer cells ectopically expressing the bovine binding domain for BLV gp51 (clone BLVRcpl) had an increased susceptibility to BLV infection compared to untransfected control cells . Furthermore, a significant increase in the sensitivity to BLV infection was evidenced in BLVRcpl-transfected cells after antibiotic selection, which highlights the potential role of this molecule in BLV infection . Posteriorly, the BLV receptor (BLVR) is related to AP-3, which participates in intracellular protein transport . According to The Cancer Genome Atlas (TCGA) database , AP3D1 expression was increased in primary BC and metastasis compared to normal breast tissues, suggesting again that BC cells with increased levels of AP3D1 could be more susceptible to BLV infection ( ). Moreover, an increased AP3D1 gene expression was evidenced in invasive ductal carcinoma compared to invasive lobular carcinoma . Taken together, these findings suggest that BLV entry into breast epithelial cells can be induced by overexpressing key receptors involved in this process. Nevertheless, further functional studies in breast epithelial cells are required to validate this hypothesis.
Although the potential involvement of BLV in BC still remains controversial, the virus has been widely detected in BC samples and has been associated with an increased risk of tumor development [ , , ]. For instance, a meta-analysis conducted by Khatami et al., which included nine case-control studies with a total of 826 BC cases and 898 individuals in the control groups, found an association between BLV infection and the risk of BC development (OR = 2.57; 95% CI: 1.45–4.56; p = 0.001) . Another meta-analysis conducted by Saeedi-Moghaddam et al. including 11 studies, 3340 cases, and 635 controls also found an association of BLV infection and BC (OR = 3.92, 95% CI: 2.98–5.16; p < 0.00001) . Particularly, BLV DNA was evidenced in 22/72 (30.5%) samples of BC tissues, which was statistically increased compared to samples from patients with healthy breast tissues (10/72; 13.9%) (OR = 2.73, 95% CI: 1.18–6.29; p = 0.027) . Similarly, Olaya-Galán et al. found the occurrence of BLV DNA in 46/75 (61.3%) samples from BC cases and in 40/83 (48.2%) of the control tissues by nested PCR, linking the viral presence with an increased risk of BC development (OR = 2.45, 95% CI: 1.08–5.52; p = 0.031) . While Buehring et al. (2015) demonstrated the presence of BLV DNA in 67/114 (59%) of BC samples using in situ PCR, and it was significantly increased compared to the 30/104 (29%) samples obtained from the controls (OR = 3.07, 95% CI: 1.66–5.69; p = 0.0004) . Additionally, an increased presence of BLV DNA in premalignant breast tissues compared to healthy breast specimens was also demonstrated. In fact, Buehring et al. (2015) found an intermediate frequency of BLV DNA in premalignant breast tissues (8/21; 38%) between the BC and normal control groups ( p for trend < 0.001) . In the same way, Baltzell et al. (2018) obtained an increased frequency of BLV tax DNA by in situ PCR from normal breast specimens (20/103; 19.6%) compared to premalignant tissues (18/52; 34.0%) and BC plus ductal carcinoma in situ (DCIS) samples (49/89; 54.4%). In consequence, the presence of BLV tax DNA was related to an increased risk of BC or DCIS (OR = 5.25, 95% CI: 2.69–10.23; p < 0.0001) . A study conducted by Lawson and Glenn (2017) analyzing the paired samples of benign breast tissue and subsequent BC specimens from the same patients revealed a higher frequency of BLV DNA in both benign breast tissues (18/23; 78.3%) and the later BC samples (20/22; 90.9%) compared to healthy breast specimens (6/17; 35.3%) . Similarly, in a paired study, Buehring et al. (2017) observed an increased probability of BC development in women with BLV-positive results in both initial and subsequent samples, compared to those in whom BLV was either not detected or only positive in one of the paired specimens ( p = 0.0484) . Finally, Lendez et al. (2018) demonstrated that BLV DNA occurrence in BC tissues was associated with increased proliferation rates ( p = 0.014) and HER-2 oncogene expression ( p = 0.042) . Similarly, Khan et al. reported a higher prevalence of BLV positivity in grade II invasive ductal carcinoma (IDC) (500/559; 89.4%) compared to grade I (59/559; 10.5%) and grade III tumors (0/559) . However, other studies found no significant association between the presence of BLV and the tumor size, disease stage, estrogen receptor (ER) levels, progesterone receptor (PR) levels, human epidermal growth factor receptor 2 (HER-2) levels, proliferation index, or other clinicopathological features in BC patients [ , , ]. Interestingly, it was suggested that the failure to efficiently eliminate BLV due to low binding affinity for HLA-II may contribute to BC development . However, the presence of BLV DNA in BC tissues does not necessarily imply an active viral infection or causation. In this regard, the expression of the BLV p24 protein was detected in 10% of BC tissues , while Buehring et al. found the same protein in 12/236 (5.1%) of the BC specimens . In addition, the presence of gp51 was evidenced in 7% of BC samples . Furthermore, it was demonstrated that the MCF-7 cells were able to maintain a stable BLV infection over the 3-month follow-up, confirmed by both PCR and the immunohistochemical expression of the BLV p42 protein . These facts together allow the consideration of a potential active replication of BLV in BC tissues. Overall, the evidence indicates an increased frequency of BLV in BC tissues compared to non-tumor controls, suggesting a potential association between BLV infection and the risk of BC development. However, some studies have reported a decreased frequency of BLV infection in BC tissues [ , , ], while others found no significant differences in BLV presence between BC cases and non-tumor controls . The discrepancies regarding the potential association of BLV infection and BC may be attributed to differences in detection methods (PCR, in situ PCR, nested PCR) and also in the viral DNA sequence used as a target ( tax , gag , env , LTR). Furthermore, differences in the amount of beef and dairy product consumption across the study populations (North American, South American, European, Australian, and Asian) could also explain the discrepancies between the frequencies of BLV DNA found in BC patients . Additionally, it is important to consider that other risk factors, such as genetics and environmental exposure, may confound the observed association between BLV infection and BC development. Future studies should adjust for these variables to clarify the relationship. A summary of these studies is presented in .
The oncogenic properties of BLV in animal and human cells have been demonstrated [ , , ]. However, to the best of our knowledge, there is no information available regarding the direct role of BLV in human BC initiation or progression. This knowledge gap is critical given the potential implications of BLV as a zoonotic agent with oncogenic capabilities. This section focuses on the oncogenic potential of BLV, addressing three key areas: (1) BLV in bovine mammary cells, (2) the closely related HTVL-1 tax protein in human BC cells, and (3) BLV in human cells from different origins as potential models for a better understanding of BLV’s contribution to human BC. BLV has been shown to enhance the proliferation rate of C72 bovine mammary cells, although these cells were unable to grow in soft agar, a hallmark of oncogenic transformation . Infected bovine mammary epithelial cells (MAC-T) exhibited significantly higher expression levels of TNF-α mRNA compared to uninfected cells ( p < 0.001) . Conversely, another study reported reduced viability in BLV-infected MAC-T cells, accompanied by Bcl-2 downregulation and increased TLR9 mRNA expression . Furthermore, the BLV Tax protein was observed to induce DNA damage and impair DNA repair mechanisms in mammalian cells, including bovine mammary epithelial cells . BLV p34 was shown to cooperate with the Ha-ras oncogene in transforming rat embryo fibroblasts, which subsequently formed tumors when injected into nude mice . On the other hand, some authors reported the potential role of the HTLV-1 tax protein in human BC development [ , , ]. HTLV-1 is a closely related retrovirus to BLV that encodes a similar tax protein . In this regard, the contribution of HTLV-1 tax protein to epithelial cell carcinogenesis could provide valuable information to elucidate the potential role of the BLV tax protein in BC development. For instance, it was reported that the HTLV-1 tax protein interacts with CREB-binding protein (CBP)/p300, inhibiting the activation of BRCA1 induced by ERα . In addition, the HTLV-1 tax protein stimulated the E2–ERα-mediated expression of genes controlled by estrogen response elements (EREs) . Moreover, the HTLV-1 tax protein has the capacity to inhibit BRCA1-mediated activation of p53 target promoters . Finally, the capacity of BLV Tax to deregulate the expression of 122 genes (upregulated: 90, downregulated: 32) was demonstrated in HeLa cells ectopically expressing this molecule . Among them, the overexpression of CYR61, FOS, JUN, RORA, NR4A2, RRAD, GEM, and TNFAIP6 was evidenced at both the transcript and protein levels. In contrast, BLV Tax induced the downregulation of ID2, TNFSF10, IFIT1, and IFIT3 . The capacity of BLV Tax to induce the c-fos promoter activation in SW480 human carcinoma colon cells was demonstrated . Interestingly, human glioblastoma cells with integrated BLV showed proliferation advantages compared to uninfected parental cells . In non-small cell lung cancer (NSCLC), the presence of BLV was significantly associated with PSG4 and CPB2 downregulation . Additionally, BLV Tax induced DNA damage and disrupted DNA repair mechanisms in H9 human T cells, consistent with observations in bovine mammary cells . Collectively, these findings suggest that BLV may affect critical cellular functions, including DNA damage repair, cell proliferation, apoptosis resistance, and immune responses, thereby contributing to oncogenesis. The presence of BLV p24 and gp51 proteins in BC tissues, as detected by immunohistochemistry, supports the possibility of active viral infection [ , , ]. However, despite the mounting evidence, the precise molecular mechanisms by which BLV proteins contribute to BC initiation and progression remain unclear. Therefore, further clinical and experimental studies are needed to establish the direct role of BLV proteins in BC initiation and progression.
The present study showed evidence to support the correlation between BLV infection and BC development in women. Although the exact molecular mechanisms by which BLV could act as a cofactor in breast carcinogenesis are not fully understood, the present review highlights some possibilities. Firstly, the detection of BLV in dairy products and meat for human consumption jointly with the occurrence of anti-BLV antibodies in female blood makes possible the potential transmission of BLV to humans through the diet. Second, some host receptors involved in BLV attachment and fusion to epithelial cells are overexpressed in BC, which make BLV entry into human mammary epithelial cells plausible. Thirdly, the detection of BLV proteins in BC tissues, joined with the capacity of some viral proteins to disrupt key cellular pathways, makes the potential contribution of BLV to human breast carcinogenesis reasonable. However, further clinical and experimental studies focusing on the potential contribution of BLV to BC initiation and progression are strongly necessary. For instance, longitudinal studies following BLV-infected women would be valuable in assessing the long-term effects of BLV infection on BC development. Furthermore, additional experiments are necessary to evaluate the function of BLV-encoded proteins, including Tax, in human breast epithelial cells to enhance understanding of their possible role in BC development and progression. In the future, if BLV is confirmed as a risk factor for BC, it will be important to strengthen strategies to reduce exposure and potential viral transmission to humans, such as the expansion of screening programs to test for BLV presence in dairy products and beef.
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Korean Gastric Cancer Association-Led Nationwide Survey on Surgically Treated Gastric Cancers in 2023 | febc2679-1041-4fbe-9c7f-82c91a8f744d | 11739641 | Laparoscopy[mh] | Gastric cancer remains a major public health issue, particularly in East Asia, where its incidence and mortality rates are among the highest globally . In South Korea, gastric cancer is one of the most prevalent cancers. According to the latest National Cancer Registry statistics for 2021, gastric cancer accounted for approximately 10.6% of all cancer cases, making it the fourth most commonly diagnosed cancer overall. Among men, it was the second most frequent cancer, while among women, it ranked fifth . Despite its high prevalence, advances in national cancer screening programs and early diagnostic techniques have led to a steady increase in early gastric cancer (EGC) detection, contributing to improved patient outcomes . While surgical resection remains the primary gastric cancer treatment, minimally invasive approaches such as laparoscopic and robotic surgeries are becoming increasingly common. To systematically track and analyze evolving trends in gastric cancer treatment, the Korean Gastric Cancer Association (KGCA) has conducted nationwide surveys periodically since 1995 . The 5-year interval was recently reduced to a four-year interval to align with the term of the association’s executive board. Accordingly, data collection for the most recent survey occurred in 2023. This survey provides comprehensive data on patient demographics, pathological characteristics, surgical methods, and operative outcomes, serving as a valuable resource for understanding treatment advancements and trends. The 2019 nationwide survey, which collected data on 14,076 cases from 68 institutions, highlighted important trends in gastric cancer treatment, including an increased proportion of early and upper-third gastric cancers, widespread adoption of laparoscopic techniques, and the first-ever reporting of surgical morbidity and mortality rates . The nationwide survey data collected over the years has served as a critical foundation for diverse research endeavors. Numerous studies have utilized this comprehensive dataset, yielding clinically significant findings that have been published in various academic journals . These efforts underscore the importance of the nationwide survey in providing robust and reliable data that continue to advance gastric cancer research and inform evidence-based clinical practice. Building on the insights from previous surveys, this study aims to present the findings of the 2023 nationwide survey on surgically treated gastric cancer. By analyzing the latest data, we aim to identify recent trends in patient characteristics, surgical techniques, and treatment outcomes, providing a comprehensive overview of the current state of gastric cancer management in South Korea. These findings will inform future clinical decision-making and research directions.
Data collection This survey was conducted to retrieve information regarding all the new patients treated surgically in 2023. Before data collection, emails were sent to all KGCA members to ascertain their willingness to participate in the current survey and to request that they designate representative surgeons for each hospital to promote active correspondence. The case report form was sent to each representative surgeon in the hospital who agreed to participate in the current national survey program. Data collection was conducted from March 2024 to December 2024. The KGCA information committee reviewed the collected data and filtered suspected incorrect or missing data. The incorrect, missing, or equivocal data were queried back to the data manager in each hospital. Missing values were either treated as “not available (NA)” in the analysis of categorical data or were excluded from the analysis of continuous data. This study followed the ethical principles for medical research in accordance with the Declaration of Helsinki and obtained approval from the relevant Institutional Review Board for data collection. (representative approval No. XC24RADI0052). Patient consent was waived as the researchers collected anonymized data. Survey data The survey dataset consisted of 86 items encompassing a wide range of information, including patient demographics and medical history, surgical details, post-operative outcomes, pathology findings, and information about chemotherapy. Details about the survey items are included in . Each piece of data that was significantly altered or added in this survey compared to the previous survey is highlighted for easy identification. In the patients’ demographic characteristics, smoking and tobacco history were added. Patients’ underlying comorbidities were estimated as yes or no in each specific disease, such as diabetes and hypertension. Detailed information regarding the previous endoscopic submucosal dissection (ESD) procedure was included. The status of the surgical procedure was categorized as upfront surgery, neoadjuvant, or conversion surgery, depending on the pre-surgery treatment. In the surgical information, information regarding emergency surgery and the specific needle grasper utilized in reduced-port surgery was added. Additionally, data related to intraoperative blood transfusions and the placement of drainage tubes were included. As a significant modification, the type of trocar used in reduced-port surgery was specified. Furthermore, to reflect the diversity of anastomosis methods following proximal gastrectomy (PG), double-flap esophago-gastrostomy and esophago-gastrostomy with an anti-reflux procedure were incorporated. From the 2019 survey, post-operative complications and mortality were also examined. A post-operative complication was defined as any deviation from the normal clinical post-operative course within 30 days after surgery. Post-operative complications were classified as follows: anastomosis leakage, anastomosis stricture, duodenal stump leakage, intra-abdominal bleeding, luminal bleeding, pancreatic fistula, intra-abdominal abscess, fluid collection, wound problem, mechanical ileus, pneumonia, cerebrovascular accident, heart problem, chyle ascites, and others. Chyle ascites was added to the types of complication categories in the current survey. Additionally, the complication detection period was also investigated . Regarding pathological information, histological types were classified according to the 2010 World Health Organization (WHO) classification . Pathological staging was determined according to the eighth edition of the American Joint Committee on Cancer tumor-node-metastasis (TNM) classification system . Regarding the pathologic data, the depth of invasion was added, which includes lamina propria, muscularis mucosae, sm1, sm2, and sm3. Finally, the types of adjuvant chemotherapy and other regimens were investigated. Statistical analysis Continuous variables were presented as averages and standard deviations, and nominal variables were presented as numbers and proportions. Descriptive analyses were conducted to compare the results of the 2023 survey with the previous results since 1995.
This survey was conducted to retrieve information regarding all the new patients treated surgically in 2023. Before data collection, emails were sent to all KGCA members to ascertain their willingness to participate in the current survey and to request that they designate representative surgeons for each hospital to promote active correspondence. The case report form was sent to each representative surgeon in the hospital who agreed to participate in the current national survey program. Data collection was conducted from March 2024 to December 2024. The KGCA information committee reviewed the collected data and filtered suspected incorrect or missing data. The incorrect, missing, or equivocal data were queried back to the data manager in each hospital. Missing values were either treated as “not available (NA)” in the analysis of categorical data or were excluded from the analysis of continuous data. This study followed the ethical principles for medical research in accordance with the Declaration of Helsinki and obtained approval from the relevant Institutional Review Board for data collection. (representative approval No. XC24RADI0052). Patient consent was waived as the researchers collected anonymized data.
The survey dataset consisted of 86 items encompassing a wide range of information, including patient demographics and medical history, surgical details, post-operative outcomes, pathology findings, and information about chemotherapy. Details about the survey items are included in . Each piece of data that was significantly altered or added in this survey compared to the previous survey is highlighted for easy identification. In the patients’ demographic characteristics, smoking and tobacco history were added. Patients’ underlying comorbidities were estimated as yes or no in each specific disease, such as diabetes and hypertension. Detailed information regarding the previous endoscopic submucosal dissection (ESD) procedure was included. The status of the surgical procedure was categorized as upfront surgery, neoadjuvant, or conversion surgery, depending on the pre-surgery treatment. In the surgical information, information regarding emergency surgery and the specific needle grasper utilized in reduced-port surgery was added. Additionally, data related to intraoperative blood transfusions and the placement of drainage tubes were included. As a significant modification, the type of trocar used in reduced-port surgery was specified. Furthermore, to reflect the diversity of anastomosis methods following proximal gastrectomy (PG), double-flap esophago-gastrostomy and esophago-gastrostomy with an anti-reflux procedure were incorporated. From the 2019 survey, post-operative complications and mortality were also examined. A post-operative complication was defined as any deviation from the normal clinical post-operative course within 30 days after surgery. Post-operative complications were classified as follows: anastomosis leakage, anastomosis stricture, duodenal stump leakage, intra-abdominal bleeding, luminal bleeding, pancreatic fistula, intra-abdominal abscess, fluid collection, wound problem, mechanical ileus, pneumonia, cerebrovascular accident, heart problem, chyle ascites, and others. Chyle ascites was added to the types of complication categories in the current survey. Additionally, the complication detection period was also investigated . Regarding pathological information, histological types were classified according to the 2010 World Health Organization (WHO) classification . Pathological staging was determined according to the eighth edition of the American Joint Committee on Cancer tumor-node-metastasis (TNM) classification system . Regarding the pathologic data, the depth of invasion was added, which includes lamina propria, muscularis mucosae, sm1, sm2, and sm3. Finally, the types of adjuvant chemotherapy and other regimens were investigated.
Continuous variables were presented as averages and standard deviations, and nominal variables were presented as numbers and proportions. Descriptive analyses were conducted to compare the results of the 2023 survey with the previous results since 1995.
Participating institutions and patients Sixty-six institutions participated in this survey, and data were collected from 12,751 patients who underwent surgery for gastric adenocarcinoma in 2023. The annual number of surgeries was more than 1,000 at two institutions and between 500 and 999 at four other institutions. These six institutions accounted for 43.6% (5,555/12,751) of the total number of surgeries. Nine institutions performed 200–499 surgeries, 18 performed 100–199 surgeries, and 33 performed fewer than 100 surgeries. Age, sex, and body mass index (BMI) distribution Patients’ age, sex, pre-operative BMI, and upfront chemotherapy are presented in . The mean age was 64.6±11.6 years, which was slightly higher than that reported in the 2019 survey (62.9±11.9 years). The proportion of patients aged ≥71 years increased from 9.1% in 1995 to 31.7% in 2023, whereas the proportion of patients aged ≤40 years decreased from 13.3% in 1995 to 2.7% in 2023. The male-to-female ratio was 1.89:1, with little change since 1995. In the 2023 survey, the mean BMI was 23.9±3.5 kg/m 2 , with 60.2% of patients having a normal BMI (<25 kg/m 2 ) according to the WHO BMI classification. Among all gastric cancer patients, 97.4% underwent surgical treatment first, 1.2% received neoadjuvant chemotherapy, and 1.4% received palliative chemotherapy in 2023. Histopathological characteristics of gastric cancer The majority of tumors were single tumors (95.8%), followed by two tumors (3.7%) and three or more tumors (0.5%). In terms of tumor location, the lower third of the stomach was the most common site (53.1%), with the proportion of tumors in the upper third decreasing slightly to 16.8% compared to 2019 ( , ). The most common tumor size was between 2.0 and 3.9 cm. The macroscopic type showed no significant difference compared to the 2019 results: EGC type IIc was the most common; Borrmann type 3 was predominant among advanced gastric cancer (AGC). The distribution of tumor differentiation changed by 2023, with a decrease in poorly differentiated tumors (17.2%) and an increase in signet ring cell carcinoma tumors (23.8%). Tumor-node-metastasis stages The proportion of EGC (pT1, Nany) was comparable in 2019 and 2023 at 63.6% and 63.1%, respectively; however, the ratio of T1b (31.8%) was higher than that of T1a (31.3%) ( , ). The proportion of node positivity increased to 30.1%. There was an increase in advanced stage cancers (Stage III and IV), observed in 21.3% of cases in 2023 compared to 19.7% in 2019 ( ). presents a detailed post-chemotherapeutic pathologic (yp) classification. The frequencies of ypT3 and ypT4a were high, at 24.1% (78/324) and 23.1% (75/324), respectively, among patients who underwent surgery after chemotherapy, while no residual tumor (ypT0) was observed in 7.1% of the cases. Lymph node metastasis and distant metastasis were confirmed in 63.6% and 42.0% of patients who underwent chemotherapy followed by surgery, respectively. On average, 37.6 lymph nodes were harvested, with more than 16 lymph nodes obtained in 96.1% of the patients. Surgery-related factors The surgical approach (open vs. laparoscopic) has significantly evolved over time. The proportion of minimally invasive surgeries (laparoscopic/robotic) increased dramatically from 6.6% in 2004 to 80.3% in 2023 ( ). Detailed analysis of laparoscopic methods, including laparoscopy-assisted and totally laparoscopic approaches, has been conducted since 2014. The totally laparoscopic approach exhibited a consistent upward trend, increasing to 63.2% in 2023 ( ). In contrast, laparoscopy-assisted approaches decreased by 7.7% compared to the 2014 and 2019 data. Robotic approaches, although still less common, increased steadily from 2.1% in 2014 to 9.5% in 2023. Distal gastrectomy (DG) (72.3%) remained the most prevalent type of surgery, followed by total gastrectomy (TG) (18.6%). The proportion of PG has shown a consistent rise since 2014, reaching 3.4% in 2023. The proportion of pylorus-preserving gastrectomy was stable at 1.8%, similar to the 2014 (1.5%) and 2019 (1.7%) rates. As in 2019, most patients (≥95.0%) underwent D1+ or more extensive lymph node dissections, and curative (R0) resections were achieved in 93.9% of the cases. Reconstruction methods and surgical outcomes by approach The reconstruction methods are summarized in . In DG, Billroth II reconstruction was the most frequently performed method in 2023 (48.8%), followed by Billroth I (32.1%) and Roux-en-Y reconstruction (19.2%, including both simple and uncut methods) ( ). Since 2009, the proportion of Billroth II reconstructions has steadily increased, whereas Billroth I reconstructions have gradually declined. For PG, double tract reconstruction remained the most common method (51.9%), although its frequency has declined compared to previous years. Simple esophago-gastrostomy, double flap esophago-gastrostomy, and esophago-gastrostomy with anti-reflux were performed in 16.7%, 18.1%, and 12.8% of cases, respectively. The reconstruction methods and surgical outcomes based on the surgical approach in 2023 are detailed in . Billroth I reconstruction was the most frequently used method for laparoscopy-assisted DG (53.6%) and robotic gastrectomy (51.3%), while Billroth II was predominant in totally laparoscopic (52.2%) and open gastrectomy (46.5%). Stapler usage patterns varied by surgical approach. Circular staplers were primarily used for anastomosis in open (59.4%) and laparoscopy-assisted (53.2%) DG, while linear staplers were utilized in more than 95% of totally laparoscopic and robotic gastrectomy. In TG, circular staplers dominated in the open approach (85.5%), whereas linear staplers were more common in other surgical approaches. Blood loss during DG was lowest in the robotic approach compared to other approach. For TG, the laparoscopy-assisted method reported the least blood loss. Robotic gastrectomy required the longest operating time, while open gastrectomy was comparatively faster across both DG and TG. Post-operative morbidity and mortality Post-operative mortality data were available for 12,081 patients (94.7%), with 125 patients (1.0%) reported to have died within 30 days post-surgery or during their hospital stay ( ). Information on post-operative morbidity was obtained for 12,652 patients (99.2%), among whom 1,937 (15.3%) experienced complications. The incidence of local complications was 9.4%, while systemic complications were observed in 3.5% of patients. The most frequently reported local complication was intra-abdominal fluid collection (1.8%), followed by anastomotic leakage (1.3%), mechanical ileus (1.3%), and wound-related issues (1.2%). The incidence of chyle ascites, reported for the first time in 2023, was 0.3%. For systemic complications, pulmonary issues were the most prevalent, affecting 2.6% of the patients.
Sixty-six institutions participated in this survey, and data were collected from 12,751 patients who underwent surgery for gastric adenocarcinoma in 2023. The annual number of surgeries was more than 1,000 at two institutions and between 500 and 999 at four other institutions. These six institutions accounted for 43.6% (5,555/12,751) of the total number of surgeries. Nine institutions performed 200–499 surgeries, 18 performed 100–199 surgeries, and 33 performed fewer than 100 surgeries.
Patients’ age, sex, pre-operative BMI, and upfront chemotherapy are presented in . The mean age was 64.6±11.6 years, which was slightly higher than that reported in the 2019 survey (62.9±11.9 years). The proportion of patients aged ≥71 years increased from 9.1% in 1995 to 31.7% in 2023, whereas the proportion of patients aged ≤40 years decreased from 13.3% in 1995 to 2.7% in 2023. The male-to-female ratio was 1.89:1, with little change since 1995. In the 2023 survey, the mean BMI was 23.9±3.5 kg/m 2 , with 60.2% of patients having a normal BMI (<25 kg/m 2 ) according to the WHO BMI classification. Among all gastric cancer patients, 97.4% underwent surgical treatment first, 1.2% received neoadjuvant chemotherapy, and 1.4% received palliative chemotherapy in 2023.
The majority of tumors were single tumors (95.8%), followed by two tumors (3.7%) and three or more tumors (0.5%). In terms of tumor location, the lower third of the stomach was the most common site (53.1%), with the proportion of tumors in the upper third decreasing slightly to 16.8% compared to 2019 ( , ). The most common tumor size was between 2.0 and 3.9 cm. The macroscopic type showed no significant difference compared to the 2019 results: EGC type IIc was the most common; Borrmann type 3 was predominant among advanced gastric cancer (AGC). The distribution of tumor differentiation changed by 2023, with a decrease in poorly differentiated tumors (17.2%) and an increase in signet ring cell carcinoma tumors (23.8%).
The proportion of EGC (pT1, Nany) was comparable in 2019 and 2023 at 63.6% and 63.1%, respectively; however, the ratio of T1b (31.8%) was higher than that of T1a (31.3%) ( , ). The proportion of node positivity increased to 30.1%. There was an increase in advanced stage cancers (Stage III and IV), observed in 21.3% of cases in 2023 compared to 19.7% in 2019 ( ). presents a detailed post-chemotherapeutic pathologic (yp) classification. The frequencies of ypT3 and ypT4a were high, at 24.1% (78/324) and 23.1% (75/324), respectively, among patients who underwent surgery after chemotherapy, while no residual tumor (ypT0) was observed in 7.1% of the cases. Lymph node metastasis and distant metastasis were confirmed in 63.6% and 42.0% of patients who underwent chemotherapy followed by surgery, respectively. On average, 37.6 lymph nodes were harvested, with more than 16 lymph nodes obtained in 96.1% of the patients.
The surgical approach (open vs. laparoscopic) has significantly evolved over time. The proportion of minimally invasive surgeries (laparoscopic/robotic) increased dramatically from 6.6% in 2004 to 80.3% in 2023 ( ). Detailed analysis of laparoscopic methods, including laparoscopy-assisted and totally laparoscopic approaches, has been conducted since 2014. The totally laparoscopic approach exhibited a consistent upward trend, increasing to 63.2% in 2023 ( ). In contrast, laparoscopy-assisted approaches decreased by 7.7% compared to the 2014 and 2019 data. Robotic approaches, although still less common, increased steadily from 2.1% in 2014 to 9.5% in 2023. Distal gastrectomy (DG) (72.3%) remained the most prevalent type of surgery, followed by total gastrectomy (TG) (18.6%). The proportion of PG has shown a consistent rise since 2014, reaching 3.4% in 2023. The proportion of pylorus-preserving gastrectomy was stable at 1.8%, similar to the 2014 (1.5%) and 2019 (1.7%) rates. As in 2019, most patients (≥95.0%) underwent D1+ or more extensive lymph node dissections, and curative (R0) resections were achieved in 93.9% of the cases.
The reconstruction methods are summarized in . In DG, Billroth II reconstruction was the most frequently performed method in 2023 (48.8%), followed by Billroth I (32.1%) and Roux-en-Y reconstruction (19.2%, including both simple and uncut methods) ( ). Since 2009, the proportion of Billroth II reconstructions has steadily increased, whereas Billroth I reconstructions have gradually declined. For PG, double tract reconstruction remained the most common method (51.9%), although its frequency has declined compared to previous years. Simple esophago-gastrostomy, double flap esophago-gastrostomy, and esophago-gastrostomy with anti-reflux were performed in 16.7%, 18.1%, and 12.8% of cases, respectively. The reconstruction methods and surgical outcomes based on the surgical approach in 2023 are detailed in . Billroth I reconstruction was the most frequently used method for laparoscopy-assisted DG (53.6%) and robotic gastrectomy (51.3%), while Billroth II was predominant in totally laparoscopic (52.2%) and open gastrectomy (46.5%). Stapler usage patterns varied by surgical approach. Circular staplers were primarily used for anastomosis in open (59.4%) and laparoscopy-assisted (53.2%) DG, while linear staplers were utilized in more than 95% of totally laparoscopic and robotic gastrectomy. In TG, circular staplers dominated in the open approach (85.5%), whereas linear staplers were more common in other surgical approaches. Blood loss during DG was lowest in the robotic approach compared to other approach. For TG, the laparoscopy-assisted method reported the least blood loss. Robotic gastrectomy required the longest operating time, while open gastrectomy was comparatively faster across both DG and TG.
Post-operative mortality data were available for 12,081 patients (94.7%), with 125 patients (1.0%) reported to have died within 30 days post-surgery or during their hospital stay ( ). Information on post-operative morbidity was obtained for 12,652 patients (99.2%), among whom 1,937 (15.3%) experienced complications. The incidence of local complications was 9.4%, while systemic complications were observed in 3.5% of patients. The most frequently reported local complication was intra-abdominal fluid collection (1.8%), followed by anastomotic leakage (1.3%), mechanical ileus (1.3%), and wound-related issues (1.2%). The incidence of chyle ascites, reported for the first time in 2023, was 0.3%. For systemic complications, pulmonary issues were the most prevalent, affecting 2.6% of the patients.
The Nationwide Gastric Cancer Data Survey, first initiated in 1994, is conducted and analyzed every five years, providing valuable insights into trends and changes in gastric cancer management over time. The 2023 data collection marks the 7th iteration of this survey, continuing its legacy of contributing to the understanding of gastric cancer in Korea. While the survey interval has been reduced to align with the term of the association’s executive board, this change also reflects the need to adapt to the rapidly evolving landscape of modern healthcare, where advancements in technology, treatment modalities, and patient management occur at an unprecedented pace. By conducting the survey more frequently, we aim to better recognize and respond to emerging trends in gastric cancer, enabling timely updates to medical policies, treatment strategies, and healthcare practices that align with these changes. Owing to the ongoing medical crisis in South Korea in 2024, the number of participating institutions in this nationwide survey slightly decreased from 68 hospitals in the previous survey in 2019 to 66 hospitals in this survey. Consequently, the number of surveyed patients also decreased from 14,016 to 12,751. However, this reduction in the total number of surveyed patients in the current survey was mainly caused by the reduction in the total number of gastric cancer surgeries performed in Korea. According to statistics from the Health Insurance Review and Assessment Service open portal, the number of gastric cancer surgery claims decreased from 14,947 cases in 2019 to 14,164 cases in 2023. This trend may be attributed to the widespread implementation of health screening programs in Korea, which has led to an increase in the diagnosis of EGC and a corresponding shift toward ESD over surgical intervention. To capture this recent trend, ESD-related data were added to this survey. Additionally, the survey incorporated new categories related to surgery, reflecting the adoption of innovative surgical techniques and anastomosis methods in clinical practice. Previously ambiguous factors were also refined and subdivided for greater specificity. One of the key findings of this nationwide survey is the continued increase in the proportion of EGC among all surgically treated patients, as well as the rising proportion of EGC cases ( , ). With the progression toward a super-aged society and the continuing national health screening program, the proportion of EGC is expected to increase further. A significant proportion of EGCs can be treated endoscopically, but there remains a considerable percentage of EGC cases that require surgical intervention . Additionally, as less invasive surgical treatments, such as totally laparoscopic surgery and robotic surgery, become more widely applied in clinical practice, a greater number of elderly patients are likely to become suitable candidates for surgery. According to a multi-center retrospective study in Korea, gastric cancer surgery in elderly patients aged ≥80 years achieves reasonable long-term survival despite the increased risk of severe complications . The current study revealed that the proportion of patients aged 71 years or older was 31.7%, more than a 20% increase from the 1995 data. However, evidence remains lacking , and further research on the safety of gastric cancer surgery in older adult populations, particularly those aged 75 years and older or 80 years and older, will be essential. Meanwhile, the proportion of gastric cancer in younger patients has gradually declined during the survey period. The proportion of patients in the young-aged group (under 30 years) has consistently decreased with each survey, showing a total reduction of over 1.5% (from 1.9% in 1995 to 0.3% in 2023). The proportion of patients in the middle-aged group (from 31 to 50 years) also declined by over 9%. This trend is largely attributable to the continued decrease in Helicobacter pylori infection rates among younger age groups . However, long-term monitoring of trends in young-onset gastric cancer incidence is necessary. The histologic composition of gastric cancer in 2023 showed some differences compared to 2019, which may reflect evolving diagnostic criteria and reporting practices. The publication of the 5th edition of the WHO tumor classification in late 2019 and the updated standardized pathology report by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists in early 2023 likely influenced these trends. Notably, the WHO 5th edition clarified the diagnostic criteria for poorly cohesive carcinoma (PCC), distinguishing PCC (not otherwise specified) from PCC (signet ring cell type), which were previously used interchangeably. Although interobserver variability in histologic interpretation remains a challenge, these updates aimed to enhance diagnostic precision and reproducibility. It is anticipated that these efforts will improve consistency in histologic classification and contribute to more reliable clinicopathologic correlations. The TNM staging results show that while the overall proportion of EGC has remained stable, the proportion of pT1a cases decreased slightly relative to pT1b cases. This shift may be attributed to the increasing application of ESD for small, well-differentiated, and superficially invasive EGCs that meet the ESD criteria. Further insights into the impact of widespread ESD application on pT1 stage distribution could be obtained through a comprehensive analysis of nationwide data on ESD-treated patients with EGC. The current survey also revealed significant changes in surgical approaches for gastric cancer in Korea. A notable finding was the complete reversal in trends, with open surgery accounting for 80% of cases in 2004, while minimally invasive surgery reached 80.3% in 2023. Among the minimally invasive techniques, laparoscopic surgery has shown a steady annual increase, particularly in the proportion of totally laparoscopic procedures employing intracorporeal anastomosis. This trend may be attributed to better outcomes of minimally invasive surgery reported in studies such as KLASS-02, KLASS-04, and KLASS-05 conducted by the Korean Laparoendoscopic Gastrointestinal Surgery Study Group. This pattern is expected to continue. In Korea’s healthcare system, where the National Health Insurance covers most costs for conventional gastric cancer surgeries (open or laparoscopic), leaving patients with only 5% out-of-pocket expenses, the steady growth of robotic surgery, which requires significantly higher costs because of the lack of insurance coverage, provides important insights. Studies highlighting that robotic surgery can effectively reduce intraoperative and post-operative complications may partly explain its steady growth. Surgeons taking full control of the camera and assisting can also meet the needs of the healthcare environment, where the number of surgeons and medical staff is declining. Regarding the extent of resection, one of the most notable changes was the increase in the proportion of PG to 3.4% in 2023. Given the number of proximally located EGCs and the proportion of PG surgeries, it is likely that many patients suitable for PG will still undergo TG. However, the gradual increase in PG is significant, likely due to ongoing clinical trials and educational workshops in Korea regarding different reconstruction methods to reduce complications such as reflux after PG. While the proportion of double tract anastomosis decreased from 81.2% in 2019 to 51.9% in 2023, there was an increase in various types of esophagogastric anastomosis to prevent reflux, with double flap anastomosis being the most commonly performed, accounting for 18.1% of all PG cases. If the reflux prevention and quality-of-life benefits of these reconstructive methods are further validated by multiple studies , the adoption of PG may further increase over time. Regarding post-operative outcomes, post-operative morbidity and mortality rates were reported for the second time following the 2019 data. In 2019, the post-operative morbidity and mortality rates were 14.5% and 1.0%, respectively, while in 2023, they were 15.3% and 1.0%, respectively. The incidence rates of specific complications were similar between 2019 and 2023. Notably, data on chyle ascites were collected for the first time in 2023 and identified in 0.3% of the patients. A notable change in the 2023 survey was the inclusion of data regarding patients who underwent pre-operative chemotherapy, as well as detailed adjuvant chemotherapy regimens (TS-1, CapOx), which had not been reported in previous surveys ( ). Pre-operative chemotherapy was categorized into neoadjuvant and palliative chemotherapy ( ). In South Korea, active screening and curative treatment have traditionally been prioritized, resulting in fewer surgeries following neoadjuvant therapy compared to Western countries. However, with the recent development of chemotherapeutic agents, cases of AGC managed with neoadjuvant therapy are gradually increasing, along with instances of conversion surgery after palliative chemotherapy. This suggests that while the proportion of AGC has been gradually decreasing compared to EGC, pivotal phase 3 studies such as FLOT4, PRODIGY, and RESOLVE have emphasized the increasing importance of neoadjuvant and perioperative chemotherapy for locally AGC . Additionally, conversion surgery may be considered for certain selected patients with good responses to palliative chemotherapy, reflecting its increasing feasibility with advancements in palliative chemotherapy. Among the surveyed patients, 2,677 (21.0%) received standard adjuvant chemotherapy, with TS-1 and capecitabine plus oxaliplatin administered to 40.7% and 59.3% of these patients, respectively. Recent studies have also investigated the addition of immunotherapy in the perioperative setting, with the expectation that advancements in systemic chemotherapy will further improve outcomes for AGC. The inclusion of information on chemotherapy in this survey provides an opportunity to evaluate the role of chemotherapy in enabling surgical treatment for gastric cancer. As more cases are accumulated, future data may offer insights into the contribution of chemotherapy to conversion surgery and the outcomes of neoadjuvant therapy. The survey results also demonstrate the growing emphasis on multidisciplinary treatment strategies in gastric cancer, moving beyond surgery to personalized, tailored therapies. This shift highlights the increasing recognition of preoperative chemotherapy as part of a multidisciplinary approach to optimize treatment outcomes. In conclusion, although the current study did not encompass all gastric cancer surgeries performed in Korea in 2023, the results of the 2023 nationwide survey provide a comprehensive overview of the current status of gastric cancer treatment in Korea. This information will serve as a foundation for future gastric cancer research.
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Cornea specialists are the highest opioid prescribers at a large academic eye institute in the USA | 562c8abc-849f-4660-a17c-e59dd36a2cbd | 11877224 | Ophthalmology[mh] | The opioid epidemic, declared a public health crisis in 2017, has resulted in a significant number of overdose deaths, with a notable increase from 47 000 in 2018 to 81 000 000 in 2023. Previous research indicates that many heroin users were initially introduced to opioids through prescription drugs. While primary care and pain management specialists prescribe the majority of opioids, surgical specialties, including ophthalmology, also contribute to opioid prescriptions. Despite ophthalmologists prescribing fewer opioids than average, there has been a reported increase in opioid prescriptions following ocular surgeries. This study reveals that the cornea department at a large academic eye centre is responsible for a third of all opioid prescriptions, with over 50% of corneal crosslinking patients receiving opioids postprocedure. The study highlights that most of these prescriptions had low morphine equivalent doses and limited refills. Additionally, it was found that trainees, particularly fellows, wrote a significant portion of these prescriptions, indicating a potential gap in opioid prescribing training among ophthalmology trainees. The findings emphasise the need for standardised opioid prescribing guidelines in ophthalmology, particularly for corneal procedures, to mitigate opioid misuse. The study suggests that future guidelines should be distributed to both trainees and faculty to ensure comprehensive education on opioid management. Moreover, the results underscore the importance of developing opioid-sparing pain therapies and addressing geographic disparities in opioid prescribing patterns. This study could inform policy changes and training programmes to better equip ophthalmologists in managing postoperative pain while reducing the risk of long-term opioid dependence. The opioid epidemic was declared a public health crisis in 2017, and the current opioid epidemic has led to a staggering number of deaths per year from drug overdose, with nearly 47 000 deaths in 2018 alone, and almost doubling to a record 81 000 deaths in 2023. This is notable since approximately 645 000 deaths were reported from prescription or illicit opioid overdose in the 22 years between 1999 and 2021. While primary care providers and pain management specialties prescribe the most opioids overall, surgical specialties also contribute to opioid prescriptions in routine postoperative care. Prior investigations for opioid-naïve patients undergoing major and minor surgical procedures suggest that about 6% continue to fill opioid prescriptions more than 3 months later. Opioid use following ophthalmic surgeries has been recently noted to predispose patients significantly more to opioid overdose, hospitalisations and mortality. Thus, it is important to continue to understand and raise awareness of surgeons’ opioid prescription patterns for postoperative pain control in the current opioid epidemic. Opioid management training for prescribers varies across the USA. Several national surveys of trainees from different surgical specialties (eg, general surgery, plastic surgery, cardiac surgery and otolaryngology) found a high variability in the amount of training received for opioid prescribing during medical school and residency. Moreover, a survey of general surgery training programmes found that roughly two-thirds of surgical residents reported feeling that they had received inadequate training in prescribing opioids. A quality improvement study of over 5000 ophthalmic surgeries showed a reduction of overprescribing opioids in opioid-naïve patients after implementation of a standardised opioid prescribing guideline at a single academic institution. These guidelines have been supported by the American Board of Ophthalmology and can be reviewed for maintenance of certification credit for all participating ophthalmologists. Similar guidelines have been demonstrated to be effective in other specialties as well. Postoperative opioid prescribing for pain management is of particular interest to cornea surgeons given the unique sensory characteristics of the cornea. The cornea is the most densely innervated tissue in the human body, with approximately 7000 nociceptors per square millimetre, making it 300 to 600 times more sensitive than skin. This dense sensory innervation originates from the ophthalmic division of the trigeminal ganglion, with extensive branching into the subbasal nerve plexus that supplies the corneal epithelium. As a result, even minor corneal injuries can cause significant pain and frequently prompt emergency department visits. For corneal surgical procedures, such as photorefractive keratectomy (PRK), phototherapeutic keratectomy and corneal crosslinking, postoperative pain is common and often severe, correlating with nerve fibre exposure, epithelial damage and stromal tissue ablation. Given the acute pain associated with these procedures and the relatively slow recovery of corneal nerves, opioids are frequently prescribed for short-term pain management. With this growing insight into the role ophthalmologists may play in the current opioid epidemic, as well as the variability in opioid management education among trainees, we sought to evaluate the opioid prescription pattern across ophthalmic subspecialties at a large academic eye centre. We also examined the level of prescriber training to better understand who is prescribing opioids. We conducted a retrospective cohort study at a single academic ophthalmology centre. All opioid prescriptions written for patients 18 years or older in the year 2018 were included in our analysis. Prescriptions were identified through electronic medical records. For each prescription, the patient demographics, the associated primary procedure or diagnosis code and the prescriber information were collected. All opioid prescriptions were collected, regardless of association with a procedure. A prescription was considered a duplicate and excluded if it included identical prescription information and was written within 1 hour of each other. If an alternate prescription was written within 1 hour of the first prescription, then this first prescription was excluded, and the latter prescription data was collected. The department of the prescriber was categorised into subspecialties including cornea, oculoplastics, retina, strabismus, glaucoma, comprehensive ophthalmology or uveitis. The training level of each prescriber was categorised as either an attending, fellow or resident. Descriptive statistics were calculated with means±SD for continuous variables, as well as frequencies and percentages for categorical variables. Statistical analysis was performed using SAS software (V.9.2, USA). Research ethics approval Massachusetts General Brigham’s Institutional Review Board (IRB) declared this study (2019P000259) exempt from review as all data were deidentified; thus, patient consent was waived. Hence, the IRB/Ethics Committee ruled that approval was not required for this study. All research adhered to the tenets of the Declaration of Helsinki. Patient and public involvement statement Patients and the public were not involved in any way. Massachusetts General Brigham’s Institutional Review Board (IRB) declared this study (2019P000259) exempt from review as all data were deidentified; thus, patient consent was waived. Hence, the IRB/Ethics Committee ruled that approval was not required for this study. All research adhered to the tenets of the Declaration of Helsinki. Patients and the public were not involved in any way. Total unique opioid prescriptions and patient characteristics Our study found that in 2018, a cumulative 75 412 ophthalmic procedures were performed at Massachusetts Eye and Ear (MEE) , large academic eye centre and 1654 (2.2%) unique opioid prescriptions were written . The patients who received prescriptions were 51.4% (n=851) female, 65.56% (n=1084) White and with an average age of 52.3±18.5 (range 18–95 years) . Opioid prescriptions and their morphine equivalent dose (MED) Oxycodone 5 mg tablets were most prescribed (n=553, 33.4%), followed by hydrocodone 5mg-acetaminophen 300 mg tablets (n=381, 23.0%) and oxycodone 5 mg–acetaminophen 325 mg tablets (n=368, 22.2%) . In terms of morphine equivalent dose (MED), 7.5 MED was the most prescribed dosage (n=921, 55.7%). Most prescriptions were written for 10 pills (mean 12.4±6.6 pills, median 10, mode 10). The range of pills dispensed was from 1 pill to 60 pills. Most had 0 refills (mean 0.0±0.01 refills, median 0, mode 0), with a single prescription of 1 refill and a single prescription of 3 refills. Patients and ophthalmic procedures receiving opioids Of the 453 opioid prescriptions from the cornea department, the majority were for cornea crosslinking (237 prescriptions, 52.3% of all crosslinking procedures) . Other less common cornea procedures associated with an opioid prescription included PRK (96), superficial keratectomy (53), phototherapeutic keratectomy (36), penetrating keratoplasty (31), pterygium excisions (28), deep anterior lamellar keratoplasty (9), conjunctival biopsy (8), Descemet membrane endothelial keratoplasty (7), Descemet stripping endothelial keratoplasty or Descemet stripping automated endothelial keratoplasty (7), laser-assisted in situ keratomileusis (LASIK) or LASIK revisions (7), amniotic membrane grafting (6) and cryotherapy (3). Additional opioid prescriptions were given for cornea diagnoses but had no associated procedure, including Acanthamoeba keratitis (9), ocular graft-versus-host disease (oGVHD) (3), recurrent corneal erosion (3), corneal chemical injury (2) and zoster ophthalmicus (1). Of the 367 opioid prescriptions from the oculoplastics department, the majority were for blepharoplasty (185 prescriptions, 17.8% of all blepharoplasty procedures) . Other opioid prescriptions associated with common oculoplastics procedures included enucleation or eviscerations (73, 50.7%), ptosis repair (43, 2.3%), entropion or ectropion repair (24, 4.3%), dacryocystorhinostomy (19, 3%), orbitotomy/orbital fracture repair/orbital decompression (18, 4.5%), brow ptosis repair (six prescriptions, 1%) or canalicular repair or punctoplasty (five prescriptions, 2.3%). Other less common procedures associated with an opioid prescription included post-Mohs reconstruction (22), eyelid or conjunctival biopsy (11), incision and drainage of abscess (2) and temporal artery biopsy (2). Other opioid prescriptions for oculoplastics diagnosis but without an associated procedure included orbital fractures without repair (3) and facial cellulitis (1). Of the 305 opioid prescriptions from the retina department, the majority were for pars plana vitrectomy (136 prescriptions, 1.8% of pars plana vitrectomy procedures) . Other retina procedures that had associated opioid prescriptions included tantalum marker ring placement (89, 26.1%) and scleral buckle (60, 7.3%). Other less common procedures associated with an opioid prescription included intravitreal injections (6), panretinal photocoagulation (4) and transscleral biopsy (2). Other opioid prescriptions for retina diagnoses without an associated procedure included panuveitis or scleritis (4), vitreous haemorrhage secondary to trauma (2) and retinal necrosis (1). There were 127 opioid prescriptions following strabismus surgery (11.2% of all strabismus surgeries) . 97 were following cyclophotocoagulation (9.6% of all cyclophotocoagulations). 37 opioid prescriptions were following open globe repairs (17% of all open globe repairs). 10 were following small incisional cataract surgery (0.1% of all cataract surgeries). Opioid prescription patterns of ophthalmology prescribers and departments Analysis of the prescription by individual prescriber revealed 97 unique prescribers, over half of which were trainees (25.8% residents and 27.8% fellows) . Analysis of the prescribers per individual prescription showed that 283 (17.1%) prescriptions written by residents versus 521 (31.5%) prescriptions were written by fellows . When looking by department, the departments with the most unique prescribers were cornea (22; 22.7%) and retina (22; 22.7%) . This analysis excluded residents who are not assigned to a specific department, but overall had the highest percentage of individual prescribers (25; 25.8%). We also examined the total number of individual opioid prescriptions, since some providers will write more than one and a few patients received more than one prescription. For the total number of prescriptions, most were written by the cornea (32.8%) department, followed by the oculoplastics (22.2%) and retina departments (18.5%) . Our study found that in 2018, a cumulative 75 412 ophthalmic procedures were performed at Massachusetts Eye and Ear (MEE) , large academic eye centre and 1654 (2.2%) unique opioid prescriptions were written . The patients who received prescriptions were 51.4% (n=851) female, 65.56% (n=1084) White and with an average age of 52.3±18.5 (range 18–95 years) . Oxycodone 5 mg tablets were most prescribed (n=553, 33.4%), followed by hydrocodone 5mg-acetaminophen 300 mg tablets (n=381, 23.0%) and oxycodone 5 mg–acetaminophen 325 mg tablets (n=368, 22.2%) . In terms of morphine equivalent dose (MED), 7.5 MED was the most prescribed dosage (n=921, 55.7%). Most prescriptions were written for 10 pills (mean 12.4±6.6 pills, median 10, mode 10). The range of pills dispensed was from 1 pill to 60 pills. Most had 0 refills (mean 0.0±0.01 refills, median 0, mode 0), with a single prescription of 1 refill and a single prescription of 3 refills. Of the 453 opioid prescriptions from the cornea department, the majority were for cornea crosslinking (237 prescriptions, 52.3% of all crosslinking procedures) . Other less common cornea procedures associated with an opioid prescription included PRK (96), superficial keratectomy (53), phototherapeutic keratectomy (36), penetrating keratoplasty (31), pterygium excisions (28), deep anterior lamellar keratoplasty (9), conjunctival biopsy (8), Descemet membrane endothelial keratoplasty (7), Descemet stripping endothelial keratoplasty or Descemet stripping automated endothelial keratoplasty (7), laser-assisted in situ keratomileusis (LASIK) or LASIK revisions (7), amniotic membrane grafting (6) and cryotherapy (3). Additional opioid prescriptions were given for cornea diagnoses but had no associated procedure, including Acanthamoeba keratitis (9), ocular graft-versus-host disease (oGVHD) (3), recurrent corneal erosion (3), corneal chemical injury (2) and zoster ophthalmicus (1). Of the 367 opioid prescriptions from the oculoplastics department, the majority were for blepharoplasty (185 prescriptions, 17.8% of all blepharoplasty procedures) . Other opioid prescriptions associated with common oculoplastics procedures included enucleation or eviscerations (73, 50.7%), ptosis repair (43, 2.3%), entropion or ectropion repair (24, 4.3%), dacryocystorhinostomy (19, 3%), orbitotomy/orbital fracture repair/orbital decompression (18, 4.5%), brow ptosis repair (six prescriptions, 1%) or canalicular repair or punctoplasty (five prescriptions, 2.3%). Other less common procedures associated with an opioid prescription included post-Mohs reconstruction (22), eyelid or conjunctival biopsy (11), incision and drainage of abscess (2) and temporal artery biopsy (2). Other opioid prescriptions for oculoplastics diagnosis but without an associated procedure included orbital fractures without repair (3) and facial cellulitis (1). Of the 305 opioid prescriptions from the retina department, the majority were for pars plana vitrectomy (136 prescriptions, 1.8% of pars plana vitrectomy procedures) . Other retina procedures that had associated opioid prescriptions included tantalum marker ring placement (89, 26.1%) and scleral buckle (60, 7.3%). Other less common procedures associated with an opioid prescription included intravitreal injections (6), panretinal photocoagulation (4) and transscleral biopsy (2). Other opioid prescriptions for retina diagnoses without an associated procedure included panuveitis or scleritis (4), vitreous haemorrhage secondary to trauma (2) and retinal necrosis (1). There were 127 opioid prescriptions following strabismus surgery (11.2% of all strabismus surgeries) . 97 were following cyclophotocoagulation (9.6% of all cyclophotocoagulations). 37 opioid prescriptions were following open globe repairs (17% of all open globe repairs). 10 were following small incisional cataract surgery (0.1% of all cataract surgeries). Analysis of the prescription by individual prescriber revealed 97 unique prescribers, over half of which were trainees (25.8% residents and 27.8% fellows) . Analysis of the prescribers per individual prescription showed that 283 (17.1%) prescriptions written by residents versus 521 (31.5%) prescriptions were written by fellows . When looking by department, the departments with the most unique prescribers were cornea (22; 22.7%) and retina (22; 22.7%) . This analysis excluded residents who are not assigned to a specific department, but overall had the highest percentage of individual prescribers (25; 25.8%). We also examined the total number of individual opioid prescriptions, since some providers will write more than one and a few patients received more than one prescription. For the total number of prescriptions, most were written by the cornea (32.8%) department, followed by the oculoplastics (22.2%) and retina departments (18.5%) . Ophthalmologists, like other providers, must balance adequate management of acute post-operative pain with long-term risks of opioid dependence to help reduce opioid misuse. This is especially true, since it was reported that about 10% of patients do not experience sufficient postoperative pain control. Overall, ophthalmologists in the USA prescribe opioids less than some providers, accounting for an estimated 4–8% of the total ophthalmic prescriptions; yet a recent study found a sustained increase in filled opioid prescriptions due to ocular surgeries between 2000 and 2016. A large healthcare claims-based study found that 3.4% of opioid-naïve patients who received an initial opioid prescription at the time of incisional ophthalmic surgery had new, persistent opioid use after the perioperative period. Therefore, ophthalmologists still play an important role in the opioid epidemic. In our study, the opioid prescriptions had a low MED with an average of 7.5. The opioid prescriptions also had a limited number of pills dispensed (12.4±6.75), and most were without refills (0.0±0.01, range 0–3). While the overall prescriptions were low and had a low MED in our study, patients who were prescribed opioids within 7 days of ambulatory surgery were reported to be 44% more likely to become long-term users. Also, a short course of prescribed opioids after ophthalmic surgery was recently reported to significantly increase the rates of patient chronic opioid overdose, hospitalisations and mortality. Importantly, a large study on opioid-naïve patients undergoing ophthalmic surgery suggested that 3.4% of patients continued to use opioids, despite low morphine equivalents. These reports are notable when considering strategies to mitigate opioid abuse, since ophthalmologists are known to typically prescribe 5-day opioid supplies. Approaches for reducing opioid prescriptions, while still effectively managing postoperative pain due to ophthalmic surgeries, have ranged from oral or intravenous non-narcotic alternatives including pregabalin, acetaminophen and ibuprofen, ketorolac, memantine and local anaesthetics (eg, bupivacaine, lidocaine, diluted proparacaine) that prevent pain development to novel therapies, such as a tetracaine-eluting contact lens that provides sustained and controlled pain relief. Corneal injury represented an estimated 337 000 annual emergency department visits in the USA between 2010 and 2018, and cornea specialists are some of the most frequent opioid prescribers as their patients are often predisposed to significant pain. The cornea has more nerve endings than any other part of the body, and current pain control methods for the ocular surface are limited. Topical anaesthetics are well known to cause ocular morbidities, particularly corneal toxicity, so systemic opioids may be prescribed for severe pain. Indeed, we found that most opioid prescriptions at our institution came from the cornea department. Similarly, a cohort study of patients undergoing cornea surgery found that 70% to 90% of patients received an opioid prescription, likely due to the high proportion undergoing surface ablative procedures. Another more recent study reported a range of 77.2 to 83.9% of cornea physicians prescribing opioids. Furthermore, we found that 2.2% of all ophthalmic procedures were associated with an opioid prescription. A similar rate of opioid prescriptions was reported by a large study on US insurer’s claims database, which found that 1.9% of incisional ocular surgeries had an associated opioid prescription, but the rate increased to 6.1% for corneal surgeries alone. The procedure with the highest associated opioid prescription was corneal crosslinking, where 52.3% of procedures received an associated opioid prescription. No previous study to our knowledge has reported on opioid prescription patterns associated with corneal crosslinking, despite it being well established that cornea specialists are frequent opioid prescribers. Opioid prescriptions were also provided in the non-operative setting for ocular pain control. Within the cornea department, opioid prescriptions were provided for cornea diagnoses such as Acanthamoeba keratitis, oGVHD, recurrent corneal erosions, zoster ophthalmicus and corneal chemical injuries. Thus, ophthalmologists, and in particular cornea specialists who are prescribing opioids for pain management, should be aware of the potential need for additional pain control for their patients in the non-operative setting. This is of particular importance as there is strong evidence for only minimal short-term benefits to opioid prescribing, while research on the potential long-term benefits remains limited. This study also highlights the role of trainees, particularly fellows, in prescribing opioids postoperatively at our institution. Of the 97 unique providers who wrote opioid prescriptions, about half were trainees (25.8% residents, 27.8% fellows, 46.4% attendings). Of the total 1655 unique opioid prescriptions written, 17.0% were written by residents, 31.5% by fellows and 60.1% by attendings. While several studies have highlighted a lack of opioid training among surgical residents, there are no surveys on opioid training among ophthalmology residents or fellows. It is possible that similar medical school curricula have left a gap in knowledge in this area. A small survey of general surgical residents found that the majority expressed a preference for more formal training or guidelines for opioid prescriptions for routine postoperative management. There has been a recent call to standardise opioid prescriptions and create guidelines within ophthalmology, and our study suggests that future guidelines should be distributed to trainees as well as faculty to reach the most common prescribers. For instance, a study evaluating the effect of state-level policies on opioid prescribing patterns showed that the enactment of the Michigan Opioid Laws in 2017 and 2018 led to a reduced number of opioid prescriptions for oculoplastic procedures. Similarly, another more recent study including almost 20 000 ophthalmologists across the USA reported a significant annual reduction in prescribed opioids from 2016 to 2018 for the cornea, retina, glaucoma and comprehensive ophthalmology subspecialties. However, these state-level policies are variable and may not uniformly impact trainees. This agrees with our findings, where although the cornea, oculoplastics and retina subspecialties consistently had the most opioid prescribers at our institute as across the USA, each one prescribed about three to four times less than the national average in 2018: cornea (77.2% vs 32.8%), oculoplastics (86% vs 22.2%) and retina (54.5% vs 18.5%). Our findings further suggest a geographic disparity in opioid prescribing patterns, which was previously reported as well. Additionally, the fact that trainees may train for residency in one state and undergo fellowship in another may additionally pose a challenge for trainees. The strengths of this study include that it was performed at a large academic eye institute, with a wide range of procedures performed and subspecialties surveyed. Moreover, we contributed data to the limited knowledge on opioid prescribing patterns regarding procedures and subspecialties previously not reported. This further included newly found differences in prescribing habits between trainee and non-trainee ophthalmologists. In terms of study limitations, the retrospective chart-based review prevents us from confirming whether the opioid prescriptions were actually filled or taken. However, this provides data on the ophthalmologists’ perception of post-operative pain needs and is not necessarily representative of the patients’ actual pain medication needs. Additionally, the results reflect the practice patterns of only a single institution and are extracted based on primary procedure codes. Therefore, the results may reflect individual or departmental practices rather than overall field trends and may not capture the full extent of the surgery if multiple procedures were performed. We also did not assess whether the patient was opioid-naïve, which may necessitate higher MED for equivalent pain control. Finally, another limitation is that an evaluation of the association between provider and patient characteristics to opioid prescribing was not performed. The opioid epidemic in the USA has spurred significant changes in prescribing practices across medical specialties, including ophthalmology. Regulatory frameworks, such as the Centers for Disease Control and Prevention opioid prescribing guidelines and Drug Enforcement Administration oversight, have tightened access to opioids, encouraging clinicians to seek non-opioid alternatives wherever possible. Globally, approaches to corneal pain management and opioid prescribing vary widely, influenced by healthcare infrastructure, cultural attitudes and regulatory policies. In high-resource settings such as Europe and Australia, opioid use is also limited, with greater emphasis on non-opioid therapies and multidisciplinary approaches. In contrast, low-resource settings often face significant barriers to care, including limited access to advanced diagnostic tools and medications, resulting in a reliance on traditional remedies or over-the-counter analgesics. Middle-income countries, such as India and Brazil, are navigating an intermediate landscape, with increasing access to advanced care but ongoing variability in provider training and opioid regulation. Furthermore, specialised pain clinics in many high-income countries serve as a structured and safer pathway for opioid access when necessary. These clinics, often led by anaesthesiologists with multidisciplinary teams, provide comprehensive pain management, integrating psychological support and non-opioid therapies alongside carefully monitored opioid prescriptions to minimise misuse risk. Given their success in balancing pain relief with opioid stewardship, expanding access to specialised pain clinics in the USA may offer a safer, more controlled alternative to widespread opioid prescribing. The American Society of Interventional Pain Physicians (ASIPP) has published guidelines emphasising the importance of comprehensive assessment and monitoring in specialised settings to ensure safe opioid use within a structured framework. This model could ensure that patients requiring opioids receive them within a multidisciplinary framework that prioritises both efficacy and safety. Research on practice-specific postoperative opioid prescribing for pain management in ophthalmology continues to be of importance. Addressing the opioid epidemic in the field of ophthalmology will require raised awareness and better understanding of the practice patterns of opioid prescriptions, both in the operative and non-operative setting. While opioid prescriptions are generally low for ophthalmic procedures across departments, this study highlights that cornea specialists accounted for nearly a third of opioid prescriptions. Further understanding of postprocedural corneal surface pain management, opioid tapering guidelines, geographic disparities and developing opioid-sparing pain therapies is needed. |
A simple do-it-yourself model of phacoemulsification for resident training | 3b422120-96e4-446a-8382-97755ad5f333 | 8597513 | Ophthalmology[mh] | The simple DIY model comprises a small rubber ball, on which a crater is created with the help of a sharp-edged blade. The depth of crater in the periphery is 3 mm and at the centre 5 mm, with diameter of crater being 9 mm. The nucleus is made with the help of cornflour (Weikfield Foods, India), one standard teaspoon with water in equal amounts, and 1 mL of feviglue (Pidilite, India). To harden the nucleus, one can use double amounts of cornflour. The mixture is heated for 2 min, which results in a dough-like consistency from which model lens nucleus is made. The lens is then placed on the crater created, and above it, an artificial cornea is placed. Such corneas can be obtained from already used, discarded single-use wax eyes. The artificial cornea is fixed to the rubber ball with the help of Fevikwik (Pidilite, India) and a watertight chamber with adequate depth is created [Fig. - ]. The model is then mounted on the mannequin head and phacoemulsification steps like sculpting, chopping and foldable intraocular lens insertion can be practised [ and ]. Once the surgery has been performed, the cornea can again be separated from rubber ball and another artificial ‘lens’ can be again placed in crater and repeat cycles of surgical practices can be performed. The lens is made so as to resemble the human lens, with a less convex anterior surface and a more convex posterior surface to fit in the crater created, with an adequate distance being left between the cornea and lens. The model was used for initial phacoemulsification training by five residents. The residents were given a questionnaire at the end of practice session. All five residents found the session to be useful, in helping them to gain confidence in performing the sculpting and chopping. Two of the five residents found the model to have tissue handling experience similar to human tissue.
Wet-lab training is of immense value to boost the confidence of the young trainee residents. A large number of training models for resident training have been described, but most of them are not feasible and are not cost-effective. Animal eyes are an inexpensive training model for cataract surgery. The common problems encountered during goat’s eye cataract surgery training include the soft nucleus, pre-existing posterior capsule rupture and subluxation of lens caused during the animal eye enucleation. As a result of this, it becomes difficult to train the residents in various steps of phacoemulsification. Various artificial eyes like phaco-I (Madhu instruments) and Kitaro eye sets are available, but these options are for single use only and not cost-effective. The Kitaro eye set cost around. Our model can be used multiple times and the cost of its preparation is as low as Rs. 30. The limitation of our model is that capsulorrhexis cannot be practised upon, but it helps to gain the hand–foot–eye and sound coordination for residents who want to master phacoemulsification.
Thus, to conclude the “Do it yourself” model is a simple and cost effective option for the basic phaco-emulsification training of the residents. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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Comparative Metabolomic Analysis and Antinociceptive Effect of Methanolic Extracts from | 6213a4cf-f3ec-408f-9fc4-95a0761f7708 | 11597310 | Biochemistry[mh] | The species of the genus Salvia L. have been used throughout the world for their broad spectrum of biological activities, to name a few, they have been used for the treatment of digestive problems, cardiovascular and cerebrovascular diseases, pain, bronchitis, cough, asthma, inflammation, depression, anxiety, insomnia, and skin conditions [ , , , ]. Pharmacological studies report its antioxidant, antidiabetic, antiviral, antinociceptive, anti-inflammatory, anti-Alzheimer, and antitumor properties, among others. Terpenoids, phenolic acids, and flavonoids are compounds responsible for the medicinal effects of sage [ , , , , , , ]. Regarding the analgesic properties of Salvia , there is evidence in the literature of its effect through different models of nociceptive and inflammatory pain in rodents. The ethanolic extract of S. plebeia R.Br. presents pharmacological activity in the abdominal pain model and in the inflammatory process induced in the carrageenan test . The hydroalcoholic extract of S. officinalis L. produces antinociceptive and anti-inflammatory effects in abdominal stretching, formalin and carrageenan tests . Likewise, the hydroalcoholic extract of S. miltiorrhiza Bunge has analgesic and anti-inflammatory effects using the collagen-induced arthritis model . Similarly, the ethanolic extract of S. lachnostachys Benth. had good activity both in the formalin test and the anti-arthritis model . Mexico is considered one of the areas with the greatest diversity of the Salvia genus in the world, represented by around 307 species . Almost all Mexican salvias (sages) species are included within the subgenus Calosphace . From ancient times to the present, various species of Salvia have been known for their wide range of ornamental, cosmetic, culinary and medicinal uses [ , , , ]. The last one is the most notable, as there are around 56 species belonging to the subgenus Calosphace used in traditional Mexican medicine to treat various diseases of the digestive system, nervous disorders, pregnancy, childbirth and postpartum, and other culture-bound syndromes . Within the wide spectrum of properties of traditionally used Mexican salvias, analgesic stands out [ , , ]. Some examples of sages with this characteristic are S. microphylla Kunth, S. coccinea Buc’hoz ex Etl., S. lavanduloides Kunth, S. elegans Vahl, S. polystachia Cav., S. leucantha Cav., S. mexicana L., S. hispanica L., S. amarissima Ortega, and S. tiliifolia Vahl, of which the aerial part is used, prepared as an infusion, to treat pain, mainly in south-central Mexico (Yucatan, Chiapas, Oaxaca, Guerrero, Morelos, Michoacan) [ , , , , , , , , , ]. Despite the analgesic properties of Mexican salvias, most in vitro, in vivo and ex vivo studies, both of extracts and isolated compounds, have been mainly directed to the evaluation of antimicrobial and cytotoxic effects [ , , ]. Only the species S. amarissima (Syn. S. circinate Cav.), S. purpurea Cav., S. semiatrata Zucc., and S. tiliifolia of the subgenus Calosphace have been evaluated in antinociception models. Studies have reported no acute oral toxicity of the extracts and a significant reduction in nociception of extracts of different polarity, at doses between 100 and 300 mg/kg, administered orally (p.o.), as well as of isolated compounds of diterpene nature (amarisolide A, tilifodiolide and 7-keto-neoclerodan-3,13-dien-18,19:15,16-diolide) and phenolic (pedalitin) at doses of 1–10 mg/kg, p.o. [ , , , ]. The potent antinociceptive effect of compounds of this nature, isolated from other botanical families, has been corroborated in in vivo tests [ , , , ]. In relation to the above, it should be noted that various phytochemical studies of approximately 50 species of Salvia of the subgenus Calosphace have reported the presence of secondary metabolites of terpene and phenolic nature, with diterpenes (abietane, clerodane, labdane and pimarane) being the most abundant, even postulated as chemotaxonomic markers [ , , , ]. S. cinnabarina M.Martens & Galeotii, S. lavanduloides and S. longispicata M.Martens & Galeotii, are three species of the subgenus Calosphace , used in tea form for analgesic purposes in traditional Mexican medicine and that have a wide distribution in Mexican territory, with the exception of the Baja California peninsula . There are no reports on the antinociceptive potential in in vivo models and little is known about its phytochemistry. Therefore, in this study, the chemical composition is explored by means of an untargeted metabolomic analysis, using ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UPLC-ESI +/− -MS-QTOF), for the identification of a significant number of specialised metabolites in the selected species. Likewise, acute oral toxicity is evaluated following the Organisation for Economic Co-operation and Development (OECD) Guidelines for the Testing of Chemicals (2001), and antinociceptive activity using the formalin test of methanol extract by oral route .
2.1. Chemical Profiling via Ultra Performance Liquid Chromatography Coupled to Mass Spectrometry Quadrupole Time of Flight (UPLC-ESI +/− -MS-QTOF) 2.1.1. Preliminary Comparison of the Retention Time-Mass/Charge Features Between Salvia Species A preliminary comparative analysis of the constitution of retention time-mass/charge (rt- m / z ) features obtained by UPLC-ESI +/− -MS-QTOF, of the three sages, shows that they share a low percentage of similarity between them. This is visualised by the Venn diagram ( A) and the principal component analysis (PCA) ( B), which indicate that the three salvias do not group together by similarity in their rt- m / z profile. 2.1.2. Difference in Chemical Composition of Sages The experimental m / z values obtained from the three sages compared with the data reported from molecules previously isolated from Mexican Salvia species allowed the tentative identification of 46 metabolites including five phenolic acids, 13 flavonoids, 24 diterpenes and four triterpenes. shows the chromatographic (rt) and spectrometric ( m / z ) data for each compound. It is important to note that when comparing the historical data of compounds previously isolated from Mexican salvias with the experimental data, only 46 data points were correlated with a mass error of less than 5 ppm in negative mode and one in positive mode. The positive value corresponds to kaempferol, which is also identified in negative mode. Both are indicated as compound 18 with the following notation: Kaempferol*, in positive mode, was identified in S. cinnabarina and Kaempferol**, in negative mode, in S. lavanduloides . The most relevant results are briefly mentioned. Diterpenes were the group with the highest number of molecules identified in the extracts of sages ( , No. 19 – 42 ), detected in rt from 6.54 to 12.16 min. The abietanes and clerodanes stand out with 14 and 8 structures, respectively. The abietanes ( 29 , 30 , 32 – 34 , 36 ), clerodane 23 , pimarane 41 and labdane 42 were identified in S. cinnabarina . The abietanes ( 27 , 28 , 34 , 35 , 38 – 40 ) and the clerodanes, amarisolide F ( 19 ) and salvixalapadiene ( 21 ) were present in S. longispicata . Furthermore, seven clerodanes ( 19 – 22 , 24 – 26 ) and three abietanes (27 , 31 , 37 ) were detected in S. lavanduloides , identified as 16-hydroxycarnosic acid, 16-acetoxycarnosic acid and 7α-acetoxy-6,7 dihydroicetexone, respectively. Flavonoids were the second largest group with 13 compounds identified ( 2 , 4 – 8 , 10 – 12 , 15 – 18 ). Rutin ( 5 ) was present in all three salvias, whereas luteolin-7-O-glucuronide ( 8 ), apigenin ( 12 ) and 5,6-dihydroxy-7,3′,4′-trimethoxy ( 17 ) were only present in S. cinnabarina . Schaftoside ( 2 ), quercetin ( 11 ) and kaempferol ( 18 ) were found in S. lavanduloides . Also, cyanidin 3,5-diglucoside ( 4 ) and miquelianin ( 6 ) were identified only in S. longispicata . Phenolic acids were the third group identified ( 1 , 3 , 9 , 13 and 14 ) at a retention time of 0.52, 3.41, 4.67, 5.2 and 5.37 min, respectively. Compound 1 , identified as sagerinic acid, represented by the molecular ion m / z 719.1643, was detected only in S. cinnabarina . Syringic acid ( 3 ) with an ion m / z at 197.0449 was found in S. longispicata and salvianolic acid A ( 14 ) with m / z at 493.1141 in S. lavanduloides . Rosmarinic acid ( 13 ) with an ion m / z at 359.0775 was present in all three salvias. Finally, triterpenoids were identified as a fourth group, an oleanane derivative ( 43 ) was only present in S. cinnabarina , while 3-hydroxyestran-17-one ( 44 ) and an ursane derivative ( 45 ) were found in all three salvias ( ). The chemical structures of the identified compounds are shown in A. The comparative analysis of the chemical composition of the three sages using a Venn diagram ( B) showed that S. lavanduloides shares more compounds with S. longispicata ( 7 , 16 , 19 , 21 , 27 ), corresponding to quercetin glycoside, pedalitin, amarisolide F, salvixalapadiene, and 16-hydroxycarnosic acid, respectively. Three metabolites are common between S. cinnabarina and S. longispicata : salviaflaside ( 9 ), 5,6-dihydro-6α-hydroxysalviasperanol ( 34 ) and 2-hydroxyursolic acid ( 46 ). Likewise, rhamnetin 3-glucoside ( 10 ), luteolin ( 15 ) and kaempferol ( 18 ) were identified in S. cinnabarina and S. lavanduloides . Of these compounds, only four are shared between the three species: rutin ( 5 ), rosmarinic acid ( 13 ), 3-hydroxyestran-17-one ( 44 ), and 11β-hydroxy-3-oxo-urs-12-en-28-oic acid ( 45 ) ( B). In S. cinnabarina , 13 chemical constituents were identified as unique ( 1 , 8 , 12 , 17 , 23 , 29 , 30 , 32 , 33 , 36 , 41 , 42 , 43 ), 10 in S. lavanduloides ( 2 , 11 , 14 , 20 , 22 , 24 , 25 , 26 , 31 , 37 ), and 8 in S. longispicata ( 3 , 4 , 6 , 28 , 35 , 38 , 39 , 40 ) ( B). The differences of the 46 compounds between the three salvias are presented in a heat map ( ). In this map, red indicates a relatively higher intensity of each of the compounds present in the sages and blue a lower intensity. Abietanes ( 27 – 40 ) and clerodanes ( 19 – 26 ) were the most common among salvias, with 22 compounds identified. Abietanes predominate in S. longispicata and S. cinnabarina , and clerodanes in S. lavanduloides . Pimarane ( 41 ) and labdane ( 42 ) were found in S. cinnabarina . Regarding phenolic compounds ( 1 – 18 ) and triterpenoids ( 43 – 46 ), they are present in greater quantities in S. cinnabarina and S. lavanduloides , compared to S. longispicata ( ). 2.2. Acute Toxicity of the Methanol Extracts of Salvias The methanolic extracts of the three sages did not produce acute toxicity effects at the doses tested, nor at the maximum dose explored according to OECD’s test No. 423, indicating a parameter of LD 50 > 2000 mg/kg, p.o. There was no significant difference in the weight of mice receiving the extract compared to the vehicle during the 14-day evaluation ( ). Likewise, during the periodic observation throughout the assessment, no signs of toxicity such as changes in the skin and fur, somatomotor activity or behavioural changes were observed, nor were tremors, convulsions, diarrhoea, lethargy, sleep, or coma detected. 2.3. Antinociceptive Effect of Sage Extracts on the Neurogenic and Inflammatory Phases of the Formaline Test Methanolic extracts at a dose of 300 mg/kg, p.o. and diclofenac (DFC, reference drug at 10 mg/kg, p.o.) significantly reduced nociceptive behaviour in both the neurogenic phase (F 4,25 = 7.571, p < 0.0004) ( A) and the inflammatory phase (F 4,25 = 19.93, p < 0.0001) ( B) compared to the group receiving the vehicle. However, the S. longispicata extract showed a strong decrease in nociceptive behaviour in both phases, similar to the reference drug.
+/− -MS-QTOF) 2.1.1. Preliminary Comparison of the Retention Time-Mass/Charge Features Between Salvia Species A preliminary comparative analysis of the constitution of retention time-mass/charge (rt- m / z ) features obtained by UPLC-ESI +/− -MS-QTOF, of the three sages, shows that they share a low percentage of similarity between them. This is visualised by the Venn diagram ( A) and the principal component analysis (PCA) ( B), which indicate that the three salvias do not group together by similarity in their rt- m / z profile. 2.1.2. Difference in Chemical Composition of Sages The experimental m / z values obtained from the three sages compared with the data reported from molecules previously isolated from Mexican Salvia species allowed the tentative identification of 46 metabolites including five phenolic acids, 13 flavonoids, 24 diterpenes and four triterpenes. shows the chromatographic (rt) and spectrometric ( m / z ) data for each compound. It is important to note that when comparing the historical data of compounds previously isolated from Mexican salvias with the experimental data, only 46 data points were correlated with a mass error of less than 5 ppm in negative mode and one in positive mode. The positive value corresponds to kaempferol, which is also identified in negative mode. Both are indicated as compound 18 with the following notation: Kaempferol*, in positive mode, was identified in S. cinnabarina and Kaempferol**, in negative mode, in S. lavanduloides . The most relevant results are briefly mentioned. Diterpenes were the group with the highest number of molecules identified in the extracts of sages ( , No. 19 – 42 ), detected in rt from 6.54 to 12.16 min. The abietanes and clerodanes stand out with 14 and 8 structures, respectively. The abietanes ( 29 , 30 , 32 – 34 , 36 ), clerodane 23 , pimarane 41 and labdane 42 were identified in S. cinnabarina . The abietanes ( 27 , 28 , 34 , 35 , 38 – 40 ) and the clerodanes, amarisolide F ( 19 ) and salvixalapadiene ( 21 ) were present in S. longispicata . Furthermore, seven clerodanes ( 19 – 22 , 24 – 26 ) and three abietanes (27 , 31 , 37 ) were detected in S. lavanduloides , identified as 16-hydroxycarnosic acid, 16-acetoxycarnosic acid and 7α-acetoxy-6,7 dihydroicetexone, respectively. Flavonoids were the second largest group with 13 compounds identified ( 2 , 4 – 8 , 10 – 12 , 15 – 18 ). Rutin ( 5 ) was present in all three salvias, whereas luteolin-7-O-glucuronide ( 8 ), apigenin ( 12 ) and 5,6-dihydroxy-7,3′,4′-trimethoxy ( 17 ) were only present in S. cinnabarina . Schaftoside ( 2 ), quercetin ( 11 ) and kaempferol ( 18 ) were found in S. lavanduloides . Also, cyanidin 3,5-diglucoside ( 4 ) and miquelianin ( 6 ) were identified only in S. longispicata . Phenolic acids were the third group identified ( 1 , 3 , 9 , 13 and 14 ) at a retention time of 0.52, 3.41, 4.67, 5.2 and 5.37 min, respectively. Compound 1 , identified as sagerinic acid, represented by the molecular ion m / z 719.1643, was detected only in S. cinnabarina . Syringic acid ( 3 ) with an ion m / z at 197.0449 was found in S. longispicata and salvianolic acid A ( 14 ) with m / z at 493.1141 in S. lavanduloides . Rosmarinic acid ( 13 ) with an ion m / z at 359.0775 was present in all three salvias. Finally, triterpenoids were identified as a fourth group, an oleanane derivative ( 43 ) was only present in S. cinnabarina , while 3-hydroxyestran-17-one ( 44 ) and an ursane derivative ( 45 ) were found in all three salvias ( ). The chemical structures of the identified compounds are shown in A. The comparative analysis of the chemical composition of the three sages using a Venn diagram ( B) showed that S. lavanduloides shares more compounds with S. longispicata ( 7 , 16 , 19 , 21 , 27 ), corresponding to quercetin glycoside, pedalitin, amarisolide F, salvixalapadiene, and 16-hydroxycarnosic acid, respectively. Three metabolites are common between S. cinnabarina and S. longispicata : salviaflaside ( 9 ), 5,6-dihydro-6α-hydroxysalviasperanol ( 34 ) and 2-hydroxyursolic acid ( 46 ). Likewise, rhamnetin 3-glucoside ( 10 ), luteolin ( 15 ) and kaempferol ( 18 ) were identified in S. cinnabarina and S. lavanduloides . Of these compounds, only four are shared between the three species: rutin ( 5 ), rosmarinic acid ( 13 ), 3-hydroxyestran-17-one ( 44 ), and 11β-hydroxy-3-oxo-urs-12-en-28-oic acid ( 45 ) ( B). In S. cinnabarina , 13 chemical constituents were identified as unique ( 1 , 8 , 12 , 17 , 23 , 29 , 30 , 32 , 33 , 36 , 41 , 42 , 43 ), 10 in S. lavanduloides ( 2 , 11 , 14 , 20 , 22 , 24 , 25 , 26 , 31 , 37 ), and 8 in S. longispicata ( 3 , 4 , 6 , 28 , 35 , 38 , 39 , 40 ) ( B). The differences of the 46 compounds between the three salvias are presented in a heat map ( ). In this map, red indicates a relatively higher intensity of each of the compounds present in the sages and blue a lower intensity. Abietanes ( 27 – 40 ) and clerodanes ( 19 – 26 ) were the most common among salvias, with 22 compounds identified. Abietanes predominate in S. longispicata and S. cinnabarina , and clerodanes in S. lavanduloides . Pimarane ( 41 ) and labdane ( 42 ) were found in S. cinnabarina . Regarding phenolic compounds ( 1 – 18 ) and triterpenoids ( 43 – 46 ), they are present in greater quantities in S. cinnabarina and S. lavanduloides , compared to S. longispicata ( ).
Salvia Species A preliminary comparative analysis of the constitution of retention time-mass/charge (rt- m / z ) features obtained by UPLC-ESI +/− -MS-QTOF, of the three sages, shows that they share a low percentage of similarity between them. This is visualised by the Venn diagram ( A) and the principal component analysis (PCA) ( B), which indicate that the three salvias do not group together by similarity in their rt- m / z profile.
The experimental m / z values obtained from the three sages compared with the data reported from molecules previously isolated from Mexican Salvia species allowed the tentative identification of 46 metabolites including five phenolic acids, 13 flavonoids, 24 diterpenes and four triterpenes. shows the chromatographic (rt) and spectrometric ( m / z ) data for each compound. It is important to note that when comparing the historical data of compounds previously isolated from Mexican salvias with the experimental data, only 46 data points were correlated with a mass error of less than 5 ppm in negative mode and one in positive mode. The positive value corresponds to kaempferol, which is also identified in negative mode. Both are indicated as compound 18 with the following notation: Kaempferol*, in positive mode, was identified in S. cinnabarina and Kaempferol**, in negative mode, in S. lavanduloides . The most relevant results are briefly mentioned. Diterpenes were the group with the highest number of molecules identified in the extracts of sages ( , No. 19 – 42 ), detected in rt from 6.54 to 12.16 min. The abietanes and clerodanes stand out with 14 and 8 structures, respectively. The abietanes ( 29 , 30 , 32 – 34 , 36 ), clerodane 23 , pimarane 41 and labdane 42 were identified in S. cinnabarina . The abietanes ( 27 , 28 , 34 , 35 , 38 – 40 ) and the clerodanes, amarisolide F ( 19 ) and salvixalapadiene ( 21 ) were present in S. longispicata . Furthermore, seven clerodanes ( 19 – 22 , 24 – 26 ) and three abietanes (27 , 31 , 37 ) were detected in S. lavanduloides , identified as 16-hydroxycarnosic acid, 16-acetoxycarnosic acid and 7α-acetoxy-6,7 dihydroicetexone, respectively. Flavonoids were the second largest group with 13 compounds identified ( 2 , 4 – 8 , 10 – 12 , 15 – 18 ). Rutin ( 5 ) was present in all three salvias, whereas luteolin-7-O-glucuronide ( 8 ), apigenin ( 12 ) and 5,6-dihydroxy-7,3′,4′-trimethoxy ( 17 ) were only present in S. cinnabarina . Schaftoside ( 2 ), quercetin ( 11 ) and kaempferol ( 18 ) were found in S. lavanduloides . Also, cyanidin 3,5-diglucoside ( 4 ) and miquelianin ( 6 ) were identified only in S. longispicata . Phenolic acids were the third group identified ( 1 , 3 , 9 , 13 and 14 ) at a retention time of 0.52, 3.41, 4.67, 5.2 and 5.37 min, respectively. Compound 1 , identified as sagerinic acid, represented by the molecular ion m / z 719.1643, was detected only in S. cinnabarina . Syringic acid ( 3 ) with an ion m / z at 197.0449 was found in S. longispicata and salvianolic acid A ( 14 ) with m / z at 493.1141 in S. lavanduloides . Rosmarinic acid ( 13 ) with an ion m / z at 359.0775 was present in all three salvias. Finally, triterpenoids were identified as a fourth group, an oleanane derivative ( 43 ) was only present in S. cinnabarina , while 3-hydroxyestran-17-one ( 44 ) and an ursane derivative ( 45 ) were found in all three salvias ( ). The chemical structures of the identified compounds are shown in A. The comparative analysis of the chemical composition of the three sages using a Venn diagram ( B) showed that S. lavanduloides shares more compounds with S. longispicata ( 7 , 16 , 19 , 21 , 27 ), corresponding to quercetin glycoside, pedalitin, amarisolide F, salvixalapadiene, and 16-hydroxycarnosic acid, respectively. Three metabolites are common between S. cinnabarina and S. longispicata : salviaflaside ( 9 ), 5,6-dihydro-6α-hydroxysalviasperanol ( 34 ) and 2-hydroxyursolic acid ( 46 ). Likewise, rhamnetin 3-glucoside ( 10 ), luteolin ( 15 ) and kaempferol ( 18 ) were identified in S. cinnabarina and S. lavanduloides . Of these compounds, only four are shared between the three species: rutin ( 5 ), rosmarinic acid ( 13 ), 3-hydroxyestran-17-one ( 44 ), and 11β-hydroxy-3-oxo-urs-12-en-28-oic acid ( 45 ) ( B). In S. cinnabarina , 13 chemical constituents were identified as unique ( 1 , 8 , 12 , 17 , 23 , 29 , 30 , 32 , 33 , 36 , 41 , 42 , 43 ), 10 in S. lavanduloides ( 2 , 11 , 14 , 20 , 22 , 24 , 25 , 26 , 31 , 37 ), and 8 in S. longispicata ( 3 , 4 , 6 , 28 , 35 , 38 , 39 , 40 ) ( B). The differences of the 46 compounds between the three salvias are presented in a heat map ( ). In this map, red indicates a relatively higher intensity of each of the compounds present in the sages and blue a lower intensity. Abietanes ( 27 – 40 ) and clerodanes ( 19 – 26 ) were the most common among salvias, with 22 compounds identified. Abietanes predominate in S. longispicata and S. cinnabarina , and clerodanes in S. lavanduloides . Pimarane ( 41 ) and labdane ( 42 ) were found in S. cinnabarina . Regarding phenolic compounds ( 1 – 18 ) and triterpenoids ( 43 – 46 ), they are present in greater quantities in S. cinnabarina and S. lavanduloides , compared to S. longispicata ( ).
The methanolic extracts of the three sages did not produce acute toxicity effects at the doses tested, nor at the maximum dose explored according to OECD’s test No. 423, indicating a parameter of LD 50 > 2000 mg/kg, p.o. There was no significant difference in the weight of mice receiving the extract compared to the vehicle during the 14-day evaluation ( ). Likewise, during the periodic observation throughout the assessment, no signs of toxicity such as changes in the skin and fur, somatomotor activity or behavioural changes were observed, nor were tremors, convulsions, diarrhoea, lethargy, sleep, or coma detected.
Methanolic extracts at a dose of 300 mg/kg, p.o. and diclofenac (DFC, reference drug at 10 mg/kg, p.o.) significantly reduced nociceptive behaviour in both the neurogenic phase (F 4,25 = 7.571, p < 0.0004) ( A) and the inflammatory phase (F 4,25 = 19.93, p < 0.0001) ( B) compared to the group receiving the vehicle. However, the S. longispicata extract showed a strong decrease in nociceptive behaviour in both phases, similar to the reference drug.
Salvia is the most diverse genus within the Lamiaceae family, and Mexico is home to the largest number of species, with approximately 307 , of which around 56 species have been used in traditional Mexican medicine, with different healing properties [ , , ]. Despite the richness of the genus and its wide use for its medicinal properties in different parts of the world [ , , , ], metabolomic studies are still few, mainly focused on species with some use and addressing different objectives, such as S. miltiorrhiza from the Old World, from the subgenus Glutinaria , or S. hispanica , from Mexico, which is within the subgenus Calosphace . This work includes three species of the subgenus Calosphace , which belong to different sections and to different clades . To explain the medicinal properties of these species, in particular their antinociceptive effect, their chemical compositions were obtained and compared with each other. Untargeted metabolomic analysis with UPLC-ESI +/− -MS-QTOF allowed the identification of a total of 46 compounds of phenolic and terpene nature in the extracts of salvias and also highlighted that the three species present particular chemical profiles, with only four shared compounds (rutin, rosmarinic acid, 11β-hydroxy-3-oxo-urs-12-en-28-oic acid and 3-hydroxyestran-17-one). The first three are widely distributed, both in Salvia [ , , , ] and in various botanical families [ , , ], and this is explained because they are compounds that intervene in defence mechanisms against other organisms or that improve tolerance to certain environmental factors such as pollution, UV light and lack of water [ , , , , ]. Phenolic acids such as sagerinic, syringic and salvianolic were first identified in S. cinnabarina , S. longispicata , and S. lavanduloides , respectively. These metabolites have been previously reported in Salvia species [ , , ]. Regarding flavonoids, 13 were identified, some of which are exclusive to each sage such as schaftoside, miquelianin, and luteolin-7-O-glucoronide detected in S. lavanduloides , S. longispicata and S. cinnabarina , respectively. Common flavonoids of the genus were also identified, like kaemperol, pedalitin, apigenin, quercetin, luteolin, and the glycosides of the last three compounds [ , , ]. With respect to triterpenoids, four compounds were identified in the three salvias. Previous research reports that oleanolic acid, ursolic acid, and their derivatives are common and present in almost all Salvia species [ , , , ]. Mainly terpene components are known in both S. cinnabarina and S. lavanduloides . This work contributed to expanding the phytochemical knowledge of these species by identifying the presence of structures from the group of phenolic compounds, which little is known in Mexican sages. On the other hand, it is the first time that the metabolite profile in S. longispicata has been investigated. The most characteristic metabolites found in Salvia are the diterpenes (clerodanes and abietanes). Clerodanes are almost restricted to Neotropical salvias and are found mainly in the subgenus Calosphace . On the other hand, abietanes are present in European, Asian and American sages, in all subgenera, and are also found in Mexican salvias, both in the subgenus Audibertia , where they seem to be more abundant, and in the subgenus Calosphace , to which the three species studied belong. In addition, 14 abietane and eight clerodane structures were identified in this research. It should be noted that abietanes predominate in S. longispicata and S. cinnabarina , and clerodanes in S. lavanduloides , in the latter, two clerodanes have previously been isolated . At the same time, this work reports, for the first time, the presence of five more clerodanes and two more abietanes in S. lavanduloides . On the other hand, five abietanes, one clerodane, one labdane, and one pimarane were identified in the extract of S. cinnabarina . These last two compounds have already been previously identified and isolated in this species . It is worth noting that labdanes and pimaranes are not very abundant in Salvia , being identified only in S. hispanica , S. parryi A.Gray, S. fulgens Cav., S. microphylla , S. greggii A. Gray, S. sclarea L., and S. officinalis . Specifically, the chemical profile of the three sages is contrasting, given that they are not phylogenetically close and, despite the fact that they were all collected in the State of Oaxaca, the microenvironments where they develop are different. Salvia cinnabarina belongs to the Incarnatae section and is the only one that synthesizes pimaranes and labdanes [ , , ], compounds not present in the Lavanduloideae section and the Angulatae section, which respectively include S. lavanduloides and S. longispicata , so these diterpenoids could be good chemotaxonomic markers. Flavonoids are common and widely distributed in angiosperms, also in the Lamiaceae family and particularly in Salvia . Chemotaxonomy has always been a field of exploration, so it is not uncommon for phenolic compounds to be studied in this context, investigating their usefulness in characterising and differentiating Taxa or in developing hypotheses of phytochemical evolution , in addition to finding better species to obtain natural products. Although it is not an objective of the work, in the case of flavonoids, the comparison exercise is carried out between the three species, to investigate their value as taxonomic markers. They are documented to present different profiles: S. cinnabarina , a herb with red flowers and exserted stamens, exhibits seven flavonoids, of which it shares four with S. lavanduloides , a herb with blue flowers and inset stamens, and one with S. longispicata , a suffrutex with blue flowers and inset stamens. S. longispicata has four flavonoids, of which it shares one with S. cinnabarina and two with S. lavanduloides . The greatest similarity is found between S. cinnabarina and S. lavanduloides , something that is not expected, given the morphological characteristics of each species and the position they present in the phylogenies [ , , ] since S. cinnabarina is located in a more basal clade with respect to the other two, which are found in more recent and closer clades. We do not consider these results sufficient to evaluate the value of these compounds as taxonomic markers, and we think it is necessary to include a larger number of species in studies with this objective; taking into account that, unlike Old World salvias, studies reporting phenolic compounds for American sages are still scarce. In order to determine the analgesic potential of Salvia species, the methanolic extracts of the three salvias were evaluated using the formalin test. The results show the effect of the extracts at the central and peripheral level, associated with the reduction of nociceptive behaviour in the neurogenic and inflammatory phases. It is worth noting that the extract of S. longispicata reduced nociceptive behavior to a greater extent in both phases. This was possibly due to the chemical differences with respect to the other two salvias. The main difference lies in the presence of a greater number of abietane-type diterpenes. In this regard, the therapeutic effect of tanshinones, carnosic acid and carnosol, isolated from various species of Salvia , is reported in various conditions that cause nociceptive pain, associated with inflammation [ , , , ]. These results are consistent with the antinociceptive effect observed in other Salvia species, such as the ethanolic extract and nor-abietane fruticulin, obtained from S. lachnostachys , that had good activity in the formalin test . Additionally, the hydroalcoholic extract and terpenoids isolated from S. officinalis produced antinociceptive and anti-inflammatory activity in the Writhing, formalin, and carrageenan tests . Extracts of different polarity, as well as clerodane-type compounds from S. amarissima (Syn. Salvia circinata ), S. divinorum Epling & Jativa, S. semiatrata , S. purpurea , and S. tiliifolia promoted significant effects in pain and inflammation tests (Writhing, formalin, hot plate, carrageenan tests, and in a model of fibromyalgia and allodynia) [ , , , , , , ]. Several studies have reported the analgesic and anti-inflammatory properties, both in vitro and in vivo models, of flavonoids such as apigenin, kaempferol, quercetin, rutin, and luteolin [ , , , ] as well as some phenolic acids such as rosmarinic, sagerinic, syringic, and salvianolic . Among terpenoids, those of the di- type have been little studied regarding their analgesic potential, however, an in vitro study of the anti-inflammatory effect of hardwickiic acid is reported . Finally, regarding triterpenoids, the anti-pain potential of oleanolic and ursolic acids, as well as their derivatives, has been widely studied in nociception models [ , , , , , ]. All of the above explains why, despite the different chemical profiles of S. cinnabarina , S. lavanduloides , and S. longispicata , all three have antinociceptive effects, since both shared and exclusive metabolites have shown good results in evaluations of their analgesic properties. The background on the analgesic effect of Salvia and the agreement with the results obtained suggest a high potential as a medicinal alternative for pain relief, due to the synergy of terpene and phenolic molecules present in the genus. Due to the need to know the safety of the plants used in traditional Mexican medicine, an evaluation of the acute toxicity of methanol extracts at a dose of 2000 mg/kg p.o. of S. cinnabarina , S. lavanduloides , and S. longispicata was carried out, the results of which place them at a non-toxic level of use (OECD 2001) . The safety of use of these sages is consistent with the acute toxicity results of other species of the genus, with an LD 50 > 2000 mg/kg, p.o. calculated for extracts. For example, for the hydroalcoholic extract of S. officinalis leaves, an LD 50 = 44.75 g/kg, p.o. was reported . The infusion of S. circinata presented an LD 50 = 5 g/kg, p.o. and an LD 50 > 2000 mg/kg, administered intraplantarly (i. p.) . While for S. hypoleuca Benth. the LD 50 = 1800 mg/kg, i. p. . Finally, for the extracts of different polarity from the aerial part of S. purpurea and S. semiatrata , the LD 50 was greater than 2000 mg/kg, o.p. , making them absolutely safe and therefore, good prospects for use as novel analgesics agents.
4.1. Drugs and Reagents Diclofenac (DCF) and 37% formalin were purchased from Merck México (Naucalpan, Mexico, Mexico). Tween 80 and saline solution (SS) were purchased from Sigma-Aldrich (St. Louis, MO, USA). The solvent (methanol HPLC grade) used for extraction was purchased from Tecsiquim, S.A. de C.V. (Mexico City, Mexico). The analysis phytochemicals (methanol, leucine enkephalin, acetonitrile, water, and formic acid) were LC-MS grade and purchased from Sigma-Aldrich. 4.2. Collection of Plant Material One kilogram of the aerial part of each of the sages was collected in the surroundings of Miahuatlán, Oaxaca, in June 2019 ( ). Fresh plant material was placed in a drying chamber at 32 °C. Salvias were identified by Ph.D. Martha J. Martínez Gordillo. Voucher specimens of these samples were deposited at the FCME Herbarium of the Faculty of Sciences (FCME), the National Autonomous University of Mexico (UNAM). 4.3. Preparations of the Extracts The plant material of each sage was dried at room temperature and finely ground with a blender. Then, five grams of dried and ground plant material were weighed in quadruplicate in Falcon ® conical tubes (Corning Inc., Corning, NY, USA), 50 mL of HPLC grade methanol was added and placed in an ultrasonic bath (Branson Bransonic ® Bath 2800, Emerson Electric Co., St. Louis, MO, USA) for 20 min at room temperature and ultrasonic wave frequency of 40 kHz. It was then filtered (medium-pore filter paper) and evaporated to dryness with a rotary evaporator at a temperature of 45 °C (RE100-Pro Digital Rotary Evaporator, DLAB SCIENTIFIC Co., Shunyi, Beijing, China). The dried extracts were stored in amber glass vials away from sunlight and moisture. 4.4. Chemical Profiling via Ultra Performance Liquid Chromatography Coupled Mass Spectrometry (UPLC-ESI +/− -MS-QTOF) Chemical profiling of methanol extracts was performed as was previously described by Monribot-Villanueva et al. (2020) . The analysis was carried out using an ultra-high-resolution chromatographic system (ACQUITY UPLC I-Class System, Waters Co., Milford, MA, USA) coupled with a quadrupole time of flight (QTOF) high-resolution mass spectrometer (SYNAPT G2-Si Mass Spectrometry, Waters Co., Milford, MA, USA) with an electrospray ionisation source in positive and negative mode. An ACQUITY UPLC BEH C18 column (Waters Co., Milford, MA, USA) was used, with column and sample temperatures of 40° and 15 °C, respectively. The flow rate was 0.3 mL/min and 5 µL of extract was injected. The mobile phase consisted of a gradient of water and acetonitrile, both with 0.1% formic acid. The gradient conditions were 0–20 min linear gradient 1−99% B, then 20–24 min an isocratic step at 99% B, next 24–25 min a linear gradient 90–1% B, and finally an isocratic step at 1% B for 5 min (total run time 30 min). The mass spectrometer conditions were: Capillary, sampling cone and source offset voltages of 3000, 40, and 80 V, respectively. Source and desolvation temperatures of 120 and 20 °C, respectively. Desolvation gas flow was set at 600 L/h and the nebulizer pressure of 6.5 Bar. The peptide leucine-enkephalin was used as the lock mass (556.2771, [M + H] + ; 554.2615, [M − H] − ). The mass acquisition method used was MSe in high-resolution mode (>29,000 m / z for leucine-enkephalin in both ionisation modes) using a mass range of 50–1200 Da and a scan time of 0.5 s. The collision energies for Function 1 were 6 V and for Function 2 were a ramp from 10 to 30 V. Spectrometric data were acquired and processed with MassLynx version 4.1 and MarkerLynx version 4.1 software (Waters TM Corporation, Milford, MA, USA). 4.5. Pharmacological Evaluations 4.5.1. Animals The pharmacological evaluation was carried out in male CD-1 mice (25–30 g of body weight). The mice were provided by the biotherium of the Faculty of Sciences. Mice were placed in acrylic boxes with water and food ad libitum and kept at a controlled temperature of 22 ± 2 °C, standard humidity (50 ± 5%) and with a 12 h light/dark cycle. All experimental procedures were carried out in accordance with the Official Mexican Standards, NOM-062-ZOO-1999 , and International Standards for the Care and Use of Laboratory Animals in Research guidelines. The protocol was accepted by the Committee on Academic Ethics and Scientific Responsibility (CEARC for its acronym in Spanish) of the Faculty of Sciences, UNAM, under the folio PI_2021_08_02_Aguirre. Extracts and the reference drug were suspended in 0.9% SS and Tween 80. All treatments were administered orally (p.o.) in a volume of 10 mL/kg of mouse body weight and were prepared on the day of the experiment. 4.5.2. Acute Toxicity The toxicity of Salvia extracts was evaluated following OECD’s test No. 423 (2001). The experimental groups of three mice were administered a maximum dose of 2000 mg/kg, p.o. with the methanol extracts. The mice were observed for fourteen days to record signs of toxicity such as weight loss, motor incoordination, ataxia, respiratory arrest, or death. 4.5.3. Formalin Test The experiments were divided into groups of five animals, which received the following treatment: saline solution (SS), reference drug (DFC, 10 mg/kg), and the dose of methanol extract (300 mg/kg, p.o.). Once the acute oral toxicity was evaluated, a wide window of therapeutic activity was obtained in which no toxic effects were observed. This allowed the choice of a single dose of 300 mg/kg, in accordance with the background obtained by the working group, which demonstrates the significant effect in various pain models of extracts of different polarity from various species of Salvia (23–25). After 30 min of treatment administration, animals were injected subcutaneously on the intraplantar surface of the right hind limb with 20 µL of 1% formalin to produce a licking behaviour. Individually, the mice were placed inside a glass cylinder, surrounded by mirrors, to facilitate viewing of the behaviour from all angles by the evaluator. Then, the time spent licking the limb administered with the nociceptive agent was measured for 1 min every 5 min for a period of 30 min. Two phases were recorded in this test: neurogenic (0–10 min) and inflammatory (10–30 min) phases. A significant decrease in either phase was interpreted as demonstrative of an antinociceptive effect . 4.6. Statistical Analysis Spectrometric data were acquired and processed with the MassLynx v. 4.1 and MarkerLynx v. 4.1 software from Waters (Milford, MA, USA). The intensity of each ion was normalised and filtered relative to the total ion count to generate a data matrix. Such matrix included m / z values, retention times and normalised peak areas. The mass spectra of the chromatographic peaks were compared with public spectral databases of FooDB, MassBank, LOTUS, Scopus and UNIIQUIM, using a maximum mass error of ±5 ppm as an accuracy criterium of chemical identity. The m / z dataset underwent pre-processing, which involved centring on the mean and scaling using the Pareto principle. Subsequently, for pattern recognition, a PCA and a heat map were applied using the MetaboAnalyst v. 6.0 (Xia Lab, Montreal, QC, Canada) platform. Data from the antinociceptive activity experiments were statistically analysed using Prism 8 software v. 8.4.3 (GraphPad Software Inc., Boston, MA, USA) and ANOVA, followed by Dunnett’s post hoc test, to compare treatments against the vehicle group. A value of p > 0.05 was considered significant.
Diclofenac (DCF) and 37% formalin were purchased from Merck México (Naucalpan, Mexico, Mexico). Tween 80 and saline solution (SS) were purchased from Sigma-Aldrich (St. Louis, MO, USA). The solvent (methanol HPLC grade) used for extraction was purchased from Tecsiquim, S.A. de C.V. (Mexico City, Mexico). The analysis phytochemicals (methanol, leucine enkephalin, acetonitrile, water, and formic acid) were LC-MS grade and purchased from Sigma-Aldrich.
One kilogram of the aerial part of each of the sages was collected in the surroundings of Miahuatlán, Oaxaca, in June 2019 ( ). Fresh plant material was placed in a drying chamber at 32 °C. Salvias were identified by Ph.D. Martha J. Martínez Gordillo. Voucher specimens of these samples were deposited at the FCME Herbarium of the Faculty of Sciences (FCME), the National Autonomous University of Mexico (UNAM).
The plant material of each sage was dried at room temperature and finely ground with a blender. Then, five grams of dried and ground plant material were weighed in quadruplicate in Falcon ® conical tubes (Corning Inc., Corning, NY, USA), 50 mL of HPLC grade methanol was added and placed in an ultrasonic bath (Branson Bransonic ® Bath 2800, Emerson Electric Co., St. Louis, MO, USA) for 20 min at room temperature and ultrasonic wave frequency of 40 kHz. It was then filtered (medium-pore filter paper) and evaporated to dryness with a rotary evaporator at a temperature of 45 °C (RE100-Pro Digital Rotary Evaporator, DLAB SCIENTIFIC Co., Shunyi, Beijing, China). The dried extracts were stored in amber glass vials away from sunlight and moisture.
+/− -MS-QTOF) Chemical profiling of methanol extracts was performed as was previously described by Monribot-Villanueva et al. (2020) . The analysis was carried out using an ultra-high-resolution chromatographic system (ACQUITY UPLC I-Class System, Waters Co., Milford, MA, USA) coupled with a quadrupole time of flight (QTOF) high-resolution mass spectrometer (SYNAPT G2-Si Mass Spectrometry, Waters Co., Milford, MA, USA) with an electrospray ionisation source in positive and negative mode. An ACQUITY UPLC BEH C18 column (Waters Co., Milford, MA, USA) was used, with column and sample temperatures of 40° and 15 °C, respectively. The flow rate was 0.3 mL/min and 5 µL of extract was injected. The mobile phase consisted of a gradient of water and acetonitrile, both with 0.1% formic acid. The gradient conditions were 0–20 min linear gradient 1−99% B, then 20–24 min an isocratic step at 99% B, next 24–25 min a linear gradient 90–1% B, and finally an isocratic step at 1% B for 5 min (total run time 30 min). The mass spectrometer conditions were: Capillary, sampling cone and source offset voltages of 3000, 40, and 80 V, respectively. Source and desolvation temperatures of 120 and 20 °C, respectively. Desolvation gas flow was set at 600 L/h and the nebulizer pressure of 6.5 Bar. The peptide leucine-enkephalin was used as the lock mass (556.2771, [M + H] + ; 554.2615, [M − H] − ). The mass acquisition method used was MSe in high-resolution mode (>29,000 m / z for leucine-enkephalin in both ionisation modes) using a mass range of 50–1200 Da and a scan time of 0.5 s. The collision energies for Function 1 were 6 V and for Function 2 were a ramp from 10 to 30 V. Spectrometric data were acquired and processed with MassLynx version 4.1 and MarkerLynx version 4.1 software (Waters TM Corporation, Milford, MA, USA).
4.5.1. Animals The pharmacological evaluation was carried out in male CD-1 mice (25–30 g of body weight). The mice were provided by the biotherium of the Faculty of Sciences. Mice were placed in acrylic boxes with water and food ad libitum and kept at a controlled temperature of 22 ± 2 °C, standard humidity (50 ± 5%) and with a 12 h light/dark cycle. All experimental procedures were carried out in accordance with the Official Mexican Standards, NOM-062-ZOO-1999 , and International Standards for the Care and Use of Laboratory Animals in Research guidelines. The protocol was accepted by the Committee on Academic Ethics and Scientific Responsibility (CEARC for its acronym in Spanish) of the Faculty of Sciences, UNAM, under the folio PI_2021_08_02_Aguirre. Extracts and the reference drug were suspended in 0.9% SS and Tween 80. All treatments were administered orally (p.o.) in a volume of 10 mL/kg of mouse body weight and were prepared on the day of the experiment. 4.5.2. Acute Toxicity The toxicity of Salvia extracts was evaluated following OECD’s test No. 423 (2001). The experimental groups of three mice were administered a maximum dose of 2000 mg/kg, p.o. with the methanol extracts. The mice were observed for fourteen days to record signs of toxicity such as weight loss, motor incoordination, ataxia, respiratory arrest, or death. 4.5.3. Formalin Test The experiments were divided into groups of five animals, which received the following treatment: saline solution (SS), reference drug (DFC, 10 mg/kg), and the dose of methanol extract (300 mg/kg, p.o.). Once the acute oral toxicity was evaluated, a wide window of therapeutic activity was obtained in which no toxic effects were observed. This allowed the choice of a single dose of 300 mg/kg, in accordance with the background obtained by the working group, which demonstrates the significant effect in various pain models of extracts of different polarity from various species of Salvia (23–25). After 30 min of treatment administration, animals were injected subcutaneously on the intraplantar surface of the right hind limb with 20 µL of 1% formalin to produce a licking behaviour. Individually, the mice were placed inside a glass cylinder, surrounded by mirrors, to facilitate viewing of the behaviour from all angles by the evaluator. Then, the time spent licking the limb administered with the nociceptive agent was measured for 1 min every 5 min for a period of 30 min. Two phases were recorded in this test: neurogenic (0–10 min) and inflammatory (10–30 min) phases. A significant decrease in either phase was interpreted as demonstrative of an antinociceptive effect .
The pharmacological evaluation was carried out in male CD-1 mice (25–30 g of body weight). The mice were provided by the biotherium of the Faculty of Sciences. Mice were placed in acrylic boxes with water and food ad libitum and kept at a controlled temperature of 22 ± 2 °C, standard humidity (50 ± 5%) and with a 12 h light/dark cycle. All experimental procedures were carried out in accordance with the Official Mexican Standards, NOM-062-ZOO-1999 , and International Standards for the Care and Use of Laboratory Animals in Research guidelines. The protocol was accepted by the Committee on Academic Ethics and Scientific Responsibility (CEARC for its acronym in Spanish) of the Faculty of Sciences, UNAM, under the folio PI_2021_08_02_Aguirre. Extracts and the reference drug were suspended in 0.9% SS and Tween 80. All treatments were administered orally (p.o.) in a volume of 10 mL/kg of mouse body weight and were prepared on the day of the experiment.
The toxicity of Salvia extracts was evaluated following OECD’s test No. 423 (2001). The experimental groups of three mice were administered a maximum dose of 2000 mg/kg, p.o. with the methanol extracts. The mice were observed for fourteen days to record signs of toxicity such as weight loss, motor incoordination, ataxia, respiratory arrest, or death.
The experiments were divided into groups of five animals, which received the following treatment: saline solution (SS), reference drug (DFC, 10 mg/kg), and the dose of methanol extract (300 mg/kg, p.o.). Once the acute oral toxicity was evaluated, a wide window of therapeutic activity was obtained in which no toxic effects were observed. This allowed the choice of a single dose of 300 mg/kg, in accordance with the background obtained by the working group, which demonstrates the significant effect in various pain models of extracts of different polarity from various species of Salvia (23–25). After 30 min of treatment administration, animals were injected subcutaneously on the intraplantar surface of the right hind limb with 20 µL of 1% formalin to produce a licking behaviour. Individually, the mice were placed inside a glass cylinder, surrounded by mirrors, to facilitate viewing of the behaviour from all angles by the evaluator. Then, the time spent licking the limb administered with the nociceptive agent was measured for 1 min every 5 min for a period of 30 min. Two phases were recorded in this test: neurogenic (0–10 min) and inflammatory (10–30 min) phases. A significant decrease in either phase was interpreted as demonstrative of an antinociceptive effect .
Spectrometric data were acquired and processed with the MassLynx v. 4.1 and MarkerLynx v. 4.1 software from Waters (Milford, MA, USA). The intensity of each ion was normalised and filtered relative to the total ion count to generate a data matrix. Such matrix included m / z values, retention times and normalised peak areas. The mass spectra of the chromatographic peaks were compared with public spectral databases of FooDB, MassBank, LOTUS, Scopus and UNIIQUIM, using a maximum mass error of ±5 ppm as an accuracy criterium of chemical identity. The m / z dataset underwent pre-processing, which involved centring on the mean and scaling using the Pareto principle. Subsequently, for pattern recognition, a PCA and a heat map were applied using the MetaboAnalyst v. 6.0 (Xia Lab, Montreal, QC, Canada) platform. Data from the antinociceptive activity experiments were statistically analysed using Prism 8 software v. 8.4.3 (GraphPad Software Inc., Boston, MA, USA) and ANOVA, followed by Dunnett’s post hoc test, to compare treatments against the vehicle group. A value of p > 0.05 was considered significant.
The untargeted metabolomic analysis and the review previously carried out on the chemical constituents of salvias allowed for the chemical differentiation of S. cinnabarina , S. lavanduloides , and S. longispicata , of which 46 compounds were identified. In this study, advanced analytical and chemometric techniques were used to identify bioactive compounds and distinctive chemical markers of three Mexican sages, making it one of the few studies that have used the metabolomic technique in Mexico. Likewise, the importance of the synergy of the constituents of terpene and phenolic nature was visualised, which plays an important role in the efficacy and safety of the use of salvias as an alternative therapy in the treatment of pain. The results of this study reinforce the richness of secondary metabolism as well as the therapeutic properties of Mexican Salvia species used in Traditional Medicine. It also provides evidence that S. cinnabarina , S. lavanduloides , and S. longispicata may be a source of effective and safe compounds with analgesic potential. Future trials evaluating extracts and isolated compounds from Salvia in various biological models are necessary to propose and integrate new drugs into healthcare due to the growing interest in finding alternative therapies.
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Bibliometric analysis of potassium channel research | 6c04ffb0-dafd-450e-a4d4-08640cc92a44 | 7039634 | Physiology[mh] | Seventeen thousand three hundred and ninety-two articles were obtained, to explore the trends in potassium channel research, we visualized the yearly outputs of relevant articles . As shown in the trend of world potassium channel research publications remained stable high in the past 10 years, the average annual publications are 1,739.
Distribution maps provide valuable information and help researchers to identify potential collaborators .The data showing the publication contributions of different countries and institutions are shown in , while the connection between countries or institutions is shown in the network . Countries and institutions engaged in potassium channel research were distributed worldwide. The 17,392 articles on potassium channel research were published by more than 7000 research institutions in 106 countries/territories . The USA, Peoples R China, Germany, England, and Japan were at the top of the list. USA (6,616 articles) and Peoples R China (2,722articles) were the top two countries. ) shows that the United States attached great importance to cooperation, and had close cooperation with China, Canada, Japan, South Africa, Britain, and Australia. ) shows that most of the publications were published by American institutions ( (b)), with University of California produced the highest number of publications on potassium channels (177), followed by Center national de la recherche scientifique (405) and Institut National de la Sante et de la Recherche Medicale (INSERM) (360) .
Seventeen thousand three hundred and ninety-two articles have been published in 2,265 journals, there are 10 journals with publication volume greater than 100.The top 10 journals in terms of the number of publications are indicated in . The journal Plos One had the highest number at 721 (4.15%) (IF = 2.776,2018), The Journal of biological chemistry published 451 papers (2.59%) (IF = 4.106, 2018) in potassium channel research. The Journal of neuroscience ranked third at 370 papers (2.13%) (IF = 6.074, 2018). As for the co-cited journals , proceedings of the national academy of sciences of the united states of america (10,446) was the most frequently cited journal in potassium channel research, the second was The Journal of biological chemistry (9408), followed by Nature (9316).
Knowledge maps can provide information on influential research groups and potential collaborators and can help researchers to establish collaborations . Approximately 57,811authors contributed 17,392 articles related to potassium channel research. The networks shown in ) indicate the cooperation among authors. Colin G Nichols was the most prolific in terms of publications on potassium channel research (66 papers), followed by Wei Wang (62 papers) and Heike Wulff (59 papers). There was also a wide distribution of co-cited authors in the field of potassium channels. The connection network between co-cited authors was measured using CiteSpace V .The papers published by Sanguinetti MC had the highest number of co-citations (1134 papers), followed by Hille B (1092 papers) and J. Long SB (812papers) (see ).
shows the 15 research areas that most frequently appeared in publications related to potassium channel research from 2009 to 2018. Neurosciences accounted for the largest number of publications, followed by biochemistry and molecular biology and physiology.
Keywords provide a reasonable description of research hotspots, whereas burst words represent new research frontiers . CiteSpace V was used to construct a knowledge map of keyword co-occurrence and identified the top 20 keywords in potassium channel research articles from 2009 to 2018 , according to frequency. The top keywords were “potassium channel,” “ion channel” “expression,” “mechanism” “cell” “protein” “rat,” “ca2+ activated k+ channel” and “nitric oxide” . Therefore, research hotspots can be summarized into the following aspects: Gene expression, ‘ca2+ activated k+ channel,’ and “nitric oxide”. Keywords were identified and analyzed using strong citation bursts to explore the frontiers of research. We depicted the time intervals a blue line and the time period that represents a burst keyword category as a red line, indicating the beginning and the end of the time interval of each burst . As shown in , the keywords that had strong bursts after 2014 were “bk channel” “blood pressure” “oxidative stress” “disease”, “identification”, “action potential” and “electrophysiology”. The top four research frontiers of potassium channel research were as follows: 1. bk channel 2. blood pressure 3. oxidative stress 4. electrophysiology. According to bibliometrics analysis, the trend of world potassium channel research publications remained stable high in the past 10 years. The USA, Peoples R China, and Germany were the top countries that contributed to publications on potassium channel research. Cooperation between countries or institutions can promote the development and progress of research. The USA had close cooperation with China, Canada, Japan, South Africa, Britain, and Australia and made significant contributions to potassium channel research. University of California produced the highest number of publications on potassium channels. The impact factor (IF) of a journal is an important factor in evaluating its value and that of included articles .In the top 10 published journals, “Proceedings of the National Academy of Sciences of the United States of America” had the highest impact factor (9.580), followed by the Journal of neuroscience (6.074) and Journal of physi-london (4.950). Therefore, it is a challenge to publish more high impact factor papers on potassium channel research. Through the analysis of the research areas, we found that potassium channels are most studied in Neurosciences, biochemistry and molecular biology and physiology. Of the top 10 authors identified in this analysis, each contributed to more than 39 papers. In the network of authors contributed to potassium channel research, the largest node was (Colin G Nichols 66 articles), indicating that his important role in potassium channel research. Colin G Nichols mainly focused on the structural changes of potassium ion gated channels , the changes of potassium ion channels in cardiovascular diseases , nervous system diseases and endocrine system diseases . Wang Wei was also highly published. He and his colleagues did not cooperate much. Their research was mainly published in 2014 and 2016. His research focused on the effect of the potassium channel on neuropathic pain and the contribution of TWIK-1 channels to astrocyte K+ current . The number of citations of the top 10 co-cited authors was at least 480, and the top one was Sanguinetti MC whose studies implicated dysfunction of Ikr channels in long-QT syndrome . The number of publications and co-citations of Wulff H was both high, indicating that he attaches importance to both quantity and quality. The main research direction of Wulff H was molecular properties and physiological roles of ion channels in the immune system . His review discusses pharmacological strategies for targeting K(V) channels with venom peptides, antibodies, and small molecules, and highlights recent progress in the preclinical and clinical development of drugs targeting the K(V)1 subfamily, the K(V)7 subfamily (also known as KCNQ), K(V) 10.1 (also known as EAG1 and KCNH1) and K(V) 11.1 (also known as HERG and KCNH2) channels . Nichols C G, Wang Wei, and Wulff H might be good candidates for research collaboration in this field. Through the keyword cluster analysis, research hotspots can be summarized into the following aspects: 1.Gene expression, the differential expression of the potassium channel gene is related to the occurrence of various diseases. Researches show that mutations in KCNJ10 cause a specific disorder, consisting of epilepsy, ataxia, sensorineural deafness, and tubulopathy, and possibly also play a major role in blood-pressure maintenance and its regulation . 2.Ca2+ activated k+ channel, Calcium-activated potassium channels are potassium channels gated by calcium , or that are structurally or phylogenetically related to calcium-gated channels. According to the sequence homology of transmembrane hydrophobic cores,Calcium-activated potassium channels are divided into three subtypes: BK channel, IK channel and SK channel . 3.Nitric oxide, KATP activation associated with increased nitric oxide concentrations and inducible nitric oxide synthase induction is a key factor in cardiovascular and cerebrovascular diseases . Studies have shown that Salvinorin A dilates cerebral arteries via activation of nitric oxide synthase, adenosine triphosphate-sensitive potassium channel, and the κ opioid receptor . The frontiers of potassium channel research were predicted using the strongest citation bursts of publications. The three research frontiers of potassium channel research were as follows: BK channel, the high-conductance calcium-activated potassium channel (BK channel) is a very complex ligand-gated potassium channel . It is also regulated by voltage and intracellular calcium ion concentration, linking the cellular calcium signal system and membrane potential to form a negative feedback regulation, which plays a key role in many important physiological processes including smooth muscle contraction and neurotransmitter release . Blood pressure, small-conductance (KCa2.1–2.3) and intermediate-conductance (KCa3.1) calcium-activated K channels are critically involved in modulating calcium-signaling cascades and membrane potential in both excitable and nonexcitable cells . Potassium homeostasis plays an essential role in the control of blood pressure . One study found that the altered ATP-sensitive potassium channels may be related to the obesity-triggered increase in blood pressure . Oxidative stress is suspected to be important in cardiovascular diseases, neurodegenerative diseases, cancerdiseases, cancer, and other aging-associated diseases. Mitochondrial ATP-sensitive potassium channels [mito(KATP)] play a critical role in modulating intracellular ROS . The study revealed that renin-angiotensin system overactivation is involved in the aging process in several tissues by increasing oxidative damage and inflammation, activation of mitochondrial ATP-sensitive potassium channels [mitoK(ATP)] may play a major role in the angiotensin II-induced effects on aging and neurodegeneration . Electrophysiology, potassium channels play an important role in regulating membrane potential and excitability of cells. With the development of electrophysiological technology, the molecular structure and functional characteristics of potassium channels have been revealed gradually. Data on potassium channel publications were collected and retrieved from the Web of Science Core Collection database, and the analysis was relatively sophisticated and objective. A limitation of our bibliometric analysis was that, compared with papers published several years ago, recent articles did not have a high citation count. Nevertheless, CiteSpace is a useful tool for further research into potassium channels.
Our study has demonstrated that numerous countries' institutions and authors have focused on potassium channel research and a lot of literature has been published. Bibliometric analysis of the literature on the potassium channels was important in allowing researchers to identify cooperations, find research hotspots and predict the frontiers of potassium channel research.
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Factors associated with disease knowledge and attitude among ambulatory patients with type 2 diabetes – a multicenter study | 52308180-e8a8-4f90-8782-66724e2a08fe | 11345965 | Health Literacy[mh] | Diabetes is a foremost reason for death and life expectancy reduction in humans . It is also a key universal health concern which poses a heavy challenge to public health and socio-economic progress . The prevalence of diabetes is on the increase, especially in low- and middle-income countries . The worldwide burden of diabetes has soared recently, and this trend may continue . Diabetes knowledge includes patients’ understanding of risk factors, worsening factors and complications of diabetes while diabetes attitude involves patients’ thoughts and behavior towards diabetes. There are lots of variables interfering with the management process of diabetes. Disease knowledge and attitude of diabetes patients have been found to impact their disease prognosis and quality of life . Previous studies in Nigeria reported varying levels of disease knowledge and attitude among this cohort of patients. While a study in North-Western Nigeria reported good diabetes knowledge and attitude , another study carried out in the same zone reported a below-average diabetes knowledge and average diabetes attitude . Also, a study in South-Southern Nigeria revealed poor disease knowledge and average attitude displayed by diabetes patients while yet another study in South-Western Nigeria reported good knowledge and attitude among the diabetes patients . Aside from diabetes knowledge and attitude assessment, it is important to evaluate other associated variables such as medication adherence, level of education and health literacy which may play vital roles in disease control. Adequate adherence to medication, diet and exercise are a sine qua non to effective disease control and improved therapeutic outcomes among diabetes patients . Studies have shown a positive association between patients’ level of formal education and diabetes management . Consistent medication adherence plays a major role in glycemic control and in improving health outcomes of patients . Clifford and colleagues , in a systematic review, stated that self-report and medication possession ratio are two widely used methods of medication adherence assessment. Another review also reported that medication adherence was associated with better glycemic control, lesser visits to emergency departments, reduced hospitalisations, and reduced medical costs . In addition, the review also identified that health training, point-of-care testing, pharmacists’ involvement, case managers, and phone interventions were some of the factors which enhance patients’ medication adherence. Health literacy is an important factor for accessing healthcare and making informed health-related decisions . Inadequate health literacy is related to poor health outcomes, inefficient access to healthcare services and inadequate understanding of health-related information . Association between health literacy level and medication discrepancies were reported by previous studies . High health literacy has been reported to increase glycemic control in diabetes patients . However, there is dearth of literature on comparing disease knowledge and attitude among ambulatory type 2 diabetes patients and the related factors in Nigeria. Also, the interactions between the variables could have important implications for consideration by healthcare professionals. Therefore, this study assessed associations and comparison of diabetes knowledge and attitude with selected variables such as medication adherence, medication discrepancy, glycemic control and health literacy.
Study design, setting and participants A cross-sectional study was carried out in three tertiary healthcare facilities in Nigeria. The study sites were the University College Hospital, Ibadan (950-bed healthcare facility), the University of Ilorin Teaching Hospital, Ilorin (650-bed healthcare facility), and the Federal Medical Center, Abeokuta (250-bed healthcare facility). These healthcare facilities are key referral centers and accredited for undergraduate and postgraduate education for pharmacists, physicians, physiotherapists, nurses, and other healthcare practitioners. Ambulatory diabetes patients above eighteen years of age who were on at least one medication for diabetes were recruited for the study. Patients who were unconscious, pregnant or did not give their consent were excluded from the study. Sample size calculation was based on disease prevalence which according to the International Diabetes Federation is 3.7% in Nigeria . With 5% precision and 95% confidence interval, the minimum sample size for each study center was 55 patients, making 165 in total. 10% nonresponse rate was factored in to make a total of 188 patients. Data collection tools The diabetes knowledge and attitude assessment scales for patients were developed by the authors sequel to extensive literature search. The diabetes knowledge assessment scale is an 18-item scale with three options – “yes”, “no” and “don’t know”. Each correct response was assigned “1” point while each incorrect response was assigned “0” point. The diabetes attitude assessment scale is a 14-item scale with a Likert response ranging from ‘strongly disagree’ to ‘strongly agree’. The Likert responses were assigned one to five points based on the expected response to questions asked. Both scales were subjected to content validation by four faculties in the Department of Clinical Pharmacy and Pharmacy Administration, Faculty of Pharmacy, University of Ibadan. Face validation was done by pretesting the scales among twenty ambulatory diabetes patients at Catholic Hospital, Oluyoro in Ibadan. Cronbach Alpha reliability test was conducted to ascertain the internal consistency of the knowledge and attitude scales. Cronbach alpha for diabetes knowledge and attitude assessment scales were 0.70 and 0.83, respectively. Each participant’s scores for both scales were summed, converted to percentages, and categorized as follows: poor = 0–49.9%, fair = 50–69.9%, good = 70–89.9%, and excellent ≥ 90%. The validated 18-item Short Assessment Health Literacy–English (SAHL-E) scale was utilised for patients’ health literacy evaluation . Patients with 0–14 points were categorized to have low health literacy and those with 15–18, high health literacy. Patients’ self-reported medication adherence was evaluated using the validated 4-item Morisky, Levine, Green scale used with permission from Professor Donald E. Morisky. Responses were coded “yes” and assigned a score of “0” while “no” was assigned a score of “1”. High adherence was defined as a total score of zero, medium adherence as 1 and low adherence as > 1. Medication reconciliation was carried out for the recruited patients. Information on whether or not they had their medication packs with them was noted. Medication discrepancies, defined as inconsistencies between prescribed medications, including the dosage regimen and the medications taken by the patients , were also documented. For the purpose of this study, geriatric patients were ≥ 60 years. The semi-structured questionnaire was divided into five sections. Sections A was for sociodemographic data, while Sections B to E were for diabetes knowledge, diabetes attitude, health literacy and medication adherence assessments, respectively. The participants were approached while waiting to see their physicians on clinic days. The purpose of the study was explained to them before their informed consent was obtained. The questionnaire, which took about 20–30 min to complete, was then administered to the patients who were consecutively sampled. The questionnaire was translated to Yoruba language (the local language) for patients who did not understand English language. Glycemic control was defined as a fasting blood glucose ranging from 70 to 130 mg/dL . Fasting blood glucose value at the clinic on the day of clinic appointment was documented. Data analysis Data was analyzed using SPSS for Windows Version 20.0 (IBM Corp, New York, USA). Descriptive statistics was summarized with frequency counts, percentages, and mean ± standard deviation. Negatively worded questions were reversed during analysis. Standard multiple regression analysis was carried out to assess associations between diabetes knowledge and attitude with gender, medication discrepancy, educational qualification, health literacy, age, glycemic control, and medication adherence. Independent-samples t-test evaluated the difference between means scores of patients’ diabetes knowledge and attitude scores among categorical variables such as gender, health literacy, glycemic control and medication discrepancy. One-way analysis of variance compared patients’ diabetes knowledge and attitude with level of formal education and medication adherence.
A cross-sectional study was carried out in three tertiary healthcare facilities in Nigeria. The study sites were the University College Hospital, Ibadan (950-bed healthcare facility), the University of Ilorin Teaching Hospital, Ilorin (650-bed healthcare facility), and the Federal Medical Center, Abeokuta (250-bed healthcare facility). These healthcare facilities are key referral centers and accredited for undergraduate and postgraduate education for pharmacists, physicians, physiotherapists, nurses, and other healthcare practitioners. Ambulatory diabetes patients above eighteen years of age who were on at least one medication for diabetes were recruited for the study. Patients who were unconscious, pregnant or did not give their consent were excluded from the study. Sample size calculation was based on disease prevalence which according to the International Diabetes Federation is 3.7% in Nigeria . With 5% precision and 95% confidence interval, the minimum sample size for each study center was 55 patients, making 165 in total. 10% nonresponse rate was factored in to make a total of 188 patients.
The diabetes knowledge and attitude assessment scales for patients were developed by the authors sequel to extensive literature search. The diabetes knowledge assessment scale is an 18-item scale with three options – “yes”, “no” and “don’t know”. Each correct response was assigned “1” point while each incorrect response was assigned “0” point. The diabetes attitude assessment scale is a 14-item scale with a Likert response ranging from ‘strongly disagree’ to ‘strongly agree’. The Likert responses were assigned one to five points based on the expected response to questions asked. Both scales were subjected to content validation by four faculties in the Department of Clinical Pharmacy and Pharmacy Administration, Faculty of Pharmacy, University of Ibadan. Face validation was done by pretesting the scales among twenty ambulatory diabetes patients at Catholic Hospital, Oluyoro in Ibadan. Cronbach Alpha reliability test was conducted to ascertain the internal consistency of the knowledge and attitude scales. Cronbach alpha for diabetes knowledge and attitude assessment scales were 0.70 and 0.83, respectively. Each participant’s scores for both scales were summed, converted to percentages, and categorized as follows: poor = 0–49.9%, fair = 50–69.9%, good = 70–89.9%, and excellent ≥ 90%. The validated 18-item Short Assessment Health Literacy–English (SAHL-E) scale was utilised for patients’ health literacy evaluation . Patients with 0–14 points were categorized to have low health literacy and those with 15–18, high health literacy. Patients’ self-reported medication adherence was evaluated using the validated 4-item Morisky, Levine, Green scale used with permission from Professor Donald E. Morisky. Responses were coded “yes” and assigned a score of “0” while “no” was assigned a score of “1”. High adherence was defined as a total score of zero, medium adherence as 1 and low adherence as > 1. Medication reconciliation was carried out for the recruited patients. Information on whether or not they had their medication packs with them was noted. Medication discrepancies, defined as inconsistencies between prescribed medications, including the dosage regimen and the medications taken by the patients , were also documented. For the purpose of this study, geriatric patients were ≥ 60 years. The semi-structured questionnaire was divided into five sections. Sections A was for sociodemographic data, while Sections B to E were for diabetes knowledge, diabetes attitude, health literacy and medication adherence assessments, respectively. The participants were approached while waiting to see their physicians on clinic days. The purpose of the study was explained to them before their informed consent was obtained. The questionnaire, which took about 20–30 min to complete, was then administered to the patients who were consecutively sampled. The questionnaire was translated to Yoruba language (the local language) for patients who did not understand English language. Glycemic control was defined as a fasting blood glucose ranging from 70 to 130 mg/dL . Fasting blood glucose value at the clinic on the day of clinic appointment was documented.
Data was analyzed using SPSS for Windows Version 20.0 (IBM Corp, New York, USA). Descriptive statistics was summarized with frequency counts, percentages, and mean ± standard deviation. Negatively worded questions were reversed during analysis. Standard multiple regression analysis was carried out to assess associations between diabetes knowledge and attitude with gender, medication discrepancy, educational qualification, health literacy, age, glycemic control, and medication adherence. Independent-samples t-test evaluated the difference between means scores of patients’ diabetes knowledge and attitude scores among categorical variables such as gender, health literacy, glycemic control and medication discrepancy. One-way analysis of variance compared patients’ diabetes knowledge and attitude with level of formal education and medication adherence.
A total of 188 diabetes patients, 51 (27.1%) at Federal Medical Center, Abeokuta, 69 (36.7%) University College Hospital, Ibadan, and 68 (36.2%) University of Ilorin Teaching Hospital, Ilorin participated in the study. There were 112 (59.6%) females who participated in the study. Mean age of the patients was 58.69 ± 13.68 years. Further details on participants’ sociodemographic characteristics are shown in Table . Medication discrepancy was observed among 101 (53.7%) patients. Self-reported medication adherence of the participants showed that 103 (54.8%), 47 (25.0%) and 38 (20.2%) had high, medium and low medication adherence, respectively. Ninety-one (48.4%) were found to have high health literacy while 97 (51.6%) had low health literacy. Majority, 167 (88.8%) knew that diabetes is not contagious. Only 52 (27.7%) knew that untreated diabetes does not lead to typhoid fever. One hundred and twenty-six (67.0%) knew that diabetes is incurable. Average diabetes knowledge score was 14.64 ± 2.55 out of a maximum obtainable score of 18. Majority of the patients, 91 (48.4%) and 61 (32.4%) had “good” and “excellent” diabetes knowledge score, respectively (Table ). Eighty-five (45.2%) participants strongly disagreed with the statement that “It is not important to have a self-monitoring blood glucose meter”. One hundred and sixty-nine (89.9%) believed strongly that taking their medications would make them live long. Majority, 53 (28.2%) and 126 (67.0%) had “good” and “excellent” attitude to diabetes, respectively. A mean score of 62.50 ± 6.86 out of a maximum obtainable score of 70 was obtained for diabetes attitude assessment (Table ). Cronbach alpha for diabetes knowledge and attitude assessment scales were 0.70 and 0.83, respectively. Participants’ diabetes knowledge was higher among those with higher level of formal education ( p = 0.046), higher diabetes attitude ( p < 0.001) and high health literacy ( p = 0.002). For diabetes attitude, individuals older than 60 years of age ( p = 0.029), with higher diabetes knowledge ( p < 0.001) and high health literacy ( p = 0.005) had significantly higher values.were significantly different Details on the comparisons between diabetes knowledge and attitude with some selected variables are given in Table . Significant positive association was observed between diabetes knowledge and health literacy (Beta = 0.021, p = 0.029) (Table ).
The study revealed significant associations between type 2 diabetes patients’ diabetes knowledge and health literacy. Significant differences were observed between disease knowledge and educational level, disease attitude and health literacy, while disease attitude was significantly different when compared with age and disease knowledge. Disease knowledge, attitude, level of formal education, health literacy, patient’s age, number of medications taken by patients, medication adherence, medication discrepancy, and glycemic control were all evaluated in this study. It is important to consider these variables during the management of diabetes patients to achieve better health outcomes. Majority of the patients had good diabetes knowledge with only two having less than 50% knowledge score. While a study carried out in North-western Nigeria had a similar observation , on the contrary, other studies in North-Western , and South-Southern Nigeria reported poor diabetes knowledge among diabetes patients. While patients’ knowledge in the study is commendable, there is need for regular knowledge update. Also, another study in South-Western Nigeria reported good knowledge and attitude among the diabetes patients . Many studies carried out in other developing nations such as Bangladesh, Ethiopia Mongolia and Zimbabwe observed inadequate knowledge of diabetes among patients . Studies carried out in Bangladesh , and Sri Lanka and the United Arab Emirates however reported good diabetes knowledge among majority of the patients. It is worthy to note that different diabetes knowledge assessment tools were used for these studies. Dearth of effectively trained healthcare practitioners is a factor that might be responsible for the poor diabetes knowledge among the patients . Healthcare practitioners need to consistently educate patients on diabetes-related knowledge as it is vital in diabetes management . In the study setting, diabetes patients are jointly educated by nurses on each clinic appointment before their appointment with the physicians. The ambulatory diabetes patients also have association in each hospital, where they come together monthly for peer group discussion. Peer support has been found to aid learning and adaptations for self-management among diabetes patients , thereby complementing information provided by the physicians on self-management of the disease. Interestingly, two thirds of the participants believed that taking “bitters” such as Swedish bitters helps to reduce blood sugar. There is a general belief that bitters could be good for elevated blood sugar level. A study carried out in India and another in Saudi Arabis reported the misconception among diabetes patients . Some diabetes patients may rely on these preparations instead of adequately adhering to the prescribed medications thereby worsening their disease condition. Also, about 15% believed that herbal remedies were more effective than prescribed medications at managing blood glucose level. It will not be a surprise if this 15% abandon their medications for herbal remedies. Consumption of herbal remedies could lead to diabetic kidney disease which in turn could affect glycemic control . With a third of the study participants not knowing that diabetes is incurable, and that they will have to be on medications indefinitely, the need for improved patient education becomes glaring. Patients need to be educated on the fact that they will be on medications indefinitely. Some patients have been known to stop their medications once they feel better and stopping the medications could predispose to developing complications of diabetes. Some of the participants were not aware that obesity is a risk factor for diabetes. For diabetes, adequate adherence to exercise, diet and medications is required for improved patient outcomes. Obesity causes insulin resistance and there is need for patients to be aware of it. Also, some of the participants were not aware that diabetes could be genetic, and this may expose their offspring to higher risks. Such children could be educated by their parents to minimize their risks for type 2 diabetes. On the other hand, almost of the participants were knowledgeable about diet requirement and exercise. Although, such knowledge of such health benefits does not guarantee adherence to the practice, it places the patient at a good vantage. Many of the patients were also aware of the complications of diabetes such as blindness and kidney disease. However, some of them believed that diabetes could lead to typhoid fever. Level of formal education, diabetes attitude and health literacy were associated with diabetes knowledge in this study. As expected, patients with high health literacy, better diabetes attitude, as well as those with higher formal educational qualification had better diabetes knowledge. Level of formal education was significantly associated with diabetes knowledge and attitude . A related study in Netherland observed a significant association between poor diabetes knowledge and attitude . Herath and colleagues in Sri Lanka , Gautam and colleagues in Nepal, Salem and colleagues in Riyadh, and Phoosuwan and colleagues in Thailand observed better diabetes knowledge among patients with higher educational level . Average health literacy was observed among the patients. Level of formal education was significantly different with health literacy level. Teach back technique is a method that would help to simplify communications, where patients are asked to explain what they were told by healthcare practitioners in their own words . It helps to address low health literacy. Majority of patients displayed good attitude towards diabetes. This is similar to the study by Sadiq et al. in North-Western Nigeria , but unlike what was reported among diabetes patients in North-western Nigeria where poor attitude was reported . Diabetes attitude was found to be poor among majority of patients in a study carried out in Sri Lanka , and average in Palestine . While majority of the diabetes patients displayed excellent attitude in this study, it is needful to keep educating them in order to encourage positive attitudes and not resign to fate or other alternative practices. There was no significant association observed in this study between diabetes knowledge and medication adherence. A cross-sectional studied carried out among diabetes patients also reported no significant association between diabetes knowledge and medication adherence . High medication adherence was observed among majority of the patients. Medication adherence was not found to be significantly different when compared with age, educational level, diabetes knowledge or attitude. Even though polypharmacy, due to comorbidities, is a risk for poor medication adherence, the present study and a similar study showed that medication adherence for diabetes patients does not decline with increase in medications taken. Glycemic control had no significant association with diabetes knowledge and attitude in this study. Another study carried out in Enugu State, Nigeria also found no significant association between diabetes attitude and glycemic control but found a significant association between diabetes knowledge and glycemic control . Glycemic control was significantly different with patients’ age, medication adherence and level of formal education. Geriatric patients are more likely to have comorbidities that could impact on their glycemic control. However, the geriatric patients in this study showed a significantly better attitude to diabetes which could explain their better glycemic control, despite the likelihood of comorbidities. Similar studies also reported that glycemic control was associated with formal education and medication adherence . However, a study by Al-Rasheedi found no association between glycemic control and level of educational qualification . A major limitation to this study was that glycemic control was assessed using fasting blood glucose instead of glycated hemoglobin (HbA1c) which is the gold standard. Also, data on level of income and duration of diabetes were not included in the study.
The diabetes patients displayed good disease knowledge and attitude. Level of health literacy and medication discrepancy was average among the patients, while a high proportion showed high medication adherence. Patients’ health literacy was significantly positively associated with diabetes knowledge. The determinants of diabetes knowledge are level of formal education, diabetes attitude, health literacy, and age; while the determinants of diabetes attitude are health literacy, age and diabetes knowledge. While the patients displayed good disease knowledge and attitude, it is important to ensure that this does not decline. The average level of health literacy should be put into consideration when passing medical information to the patients so as to ensure that they are able to appropriately interpret and comprehend the instructions.
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Proteomic patterns associated with ketamine response in major depressive disorders | 5b259b62-c430-4f2a-b706-64945530400b | 11723896 | Biochemistry[mh] | Major depressive disorder (MDD) is a severe mental health condition characterized by numerous emotional, cognitive, and physical symptoms that significantly impact the daily life of an individual (Gotlib and Joormann ). The core features of MDD include persistent low mood and loss of interest or pleasure in once-enjoyable activities (Kennedy ). Physical symptoms of MDD encompass fatigue and a lack of energy, contributing to a sense of physical and emotional exhaustion (Targum and Fava ). Feelings of worthlessness, excessive guilt, and self-criticism are frequent, which can distort one's self-perception. One of the most concerning aspects of MDD is the potential for suicidal thoughts or behaviors (Cai et al. ). Individuals may experience recurrent thoughts of death, contemplate suicide, or even formulate a specific plan to end their lives. This emphasizes the urgency of timely intervention and appropriate treatment. The use of ketamine to treat MDD has progressed from laboratory research to clinical application (Grady et al. ). Ketamine has been found to rapidly alleviate depressive symptoms at low doses, especially in individuals who have not responded well to traditional antidepressant medications (Krystal et al. ). Ketamine's antidepressant mechanism of action is linked to its interaction with NMDA (N-methyl-D-aspartate) receptors in the brain (Zanos and Gould ). It blocks these receptors, which subsequently affects the release of certain neurotransmitters, such as glutamate. This alteration in neurotransmission is believed to contribute to its antidepressant effects. Moreover, ketamine has been shown to promote neuroplasticity, the ability of the brain to reorganize and form new neural connections (Wu et al. ). This can potentially help reshape dysfunctional neural circuits that are implicated in depression. Research trials have demonstrated the effectiveness of ketamine in various studies; hence, the U.S. Food and Drug Administration (FDA) approved esketamine (a derivative of ketamine) nasal spray for treatment-resistant depression in 2019 (Wei et al. ). The response of individuals with MDD to ketamine treatment can vary widely (Shin and Kim ). Some individuals may experience substantial alleviation of their depressive symptoms, whereas others may see only partial or temporary relief. Proteomics, which involves the comprehensive study of proteins within a cell, tissue, or organism, is a valuable method for investigating drug mechanisms, developing personalized medicines, and identifying potential drug targets (Al-Amrani et al. ). However, little is known about how drugs interact with biological systems at the protein level, especially how ketamine affects MDD patients in this context. Therefore, here we implemented high-resolution mass spectrometry (MS)-based plasma proteomics to study ketamine response in 30 MDD patients whose plasma samples were collected before and after treatment. First, alterations at the proteomic level between responders and non-responders were analyzed using post-treatment proteomics data. Second, the temporal dynamics of proteomic changes from pre- to post-treatment were examined to gain insights into the mechanism of action of ketamine following drug administration. Third, pre-treatment proteomics data were utilized to identify proteins that could serve as predictors of individual responses to ketamine prior to treatment.
Ethical approval The study protocol was approved by the ethics committee for the Affiliated Brain Hospital of Guangzhou Medical University [(2016) No (030)] and was registered in the Chinese Clinical Trials Registry (Registration Number: ChiCTR-OOC-17012239; RRID:SCR_006037). The study was conducted according to the principles of the Declaration of Helsinki, and oral and written informed consent was obtained from all participants. Participant recruitment and clinical data collection The participants were administered six ketamine infusions (0.5 mg/kg, i.v.) in 50 mL 0.9% saline over a period of two weeks. Each infusion lasted 40 min, and the patients were closely monitored by proficient healthcare practitioners. Fasting plasma samples and clinical evaluations were obtained the day prior to the initial infusion and the day following the completion of the sixth infusion. The efficacy of the intervention was evaluated using the Hamilton Rating Scale for Depression (HAMD). A positive response was indicated by a decrease of at least 50% in the overall HAMD score compared with the baseline score. Plasma sample collection We used 5 mL vacutainer anticoagulant tubes with heparin lithium to collect fasting blood samples. The collected samples were centrifuged at a speed of 3000 revolutions per minute for 12 min, one hour after sample collection. The supernatant was divided into Eppendorf tubes in equal volumes, and subsequently subjected to cryopreservation at a temperature of −80 °C until MS-based proteomics analysis was performed. MS-based proteomics All MS-based analyses in this study were performed at Novogene (Novogene Co., Ltd. Beijing). High-abundance proteins were removed. The proteins were digested with trypsin. An Orbitrap Q Exactive HF-X mass spectrometer (Thermo Fisher; RRID:SCR_020564) in data-independent acquisition (DIA) mode was used. For the DIA operation, the m/z range was 350 to 1500, the MS1 resolution was 60,000 (at m/z 200), the full-scan automatic gain control (AGC) target value was 5 × 10 5 , the maximum ion injection time was 20 ms, the MS2 resolution was 30,000 (at 200 m/z), the peptides were fragmented by higher-energy collisional dissociation (HCD), the AGC target value was 1 × 10 6 , and the normalized collision energy was 27%. The raw MS detection data were saved as raw files. To identify and quantify proteins, the raw data generated by MS analysis were analyzed by Novogene (Novogene Co., Ltd., Beijing) in December 2022 using softwares such as Proteome Discoverer 2.2 (PD 2.2, Thermo; RRID:SCR_014477) and Spectronaut (version 14.0, Biognosys). For protein annotation, the Swiss-Prot/reviewed human reference proteome from the UniProt ( https://www.uniprot.org ; RRID:SCR_002380) database was used. Proteomics data processing Pre-treatment samples and post-treatment samples were sent for MS analysis at two different time points. For simplicity, we also referred to data derived from pre-treatment samples as DIA-pre, and data derived from post-treatment samples as DIA-post. To discern proteomic dynamics from pre- to post-treatment, data from the two batches need to be merged into a single data set so that expression levels of the same protein at different time points are comparable. Therefore, two pre-treatment samples as bridge samples were added and analyzed alongside post-treatment samples. With the bridge samples, we could also evaluate technical reproducibility across different batches via correlation analysis. When processing individual proteomics data sets, bridge samples in DIA-post were removed. Afterwards, DIA-pre and DIA-post were filtered such that proteins had at least 70% quantified values (proteins with > 30% missing values were discarded), and the missing values were set to 0. Protein abundance values were then log2 transformed for downstream analysis. To merge DIA-pre and DIA-post, protein abundance values relative to the bridge sample were calculated within each data set. To avoid a zero denominator, proteins of 0 values in the bridge sample were discarded. DIA-pre and DIA-post were then merged into a single harmonized data set accordingly (also referred to as DIA-merge). Differential abundance analysis Differentially abundant proteins (DAPs) were identified via ANCOVA implemented in R (RRID:SCR_001905) while controlling for covariates body mass index (BMI) and family history. A protein was considered a DAP across a given condition if its fold change was > 1.2 and p was < 0.05 unless otherwise noted. Of note, no multiple testing correction was performed unless otherwise specified. Human plasma proteins The Human Plasma Proteome Project (HPPP), which is part of the HUPO (RRID:SCR_010707) Human Proteome Project (HPP), aims to detect an ensemble of human plasma proteins with high quality mass spectrometry evidence (Deutsch et al. ). The human plasma 2021–07 build that contains 4395 canonical proteins identified by HPPP was downloaded from the Human Plasma PeptideAtlas database ( https://peptideatlas.org/builds/human/plasma/ ; RRID:SCR_006783). Plasma sample contamination analysis To assess and avoid sample-related biases originating from erythrocytes, platelets, and the blood coagulation system, three panels of quality markers defined by Geyer and colleagues via plasma proteome profiling were obtained (Geyer et al. ). Each of the erythrocyte and platelet panels contains 29 proteins, and the coagulation panel contains 31 proteins. For erythrocyte and platelet panels, the contamination index was calculated by summing their abundances and dividing by the summed abundance of all quantified plasma proteins. The coagulation contamination index was calculated as the sum of all plasma proteins divided by the sum of the proteins in the coagulation panel. We then assessed the quality of samples one by one by calculating the three contamination indices. For each panel of indices, we defined potentially contaminated samples as those with a value more than two standard deviations above the mean. Secreted proteins The human secretome, which comprises proteins secreted by various tissues, holds vital importance both for advancing our fundamental comprehension of human biology and for pinpointing promising targets in the development of novel diagnostic tools and therapeutic interventions. Final locations of proteins were obtained from the Human Protein Atlas ( https://www.proteinatlas.org ; RRID:SCR_006710) database, where the final location of a protein in the human body was defined by reviewing the literature, bioinformatics analyses, and experimental data (Uhlén et al. ; Uhlén et al. ). The downloaded data set contains 2793 genes that encode proteins secreted into 10 places, namely blood, brain, digestive system, female reproductive system, male reproductive system, other tissues, extracellular matrix, immunoglobulin genes, intracellular and membrane, and unknown location. Protein existence The protein existence status of a protein indicates the type of evidence that supports the existence of the protein (Zahn-Zabal et al. ). The data of protein existence were downloaded from the neXtProt database ( https://www.nextprot.org/ ; RRID:SCR_008911) from the 2022–08–18 release. Lists of accession numbers for proteins with existence evidence at protein level (PE1), at transcript level (PE2), by homology (PE3), predicted (PE4), and uncertain (PE5) were obtained. Functional enrichment analysis To find enriched biological pathways of a gene list of interest, Metascape (RRID:SCR_016620) was used (Zhou et al. ). We narrowed gene set terms down to biological processes of Gene Ontology (RRID:SCR_002811), canonical pathways, hallmark gene sets, Reactome gene sets (RRID:SCR_003485), KEGG pathway (RRID:SCR_012773), BioCarta gene sets (RRID:SCR_006917), and PANTHER pathway (RRID:SCR_004869). Other parameters were set to their default values. Correlation analysis The correlation between protein abundance and HAMD scores was evaluated using the cor function in R software, with Pearson correlation coefficients and p values estimated as well. Proteins with predictive value for ketamine response To estimate the performance of a protein in predicting ketamine response before treatment, we performed receiver operating characteristic (ROC) curve analysis in pre-treatment samples using R software. The ROC analysis was conducted exclusively for DAPs that were significantly correlated with HAMD scores. Statistics Differences in demographics and clinical variables between the two groups at baseline (i.e., before treatment) were analyzed in R software using Fisher’s exact test, t test, and chi-squared test, whichever is appropriate. Data deposition The MS-based proteomics data have been deposited into the ProteomeXchange Consortium ( http://proteomecentral.proteomexchange.org ; RRID:SCR_004055) via the iProX (RRID:SCR_026109) partner repository (Chen et al. ). Validation cohort For external validation of dysregulated proteins between ketamine responders and nonresponders, the data set GSE185855 from GEO (Gene Expression Omnibus; RRID:SCR_005012) was used. It is derived from the investigation of whole blood transcriptional profiles related to human MDD and gene expression changes associated with treatment response to ketamine (Cathomas et al. ). We used a metric of effect size, Cliff’s delta, to determine up- or down-regulated genes in ketamine responders (Cliff ; Cliff ). The R package effsize was used to compute Cliff’s delta values, using TPM (transcripts per million) expression values as input. The computed Cliff’s delta, D, is a non-parametric measure of the segregation between responders and non-responders, and it ranges from −1 to 1. A negative D indicates expression levels in non-responders tend to be higher than responders, while a positive D indicates expression levels in responders tend to be higher than non-responders. The magnitude of the effect size of Cliff’s delta is assessed using |D|< 0.147 for negligible, |D|< 0.33 for small, |D|< 0.474 for medium, and others for large (Lin et al. ). For genes that passed the negligible effect size threshold, a positive D indicates up-regulation, while a negative D indicates down-regulation in ketamine responders.
The study protocol was approved by the ethics committee for the Affiliated Brain Hospital of Guangzhou Medical University [(2016) No (030)] and was registered in the Chinese Clinical Trials Registry (Registration Number: ChiCTR-OOC-17012239; RRID:SCR_006037). The study was conducted according to the principles of the Declaration of Helsinki, and oral and written informed consent was obtained from all participants.
The participants were administered six ketamine infusions (0.5 mg/kg, i.v.) in 50 mL 0.9% saline over a period of two weeks. Each infusion lasted 40 min, and the patients were closely monitored by proficient healthcare practitioners. Fasting plasma samples and clinical evaluations were obtained the day prior to the initial infusion and the day following the completion of the sixth infusion. The efficacy of the intervention was evaluated using the Hamilton Rating Scale for Depression (HAMD). A positive response was indicated by a decrease of at least 50% in the overall HAMD score compared with the baseline score.
We used 5 mL vacutainer anticoagulant tubes with heparin lithium to collect fasting blood samples. The collected samples were centrifuged at a speed of 3000 revolutions per minute for 12 min, one hour after sample collection. The supernatant was divided into Eppendorf tubes in equal volumes, and subsequently subjected to cryopreservation at a temperature of −80 °C until MS-based proteomics analysis was performed.
All MS-based analyses in this study were performed at Novogene (Novogene Co., Ltd. Beijing). High-abundance proteins were removed. The proteins were digested with trypsin. An Orbitrap Q Exactive HF-X mass spectrometer (Thermo Fisher; RRID:SCR_020564) in data-independent acquisition (DIA) mode was used. For the DIA operation, the m/z range was 350 to 1500, the MS1 resolution was 60,000 (at m/z 200), the full-scan automatic gain control (AGC) target value was 5 × 10 5 , the maximum ion injection time was 20 ms, the MS2 resolution was 30,000 (at 200 m/z), the peptides were fragmented by higher-energy collisional dissociation (HCD), the AGC target value was 1 × 10 6 , and the normalized collision energy was 27%. The raw MS detection data were saved as raw files. To identify and quantify proteins, the raw data generated by MS analysis were analyzed by Novogene (Novogene Co., Ltd., Beijing) in December 2022 using softwares such as Proteome Discoverer 2.2 (PD 2.2, Thermo; RRID:SCR_014477) and Spectronaut (version 14.0, Biognosys). For protein annotation, the Swiss-Prot/reviewed human reference proteome from the UniProt ( https://www.uniprot.org ; RRID:SCR_002380) database was used.
Pre-treatment samples and post-treatment samples were sent for MS analysis at two different time points. For simplicity, we also referred to data derived from pre-treatment samples as DIA-pre, and data derived from post-treatment samples as DIA-post. To discern proteomic dynamics from pre- to post-treatment, data from the two batches need to be merged into a single data set so that expression levels of the same protein at different time points are comparable. Therefore, two pre-treatment samples as bridge samples were added and analyzed alongside post-treatment samples. With the bridge samples, we could also evaluate technical reproducibility across different batches via correlation analysis. When processing individual proteomics data sets, bridge samples in DIA-post were removed. Afterwards, DIA-pre and DIA-post were filtered such that proteins had at least 70% quantified values (proteins with > 30% missing values were discarded), and the missing values were set to 0. Protein abundance values were then log2 transformed for downstream analysis. To merge DIA-pre and DIA-post, protein abundance values relative to the bridge sample were calculated within each data set. To avoid a zero denominator, proteins of 0 values in the bridge sample were discarded. DIA-pre and DIA-post were then merged into a single harmonized data set accordingly (also referred to as DIA-merge).
Differentially abundant proteins (DAPs) were identified via ANCOVA implemented in R (RRID:SCR_001905) while controlling for covariates body mass index (BMI) and family history. A protein was considered a DAP across a given condition if its fold change was > 1.2 and p was < 0.05 unless otherwise noted. Of note, no multiple testing correction was performed unless otherwise specified.
The Human Plasma Proteome Project (HPPP), which is part of the HUPO (RRID:SCR_010707) Human Proteome Project (HPP), aims to detect an ensemble of human plasma proteins with high quality mass spectrometry evidence (Deutsch et al. ). The human plasma 2021–07 build that contains 4395 canonical proteins identified by HPPP was downloaded from the Human Plasma PeptideAtlas database ( https://peptideatlas.org/builds/human/plasma/ ; RRID:SCR_006783).
To assess and avoid sample-related biases originating from erythrocytes, platelets, and the blood coagulation system, three panels of quality markers defined by Geyer and colleagues via plasma proteome profiling were obtained (Geyer et al. ). Each of the erythrocyte and platelet panels contains 29 proteins, and the coagulation panel contains 31 proteins. For erythrocyte and platelet panels, the contamination index was calculated by summing their abundances and dividing by the summed abundance of all quantified plasma proteins. The coagulation contamination index was calculated as the sum of all plasma proteins divided by the sum of the proteins in the coagulation panel. We then assessed the quality of samples one by one by calculating the three contamination indices. For each panel of indices, we defined potentially contaminated samples as those with a value more than two standard deviations above the mean.
The human secretome, which comprises proteins secreted by various tissues, holds vital importance both for advancing our fundamental comprehension of human biology and for pinpointing promising targets in the development of novel diagnostic tools and therapeutic interventions. Final locations of proteins were obtained from the Human Protein Atlas ( https://www.proteinatlas.org ; RRID:SCR_006710) database, where the final location of a protein in the human body was defined by reviewing the literature, bioinformatics analyses, and experimental data (Uhlén et al. ; Uhlén et al. ). The downloaded data set contains 2793 genes that encode proteins secreted into 10 places, namely blood, brain, digestive system, female reproductive system, male reproductive system, other tissues, extracellular matrix, immunoglobulin genes, intracellular and membrane, and unknown location.
The protein existence status of a protein indicates the type of evidence that supports the existence of the protein (Zahn-Zabal et al. ). The data of protein existence were downloaded from the neXtProt database ( https://www.nextprot.org/ ; RRID:SCR_008911) from the 2022–08–18 release. Lists of accession numbers for proteins with existence evidence at protein level (PE1), at transcript level (PE2), by homology (PE3), predicted (PE4), and uncertain (PE5) were obtained.
To find enriched biological pathways of a gene list of interest, Metascape (RRID:SCR_016620) was used (Zhou et al. ). We narrowed gene set terms down to biological processes of Gene Ontology (RRID:SCR_002811), canonical pathways, hallmark gene sets, Reactome gene sets (RRID:SCR_003485), KEGG pathway (RRID:SCR_012773), BioCarta gene sets (RRID:SCR_006917), and PANTHER pathway (RRID:SCR_004869). Other parameters were set to their default values.
The correlation between protein abundance and HAMD scores was evaluated using the cor function in R software, with Pearson correlation coefficients and p values estimated as well.
To estimate the performance of a protein in predicting ketamine response before treatment, we performed receiver operating characteristic (ROC) curve analysis in pre-treatment samples using R software. The ROC analysis was conducted exclusively for DAPs that were significantly correlated with HAMD scores.
Differences in demographics and clinical variables between the two groups at baseline (i.e., before treatment) were analyzed in R software using Fisher’s exact test, t test, and chi-squared test, whichever is appropriate.
The MS-based proteomics data have been deposited into the ProteomeXchange Consortium ( http://proteomecentral.proteomexchange.org ; RRID:SCR_004055) via the iProX (RRID:SCR_026109) partner repository (Chen et al. ).
For external validation of dysregulated proteins between ketamine responders and nonresponders, the data set GSE185855 from GEO (Gene Expression Omnibus; RRID:SCR_005012) was used. It is derived from the investigation of whole blood transcriptional profiles related to human MDD and gene expression changes associated with treatment response to ketamine (Cathomas et al. ). We used a metric of effect size, Cliff’s delta, to determine up- or down-regulated genes in ketamine responders (Cliff ; Cliff ). The R package effsize was used to compute Cliff’s delta values, using TPM (transcripts per million) expression values as input. The computed Cliff’s delta, D, is a non-parametric measure of the segregation between responders and non-responders, and it ranges from −1 to 1. A negative D indicates expression levels in non-responders tend to be higher than responders, while a positive D indicates expression levels in responders tend to be higher than non-responders. The magnitude of the effect size of Cliff’s delta is assessed using |D|< 0.147 for negligible, |D|< 0.33 for small, |D|< 0.474 for medium, and others for large (Lin et al. ). For genes that passed the negligible effect size threshold, a positive D indicates up-regulation, while a negative D indicates down-regulation in ketamine responders.
Study design and participants We collected blood samples from a cohort of 30 MDD patients. For every participant, we collected samples both before and after ketamine treatment, which allowed us to examine the proteomic changes at different time points. At the end of the treatment, 20 responders (also referred to as R) and 10 non-responders (also referred to as NR) were identified (Fig. ). We compared demographic differences between the responders and non-responders. Except for body mass index (BMI) and family history, there was no significant difference between the two sub-populations (Table ). We then performed MS-based proteome profiling on each sample. The MS-based method implemented in this study has high robustness in terms of reproducibility, with a Pearson correlation coefficient of nearly 1 and p < 2.2e-16 (Supplementary Fig. ). Afterwards, downstream analyses of the obtained proteomics data were carried out. Pre-treatment proteomic profiles The in-depth proteomic landscape of 30 MDD patients before ketamine treatment was resolved using a high-resolution DIA MS-based method, and the proteome data, namely DIA-pre, was acquired. From the cohort, 8034 peptides in total were obtained, with the number ranging between 3669 and 6280 in individual samples, and with 2881 peptides repeatedly detected across all samples (Fig. A). After mapping these peptides to the human reference proteome, a total of 562 proteins were quantified in at least one sample, with the number ranging between 320 and 530 proteins in individual samples, and with 264 proteins commonly quantified across all samples (Fig. B). These identified proteins were supported by an average of 14 peptides, and 493 of these proteins (87.7%) could be traced and supported by at least 2 peptides (Fig. C). The number of samples where a protein was observed was counted. A small number of proteins were found to be restricted to a few samples while most of the proteins were quantified in the majority of the samples analyzed. The distribution of proteins identified in different samples was analyzed, and we found that only 21 proteins were detected in a single sample, that 541 proteins were quantified in at least 2 samples, that up to 264 (47%) proteins were simultaneously quantified in all 30 samples, and that, on average, proteins could be detected across 22 samples (Fig. D). To further evaluate the quality of DIA-pre, we compared it against public data sets. The sample contamination analysis revealed that no sample was contaminated by erythrocytes, platelets, or coagulation factors (Fig. E). Notably, the majority (522/562) of the proteins we identified were also in HPPP, constituting 12% of the HPPP data set (Fig. F). In line with the nature of our plasma samples, the identified proteins were mainly secreted into the blood (Fig. G). Nearly all of the identified proteins presented PE1 and PE2 levels of existence, and the majority had a level of PE1 (Fig. H). Therefore, these findings indicate high reliability of the MS-based analysis and high quality of the DIA-pre data set. Post-treatment proteomic profiles The proteome of MDD patients treated with ketamine holds great potential for advancing biomedical research and personalized medicine, but it has not been fully explored. In this study, we present an in-depth proteomic analysis of 30 MDD patients following ketamine treatment using a high-resolution, DIA-MS-based strategy. This resulted in the generation of a comprehensive proteome dataset, referred to as DIA-post. From the cohort, 8118 peptides in total were obtained, with the number ranging between 4876 and 6231 in individual samples, and with 3606 peptides repeatedly detected across all samples (Fig. A). After mapping these peptides to the human reference proteome, a total of 528 proteins were quantified in at least one sample, with the number ranging between 401 and 490 proteins in individual samples, and with 315 proteins commonly quantified across all samples (Fig. B). These identified proteins were supported by an average of 15 peptides, and 457 of these proteins (86.5%) could be traced and supported by at least 2 peptides (Fig. C). The number of samples where a protein was observed was counted. A small number of proteins were found to be restricted to a few samples while most of the proteins were quantified in the majority of the samples analyzed. The distribution of proteins identified in different samples was analyzed, and we found that only 5 proteins were detected in a single sample, that 523 proteins were quantified in at least 2 samples, that up to 315 (59.7%) proteins were simultaneously quantified in all 30 samples, and that, on average, proteins could be detected across 24 samples (Fig. D). We compared DIA-post with public data to further evaluate its quality. The sample contamination analysis revealed that no sample was contaminated by erythrocytes, platelets, or coagulation factors (Fig. E). Notably, the majority (489/528) of the proteins we identified were also in HPPP, constituting 11% of the HPPP data set (Fig. F). In line with the nature of our plasma samples, the identified proteins were mainly secreted into the blood (Fig. G). Nearly all of the identified proteins presented PE1 and PE2 levels of existence, and the majority had a level of PE1 (Fig. H). Therefore, these discoveries indicate high reliability of the MS-based analysis and high quality of the DIA-post data set. Proteome differences between ketamine responders and non-responders Hypothesizing that the differences in patients’ response to ketamine are merely superficial reflections of underlying molecular differences deeply rooted in the proteome, we analyzed altered proteins between ketamine responders and non-responders using the DIA-post data set. Differential abundance analysis revealed 45 DAPs, accounting for 11.3% of the total quantified post-treatment proteome. Compared to non-responders, 38 out of the 45 DAPs were up-regulated in responders, while the remained were down-regulated (Fig. A and B). We then performed unsupervised principal component analysis (PCA) and hierarchical clustering of the samples on the basis of the DAPs. The PCA result revealed a clear separation between responders and non-responders in the first two components (Fig. C). In agreement with the PCA result, hierarchical clustering clearly separated the two groups of the samples (Fig. D). Correlations between protein abundance and HAMD scores measured post ketamine treatment were analyzed. As shown in Fig. A and B, there were 31 proteins significantly correlated with post-treatment HAMD scores (p < 0.05), and the correlations were predominantly negative. Among the 31 proteins, there were 9 DAPs, and they were all negatively correlated with post-treatment HAMD scores, with the exception of IGLV2-23. Correlations between protein abundance and decreases in HAMD scores from pre-treatment to post-treatment were analyzed as well. As shown in Fig. C and D, 24 proteins were significantly correlated with HAMD score decreases (p < 0.05), and most of the correlations were positive. Among them, six proteins were also DAPs, namely IGKV2D-30, COMP, IGHV3-64, IGHV3-15, ADAMTSL4, and IGLV2-23. Intriguingly, these six proteins were also significantly correlated with post-treatment HAMD scores. Upon analyzing the correlations of the six proteins, we found a striking pattern: proteins negatively correlated with post-treatment HAMD scores were positively correlated with the reduction in HAMD scores, and vice versa (Supplementary Fig. and Fig. E-J). These proteins may constitute a core set of plasma proteins associated with the mechanism by which ketamine alleviates depression. To further elucidate the function of the six proteins, we annotated them with Gene Ontology terms. The main biological process they are involved in is related to immune response, and they mainly possess the molecular function of binding to other biomolecules (Supplementary Table ). We then examined their differential expression profiles and found that all but IGLV2-23 were up-regulated in ketamine responders (Fig. A-F). Proteins frequently collaborate with each other to exert their functions. We used 398 proteins in the DIA-post data set and incorporated 2 clinical parameters (group label and post-treatment HAMD score). The proteins, along with the clinical parameters, comprised a vector of 400 elements. We cross-correlated them to generate a matrix of 160,000 correlation coefficients. We then developed a global correlation map to capture the coordination between the proteins and clinical metrics, aiming to uncover the antidepressant mechanisms of ketamine. As can be seen in Fig. G, five of the six proteins form two big cluster areas with other proteins and the group clinical parameter. On the contrary, IGLV2-23, the only protein up-regulated in non-responders and positively correlated with post-treatment HAMD scores, clusters closely with the corresponding clinical parameter and maintains a distinct distance from the other two areas. We further carried out enrichment analysis of proteins belonging to the two clusters, and the enriched pathways are related to immune response. These findings indicate that the antidepressive effect of ketamine results from co-regulation of proteins that perform similar functions in the body. Bearing these results in mind, we propose that the differences in patients’ response to ketamine is manifested by the six-protein panel and that the antidepressive mechanisms of ketamine is associated mainly with immune response. Compared with the other five proteins, IGLV2-23 functions in an opposite way. It is down-regulated in responders, negatively correlated with HAMD score decreases, and positively correlated with post-treatment HAMD scores. Ketamine is likely to take antidepressive effect by down-regulating IGLV2-23 and up-regulating the other five proteins. Dynamic proteome rearrangements reveal the effect of ketamine over time Drug response is reflected in the change that occurs between two states (e.g., pre- and post-treatment), rather than a snapshot of one of them. To identify how ketamine affects the proteome over time, we used matched samples from the same donors in our cohort and performed a paired Student’s t test between matched pre- and post-treatment samples for responders and non-responders, respectively. For easy writing and reading, the comparison in responders is named R_pre_post, and that in non-responders is named NR_pre_post. Here the differential abundance analysis was performed via paired Student’s t-test using R software. P values were adjusted using the Benjamini–Hochberg method via the p.adjust function in R. A more stringent significance cutoff was used to select DAPs. We chose adjusted p < 0.01 instead of p < 0.05 to reduce the proportion of common DAPs between R_pre_post and NR_pre_post (Supplementary Fig. ). The change in the cutoff mainly affected the number of DAPs in NR_pre_post, whereas the impact was subtle in R_pre_post. The number of DAPs in NR_pre_post dramatically decreased from 83 to 11. This stringent approach is designed to minimize false positives and uncover accurate results. We identified 81 significantly altered proteins in responders over the entire time course, accounting for 22.3% of all proteins; however, 97% of the proteins remained unaltered after treatment in non-responders (Fig. A and Supplementary Fig. ). Subsequent PCA and hierarchical clustering revealed that pre- and post-treatment samples of responders were clearly separated by the altered proteins (Fig. B and ). Enrichment analysis of up-regulated proteins upon treatment in responders revealed a significant enrichment of adaptive immune response, humoral immune response, plasma lipoprotein remodeling, hydrogen peroxide catabolic process, amyloid fiber formation, response to glucocorticoid, NABA ECM regulators, extracellular matrix organization, hemostasis, and axon development (Fig. D). Enrichment analysis of down-regulated proteins upon treatment in responders revealed a significant enrichment of adaptive immune response, blood vessel morphogenesis, response to wounding, and negative regulation of cell differentiation (Fig. E). The results indicate ketamine triggers changes in proteins belonging to different functional groups to execute its effect over time post administration. Proteins capable of differentiating ketamine responders from non-responders Identifying a metric to distinguish responders from non-responders before treatment is beneficial to patients and would ultimately facilitate personalized medicine in MDD treatment. Here, we used proteome data from pre-treatment samples to identify proteins that can predict the response of MDD patients to ketamine before treatment. We performed PCA before differential abundance analysis and found that data points of two samples were located far from other data points (Supplementary Fig. ). They seemed to be outliers and were removed from analysis to reduce distortion caused by them. We found 14 DAPs in responders versus non-responders (Supplementary Fig. A). Next, PCA revealed that the two groups can be separated by these DAPs to a certain extent (Supplementary Fig. B). Even though there were two samples incorrectly clustered into the NR group by hierarchical clustering, the divergence of the two clusters was obvious (Supplementary Fig. C). Next, we performed correlation analysis of protein abundance with HAMD scores measured before treatment. Twenty proteins significantly correlated with pre-treatment HAMD scores were discovered (Fig. A and B). Among them, three proteins were also DAPs (Supplementary Fig. C) and were negatively correlated with pre-treatment HAMD scores (Fig. C-E). These three proteins were also up-regulated in responders (Supplementary Fig. C). To determine whether a higher expression level of these proteins indicates a better clinical outcome, we performed receiver operating characteristic (ROC) analysis. Indeed, all three proteins achieved good performance in predicting ketamine response, using the pre-treatment proteomics data only (Fig. F-H). Therefore, it is reasonable to apply these proteins as treatment response biomarkers in clinic to identify MDD patients suitable for ketamine treatment at an early stage.
We collected blood samples from a cohort of 30 MDD patients. For every participant, we collected samples both before and after ketamine treatment, which allowed us to examine the proteomic changes at different time points. At the end of the treatment, 20 responders (also referred to as R) and 10 non-responders (also referred to as NR) were identified (Fig. ). We compared demographic differences between the responders and non-responders. Except for body mass index (BMI) and family history, there was no significant difference between the two sub-populations (Table ). We then performed MS-based proteome profiling on each sample. The MS-based method implemented in this study has high robustness in terms of reproducibility, with a Pearson correlation coefficient of nearly 1 and p < 2.2e-16 (Supplementary Fig. ). Afterwards, downstream analyses of the obtained proteomics data were carried out.
The in-depth proteomic landscape of 30 MDD patients before ketamine treatment was resolved using a high-resolution DIA MS-based method, and the proteome data, namely DIA-pre, was acquired. From the cohort, 8034 peptides in total were obtained, with the number ranging between 3669 and 6280 in individual samples, and with 2881 peptides repeatedly detected across all samples (Fig. A). After mapping these peptides to the human reference proteome, a total of 562 proteins were quantified in at least one sample, with the number ranging between 320 and 530 proteins in individual samples, and with 264 proteins commonly quantified across all samples (Fig. B). These identified proteins were supported by an average of 14 peptides, and 493 of these proteins (87.7%) could be traced and supported by at least 2 peptides (Fig. C). The number of samples where a protein was observed was counted. A small number of proteins were found to be restricted to a few samples while most of the proteins were quantified in the majority of the samples analyzed. The distribution of proteins identified in different samples was analyzed, and we found that only 21 proteins were detected in a single sample, that 541 proteins were quantified in at least 2 samples, that up to 264 (47%) proteins were simultaneously quantified in all 30 samples, and that, on average, proteins could be detected across 22 samples (Fig. D). To further evaluate the quality of DIA-pre, we compared it against public data sets. The sample contamination analysis revealed that no sample was contaminated by erythrocytes, platelets, or coagulation factors (Fig. E). Notably, the majority (522/562) of the proteins we identified were also in HPPP, constituting 12% of the HPPP data set (Fig. F). In line with the nature of our plasma samples, the identified proteins were mainly secreted into the blood (Fig. G). Nearly all of the identified proteins presented PE1 and PE2 levels of existence, and the majority had a level of PE1 (Fig. H). Therefore, these findings indicate high reliability of the MS-based analysis and high quality of the DIA-pre data set.
The proteome of MDD patients treated with ketamine holds great potential for advancing biomedical research and personalized medicine, but it has not been fully explored. In this study, we present an in-depth proteomic analysis of 30 MDD patients following ketamine treatment using a high-resolution, DIA-MS-based strategy. This resulted in the generation of a comprehensive proteome dataset, referred to as DIA-post. From the cohort, 8118 peptides in total were obtained, with the number ranging between 4876 and 6231 in individual samples, and with 3606 peptides repeatedly detected across all samples (Fig. A). After mapping these peptides to the human reference proteome, a total of 528 proteins were quantified in at least one sample, with the number ranging between 401 and 490 proteins in individual samples, and with 315 proteins commonly quantified across all samples (Fig. B). These identified proteins were supported by an average of 15 peptides, and 457 of these proteins (86.5%) could be traced and supported by at least 2 peptides (Fig. C). The number of samples where a protein was observed was counted. A small number of proteins were found to be restricted to a few samples while most of the proteins were quantified in the majority of the samples analyzed. The distribution of proteins identified in different samples was analyzed, and we found that only 5 proteins were detected in a single sample, that 523 proteins were quantified in at least 2 samples, that up to 315 (59.7%) proteins were simultaneously quantified in all 30 samples, and that, on average, proteins could be detected across 24 samples (Fig. D). We compared DIA-post with public data to further evaluate its quality. The sample contamination analysis revealed that no sample was contaminated by erythrocytes, platelets, or coagulation factors (Fig. E). Notably, the majority (489/528) of the proteins we identified were also in HPPP, constituting 11% of the HPPP data set (Fig. F). In line with the nature of our plasma samples, the identified proteins were mainly secreted into the blood (Fig. G). Nearly all of the identified proteins presented PE1 and PE2 levels of existence, and the majority had a level of PE1 (Fig. H). Therefore, these discoveries indicate high reliability of the MS-based analysis and high quality of the DIA-post data set.
Hypothesizing that the differences in patients’ response to ketamine are merely superficial reflections of underlying molecular differences deeply rooted in the proteome, we analyzed altered proteins between ketamine responders and non-responders using the DIA-post data set. Differential abundance analysis revealed 45 DAPs, accounting for 11.3% of the total quantified post-treatment proteome. Compared to non-responders, 38 out of the 45 DAPs were up-regulated in responders, while the remained were down-regulated (Fig. A and B). We then performed unsupervised principal component analysis (PCA) and hierarchical clustering of the samples on the basis of the DAPs. The PCA result revealed a clear separation between responders and non-responders in the first two components (Fig. C). In agreement with the PCA result, hierarchical clustering clearly separated the two groups of the samples (Fig. D). Correlations between protein abundance and HAMD scores measured post ketamine treatment were analyzed. As shown in Fig. A and B, there were 31 proteins significantly correlated with post-treatment HAMD scores (p < 0.05), and the correlations were predominantly negative. Among the 31 proteins, there were 9 DAPs, and they were all negatively correlated with post-treatment HAMD scores, with the exception of IGLV2-23. Correlations between protein abundance and decreases in HAMD scores from pre-treatment to post-treatment were analyzed as well. As shown in Fig. C and D, 24 proteins were significantly correlated with HAMD score decreases (p < 0.05), and most of the correlations were positive. Among them, six proteins were also DAPs, namely IGKV2D-30, COMP, IGHV3-64, IGHV3-15, ADAMTSL4, and IGLV2-23. Intriguingly, these six proteins were also significantly correlated with post-treatment HAMD scores. Upon analyzing the correlations of the six proteins, we found a striking pattern: proteins negatively correlated with post-treatment HAMD scores were positively correlated with the reduction in HAMD scores, and vice versa (Supplementary Fig. and Fig. E-J). These proteins may constitute a core set of plasma proteins associated with the mechanism by which ketamine alleviates depression. To further elucidate the function of the six proteins, we annotated them with Gene Ontology terms. The main biological process they are involved in is related to immune response, and they mainly possess the molecular function of binding to other biomolecules (Supplementary Table ). We then examined their differential expression profiles and found that all but IGLV2-23 were up-regulated in ketamine responders (Fig. A-F). Proteins frequently collaborate with each other to exert their functions. We used 398 proteins in the DIA-post data set and incorporated 2 clinical parameters (group label and post-treatment HAMD score). The proteins, along with the clinical parameters, comprised a vector of 400 elements. We cross-correlated them to generate a matrix of 160,000 correlation coefficients. We then developed a global correlation map to capture the coordination between the proteins and clinical metrics, aiming to uncover the antidepressant mechanisms of ketamine. As can be seen in Fig. G, five of the six proteins form two big cluster areas with other proteins and the group clinical parameter. On the contrary, IGLV2-23, the only protein up-regulated in non-responders and positively correlated with post-treatment HAMD scores, clusters closely with the corresponding clinical parameter and maintains a distinct distance from the other two areas. We further carried out enrichment analysis of proteins belonging to the two clusters, and the enriched pathways are related to immune response. These findings indicate that the antidepressive effect of ketamine results from co-regulation of proteins that perform similar functions in the body. Bearing these results in mind, we propose that the differences in patients’ response to ketamine is manifested by the six-protein panel and that the antidepressive mechanisms of ketamine is associated mainly with immune response. Compared with the other five proteins, IGLV2-23 functions in an opposite way. It is down-regulated in responders, negatively correlated with HAMD score decreases, and positively correlated with post-treatment HAMD scores. Ketamine is likely to take antidepressive effect by down-regulating IGLV2-23 and up-regulating the other five proteins.
Drug response is reflected in the change that occurs between two states (e.g., pre- and post-treatment), rather than a snapshot of one of them. To identify how ketamine affects the proteome over time, we used matched samples from the same donors in our cohort and performed a paired Student’s t test between matched pre- and post-treatment samples for responders and non-responders, respectively. For easy writing and reading, the comparison in responders is named R_pre_post, and that in non-responders is named NR_pre_post. Here the differential abundance analysis was performed via paired Student’s t-test using R software. P values were adjusted using the Benjamini–Hochberg method via the p.adjust function in R. A more stringent significance cutoff was used to select DAPs. We chose adjusted p < 0.01 instead of p < 0.05 to reduce the proportion of common DAPs between R_pre_post and NR_pre_post (Supplementary Fig. ). The change in the cutoff mainly affected the number of DAPs in NR_pre_post, whereas the impact was subtle in R_pre_post. The number of DAPs in NR_pre_post dramatically decreased from 83 to 11. This stringent approach is designed to minimize false positives and uncover accurate results. We identified 81 significantly altered proteins in responders over the entire time course, accounting for 22.3% of all proteins; however, 97% of the proteins remained unaltered after treatment in non-responders (Fig. A and Supplementary Fig. ). Subsequent PCA and hierarchical clustering revealed that pre- and post-treatment samples of responders were clearly separated by the altered proteins (Fig. B and ). Enrichment analysis of up-regulated proteins upon treatment in responders revealed a significant enrichment of adaptive immune response, humoral immune response, plasma lipoprotein remodeling, hydrogen peroxide catabolic process, amyloid fiber formation, response to glucocorticoid, NABA ECM regulators, extracellular matrix organization, hemostasis, and axon development (Fig. D). Enrichment analysis of down-regulated proteins upon treatment in responders revealed a significant enrichment of adaptive immune response, blood vessel morphogenesis, response to wounding, and negative regulation of cell differentiation (Fig. E). The results indicate ketamine triggers changes in proteins belonging to different functional groups to execute its effect over time post administration.
Identifying a metric to distinguish responders from non-responders before treatment is beneficial to patients and would ultimately facilitate personalized medicine in MDD treatment. Here, we used proteome data from pre-treatment samples to identify proteins that can predict the response of MDD patients to ketamine before treatment. We performed PCA before differential abundance analysis and found that data points of two samples were located far from other data points (Supplementary Fig. ). They seemed to be outliers and were removed from analysis to reduce distortion caused by them. We found 14 DAPs in responders versus non-responders (Supplementary Fig. A). Next, PCA revealed that the two groups can be separated by these DAPs to a certain extent (Supplementary Fig. B). Even though there were two samples incorrectly clustered into the NR group by hierarchical clustering, the divergence of the two clusters was obvious (Supplementary Fig. C). Next, we performed correlation analysis of protein abundance with HAMD scores measured before treatment. Twenty proteins significantly correlated with pre-treatment HAMD scores were discovered (Fig. A and B). Among them, three proteins were also DAPs (Supplementary Fig. C) and were negatively correlated with pre-treatment HAMD scores (Fig. C-E). These three proteins were also up-regulated in responders (Supplementary Fig. C). To determine whether a higher expression level of these proteins indicates a better clinical outcome, we performed receiver operating characteristic (ROC) analysis. Indeed, all three proteins achieved good performance in predicting ketamine response, using the pre-treatment proteomics data only (Fig. F-H). Therefore, it is reasonable to apply these proteins as treatment response biomarkers in clinic to identify MDD patients suitable for ketamine treatment at an early stage.
Due to limitations such as low remission rate, delayed onset of effect, and side effects of most currently available antidepressants targeting the monoamine system, the need for a more effective and rapid-acting antidepressant is necessary (Katz et al. ). After the study demonstrating that intravenous administration of ketamine may have a rapid effect of antidepression in MDD patients, ketamine has been a focus of attention as a novel antidepressant with a novel target associated with the glutamatergic system (Berman et al. ). Ketamine has been shown to be effective in treating suicidal ideation in emergency room settings, and numerous studies involving both humans and animals have demonstrated its antidepressant effects (Krystal et al. ). While encouraging clinical and preclinical findings have been reported, there is still controversy surrounding the efficacy of ketamine in treating MDD. Approximately 10% of depressed patients who receive ketamine treatment do not experience a response, and this percentage may be even higher for individuals with treatment-resistant depression (Murrough et al. ; Szymkowicz et al. ). This emphasizes efforts in studying ketamine response so that more effective treatment interventions for MDD can be developed. To date, many efforts have been made to examine transcriptional regulations by ketamine. Mastrodonato et al. found that the activation of ventral CA3 mediates the prophylactic efficacy of ketamine against depressive-like behaviors caused by stress (Mastrodonato et al. ). Kim et al. found that the phosphorylation of methyl-CpG-binding protein 2 (MeCP2) at Ser421 is essential for the sustained, but not the rapid, antidepressant effects of ketamine, and additionally, this phosphorylation is required for the long-term regulation of synaptic strength following ketamine treatment (Kim et al. ). Ho et al. discovered that ketamine modulates the type I interferon pathway, at least in part by influencing signal transducer and activator of transcription 3 (STAT3) which is crucial for immune responses and may therefore contribute to the antidepressant effects of ketamine (Ho et al. ). Bagot et al. found that ketamine induces changes of gene expression in hippocampus and resilience-associated transcription in prefrontal cortex (Bagot et al. ). Although some progress has been made in proteomic research on the antidepressant effects of ketamine, it remains limited to animal models. Shweiki and colleagues conducted label-free shotgun proteomics analysis on mouse brain tissues one hour after s-ketamine administration, and they discovered a significant proteomic pattern of the rapid effect of ketamine in the amygdala (Al Shweiki et al. ). In their research involving proteomics and metabolomics in mice, Weckmann and colleagues discovered that ketamine influences the AMPAR subunit Gria2, leading to reduced GABAergic inhibition and subsequently heightened excitatory neuronal activity (Weckmann et al. ). Weckmann and team analyzed the hippocampi of mice treated with ketamine using metabolomic and proteomic profiling. Their analysis found that mitochondrial energy metabolism and the antioxidant defense system are key downstream effectors in the response to ketamine (Weckmann et al. ). Human plasma and serum are rich sources of biological information that reflects normal physiological conditions, disease processes, or responses to exposures or interventions (Anderson and Anderson ). Laboratory tests most frequently involve proteins and enzymes, highlighting the critical role of the plasma proteome in clinical diagnostics and guiding medical decisions (Geyer et al. ). MS-based proteomics now enables highly specific and quantitative analysis of the plasma proteome. Here, we employed plasma proteome profiling of a cohort of 30 MDD patients. To the best of our knowledge, this study represents the first investigation of ketamine response in human beings using plasma proteomics. Our study provides a foundation for future research in this area. We revealed the proteomic landscape of MDD patients before ketamine treatment for the first time. In pre-treatment proteome, 8034 peptides were obtained, within which 2881 peptides repeatedly detected across all samples; 562 proteins were quantified in at least one sample, with 264 proteins commonly quantified across all samples; the identified proteins were supported by an average of 14 peptides, and 493 of these proteins (87.7%) could be traced and supported by at least 2 peptides; a small number of proteins were found to be restricted to a few samples while most of the proteins were quantified in the majority of the samples analyzed; contamination analysis showed no sample was contaminated by erythrocytes, platelets, or coagulation factors; compared to the HPPP data, the majority (522/562) of the proteins we identified were in HPPP, constituting 12% of the HPPP data set; the identified proteins were mainly secreted into the blood; and nearly all of the identified proteins have a protein existence level of PE1 and PE2, with the majority as PE1. We revealed the proteomic landscape of MDD patients after ketamine treatment for the first time. In post-treatment proteome, 8118 peptides were obtained, within which 3606 peptides were repeatedly detected across all samples; 528 proteins were quantified in at least one sample, with 315 proteins commonly quantified across all samples; the identified proteins were supported by an average of 15 peptides, and 457 of these proteins (86.5%) could be traced and supported by at least 2 peptides; a small number of proteins were found to be restricted to a few samples while most of the proteins were quantified in the majority of the samples analyzed; contamination analysis showed no sample was contaminated by erythrocytes, platelets, or coagulation factors; compared to the HPPP data, the majority (489/528) of the proteins we identified were in HPPP, constituting 11% of the HPPP data set; the identified proteins were mainly secreted into the blood; and nearly all of the identified proteins have a protein existence level of PE1 and PE2, with the majority as PE1. Changes in human plasma proteins are widely acknowledged as key indicators of drug effects (Li et al. ). After two weeks of ketamine treatment, MDD patients were grouped into responders and non-responders, according to their treatment outcomes. We then analyzed differentially abundant proteins between responders and non-responders. The differential abundance analysis identified 45 DAPs and most of them were up-regulated in responders (Fig. ). Correlation analysis revealed that six DAPs (namely IGKV2D-30, COMP, IGHV3-64, IGHV3-15, ADAMTSL4, and IGLV2-23) were significantly correlated with the decrease of HAMD scores from pre- to post-treatment (Fig. C-J). IGLV2-23 was up-regulated in non-responders and negatively correlated with HAMD decreases. In contrast, the other five proteins were up-regulated in responders and positively correlated with HAMD score decreases. This indicates IGLV2-23 and the other five proteins need to be regulated in opposite modes for ketamine to achieve its intended effect. Using GSE185855 as a validation data set, we confirmed the up-regulation of ADAMTSL4 and IGKV2D-30 in ketamine responders within the external validation cohort (Supplementary Fig. ) (Cathomas et al. ). The unsuccessful validation of the other four proteins may be attributed to differences between the cohorts. Specifically, the validation cohort consisted exclusively of treatment-resistant depression cases, whereas ours additionally included non-resistant depression cases. Furthermore, the discrepancy could also result from differences between RNA-seq and proteomics data because transcriptomes and proteomes of human tissues could be different from each other (Wilhelm et al. ). We annotated these six proteins by Gene Ontology, and they are mainly related to immune response biological processes and the biomolecule binding molecular function. Global correlation analysis of protein expression plus clinical parameters revealed that the six proteins and their co-expressed proteins were enriched in pathways associated with immune response (Fig. ). It is widely recognized that depression correlates with inflammatory factors present in both the innate and adaptive immune systems (Roman and Irwin ). Repeated stress in animals can lead to immune activation, which may result in behaviors similar to depression (Hodes et al. ). Higher levels of circulating markers of inflammation are associated with a poor response to antidepressant treatment, but the findings regarding ketamine point in the opposite direction (Carvalho et al. ; O’Brien et al. ). A focused multiplexed proteomic analysis also revealed ketamine-induced alterations in immune markers within rat serum (Wesseling et al. ). In line with these existing studies, our findings provide a molecular rationale for the investigation of ketamine as an antidepressant by an immunologic lens that links immune dysfunction to depressive disorders. We conducted quantitative proteomics analysis to elucidate termporal proteome dynamics of paired plasma samples obtained from MDD patients, both prior to ketamine administration and following completion of the treatment. The plasma proteome profiles of a meticulously documented longitudinal cohort, accompanied by extensive clinical annotations, offers an inaugural prospect for a systematic examination of the dynamic impact of ketamine on MDD over time. The comparison of paired proteomes in non-responders demonstrated subtle alterations over time (Supplementary Fig. ). This may explain the lack of effectiveness observed in non-responders. Following the comparison of paired proteomes in responders, we characterized the longitudinal trajectories of 81 significantly altered proteins in response to ketamine administration. We then applied functional enrichment analysis to uncover the underlying physiological mechanisms driving these changes. The up-regulated proteins were enriched in adaptive immune response, humoral immune response, plasma lipoprotein remodeling, hydrogen peroxide catabolic process, amyloid fiber formation, response to glucocorticoid, NABA ECM regulators, extracellular matrix organization, hemostasis, and axon development (Fig. D). The down-regulated proteins were enriched in adaptive immune response, blood vessel morphogenesis, response to wounding, and negative regulation of cell differentiation (Fig. E). Interestingly, Herzog et al. conducted a longitudinal cerebrospinal fluid proteome profiling using an unbiased, hypothesis-free MS-based proteomics approach. Their findings revealed that significantly differentially expressed proteins are predominantly implicated in the glucocorticoid receptor signaling pathway, which aligns with our temporal dynamics analysis (Herzog et al. ). The results imply that glucocorticoid plays an important role in the antidepressive action of ketamine. During the drug selection process, it is crucial to ascertain which patients will exhibit favorable responses to treatment. Clinical studies have demonstrated the efficacy of ketamine infusion in resolving symptoms in MDD patients. However, those findings are usually controversial. For example, Murrough et al. found that a slower processing speed at baseline predicted a better ketamine response, but Gorlyn et al. suggested that slower processing speed is linked to a poorer response (Gorlyn et al. ; Murrough et al. ). Here we expected to find predictors of ketamine response at the proteomic level. Taking ROC analysis as the strategy, we found the baseline expression levels of three proteins (i.e., PI16, NEO1, and TNXB) exhibit good performance in predicting MDD patients’ response to ketamine treatment. PI16 has shown anti-inflammatory properties and is involved in regulating the immune response (Garrity et al. ). NEO1 is known to play a role in various biological processes, including neural development and axon guidance (Wilson and Key ). TNXB is predominantly expressed in connective tissues and its function appears to be context-dependent (Chiquet-Ehrismann and Tucker ). All the three proteins are negatively correlated with HAMD scores, indicating that higher expression levels of these proteins are associated with lower depression severity. Therefore, these proteins not only have the potential to predict the response to ketamine treatment but also tend to be linked to the pathology of MDD. Missing values caused by the limit of detection or quantification are widely observed in MS-based proteomics studies. In the present study, proteins of more than 30% missing values were discarded. This criteria of proteomics data filtration has been widely used and it ensures sufficient and high-quality data for downstream analysis (Shenoy et al. ; Shu et al. ). Regarding the imputation of missing values, we simply replaced them with 0, a common practice in similar studies (Bader et al. ; Blume et al. ). However, there are other imputation methods that merit consideration in future studies, such as imputation based on a (multivariate) normal distribution or replacing missing values with the minimum value from each sample (Liu and Dongre ). We acknowledge that the present study has some limitations. First, due to the challenges in participant recruitment, the number of plasma samples available for proteomics profiling was limited. Regardless of the promising findings achieved in this initial study, it would be ideal to involve a larger number of clinical samples, preferably from multiple centers. Such an expansion would not only enhance the robustness and generalizability of our findings but also provide a more comprehensive understanding of the variability and consistency of our results across different populations and settings. Second, owing to the relatively small number of participants, the clinical nature of the six core proteins and the three treatment response biomarkers awaits further verification in larger independent populations. Besides statistical analyses, additional experiments need to be performed for stringent validation of the detailed roles of the core proteins and biomarker proteins. Lastly, the lack of long-term follow-up after treatment completion limits clinical manifestations, which should be carefully addressed during the initial design phase of future experiments to ensure more comprehensive outcomes and better support the translation of research into clinical practice.
Although ketamine has been used as a rapid-acting antidepressant, its molecular mechanisms of action remain elusive. In this work, we aimed to study ketamine response from a system-wide perspective at the proteomic level. This was carried out by profiling matched pre- and post-treatment samples of a cohort of 30 MDD patients using an MS-based plasma proteomics strategy. To our knowledge, this is the first large-scale plasma proteomics study in MDD patients. For the first time, we revealed the proteomic landscapes of MDD patients both before and after ketamine treatment. We discovered a panel of six proteins which has core functional relevance with the antidepressive effects of ketamine. By comparing pre- and post-treatment proteomes of the same sample donors, we discerned the temporal pattern of proteomic changes caused by ketamine administration. We analyzed the ability of protein expression levels to predict patients’ response to ketamine, and we identified three proteins as predictors of ketamine response prior to treatment initiation. In conclusion, this is the most extensive quantitative plasma proteomics study of ketamine response in MDD thus far, providing the research community with a rich resource to better understand the response of MDD patients to ketamine. Moreover, it will also shed light on the discovery of valuable biomarker candidates and new strategies for MDD treatment.
Below is the link to the electronic supplementary material. Fig. 9 Supplementary Figure 1. Pearson correlation between DIA-pre and DIA-post. Replicate measurements of the same sample show high reproducibility. Points in the diagram represent proteins. High resolution image (TIF 2067 KB) Fig. 10 Supplementary Figure 2. Correlation of individual proteins with post-treatment HAMD scores. High resolution image (TIF 487 KB) Fig. 11 Supplementary Figure 3. Shared proteins at different cutoff values. (A) Common DAPs at p < 0.05. (B) Common DAPs at adjusted p < 0.01. High resolution image (TIF 67 KB) Fig. 12 Supplementary Figure 4. Differential abundance profile of non-responders before and after treatment. High resolution image (TIF 1783 KB) Fig. 13 Supplementary Figure 5. The two samples as outliers denoted by blue arrows were removed from analysis. High resolution image (TIF 1787 KB) Fig. 14 Supplementary Figure 6. Analyses of the DIA-pre data. (A) Differential abundance analysis in R versus NR. (B) PCA based on DAPs in A. (C) Hierarchical clustering based on DAPs in A. High resolution image (TIF 457 KB) Fig. 15 Supplementary Figure 7. Gene expression levels of six DAPs in the data set GSE185855. ADAMTSL4, IGKV2D-30 and IGLV2-23 were up-regulated, and IGHV3-64 was down-regulated in ketamine responders. COMP and IGHV3-15 did not pass the negligible effect size threshold. Large: ***; medium: **; Public data: https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185855; Number of responders: 3; Number of non-responders: 2. High resolution image (TIF 62 KB) Supplementary file8 (DOCX 11 KB)
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Community Hospice Nurses’ Perspectives on Needs, Preferences, and Challenges Related to Caring for Children With Serious Illness | 97dd2546-fb54-4081-9011-93bb88f9df29 | 8491107 | Pediatrics[mh] | Approximately 500 000 children in the US have a serious illness, of whom 10% die annually, and of those, 11% die at home —a number that continues to increase. Optimal provision of home-based hospice services can lessen symptom burden and improve quality of life, reduce parental psychosocial stress, , decrease costs, , and limit clinician distress. Accordingly, the Institute of Medicine and the American Academy of Pediatrics advocate for the early integration of palliative and hospice services for children with serious illness. , , Presently, however, only 1 in 10 dying children receive hospice care, usually through adult organizations. , , Although National Hospice and Palliative Care Organization surveys have shown that more than three-quarters of adult hospices serve pediatric patients, only 14% have pediatric-specific programs. Johnston et al revealed that bereaved parents desired home death but reported that lack of home support made dying at home challenging, with poor symptom management leading to returns to the hospital. Caring for children at the end of life poses unique challenges that demand pediatric-specific knowledge. Alongside balancing symptom management, communication, and care coordination, hospice clinicians also carry an emotional burden, which may contribute to stress and moral distress. , Unfortunately, few community hospice nurses receive pediatric-specific training, resources, and support. , , A previous study surveyed more than 550 hospice nurses across 71 hospice agencies that offer care to children in the tristate region of Tennessee, Arkansas, and Mississippi and found that nearly 90% of nurses had no training in pediatric palliative or hospice care; 50% had no pediatric hospice experience; those with exposure to pediatric hospice care described limited training (eg, a 2-day course); and few had opportunities to maintain or build their skill sets. Unsurprisingly, hospice nurses reported overwhelming discomfort with pediatric-specific care , , and a strong desire for further education, resources, and support specific to the care of pediatric patients. In fact, many nurses requested training on any or all topics. Qualitative analysis of short-answer survey items identified several key gaps in knowledge self-reported by hospice nurses, including pediatric medication use and dosing, physical symptom assessment and management, psychosocial assessment and management, and communication. Nonetheless, hospice nurses’ educational needs and preferences regarding pediatric-specific training, resources, and support systems are not well understood. To address this deficit, an interdisciplinary collaborative of pediatric palliative care and hospice physicians, advanced practice health care professionals, and nurses partnered with researchers to develop a qualitative study of hospice nurses’ pediatric-specific training needs and preferences. The ultimate goal of the study was to present nurse-driven recommendations for optimizing pediatric educational resources, training programs, hospice policies, and supportive interventions to improve the overall provision of community-based hospice care to children with serious illness and their families.
This qualitative study was reviewed and approved by the institutional review board at St Jude Children’s Research Hospital, and all participants provided formal verbal consent. This study followed the Consolidated Criteria for Reporting Qualitative Research ( COREQ ) reporting guideline. Preceding Survey Study Methods for the 2018 population-level survey study of hospice nurse experiences and comfort with pediatric hospice provision have been previously described. , , Briefly, we identified all accredited hospice organizations that offer services to pediatric patients in the tristate region of Tennessee, Mississippi, and Arkansas, comprising an institutional catchment area with notably poor access to hospice organizations, with approximately one-quarter to one-third of individuals lacking services within a 30-minute drive. Interview Guide Development and Content Following review of the literature related to barriers to provision of pediatric hospice care to children in the community, , , , , , , , , , a semistructured interview guide was drafted by a multisite, interdisciplinary team of pediatric palliative care and hospice clinicians and researchers. Interview questions were iteratively reviewed and refined by a panel of stakeholders, including 2 pediatric hospice physicians and 5 pediatric hospice nurses, with serial item assessment for content and construct validity until consensus was achieved. The final interview guide (eFigure in the ) included questions to assess comfort levels with, training and experience in, and barriers to caring for children with serious illness. Open-ended questions were designed to explore hospice nurses’ training and support needs and preferences in pediatric palliative and hospice care. Participant Selection, Consent, and Interview Processes Prior to this interview study, a mixed-methods survey was distributed to 551 community hospice nurses from 71 hospice agencies across the region, 226 of whom indicated willingness to have a follow-up interview. Survey participants self-identified their race and ethnicity, selecting from a provided list of categories. Purposive sampling was used to select a cohort of 41 nurses representing different self-reported levels of comfort with pediatric hospice care provision, self-identified as very uncomfortable, somewhat uncomfortable, somewhat comfortable, and very comfortable. Nurses were randomly selected until more than 10 were enrolled from each stratum. Only 3 nurses declined interviews. Email invitations were sent to selected nurses, and for those who wished to participate, an audio-recorded telephone interview was conducted by a female physician (A.S.P.) with expertise in pediatric complex care and a doctoral degree in anthropology, with no others present on the telephone call. Before beginning each interview, the interviewer introduced herself and her background and obtained formal verbal consent. Semistructured interviews were conducted over a period of 2 months between February and April 2019. Interviews were transcribed verbatim by trained medical transcriptionists. Codebook Development, Coding, Adjudication, and Analysis Content analyses were conducted using MAXQDA (VERBI Software) to organize data. The eTable in the presents each step of codebook development, piloting, coding, and synthesis and validation, all of which were performed in accordance with COREQ guidelines. Interviews continued until data saturation was reached.
Methods for the 2018 population-level survey study of hospice nurse experiences and comfort with pediatric hospice provision have been previously described. , , Briefly, we identified all accredited hospice organizations that offer services to pediatric patients in the tristate region of Tennessee, Mississippi, and Arkansas, comprising an institutional catchment area with notably poor access to hospice organizations, with approximately one-quarter to one-third of individuals lacking services within a 30-minute drive.
Following review of the literature related to barriers to provision of pediatric hospice care to children in the community, , , , , , , , , , a semistructured interview guide was drafted by a multisite, interdisciplinary team of pediatric palliative care and hospice clinicians and researchers. Interview questions were iteratively reviewed and refined by a panel of stakeholders, including 2 pediatric hospice physicians and 5 pediatric hospice nurses, with serial item assessment for content and construct validity until consensus was achieved. The final interview guide (eFigure in the ) included questions to assess comfort levels with, training and experience in, and barriers to caring for children with serious illness. Open-ended questions were designed to explore hospice nurses’ training and support needs and preferences in pediatric palliative and hospice care.
Prior to this interview study, a mixed-methods survey was distributed to 551 community hospice nurses from 71 hospice agencies across the region, 226 of whom indicated willingness to have a follow-up interview. Survey participants self-identified their race and ethnicity, selecting from a provided list of categories. Purposive sampling was used to select a cohort of 41 nurses representing different self-reported levels of comfort with pediatric hospice care provision, self-identified as very uncomfortable, somewhat uncomfortable, somewhat comfortable, and very comfortable. Nurses were randomly selected until more than 10 were enrolled from each stratum. Only 3 nurses declined interviews. Email invitations were sent to selected nurses, and for those who wished to participate, an audio-recorded telephone interview was conducted by a female physician (A.S.P.) with expertise in pediatric complex care and a doctoral degree in anthropology, with no others present on the telephone call. Before beginning each interview, the interviewer introduced herself and her background and obtained formal verbal consent. Semistructured interviews were conducted over a period of 2 months between February and April 2019. Interviews were transcribed verbatim by trained medical transcriptionists.
Content analyses were conducted using MAXQDA (VERBI Software) to organize data. The eTable in the presents each step of codebook development, piloting, coding, and synthesis and validation, all of which were performed in accordance with COREQ guidelines. Interviews continued until data saturation was reached.
A total of 41 community hospice nurses completed interviews. presents self-reported participant demographic data and clinical practice variables. Thirty-eight of the nurses were women (92.7%) and 3 were men (7.3%), with a median age of 40-49 years (range, 20-29 to ≥60 years) and median tenure of 5-9 years (range, <1 to ≥20 years) practicing as a hospice nurse. Respondents included 1 American Indian or Alaska Native nurse (2.4%), 1 Black nurse (2.4%), and 39 White nurses (95.1%). Interview duration ranged from 20 to 60 minutes. “I Don’t Ever Really Feel Comfortable”: Hospice Nurse Discomfort With and Lack of Training in Provision of Pediatric Care Many nurses reported that they almost always feel uncomfortable with or underprepared to care for children. When asked, “Will you please think back to the last time you were working with a child with palliative or hospice care needs in which you felt uncomfortable or underprepared and tell me about that,” one interviewee responded: “About every day,” and another explained: “I don’t ever really feel comfortable.” One nurse described the apprehension that she and her colleagues feel: “We all get kind of a pit in our stomach of ‘How am I going to take care of this child and their family?’” Another nurse offered: “I have such a lack of education and knowledge in taking care of children in hospice that if I got them as a patient, I would have no idea.” Reflecting on a particular experience caring for a pediatric patient, one nurse shared: “This day—it was a learning curve for everybody, and I don't feel like we had the training, the tools, or the resources to benefit the patient.” These feelings of discomfort and lack of preparation were reported more frequently by nurses who, in the preceding survey, had self-identified as either somewhat or very uncomfortable compared with those who had self-identified as either somewhat or very comfortable. Importantly, many conveyed that this discomfort makes nurses unwilling to care for a child at the end of life. presents specific facets of pediatric care with which hospice nurses reported feeling uncomfortable. Themes included communicating with a sick child and the child’s parents, communicating with siblings, caring for pediatric patients without sufficient pediatric physician support, symptom management in pediatric patients (as compared with adult patients), anticipating what is normal for pediatric patients overall and especially at the end of life, and preparing for and witnessing a child’s death. “We Feel Like We’re Inventing It Out Here”: Rationale for Further Training in Pediatric Palliative and Hospice Care Universally, nurses reported that their training in pediatric palliative and hospice care had been limited. One nurse shared: “I mean, I got a whole week and a half of training total in hospice, and then I had to wing it on my own.” Nurses explained why further pediatric training is essential and urgent, including 5 key themes : the need to absorb increasing pediatric hospice referrals, the geographic isolation of many hospice nurses from clinicians trained in pediatric care, the difficulty of finding hospices willing to accept pediatric patients, the dearth of opportunities for gaining experience and building skills and confidence given the relative rarity of pediatric patients as compared with adults, and the fundamental difference between caring for children and caring for adults. One nurse explained: “Children aren’t little adults. There’s comparison of a child to an adult, and you have to approach them different[ly].” Two nurses emphasized that acceptance of concurrent care is one key way pediatric palliative and hospice care differs from that of adults and recommended as a topic for pediatric-specific curricula: “Something that is a gray area for me is current care. There was always that question—because in the adult world, there’s a line. There’s definitely a line of what you can’t do and what you can. Peds is a whole different world… What is acceptable under hospice? How far can we go? I mean, that’s my understanding [that] anyone can continue to get as much aggressive treatment as they need or as they want….” “So I’m Not in This Alone”: Preferences for Educators and Access to Expertise Nurses described specific preferences for educators . Many emphasized the importance of incorporating experienced pediatric clinicians as teachers: “I would want a pediatric palliative care physician or nurse practitioner to come in and talk to us specifically about the different things regarding pediatric patients. And really share those experiences and tell us, kind of help us walk through what would work and what wouldn’t work and just different options.” One nurse stated that her agency would not accept pediatric patients if they did not have pediatric palliative care physician support: “I would have a very difficult time saying, ‘Yes, we will accept this pediatric patient,’ if I didn’t know we didn’t have a strong pediatric physician providing the clinical resources we need… [We need support in terms of] clinical background and making sure we’re dosing correctly, [that] we’re recognizing signs and symptoms, [that] we’re managing them to the best of our ability.” Many nurses also underscored the importance of multidisciplinary pediatric palliative care clinician support for real-time learning: “It’s just being available because we kind of feel like we’re in the dark sometimes, and we don’t really know where we’re supposed to be turning and what we’re supposed to be doing. And it’s very helpful to have that direct line that you can call and just say, hey look, I don’t know what’s going on here.” Many requested access to more experienced nurses to provide them with hands-on training. Last, some nurses described parents of seriously ill children as fundamental teachers of best practices in palliative and hospice care. One nurse shared: “Of course, the parents had been trained backwards and forwards, up and down… so, if there was something that I might not have known… As a nurse, you always want to feel like that you know what you are doing when you go out there, but sometimes you don’t and have to rely on that family.” “I’m More of a Hands-On, Interactive Learner”: Preferred Learning Modalities and Training Topics Preferred training modalities are also described in . In-person learning from a teacher through face-to-face interactions was the most frequent recommendation. Many also suggested establishing a learning community to bring like-minded clinicians together to learn in solidarity. Many mentioned the importance of experiential learning from a teacher with rich past experiences caring for seriously ill children. Several nurses suggested preceptorships and one-on-one mentoring in the field, in which “somebody goes out with us and watches us do a visit, and then we go back and sit down and talk about [it], not ‘this is what you’re doing wrong’ but ‘hey, this is what you could be doing better.’” Others described creation of a nurse educator role, someone with extensive experience in pediatric palliative and hospice care available at all times for consultation. We imagine a system in which hospice nurses with deep and broad experiences caring for children are paired with hospice nurses with little experience and comfort with pediatric care both to care for patients side-by-side in the field and to develop bidirectional, longitudinal mentor-mentee communication that can empower the less experienced nurse to take on more pediatric patients. Nurses also identified specific educational topics as crucial to training nurses to provide pediatric hospice and palliative care. Most commonly requested topics fell into 3 categories: technical skills (eg, pediatric pathophysiology, symptom management, pediatric devices and equipment, and common issues for children at the end of life), communication (eg, engaging in age-appropriate ways, caring for the family unit, navigating difficult conversations, providing end-of-life and comfort care, and contextual sensitivity), and resilience (eg, strategies for self-care and boundaries). The presents a synopsis of preferred topics. “Time Is the Biggest Thing”: Barriers to Training and Solutions for Overcoming Challenges Nurses identified specific barriers to receiving ideal training : lack of time away from professional or personal responsibilities, difficulties subsidizing training costs, lack of awareness of available training opportunities, geographic distance from training opportunities, lack of easy access to centralized resources, perception that hospice agencies do not value such training, and emotional burnout resulting in staff attrition. With foresight and vision, nurses readily suggested strategies to overcome these barriers , including staffing and scheduling approaches, funding resources, visibility and accessibility tools, informing hospice agencies at large about how critical these resources are, and resilience training. Many nurses were hopeful; one shared past success in motivating for pediatric-specific training: “I know when I presented it to the last organization that I worked with…when [nurses] really pushed for it and produced sufficient evidence, [the agency] allowed it to happen.”
Many nurses reported that they almost always feel uncomfortable with or underprepared to care for children. When asked, “Will you please think back to the last time you were working with a child with palliative or hospice care needs in which you felt uncomfortable or underprepared and tell me about that,” one interviewee responded: “About every day,” and another explained: “I don’t ever really feel comfortable.” One nurse described the apprehension that she and her colleagues feel: “We all get kind of a pit in our stomach of ‘How am I going to take care of this child and their family?’” Another nurse offered: “I have such a lack of education and knowledge in taking care of children in hospice that if I got them as a patient, I would have no idea.” Reflecting on a particular experience caring for a pediatric patient, one nurse shared: “This day—it was a learning curve for everybody, and I don't feel like we had the training, the tools, or the resources to benefit the patient.” These feelings of discomfort and lack of preparation were reported more frequently by nurses who, in the preceding survey, had self-identified as either somewhat or very uncomfortable compared with those who had self-identified as either somewhat or very comfortable. Importantly, many conveyed that this discomfort makes nurses unwilling to care for a child at the end of life. presents specific facets of pediatric care with which hospice nurses reported feeling uncomfortable. Themes included communicating with a sick child and the child’s parents, communicating with siblings, caring for pediatric patients without sufficient pediatric physician support, symptom management in pediatric patients (as compared with adult patients), anticipating what is normal for pediatric patients overall and especially at the end of life, and preparing for and witnessing a child’s death.
Universally, nurses reported that their training in pediatric palliative and hospice care had been limited. One nurse shared: “I mean, I got a whole week and a half of training total in hospice, and then I had to wing it on my own.” Nurses explained why further pediatric training is essential and urgent, including 5 key themes : the need to absorb increasing pediatric hospice referrals, the geographic isolation of many hospice nurses from clinicians trained in pediatric care, the difficulty of finding hospices willing to accept pediatric patients, the dearth of opportunities for gaining experience and building skills and confidence given the relative rarity of pediatric patients as compared with adults, and the fundamental difference between caring for children and caring for adults. One nurse explained: “Children aren’t little adults. There’s comparison of a child to an adult, and you have to approach them different[ly].” Two nurses emphasized that acceptance of concurrent care is one key way pediatric palliative and hospice care differs from that of adults and recommended as a topic for pediatric-specific curricula: “Something that is a gray area for me is current care. There was always that question—because in the adult world, there’s a line. There’s definitely a line of what you can’t do and what you can. Peds is a whole different world… What is acceptable under hospice? How far can we go? I mean, that’s my understanding [that] anyone can continue to get as much aggressive treatment as they need or as they want….”
Nurses described specific preferences for educators . Many emphasized the importance of incorporating experienced pediatric clinicians as teachers: “I would want a pediatric palliative care physician or nurse practitioner to come in and talk to us specifically about the different things regarding pediatric patients. And really share those experiences and tell us, kind of help us walk through what would work and what wouldn’t work and just different options.” One nurse stated that her agency would not accept pediatric patients if they did not have pediatric palliative care physician support: “I would have a very difficult time saying, ‘Yes, we will accept this pediatric patient,’ if I didn’t know we didn’t have a strong pediatric physician providing the clinical resources we need… [We need support in terms of] clinical background and making sure we’re dosing correctly, [that] we’re recognizing signs and symptoms, [that] we’re managing them to the best of our ability.” Many nurses also underscored the importance of multidisciplinary pediatric palliative care clinician support for real-time learning: “It’s just being available because we kind of feel like we’re in the dark sometimes, and we don’t really know where we’re supposed to be turning and what we’re supposed to be doing. And it’s very helpful to have that direct line that you can call and just say, hey look, I don’t know what’s going on here.” Many requested access to more experienced nurses to provide them with hands-on training. Last, some nurses described parents of seriously ill children as fundamental teachers of best practices in palliative and hospice care. One nurse shared: “Of course, the parents had been trained backwards and forwards, up and down… so, if there was something that I might not have known… As a nurse, you always want to feel like that you know what you are doing when you go out there, but sometimes you don’t and have to rely on that family.”
Preferred training modalities are also described in . In-person learning from a teacher through face-to-face interactions was the most frequent recommendation. Many also suggested establishing a learning community to bring like-minded clinicians together to learn in solidarity. Many mentioned the importance of experiential learning from a teacher with rich past experiences caring for seriously ill children. Several nurses suggested preceptorships and one-on-one mentoring in the field, in which “somebody goes out with us and watches us do a visit, and then we go back and sit down and talk about [it], not ‘this is what you’re doing wrong’ but ‘hey, this is what you could be doing better.’” Others described creation of a nurse educator role, someone with extensive experience in pediatric palliative and hospice care available at all times for consultation. We imagine a system in which hospice nurses with deep and broad experiences caring for children are paired with hospice nurses with little experience and comfort with pediatric care both to care for patients side-by-side in the field and to develop bidirectional, longitudinal mentor-mentee communication that can empower the less experienced nurse to take on more pediatric patients. Nurses also identified specific educational topics as crucial to training nurses to provide pediatric hospice and palliative care. Most commonly requested topics fell into 3 categories: technical skills (eg, pediatric pathophysiology, symptom management, pediatric devices and equipment, and common issues for children at the end of life), communication (eg, engaging in age-appropriate ways, caring for the family unit, navigating difficult conversations, providing end-of-life and comfort care, and contextual sensitivity), and resilience (eg, strategies for self-care and boundaries). The presents a synopsis of preferred topics.
Nurses identified specific barriers to receiving ideal training : lack of time away from professional or personal responsibilities, difficulties subsidizing training costs, lack of awareness of available training opportunities, geographic distance from training opportunities, lack of easy access to centralized resources, perception that hospice agencies do not value such training, and emotional burnout resulting in staff attrition. With foresight and vision, nurses readily suggested strategies to overcome these barriers , including staffing and scheduling approaches, funding resources, visibility and accessibility tools, informing hospice agencies at large about how critical these resources are, and resilience training. Many nurses were hopeful; one shared past success in motivating for pediatric-specific training: “I know when I presented it to the last organization that I worked with…when [nurses] really pushed for it and produced sufficient evidence, [the agency] allowed it to happen.”
In this qualitative study, nurses providing hospice and palliative care to patients and families across Tennessee, Mississippi, and Arkansas expressed their lack of comfort and training in pediatric care provision, their strong desire for pediatric-specific education, and their belief that there is an urgent need for development of resources and training to improve pediatric palliative and hospice care practice in the community. Additionally, nurses stated clear preferences with respect to source, delivery, and topical content; recognized practical threats to educational resources and programs; and proposed solutions for circumventing or overcoming these barriers. We found few meaningful differences thematically between nurses stratified by self-reported levels of comfort with provision of care to children and their families. The most striking finding echoed across the 41 interviews was the immediacy with which hospice nurses expressed a need for pediatric-specific training and support. Nearly all nurses felt both privileged and burdened by the responsibility of caring for dying children, conveying urgency in their need for interventions to ensure provision of optimal care. These findings are a call to action for the palliative care community to collaborate in rapid implementation of educational programs and networks to systematically support hospice nurses in the field. Nurses also stressed the importance of access to experts in pediatric hospice and palliative care. Notably, access to information was described as essential but not sufficient—community and solidarity are critical aspects of education and support. Building on nurses’ keen discernment of what matters most as they care for children in the community, we propose a training model built upon a foundation of community building. Recognizing that extensive didactic programming may not be feasible for full-time nurses, we advocate for development of a spoke-and-hub model in which pediatric academic centers partner with community hospices serving their surrounding catchment areas to bring clinicians together on a regular basis to carry out didactic learning, foster a sense of community and solidarity, help nurses network with colleagues, and reinforce access to colleagues and experts who can offer guidance in real time. Precedent exists for this type of program as seen in the Partners in Pediatric Palliative Care model ; the Georgia Hospice and Palliative Care Organization ; and the virtual, technology-mediated teleteaching Project ECHO (Extension for Community Healthcare Outcomes). Although specific processes may vary by regional collaborative, we suggest a multifaceted approach including (1) an annual retreat; (2) a monthly, 1-hour virtual meeting during which nurses present case studies from the field and ask for guidance from pediatric palliative care experts; and (3) face-to-face spin-off learning in the forms of both in-service apprenticeship with a nurse champion and one-on-one guidance from nurse mentors in patients’ homes. Crucially, to serve nurses’ multifaceted needs, the expert team designing and implementing this intervention must be interprofessional, including physicians, advanced practice health care professionals, psychologists, social workers, chaplains, and child life specialists, as well as hospice nurses with experience in pediatric care. Limitations Our study had several limitations. First, findings from nurses in our tristate region are not inherently representative of hospice nurse experiences or preferences nationwide. Nonetheless, statewide data from Georgia and Nebraska corroborate our findings, suggesting that they may be representative of the experience of hospice nurses across the country. Second, we did not assess competence in the field and thus cannot know how self-reported comfort levels correlate with competence. Third, the cohort of nurses interviewed were predominantly women and racially and ethnically homogenous; the majority were White, and all were non-Hispanic. This sample is not representative of the tristate region’s overall population, although it is worth exploring in further research whether such homogeneity is representative of the hospice nurse population serving the region. Fourth, many hospice nurses had limited exposure to pediatric patients, which may constrain their ability to offer comprehensive training preferences and recommendations. Finally, our findings may underrepresent the need for pediatric-specific training and support among hospice nurses given the potential for selection bias for nurses who may have had more exposure to pediatric hospice patients.
Our study had several limitations. First, findings from nurses in our tristate region are not inherently representative of hospice nurse experiences or preferences nationwide. Nonetheless, statewide data from Georgia and Nebraska corroborate our findings, suggesting that they may be representative of the experience of hospice nurses across the country. Second, we did not assess competence in the field and thus cannot know how self-reported comfort levels correlate with competence. Third, the cohort of nurses interviewed were predominantly women and racially and ethnically homogenous; the majority were White, and all were non-Hispanic. This sample is not representative of the tristate region’s overall population, although it is worth exploring in further research whether such homogeneity is representative of the hospice nurse population serving the region. Fourth, many hospice nurses had limited exposure to pediatric patients, which may constrain their ability to offer comprehensive training preferences and recommendations. Finally, our findings may underrepresent the need for pediatric-specific training and support among hospice nurses given the potential for selection bias for nurses who may have had more exposure to pediatric hospice patients.
In this qualitative study, community hospice nurses expressed an urgent need and clear preferences for pediatric-specific training, awareness of barriers to training, and recommendations for circumventing these challenges. We hope that these findings will inform development and investigation of educational resources and training opportunities for nurses to enable optimal provision of palliative and hospice care to children with serious illness.
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Gene editing with CRISPR-Cas12a guides possessing ribose-modified pseudoknot handles | 68fb796c-848f-4be3-92b6-5f2489adb2d1 | 8593028 | Pathology[mh] | Clustered regularly interspaced short palindromic repeats (CRISPR) and their CRISPR-associated (Cas) enzymes represent an ancient bacterial immune system evolved to fight invading viral pathogens – . The core enzymatic component is a ribonucleoprotein (RNP) comprised of one or more Cas proteins, with at least one being a nuclease, which are associated with one or two CRISPR RNAs (crRNAs) – . After recognition of a short protospacer adjacent motif (PAM) sequence by the Cas endonuclease, base-pairing of crRNA nucleotides to target DNA then guides sequence-specific and site-specific endonucleolytic cleavage of DNA phosphodiester bonds , – . Cas9 from Streptococcus pyogenes ( Sp Cas9) and Cas12a, also known as Cpf1, from Acidominococcus species ( As Cas12a) are among the most heavily co-opted and engineered CRISPR-Cas systems for creation of model organisms and development of human therapeutics – . They both efficiently induce DNA double-strand breaks and guide genome editing in mammalian cells , , , – , utilize a single Cas enzyme and can function with a single-guide RNA (sgRNA), although Cas9 functions as a dual-guide RNA in nature , , , . While these enzymes can ultimately result in similar gene editing outcomes, such as genetic knockout or donor DNA sequence knock-in, they are quite distinct. Cas12a is a smaller protein that naturally utilizes a single crRNA guide (39 nucleotides), less than half the size of the commonly used artificial Cas9 sgRNA (99 nucleotides) , , . Cas12a recognizes thymine (T)-rich PAMs, whereas Sp Cas9 uses guanine (G)-rich PAMs , , , . The Cas12a crRNA adopts a pseudoknot structure at its 5′ end that creates a “handle” for Cas12a to bind, as opposed to a series of stem structures for Sp Cas9 , . A unique property of Cas12a is trans activity, which is a non-sequence-specific single-stranded DNA cleavage (ssDNase) activity with high catalytic turnover , . Trans activity requires that the Cas12a RNP first bind to and cut a target DNA strand, which is referred to as cis activity. Trans activity has been exploited to create molecular diagnostics that can detect very small amounts of DNA and amplify the detection signal through cleavage of ssDNA substrates that can be detected, such as by fluorescence, antibodies on test strips, and nanopores , , . The digestion of the ssDNA reporter by trans activity is intrinsically tied to the cis cleavage of the specific target DNA because both mechanisms use the same catalytic residues , . Mutation of neighboring amino acids or REC (recognition lobe) linker and lid regions of Cas12a, however, could allow trans but not cis activity when Cas12a was bound to a complementary single-strand DNA target . However, it appears that cis and trans activity cannot be fully uncoupled for recognition of double-stranded targets via trans activity without cis cleavage of the target strand , . CRISPR-Cas systems hold tremendous promise for revolutionizing medicine, particularly through improved gene therapy or gene-targeted approaches , – . To achieve this potential, however, various challenges must be overcome. These include long-term safety, delivery, and efficacy , , – , – . Lipid nanoparticles are a leading technology being developed for delivery of Cas enzymes, either as protein or as mRNA that encode the Cas protein, along with their cognate crRNA guides , – . In principle, this may allow greater spatial and temporal control over tissue and cell targeting and provide a better window of safety when compared to therapeutic delivery approaches that involve genetically encoded expression of the CRISPR-Cas system, such as adeno-associated viruses . However, RNA is not an ideal drug due to its size and lability—it is quickly degraded in the body. Chemical modification has emerged as a practical necessity to stabilize and control the half-life, bioavailability, and activity of RNA and nucleic acid drugs , . Chemical modification has been a pillar in the growing success of other nucleic acid-based therapeutics, including antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs) , , . The lessons learned from these technologies can be applied to CRISPR-based therapeutics. The degree of chemical modification required for crRNA guides is unclear and may depend on delivery or target tissue. Nonetheless, ultimate control over stability, protein interaction, enzyme activity, and pharmacology would ideally be achieved by understanding what chemical modifications are tolerated at every position within a crRNA guide , , , – . Previous investigations of CRISPR-Cas guide RNA chemical modification have primarily focused on improving therapeutic gene editing by increasing nuclease resistance, understanding biochemical limitations, and reducing off-target editing. Minimal addition of modified nucleotides or inter-nucleotide linkages at the guide RNA 5′ and 3′ termini have been shown to maintain or increase editing, presumably through reduced nuclease sensitivity. These have included 2′- O -methyl with phosphorothioate (PS-2′OMe) or 2′- O -methyl-3′-thiophosphonoacetate (2′OMe thioPACE) for Cas9 , . In the Cas12a system, 3′ end capping has been explored with 2′-F, 2′- O -methyl, unlocked nucleic acid (UNA), locked nucleic acid (LNA), and phosphorothioate (PS) while 5′ end capping has been explored by addition of short MS or DNA-PS modified sequences onto the 5′ handle . Interestingly, extension of the 3′ end with 2′- O -methyl nucleotides or the 5′ handle with DNA-PS has also been reported to improve editing or increase the kinetics of trans cleavage activity for Cas12a, respectively. More complete or systematic modification of Cas9 and Cas12a guide RNAs has been explored using a variety of chemistries. DNA (2′-deoxy) has been reported to alter enzyme activity or specificity while helping to probe 2′-hydroxyl requirements of the enzyme , – . A broader array of modifications, like 2′-F, 2′- O -methyl, bridged nucleic acid (BNA), UNA, LNA, 2′F-arabinonucleic acid (FANA), and PS have been tested alone or in combination as well , , , – . These studies largely demonstrated that much of the guide could be modified, with moderate to high editing preserved, but particular positions, such as seed regions or individual residues, required RNA nucleotides. Specificity could also be improved with careful placement of modifications in the guide region , , , . For Cas9, retention of editing activity has been suggested to correlate with conserved polar contacts between the protein and the hydroxyl at the ribose 2′ position and the need to retain A-form-like helical architecture – , . For these apparently conserved positions between Cas9 and its guide, RNA cannot be readily replaced. For Cas12a, attempts to fully modify the crRNA guide have proven unsuccessful , , . However, the 5′ pseudoknot handle posed the greatest challenge as it appeared to tolerate very little modification to the ribose, suggesting that successful modification of this unique structure would be the major limitation to greater modification of Cas12a guides for therapeutic development. To address this bottleneck, we took a rational, structure-guided approach with respect to predicted 2′-hydoxyl (2′-OH) polar contacts. In this work, we utilized chemical modifications that specifically explored ribose and 2′-OH properties. We successfully modified the 5′ pseudoknot and obtained very robust gene editing when as few as 6 out of 19 residues remained unmodified. The key positions that remained resistant to modification correlated with predicted 2′-OH polar contacts within the Cas12a-crRNA crystal structure , . The bridging phosphodiester bonds 3′ to these residue positions could further be modified to PS and retain very high cis and trans cleavage activity, as well as gene editing. When crRNAs with chemically modified 5′ pseudoknot handles were screened for trans cleavage activity, some induced differential activities like high trans activity with little or no cis dsDNA target cleavage. These results were relegated to the high catalytic turnover of trans activity even when very modest cis cleavage occurred. Together, these results advance efforts toward chemical modification of As Cas12a guides for therapeutic editing and potential diagnostic applications. Probing 2′-OH contacts and A-form preference with 2′-deoxyribose Acidominococcus species Cas12a ( As Cas12a) and a 39-nucleotide crRNA were used for this study. The crRNA can be structurally and functionally divided into two domains: a 19-nucleotide 5′ handle with a pseudoknot structure that anchors crRNA binding to Cas12a and a 20-nucleotide 3′ guide region that base-pairs to complementary target strand DNA (Fig. ). A crystal structure of As Cas12a has enabled prediction of potentially important polar contacts or hydrogen bonds between As Cas12a and the RNA via 2′-hydroxyl (2′-OH) groups in the pseudoknot structure, as well as intramolecular 2′-OH RNA-RNA contacts . The importance of RNA A-form helical structure and 2′-OH chemistry has been partially investigated for pseudoknot stability and protein interaction , , but not in the context of CRISPR-Cas systems. The unique noncanonical nature of the Cas12a 5′ pseudoknot, as well as previous attempts at modification , , , suggested that it would be challenging to modify for therapeutic development. To focus on the pseudoknot structure and uncouple it from guide region effects, we maintained an entirely native RNA ribose (2′-OH) guide region throughout most of this study. This was accomplished through splint ligation of a 5′ phosphorylated guide RNA and chemically modified pseudoknot RNAs using T4 DNA ligase (Supplementary Fig. ) or direct solid-phase chemical synthesis of the entire crRNA when modification schemes prevented efficient enzymatic ligation. Enzymatic ligation facilitated more cost-effective and modular production of full-length crRNAs. To investigate the role of the ribose 2′-OH and A-form structural preferences in 5′ pseudoknot structure-function for As Cas12a, we substituted RNA nucleotides with 2′-deoxy (DNA), 2′-fluoro (2′-F), oxepane (OxN), 2′-arabino (2′-araOH), and 2′-amino (2′-NH 2 ) residues (Fig. ). While DNA nucleotides can probe the importance of 2′-OH contacts, they introduce conformational flexibility and can therefore also probe the importance of A-form structural preferences , , . Pseudoknots are noncanonical RNA structures that have also been generated with single-stranded DNA , . Thus, we initially synthesized a crRNA with all nucleotides in the pseudoknot substituted with DNA (cpEGIP-D1). No sequence-specific ( cis ) cleavage activity was observed for this design in vitro, indicating that either 2′-OH contacts or A-form helical structure, or both were necessary for Cas12a RNP assembly or enzyme activity (Fig. ). Based on an As Cas12a crystal structure , we identified putative critical 2′-OH contacts in the pseudoknot structure at positions -1, -6, −10, -13, -14, -17, -18, and -19. Converting these positions back to RNA, except -19, (cpEGIP-N1) completely rescued in vitro cleavage activity. These results, along with inspection of the Cas12a crystal structure, suggested to us that the 2′-OH at residue -19 may not be a critical polar contact that impacts activity. Conversely, an all-RNA pseudoknot with the same seven potentially critical 2′-OH contact positions (omitting position -19) replaced with DNA (cpEGIP-N2) only provided a quarter of the normal As Cas12a activity. Thus, these results supported the critical role of 2′-OH contacts for either pseudoknot structure or protein interaction. However, the observation that cpEGIP-N2 still conferred cleavage activity with no 2′-OH groups at the predicted critical positions also suggested that A-form helical structure or C3′- endo sugar pucker may play an important, albeit potentially lesser role. Indeed, adding additional DNA nucleotides to cpEGIP-N2 to create cpEGIP-A1, which possessed only six RNA residues, abrogated cleavage activity. The activity of cpEGIP-N2, although low, also suggested that pseudoknot 2′-OH contacts may not be obligatory for activity. To further test the role of individual positions and explore RNA–DNA combinations, we synthesized and tested several more crRNAs. Starting with a design that preserved the putative critical 2′-OH contacts and included more RNA residues (cpEGIP-B1), we replaced -19, -18, and -17 positions individually (cpEGIP-B1a, -B1b, and -B1c). None of these substitutions were detrimental to activity (Fig. ). We then added more DNA residues, including at positions -14 and -1. This resulted in substantially reduced activity (cpEGIP-B1d). Adding RNA back to positions -14 and -15 improved activity (cpEGIP-B1e). Placing a DNA nucleotide at the putative critical 2′-OH position -6, as well as -3, showed even greater enzyme activity (cpEGIP-B1f), suggesting that -6 is more tolerant of 2′-OH loss. Comparing two pseudoknots with the same DNA substitution pattern but with or without DNA at position -1 (cpEGIP-B1g and -B1h) revealed that DNA at -1 was not only well tolerated but also seemed to enhance the activity. These results suggested that no specific critical 2′-OH position was necessarily more important than another and instead that their cumulative loss is additive and negatively impacts enzyme activity. To test both specific positions and cumulative DNA effects, we systematically walked overlapping blocks of 4–6 DNA nucleotides across the pseudoknot sequence (cpEGIP-E1 through -E5). As Cas12a exhibited high activity with all these crRNAs (Fig. ). This result supports the notion that no individual RNA position is essential and high activity can be achieved in vitro with DNA substitutions if sufficient RNA nucleotide content is preserved. Indeed, a new series of crRNAs where we added increasing numbers of DNA residues, including at potentially critical 2′-OH contact positions (cpEGIP-F1 through -F6), abrogated As Cas12a activity. These results support the important role of A-form helical preference or reduced flexibility introduced by C3′- endo sugar pucker. Previous studies by us and others have determined that specific native 2′-OH ribose chemistry (RNA nucleotides) is not necessary for in vitro cleavage but is required for efficient gene editing in cells by CRISPR-Cas9 from S. pyogenes , , . Critical 2′-OH contact positions lie in the Sp Cas9 crRNA guide (spacer) seed region and the repeat region proximal to the guide , . Thus, they are localized in the center of the Sp Cas9 crRNA. Furthermore, RNA–DNA chimeric Cas9 crRNAs composed of DNA with only RNA at the critical 2′-OH positions were highly active in vitro . To determine if a similar phenomenon existed for the 5′ pseudoknot of Cas12a, we selected several RNA–DNA chimeric pseudoknot crRNAs with high activity in vitro and tested their ability to knock out, and therefore edit, an EGFP gene. We started with HEK293T cells stably expressing EGFP and transduced them with a 3xNLS- As Cas12a-expressing lentivector followed by selection (Supplementary Fig. ). crRNAs were lipid-transfected into these custom HEK293T cells constitutively expressing EGFP and As Cas12a. For cell-based editing experiments, 5′ pseudoknots were ligated to a different guide sequence (hence the designation cpEGIPe) designed to target the integrated EGFP gene (Supplementary Fig. ). Our native all-RNA control routinely generated about 70–80% knockout of EGFP when measured by flow cytometry 5 days after transfection (Fig. and Supplementary Fig. ). However, the RNA–DNA chimeric pseudoknots generated little or no editing activity. Notably, cpEGIPe-N1 was inactive despite preserving RNA at the putative critical 2′-OH positions. Only cpEGIPe-B1a provided modest editing (approximately 10%), perhaps due to better conservation of A-form structure by additional RNA nucleotides. Thus, as had been observed with Sp Cas9 crRNAs, retaining 2′-OH at potentially critical positions appeared to be necessary but not sufficient to provide gene editing activity , . These results highlight the more complex nature of editing in cells and support the complementary role of both A-form helical structure and 2′-OH contacts within the Cas12a crRNA 5′ pseudoknot. 2′-OH substitutions and RNA mimics in the 5′ pseudoknot To further investigate the nature of A-form helical preference and ribose chemical compatibility in 5′ pseudoknot structure–activity, we substituted RNA nucleotides with additional modified ribose nucleotides or sugar replacements. The first design was a complete substitution of the pseudoknot with 2′-fluoro-ribose (2′-F) (cpEGIP-SJ01). This fully modified pseudoknot provided very high cleavage activity, similar to or higher than the native all-RNA control (Fig. ). The robust activity of this modified pseudoknot indicated that the hydroxyl chemistry at the 2′ position was completely dispensable for intrinsic enzyme activity. Importantly, 2′-F is known to stabilize C3′- endo sugar pucker and strongly favor A-form helical structure , . However, when tested for cell-based editing activity cpEGIP-SJ01 was completely inactive (Fig. ). 2′-F nucleotides are potentially able to accept hydrogen bonds but not donate them, making them an incomplete replacement for RNA where 2′-OH contacts may be critical. While the combination of stable structure, mimicry of RNA properties, and maintenance of sufficient 2′ contacts have enabled 2′-F to substitute for 2′-OH in vitro, cell-based editing is apparently more sensitive and likely requires retention of specific 2′-OH contacts. To specifically investigate positions with predicted 2′-OH contacts, we synthesized crRNAs with RNA or 2′-F pseudoknots containing oxepane nucleic acid (OxN) and 2′-araOH in putative critical 2′-OH positions. OxN is a seven-membered ring structure that can be synthesized with multiple hydroxyl groups and a phosphodiester linkage at different ring positions . We synthesized thymidine (OxT) nucleotide replacements with the phosphodiester linkage at three different positions, designated OxT-1, -2, and -3. These were then incorporated into the pseudoknot sequence at putative critical 2′-OH positions -13 and -17 during solid-phase synthesis. The incorporation of OxN (cpEGIP-SJ03, -SJ04, and -SJ05) completely abrogated As Cas12a activity, indicating that certain OxN properties, such as the bulkiness of the seven-membered ring or conformational restraints, may simply be incompatible despite providing hydroxyl groups at various positions (Fig. ). Based on these results we chose to not proceed further with OxN. Arabinose nucleotides (2′-araOH) are stereoisomers of RNA that place the hydroxyl group at the 2′ position on the opposite face of the ribose ring. While arabinonucleosides retain a 2′-OH group, the “up” orientation steers the arabinose sugar to adopt a C2′- endo (DNA-like) conformation . When placing 2′-araOH at -13 and -17 positions (cpEGIP-SJ06), some enzyme activity was retained. We therefore chose to explore more 2′-araOH substitutions but in the background of a 2′-F pseudoknot, reasoning that the strong A-form preference of 2′-F might offset structural preferences of 2′-araOH. Incorporating more than two 2′-araOH (cpEGIP-SJ09, -SJ12, and -SJ13) severely reduced or eliminated enzyme activity (Fig. ). Only cpEGIP-SJ10, with 2′-araOH at positions -13 and -17, supported high in vitro As Cas12a cleavage activity. These results suggest that 2′-F may be successfully combined with other modifications that would otherwise be too detrimental to support high activity. Despite the promising in vitro activity of cpEGIP-SJ10, it provided no editing in cells (Fig. ). 2′-Fluoro, 2′-OH, and 2′-amino combinations in the 5′ pseudoknot The high in vitro activity of 2′-F and its ability to counteract detrimental effects of 2′-araOH incorporation prompted us to create pseudoknots with a combination of 2′-F and RNA nucleotides that might improve cell-based editing. We made an all-2′-F pseudoknot with RNA nucleotides at putative critical 2′-OH positions (except -19). This design, cpEGIP-SJ14, supported very high in vitro cleavage ( cis ) activity (Fig. ). Importantly, when we transfected this same design (cpEGIPe-SJ14) into HEK293T cells stably expressing EGFP and As Cas12a, we observed robust editing of EGFP at levels as high or greater than our native RNA control cpEGIPe (Fig. ). Other designs that further reduced the number of RNA nucleotides to 5 and incorporated 2′-F at putative critical positions (cpEGIP-SJ15, -16, and -17) did not affect in vitro cleavage. However, the analogous designs targeting cellular EGFP showed varying degrees of reduced editing efficiency (Fig. ). This result supports the critical role of the putative 2′-OH positions and the value of modifications that retain strong A-form-like helical structure for high editing efficiency. Different degrees of editing among RNA and 2′-F combinations suggested that some 2′-OH interactions were more critical than others, but clear patterns were difficult to discern. Therefore, we created a new series of cpEGIP-SJ14 designs where each of the seven remaining RNA nucleotide were individually substituted with a 2′-F residue. While all designs were highly active in vitro (Fig. ), clearer trends were observed for cell-based editing. Placing 2′-F at -18 and -17 in the SJ14 design (cpEGIPe-SJ14-1 and -SJ14-2) was very detrimental to editing, reducing it to below 10% (Fig. ). Positions -14, -13, and -10 could be individually replaced by 2′-F (cpEGIPe-SJ14-3, -SJ14-4, and -SJ14-5) with only mild reductions in editing compared to the RNA control. Surprisingly, replacement at position -6 (cpEGIPe-SJ14-6) resulted in very robust editing of ~90%, suggesting that this position is less sensitive and can be replaced readily with 2′-F. This result reinforced our initial finding with DNA replacements that suggested position -6 does not depend heavily on 2-OH contacts or chemistry (Fig. ). Finally, replacing position -1 with 2′-F created strong reductions in gene editing activity. Walking 2′-F through the remaining putative 2′-OH positions identified a crRNA with a pseudoknot having only six RNA residues out of 19 (cpEGIPe-SJ14-6) that produced As Cas12a editing activity as high or greater than a native crRNA. It also identified higher sensitivity to 2′-F substitution at the terminal ends of the pseudoknot sequence. The positive performance of 2′-F but generally poor performance of 2′-araOH and OxN indicated that smaller structural perturbations of the ribose and the ability to provide hydrogen-bonding potential at the 2′ position were desirable. To determine if further RNA reduction at putative critical 2′-OH positions might be possible, we identified 2′-amino (2′-NH 2 ) as a potentially promising modification. The relatively small amino moiety and its ability to both donate and accept hydrogen bonds made it an attractive replacement for RNA. In addition, the pKa of the 2′-amino should be 6.2, as determined by Eckstein and colleagues , making the major species non-protonated at physiological pH. 2′-NH 2 nucleotides have been used for other technologies, like aptamer and ribozyme development – , but have not been applied to CRISPR guide RNA modification previously. Starting with an all-2′-F pseudoknot, we sought to replace the putative critical positions individually with 2′-NH 2 to ensure that in vitro activity was not affected. Because 2′-NH 2 is an uncommon modification and only pyrimidine monomers were commercially available, we did not substitute positions -18 and -6. All the crRNAs containing a 2′-NH 2 substitution in the 2′-F pseudoknot (cpEGIP-LA-N14-1 through -LA-N14-5) were highly active in vitro (Fig. ), indicating no negative impact on intrinsic enzyme activity. However, none of these designs targeting EGFP in cells showed significant gene editing activity (Fig. ). To begin with modified pseudoknots more likely to generate gene editing activity, we created the equivalent of cpEGIP-SJ14 (~80% editing) but walked a 2′-NH 2 through each remaining native RNA nucleotide position (except -18 and -6). These new designs, cpEGIP-LA-N14-6 through -LA-N14-10, all exhibited robust in vitro cleavage activity (Fig. ). When targeting the stably expressed EGFP gene in cells, these designs presented varying degrees of gene editing. Substitution at position -17 with 2′-NH 2 abrogated gene editing activity (cpEGIPe-LA-N14-6). Substitution at positions -13 and -1 resulted in approximately 30% gene editing (cpEGIPe-LA-N14-8 and -LA-N14-10). In contrast, substitutions with 2′-NH 2 at positions -10 and -14 (cpEGIPe-LA-N14-9 and -LA-N14-7) provided ~60–70% editing, which is substantial considering that the native RNA pseudoknot typically provides 80% editing. Interestingly, substitution at position -14 resulted in similar activities whether 2′-F (cpEGIPe-SJ14-3) or 2′-NH 2 (cpEGIPe-LA-N14-7) were used, suggesting relatively flexible accommodation at this position. 2′-NH 2 was not suitable for replacing RNA at positions -17 or -1, which was also the case with 2′-F (cpEGIPe-SJ14-2 and cpEGIPe-SJ14-7). However, position -13 was differentially affected, with 2′-F being very well-tolerated (cpEGIPe-SJ14-4), whereas 2′-NH 2 was poorly tolerated (cpEGIPe-LA-N14-8). Amines do not form hydrogen bonds as stably as alcohols and are bulkier at the 2′ position than OH and F, which may explain differential activity effects. Trans cleavage activity of modified Cas12a crRNAs Differences in sequence-specific cis cleavage in vitro versus cell-based gene editing prompted us to investigate whether chemically modified 5′ pseudoknots impacted non-sequence-specific trans cleavage activity. We employed a fluorescence-based assay similar to that originally reported by Chen and coworkers (Supplementary Fig. ). We systematically screened all crRNAs with modified pseudoknots and plotted their maximum trans activity after 1 h of reaction time. We found that levels of trans and cis activity closely mirrored one another for most crRNAs (Fig. ). This would be expected since trans cleavage activity relies on the same active site as cis cleavage activity , . However, a few crRNAs with modified 5′ pseudoknots generated differential cis versus trans activity. For example, cpEGIP-B1d and cpEGIP-F6 both had little or no cis activity but exhibited about 50% trans activity (Fig. ). However, after incubation for 2 h, both reached similar activity levels as the all-RNA control crRNA (Supplementary Fig. ). In contrast, cpEGIP-SJ10 and cpEGIP-LA-N14-1 both exhibited very high cis cleavage but low trans cleavage activity (~10%) (Fig. ). Incubation for over 2 h resulted in no additional trans cleavage for cpEGIP-SJ10 and less than 40% for -LA-N14-1 (Supplementary Fig. ). To determine whether the apparent differential cis – trans activity was guide-sequence dependent, we ligated the modified 5′ pseudoknot to the cpEGIPe guide sequence used for editing in cells. With this guide sequence, both cpEGIPe-B1d and cpEGIPe-F6 still produced markedly low cis but about 50% trans activity (Fig. ), which reached full trans activity after an additional 60 min of incubation (Supplementary Fig. ). In addition, cpEGIPe-F1 still produced almost no cis activity but now generated very high trans activity. Two modified crRNAs that had previously shown high cis but low trans activity, cpEGIPe-SJ10 and cpEGIPe-LA-N14-1, now exhibited similar cis – trans activity profiles. One possible explanation for these results is that chemical modifications may enable conformational changes to Cas12a that allow trans cleavage without target binding. However, trans cleavage assays lacking target DNA for several crRNAs did not produce any significant trans activity (Supplementary Fig. ). An alternative explanation for trans activity with little or no cis activity could potentially be “nicking” of one of the target DNA duplex strands. This could conceivably activate Cas12a trans activity but not be readily observed in typical cis cleavage assays, which use non-denaturing gel electrophoresis. Therefore, we individually 5′ radiolabeled non-target (sense) and target (antisense) strands and performed trans cleavage assays on duplexes using cpEGIPe and cpEGIPe-B1d, -F1, -F6, and -SJ14-7 crRNAs, followed by resolution of reaction products on denaturing polyacrylamide gels (Supplementary Fig. ). The cleavage of individual duplex strands very closely matched that of our previous cis assays, indicating that differential strand nicking was not a likely explanation for high trans but low cis activity. To further investigate the mechanism of apparent differential cis – trans activity, we generated hybrid dsDNA targets that incorporated a partially PS-modified non-target (sense) or target (antisense) strand (Supplementary Fig. ) . The PS-modified target strand was observed to consistently reduce trans activity by about 60% for both native and chemically modified pseudoknot-containing crRNAs while a PS-modified non-target strand had little or no effect (Supplementary Fig. ). These results are consistent with trans activity first requiring cis cleavage of the target strand . Thus, we conclude that high catalytic turnover of trans activity versus the low turnover of cis activity is the most likely explanation for apparent differential cis – trans activity. The modified crRNAs that displayed differential cis – trans activity likely fell into an activity regime that made this effect easily observable. Nonetheless, chimeric RNA–DNA pseudoknots did not appear to change the intrinsic enzyme mechanism of trans cleavage (Supplementary Fig. ). The crRNA possessing the maximum number of modifications and exhibiting little or no loss in editing was cpEGIPe-SJ14-6. However, this modification scheme retained six RNA residues, which may be subject to RNase attack in therapeutic contexts. Thus, to further stabilize these final positions, we replaced the phosphodiester linkage 3′ to each remaining RNA residue with PS linkages. This newly modified pseudoknot was ligated to the cpEGIPe guide possessing two terminal 3′ PS linkages and 2′- O -methyl nucleotides to further stabilize against 3′ exonucleases. This new modified crRNA, cpEGIPe-SJ14-6PSfull, exhibited full cis, trans and editing activities (Fig. ). Thus, As Cas12a crRNAs can be generated with heavily modified pseudoknots that should protect every nucleotide from nucleases and retain robust editing activity. To test the nuclease resistance of several pseudoknots and ligated crRNAs, we also performed serum stability assays (Supplementary Fig. ). Native crRNA (cpEGIPe) and an RNA–DNA chimeric pseudoknot (cpEGIPe-F6) were completely digested under the conditions tested. The cpEGIPe-SJ01 pseudoknot, composed entirely of 2′-F, was preserved while the cpEGIPe-SJ14 pseudoknot, containing 2′-F and seven RNA residues, was significantly degraded. To test the effect of additional PS modifications, full-length crRNAs were generated by enzymatic ligation. Addition of two terminal PS modifications to the SJ14-6 design (cpEGIPe-SJ14-6PS) improved stability of the modified 5′-pseudoknot slightly (lanes 8 and 10). In contrast, the 5′ pseudoknot of cpEGIP-SJ14-6PSfull was well preserved against degradation (lane 12). These results confirm that select 2′-F and PS modification of the 5′ pseudoknot can stabilize against common serum nucleases. To determine whether pseudoknot modifications may be impacting enzyme activity through large conformational effects, we performed limited trypsin hydrolysis on As Cas12a RNP complexes (Supplementary Fig. ). As Cas12a by itself, assembled as a native RNP with cpEGIPe, or further bound to its cognate dsDNA target revealed unique limited trypsin digestion patterns. However, no difference in the trypsin digestion pattern was observed when comparing native RNP complexes with RNPs assembled from heavily modified pseudoknot guides (cpEGIPe-SJ14-6 and cpEGIPe-SJ14-6PSfull) previously shown to possess robust in vitro cleavage and editing activity (Figs. and ). Further addition of a cognate dsDNA target to modified RNP complexes also showed no differences when compared to the native RNP complex with bound target. Thus, crRNAs with modified pseudoknots that confer high editing activity do not perturb gross As Cas12a conformation. Acidominococcus species Cas12a ( As Cas12a) and a 39-nucleotide crRNA were used for this study. The crRNA can be structurally and functionally divided into two domains: a 19-nucleotide 5′ handle with a pseudoknot structure that anchors crRNA binding to Cas12a and a 20-nucleotide 3′ guide region that base-pairs to complementary target strand DNA (Fig. ). A crystal structure of As Cas12a has enabled prediction of potentially important polar contacts or hydrogen bonds between As Cas12a and the RNA via 2′-hydroxyl (2′-OH) groups in the pseudoknot structure, as well as intramolecular 2′-OH RNA-RNA contacts . The importance of RNA A-form helical structure and 2′-OH chemistry has been partially investigated for pseudoknot stability and protein interaction , , but not in the context of CRISPR-Cas systems. The unique noncanonical nature of the Cas12a 5′ pseudoknot, as well as previous attempts at modification , , , suggested that it would be challenging to modify for therapeutic development. To focus on the pseudoknot structure and uncouple it from guide region effects, we maintained an entirely native RNA ribose (2′-OH) guide region throughout most of this study. This was accomplished through splint ligation of a 5′ phosphorylated guide RNA and chemically modified pseudoknot RNAs using T4 DNA ligase (Supplementary Fig. ) or direct solid-phase chemical synthesis of the entire crRNA when modification schemes prevented efficient enzymatic ligation. Enzymatic ligation facilitated more cost-effective and modular production of full-length crRNAs. To investigate the role of the ribose 2′-OH and A-form structural preferences in 5′ pseudoknot structure-function for As Cas12a, we substituted RNA nucleotides with 2′-deoxy (DNA), 2′-fluoro (2′-F), oxepane (OxN), 2′-arabino (2′-araOH), and 2′-amino (2′-NH 2 ) residues (Fig. ). While DNA nucleotides can probe the importance of 2′-OH contacts, they introduce conformational flexibility and can therefore also probe the importance of A-form structural preferences , , . Pseudoknots are noncanonical RNA structures that have also been generated with single-stranded DNA , . Thus, we initially synthesized a crRNA with all nucleotides in the pseudoknot substituted with DNA (cpEGIP-D1). No sequence-specific ( cis ) cleavage activity was observed for this design in vitro, indicating that either 2′-OH contacts or A-form helical structure, or both were necessary for Cas12a RNP assembly or enzyme activity (Fig. ). Based on an As Cas12a crystal structure , we identified putative critical 2′-OH contacts in the pseudoknot structure at positions -1, -6, −10, -13, -14, -17, -18, and -19. Converting these positions back to RNA, except -19, (cpEGIP-N1) completely rescued in vitro cleavage activity. These results, along with inspection of the Cas12a crystal structure, suggested to us that the 2′-OH at residue -19 may not be a critical polar contact that impacts activity. Conversely, an all-RNA pseudoknot with the same seven potentially critical 2′-OH contact positions (omitting position -19) replaced with DNA (cpEGIP-N2) only provided a quarter of the normal As Cas12a activity. Thus, these results supported the critical role of 2′-OH contacts for either pseudoknot structure or protein interaction. However, the observation that cpEGIP-N2 still conferred cleavage activity with no 2′-OH groups at the predicted critical positions also suggested that A-form helical structure or C3′- endo sugar pucker may play an important, albeit potentially lesser role. Indeed, adding additional DNA nucleotides to cpEGIP-N2 to create cpEGIP-A1, which possessed only six RNA residues, abrogated cleavage activity. The activity of cpEGIP-N2, although low, also suggested that pseudoknot 2′-OH contacts may not be obligatory for activity. To further test the role of individual positions and explore RNA–DNA combinations, we synthesized and tested several more crRNAs. Starting with a design that preserved the putative critical 2′-OH contacts and included more RNA residues (cpEGIP-B1), we replaced -19, -18, and -17 positions individually (cpEGIP-B1a, -B1b, and -B1c). None of these substitutions were detrimental to activity (Fig. ). We then added more DNA residues, including at positions -14 and -1. This resulted in substantially reduced activity (cpEGIP-B1d). Adding RNA back to positions -14 and -15 improved activity (cpEGIP-B1e). Placing a DNA nucleotide at the putative critical 2′-OH position -6, as well as -3, showed even greater enzyme activity (cpEGIP-B1f), suggesting that -6 is more tolerant of 2′-OH loss. Comparing two pseudoknots with the same DNA substitution pattern but with or without DNA at position -1 (cpEGIP-B1g and -B1h) revealed that DNA at -1 was not only well tolerated but also seemed to enhance the activity. These results suggested that no specific critical 2′-OH position was necessarily more important than another and instead that their cumulative loss is additive and negatively impacts enzyme activity. To test both specific positions and cumulative DNA effects, we systematically walked overlapping blocks of 4–6 DNA nucleotides across the pseudoknot sequence (cpEGIP-E1 through -E5). As Cas12a exhibited high activity with all these crRNAs (Fig. ). This result supports the notion that no individual RNA position is essential and high activity can be achieved in vitro with DNA substitutions if sufficient RNA nucleotide content is preserved. Indeed, a new series of crRNAs where we added increasing numbers of DNA residues, including at potentially critical 2′-OH contact positions (cpEGIP-F1 through -F6), abrogated As Cas12a activity. These results support the important role of A-form helical preference or reduced flexibility introduced by C3′- endo sugar pucker. Previous studies by us and others have determined that specific native 2′-OH ribose chemistry (RNA nucleotides) is not necessary for in vitro cleavage but is required for efficient gene editing in cells by CRISPR-Cas9 from S. pyogenes , , . Critical 2′-OH contact positions lie in the Sp Cas9 crRNA guide (spacer) seed region and the repeat region proximal to the guide , . Thus, they are localized in the center of the Sp Cas9 crRNA. Furthermore, RNA–DNA chimeric Cas9 crRNAs composed of DNA with only RNA at the critical 2′-OH positions were highly active in vitro . To determine if a similar phenomenon existed for the 5′ pseudoknot of Cas12a, we selected several RNA–DNA chimeric pseudoknot crRNAs with high activity in vitro and tested their ability to knock out, and therefore edit, an EGFP gene. We started with HEK293T cells stably expressing EGFP and transduced them with a 3xNLS- As Cas12a-expressing lentivector followed by selection (Supplementary Fig. ). crRNAs were lipid-transfected into these custom HEK293T cells constitutively expressing EGFP and As Cas12a. For cell-based editing experiments, 5′ pseudoknots were ligated to a different guide sequence (hence the designation cpEGIPe) designed to target the integrated EGFP gene (Supplementary Fig. ). Our native all-RNA control routinely generated about 70–80% knockout of EGFP when measured by flow cytometry 5 days after transfection (Fig. and Supplementary Fig. ). However, the RNA–DNA chimeric pseudoknots generated little or no editing activity. Notably, cpEGIPe-N1 was inactive despite preserving RNA at the putative critical 2′-OH positions. Only cpEGIPe-B1a provided modest editing (approximately 10%), perhaps due to better conservation of A-form structure by additional RNA nucleotides. Thus, as had been observed with Sp Cas9 crRNAs, retaining 2′-OH at potentially critical positions appeared to be necessary but not sufficient to provide gene editing activity , . These results highlight the more complex nature of editing in cells and support the complementary role of both A-form helical structure and 2′-OH contacts within the Cas12a crRNA 5′ pseudoknot. To further investigate the nature of A-form helical preference and ribose chemical compatibility in 5′ pseudoknot structure–activity, we substituted RNA nucleotides with additional modified ribose nucleotides or sugar replacements. The first design was a complete substitution of the pseudoknot with 2′-fluoro-ribose (2′-F) (cpEGIP-SJ01). This fully modified pseudoknot provided very high cleavage activity, similar to or higher than the native all-RNA control (Fig. ). The robust activity of this modified pseudoknot indicated that the hydroxyl chemistry at the 2′ position was completely dispensable for intrinsic enzyme activity. Importantly, 2′-F is known to stabilize C3′- endo sugar pucker and strongly favor A-form helical structure , . However, when tested for cell-based editing activity cpEGIP-SJ01 was completely inactive (Fig. ). 2′-F nucleotides are potentially able to accept hydrogen bonds but not donate them, making them an incomplete replacement for RNA where 2′-OH contacts may be critical. While the combination of stable structure, mimicry of RNA properties, and maintenance of sufficient 2′ contacts have enabled 2′-F to substitute for 2′-OH in vitro, cell-based editing is apparently more sensitive and likely requires retention of specific 2′-OH contacts. To specifically investigate positions with predicted 2′-OH contacts, we synthesized crRNAs with RNA or 2′-F pseudoknots containing oxepane nucleic acid (OxN) and 2′-araOH in putative critical 2′-OH positions. OxN is a seven-membered ring structure that can be synthesized with multiple hydroxyl groups and a phosphodiester linkage at different ring positions . We synthesized thymidine (OxT) nucleotide replacements with the phosphodiester linkage at three different positions, designated OxT-1, -2, and -3. These were then incorporated into the pseudoknot sequence at putative critical 2′-OH positions -13 and -17 during solid-phase synthesis. The incorporation of OxN (cpEGIP-SJ03, -SJ04, and -SJ05) completely abrogated As Cas12a activity, indicating that certain OxN properties, such as the bulkiness of the seven-membered ring or conformational restraints, may simply be incompatible despite providing hydroxyl groups at various positions (Fig. ). Based on these results we chose to not proceed further with OxN. Arabinose nucleotides (2′-araOH) are stereoisomers of RNA that place the hydroxyl group at the 2′ position on the opposite face of the ribose ring. While arabinonucleosides retain a 2′-OH group, the “up” orientation steers the arabinose sugar to adopt a C2′- endo (DNA-like) conformation . When placing 2′-araOH at -13 and -17 positions (cpEGIP-SJ06), some enzyme activity was retained. We therefore chose to explore more 2′-araOH substitutions but in the background of a 2′-F pseudoknot, reasoning that the strong A-form preference of 2′-F might offset structural preferences of 2′-araOH. Incorporating more than two 2′-araOH (cpEGIP-SJ09, -SJ12, and -SJ13) severely reduced or eliminated enzyme activity (Fig. ). Only cpEGIP-SJ10, with 2′-araOH at positions -13 and -17, supported high in vitro As Cas12a cleavage activity. These results suggest that 2′-F may be successfully combined with other modifications that would otherwise be too detrimental to support high activity. Despite the promising in vitro activity of cpEGIP-SJ10, it provided no editing in cells (Fig. ). The high in vitro activity of 2′-F and its ability to counteract detrimental effects of 2′-araOH incorporation prompted us to create pseudoknots with a combination of 2′-F and RNA nucleotides that might improve cell-based editing. We made an all-2′-F pseudoknot with RNA nucleotides at putative critical 2′-OH positions (except -19). This design, cpEGIP-SJ14, supported very high in vitro cleavage ( cis ) activity (Fig. ). Importantly, when we transfected this same design (cpEGIPe-SJ14) into HEK293T cells stably expressing EGFP and As Cas12a, we observed robust editing of EGFP at levels as high or greater than our native RNA control cpEGIPe (Fig. ). Other designs that further reduced the number of RNA nucleotides to 5 and incorporated 2′-F at putative critical positions (cpEGIP-SJ15, -16, and -17) did not affect in vitro cleavage. However, the analogous designs targeting cellular EGFP showed varying degrees of reduced editing efficiency (Fig. ). This result supports the critical role of the putative 2′-OH positions and the value of modifications that retain strong A-form-like helical structure for high editing efficiency. Different degrees of editing among RNA and 2′-F combinations suggested that some 2′-OH interactions were more critical than others, but clear patterns were difficult to discern. Therefore, we created a new series of cpEGIP-SJ14 designs where each of the seven remaining RNA nucleotide were individually substituted with a 2′-F residue. While all designs were highly active in vitro (Fig. ), clearer trends were observed for cell-based editing. Placing 2′-F at -18 and -17 in the SJ14 design (cpEGIPe-SJ14-1 and -SJ14-2) was very detrimental to editing, reducing it to below 10% (Fig. ). Positions -14, -13, and -10 could be individually replaced by 2′-F (cpEGIPe-SJ14-3, -SJ14-4, and -SJ14-5) with only mild reductions in editing compared to the RNA control. Surprisingly, replacement at position -6 (cpEGIPe-SJ14-6) resulted in very robust editing of ~90%, suggesting that this position is less sensitive and can be replaced readily with 2′-F. This result reinforced our initial finding with DNA replacements that suggested position -6 does not depend heavily on 2-OH contacts or chemistry (Fig. ). Finally, replacing position -1 with 2′-F created strong reductions in gene editing activity. Walking 2′-F through the remaining putative 2′-OH positions identified a crRNA with a pseudoknot having only six RNA residues out of 19 (cpEGIPe-SJ14-6) that produced As Cas12a editing activity as high or greater than a native crRNA. It also identified higher sensitivity to 2′-F substitution at the terminal ends of the pseudoknot sequence. The positive performance of 2′-F but generally poor performance of 2′-araOH and OxN indicated that smaller structural perturbations of the ribose and the ability to provide hydrogen-bonding potential at the 2′ position were desirable. To determine if further RNA reduction at putative critical 2′-OH positions might be possible, we identified 2′-amino (2′-NH 2 ) as a potentially promising modification. The relatively small amino moiety and its ability to both donate and accept hydrogen bonds made it an attractive replacement for RNA. In addition, the pKa of the 2′-amino should be 6.2, as determined by Eckstein and colleagues , making the major species non-protonated at physiological pH. 2′-NH 2 nucleotides have been used for other technologies, like aptamer and ribozyme development – , but have not been applied to CRISPR guide RNA modification previously. Starting with an all-2′-F pseudoknot, we sought to replace the putative critical positions individually with 2′-NH 2 to ensure that in vitro activity was not affected. Because 2′-NH 2 is an uncommon modification and only pyrimidine monomers were commercially available, we did not substitute positions -18 and -6. All the crRNAs containing a 2′-NH 2 substitution in the 2′-F pseudoknot (cpEGIP-LA-N14-1 through -LA-N14-5) were highly active in vitro (Fig. ), indicating no negative impact on intrinsic enzyme activity. However, none of these designs targeting EGFP in cells showed significant gene editing activity (Fig. ). To begin with modified pseudoknots more likely to generate gene editing activity, we created the equivalent of cpEGIP-SJ14 (~80% editing) but walked a 2′-NH 2 through each remaining native RNA nucleotide position (except -18 and -6). These new designs, cpEGIP-LA-N14-6 through -LA-N14-10, all exhibited robust in vitro cleavage activity (Fig. ). When targeting the stably expressed EGFP gene in cells, these designs presented varying degrees of gene editing. Substitution at position -17 with 2′-NH 2 abrogated gene editing activity (cpEGIPe-LA-N14-6). Substitution at positions -13 and -1 resulted in approximately 30% gene editing (cpEGIPe-LA-N14-8 and -LA-N14-10). In contrast, substitutions with 2′-NH 2 at positions -10 and -14 (cpEGIPe-LA-N14-9 and -LA-N14-7) provided ~60–70% editing, which is substantial considering that the native RNA pseudoknot typically provides 80% editing. Interestingly, substitution at position -14 resulted in similar activities whether 2′-F (cpEGIPe-SJ14-3) or 2′-NH 2 (cpEGIPe-LA-N14-7) were used, suggesting relatively flexible accommodation at this position. 2′-NH 2 was not suitable for replacing RNA at positions -17 or -1, which was also the case with 2′-F (cpEGIPe-SJ14-2 and cpEGIPe-SJ14-7). However, position -13 was differentially affected, with 2′-F being very well-tolerated (cpEGIPe-SJ14-4), whereas 2′-NH 2 was poorly tolerated (cpEGIPe-LA-N14-8). Amines do not form hydrogen bonds as stably as alcohols and are bulkier at the 2′ position than OH and F, which may explain differential activity effects. cleavage activity of modified Cas12a crRNAs Differences in sequence-specific cis cleavage in vitro versus cell-based gene editing prompted us to investigate whether chemically modified 5′ pseudoknots impacted non-sequence-specific trans cleavage activity. We employed a fluorescence-based assay similar to that originally reported by Chen and coworkers (Supplementary Fig. ). We systematically screened all crRNAs with modified pseudoknots and plotted their maximum trans activity after 1 h of reaction time. We found that levels of trans and cis activity closely mirrored one another for most crRNAs (Fig. ). This would be expected since trans cleavage activity relies on the same active site as cis cleavage activity , . However, a few crRNAs with modified 5′ pseudoknots generated differential cis versus trans activity. For example, cpEGIP-B1d and cpEGIP-F6 both had little or no cis activity but exhibited about 50% trans activity (Fig. ). However, after incubation for 2 h, both reached similar activity levels as the all-RNA control crRNA (Supplementary Fig. ). In contrast, cpEGIP-SJ10 and cpEGIP-LA-N14-1 both exhibited very high cis cleavage but low trans cleavage activity (~10%) (Fig. ). Incubation for over 2 h resulted in no additional trans cleavage for cpEGIP-SJ10 and less than 40% for -LA-N14-1 (Supplementary Fig. ). To determine whether the apparent differential cis – trans activity was guide-sequence dependent, we ligated the modified 5′ pseudoknot to the cpEGIPe guide sequence used for editing in cells. With this guide sequence, both cpEGIPe-B1d and cpEGIPe-F6 still produced markedly low cis but about 50% trans activity (Fig. ), which reached full trans activity after an additional 60 min of incubation (Supplementary Fig. ). In addition, cpEGIPe-F1 still produced almost no cis activity but now generated very high trans activity. Two modified crRNAs that had previously shown high cis but low trans activity, cpEGIPe-SJ10 and cpEGIPe-LA-N14-1, now exhibited similar cis – trans activity profiles. One possible explanation for these results is that chemical modifications may enable conformational changes to Cas12a that allow trans cleavage without target binding. However, trans cleavage assays lacking target DNA for several crRNAs did not produce any significant trans activity (Supplementary Fig. ). An alternative explanation for trans activity with little or no cis activity could potentially be “nicking” of one of the target DNA duplex strands. This could conceivably activate Cas12a trans activity but not be readily observed in typical cis cleavage assays, which use non-denaturing gel electrophoresis. Therefore, we individually 5′ radiolabeled non-target (sense) and target (antisense) strands and performed trans cleavage assays on duplexes using cpEGIPe and cpEGIPe-B1d, -F1, -F6, and -SJ14-7 crRNAs, followed by resolution of reaction products on denaturing polyacrylamide gels (Supplementary Fig. ). The cleavage of individual duplex strands very closely matched that of our previous cis assays, indicating that differential strand nicking was not a likely explanation for high trans but low cis activity. To further investigate the mechanism of apparent differential cis – trans activity, we generated hybrid dsDNA targets that incorporated a partially PS-modified non-target (sense) or target (antisense) strand (Supplementary Fig. ) . The PS-modified target strand was observed to consistently reduce trans activity by about 60% for both native and chemically modified pseudoknot-containing crRNAs while a PS-modified non-target strand had little or no effect (Supplementary Fig. ). These results are consistent with trans activity first requiring cis cleavage of the target strand . Thus, we conclude that high catalytic turnover of trans activity versus the low turnover of cis activity is the most likely explanation for apparent differential cis – trans activity. The modified crRNAs that displayed differential cis – trans activity likely fell into an activity regime that made this effect easily observable. Nonetheless, chimeric RNA–DNA pseudoknots did not appear to change the intrinsic enzyme mechanism of trans cleavage (Supplementary Fig. ). The crRNA possessing the maximum number of modifications and exhibiting little or no loss in editing was cpEGIPe-SJ14-6. However, this modification scheme retained six RNA residues, which may be subject to RNase attack in therapeutic contexts. Thus, to further stabilize these final positions, we replaced the phosphodiester linkage 3′ to each remaining RNA residue with PS linkages. This newly modified pseudoknot was ligated to the cpEGIPe guide possessing two terminal 3′ PS linkages and 2′- O -methyl nucleotides to further stabilize against 3′ exonucleases. This new modified crRNA, cpEGIPe-SJ14-6PSfull, exhibited full cis, trans and editing activities (Fig. ). Thus, As Cas12a crRNAs can be generated with heavily modified pseudoknots that should protect every nucleotide from nucleases and retain robust editing activity. To test the nuclease resistance of several pseudoknots and ligated crRNAs, we also performed serum stability assays (Supplementary Fig. ). Native crRNA (cpEGIPe) and an RNA–DNA chimeric pseudoknot (cpEGIPe-F6) were completely digested under the conditions tested. The cpEGIPe-SJ01 pseudoknot, composed entirely of 2′-F, was preserved while the cpEGIPe-SJ14 pseudoknot, containing 2′-F and seven RNA residues, was significantly degraded. To test the effect of additional PS modifications, full-length crRNAs were generated by enzymatic ligation. Addition of two terminal PS modifications to the SJ14-6 design (cpEGIPe-SJ14-6PS) improved stability of the modified 5′-pseudoknot slightly (lanes 8 and 10). In contrast, the 5′ pseudoknot of cpEGIP-SJ14-6PSfull was well preserved against degradation (lane 12). These results confirm that select 2′-F and PS modification of the 5′ pseudoknot can stabilize against common serum nucleases. To determine whether pseudoknot modifications may be impacting enzyme activity through large conformational effects, we performed limited trypsin hydrolysis on As Cas12a RNP complexes (Supplementary Fig. ). As Cas12a by itself, assembled as a native RNP with cpEGIPe, or further bound to its cognate dsDNA target revealed unique limited trypsin digestion patterns. However, no difference in the trypsin digestion pattern was observed when comparing native RNP complexes with RNPs assembled from heavily modified pseudoknot guides (cpEGIPe-SJ14-6 and cpEGIPe-SJ14-6PSfull) previously shown to possess robust in vitro cleavage and editing activity (Figs. and ). Further addition of a cognate dsDNA target to modified RNP complexes also showed no differences when compared to the native RNP complex with bound target. Thus, crRNAs with modified pseudoknots that confer high editing activity do not perturb gross As Cas12a conformation. Chemical modification of RNA is a method to probe the role of functional groups in RNA and RNP structure and biochemical activity , . It is also a critical step in converting RNA into drug-like molecules . In this study, we have used chemical modification to investigate the necessity of the ribose 2′-OH group in the As Cas12a crRNA 5′ pseudoknot structure for enzyme activity. The primary question was whether the pseudoknot structure was too complex or sensitive for efficient chemical modification, which previous studies had suggested , , . The rationale for our approach is the high likelihood that therapeutic applications of Cas12a that require direct delivery of the crRNA will also require heavy or complete chemical modification, as is the case for siRNAs. In particular, the lability of RNA is directly linked to the presence of a 2′-OH that can help catalyze intramolecular phosphodiester bond self-cleavage or attract ribonucleases . The 5′ pseudoknot anchors crRNA binding to Cas12a and is highly conserved across the CRISPR-Cas12a family , , . The conservation of pseudoknot sequence and structure suggests that the 5′ pseudoknot architecture is fine-tuned for Cas12a function and cannot be easily perturbed , . However, if successful chemical modification schemes can be identified, they should translate to other Cas12a proteins if RNA-protein contacts are preserved, which appears to be the case from recent structural investigations , , . Here we focused primarily on 2′-deoxyribose, or DNA, and 2′-F as substitutions and also included modifications designed to potentially retain hydrogen bonding between pseudoknot nucleotides or with As Cas12a protein. We have demonstrated that as many as 13 out of 19 nucleotides can be converted to 2′-F with no impact on efficiency of EGFP editing in human cells. Attempting to systematically modify remaining putative critical 2′-OH positions with 2′-F, OxN, 2′-araOH, and 2′-NH 2 resulted in moderate success. However, it was clear that a few positions are resistant to modification and seem to rely heavily on the 2′-OH group. For example, our results suggested that the more centrally positioned 2′-OH contacts, especially at residues -14, -10, and -6, were more tolerant to substitution while terminal residues (-18, -17, and -1) were less tolerant. Although OxN and 2′-araOH were not sufficient substitutes for ribose, it appears that a few 2′-NH 2 and 2′-deoxy could be incorporated in the context of 2′-F. Positions most amenable to these modifications are position -19 and more central positions like -6. In summary, removal of all but a handful of ribose sugars is achievable in the 5′ pseudoknot structure of As Cas12a crRNAs while still maintaining very high gene editing activity in cells. In addition, selective placement of PS linkages 3′ to remaining RNA nucleotides further stabilized the RNA while not compromising editing activity. A similar approach succeeded in stabilizing remaining RNA positions in a Cas9 guide RNA, although editing in the final heavily modified RNA guide was significantly reduced . Previously, full PS modification of the native 5′ pseudoknot of the As Cas12a crRNA resulted in a substantial loss of editing in cells . Previous attempts to modify the 5′ pseudoknot sequence replaced entire blocks of contiguous nucleotides, several at a time, with DNA, 2′-F, or 2′- O -methyl , . This approach is typically suitable for oligonucleotides that function almost exclusively through Watson–Crick base-pairing, such as ASOs or siRNAs , . However, it resulted in no editing activity, likely due to loss of critical 2′-OH contacts. Overall, these results reinforce the need to incorporate molecular and structural data into modification design and the value of nucleotide analogs that can mimic or substitute the properties of native ribose. Ultimately, complete ribose chemical modification of the entire crRNA would be desirable for precise control over therapeutic development. Attempts to modify the guide region of Cas12a crRNAs explored 2′- O -methyl, 2′-F, DNA, LNA, UNA, and PS linkages , . The general conclusion from these studies was that modification at or near the 3′ end of the guide region is relatively well-tolerated for most modifications. However, modification at the 5′ end of the guide, and therefore within or near the “seed” region, were very poorly tolerated. A notable feature of the seed region of both Cas12a and Cas9 CRISPR systems is the concentrated presence of conserved 2′-OH contacts with the Cas protein , . In addition, the ability for Cas9 to recognize and bind DNA targets, as well as catalyze cleavage, has been shown to be dependent on the formation of an A-form-like duplex between the guide and target DNA , . Together, the 2′-OH and A-form-like architectural requirements of crRNAs reflect on the unique co-evolution of bacterial CRISPR-Cas systems to use RNA as guides , , . Complete chemical modification of guide RNAs, such as for therapeutic CRISPR-based editing, will require addressing the 2′-OH bottleneck that has finally become apparent for Cas9 and Cas12a, and probably for other Cas enzymes. Nonetheless, our results combined with previous studies now provide a roadmap to near-complete chemical modification across the entire Cas12a crRNA. We propose that a primarily 2′-F and 2′- O -methyl oligonucleotide, with some DNA or 2′-NH 2 nucleotides, combined with selective PS modification, may be sufficient to provide drug-like profiles with favorable editing activity. Exploring a greater diversity of modifications at well-placed positions may further unlock efficient editing with little or no native RNA residues. In addition, other properties of Cas12a will need to be investigated, such as the impact of chemical modification schemes on off-target editing, as heavier modification is incorporated. A recurring theme in crRNA chemical modification studies, especially with Cas9, is that heavy modification schemes successful for in vitro cleavage often do not translate into high editing efficiency in cells , , , . For example, all RNA nucleotides can be replaced with 2′-F in the Cas9 crRNA , and now the Cas12a pseudoknot, and provide very high cleavage in vitro. However, these crRNAs provide little or no editing in cells. Converting predicted 2′-OH polar contact positions back to RNA usually rescues gene editing , . Thus, it appears that intrinsic biochemical activity is not dependent on 2′-OH contacts in bulk reactions in vitro but these become critical within cells, perhaps due to low biochemical RNP concentrations, more complex chromosomal DNA targets, or other unexplored biochemical or cellular factors . Experiments like precision biochemical, thermodynamic, and structural studies, as well as sophisticated single-molecule or gene editing assays in cells, may be necessary to fully understand this phenomenon and unlock “RNA-free” CRISPR-Cas editing for advanced therapeutic control. The discovery of non-sequence-specific ssDNase cleavage, or trans activity, by Cas12a was quickly converted into an amplification-based diagnostic method . After sequence-specific binding and cutting ( cis cleavage) of a DNA target, the catalytic domain of Cas12a is proposed to become solvent exposed such that ssDNA is accessible to the active site , . This results in high turnover degradation of ssDNA. Once DNA target paired to the guide RNA is released, ssDNase cleavage activity should cease as Cas12a returns to a pre-catalytic structural state . Thus, trans cleavage activity of Cas12a appears to be intrinsically tied to its cis cleavage activity, turnover of cis cleavage products, and conformational-state transitions. In this study, we initially found what appeared to be differences in cis versus trans cleavage activity for a few crRNAs possessing chemically modified pseudoknots. Certain modification patterns or schemes contributed to this effect. Ultimately, the differential cis – trans activity observed here appears to be a consequence of variable cis cleavage compared to catalytic trans turnover rates for certain guides. This can result in variable ratios of cis to trans activity at time points within a certain activity regime. However, trans activity by modified crRNAs still required cleavage of the target antisense DNA strand in a dsDNA target. Thus, the overall mechanism of trans activity was unaffected. The pseudoknot is proposed to influence catalysis by modulation of As Cas12a conformational transitions , , which may explain how various activity profiles were achieved by modified pseudoknots. If differential cis – trans cleavage activity could be controlled predictably, it might prove useful for some applications. For example, binding to a specific on-target DNA without cleaving ( cis activity) but still allowing trans activity, could provide trans activity for long durations and possibly improve diagnostics. Conversely, cis cleavage without activation of trans cleavage might improve the specificity or safety of other applications, like gene editing . Recently, it was reported that extending the 5′ or 3′ ends of the LbCas12a crRNA could increase on-target activity, and especially enhance trans cleavage rates . Thus, multiple types of crRNA modification may be useful for modulating cis specificity and trans turnover. RNA synthesis DNA oligonucleotides, crRNAs, and DNA–RNA chimeric 5′-handle RNAs were synthesized and purified by Integrated DNA Technologies (IDT). Full-length crRNAs, including DNA–RNA and chemically modified crRNA, were ligated using splint ligation (Supplementary Fig. and Supplementary Tables and ). Chemically modified 5′-handles were custom synthesized and mass confirmed by mass spectrometry (Supplementary Table ). Custom, chemically synthesized oligonucleotides may be available upon request and after appropriate inter-institutional material transfer agreements are approved. Single-stranded fluorophore-quencher (FQ) DNA substrate was synthesized commercially by IDT. Oligonucleotide chemical syntheses were carried out using either an ABI 3400 DNA synthesizer (Applied Biosystems) or a MerMade 12 Oligonucleotide synthesizer (BioAutomation) on a Unylinker CPG (ChemGenes) solid support at a 1 µmol scale. Conventional 2′-tert-butyl-dimethylsilyl (TBDMS) ribonucleoside, 2′-fluoro-ribonucleoside (2′-FRNA), and 2′-trifluoroacetyl amino phosphoramidites (ChemGenes) were used, along with newly synthesized oxepane phosphoramidites. Phosphoramidites were dissolved in MeCN (0.15 M) and activated with 5-ethylthio-1H-tetrazole (0.25 M in MeCN). Capping of failed couplings was carried out by the simultaneous delivery of acetic anhydride in pyridine/THF and N-methylimidazole (16% in THF) and contacting the solid support for 6 s. Oxidation of the phosphite triester intermediates was affected with 0.1 M iodine in pyridine/H 2 O/THF (20 s). A solution of 3% trichloroacetic acid in THF, delivered over 95 s, was used to deprotect DMTr groups. Deprotection and cleavage of oligonucleotides from the solid support was achieved by treatment with 1 mL of cold 29% aqueous ammonia/ethanol (3:1, v/v) for 16 h at 65 °C (or 48 h at room temperature for oxepane-containing oligonucleotides). The samples were centrifuged and the supernatant was transferred to a clean 1.5 mL microcentrifuge tube and vented for 30 min, chilled on dry ice, and evaporated to dryness. Removal of the 2′-TBDMS protecting groups for the RNA-containing oligonucleotides was achieved by treatment with a 300 µL solution of NMP/Et 3 N/TREAT-HF (3:4:6, v/v) for 90 min at 65 °C (samples in the SJ series were desilylated by exposure to neat TREAT-HF for 48 h), followed by quenching with 3 M NaOAc buffer (50 µL; pH 5.5) and precipitation of the crude oligonucleotide from cold butanol (1 mL, −20 °C). Samples were chilled on dry ice for 30 min and then centrifuged. After removing the supernatant, the remaining pellet was evaporated to dryness, taken up in autoclaved Milli-Q water (1 mL), and filtered. Crude oligonucleotides were purified by ion exchange (IE) HPLC. cpEGIP-LA oligonucleotides were purified on a Waters 1525 instrument using a Protein-Pak DEAE 5PW anion exchange column (21.5 mm × 150 mm). A buffer system consisting of buffer A (10 mM NaOAc, 20% MeCN in Milli-Q water) and buffer B (0.5 M LiClO 4 , 10 mM NaOAc, 20% MeCN in Milli-Q water) was used for analysis and purification. Using a gradient of 0–50% LiClO 4 (buffer B) over 50 min (10 mL/min, 60 °C), the desired compounds eluted at around 30 min. cpEGIP-SJ oligonucleotides were purified on an Agilent 1200 Series Instrument using a Protein-Pak DEAE 5PW column (7.5 × 75 mm) at a flow rate of 1 mL/min, with a buffer system consisting of buffer A (Milli-Q water) and buffer B (1 M LiClO 4 in Milli-Q water) using a method of 0–60% buffer B over 37 min at 60 °C. Following collection of the desired peaks, excess LiClO 4 salts were removed using Gel Pak 2.5 size exclusion columns (Glen Research). Purified oligonucleotides were characterized by electrospray ionization-mass spectrometry (Supplementary Table ) and quantitated by UV spectroscopy. Extinction coefficients were determined using the IDT OligoAnalyzer tool ( https://www.idtdna.com/calc/analyzer ). Extinction coefficients for RNA were used for oligonucleotides containing oxepane modifications. crRNA splint ligation crRNA guide sequence (200 pmol), synthesized with a 5′ phosphate, was ligated to 200 pmol of 5′-handle RNA (synthesized with a 3′-OH) using T4 DNA ligase (Supplementary Table ) For DNA ligase, 220 pmol splint DNA, complementary to both guide and 5′-handle RNA, was annealed to 200 pmol of each crRNA portion in RNA resuspension buffer (5 mM Tris, pH 7.4, 0.5 mM EDTA) at 65 °C, then slow-cooled to room temperature. Ligation was performed using 1 µL of concentrated DNA ligase (30 U/μL) (Thermo Scientific, EL0013), 1x ligation buffer (400 mM Tris-HCL, 100 mM MgCl 2 , 100 mM DTT, 5 mM ATP), and 0.5 µL of SUPERase-In (Invitrogen) in a final volume of 100 μL. The reaction was incubated for 90 min at 37 °C and stopped by adding 1 µL of 0.5 M EDTA pH 8 and phenol-chloroform extracted. Ligation products were visualized by resolving on 15% denaturing polyacrylamide gels and staining with methylene blue. Full-length ligation products were gel-purified by crush-and-soak elution, phenol-chloroform extracted, ethanol precipitated, and quantified by measuring absorbance at 260 nm and calculated extinction coefficients using nearest neighbor approximations with Beer’s Law. Electrospray ionization-mass spectrometry was used to confirm the mass of a few full-length, ligated crRNAs to ensure ligation and gel-purification was proceeding properly. As Cas12a enzyme expression and purification Plasmid encoding of an As Cas12a was obtained from Addgene (79007). As Cas12a proteins were prepared similarly to that previously described for Sp Cas9 . Briefly, protein expression was induced in Rosetta (DE3) cells grown in Luria-Bertani (LB) broth with 0.2 mM isopropyl thiogalactopyranoside (IPTG) at 18 °C for 16 h. Cell pellets were resuspended in 6 mL chilled binding buffer (20 mM Tris-HCl, pH 8.0, 250 mM NaCl, 1 mM PMSF, 5 mM imidazole) per 0.5 L of culture. Resuspended cells were sonicated and clarified by centrifugation. For the 0.5 L of culture, 5 mL His-Pur Cobalt-CMA resin (Thermo Scientific) was equilibrated with binding buffer and the supernatant added to the equilibrated resin and incubated at 4 °C for 1 h with inversion to mix every 15 min. The column was washed sequentially with at least 10 bed volumes of increasing concentrations of NaCl in wash buffer (20 mM Tris-HCl, pH 8.0, 10 mM imidazole, 0.25/0.5/0.75/1.0 M NaCl). Protein was eluted with 130 mM imidazole buffer (20 mM Tris-HCl, pH 8.0, 250 mM NaCl, 200 mM imidazole). Purified As Cas12a enzyme was concentrated and buffer exchanged using centrifugal concentrators (Sartorius, 30,000 MWCO) into 2x storage buffer (40 mM Tris, pH 7.5, 300 mM KCl, 1 mM EDTA, and 2 mM DTT). Then one volume of glycerol added to obtain a final of 50% glycerol. Protein stocks were then stored at −80 °C. Concentration of As Cas12a was determined by UV absorbance at 280 nm using a calculated extinction coefficient and Beer’s law. In vitro As Cas12a Cis cleavage activity assays A 1 kb fragment of the target EGFP gene was PCR-amplified using “cpEGIP_vitro targ” primers (Supplementary Table ) from plasmid DNA (Addgene, 26777) and purified by phenol-chloroform extraction and ethanol precipitation. Target DNA (185 ng) was spotted into tubes and combined with the As Cas12a (0.75 µM final) and crRNA (0.3 µM final) in 1x cleavage buffer (20 mM Tris-HCl, pH 7.5, 100 mM KCl, 5% glycerol, 1 mM DTT, 0.5 mM EDTA, 2 mM MgCl 2 ) supplemented with 0.1 mg/mL of purified yeast tRNA. Molar excess of the As Cas12a over crRNA allows RNP concentration approximation by using crRNA concentration. Although a fraction of the Cas enzyme remains unbound, we have previously found this approach to be an accurate method for predicting the concentration of actual assembled RNP complexes , . The 40 µL reaction was incubated at 37 °C for 2 h. The reaction was then treated with 10 µg of RNase A (Thermo Scientific) for 15 min followed by 20 µg of Proteinase K (Thermo Scientific) for 15 min at room temperature. The reaction products were then precipitated in 10 volumes of 2% LiClO 4 in acetone for >1 h at −20 °C. Precipitated reactions were centrifuged and washed with acetone, air dried, and resuspended in gel-loading dye (10% glycerol, 1x TBE, orange G dye) and resolved on 1.5% agarose gels. Agarose gels were stained with ethidium bromide and visualized using a UV imager. The fractions of target cleaved versus uncleaved were quantified using ImageJ software (v1.43u). Dot plot data points represent experimental replicates, not technical replicates. For cleavage time-course assays, As Cas12a and crRNA (cpEGIP or cpEGIP-SJ14) were assembled at room temperature for 10 min. The RNP was then added to a target DNA in at 37 °C in a final of 1x cleavage buffer and reactions stopped at indicated time points by precipitation with 2% LiClO 4 in acetone and incubated at −20 °C. Samples were pelleted by centrifugation then washed with acetone. After samples were air dried, they were resuspended in 1x loading dye (10% glycerol, 1x TBE, orange G dye), treated with RNase A and proteinase K as described above, and cleavage products resolved on 1.5% agarose gels. Quantification was performed as described above. Generation of HEK293T cells stably expressing EGFP and As Cas12a HEK293T cells stably expressing EGFP were a kind gift from Dr. Wen Xue . We subcloned As Cas12a from pY010 (pcDNA3.1-hAsCpf1) (Addgene, 69982) into pLJM1-EGFP lentivector (Addgene, 19319) such that the EGFP gene was replaced with As Cas12a. Subcloning was performed with Nhe I and Eco RI restriction enzymes and resulted in retention of the C-terminal NLS and HA tag on As Cpf1 in the new vector, pLJM1- As Cas12a (Supplementary Fig. ). The PGK-driven puromycin resistance gene was replaced with a hygromycin resistance gene downstream of an internal ribosomal entry site. HEK293T cells were transfected with pLJM1- As Cas12a, pCMV-VSVG (Addgene, 8454), and pCMV-dR8.2 dvpr (Addgene, 8455) using the calcium phosphate technique. Medium was replaced 18 h after transfection. Lentiviral containing medium was collected 48 h later and centrifuged at 1000 g for 5 min. Hexadimethrine bromide was added to the medium (8 µg/mL) and the medium was used to infect HEK293T-EGFP cells on 6-well plates for 8 h. Transfection of cells with pLJM1- As Cas12a and staining with anti-HA (Santa Cruz Biotechnology, 1:1000) revealed primarily cytoplasmic localization (Supplementary Fig. ). Therefore, we cloned an additional 3x NLS tag onto the N-terminus of As Cas12a to generate pLJM1-3xNLS- As Cas12a. Staining with anti-HA revealed exclusively nuclear staining (Supplementary Fig. ). Stably integrated cells were selected using 100 µg/mL hygromycin and a clonal cell line was expanded. Expression and nuclear localization of As Cas12a was confirmed in the stable cell line (Supplementary Fig. ). Stable pLJM1-3xNLS- As Cas12a HEK293T-EGFP cells may be available upon request and after appropriate inter-institutional material transfer agreements are approved. Cell-based editing measured by flow cytometry HEK293T cells expressing EGFP and As Cas12a were grown in Dulbecco’s modified eagle’s medium (DMEM) with 1x non-essential amino acids (NEAA), 5% cosmic calf serum (CCS) and 2.5% fetal bovine serum (FBS) without antibiotics. Cells were reverse-transfected (40,000 cells) in six experimental replicates in 96-well plates with 20 pmol of crRNA and 0.3 µL RNAiMAX lipid (Invitrogen) in a final reaction of 200 μL of OptiMEM. After 8 h, one volume of media containing 5% FBS and 5% CCS was added to cells and further incubated overnight. Media was then replaced with full media and cells grown for an additional 4 days. For flow cytometry, cells were washed with 200 μL phosphate-buffered saline (PBS) and trypsinized by adding 70 μL of trypsin-EDTA solution. Then, 100 μL of media was added to the cells. The cells were spun for 5 min at 300 g at room temperature. Cells were washed again with 200 μL PBS, resuspended in 200 μL PBS and counted in an Attune flow cytometer. EGFP was detected using the blue laser (BL1 channel). At least 20,000 events were collected and analyzed by Attune software (v3.12). The cells were gated based on forward and side scattering (FSC-A/SSC-A) to remove cell debris, gated to select single cells, and gated to select EGFP-positive cells. The quadrant gate was established using the signal from non-EGFP-expressing control cells. Untreated HEK293T cells expressing EGFP and As Cas12a contained ∼5% non-fluorescent cells (Fig. ). The average from five or six replicates (see figure legends) was used for background subtraction to determine the extent of cell-based editing after treatment. Two crRNAs with different guide sequences, cpEGIP and cpEGIPe, were initially screened. cpEGIPe provided substantial editing activity (75–80%) and was chosen for subsequent modification and editing experiments in cells (Supplementary Fig. ). Fluorophore-quencher (FQ) Trans cleavage reporter assay As Cas12a and crRNA were preassembled into RNP complex by incubating 500 nM As Cas12a with 550 nM crRNA and 25 nM DNA target in 1X cleavage buffer (20 mM Tris-HCl, pH 7.5, 100 mM KCl, 5% glycerol, 1 mM DTT, 0.5 mM EDTA, 2 mM MgCl 2 ) on ice for 15 min. Certain experiments either omitted target DNA, crRNA, or used PS-modified target at the same concentrations as indicated above. Reactions were initiated by adding FQ ssDNA substrate to a final of 3 µM and placing the plate in a Bio-Rad CFX96 instrument with the block set at 4 °C. The block was cycled to 37 °C and the plate was read using the SYBR-only channel every 53 s (reading takes 7 s) such that fluorescence readings were collected at 1 min intervals. Fluorescence was collected for up to 150 min. Maximum fluorescence values at 1 h were used to compare non-sequence-specific trans cleavage activity of varying crRNAs containing modified 5′ pseudoknots. Error was calculated by standard deviation, representing three or more experimental replicates. For strand-nicking cleavage assays utilizing radiolabeled target DNA strands, individual DNA strands (cpEGIPe target sequence) were 5′ radiolabeled with T4 polynucleotide kinase and 32 P-γ-ATP as previously described . Radiolabeled DNA strands were then gel-purified from a 15% denaturing Urea-PAGE by crush-and-soak elution after visualizing radioactive bands by autoradiography. Duplexes with differentially radiolabeled sense (non-target) or antisense (target) strands were annealed and slow-cooled with a ~1.2-fold molar excess of unlabeled complementary strand. Reaction conditions then utilized those of a standard trans cleavage assay but lacking a FQ-labeled ssDNA substrate. Reactions proceeded for 1 h before being stopped by phenol-chloroform extraction. Cleavage products were resolved on a 15% denaturing PAGE and exposed to phosphorimager for visualization. Limited trypsin hydrolysis of As Cas12a protein and RNP Trypsin proteolysis was performed using 30 μg of As Cas12a in the presence and absence of crRNA and double-stranded target DNA (1:1.5:2 molar ratio) . The RNP was incubated at room temperature for 5 min. The resulting samples were incubated with Trypsin-EDTA solution (0.05%, Invitrogen) at a mass ratio of 100:1 and the partial proteolysis was conducted at 37 °C for 15 min. The reaction was stopped by the addition of SDS-PAGE loading buffer and heating the samples for 5 min at 95 °C. The reaction products were analyzed by 12% SDS-PAGE and stained with Coomassie brilliant blue G-250 in 50% (v/v) methanol and 10% (v/v) acetic acid then destained in the same solution without dye. Serum stability of modified Cas12a pseudoknots and crRNAs Serum stability test was performed using 300 pmol of pseudoknot or crRNA and 5 µL of 10% FBS in 1x PBS in a total reaction volume of 50 µL. Reactions were incubated at 37 °C and then stopped after 2 h by adding 1 µL of 0.5 M EDTA. RNA was extracted by phenol-chloroform extraction, precipitated with 2% LiClO 4 , and resolved on a 15% TBE-buffered denaturing (7 M urea) polyacrylamide gel. Gels were stained with methylene blue to visualize digestion patterns. Reporting summary Further information on research design is available in the linked to this article. DNA oligonucleotides, crRNAs, and DNA–RNA chimeric 5′-handle RNAs were synthesized and purified by Integrated DNA Technologies (IDT). Full-length crRNAs, including DNA–RNA and chemically modified crRNA, were ligated using splint ligation (Supplementary Fig. and Supplementary Tables and ). Chemically modified 5′-handles were custom synthesized and mass confirmed by mass spectrometry (Supplementary Table ). Custom, chemically synthesized oligonucleotides may be available upon request and after appropriate inter-institutional material transfer agreements are approved. Single-stranded fluorophore-quencher (FQ) DNA substrate was synthesized commercially by IDT. Oligonucleotide chemical syntheses were carried out using either an ABI 3400 DNA synthesizer (Applied Biosystems) or a MerMade 12 Oligonucleotide synthesizer (BioAutomation) on a Unylinker CPG (ChemGenes) solid support at a 1 µmol scale. Conventional 2′-tert-butyl-dimethylsilyl (TBDMS) ribonucleoside, 2′-fluoro-ribonucleoside (2′-FRNA), and 2′-trifluoroacetyl amino phosphoramidites (ChemGenes) were used, along with newly synthesized oxepane phosphoramidites. Phosphoramidites were dissolved in MeCN (0.15 M) and activated with 5-ethylthio-1H-tetrazole (0.25 M in MeCN). Capping of failed couplings was carried out by the simultaneous delivery of acetic anhydride in pyridine/THF and N-methylimidazole (16% in THF) and contacting the solid support for 6 s. Oxidation of the phosphite triester intermediates was affected with 0.1 M iodine in pyridine/H 2 O/THF (20 s). A solution of 3% trichloroacetic acid in THF, delivered over 95 s, was used to deprotect DMTr groups. Deprotection and cleavage of oligonucleotides from the solid support was achieved by treatment with 1 mL of cold 29% aqueous ammonia/ethanol (3:1, v/v) for 16 h at 65 °C (or 48 h at room temperature for oxepane-containing oligonucleotides). The samples were centrifuged and the supernatant was transferred to a clean 1.5 mL microcentrifuge tube and vented for 30 min, chilled on dry ice, and evaporated to dryness. Removal of the 2′-TBDMS protecting groups for the RNA-containing oligonucleotides was achieved by treatment with a 300 µL solution of NMP/Et 3 N/TREAT-HF (3:4:6, v/v) for 90 min at 65 °C (samples in the SJ series were desilylated by exposure to neat TREAT-HF for 48 h), followed by quenching with 3 M NaOAc buffer (50 µL; pH 5.5) and precipitation of the crude oligonucleotide from cold butanol (1 mL, −20 °C). Samples were chilled on dry ice for 30 min and then centrifuged. After removing the supernatant, the remaining pellet was evaporated to dryness, taken up in autoclaved Milli-Q water (1 mL), and filtered. Crude oligonucleotides were purified by ion exchange (IE) HPLC. cpEGIP-LA oligonucleotides were purified on a Waters 1525 instrument using a Protein-Pak DEAE 5PW anion exchange column (21.5 mm × 150 mm). A buffer system consisting of buffer A (10 mM NaOAc, 20% MeCN in Milli-Q water) and buffer B (0.5 M LiClO 4 , 10 mM NaOAc, 20% MeCN in Milli-Q water) was used for analysis and purification. Using a gradient of 0–50% LiClO 4 (buffer B) over 50 min (10 mL/min, 60 °C), the desired compounds eluted at around 30 min. cpEGIP-SJ oligonucleotides were purified on an Agilent 1200 Series Instrument using a Protein-Pak DEAE 5PW column (7.5 × 75 mm) at a flow rate of 1 mL/min, with a buffer system consisting of buffer A (Milli-Q water) and buffer B (1 M LiClO 4 in Milli-Q water) using a method of 0–60% buffer B over 37 min at 60 °C. Following collection of the desired peaks, excess LiClO 4 salts were removed using Gel Pak 2.5 size exclusion columns (Glen Research). Purified oligonucleotides were characterized by electrospray ionization-mass spectrometry (Supplementary Table ) and quantitated by UV spectroscopy. Extinction coefficients were determined using the IDT OligoAnalyzer tool ( https://www.idtdna.com/calc/analyzer ). Extinction coefficients for RNA were used for oligonucleotides containing oxepane modifications. crRNA guide sequence (200 pmol), synthesized with a 5′ phosphate, was ligated to 200 pmol of 5′-handle RNA (synthesized with a 3′-OH) using T4 DNA ligase (Supplementary Table ) For DNA ligase, 220 pmol splint DNA, complementary to both guide and 5′-handle RNA, was annealed to 200 pmol of each crRNA portion in RNA resuspension buffer (5 mM Tris, pH 7.4, 0.5 mM EDTA) at 65 °C, then slow-cooled to room temperature. Ligation was performed using 1 µL of concentrated DNA ligase (30 U/μL) (Thermo Scientific, EL0013), 1x ligation buffer (400 mM Tris-HCL, 100 mM MgCl 2 , 100 mM DTT, 5 mM ATP), and 0.5 µL of SUPERase-In (Invitrogen) in a final volume of 100 μL. The reaction was incubated for 90 min at 37 °C and stopped by adding 1 µL of 0.5 M EDTA pH 8 and phenol-chloroform extracted. Ligation products were visualized by resolving on 15% denaturing polyacrylamide gels and staining with methylene blue. Full-length ligation products were gel-purified by crush-and-soak elution, phenol-chloroform extracted, ethanol precipitated, and quantified by measuring absorbance at 260 nm and calculated extinction coefficients using nearest neighbor approximations with Beer’s Law. Electrospray ionization-mass spectrometry was used to confirm the mass of a few full-length, ligated crRNAs to ensure ligation and gel-purification was proceeding properly. Cas12a enzyme expression and purification Plasmid encoding of an As Cas12a was obtained from Addgene (79007). As Cas12a proteins were prepared similarly to that previously described for Sp Cas9 . Briefly, protein expression was induced in Rosetta (DE3) cells grown in Luria-Bertani (LB) broth with 0.2 mM isopropyl thiogalactopyranoside (IPTG) at 18 °C for 16 h. Cell pellets were resuspended in 6 mL chilled binding buffer (20 mM Tris-HCl, pH 8.0, 250 mM NaCl, 1 mM PMSF, 5 mM imidazole) per 0.5 L of culture. Resuspended cells were sonicated and clarified by centrifugation. For the 0.5 L of culture, 5 mL His-Pur Cobalt-CMA resin (Thermo Scientific) was equilibrated with binding buffer and the supernatant added to the equilibrated resin and incubated at 4 °C for 1 h with inversion to mix every 15 min. The column was washed sequentially with at least 10 bed volumes of increasing concentrations of NaCl in wash buffer (20 mM Tris-HCl, pH 8.0, 10 mM imidazole, 0.25/0.5/0.75/1.0 M NaCl). Protein was eluted with 130 mM imidazole buffer (20 mM Tris-HCl, pH 8.0, 250 mM NaCl, 200 mM imidazole). Purified As Cas12a enzyme was concentrated and buffer exchanged using centrifugal concentrators (Sartorius, 30,000 MWCO) into 2x storage buffer (40 mM Tris, pH 7.5, 300 mM KCl, 1 mM EDTA, and 2 mM DTT). Then one volume of glycerol added to obtain a final of 50% glycerol. Protein stocks were then stored at −80 °C. Concentration of As Cas12a was determined by UV absorbance at 280 nm using a calculated extinction coefficient and Beer’s law. As Cas12a Cis cleavage activity assays A 1 kb fragment of the target EGFP gene was PCR-amplified using “cpEGIP_vitro targ” primers (Supplementary Table ) from plasmid DNA (Addgene, 26777) and purified by phenol-chloroform extraction and ethanol precipitation. Target DNA (185 ng) was spotted into tubes and combined with the As Cas12a (0.75 µM final) and crRNA (0.3 µM final) in 1x cleavage buffer (20 mM Tris-HCl, pH 7.5, 100 mM KCl, 5% glycerol, 1 mM DTT, 0.5 mM EDTA, 2 mM MgCl 2 ) supplemented with 0.1 mg/mL of purified yeast tRNA. Molar excess of the As Cas12a over crRNA allows RNP concentration approximation by using crRNA concentration. Although a fraction of the Cas enzyme remains unbound, we have previously found this approach to be an accurate method for predicting the concentration of actual assembled RNP complexes , . The 40 µL reaction was incubated at 37 °C for 2 h. The reaction was then treated with 10 µg of RNase A (Thermo Scientific) for 15 min followed by 20 µg of Proteinase K (Thermo Scientific) for 15 min at room temperature. The reaction products were then precipitated in 10 volumes of 2% LiClO 4 in acetone for >1 h at −20 °C. Precipitated reactions were centrifuged and washed with acetone, air dried, and resuspended in gel-loading dye (10% glycerol, 1x TBE, orange G dye) and resolved on 1.5% agarose gels. Agarose gels were stained with ethidium bromide and visualized using a UV imager. The fractions of target cleaved versus uncleaved were quantified using ImageJ software (v1.43u). Dot plot data points represent experimental replicates, not technical replicates. For cleavage time-course assays, As Cas12a and crRNA (cpEGIP or cpEGIP-SJ14) were assembled at room temperature for 10 min. The RNP was then added to a target DNA in at 37 °C in a final of 1x cleavage buffer and reactions stopped at indicated time points by precipitation with 2% LiClO 4 in acetone and incubated at −20 °C. Samples were pelleted by centrifugation then washed with acetone. After samples were air dried, they were resuspended in 1x loading dye (10% glycerol, 1x TBE, orange G dye), treated with RNase A and proteinase K as described above, and cleavage products resolved on 1.5% agarose gels. Quantification was performed as described above. As Cas12a HEK293T cells stably expressing EGFP were a kind gift from Dr. Wen Xue . We subcloned As Cas12a from pY010 (pcDNA3.1-hAsCpf1) (Addgene, 69982) into pLJM1-EGFP lentivector (Addgene, 19319) such that the EGFP gene was replaced with As Cas12a. Subcloning was performed with Nhe I and Eco RI restriction enzymes and resulted in retention of the C-terminal NLS and HA tag on As Cpf1 in the new vector, pLJM1- As Cas12a (Supplementary Fig. ). The PGK-driven puromycin resistance gene was replaced with a hygromycin resistance gene downstream of an internal ribosomal entry site. HEK293T cells were transfected with pLJM1- As Cas12a, pCMV-VSVG (Addgene, 8454), and pCMV-dR8.2 dvpr (Addgene, 8455) using the calcium phosphate technique. Medium was replaced 18 h after transfection. Lentiviral containing medium was collected 48 h later and centrifuged at 1000 g for 5 min. Hexadimethrine bromide was added to the medium (8 µg/mL) and the medium was used to infect HEK293T-EGFP cells on 6-well plates for 8 h. Transfection of cells with pLJM1- As Cas12a and staining with anti-HA (Santa Cruz Biotechnology, 1:1000) revealed primarily cytoplasmic localization (Supplementary Fig. ). Therefore, we cloned an additional 3x NLS tag onto the N-terminus of As Cas12a to generate pLJM1-3xNLS- As Cas12a. Staining with anti-HA revealed exclusively nuclear staining (Supplementary Fig. ). Stably integrated cells were selected using 100 µg/mL hygromycin and a clonal cell line was expanded. Expression and nuclear localization of As Cas12a was confirmed in the stable cell line (Supplementary Fig. ). Stable pLJM1-3xNLS- As Cas12a HEK293T-EGFP cells may be available upon request and after appropriate inter-institutional material transfer agreements are approved. HEK293T cells expressing EGFP and As Cas12a were grown in Dulbecco’s modified eagle’s medium (DMEM) with 1x non-essential amino acids (NEAA), 5% cosmic calf serum (CCS) and 2.5% fetal bovine serum (FBS) without antibiotics. Cells were reverse-transfected (40,000 cells) in six experimental replicates in 96-well plates with 20 pmol of crRNA and 0.3 µL RNAiMAX lipid (Invitrogen) in a final reaction of 200 μL of OptiMEM. After 8 h, one volume of media containing 5% FBS and 5% CCS was added to cells and further incubated overnight. Media was then replaced with full media and cells grown for an additional 4 days. For flow cytometry, cells were washed with 200 μL phosphate-buffered saline (PBS) and trypsinized by adding 70 μL of trypsin-EDTA solution. Then, 100 μL of media was added to the cells. The cells were spun for 5 min at 300 g at room temperature. Cells were washed again with 200 μL PBS, resuspended in 200 μL PBS and counted in an Attune flow cytometer. EGFP was detected using the blue laser (BL1 channel). At least 20,000 events were collected and analyzed by Attune software (v3.12). The cells were gated based on forward and side scattering (FSC-A/SSC-A) to remove cell debris, gated to select single cells, and gated to select EGFP-positive cells. The quadrant gate was established using the signal from non-EGFP-expressing control cells. Untreated HEK293T cells expressing EGFP and As Cas12a contained ∼5% non-fluorescent cells (Fig. ). The average from five or six replicates (see figure legends) was used for background subtraction to determine the extent of cell-based editing after treatment. Two crRNAs with different guide sequences, cpEGIP and cpEGIPe, were initially screened. cpEGIPe provided substantial editing activity (75–80%) and was chosen for subsequent modification and editing experiments in cells (Supplementary Fig. ). Trans cleavage reporter assay As Cas12a and crRNA were preassembled into RNP complex by incubating 500 nM As Cas12a with 550 nM crRNA and 25 nM DNA target in 1X cleavage buffer (20 mM Tris-HCl, pH 7.5, 100 mM KCl, 5% glycerol, 1 mM DTT, 0.5 mM EDTA, 2 mM MgCl 2 ) on ice for 15 min. Certain experiments either omitted target DNA, crRNA, or used PS-modified target at the same concentrations as indicated above. Reactions were initiated by adding FQ ssDNA substrate to a final of 3 µM and placing the plate in a Bio-Rad CFX96 instrument with the block set at 4 °C. The block was cycled to 37 °C and the plate was read using the SYBR-only channel every 53 s (reading takes 7 s) such that fluorescence readings were collected at 1 min intervals. Fluorescence was collected for up to 150 min. Maximum fluorescence values at 1 h were used to compare non-sequence-specific trans cleavage activity of varying crRNAs containing modified 5′ pseudoknots. Error was calculated by standard deviation, representing three or more experimental replicates. For strand-nicking cleavage assays utilizing radiolabeled target DNA strands, individual DNA strands (cpEGIPe target sequence) were 5′ radiolabeled with T4 polynucleotide kinase and 32 P-γ-ATP as previously described . Radiolabeled DNA strands were then gel-purified from a 15% denaturing Urea-PAGE by crush-and-soak elution after visualizing radioactive bands by autoradiography. Duplexes with differentially radiolabeled sense (non-target) or antisense (target) strands were annealed and slow-cooled with a ~1.2-fold molar excess of unlabeled complementary strand. Reaction conditions then utilized those of a standard trans cleavage assay but lacking a FQ-labeled ssDNA substrate. Reactions proceeded for 1 h before being stopped by phenol-chloroform extraction. Cleavage products were resolved on a 15% denaturing PAGE and exposed to phosphorimager for visualization. As Cas12a protein and RNP Trypsin proteolysis was performed using 30 μg of As Cas12a in the presence and absence of crRNA and double-stranded target DNA (1:1.5:2 molar ratio) . The RNP was incubated at room temperature for 5 min. The resulting samples were incubated with Trypsin-EDTA solution (0.05%, Invitrogen) at a mass ratio of 100:1 and the partial proteolysis was conducted at 37 °C for 15 min. The reaction was stopped by the addition of SDS-PAGE loading buffer and heating the samples for 5 min at 95 °C. The reaction products were analyzed by 12% SDS-PAGE and stained with Coomassie brilliant blue G-250 in 50% (v/v) methanol and 10% (v/v) acetic acid then destained in the same solution without dye. Serum stability test was performed using 300 pmol of pseudoknot or crRNA and 5 µL of 10% FBS in 1x PBS in a total reaction volume of 50 µL. Reactions were incubated at 37 °C and then stopped after 2 h by adding 1 µL of 0.5 M EDTA. RNA was extracted by phenol-chloroform extraction, precipitated with 2% LiClO 4 , and resolved on a 15% TBE-buffered denaturing (7 M urea) polyacrylamide gel. Gels were stained with methylene blue to visualize digestion patterns. Further information on research design is available in the linked to this article. Supplementary information. Reporting summary. |
Recent Analytical Method for Detection of Chemical Adulterants in Herbal Medicine | aa898817-6fd8-423b-a6d5-37c27fa482e7 | 8588557 | Pharmacology[mh] | Herbal medicines are widely used to treat diseases in many countries, as there are still many medicines which are reported to have severe side effects . Herbal medicines are naturally occurring, plant-derived substances, containing phytochemical compounds used for treatment or medicinal purposes . Since the market of herbal medicine is increasing every year, to date there have still been reports that found chemical adulterants in herbal medicines, thereby containing an undeclared synthetic drug. In Indonesia, in 2020, The Food and Drug Administration issued a press release regarding herbal medicine that contains undeclared synthetic drugs . Based on their regulation, herbal medicine should not contain synthetic chemicals or medicinal isolation results. Some examples of adulterated herbal medicines are undeclared ingredients, such as sildenafil in the herbal extract , sibutramine phenolphthalein in slimming, dietary capsule supplements , and dexamethasone and prednisolone in herbal medicine pellets . Adulteration with synthetic drugs can be life-threatening, especially when those medications cause potential interactions or can cause other medical conditions. Therefore, detecting the presence of undeclared synthetic drugs in herbal medicine is important. Many papers have reviewed this issue. Jamshed Haneef et al. in 2013 reviewed the analytical methods for the detection of undeclared synthetic drugs in traditional herbal medicines. They reported various analytical approaches for the detection of synthetic adulterants in herbal medicine including high-performance liquid chromatography (HPLC) with ultraviolet (UV) and diode array detectors (DAD), ion mobility spectrometry (IMS), high-performance, thin-layer chromatography (HPTLC), liquid chromatography-tandem mass spectrometry (LC-MS/MS), nuclear magnetic resonance (NMR) analysis, and hyphenated-mass spectrometric techniques . Jacob Calahan et al. in 2016 reviewed the chemical adulterants in botanical dietary supplements from 1990 to 2015, and also the various analytical techniques used for their detection, including mass spectrometry-based techniques (MS), capillary electrophoresis (CE), hyphenated techniques, and thin-layered-based analytical techniques (TLC) . The current review focuses on providing an overview of the recently available analytical technique used for the detection of chemical synthetic drugs illegally added in herbal medicines. The paper was selected based on the topic of analysis of adulterated or undeclared synthetic drugs in herbal medicines or natural products and published within the past 5 years (2016–2021). The results show that the analytical method has been developed; we found that chromatographic-based techniques and spectroscopy-based techniques are still widely used for the detection of chemical adulterants. In addition, another technique has been developed and modified for determining possible adulteration, such as UPLC combined with QTOF-MS/MS , infrared spectrophotometry combined with partial least square (PLS) or a combination with multivariate calibration of stepwise multiple linear regression (SMLR) , TLC-SERS (surface-enhanced Raman spectroscopy) and densitometry . The analytical devices, such as paper-based or polymer-based analytical devices , which offer a rapid and simple tool for detection, are also reviewed.
To date, there have been many reports of adulterated herbal medicine and dietary supplements that claimed to be all-natural, when, in fact, they contained an undeclared synthetic drug to enhance their therapeutic effect. For example, the herbal drug for weight gain or weight loss purpose, containing sibutramine, phenolphthalein, orlistat, lorcaserin, fluoxetine, sildenafil, amfepramone , caffeine, trimethoxyamphetamine, vitamin E, tramadol, fluoxetine, rizatriptan, venlafaxine and methadone ; the sexual enhancer, containing sildenafil, tadalafil, aildenafil, sulfoaildenafil, and vardenafil ; and the pain reliever, containing paracetamol, dexamethasone, and prednisolone .
The chromatographic method is still widely used for the detection of adulterated drugs because it has a high separation capacity utilizing a complex mixture, and can simultaneously detect multi-drug components in a sample. There are a variety of chromatography methods that have been used, such as thin-layer chromatography, liquid chromatography, and gas chromatography. Currently, most of the recent chromatography methods are embedded and combined with detectors, such as mass spectroscopy, Raman spectroscopy, and other detectors. provides a list of the chromatographic methods that have been applied to detect the undeclared synthetic compounds of herbal medicines. 3.1. Thin Layer Chromatography Thin Layer Chromatography (TLC) is one of the analysis methods performed through separation by chromatography. This method can be used for qualitative and quantitative analysis to identify samples of herbal medicine. This method is simple, fast, and the operating costs are inexpensive. Hence, it can be used in small laboratories to control adulterated drugs in herbal medicines. Despite the benefit of TLC, the selectivity of TLC is not sufficient for confirmation of illegal adulteration. The selectivity and sensitivity of TLC can be improved by selecting an appropriate detection for analysis. A recent study conducted by Minh et al. (2019) developed a thin layer chromatography method by combining TLC with Raman spectroscopy to increase the selectivity and sensitivity of the analysis . Raman spectroscopy, especially surface-enhanced Raman spectroscopy (SERS), is a highly specific analytical technique that can be effectively used for qualitative analysis and chemical and physical structure elucidation . Nonetheless, use of SERS is quite challenging when detecting analytes in the complex matrix, such as herbal products, which could hinder the SERS’ measurement. Combining TLC with SERS is a recent solution to detecting the undeclared synthetic compound in the complex matrix. Separation in TLC will minimize the influence of the complex matrix on the SERS measurement, meanwhile SERS will improve the selectivity and sensitivity of TLC detection. In the research by Minh et al. , the TLC method was used to separate sildenafil as the analyte, from the similar and most commonly used PDE-5-inhibitor, which is tadalafil and vardenafil, as well as from another compound of complex herbal ingredients. The 5 µL of sample solution was sprayed on an aluminum TLC plate using an adjusted mobile phase of ethyl acetate-isopropanol-25% ammonia (45:5:2.6, v/v/v ), then the spot was compared with the standard and the Rf calculated. Sildenafil, which had been separated by TLC, is then detected using Raman spectroscopy to determine the peak characteristics, including vibration, frequency, and intermolecular bonds. Surface-enhanced Raman spectroscopy amplifies Raman signals from molecules with much higher scattering efficiencies when adsorbed on metal colloidal nanoparticles or rough metal surfaces . They used a silver nanoparticles (AgNPs) colloid as an enhancer to analyze sildenafil, discovering that the morphology had been characterized previously by UV-Vis Spectroscopy and transmission electron microscopy (TEM), resulting in a small nano and uniform size. The characteristic of AgNPs affects the formation of hot spots in thin layer chromatography that would result in a better enhancement of SERS. The concentration of silver nanoparticle colloids should be great enough to form a layer on the substrate particle to make a hot spot, but it also should not increase above the level required to form a monolayer. A higher concentration level of AgNPs will accumulate on the substrate, leading to SERS signal reduction. To ensure TLC-SERS results, all the real samples were analyzed by LC-MS/MS. The results acquired by LC-MS/MS are compatible with TLC-SERS results. The TLC-SERS method shows that the limit of detection of sildenafil was 10 μg/mL (2 ng/spot), and the concentration of the sildenafil sample ranged from 0.02 to 0.2 mg/mL. Other than being coupled with SERS, the TLC method had also been developed with densitometric analysis, called TLC-densitometric. Densitometry is an instrumental analytical method based on the interaction of electromagnetic radiation with the analyte, which is a spot or stain on the TLC plate, for quantification purposes. The interaction of electromagnetic radiation with the stain on the TLC plate is determined to be the adsorption, transmission, or reflection of fluorine fluorescence, or the extinction of fluorine fluorescence from the original radiation . A determination of sibutramine as an adulterated drug in herbal medicines using TLC-densitometry was conducted by Hayun et al. (2016) . The LOD values obtained were at 217.5 ng and the LOQ values were 724.9 ng/spot. When compared with the concentration of the drug used, which is 0.50–5.00μg/spot, this method can be said to be analytically sensitive. Besides the LOD and LOQ value, it has an acceptable relative standard deviation, which were all less than 2%. The average recovery percentage is 99.70 ± 1.22, which is also acceptable. By these validation parameters, it was shown that TLC-densitometry method has a high accuracy and precision. Compared to TLC-SERS, TLC-densitometry is simpler and less consuming time. Nevertheless, the TLC-SERS have a better LOD, meaning that the method is more sensitive for measuring very small amounts of analyte. 3.2. Liquid Chromatography Another widely used chromatographic method is high-performance liquid chromatographic (HPLC), which can also be used for the separation of various components in the mixture. The separation principle of HPLC is based on the distribution of the analyte between eluent as a mobile phase and the packing material of the column as a stationary phase with high pressure through a column pump. The use of HPLC can be combined with various detectors, such as ultraviolet detectors (UV) and mass spectroscopy (MS). HPLC-UV analysis techniques can provide sensitive and reproducible analytical results that have a fast analysis time, a low sample requirement, high accuracy, and precision to determine simultaneous compounds in the sample . An example of undeclared synthetic drug analysis on herbal products using HPLC-UV was conducted by Hemdan et al. (2018) to analyze sibutramine, sildenafil, and phenolphthalein. Separation was achieved by the Inertsil C18 analytical column (4.6 × 100 mm with 5 μm particle size) with the mobile phase used for detection of sibutramine, and phenolphthalein was the potassium dihydrogen orthophosphate buffer (adjusted to pH 3 using o-phosphoric acid) and acetonitrile (40/60 v / v ) with UV detection at 223 nm, while for SLD it was an acetonitrile–potassium hydrogen phosphate buffer (pH 3.2) adjusted using o-phosphoric acid (50/50 v / v ) with detection at 230 nm. Analysis was performed at a flow rate of 1 mL/min. The result shows good agreement with HPLC-PDA and MS/MS. Aside from being combined with a UV detector, HPLC can also be coupled with a tandem mass spectrometry (MS/MS). An example of the specification and validation of HPLC-MS/MS was conducted by Lawati et al. (2017) to determine the adulteration of sildenafil, tadalafil, and vardenafil hydrochloride. The mobile phase of this method consisted of 0.1% formic acid in water (A) and 1% formic acid in 15% acetonitrile and 85% methanol (B). It was performed with gradient elution: 0–2 min 5% B, 2–4 min 5% B, 4–7 min 40% B, 7–14 min 65% B, 14–18 min 90% B, 18–23 min 90% B, 23–23.5 min 5% B, and 23.5–27 min 5% B to equilibrate for the next injection; the total run time was 27 min and the flow rate was 0.3 mL min −1 . The main principle of mass spectrometry (MS) is to generate ions from either inorganic or organic compounds then separate these ions by their mass-to-charge ratio ( m / z ) and to detect them qualitatively and quantitatively by their respective m / z and abundance. Tandem mass spectrometry combines two mass analyzers in a single instrument to increase their abilities to analyze chemical samples. Another liquid chromatography technique that can be used to detect adulteration of drugs is the ultra-high performance liquid chromatography (UPLC). UPLC operates at higher pressures (15,000 psi) and allows for lower particle sizes in columns, compared to HPLC that operates at lower pressures (max < 6000 psi). Both UPLC and HPLC have a similar accuracy and precision, however, UPLC has a better resolution, sensitivity, decreases in solvent consumption, and improves the quality of data . UPLC is commonly combined with another detector, such as QTOF-MS or QTOF-MS/MS. QTOF-MS is a hyphenated analytical technique that combines the benefits of two different mass analyzers, namely the time of flight and the quadrupole mass analyzer. This method combined the analyzers by utilizing the high compound fragmentation efficiency of quadrupole technology with the rapid analysis speed and high mass resolution capability of time-of-flight. The Q-TOF MS uses a quadrupole (four parallel rods arranged in a square formation), a collision cell, and a time-of-flight unit to produce spectra. The first quadrupole (Q1) is capable of operating as a mass filter for the selection of specific ions based on their mass-to-charge ratio ( m / z ), or in radio frequency (RF) only mode where all ions are transmitted through the quadrupole. The second quadrupole (Q2) acts as a collision cell where ions are bombarded by neutral gas molecules, such as nitrogen or argon, resulting in the fragmentation of the ions. After leaving the quadrupole, ions are reaccelerated into the ion modulator region of the time-of-flight analyzer, where they are pulsed by an electric field and accelerated orthogonally to their original direction. All ions, having acquired the same kinetic energy, now enter the flight tube, which is a field-free drift region where mass separation occurs. Ions exhibiting a lighter mass will have a shorter time of flight, whereas heavier ions will take longer to traverse the flight path towards the detector . A study conducted by Yu et al. (2016) has successfully confirmed the adulteration of caffeine, chlorpheniramine, piroxicam, betamethasone, and oxethazaine of herbal capsule products, by using UPLC-QTOF-MS. The stationary phase used in this method was the T3 column (1.8 μm, 2.1 × 100 mm) and the column temperature was set at 45 °C. The flow rate was kept at 0.6 mL/min. The mobile phase consisted of water with 0.1% formic acid (A), and acetonitrile (B). The chromatographic separation was achieved by gradient elution from 1% B to 70% B in 26 min with an additional 2 min of re-equilibration. The total run time was 28 min, and the injection volume was 2 μL. The confirmation of 5 undeclared synthetic drugs was performed through the comparison of retention time, peak, and fragmentation pattern between the sample and standard. Chromatogram of chlorphenamine, oxethazaine, piroxicam, and caffeine are the major sample peaks, which implies that adulterants are present at higher concentrations than other natural compounds in the sample. Another research that used the UPLC-QTOF mass spectrometry method was performed by Wang et al. (2018) . Instead of using a single mass spectrometry, it used tandem mass spectrometry (MS/MS) coupled with 2 mass analyzers by using a collision cell, for improving the specificity of the mass spectrometer. It was used to detect sildenafil, tadalafil, aildenafil, and sulfoaildenafil in Chinese traditional patent medicines. Chromatographic separation was performed on an SB-C18 RRHD column of Agilent (100 mm × 3.0 mm, 1.8 mm). A binary mobile solvent was used: mobile solvent A was 5 mmol/L ammonium acetate solution (adjusted pH to 3.4 with acetic acid), and mobile solvent B was acetonitrile. The mobile phase was delivered at a flow rate of 0.4 mL/min with a gradient elution profile. The gradient began at 25% B for 2 min, and then linearly ramped to 55% B within 11 min, then ramped to 90% B in 1 min and held at 90% B for 2.0 min, then the column was re-equilibrated at 25% B for 2 min before the next injection. The autosampler tray temperature was set to 15 °C, while the column temperature was 40 °C and the injection volume was 5 mL. From the validation method, it can be concluded that UPLC-QTOF-MS/MS has a high sensitivity as the LOD and LOQ values are 0.002–0.1 mcg/g and 0.005–0.25 mcg/g, respectively. It was also considered as a high precision method based on the acceptable % recovery values, which were 82.5%–103.6%. Jin et al. (2017) have also developed a UPLC-MS/MS method with graphene as the sorbent for developing a microscale solid-phase extraction (SPE) using the pipette tip as a cartridge, namely Gtip. Graphene has a unique two-dimensional double-sided polyaromatic scaffold with a high specific surface area. The π-π electrostatic stacking property endows graphene with a strong affinity for carbon-based ring structures, making it a promising adsorptional material with high loading capacity. The Gtip SPE and UPLC–MS/MS method was developed for the quantitative analysis of trace levels of synthetic adulterants in slimming supplements. In this study, the liquid slimming supplement extract was aspirated into the conditioned Gtip and dispensed back to the sample tube. The eluate was dispensed as waste. After washing with 5% aqueous ACN, the Gtip was loaded on a vacuum manifold and dried under vacuum for 5 min. Finally, the adulterated drugs were eluted from the Gtip with 200 µL 5% ammonium hydroxide (25%) in ACN as a basic condition or 0.5% formic acid in ACN as an acidic condition by 10 repeated aspirating/dispensing cycles. The eluate was filtered through a membrane filter, then analyzed by LC-MS/MS. The Gtip showed efficient and reliable analytical performance in the preconcentration and enrichment of fenfluramine, phenolphthalein, bumetanide, and sibutramine. When compared with other commercial sorbents, such as C18 and HLB, graphene was more effective than these sorbents for Gtip SPE of trace fenfluramine, phenolphthalein, bumetanide, and sibutramine under similar conditions. The overall method showed high extraction efficiency, good specificity, accuracy, reproducibility, and sensitivity by the low levels of LOD and LOQ, low values of RSD, and also a high percentage of the recovery. 3.3. Gas Chromatography Besides LC and TLC, another method that can be used to detect the adulteration of herbal medicines is gas chromatography. It is a sensitive, reproducible, accurate, and has a lower cost compared to HPLC but is rarely used in comparison to TLC and LC because it requires additional pretreatment to achieve high thermal stability and has a volatile compound . The principle of LC and GC are almost similar, the only difference is that LC uses a solvent as its mobile phase, meanwhile, GC uses inert gases in the same capacity. The main characteristic that should be considered to analyze using gas chromatography is the volatility and thermal stability of the substances. Nitrogen (N2), hydrogen (H2), and helium (He) are three gases that are commonly used as carriers in gas chromatography (GC). Among those gases, the most commonly used carrier is helium. Helium is naturally found in gases and radioactive decay and is relatively rare in the atmosphere . A recent study conducted by Lin et al. (2018) uses hydrogen as an alternative gas carrier, in anticipation of a potential helium-shortage crisis, limited supply, and an expensive price in the future. Hydrogen offers some benefits for chromatography, including increased speed, lower temperature separations, longer column life, fewer environmental concerns, and greater availability. Gas chromatography is commonly coupled with mass spectrometry (MS) as a detector. The MS breaks each separate compound coming from the GC into ionized fragments, using a high-energy beam of electrons that are passed through the sample molecule to produce electrically charged particles or ions. Each charged fragment will have a certain mass. The mass of the fragment divided by the charge is called the mass-to-charge ratio ( m / z ). The fragments then go through a process of acceleration and deflection whilst traveling through a short tunnel and being exposed to a magnetic field. They eventually hit a detection plate at the end of the tunnel, where the mass-to-charge ratio ( m / z ) and relative abundance are calculated . A compound is analyzed by GC-MS, not only by comparing its retention time to a standard (GC) but also by using its mass spectrum. As shown from , the LOD of this method is 10 to 1000 μg/g, which means that it has a good sensitivity to detect a low level of an analyte. Compared to LC and TLC, the preparation of GC samples is slightly more difficult because it requires a derivatization step preparation to convert them into the more volatile compound. The chromatographic method offers various advantages for detecting adulterated drugs in herbal medicines, including selectivity, sensitivity, and wide applicability to detect various drugs. Therefore, this method is still commonly used for routine analysis in laboratories. However, this method is relatively high cost and the instrumentations are large, making chromatography unsuitable for on-site analysis.
Thin Layer Chromatography (TLC) is one of the analysis methods performed through separation by chromatography. This method can be used for qualitative and quantitative analysis to identify samples of herbal medicine. This method is simple, fast, and the operating costs are inexpensive. Hence, it can be used in small laboratories to control adulterated drugs in herbal medicines. Despite the benefit of TLC, the selectivity of TLC is not sufficient for confirmation of illegal adulteration. The selectivity and sensitivity of TLC can be improved by selecting an appropriate detection for analysis. A recent study conducted by Minh et al. (2019) developed a thin layer chromatography method by combining TLC with Raman spectroscopy to increase the selectivity and sensitivity of the analysis . Raman spectroscopy, especially surface-enhanced Raman spectroscopy (SERS), is a highly specific analytical technique that can be effectively used for qualitative analysis and chemical and physical structure elucidation . Nonetheless, use of SERS is quite challenging when detecting analytes in the complex matrix, such as herbal products, which could hinder the SERS’ measurement. Combining TLC with SERS is a recent solution to detecting the undeclared synthetic compound in the complex matrix. Separation in TLC will minimize the influence of the complex matrix on the SERS measurement, meanwhile SERS will improve the selectivity and sensitivity of TLC detection. In the research by Minh et al. , the TLC method was used to separate sildenafil as the analyte, from the similar and most commonly used PDE-5-inhibitor, which is tadalafil and vardenafil, as well as from another compound of complex herbal ingredients. The 5 µL of sample solution was sprayed on an aluminum TLC plate using an adjusted mobile phase of ethyl acetate-isopropanol-25% ammonia (45:5:2.6, v/v/v ), then the spot was compared with the standard and the Rf calculated. Sildenafil, which had been separated by TLC, is then detected using Raman spectroscopy to determine the peak characteristics, including vibration, frequency, and intermolecular bonds. Surface-enhanced Raman spectroscopy amplifies Raman signals from molecules with much higher scattering efficiencies when adsorbed on metal colloidal nanoparticles or rough metal surfaces . They used a silver nanoparticles (AgNPs) colloid as an enhancer to analyze sildenafil, discovering that the morphology had been characterized previously by UV-Vis Spectroscopy and transmission electron microscopy (TEM), resulting in a small nano and uniform size. The characteristic of AgNPs affects the formation of hot spots in thin layer chromatography that would result in a better enhancement of SERS. The concentration of silver nanoparticle colloids should be great enough to form a layer on the substrate particle to make a hot spot, but it also should not increase above the level required to form a monolayer. A higher concentration level of AgNPs will accumulate on the substrate, leading to SERS signal reduction. To ensure TLC-SERS results, all the real samples were analyzed by LC-MS/MS. The results acquired by LC-MS/MS are compatible with TLC-SERS results. The TLC-SERS method shows that the limit of detection of sildenafil was 10 μg/mL (2 ng/spot), and the concentration of the sildenafil sample ranged from 0.02 to 0.2 mg/mL. Other than being coupled with SERS, the TLC method had also been developed with densitometric analysis, called TLC-densitometric. Densitometry is an instrumental analytical method based on the interaction of electromagnetic radiation with the analyte, which is a spot or stain on the TLC plate, for quantification purposes. The interaction of electromagnetic radiation with the stain on the TLC plate is determined to be the adsorption, transmission, or reflection of fluorine fluorescence, or the extinction of fluorine fluorescence from the original radiation . A determination of sibutramine as an adulterated drug in herbal medicines using TLC-densitometry was conducted by Hayun et al. (2016) . The LOD values obtained were at 217.5 ng and the LOQ values were 724.9 ng/spot. When compared with the concentration of the drug used, which is 0.50–5.00μg/spot, this method can be said to be analytically sensitive. Besides the LOD and LOQ value, it has an acceptable relative standard deviation, which were all less than 2%. The average recovery percentage is 99.70 ± 1.22, which is also acceptable. By these validation parameters, it was shown that TLC-densitometry method has a high accuracy and precision. Compared to TLC-SERS, TLC-densitometry is simpler and less consuming time. Nevertheless, the TLC-SERS have a better LOD, meaning that the method is more sensitive for measuring very small amounts of analyte.
Another widely used chromatographic method is high-performance liquid chromatographic (HPLC), which can also be used for the separation of various components in the mixture. The separation principle of HPLC is based on the distribution of the analyte between eluent as a mobile phase and the packing material of the column as a stationary phase with high pressure through a column pump. The use of HPLC can be combined with various detectors, such as ultraviolet detectors (UV) and mass spectroscopy (MS). HPLC-UV analysis techniques can provide sensitive and reproducible analytical results that have a fast analysis time, a low sample requirement, high accuracy, and precision to determine simultaneous compounds in the sample . An example of undeclared synthetic drug analysis on herbal products using HPLC-UV was conducted by Hemdan et al. (2018) to analyze sibutramine, sildenafil, and phenolphthalein. Separation was achieved by the Inertsil C18 analytical column (4.6 × 100 mm with 5 μm particle size) with the mobile phase used for detection of sibutramine, and phenolphthalein was the potassium dihydrogen orthophosphate buffer (adjusted to pH 3 using o-phosphoric acid) and acetonitrile (40/60 v / v ) with UV detection at 223 nm, while for SLD it was an acetonitrile–potassium hydrogen phosphate buffer (pH 3.2) adjusted using o-phosphoric acid (50/50 v / v ) with detection at 230 nm. Analysis was performed at a flow rate of 1 mL/min. The result shows good agreement with HPLC-PDA and MS/MS. Aside from being combined with a UV detector, HPLC can also be coupled with a tandem mass spectrometry (MS/MS). An example of the specification and validation of HPLC-MS/MS was conducted by Lawati et al. (2017) to determine the adulteration of sildenafil, tadalafil, and vardenafil hydrochloride. The mobile phase of this method consisted of 0.1% formic acid in water (A) and 1% formic acid in 15% acetonitrile and 85% methanol (B). It was performed with gradient elution: 0–2 min 5% B, 2–4 min 5% B, 4–7 min 40% B, 7–14 min 65% B, 14–18 min 90% B, 18–23 min 90% B, 23–23.5 min 5% B, and 23.5–27 min 5% B to equilibrate for the next injection; the total run time was 27 min and the flow rate was 0.3 mL min −1 . The main principle of mass spectrometry (MS) is to generate ions from either inorganic or organic compounds then separate these ions by their mass-to-charge ratio ( m / z ) and to detect them qualitatively and quantitatively by their respective m / z and abundance. Tandem mass spectrometry combines two mass analyzers in a single instrument to increase their abilities to analyze chemical samples. Another liquid chromatography technique that can be used to detect adulteration of drugs is the ultra-high performance liquid chromatography (UPLC). UPLC operates at higher pressures (15,000 psi) and allows for lower particle sizes in columns, compared to HPLC that operates at lower pressures (max < 6000 psi). Both UPLC and HPLC have a similar accuracy and precision, however, UPLC has a better resolution, sensitivity, decreases in solvent consumption, and improves the quality of data . UPLC is commonly combined with another detector, such as QTOF-MS or QTOF-MS/MS. QTOF-MS is a hyphenated analytical technique that combines the benefits of two different mass analyzers, namely the time of flight and the quadrupole mass analyzer. This method combined the analyzers by utilizing the high compound fragmentation efficiency of quadrupole technology with the rapid analysis speed and high mass resolution capability of time-of-flight. The Q-TOF MS uses a quadrupole (four parallel rods arranged in a square formation), a collision cell, and a time-of-flight unit to produce spectra. The first quadrupole (Q1) is capable of operating as a mass filter for the selection of specific ions based on their mass-to-charge ratio ( m / z ), or in radio frequency (RF) only mode where all ions are transmitted through the quadrupole. The second quadrupole (Q2) acts as a collision cell where ions are bombarded by neutral gas molecules, such as nitrogen or argon, resulting in the fragmentation of the ions. After leaving the quadrupole, ions are reaccelerated into the ion modulator region of the time-of-flight analyzer, where they are pulsed by an electric field and accelerated orthogonally to their original direction. All ions, having acquired the same kinetic energy, now enter the flight tube, which is a field-free drift region where mass separation occurs. Ions exhibiting a lighter mass will have a shorter time of flight, whereas heavier ions will take longer to traverse the flight path towards the detector . A study conducted by Yu et al. (2016) has successfully confirmed the adulteration of caffeine, chlorpheniramine, piroxicam, betamethasone, and oxethazaine of herbal capsule products, by using UPLC-QTOF-MS. The stationary phase used in this method was the T3 column (1.8 μm, 2.1 × 100 mm) and the column temperature was set at 45 °C. The flow rate was kept at 0.6 mL/min. The mobile phase consisted of water with 0.1% formic acid (A), and acetonitrile (B). The chromatographic separation was achieved by gradient elution from 1% B to 70% B in 26 min with an additional 2 min of re-equilibration. The total run time was 28 min, and the injection volume was 2 μL. The confirmation of 5 undeclared synthetic drugs was performed through the comparison of retention time, peak, and fragmentation pattern between the sample and standard. Chromatogram of chlorphenamine, oxethazaine, piroxicam, and caffeine are the major sample peaks, which implies that adulterants are present at higher concentrations than other natural compounds in the sample. Another research that used the UPLC-QTOF mass spectrometry method was performed by Wang et al. (2018) . Instead of using a single mass spectrometry, it used tandem mass spectrometry (MS/MS) coupled with 2 mass analyzers by using a collision cell, for improving the specificity of the mass spectrometer. It was used to detect sildenafil, tadalafil, aildenafil, and sulfoaildenafil in Chinese traditional patent medicines. Chromatographic separation was performed on an SB-C18 RRHD column of Agilent (100 mm × 3.0 mm, 1.8 mm). A binary mobile solvent was used: mobile solvent A was 5 mmol/L ammonium acetate solution (adjusted pH to 3.4 with acetic acid), and mobile solvent B was acetonitrile. The mobile phase was delivered at a flow rate of 0.4 mL/min with a gradient elution profile. The gradient began at 25% B for 2 min, and then linearly ramped to 55% B within 11 min, then ramped to 90% B in 1 min and held at 90% B for 2.0 min, then the column was re-equilibrated at 25% B for 2 min before the next injection. The autosampler tray temperature was set to 15 °C, while the column temperature was 40 °C and the injection volume was 5 mL. From the validation method, it can be concluded that UPLC-QTOF-MS/MS has a high sensitivity as the LOD and LOQ values are 0.002–0.1 mcg/g and 0.005–0.25 mcg/g, respectively. It was also considered as a high precision method based on the acceptable % recovery values, which were 82.5%–103.6%. Jin et al. (2017) have also developed a UPLC-MS/MS method with graphene as the sorbent for developing a microscale solid-phase extraction (SPE) using the pipette tip as a cartridge, namely Gtip. Graphene has a unique two-dimensional double-sided polyaromatic scaffold with a high specific surface area. The π-π electrostatic stacking property endows graphene with a strong affinity for carbon-based ring structures, making it a promising adsorptional material with high loading capacity. The Gtip SPE and UPLC–MS/MS method was developed for the quantitative analysis of trace levels of synthetic adulterants in slimming supplements. In this study, the liquid slimming supplement extract was aspirated into the conditioned Gtip and dispensed back to the sample tube. The eluate was dispensed as waste. After washing with 5% aqueous ACN, the Gtip was loaded on a vacuum manifold and dried under vacuum for 5 min. Finally, the adulterated drugs were eluted from the Gtip with 200 µL 5% ammonium hydroxide (25%) in ACN as a basic condition or 0.5% formic acid in ACN as an acidic condition by 10 repeated aspirating/dispensing cycles. The eluate was filtered through a membrane filter, then analyzed by LC-MS/MS. The Gtip showed efficient and reliable analytical performance in the preconcentration and enrichment of fenfluramine, phenolphthalein, bumetanide, and sibutramine. When compared with other commercial sorbents, such as C18 and HLB, graphene was more effective than these sorbents for Gtip SPE of trace fenfluramine, phenolphthalein, bumetanide, and sibutramine under similar conditions. The overall method showed high extraction efficiency, good specificity, accuracy, reproducibility, and sensitivity by the low levels of LOD and LOQ, low values of RSD, and also a high percentage of the recovery.
Besides LC and TLC, another method that can be used to detect the adulteration of herbal medicines is gas chromatography. It is a sensitive, reproducible, accurate, and has a lower cost compared to HPLC but is rarely used in comparison to TLC and LC because it requires additional pretreatment to achieve high thermal stability and has a volatile compound . The principle of LC and GC are almost similar, the only difference is that LC uses a solvent as its mobile phase, meanwhile, GC uses inert gases in the same capacity. The main characteristic that should be considered to analyze using gas chromatography is the volatility and thermal stability of the substances. Nitrogen (N2), hydrogen (H2), and helium (He) are three gases that are commonly used as carriers in gas chromatography (GC). Among those gases, the most commonly used carrier is helium. Helium is naturally found in gases and radioactive decay and is relatively rare in the atmosphere . A recent study conducted by Lin et al. (2018) uses hydrogen as an alternative gas carrier, in anticipation of a potential helium-shortage crisis, limited supply, and an expensive price in the future. Hydrogen offers some benefits for chromatography, including increased speed, lower temperature separations, longer column life, fewer environmental concerns, and greater availability. Gas chromatography is commonly coupled with mass spectrometry (MS) as a detector. The MS breaks each separate compound coming from the GC into ionized fragments, using a high-energy beam of electrons that are passed through the sample molecule to produce electrically charged particles or ions. Each charged fragment will have a certain mass. The mass of the fragment divided by the charge is called the mass-to-charge ratio ( m / z ). The fragments then go through a process of acceleration and deflection whilst traveling through a short tunnel and being exposed to a magnetic field. They eventually hit a detection plate at the end of the tunnel, where the mass-to-charge ratio ( m / z ) and relative abundance are calculated . A compound is analyzed by GC-MS, not only by comparing its retention time to a standard (GC) but also by using its mass spectrum. As shown from , the LOD of this method is 10 to 1000 μg/g, which means that it has a good sensitivity to detect a low level of an analyte. Compared to LC and TLC, the preparation of GC samples is slightly more difficult because it requires a derivatization step preparation to convert them into the more volatile compound. The chromatographic method offers various advantages for detecting adulterated drugs in herbal medicines, including selectivity, sensitivity, and wide applicability to detect various drugs. Therefore, this method is still commonly used for routine analysis in laboratories. However, this method is relatively high cost and the instrumentations are large, making chromatography unsuitable for on-site analysis.
A spectroscopic method is one of the widely used methods for detecting a component on a complex matrix, including adulterated drugs in herbal medicine. The spectroscopic methods that are commonly used include infrared spectroscopy, mass spectrometry (MS), and NMR spectrometry. Previous research that has been conducted to analyze synthetic compounds in herbal medicines is shown in . 4.1. Infrared Spectroscopy Infrared (IR) spectroscopy is the simplest, most rapid, and non-destructive analytical method without any previous sample pre-treatment. Moreover, when no sample pre-treatment is required, it doesn’t need additional reagent during the analytical step. Hence, potentially harmful reagents are avoided, providing benefits for the environment and being cost-effective regarding chemical waste . IR spectroscopy is used to determine structures and functional groups of compounds and identify them based on the absorption by a molecule of a particular type of light, in the IR region of the electromagnetic spectrum. Each chemically distinct molecule will have a different absorption pattern made up of the number and different types of bonds present, and the presence of different functional groups . IR spectroscopy has been developed into the latest generation of IR, named Fourier-transform infrared spectroscopy. Fourier-transform infrared spectroscopy requires a mathematical process called Fourier transform to convert the raw data into the actual spectrum. The major difference between an FTIR spectrometer and a dispersive IR spectrometer is the Michelson interferometer. The Michelson interferometer, which is the core of FTIR spectrometers, is used to split one beam of light into two, so that the paths of the two beams are different. Then the Michelson interferometer recombines the two beams and conducts them into the detector where the difference of the intensity of these two beams is measured as a function of the difference of the paths . An example of a study that used conventional IR and FTIR are shown in . Research conducted by Nugroho and Ritonga (2018) determined the adulteration of dexamethasone in a traditional herbal medicine (THM) painkiller for joint pain, using infrared spectroscopy that combined with the partial least square (PLS). Adulteration of the undeclared synthetic drug caused complex spectra and the overlapping of absorption signals of various substances, which typically makes it difficult to interpret the spectra of the adulterated samples through use of an IR spectroscopy. Therefore, it is combined with the partial least square (PLS) method to separate spectra of the analyte (dexamethasone) from the spectra of an authentic traditional herbal medicine. Using the PLS method, maximum chemical information could be obtained from spectral data by permitting the selection of wavenumbers in complex spectra and linking changes in spectra to changes at various component levels simultaneously, by calculating the contribution of other spectra that can interfere with the spectrum. The PRESS and RMSECV values obtained as the result of the cross-validation model selection for dexamethasone in traditional herbal medicine painkillers for joint pain were 0.0022721 and 0.02902, respectively. Meanwhile, the RMSEC values obtained were 0.009455. This low value of RMSEC, RMSECV, and PRESS indicated the high accuracy and precision of the analytical method. Other research that used FTIR as an analytical method to detect sildenafil citrate in herbal aphrodisiacs has been performed by Nugroho et al. (2018) . To quantify the levels of sildenafil citrate in herbal medicines, this FTIR method is combined with the multivariate calibration of stepwise multiple linear regression (SMLR). Stepwise linear regression is a method of regressing multiple variables while simultaneously removing those that aren’t important. The result of this method validation obtained 0.000310913 as RMSEC values and 0.0009191 as PRESS values. Besides being combined with SMLR, FTIR can also be hyphenated with PLS Discriminant Analysis (PLS-DA). A study using the combination of FTIR-PLS DA method was conducted by Walkowiak et al. (2019) to detect the adulteration of kaempferol, rutin, or quercetin on the Ginkgo biloba supplement. PLS-DA provides a separation with minimal probability of false classification for test samples. The RMSEC and RMSECV values obtained were 0.393 and 0.570, respectively. By comparing the RMSEC, RMSECV, and PRESS values of the three methods using IR spectroscopy, it can be concluded that the FTIR-SMLR method has the best accuracy and precision due to the lowest values of RMSEC, RMSECV, and PRESS. Two-dimensional correlation infrared spectroscopy has been developed for analysis. Two-dimensional correlation spectroscopy (2DCOS) was employed for the identification of the ephedrine and pseudoephedrine present in illegally adulterated slimming herbal products (SHPs) that have been studied by Miao et al. (2016) . In 2DCOS, similarity or dissimilarity among variations of spectroscopic intensities, which are induced by applying an external perturbation to the sample, and are examined by constructing correlation spectra defined by two independent spectral variable axes. By spreading congested or overlapped peaks along the second dimension, apparent spectral resolution is enhanced, and interpretation of complex spectra is simplified. Further information about the sequence of dipole reorientation or conformational change can also be obtained. When the contents of the adulterants are low, 1% for instance, 2DCOS analysis of SHPs becomes rather challenging. To obtain meaningful 2DCOS data, it is necessary to use suitable pretreatments before carrying out the actual correlation analysis to further improve the resolution. The study by Miao et al. (2016) used the second derivative (SD) pretreatment to identify trace amounts of ephedrine and pseudoephedrine (0.5–1% to 5% contents) in slimming herbal products by deconvoluting overlapping peaks and enhancing resolution. Thermal perturbation was applied to obtain dynamic spectra for 2D correlation analysis. SD was carried out on 1D-FTIR before 2D synchronous spectral analysis to further enhance the spectral resolution and reduce the limit of detection (LOD). This pretreatment results in an improvement of LOD values, which are <1%, thus indicating that this method has a high sensitivity. 4.2. Nuclear Magnetic Resonance (NMR) Spectroscopy Nuclear magnetic resonance (NMR) spectroscopy can also be used as a method to determine adulterated herbal products. NMR spectroscopy is an analytical technique used to determine the content and purity of a sample, as well as its molecular structure, by taking advantage of the magnetic properties of certain nuclei. The basic principle behind NMR is that some nuclei exist in specific nuclear spin states when exposed to an external magnetic field. NMR uses a large magnet to probe the intrinsic spin properties of atomic nuclei. As is the case with all spectroscopies, NMR uses a component of electromagnetic radiation (radiofrequency waves) to promote transitions between nuclear energy levels (resonance) . Recent research conducted by Wu et al. (2020) has used the development of the NMR method, low-field 1 H NMR spectra, to analyze sibutramine and phenolphthalein in slimming dietary supplements. Low-field (LF) NMR is an emerging technique based on the use of a new generation of compact NMR. It presents an opportunity to replace costlier or destructive methods while utilizing non-deuterated solvents. The lowest limit value resulting from this method was 3 mg/100 mg, as shown in . This value shows that it is considered a sensitive method, but less sensitive compared to other spectroscopic methods. 4.3. Mass Spectrometry (MS) Mass spectrometry (MS) is an analytical technique that is used to measure the mass-to-charge ratio of ions. The results are typically presented as a mass spectrum, a plot of intensity as a function of the mass-to-charge ratio . Compared to other methods, MS can be used to detect a wider range of compounds. As shown in , a study by Hu et al. (2016) , using WT-ESI-MS, could analyze more than 5 undeclared drugs (melatonin, doxepin, diazepam, chlorpheniramine, zopiclone, nitrazepam, zaleplon, alprazolam, clonazepam, and chlordiazepoxide) from an herbal dietary supplement. wooden-tip ESI-MS (WT-ESI-MS) is a technique that could be used for the direct analysis of raw samples. This technique makes use of readily available, economical, and disposable wooden toothpicks, which can be directly compatible with commercially available nano ESI ion sources, for sampling and ionization. The slim and hard wooden tips are very convenient for sampling, and the technique could be used for the analysis of samples of various forms. By using this method, the LOD values that were obtained were 0,1 mg/g, which signifies a good sensitivity analytical method. Other than being combined with wooden-tip-ESI, MS can also be combined with fast-switching +/− HV tip-ESI. Research was conducted by Yao et al. (2019) to analyze the adulteration of paracetamol, naproxen, sulfamethoxazole, diclofenac, and phenylbutazone in herbal dietary supplements. Electrospray ionization mass spectrometry (ESI-MS) was commonly performed to obtain accurate results, due to its desirable sensitivity and specificity. In most of the previous work on tip-ESI, the analytes were detected in either positive or negative ion mode. However, various synthetic drugs are alternatively amenable to either a positive or negative ion mode but simultaneously exist in adulterated herbal dietary supplements, posing a challenging task for simultaneous detection of positive and negative ions by MS. By using a fast-switching positive/negative high-voltage (+/− HV) that was applied to tip ESI-MS for the simultaneous screening of five synthetic drugs, the MS detection mode (+/−) was automatically switched, and, accordingly, the drugs can then efficiently be detect in positive/negative mode. The LOD values obtained from 5 synthetic adulterated drugs were all <0.1 ng/g. These LOD values indicate a high sensitivity of fast-switching +/− HV tip-ESI-MS, which is superior compared to WT-ESI-MS. A recent study by Wang et al. (2020) has also used MS, which was developed with ultrasonic extraction and nebulization in real-time, coupled with carbon fiber ionization (UEN/CFI-MS), to screen antidiabetic drugs, an antihypertensive drug, and hypolipidemic drug adulteration in herbal products. UEN/CFI is a pretreatment method used to ionize samples without adding auxiliary gas or a heating system. Compared with electrospray ionization (ESI), UEN/CFI has shown great compatibility with both polar and non-polar compounds. In ESI-MS, compounds with extremely low polarity, such as anthracene, are hard to detect, meanwhile, UEN/CFI exhibits no compromise for the detection of polar compounds. UEN and CFI were separated as two independent ionization sources. UEN was used as the ultrasonic extraction and nebulization device that acts to efficiently desorb the analytes from the sample. Then, the tiny droplets containing desorbed analytes were efficiently ionized by CFI-MS. During the research conducted by Wang et al. (2020), the length of carbon fiber was 0.8 mm and the voltage on the carbon fiber was ±3.0 kV, meanwhile, the capillary temperature of the mass spectrometer was controlled at 300 °C. The assisted solvent (methanol) was injected through a syringe pump at a flow rate of 5.0 mL/min. The UEN was placed directly above the tip of the carbon fiber with a vertical distance of 6.0 cm. The sample solution was placed directly in the center of the UEN for liquid samples, while solid samples were directly analyzed after adding extraction solvents. The analyte inside the sample was extracted and nebulized efficiently by UEN. Atomized sample droplets were ionized by the CFI ion source, then the ion signals of the sample were captured by the mass spectrometer. The LOD values obtained by UEN/CFI-MS were 2 mcg/g to 50 mcg/g, which indicates a high sensitivity. Furthermore, the RSD values were less than 15%, which shows that it has a decent analytical method precision. Similarly to the chromatographic method, spectrophotometric is still widely used for routine analysis in laboratories. This method also offers good selectivity and sensitivity; however, this method is highly costly and usually must act in tandem with another method to improve the analytical performance.
Infrared (IR) spectroscopy is the simplest, most rapid, and non-destructive analytical method without any previous sample pre-treatment. Moreover, when no sample pre-treatment is required, it doesn’t need additional reagent during the analytical step. Hence, potentially harmful reagents are avoided, providing benefits for the environment and being cost-effective regarding chemical waste . IR spectroscopy is used to determine structures and functional groups of compounds and identify them based on the absorption by a molecule of a particular type of light, in the IR region of the electromagnetic spectrum. Each chemically distinct molecule will have a different absorption pattern made up of the number and different types of bonds present, and the presence of different functional groups . IR spectroscopy has been developed into the latest generation of IR, named Fourier-transform infrared spectroscopy. Fourier-transform infrared spectroscopy requires a mathematical process called Fourier transform to convert the raw data into the actual spectrum. The major difference between an FTIR spectrometer and a dispersive IR spectrometer is the Michelson interferometer. The Michelson interferometer, which is the core of FTIR spectrometers, is used to split one beam of light into two, so that the paths of the two beams are different. Then the Michelson interferometer recombines the two beams and conducts them into the detector where the difference of the intensity of these two beams is measured as a function of the difference of the paths . An example of a study that used conventional IR and FTIR are shown in . Research conducted by Nugroho and Ritonga (2018) determined the adulteration of dexamethasone in a traditional herbal medicine (THM) painkiller for joint pain, using infrared spectroscopy that combined with the partial least square (PLS). Adulteration of the undeclared synthetic drug caused complex spectra and the overlapping of absorption signals of various substances, which typically makes it difficult to interpret the spectra of the adulterated samples through use of an IR spectroscopy. Therefore, it is combined with the partial least square (PLS) method to separate spectra of the analyte (dexamethasone) from the spectra of an authentic traditional herbal medicine. Using the PLS method, maximum chemical information could be obtained from spectral data by permitting the selection of wavenumbers in complex spectra and linking changes in spectra to changes at various component levels simultaneously, by calculating the contribution of other spectra that can interfere with the spectrum. The PRESS and RMSECV values obtained as the result of the cross-validation model selection for dexamethasone in traditional herbal medicine painkillers for joint pain were 0.0022721 and 0.02902, respectively. Meanwhile, the RMSEC values obtained were 0.009455. This low value of RMSEC, RMSECV, and PRESS indicated the high accuracy and precision of the analytical method. Other research that used FTIR as an analytical method to detect sildenafil citrate in herbal aphrodisiacs has been performed by Nugroho et al. (2018) . To quantify the levels of sildenafil citrate in herbal medicines, this FTIR method is combined with the multivariate calibration of stepwise multiple linear regression (SMLR). Stepwise linear regression is a method of regressing multiple variables while simultaneously removing those that aren’t important. The result of this method validation obtained 0.000310913 as RMSEC values and 0.0009191 as PRESS values. Besides being combined with SMLR, FTIR can also be hyphenated with PLS Discriminant Analysis (PLS-DA). A study using the combination of FTIR-PLS DA method was conducted by Walkowiak et al. (2019) to detect the adulteration of kaempferol, rutin, or quercetin on the Ginkgo biloba supplement. PLS-DA provides a separation with minimal probability of false classification for test samples. The RMSEC and RMSECV values obtained were 0.393 and 0.570, respectively. By comparing the RMSEC, RMSECV, and PRESS values of the three methods using IR spectroscopy, it can be concluded that the FTIR-SMLR method has the best accuracy and precision due to the lowest values of RMSEC, RMSECV, and PRESS. Two-dimensional correlation infrared spectroscopy has been developed for analysis. Two-dimensional correlation spectroscopy (2DCOS) was employed for the identification of the ephedrine and pseudoephedrine present in illegally adulterated slimming herbal products (SHPs) that have been studied by Miao et al. (2016) . In 2DCOS, similarity or dissimilarity among variations of spectroscopic intensities, which are induced by applying an external perturbation to the sample, and are examined by constructing correlation spectra defined by two independent spectral variable axes. By spreading congested or overlapped peaks along the second dimension, apparent spectral resolution is enhanced, and interpretation of complex spectra is simplified. Further information about the sequence of dipole reorientation or conformational change can also be obtained. When the contents of the adulterants are low, 1% for instance, 2DCOS analysis of SHPs becomes rather challenging. To obtain meaningful 2DCOS data, it is necessary to use suitable pretreatments before carrying out the actual correlation analysis to further improve the resolution. The study by Miao et al. (2016) used the second derivative (SD) pretreatment to identify trace amounts of ephedrine and pseudoephedrine (0.5–1% to 5% contents) in slimming herbal products by deconvoluting overlapping peaks and enhancing resolution. Thermal perturbation was applied to obtain dynamic spectra for 2D correlation analysis. SD was carried out on 1D-FTIR before 2D synchronous spectral analysis to further enhance the spectral resolution and reduce the limit of detection (LOD). This pretreatment results in an improvement of LOD values, which are <1%, thus indicating that this method has a high sensitivity.
Nuclear magnetic resonance (NMR) spectroscopy can also be used as a method to determine adulterated herbal products. NMR spectroscopy is an analytical technique used to determine the content and purity of a sample, as well as its molecular structure, by taking advantage of the magnetic properties of certain nuclei. The basic principle behind NMR is that some nuclei exist in specific nuclear spin states when exposed to an external magnetic field. NMR uses a large magnet to probe the intrinsic spin properties of atomic nuclei. As is the case with all spectroscopies, NMR uses a component of electromagnetic radiation (radiofrequency waves) to promote transitions between nuclear energy levels (resonance) . Recent research conducted by Wu et al. (2020) has used the development of the NMR method, low-field 1 H NMR spectra, to analyze sibutramine and phenolphthalein in slimming dietary supplements. Low-field (LF) NMR is an emerging technique based on the use of a new generation of compact NMR. It presents an opportunity to replace costlier or destructive methods while utilizing non-deuterated solvents. The lowest limit value resulting from this method was 3 mg/100 mg, as shown in . This value shows that it is considered a sensitive method, but less sensitive compared to other spectroscopic methods.
Mass spectrometry (MS) is an analytical technique that is used to measure the mass-to-charge ratio of ions. The results are typically presented as a mass spectrum, a plot of intensity as a function of the mass-to-charge ratio . Compared to other methods, MS can be used to detect a wider range of compounds. As shown in , a study by Hu et al. (2016) , using WT-ESI-MS, could analyze more than 5 undeclared drugs (melatonin, doxepin, diazepam, chlorpheniramine, zopiclone, nitrazepam, zaleplon, alprazolam, clonazepam, and chlordiazepoxide) from an herbal dietary supplement. wooden-tip ESI-MS (WT-ESI-MS) is a technique that could be used for the direct analysis of raw samples. This technique makes use of readily available, economical, and disposable wooden toothpicks, which can be directly compatible with commercially available nano ESI ion sources, for sampling and ionization. The slim and hard wooden tips are very convenient for sampling, and the technique could be used for the analysis of samples of various forms. By using this method, the LOD values that were obtained were 0,1 mg/g, which signifies a good sensitivity analytical method. Other than being combined with wooden-tip-ESI, MS can also be combined with fast-switching +/− HV tip-ESI. Research was conducted by Yao et al. (2019) to analyze the adulteration of paracetamol, naproxen, sulfamethoxazole, diclofenac, and phenylbutazone in herbal dietary supplements. Electrospray ionization mass spectrometry (ESI-MS) was commonly performed to obtain accurate results, due to its desirable sensitivity and specificity. In most of the previous work on tip-ESI, the analytes were detected in either positive or negative ion mode. However, various synthetic drugs are alternatively amenable to either a positive or negative ion mode but simultaneously exist in adulterated herbal dietary supplements, posing a challenging task for simultaneous detection of positive and negative ions by MS. By using a fast-switching positive/negative high-voltage (+/− HV) that was applied to tip ESI-MS for the simultaneous screening of five synthetic drugs, the MS detection mode (+/−) was automatically switched, and, accordingly, the drugs can then efficiently be detect in positive/negative mode. The LOD values obtained from 5 synthetic adulterated drugs were all <0.1 ng/g. These LOD values indicate a high sensitivity of fast-switching +/− HV tip-ESI-MS, which is superior compared to WT-ESI-MS. A recent study by Wang et al. (2020) has also used MS, which was developed with ultrasonic extraction and nebulization in real-time, coupled with carbon fiber ionization (UEN/CFI-MS), to screen antidiabetic drugs, an antihypertensive drug, and hypolipidemic drug adulteration in herbal products. UEN/CFI is a pretreatment method used to ionize samples without adding auxiliary gas or a heating system. Compared with electrospray ionization (ESI), UEN/CFI has shown great compatibility with both polar and non-polar compounds. In ESI-MS, compounds with extremely low polarity, such as anthracene, are hard to detect, meanwhile, UEN/CFI exhibits no compromise for the detection of polar compounds. UEN and CFI were separated as two independent ionization sources. UEN was used as the ultrasonic extraction and nebulization device that acts to efficiently desorb the analytes from the sample. Then, the tiny droplets containing desorbed analytes were efficiently ionized by CFI-MS. During the research conducted by Wang et al. (2020), the length of carbon fiber was 0.8 mm and the voltage on the carbon fiber was ±3.0 kV, meanwhile, the capillary temperature of the mass spectrometer was controlled at 300 °C. The assisted solvent (methanol) was injected through a syringe pump at a flow rate of 5.0 mL/min. The UEN was placed directly above the tip of the carbon fiber with a vertical distance of 6.0 cm. The sample solution was placed directly in the center of the UEN for liquid samples, while solid samples were directly analyzed after adding extraction solvents. The analyte inside the sample was extracted and nebulized efficiently by UEN. Atomized sample droplets were ionized by the CFI ion source, then the ion signals of the sample were captured by the mass spectrometer. The LOD values obtained by UEN/CFI-MS were 2 mcg/g to 50 mcg/g, which indicates a high sensitivity. Furthermore, the RSD values were less than 15%, which shows that it has a decent analytical method precision. Similarly to the chromatographic method, spectrophotometric is still widely used for routine analysis in laboratories. This method also offers good selectivity and sensitivity; however, this method is highly costly and usually must act in tandem with another method to improve the analytical performance.
Numerous conventional instrumental analytical techniques are used for the determination of adulterated drugs in herbal medicines, such as the chromatographic-based and spectroscopic-based methods that were previously described. These techniques require expensive equipment, highly trained operators, and are only suitable for routine analysis in the laboratory. Recently, the utilization of microfluidic analytical devices for drug analysis has been developed. This device offers several advantages, such as simplicity, low cost, rapid analysis, portability, and low consumption of reagent and sample . The first microfluidic paper-based analytical device (µPAD) was developed for point-of-care medical diagnostic and is now being developed for bacterial, pesticides, organic molecules, metal, and drug analysis . Various substrates have been used for fabricating microfluidic devices, including paper-based and polymer . The microfluidic device was also developed in the determination of undeclared synthetic drugs in herbal medicine, as shown in . The visualization of all the microfluidic device that has been reviewed is shown in . A study conducted by Pratiwi et al. (2018) developed an optical sensor device based on polymer poly(methyl methacrylate) (PMMA) for paracetamol detection in herbal medicine. PMMA offers some benefits as a membrane material, due to its mechanical strength, chemical inertness, and high thermal stability . A phase inversion method was applied for fabrication of the polymer membrane and colorimetric was chosen as a detection method. In this experiment, they vary the concentration of PMMA to 5%, 7.5%, and 10%, and each concentration was dissolved in the mixture with a colorimetric reagent, such as ferric chloride, Folin–Ciocalteu reagent, Nessler’s reagent, and Lieberman reagent. The mixture ratio of the solvent and reagent was 6:4, 7:3, and 8:2. The best results show on PMMA 7.5%-FeCl 3 (7:3), PMMA 5%-Folin (6:4), and PMMA 5%-Nessler (6:4). The performance of this device, including its sensitivity, stability, and selectivity, is acceptable and shows good agreement with the spectrophotometry method. The visualization of the optical sensor membrane is shown in A. Other research develops a colorimetric paper-based analytical device for allopurinol detection in herbal medicine . The study was conducted by using Whatman filter paper No. 1, No. 2, and No. 4 and Whatman chromatography as a substrate, and nine colorimetric reagents (dragendorf reagent, ferric chloride, Folin-Ciocalteu reagent, sodium nitroprusside, p-DAB reagent, Schiff reagent, potassium chlorate, tollens reagent, and sodium nitrite) based on the reaction with allopurinol. The result shows that only Folin-Ciocalteu, tollens, and p-DAB reagent can be applied to the paper. Folin-Ciocalteu will give a dark blue color when reacting with the allopurinol solution, meanwhile, tollens and p-DAB reagent give a silver and yellow color, respectively. The design of PAD following the design of universal pH indicator strip and PAD containing 3 of specific reagent, as shown in C. The results show that there was no significant difference in the results of the varying papers, and the lowest measurable detection of PAD is 75 mg/mL. The device is selective due to having different color changes with another interfering compound. Application in the real sample shows good agreement with TLC and the spectrophotometry data in 75 mg/mL. Colorimetric is one of the detection methods commonly used for PAD, due to its simplicity, high contrast when using paper as a substrate, and low-cost detection system . However, this detection method lacks sensitivity and selectivity . To improve the sensitivity and selectivity, electrochemical detection can be applied for PAD through the selection of the electrode material, measurement techniques, and detection scheme . In addition, multiple drug compounds are electrochemical active, making this detection potential for direct detection . Primpray et al. (2019) developed the paper-based analytical device with electrochemical detection for the determination of dexamethasone and prednisolone in traditional medicine. They used Whatman SG81 silica-coated paper and a design that had three channels and two different bulb shapes in the bottom and upper areas, as shown in D. The device was printed by a 3D printer with PLA filament polymer and printed as a 3D-printed cassette, providing two inlets for screen-printed carbon electrode (SPCE) insertion, together with a 3D printed cutter. The optimal mobile phase was 60% ethyl acetate in cyclohexane, and the limits of detection for dexamethasone and prednisolone were 3.59 and 11.98 µg/mL, respectively, whereas the limits of quantification were 6.00 and 20.02 µg/mL, respectively. Analysis in real samples was compared with the standard HPLC method and the result showed good correlation. Another detection method that can be applied in PAD is distance-based detection. This detection measures the length of color change along the channel of paper and is recently widely applied as a device for metal analysis . Distance-based detection offers a simplified technique for quantitative detection . The distance-based paper analytical device for sibutramine detection in slimming products was developed by Karamahito et al. (2021) . They used filter paper printed with thermometer-shaped and a ruler scale printed parallel along the channel, as shown in B. Dragendorff’s reagent was used along the channel to form an orange-red precipitate of the sibutramine-tetraiodobismuthate complex. The length of the color change is proportional to the amount of sibutramine in the sample. The result shows that this device has LOQ 0.22 mmol/L and a precision of less than 4.4%RSD. The result is also in agreement at 95% confidence level with the gas chromatographic method. This device offers simple, low-cost, and instrument-free onsite analysis. A simple and rapid analytical device for the detection of adulterated drugs in herbal medicine was also developed by Kuswandi et al. (2021) . They developed a dipstick test for dexamethasone detection constructed by immobilization of FeCl 3 and K 3 [Fe(CN) 6 ] onto cellulose acetate film in acid conditions, as shown in E. The cellulose acetate was activated by increasing the porosity of film and de-esterification. The reagent was immobilized in the detection zone of the film. The color change was green to blue in the presence of dexamethasone and captured using ImageJ for quantitative measurement. The results show the dipstick test has linearity in 0.5–75 μg/mL, and the LOD and LOQ were 0.422 μg/mL and 1.406 μg/mL, respectively. Application in the various sample shows a good agreement with UV spectrophotometric. This device offers an alternative tool for dexamethasone detection in herbal medicine. The microfluidic analytical device can be an alternative instrument-free method for the detection of adulterated drugs in herbal medicine. This device is designed for simple, portable, and easy use for direct analysis. The performance of this method can be improved by selecting an appropriate detection for analysis.
The utilization of the electrochemical method has a considerable attraction for drug analysis. Electrochemical detection offers improved selectivity, sensitivity, and can also be carried out using portable instruments . The application of this method has been demonstrated by Freitas et al. (2018) for sibutramine detection in a natural product. They used the square-wave voltammetric (SWV) method adapted to a portable batch-injection analysis (BIA), which provided a simple and portable fast screening and quantification of sibutramine in herbal products. The voltammetric system was performed using a PGSTAT 128N potentiostat/galvanostat and used a boron-doped diamond (BDD) as the working electrode. The sample was dissolved in 0.1 mol/L H 2 SO 4 as an optimum supporting electrolyte. The result shows the recovery value was 105 to 113% with the relative standard deviation less than 3% and the LOD was 0.08 to 1.94 mg/L. This system claims to be able to screen 200 analyses without handling the electrodes of the BIA-SWV system, and is also suitable for determination up to 1% of sibutramine in the sample. Other research conducted by Saichanapan et al. (2020) uses porous graphene ink-modified electrodes on the glassy carbon electrode surface (PGr-ink/GCE) to improve sensitivity for the determination of sibutramine in slimming products. ATR-FTIR spectroscopy and SEM were applied for surface characterization, meanwhile cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were applied to study the electrochemical adsorption behavior of the PGr-ink/GCE. The adsorption of sibutramine on PGr-ink/GCE was examined by square wave adsorptive stripping voltammetry (SWAdSV) to determine the concentration of sibutramine. The result showed that PGr-ink/GCE exhibited a sensitivity four times higher than bare GCE, and the limit of detection and quantification were 5 ng/mL and 15 ng/mL, respectively. In addition, this system shows good reproducibility and repeatability at less than 3.4% and RSD was 1.8 to 9.8%, respectively. The developed PGr-ink/GCE offers a simple, low detection limit, and a high sensitivity sibutramine sensor for detecting sibutramine in the sample. Electrochemical detection can be used as another approach for analyzing adulterated drugs in herbal medicine, since the sensitivity and the selectivity of the assay can improve by selecting electrode material and measurement techniques. In addition, this technique can combine with a portable addition device, creating the possibility for on-site analysis.
Traditional herbal medicine has gained approval, especially in developing countries, as an alternative or complementary medicine. The safety of herbal products has become a concern due to the herbal products that have been found to contain undeclared synthetic drugs. Many regulations state that herbal medicines should not contain illegal drugs due to the side effects of uncontrolled consumption, such as headaches, nausea, insomnia, diarrhea until hematological abnormalities, mental depression, and even inducing a coma. Reliable analytical techniques are important for detecting adulterated drugs in herbal medicine to ensure the quality of herbal medicines and to protect human health. For routine analysis in the laboratory, the use the of instrument techniques, such as chromatography-based and spectroscopic-based with various detectors, or coupled with another detection method, is most likely. The instrumental technique provides excellent accuracy, precision, and sensitivity in the determination of adulterated drugs. These techniques required large instrumentation, making them inappropriate for on-site analysis. The instrumental-free analysis has been developed for portable analysis. The platform uses analytical devices based on paper, polymer, or film as a medium for the determination of drugs. This platform offers a simple, easy and low-cost alternative tool for on-site detection. The detection method can be selected based on the practical considerations and required analytical figures of merit. In addition, improving the analytical method is still necessary to provide an alternative method that can be adapted as required.
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Validation of mortality risk scores after esophagectomy | 4a8ca9cd-ae33-440c-a150-180f4e9ed027 | 11775027 | Surgical Procedures, Operative[mh] | 544,000 people died of esophageal cancer in 2020 worldwide, which makes it the sixth leading cause of cancer-related deaths (Sung et al. ). Multimodal treatment strategies have vastly improved the survival of esophageal cancer patients over the past decades, and new therapeutic approaches, such as immunotherapy, are on the rise. However, esophagectomy is still the mainstay of curative treatment for esophageal cancer patients. Even if postoperative morbidity and mortality rates have declined over the last decades due to advances in operation techniques such as minimally invasive approaches, improved intensive care unit treatment, and improved management of complications, postoperative mortality still ranges between 4 and 10% (Enzinger and Mayer ; Siegel et al. ). Besides hospital volume, mortality rates depend mainly on the patient’s individual risk profile (Anderson et al. ; Ghaferi et al. ). For surgeons and patients, the main question is who should be treated by surgery and for whom other treatment options should be considered since mortality risk is too high. Moreover, patients with an increased risk profile should be monitored more closely to identify complications early and reduce mortality through early interventions, such as prophylactic endosponge placement (Schniewind et al. ). Various risk factors for increased mortality have been investigated (van Kooten et al. ), and different risk scores have been established (Fuchs et al. ; Liu et al. ; Ra et al. ; Steyerberg et al. ; Tekkis et al. ; Zhang et al. ). Recently, the International Esodata Study Group (IESG) established a 90-day mortality risk prediction model based on the data of 8403 patients from 39 centers in 19 countries (D’Journo et al. ). This prediction model consisting of ten different parameters allows the surgeon to calculate a more individual patient’s risk score than previous score systems. However, validation of this score in a single-center high-volume setting and comparison to previous models is absent in current literature. Therefore, the aim of this study is to evaluate this score in a large high-volume center cohort and compare its predictive value for postoperative mortality with two other existing scores by Steyerberg and Fuchs (Fuchs et al. ; Steyerberg et al. ).
Database search A prospectively maintained database of patients undergoing esophagectomy for upper gastrointestinal tract cancer at the University Hospital Heidelberg, Germany, from January 2002 until December 2021 was used for the analysis. Patients undergoing esophagectomy due to perforations were excluded. This study complies with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of the Medical Faculty of Heidelberg (S-635/2013), and the patients gave informed written consent in accordance with the local ethics committee’s vote. Mortality rates were defined from the operation to the patients’ death. We followed the TRIPOD guidelines for score validations. Scores/Risk assessment The following parameters necessary for risk score calculation were gathered from the electronic patient files: age, body-mass-index, gender, ECOG, comorbidities, neoadjuvant treatment, hospital volume, tumor histology, and surgical approach. The individual risk score for each scoring system (IESG, Steyerberg, Fuchs) was calculated for all patients. Statistical analysis The areas under the receiver operating characteristic (ROC) curves were used to estimate the diagnostic performance of the different risk scores. An AUC of 0.5 predicts no discriminative ability, while an AUC of 1 indicates perfect discrimination with 100% sensitivity and 100% specificity. Prediction models with an AUC of 0.8 and above have been labeled as very good to excellent, those with an AUC between 0.7 and 0.8. as moderate, and 0.6 to 0.7 as providing low discrimination. All analyses were performed using SPSS Statistics ® , version 28.0.1.0, and RStudio, version 1.3.959.
A prospectively maintained database of patients undergoing esophagectomy for upper gastrointestinal tract cancer at the University Hospital Heidelberg, Germany, from January 2002 until December 2021 was used for the analysis. Patients undergoing esophagectomy due to perforations were excluded. This study complies with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of the Medical Faculty of Heidelberg (S-635/2013), and the patients gave informed written consent in accordance with the local ethics committee’s vote. Mortality rates were defined from the operation to the patients’ death. We followed the TRIPOD guidelines for score validations.
The following parameters necessary for risk score calculation were gathered from the electronic patient files: age, body-mass-index, gender, ECOG, comorbidities, neoadjuvant treatment, hospital volume, tumor histology, and surgical approach. The individual risk score for each scoring system (IESG, Steyerberg, Fuchs) was calculated for all patients.
The areas under the receiver operating characteristic (ROC) curves were used to estimate the diagnostic performance of the different risk scores. An AUC of 0.5 predicts no discriminative ability, while an AUC of 1 indicates perfect discrimination with 100% sensitivity and 100% specificity. Prediction models with an AUC of 0.8 and above have been labeled as very good to excellent, those with an AUC between 0.7 and 0.8. as moderate, and 0.6 to 0.7 as providing low discrimination. All analyses were performed using SPSS Statistics ® , version 28.0.1.0, and RStudio, version 1.3.959.
A total of 758 patients were identified; data from 714 patients were available to calculate all three risk scores. The majority of the patients were male (82.2%). The median age was 61.35 (28–85). 626 (87.67%) patients underwent abdomino-thoracic esophagectomy (Ivor-Lewis procedure), 42 (5.88%) underwent abdomino-thoracic esophagectomy with cervical anastomosis, 23 (3.22%) underwent transhiatal esophagectomy with cervical anastomosis, 17 (2.38%) underwent esophago-gastrectomy and 6 (0.84%) underwent other types of resection. 496 (69.47%) patients underwent neoadjuvant treatment, mainly chemotherapy (45.93%), 19.6% received radiochemotherapy, and 0.98% radiotherapy only. Hospital volume during the period was 22–69 esophagectomies per year. In our cohort, the observed mortality rates were as follows: 30-day mortality was 3.4%, 90-day mortality was 6.86%, and in-hospital mortality was 6.72%. IESG score According to the distribution of points for the particular risk factors of the IESG score across our cohort (Table ), patients reached between − 6 and 4 points (Table A). 365 patients (51.25%) had very low (1 to 5 points), 191 (26.75%) had low (0 points), 129 (18.1%) had medium (-2 to -1 points), 20 (2.8%) had high (-4 to -3 points), and 8 (1.1%) had very high risk (-5 to -10 points) for postoperative mortality within 90 days (Table B). The 90-day mortality in our cohort was 6.86%. Table A + B demonstrates the mortality for each risk group. Steyerberg score Attributing the respective points according to the risk factors of the Steyerberg score (Table A), point scores ranged between − 3 and 3 in our patient collective (Table A). Forty-one patients had two comorbidities, with cardiovascular disease and diabetes being the most common combination. The 30-day mortality in our cohort was 3.4%. Table A shows the 30-day mortality for each group. Fuchs score After calculating points according to the relevant parameters (Table B), patients in our cohort reached scores between 0 and 10 compared to 0 and 16 in the Fuchs cohort (Table B). According to Fuchs et al., 675 patients (94.5%) had low (0–7 points), and 39 (5.5%) had a high risk (8–16 points) for in-hospital mortality. The in-hospital mortality was 6.07% in the low-risk group and at 17.95% in the high-risk group, resulting in an overall mortality rate of 6.72%. Validation of the scores In terms of diagnostic performance, the area under the ROC curve (AUC) was 0.634 (95%CI: 0.557–0.712) for the IESG risk prediction model, 0.637 (95%CI: 0.526–0.747) for the Steyerberg score, and 0.686 (95%CI: 0.611–0.760) for the Fuchs risk scale. Results are shown in Fig. a-c.
According to the distribution of points for the particular risk factors of the IESG score across our cohort (Table ), patients reached between − 6 and 4 points (Table A). 365 patients (51.25%) had very low (1 to 5 points), 191 (26.75%) had low (0 points), 129 (18.1%) had medium (-2 to -1 points), 20 (2.8%) had high (-4 to -3 points), and 8 (1.1%) had very high risk (-5 to -10 points) for postoperative mortality within 90 days (Table B). The 90-day mortality in our cohort was 6.86%. Table A + B demonstrates the mortality for each risk group.
Attributing the respective points according to the risk factors of the Steyerberg score (Table A), point scores ranged between − 3 and 3 in our patient collective (Table A). Forty-one patients had two comorbidities, with cardiovascular disease and diabetes being the most common combination. The 30-day mortality in our cohort was 3.4%. Table A shows the 30-day mortality for each group.
After calculating points according to the relevant parameters (Table B), patients in our cohort reached scores between 0 and 10 compared to 0 and 16 in the Fuchs cohort (Table B). According to Fuchs et al., 675 patients (94.5%) had low (0–7 points), and 39 (5.5%) had a high risk (8–16 points) for in-hospital mortality. The in-hospital mortality was 6.07% in the low-risk group and at 17.95% in the high-risk group, resulting in an overall mortality rate of 6.72%.
In terms of diagnostic performance, the area under the ROC curve (AUC) was 0.634 (95%CI: 0.557–0.712) for the IESG risk prediction model, 0.637 (95%CI: 0.526–0.747) for the Steyerberg score, and 0.686 (95%CI: 0.611–0.760) for the Fuchs risk scale. Results are shown in Fig. a-c.
Preoperative risk stratification is an essential tool for identifying high-risk patients. A 2020 review found 26 preoperative predictive scores of postoperative mortality, such as the Preoperative Score to Predict Postoperative Mortality, the American Society of Anesthesiologists classification system (ASA), or the Charlson comorbidity index (Charlson et al. ; Le Manach et al. ; Saklad ). In 2021, the IESG developed a new risk score to predict 90-day mortality after esophagectomy (D’Journo et al. ). Before introducing a risk prediction model to clinical use, it should be validated on patient populations. To our knowledge, this is the first study to validate the IESG score in a single-center high-volume center which has not contributed toIESG data. Steyerberg et al. reported in 2006 a predictive score including eight characteristics related to the outcome after esophagectomy (Steyerberg et al. ). A key limitation of this score is that it relies on patient data from the 1990s. As morbidity and mortality of esophagectomy have dramatically changed over the past three decades, the prognostic value of the Steyerberg score might be limited. However, the AUC of the Steyerberg score in our cohort was 0.637, confirming the initial study’s results (AUC 0.56–0.70). Compared to the original publication of the Steyerberg score, our 30-day mortality was lower (3.0% compared to 4%,7%,10%, and 11%). The most likely explanation for this difference is the abovementioned improvement in perioperative treatment. Furthermore, Steyerberg’s score is based upon SEERs (Surveillance, Epidemiology, and End Result) data, which included lacks granularity of institutional databases and therefore may have missed some relevant predictive factors including ASA (American Society of Anesthesiologists) classification. The in-hospital mortality score by Fuchs used six patient factors (age, cardiovascular, pulmonary, renal and hepatic comorbidity and tumor pathology) and two hospital factors (operation volume/year, abdominal approach) to calculate the mortality (Fuchs et al. ). The AUC for the Fuchs score was 0.686, which also agrees well with the score. The in-hospital mortality rate in our hospital was 6.7% compared to 7.7%, as calculated by the Fuchs score. The Fuchs score’s main limitation is the reliance on a nationwide database, including data on discharge records. These databases rely on accurate data but may lack details on complex cases, like preoperative functional or nutritional status or neoadjuvant treatment. Even though considerable differences between the cohorts of the original publication of the IESG score and our cohort exist, predictive values were similar with 0.634 compated to 0.68 in development and 0.64 in the validation group. Almost 60% of the patients in the IESG cohort had a minimally invasive operation, whereas in our cohort over 20 years starting in 2002, a majority received an open operation (87.4%). In the IESG cohort on the other hand the investigation period was relatively short with just four years. Although the operation technique is not part of the risk stratification for IESG, this finding shows similar performance in different settings. A limitation pertinent to the IESG score is its derivation from the Esodata database, which was not designed for this specific research questions and lacks the capacity for in-depth analysis or the consideration of additional variables. However, preoperative risk stratification should be practical and reliable. Complex scores with too many parameters are less suitable for clinical use. Parameters that need to be calculated or analyzed may need to be more practical for the clinical routine. The IESG score includes ten parameters compared to eight factors included in the Steyerberg and eight factors in the Fuchs score. Inclusion of more parameters should naturally result in a more sophisticated model yielding a more accurate risk prediction. However, in our collective all scores revealed rather low predictive power irrespective of the number of parameters included. The parameters used in the IESG score all seem reasonable and are simple to collect. Yet inclusion of ten parameters each with various numerical values results in a cumbersome calculation process which seemed slightly too complex for the clinical implementation of this score in the past. Yet, rapid advancements in artificial intelligence (AI) and related technologies have significantly expanded the possibilities for complex risk prediction models. While modern tools could manage a larger number of parameters more efficiently, practical challenges currently faced in routine clinical workflows, such as time constraints, user training, and accessibility in resource-limited settings still have to be considered. Future risk prediction models should aim to leverage the transformative potential of these innovations. The three models differed in the included comorbidities for calculating the score. Whereas Fuchs and Steyerberg found that cardiovascular, pulmonary, renal, and hepatic comorbidities had an impact, the grade of the impact differed. For example, Steyerberg gave every comorbidity one point, whereas Fuchs’s score shows more severity for renal and especially hepatic comorbidities. The IESG score, on the other hand, just gave a higher score for people with moderate or severe liver disease and did not include pulmonary or renal comorbidities but connective tissue disease and peripheral vascular disease. All investigated scores carry the risk that comorbidities are underestimated and not entirely diagnosed at the time of the risk assessment. Combining all published studies on this topic, a meta-analysis showed that an age ≥ 70 and cardiac and renal comorbidities significantly impacted the 30-day- and in-hospital mortality. In contrast, the meta-analysis did not show a significant impact of a BMI < 18.5 and pulmonary comorbidities on the 30-day- and in-hospital mortality. The alcohol intake that was also a significant prognostic factor for a 30-day- and in-hospital mortality (OR 3.1 (95%CI 2.26–4.25) was not included in any of the three predictive scores (van Kooten et al. ). Another important parameter in all three scores is hospital volume. High-risk procedures such as esophagectomy should be performed in high-volume centers to reduce morbidity and mortality (Markar et al. ; Metzger et al. ). Our study has some limitations. It is a retrospective single-center evaluation with a smaller sample size than the original publications (IESG 8403, Fuchs 23751, Steyerberg 3592 patients). Another limitation of this study is the long study period from 2002 till 2021. As noted in the introduction, substantial changes have occurred in surgical techniques, intensive care, and complication management. These advancements have likely contributed to improved outcomes in recent years. The long study period could also explain the higher mortality rates observed in our cohort’s low- and very low-risk groups compared to the IESG cohort. When analyzing only patients treated from 2015 to 2021, the mortality rates decrease to 3.2% for the low-risk group and 1.3% for the very low-risk group, which are consistent with the results reported by the IESG. Even when postoperative mortality could be reduced over the years, complication rates of up to 22–70% are mainly caused by respiratory complications like pneumonia with respiratory failure, arrhythmia, anastomotic leakage, and wound infection (Atkins et al. ; McLoughlin et al. ; Raymond et al. ). Results of the IESG score showed that this kind of complications occur more often in very high and high-risk patients (D’Journo et al. ). How can we apply high-risk patient identification in practice? First, surgery indications for high-risk patients should be critically reconsidered, especially if definitive radiochemotherapy is a viable alternative. If neoadjuvant radiochemotherapy shows a good response, surgery with its risks might be postponed in favor of regular follow-up in selected cases. However, with an AUC of < 0.7 in all scores, prediction is unreliable and therefore the scores show insufficient performance to guide these important treatment decisions. Second, procedures such as prophylactic endoluminal vacuum therapy should be considered in patients with increased risk profile. Studies in this regard currently need to be improved. A systematic review of prophylactic vacuum therapy identified four case series for patients undergoing esophagectomy for cancer treatment (Adamenko et al. ). The biggest case study with 67 patients, whereas 57 patients were identified as high-risk patients (ASA > 2, BMI > 29, WHO/ECOG score > 1, age > 65 years), was done after minimal invasive Ivor-Lewis procedure. The morbidity rate was 40% for minor and 15% for major morbidity. 73% of the patients showed an uneventful healing of anastomosis. The anastomosis leakage rate was 7.5% (Müller et al. ). Thus, prophylactic endoluminal vacuum therapy could reduce the rate of anastomosis leakage and therefore, may also reduce morbidity and mortality rates, but high-evidence is lacking. As it might be a potential option for high-risk patients the potential drawbacks of prophylactic endosponge therapy must be considered. One notable concern is its possible interference with established enhanced recovery after surgery (ERAS) or fast-track programs, which have been consistently shown to improve postoperative outcomes (Huang et al. ). This conflict underlines the need for a balanced approach carefully evaluating risks and benefits of prophylactic endosponge therapy. Future research should focus on clarifying its efficacy and determining its role in the context of high-risk patients and ERAS protocols. Last but not least, high-risk patients should be monitored more intensively after surgery to identify and treat complications early, in order to reduce perioperative morbidity and mortality by their timely treatment. In conclusion, the existing scoring systems provide a possibility for individual preoperative risk stratification, especially to identify high-risk patients. However, strategies for identifying these patients and their application in everyday clinical life currently need to be improved due to their low predictive ability.
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Differentiated Papillary NUT Carcinoma: An Unexpected, Deceptively Bland Presentation of a Sinonasal Carcinoma | 51752bae-574e-46aa-a91f-6e5ea26ca085 | 10513967 | Anatomy[mh] | Over the past decade, the spectrum of malignant tumors of the head and neck has expanded, with many entities characterized by distinct molecular alterations. For example, carcinomas comprise conventional squamous cell carcinomas, NUT carcinomas, DEK::AFF2 carcinomas, EBV- and HPV-associated carcinomas, undifferentiated as well as SWI/SNF complex deficient sinonasal carcinomas, highlighting the variety of different morphologies and molecular pathogeneses . However, morphological overlap between different entities should be considered during the process of histopathological diagnosis. Here we report the case of a 32-year-old male patient, who presented with a non-healing lesion of the upper alveolar ridge after tooth extraction, leading to an oro-antral fistula. The histological features of the initial biopsy appeared deceptively bland, prompting the differential diagnosis of reactive inflammatory changes. However, an external histopathological consultation accompanied by molecular work-up with the detection of a NSD3::NUTM1 fusion, yielded the unexpected diagnosis of a sinonasal NUT carcinoma originating from the maxillary sinus. Clinical Presentation A 32-year-old, otherwise healthy, actively smoking male patient, presented with a 5-month history of pain in the left upper jaw. He was referred to a dentist, and after treatment, including extraction of tooth 25, wound healing delay was accompanied by a persistent oro-antral fistula (Fig. ). On examination, the fistula was localized at the site of the extracted tooth and the alveolar ridge of the posterior part appeared enlarged. The first biopsy showed chronic-active inflammatory changes. A post-biopsy CT scan of the paranasal sinuses demonstrated a large osseous defect and bone erosion at the site of the extracted tooth with complete opacification of the left maxillary sinus (Fig. A). Despite the inflammatory changes noted in the first biopsy, the CT scan was interpreted as suspicious for malignancy. A second, larger biopsy was performed one month later, revealing a non-keratinizing squamous cell carcinoma. For staging purposes and resection planning, a whole body FDG-PET/CT was performed, showing metabolically enhanced osseous destruction in the left maxillary sinus (Fig. B). The patient was discussed at our multidisciplinary tumor board with the consensus that disease was staged as cT2 cN0 cM0 (UICC/TNM 8 th edition), requiring primary resection. A hemimaxillectomy with wide margins was performed. In addition, the patient underwent a selective neck dissection level I-III on the left side followed by reconstruction of the defect with a superficial circumflex iliac artery-based iliac bone-free flap. Pathology The initial biopsies revealed an exophytic-papillomatous (Fig. A), partly inverted tumor with squamous differentiation without unequivocal evidence of invasion. Based on the clinical context of a prior tooth extraction with persistent oro-antral fistula, differential diagnostic considerations encompassed prominent reactive inflammatory changes as well as an exophytic-papillomatous, well-differentiated carcinoma. Mucocytes were not detected in the Alcian-Blue-PAS-stain. Therefore, despite abundantly admixed granulocytes, a sinonasal papilloma (which could have aided the diagnosis as a possible precursor lesion) could not be confirmed. In light of the relatively mature squamous differentiation, minimal cytologic atypia and prominent inflammation, a clear diagnosis was hampered. In the second biopsy, small, discohesive collections of epithelial cells infiltrating the stroma with focal transformation into larger, basaloid aggregates without clear demarcation by a basement membrane, militated against the diagnosis of a reactive process (Fig. B–D). Additionally, the time course and clinico-radiological features favored a malignant process. The interpretation as a reactive squamous epithelial proliferation was revised with the descriptive diagnosis of an exophytic-papillomatous and partly endophytic growing carcinoma. In the ensuing external pathologic consultation, a diagnosis of a non-keratinizing squamous cell carcinoma (NKSCC) was rendered, assuming that the lesion originated from the sinonasal tract rather than the mucosa of the oral cavity, based on the latest WHO classification of Head & Neck Tumours 5th edition (beta version) . HPV DNA testing as well as EBV-RNA in situ hybridization and p16 immunohistochemistry were negative. In order to address the differential diagnosis of a DEK::AFF2 fusion-associated carcinoma, molecular profiling was performed using the FoundationOne ® Heme test. DEK::AFF2 fusion-associated carcinomas have been described recently as an emerging entity in the sinonasal tract, with the majority showing a strikingly bland histologic appearance and overlap with so-called low-grade papillary Schneiderian carcinomas . Importantly, the detection of a DEK::AFF2 gene fusion would allow for more accurate classification and prognostic assessment. Surprisingly, no DEK::AFF2 , but a NUT::NSD3 gene fusion was detected, leading to the diagnosis of a NUT carcinoma. A subsequently performed NUT immunohistochemistry (Fig. E) showed a matching “speckled type” positivity in the majority of the carcinoma cells (almost 100% in both, basaloid and more differentiated components), corroborating the diagnosis and visualizing the fusion product. In concordance with the morphology lacking mucocytes, no EGFR mutation was detected, which are very common in inverted sinonasal papilloma and their carcinoma ex papilloma . The macroscopy of the following left-sided hemimaxillectomy showed the main tumor originating in the maxillary sinus and breaking through the bone into the oral cavity. Together with the neck dissection specimen level I-III the final pathologic tumor staging (according to carcinomas of the nasal cavity and paranasal sinuses) was pT2 pN0 (0/57) L0 V0 Pn1, high-grade, R0 (UICC/TNM 8 th edition, 2017). Extensive perineural spread was noted. Clinical Follow-up Adjuvant local radiotherapy was recommended at our multidisciplinary tumorboard. One year after diagnosis and six months after completion of treatment (at the time of the case report submission), the patient showed no evidence of disease, neither clinically nor on PET/CT.
A 32-year-old, otherwise healthy, actively smoking male patient, presented with a 5-month history of pain in the left upper jaw. He was referred to a dentist, and after treatment, including extraction of tooth 25, wound healing delay was accompanied by a persistent oro-antral fistula (Fig. ). On examination, the fistula was localized at the site of the extracted tooth and the alveolar ridge of the posterior part appeared enlarged. The first biopsy showed chronic-active inflammatory changes. A post-biopsy CT scan of the paranasal sinuses demonstrated a large osseous defect and bone erosion at the site of the extracted tooth with complete opacification of the left maxillary sinus (Fig. A). Despite the inflammatory changes noted in the first biopsy, the CT scan was interpreted as suspicious for malignancy. A second, larger biopsy was performed one month later, revealing a non-keratinizing squamous cell carcinoma. For staging purposes and resection planning, a whole body FDG-PET/CT was performed, showing metabolically enhanced osseous destruction in the left maxillary sinus (Fig. B). The patient was discussed at our multidisciplinary tumor board with the consensus that disease was staged as cT2 cN0 cM0 (UICC/TNM 8 th edition), requiring primary resection. A hemimaxillectomy with wide margins was performed. In addition, the patient underwent a selective neck dissection level I-III on the left side followed by reconstruction of the defect with a superficial circumflex iliac artery-based iliac bone-free flap.
The initial biopsies revealed an exophytic-papillomatous (Fig. A), partly inverted tumor with squamous differentiation without unequivocal evidence of invasion. Based on the clinical context of a prior tooth extraction with persistent oro-antral fistula, differential diagnostic considerations encompassed prominent reactive inflammatory changes as well as an exophytic-papillomatous, well-differentiated carcinoma. Mucocytes were not detected in the Alcian-Blue-PAS-stain. Therefore, despite abundantly admixed granulocytes, a sinonasal papilloma (which could have aided the diagnosis as a possible precursor lesion) could not be confirmed. In light of the relatively mature squamous differentiation, minimal cytologic atypia and prominent inflammation, a clear diagnosis was hampered. In the second biopsy, small, discohesive collections of epithelial cells infiltrating the stroma with focal transformation into larger, basaloid aggregates without clear demarcation by a basement membrane, militated against the diagnosis of a reactive process (Fig. B–D). Additionally, the time course and clinico-radiological features favored a malignant process. The interpretation as a reactive squamous epithelial proliferation was revised with the descriptive diagnosis of an exophytic-papillomatous and partly endophytic growing carcinoma. In the ensuing external pathologic consultation, a diagnosis of a non-keratinizing squamous cell carcinoma (NKSCC) was rendered, assuming that the lesion originated from the sinonasal tract rather than the mucosa of the oral cavity, based on the latest WHO classification of Head & Neck Tumours 5th edition (beta version) . HPV DNA testing as well as EBV-RNA in situ hybridization and p16 immunohistochemistry were negative. In order to address the differential diagnosis of a DEK::AFF2 fusion-associated carcinoma, molecular profiling was performed using the FoundationOne ® Heme test. DEK::AFF2 fusion-associated carcinomas have been described recently as an emerging entity in the sinonasal tract, with the majority showing a strikingly bland histologic appearance and overlap with so-called low-grade papillary Schneiderian carcinomas . Importantly, the detection of a DEK::AFF2 gene fusion would allow for more accurate classification and prognostic assessment. Surprisingly, no DEK::AFF2 , but a NUT::NSD3 gene fusion was detected, leading to the diagnosis of a NUT carcinoma. A subsequently performed NUT immunohistochemistry (Fig. E) showed a matching “speckled type” positivity in the majority of the carcinoma cells (almost 100% in both, basaloid and more differentiated components), corroborating the diagnosis and visualizing the fusion product. In concordance with the morphology lacking mucocytes, no EGFR mutation was detected, which are very common in inverted sinonasal papilloma and their carcinoma ex papilloma . The macroscopy of the following left-sided hemimaxillectomy showed the main tumor originating in the maxillary sinus and breaking through the bone into the oral cavity. Together with the neck dissection specimen level I-III the final pathologic tumor staging (according to carcinomas of the nasal cavity and paranasal sinuses) was pT2 pN0 (0/57) L0 V0 Pn1, high-grade, R0 (UICC/TNM 8 th edition, 2017). Extensive perineural spread was noted.
Adjuvant local radiotherapy was recommended at our multidisciplinary tumorboard. One year after diagnosis and six months after completion of treatment (at the time of the case report submission), the patient showed no evidence of disease, neither clinically nor on PET/CT.
The histological and clinical features of the current case represent a highly unusual constellation. Typical NUT carcinoma is characterized by a more undifferentiated monomorphic morphology with small squamous islets and abrupt keratinization. These features were not present in our case. Nevertheless, the molecular profile, the NUT::NSD3 gene fusion, has been recurrently described in NUT carcinomas and confirms the diagnosis, especially in association with a squamous phenotype. Accordingly, this case can be regarded as part of the spectrum of NUT carcinomas and emphasizes the importance of considering this differential diagnosis in mature and well-differentiated squamous cell carcinoma. Such atypical features as well as the lack of awareness of this entity suggest an under-diagnosis and -reporting of NUT carcinomas . The partly prominent squamous epithelial differentiation and the growth pattern are highly unusual and to the best of our knowledge have not been described in NUT carcinomas. In this regard, NUT carcinomas are characterized by translocation-associated fusion oncoproteins that interfere with cell differentiation and cell growth. The majority of NUT-fusions involves BRD4 (bromodomain containing protein 4), leading to an epigenetically induced block of cell differentiation and promotion of cellular growth. NSD3 encodes a histone lysine methyltransferase that binds the extraterminal domain of BRD. In cases harboring the NUT::NSD3 fusion, this alteration probably leads to similar functional oncogenic consequences. However, as presented in this case, the level of interference with cell differentiation might be different in NUT::NSD3 fusion than in NUT::BRD4 fusion . This could explain why NUT::NSD3 fusion positive carcinomas outside the thorax appear to have a significantly better prognosis than their NUT::BRD4 positive counterparts . An additional diagnostic challenge are the reactive, inflammatory squamous epithelial changes, which can be prominent after an intervention such as a tooth extraction. The relatively young patient age and the unusual morphology led to the consideration of an HPV-associated carcinoma, which could not be substantiated, as immunohistochemistry for p16 and molecular analysis for HPV DNA were negative. A carcinoma with DEK::AFF2 gene fusion was considered as the primary differential diagnosis on morphologic grounds. These carcinomas have recently been described and exhibit similar morphologic features to the current case . Importantly, this case presented significant morphological overlap with other head and neck carcinomas. The NUT::NSD3 gene fusion has recently been described in a subset of thyroid carcinomas without classical features, so that there is a rationale for NUT immunohistochemistry and/or molecular testing in unusual cases. In particular, there is increasing evidence that NUT gene fusions can occur in tumors with different underlying cell types (other than squamoid-like cells), such as thyroid follicle cells. Additional data are needed for accurate classification of these increasingly detected neoplasms . The concept of tumoral-mucosal fusion as a potential pitfall of processes underlying the surface mucosa is recognized in minor salivary gland neoplasia . However, the observation that the majority of bland squamous cells in the mucosa were NUT IHC positive in our case, suggests that maturation may be involved. This case further demonstrates that highly sensitive and specific NUT immunohistochemistry is useful in identifying cases with unusual morphology, thus enabling accurate classification. Future studies on larger numbers of cases are needed for comparing the biological behavior and other features of “differentiated NUT carcinoma” with the classical type.
|
Development of an orally delivered GLP-1 receptor agonist through peptide engineering and drug delivery to treat chronic disease | 6e6b74dc-393f-4d66-97b5-e037f9c6bd93 | 8602401 | Pharmacology[mh] | Systemic and gastrointestinal stabilization of GLP-1 receptor agonists Protection against proteolysis in serum and the gastrointestinal tract To protect GLP-1 against both serum and gastrointestinal proteases, we modified the native peptide sequence by substituting in natural and α-methyl amino acids at predicted vulnerable sites (Fig. a). The aromatic residues Phe 12 , Tyr 19 , Phe 28 and Trp 31 are each targeted by chymotrypsin, pepsin and/or neprilysin, so were each replaced with α-methyl-L-phenylalanine (αMePhe). Introduction of αMePhe 12 imposed steric restraints that hindered synthesis, which we reduced by replacing Thr 11 with serine. A site of elastase vulnerability was removed by replacing Ser 17 with α-methyl-L-serine (αMeSer). The basic residues Lys 26 and Lys 34 in native GLP-1 are targeted by trypsin, so were replaced with α-methyl-L-lysine (αMeLys). Furthermore, Arg 36 was replaced with glycine to protect against tryptic cleavage. Protection against DPP-IV degradation was achieved by replacing Ala 8 with α-methyl-L-alanine (αMeAla), as previously described for semaglutide . To enhance aqueous solubility, Gln 23 was replaced with glutamic acid, which also removed the potential for deamidation. Finally, replacement of Leu 32 with valine provided a small but useful reduction in hydrophobicity that decreased proteolytic susceptibility of the Leu 32 -Val 33 motif. This process yielded the peptide analogue J211 (Fig. c). To lipidate J211 for improved circulating half-life, we initially adopted the same approach as used for semaglutide . Functionalizing J211 with Lys(Ɛ-(AEEA) 2 -γE-stearate) (C 18 lipid dicarboxylate) at position 26 yielded mono-lipidated J229 (Fig. d). The proteolytic stability of J229 was dramatically improved compared with semaglutide: over 80% of J229 remained intact after 2 h of incubation in fasted-state simulated intestinal fluid (FaSSIF)/pancreatin, whereas semaglutide was completely degraded in less than 20 min (Fig. a). However, the in vitro potency of J229 was compromised compared with semaglutide and native GLP-1, with half maximal effective concentration (EC 50 ) values of 132 pM versus 12 pM and 2.1 pM, respectively, in a cyclic adenosine monophosphate (cAMP) accumulation assay in Chinese hamster ovary (CHO) cells stably expressing human GLP-1R (Supplementary Fig. S1 and Table ). Bis-lipidation of a GLP-1RA We next scanned J211 for alternative lipidation sites to improve potency, and identified regions around αMePhe 19 and αMePhe 31 . These residues were replaced with side-chain functionalized lysine residues, and the previously lipidated Lys 26 was replaced with αMeLys. To reduce the number of α-methyl amino acids, αMeLys 34 was replaced with glutamic acid. Functionalization of substituted Lys 19 and Lys 31 residues with dodecanoic acid yielded MEDI7219 (Fig. e). The proteolytic stability of MEDI7219 in FaSSIF/pancreatin was dramatically improved compared with semaglutide; with over 60% remaining intact after 2 h (Fig. a). The in vitro potency of MEDI7219 was similar to semaglutide in the CHO cell cAMP accumulation assay in the presence of 0.1% bovine serum albumin (BSA), with low picomolar EC 50 values for both peptides (MEDI7219, 3.4 pM; semaglutide, 12 pM; Supplementary Fig. S1). As anticipated, the potency of these peptides was reduced when a physiological level of 4.4% human serum albumin (HSA) was used in the CHO cell assay (MEDI7219, 398 pM; semaglutide, 2630 pM; Supplementary Fig. S1), but the EC 50 difference between MEDI7219 and semaglutide was similar across assays. Potencies were comparable for both peptides when the assay was performed in the EndoC-βH1 human pancreatic β-cell line, which endogenously expresses GLP-1R (Supplementary Fig. S1). To confirm that bis-lipidation conferred a level of plasma protein binding expected to improve circulating half-life, we compared the peptides in an in vitro EScalate equilibrium shift assay. MEDI7219 and semaglutide both bound to human, dog, monkey and rat plasma proteins, with over 97% peptide bound in all cases. Higher unbound peptide proportions were observed for MEDI7219 than for semaglutide (Fig. b). Taken together, amino acid modification and bis-lipidation of MEDI7219 resulted in a proteolytically stable and potent peptide with bioactivity toward the GLP-1R in the presence of physiological HSA levels, supporting further development. Potency of subcutaneously administered bis-lipidated peptides Having confirmed the in vitro properties of MEDI7219, we assessed in vivo potency in mouse models following subcutaneous administration. Single doses of MEDI7219 dose-dependently reduced food intake over 24 h in lean C57Bl/6 J mice, with the high dose (3 nmol/kg) having comparable effects (–39.4%, P < 0.001) to an equivalent dose of semaglutide (Fig. a). Lower doses of MEDI7219 also reduced food intake (1 nmol/kg, –18.0%, P < 0.05; 0.3 nmol/kg, –12.6%). In the diet-induced obese (DIO) mouse model, MEDI7219 10 nmol/kg reduced body weight by 17.0% after 21 days, compared with an 18.7% reduction for semaglutide 10 nmol/kg and a 7.2% increase for placebo (Fig. b). Fasting glucose and insulin levels at day 14 were also reduced in DIO mice receiving once daily subcutaneous administration of MEDI7219 10 nmol/kg compared with placebo, and were similar to levels in mice receiving semaglutide 10 nmol/kg (Fig. c,d). In the diabetic db / db mouse model, MEDI7219 dose-dependently reduced glucose levels following once-daily subcutaneous administration for 28 days, with statistically significantly lower glucose levels at doses of 3–30 nmol/kg ( P < 0.001) than placebo (Fig. e). Significant reductions in glucose levels were observed as early as day 7 in mice receiving MEDI7219 10 nmol/kg or 30 nmol/kg. MEDI7219 also dose-dependently reduced HbA 1C levels compared with placebo ( P < 0.001 for doses 1–30 nmol/kg), with similar effects to those of semaglutide injected at doses of 3 nmol/kg and 30 nmol/kg (Fig. f). Selection of permeation enhancers for oral administration To optimize gastrointestinal absorption of our GLP-1 peptide analogues, we screened comprehensive panels of permeation enhancers (Supplementary Table ) in vitro using Caco-2 cell monolayers (Fig. a) and in vivo using intraduodenal administration in rats (Fig. b). These experiments used mono-lipidated J229 as a model peptide with physicochemical characteristics similar to those of the bis-lipidated lead peptide MEDI7219. The in vitro screen identified a novel combination of sodium chenodeoxycholate (NaCDC) and propyl gallate (PG) as the optimal permeation enhancers in the panel tested (Fig. a). In rats, the largest improvement in bioavailability following intraduodenal administration was with 50 mg/kg NaCDC and 25 mg/kg PG, among the panel tested. This combination increased bioavailability to a systemic fraction (%F) of 0.39 compared with 0.02 for J229 alone, at a dose of 1 mg/kg (Fig. b). Switching to MEDI7219, mean bioavailability was 13-fold higher than for semaglutide when administered intraduodenally with permeation enhancers in rats (%F, 1.01 vs 0.08) (Fig. c). Site of gastrointestinal absorption of stabilized GLP-1RA peptides in dogs We used IntelliCap controlled release capsules to determine the site of maximal gastrointestinal absorption of our stabilized GLP-1RAs in dogs. Capsules filled with J229 formulated with permeation enhancers were actuated at various pH-dependent points along the gastrointestinal tract following oral administration (Table ). Bioavailability of J229 was highest when released in the proximal colon (%F, 3.8) and the small intestine (%F, 2.2), but was low following oral gavage of the same liquid formulation used in the capsules (%F, 0.2). IntelliCap capsule transit times through each compartment of the gastrointestinal tract were recorded, and the effect of site of peptide release was investigated. When J229 was released in the small intestine, transit times through site of the release and through downstream compartments were slowed (Supplementary Table ). Therefore, we aimed to formulate MEDI7219 tablets for peptide delivery to sites of maximal absorption in the small intestine and proximal colon. Oral bioavailability of MEDI7219 tablets We formulated MEDI7219 as enteric-coated oral tablets containing 20 mg of peptide with 300 mg of permeation enhancers (100 mg of NaCDC and 200 mg of PG) for pharmacokinetic studies in dogs. The enteric coating was chosen to protect the tablet from the low pH of the stomach, and to release the drug by dissolution in the neutral pH of the intestine. For comparison, semaglutide was formulated as uncoated tablets containing 20 mg of peptide and 300 mg of SNAC permeation enhancer. After oral administration, the mean bioavailability of MEDI7219 was considerably higher than that of semaglutide (%F, 5.92 vs 0.08) and the mean plasma half-life of MEDI7219 was shorter than that of semaglutide (9.8 h vs 60.5 h) (Table ). These half-life values were consistent with the lower levels of in vitro plasma protein binding already observed for MEDI7219 compared with semaglutide (Fig. b). These findings confirmed pharmacokinetic parameters suitable for once-daily oral dosing of MEDI7219 in this tablet formulation. Effects of MEDI7219 oral tablets on weight and glucose control in a dog model of obesity and insulin resistance The potential anti-diabetic efficacy of MEDI7219 oral tablets was evaluated in dogs with obesity, insulin resistance and mild hyperglycemia induced by a high-fructose/high-fat (HFHF) diet , . Plasma glucose excursions were statistically significantly improved 10–40 min after an oral glucose challenge following single doses of MEDI7219 1 mg or 10 mg oral tablets, compared with placebo ( P < 0.05; Fig. a,b). Over 14 days, dogs receiving once-daily MEDI7219 10 mg oral tablets showed significantly higher body weight loss than those receiving placebo (–4.86% vs + 0.71%, P < 0.05; Fig. c). This correlated with significantly decreased cumulative food intake ( P < 0.05) over the 14-day period (Fig. d). An oral glucose tolerance test performed in fasted dogs postdose on day 14 also revealed significant improvements in glucose excursions in MEDI7219-treated dogs compared with placebo control ( P < 0.01; Fig. e). To investigate the potential effect of oral MEDI7219 on gastric emptying, a typical GLP-1R mediated effect , an oral dose of acetaminophen, which is absorbed in the small intestine , was administered during the glucose tolerance test in dogs on day 14. Peak plasma acetaminophen concentration was significantly reduced at 20–40 min ( P < 0.05) and delayed in the MEDI7219 group compared with the placebo group (Fig. f), indicating that MEDI7219 treatment led to a delay in gastric emptying.
Protection against proteolysis in serum and the gastrointestinal tract To protect GLP-1 against both serum and gastrointestinal proteases, we modified the native peptide sequence by substituting in natural and α-methyl amino acids at predicted vulnerable sites (Fig. a). The aromatic residues Phe 12 , Tyr 19 , Phe 28 and Trp 31 are each targeted by chymotrypsin, pepsin and/or neprilysin, so were each replaced with α-methyl-L-phenylalanine (αMePhe). Introduction of αMePhe 12 imposed steric restraints that hindered synthesis, which we reduced by replacing Thr 11 with serine. A site of elastase vulnerability was removed by replacing Ser 17 with α-methyl-L-serine (αMeSer). The basic residues Lys 26 and Lys 34 in native GLP-1 are targeted by trypsin, so were replaced with α-methyl-L-lysine (αMeLys). Furthermore, Arg 36 was replaced with glycine to protect against tryptic cleavage. Protection against DPP-IV degradation was achieved by replacing Ala 8 with α-methyl-L-alanine (αMeAla), as previously described for semaglutide . To enhance aqueous solubility, Gln 23 was replaced with glutamic acid, which also removed the potential for deamidation. Finally, replacement of Leu 32 with valine provided a small but useful reduction in hydrophobicity that decreased proteolytic susceptibility of the Leu 32 -Val 33 motif. This process yielded the peptide analogue J211 (Fig. c). To lipidate J211 for improved circulating half-life, we initially adopted the same approach as used for semaglutide . Functionalizing J211 with Lys(Ɛ-(AEEA) 2 -γE-stearate) (C 18 lipid dicarboxylate) at position 26 yielded mono-lipidated J229 (Fig. d). The proteolytic stability of J229 was dramatically improved compared with semaglutide: over 80% of J229 remained intact after 2 h of incubation in fasted-state simulated intestinal fluid (FaSSIF)/pancreatin, whereas semaglutide was completely degraded in less than 20 min (Fig. a). However, the in vitro potency of J229 was compromised compared with semaglutide and native GLP-1, with half maximal effective concentration (EC 50 ) values of 132 pM versus 12 pM and 2.1 pM, respectively, in a cyclic adenosine monophosphate (cAMP) accumulation assay in Chinese hamster ovary (CHO) cells stably expressing human GLP-1R (Supplementary Fig. S1 and Table ). Bis-lipidation of a GLP-1RA We next scanned J211 for alternative lipidation sites to improve potency, and identified regions around αMePhe 19 and αMePhe 31 . These residues were replaced with side-chain functionalized lysine residues, and the previously lipidated Lys 26 was replaced with αMeLys. To reduce the number of α-methyl amino acids, αMeLys 34 was replaced with glutamic acid. Functionalization of substituted Lys 19 and Lys 31 residues with dodecanoic acid yielded MEDI7219 (Fig. e). The proteolytic stability of MEDI7219 in FaSSIF/pancreatin was dramatically improved compared with semaglutide; with over 60% remaining intact after 2 h (Fig. a). The in vitro potency of MEDI7219 was similar to semaglutide in the CHO cell cAMP accumulation assay in the presence of 0.1% bovine serum albumin (BSA), with low picomolar EC 50 values for both peptides (MEDI7219, 3.4 pM; semaglutide, 12 pM; Supplementary Fig. S1). As anticipated, the potency of these peptides was reduced when a physiological level of 4.4% human serum albumin (HSA) was used in the CHO cell assay (MEDI7219, 398 pM; semaglutide, 2630 pM; Supplementary Fig. S1), but the EC 50 difference between MEDI7219 and semaglutide was similar across assays. Potencies were comparable for both peptides when the assay was performed in the EndoC-βH1 human pancreatic β-cell line, which endogenously expresses GLP-1R (Supplementary Fig. S1). To confirm that bis-lipidation conferred a level of plasma protein binding expected to improve circulating half-life, we compared the peptides in an in vitro EScalate equilibrium shift assay. MEDI7219 and semaglutide both bound to human, dog, monkey and rat plasma proteins, with over 97% peptide bound in all cases. Higher unbound peptide proportions were observed for MEDI7219 than for semaglutide (Fig. b). Taken together, amino acid modification and bis-lipidation of MEDI7219 resulted in a proteolytically stable and potent peptide with bioactivity toward the GLP-1R in the presence of physiological HSA levels, supporting further development. Potency of subcutaneously administered bis-lipidated peptides Having confirmed the in vitro properties of MEDI7219, we assessed in vivo potency in mouse models following subcutaneous administration. Single doses of MEDI7219 dose-dependently reduced food intake over 24 h in lean C57Bl/6 J mice, with the high dose (3 nmol/kg) having comparable effects (–39.4%, P < 0.001) to an equivalent dose of semaglutide (Fig. a). Lower doses of MEDI7219 also reduced food intake (1 nmol/kg, –18.0%, P < 0.05; 0.3 nmol/kg, –12.6%). In the diet-induced obese (DIO) mouse model, MEDI7219 10 nmol/kg reduced body weight by 17.0% after 21 days, compared with an 18.7% reduction for semaglutide 10 nmol/kg and a 7.2% increase for placebo (Fig. b). Fasting glucose and insulin levels at day 14 were also reduced in DIO mice receiving once daily subcutaneous administration of MEDI7219 10 nmol/kg compared with placebo, and were similar to levels in mice receiving semaglutide 10 nmol/kg (Fig. c,d). In the diabetic db / db mouse model, MEDI7219 dose-dependently reduced glucose levels following once-daily subcutaneous administration for 28 days, with statistically significantly lower glucose levels at doses of 3–30 nmol/kg ( P < 0.001) than placebo (Fig. e). Significant reductions in glucose levels were observed as early as day 7 in mice receiving MEDI7219 10 nmol/kg or 30 nmol/kg. MEDI7219 also dose-dependently reduced HbA 1C levels compared with placebo ( P < 0.001 for doses 1–30 nmol/kg), with similar effects to those of semaglutide injected at doses of 3 nmol/kg and 30 nmol/kg (Fig. f).
To protect GLP-1 against both serum and gastrointestinal proteases, we modified the native peptide sequence by substituting in natural and α-methyl amino acids at predicted vulnerable sites (Fig. a). The aromatic residues Phe 12 , Tyr 19 , Phe 28 and Trp 31 are each targeted by chymotrypsin, pepsin and/or neprilysin, so were each replaced with α-methyl-L-phenylalanine (αMePhe). Introduction of αMePhe 12 imposed steric restraints that hindered synthesis, which we reduced by replacing Thr 11 with serine. A site of elastase vulnerability was removed by replacing Ser 17 with α-methyl-L-serine (αMeSer). The basic residues Lys 26 and Lys 34 in native GLP-1 are targeted by trypsin, so were replaced with α-methyl-L-lysine (αMeLys). Furthermore, Arg 36 was replaced with glycine to protect against tryptic cleavage. Protection against DPP-IV degradation was achieved by replacing Ala 8 with α-methyl-L-alanine (αMeAla), as previously described for semaglutide . To enhance aqueous solubility, Gln 23 was replaced with glutamic acid, which also removed the potential for deamidation. Finally, replacement of Leu 32 with valine provided a small but useful reduction in hydrophobicity that decreased proteolytic susceptibility of the Leu 32 -Val 33 motif. This process yielded the peptide analogue J211 (Fig. c). To lipidate J211 for improved circulating half-life, we initially adopted the same approach as used for semaglutide . Functionalizing J211 with Lys(Ɛ-(AEEA) 2 -γE-stearate) (C 18 lipid dicarboxylate) at position 26 yielded mono-lipidated J229 (Fig. d). The proteolytic stability of J229 was dramatically improved compared with semaglutide: over 80% of J229 remained intact after 2 h of incubation in fasted-state simulated intestinal fluid (FaSSIF)/pancreatin, whereas semaglutide was completely degraded in less than 20 min (Fig. a). However, the in vitro potency of J229 was compromised compared with semaglutide and native GLP-1, with half maximal effective concentration (EC 50 ) values of 132 pM versus 12 pM and 2.1 pM, respectively, in a cyclic adenosine monophosphate (cAMP) accumulation assay in Chinese hamster ovary (CHO) cells stably expressing human GLP-1R (Supplementary Fig. S1 and Table ).
We next scanned J211 for alternative lipidation sites to improve potency, and identified regions around αMePhe 19 and αMePhe 31 . These residues were replaced with side-chain functionalized lysine residues, and the previously lipidated Lys 26 was replaced with αMeLys. To reduce the number of α-methyl amino acids, αMeLys 34 was replaced with glutamic acid. Functionalization of substituted Lys 19 and Lys 31 residues with dodecanoic acid yielded MEDI7219 (Fig. e). The proteolytic stability of MEDI7219 in FaSSIF/pancreatin was dramatically improved compared with semaglutide; with over 60% remaining intact after 2 h (Fig. a). The in vitro potency of MEDI7219 was similar to semaglutide in the CHO cell cAMP accumulation assay in the presence of 0.1% bovine serum albumin (BSA), with low picomolar EC 50 values for both peptides (MEDI7219, 3.4 pM; semaglutide, 12 pM; Supplementary Fig. S1). As anticipated, the potency of these peptides was reduced when a physiological level of 4.4% human serum albumin (HSA) was used in the CHO cell assay (MEDI7219, 398 pM; semaglutide, 2630 pM; Supplementary Fig. S1), but the EC 50 difference between MEDI7219 and semaglutide was similar across assays. Potencies were comparable for both peptides when the assay was performed in the EndoC-βH1 human pancreatic β-cell line, which endogenously expresses GLP-1R (Supplementary Fig. S1). To confirm that bis-lipidation conferred a level of plasma protein binding expected to improve circulating half-life, we compared the peptides in an in vitro EScalate equilibrium shift assay. MEDI7219 and semaglutide both bound to human, dog, monkey and rat plasma proteins, with over 97% peptide bound in all cases. Higher unbound peptide proportions were observed for MEDI7219 than for semaglutide (Fig. b). Taken together, amino acid modification and bis-lipidation of MEDI7219 resulted in a proteolytically stable and potent peptide with bioactivity toward the GLP-1R in the presence of physiological HSA levels, supporting further development.
Having confirmed the in vitro properties of MEDI7219, we assessed in vivo potency in mouse models following subcutaneous administration. Single doses of MEDI7219 dose-dependently reduced food intake over 24 h in lean C57Bl/6 J mice, with the high dose (3 nmol/kg) having comparable effects (–39.4%, P < 0.001) to an equivalent dose of semaglutide (Fig. a). Lower doses of MEDI7219 also reduced food intake (1 nmol/kg, –18.0%, P < 0.05; 0.3 nmol/kg, –12.6%). In the diet-induced obese (DIO) mouse model, MEDI7219 10 nmol/kg reduced body weight by 17.0% after 21 days, compared with an 18.7% reduction for semaglutide 10 nmol/kg and a 7.2% increase for placebo (Fig. b). Fasting glucose and insulin levels at day 14 were also reduced in DIO mice receiving once daily subcutaneous administration of MEDI7219 10 nmol/kg compared with placebo, and were similar to levels in mice receiving semaglutide 10 nmol/kg (Fig. c,d). In the diabetic db / db mouse model, MEDI7219 dose-dependently reduced glucose levels following once-daily subcutaneous administration for 28 days, with statistically significantly lower glucose levels at doses of 3–30 nmol/kg ( P < 0.001) than placebo (Fig. e). Significant reductions in glucose levels were observed as early as day 7 in mice receiving MEDI7219 10 nmol/kg or 30 nmol/kg. MEDI7219 also dose-dependently reduced HbA 1C levels compared with placebo ( P < 0.001 for doses 1–30 nmol/kg), with similar effects to those of semaglutide injected at doses of 3 nmol/kg and 30 nmol/kg (Fig. f).
To optimize gastrointestinal absorption of our GLP-1 peptide analogues, we screened comprehensive panels of permeation enhancers (Supplementary Table ) in vitro using Caco-2 cell monolayers (Fig. a) and in vivo using intraduodenal administration in rats (Fig. b). These experiments used mono-lipidated J229 as a model peptide with physicochemical characteristics similar to those of the bis-lipidated lead peptide MEDI7219. The in vitro screen identified a novel combination of sodium chenodeoxycholate (NaCDC) and propyl gallate (PG) as the optimal permeation enhancers in the panel tested (Fig. a). In rats, the largest improvement in bioavailability following intraduodenal administration was with 50 mg/kg NaCDC and 25 mg/kg PG, among the panel tested. This combination increased bioavailability to a systemic fraction (%F) of 0.39 compared with 0.02 for J229 alone, at a dose of 1 mg/kg (Fig. b). Switching to MEDI7219, mean bioavailability was 13-fold higher than for semaglutide when administered intraduodenally with permeation enhancers in rats (%F, 1.01 vs 0.08) (Fig. c).
We used IntelliCap controlled release capsules to determine the site of maximal gastrointestinal absorption of our stabilized GLP-1RAs in dogs. Capsules filled with J229 formulated with permeation enhancers were actuated at various pH-dependent points along the gastrointestinal tract following oral administration (Table ). Bioavailability of J229 was highest when released in the proximal colon (%F, 3.8) and the small intestine (%F, 2.2), but was low following oral gavage of the same liquid formulation used in the capsules (%F, 0.2). IntelliCap capsule transit times through each compartment of the gastrointestinal tract were recorded, and the effect of site of peptide release was investigated. When J229 was released in the small intestine, transit times through site of the release and through downstream compartments were slowed (Supplementary Table ). Therefore, we aimed to formulate MEDI7219 tablets for peptide delivery to sites of maximal absorption in the small intestine and proximal colon.
We formulated MEDI7219 as enteric-coated oral tablets containing 20 mg of peptide with 300 mg of permeation enhancers (100 mg of NaCDC and 200 mg of PG) for pharmacokinetic studies in dogs. The enteric coating was chosen to protect the tablet from the low pH of the stomach, and to release the drug by dissolution in the neutral pH of the intestine. For comparison, semaglutide was formulated as uncoated tablets containing 20 mg of peptide and 300 mg of SNAC permeation enhancer. After oral administration, the mean bioavailability of MEDI7219 was considerably higher than that of semaglutide (%F, 5.92 vs 0.08) and the mean plasma half-life of MEDI7219 was shorter than that of semaglutide (9.8 h vs 60.5 h) (Table ). These half-life values were consistent with the lower levels of in vitro plasma protein binding already observed for MEDI7219 compared with semaglutide (Fig. b). These findings confirmed pharmacokinetic parameters suitable for once-daily oral dosing of MEDI7219 in this tablet formulation.
The potential anti-diabetic efficacy of MEDI7219 oral tablets was evaluated in dogs with obesity, insulin resistance and mild hyperglycemia induced by a high-fructose/high-fat (HFHF) diet , . Plasma glucose excursions were statistically significantly improved 10–40 min after an oral glucose challenge following single doses of MEDI7219 1 mg or 10 mg oral tablets, compared with placebo ( P < 0.05; Fig. a,b). Over 14 days, dogs receiving once-daily MEDI7219 10 mg oral tablets showed significantly higher body weight loss than those receiving placebo (–4.86% vs + 0.71%, P < 0.05; Fig. c). This correlated with significantly decreased cumulative food intake ( P < 0.05) over the 14-day period (Fig. d). An oral glucose tolerance test performed in fasted dogs postdose on day 14 also revealed significant improvements in glucose excursions in MEDI7219-treated dogs compared with placebo control ( P < 0.01; Fig. e). To investigate the potential effect of oral MEDI7219 on gastric emptying, a typical GLP-1R mediated effect , an oral dose of acetaminophen, which is absorbed in the small intestine , was administered during the glucose tolerance test in dogs on day 14. Peak plasma acetaminophen concentration was significantly reduced at 20–40 min ( P < 0.05) and delayed in the MEDI7219 group compared with the placebo group (Fig. f), indicating that MEDI7219 treatment led to a delay in gastric emptying.
Oral delivery of peptide therapeutics represents a significant advance in the ability to administer medicines in a convenient and patient-friendly way, with the potential to improve adherence and consequently treatment outcomes. Overcoming the challenges of proteolytic degradation, gastrointestinal permeability, and rapid renal clearance to ensure high bioavailability, whilst maintaining biological function, requires a rational design process. We have presented a template for this process using a systematic multidisciplinary approach to develop a novel GLP-1RA peptide therapeutic that exhibited potent agonism, a circulating half-life suitable for once-daily dosing and significant oral bioavailability. The improved absolute oral bioavailability of MEDI7219, ~ 6% in dogs, was achieved without compromising potency by stepwise engineering based on structure–activity relationships. The rational approach in the design and development of MEDI7219, starting with engineering the peptide to remove sites of vulnerability to both serum and gastrointestinal proteases through amino acid substitution, contrasts with previous approaches to oral peptide delivery, which have relied on retrofitting injectables to the oral route without stabilizing peptide sequences against gastrointestinal proteases. Furthermore, enteric-coated MEDI7219 tablets were designed to withstand transit through the stomach releasing the peptide at the site of maximal absorption in the small intestine, which was identified with the use of the IntelliCap system. Taken together, the extensive screening identified an effective combination of permeation enhancers that greatly improved the inherently low uptake of a peptide from the gastrointestinal tract, resulting in high oral bioavailability (~ 6%) of MEDI7219 in dogs. MEDI7219 is the first bis-lipidated GLP-1RA peptide, and this bis-lipidation approach was crucial for promoting plasma protein binding to reduce renal clearance without sacrificing agonist activity, while minimizing the use of α-methyl amino acids to stabilize the molecule. The pair of C 12 lipids in MEDI7219 conferred a shorter circulating half-life than the single C 18 lipid dicarboxylic acid in semaglutide when tested in dogs. This correlated to plasma protein binding data, in which a higher fraction of unbound MEDI7219 than semaglutide was observed for plasma proteins of all species tested. Although the half-life of MEDI7219 is shorter than that of semaglutide in dogs, allometric scaling (Supplementary Fig. S2) supports once-daily dosing in humans (t ½ 15 h). In a dog model of obesity and insulin resistance, once-daily administration of MEDI7219 oral tablets led to both decreased glucose excursion, when challenged with an oral glucose bolus, and body weight loss, consistent with the action of other GLP-1RA peptide therapeutics , . Administration of acetaminophen during the oral glucose challenge indicated that MEDI7219 delayed gastric emptying, as expected with GLP-1R agonism – , and this also probably contributed to the decreased glucose levels. These findings confirmed that we achieved a preclinical efficacy profile for MEDI7219 supportive of progression to clinical trials. The average bioavailability of MEDI7219 was approximately fivefold higher than the published value for semaglutide in dogs (%F, 5.92 vs 1.22) . We observed lower semaglutide bioavailability with our in-house tablets than published values, resulting in an even greater magnitude of improvement in bioavailability for MEDI7219. This suggests that some methodological differences in the manufacture of oral semaglutide tablets may have led to lower bioavailability than that reported in previously published data. Nevertheless, our results confirm a dramatic and unprecedented high oral bioavailability for MEDI7219 compared with other linear peptide therapeutics. The dog model used to test the activity of MEDI7219 had advantages for the in vivo characterization because it allowed for oral administration of tablets, which is not possible in rodents. In addition, because dogs gained excess body weight on a high-fat diet and became insulin resistant, it was possible to ascertain GLP-1R-mediated pharmacological effects in the model following repeated oral dosing. Pharmacokinetic parameters are influenced by characteristics such as gastrointestinal barriers and plasma protein binding, and may vary among species. Furthermore, interspecies physiological differences, such as gastrointestinal pH values and transit time, may also affect formulation performance. Bioavailability variability was ~ 50% coefficient of variation in the well-controlled dog study but may be different in a clinical population, potentially affecting the therapeutic window. Therefore, it is crucial to consider potential translational difference when moving from dog to human studies, and to monitor these concerns closely in the clinical setting. In conclusion, here we demonstrate the very first peptide synthesized by biotechnology routes to address the intrinsic limitation of oral peptide delivery and first pass effects. Our data demonstrated reasonable bioavailability in preclinical models and therefore a very robust approach when coupled with the site of absorption and controlled drug delivery. Our systematic multidisciplinary approach for engineering a novel oral GLP-1RA offers a valuable model for the development of future oral peptide therapeutics for diabetes and other chronic conditions. This has the potential to make these peptides more accessible to patients worldwide, with the opportunity for improved patient adherence and hence reduced hospitalization or other side effects resulting from non-compliance. We leveraged advances in peptide chemistry and solid dosage formulation to develop a once-daily oral tablet GLP-1RA with high bioavailability, and demonstrated efficacy in a preclinical model of insulin resistance and obesity. Our findings warrant clinical studies of MEDI7219 to confirm translatability of observed bioavailability and pharmacology from dogs to humans.
In vivo studies The development program involved peptide optimization using in vitro models, and in vivo potency testing in mouse models and formulation testing using rat models. Methods are reported in accordance with the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines. Animal studies were conducted at AstraZeneca (Gaithersburg, MD, USA or Cambridge, UK), Charles River Laboratories (Shrewsbury, Wilmington or Worcester, MA; Mattawan, MI, USA) or Covance Laboratories (Madison, WI, USA). The study was conducted in accordance with the Animals (Scientific Procedures) Act 1986, under a Project Licence reviewed by the establishment Animal Welfare and Ethical Review Body (AWERB) and granted by the UK Home Office. Study protocols were approved by the Institutional Animal Care and Use Committee at AstraZeneca (Gaithersburg, MD, USA), Charles River Laboratories (Shrewsbury, Wilmington or Worcester, MA; Mattawan, MI) or Covance Laboratories (Madison, WI, USA), and were in compliance with national laws and regulations ensuring humane use and care of laboratory animals and the AstraZeneca Animal Welfare and Bioethics policies. In vivo studies were not blinded, confounders were not controlled for, and no criteria were set for including or excluding animals or data points from analyses. Systemic and gastrointestinal stabilization of GLP-1 receptor agonists Amino acid substitution and lipidation N -α-Fmoc-L-amino acids were from Bachem (Bubendorf, Switzerland), and α-methyl and other unnatural amino acids were from Iris Biotech (Marktredwitz, Germany), Pharmaron (Beijing, China) or PepTech (Burlington, MA, USA); solvents were from Merck (Darmstadt, Germany). Peptides J211, J229 and MEDI7219 (Fig. ) were prepared as C-terminal carboxamides on Novabiochem NovaSyn TentaGel Rink (Merck) synthesis resin using standard chemistry and coupling procedures , and reagents from Sigma-Aldrich (Gillingham, UK). Amino acids following α-methyl residues were coupled twice to ensure full incorporation. The N -terminal histidine residue of GLP-1 was incorporated as Boc-His(Trt)-OH to simplify peptide cleavage. At designated lipidation positions, Fmoc-L-Lys(Mmt)-OH was incorporated into the peptide backbone during automated assembly and the Mmt protecting groups were removed upon completion. The acidified resin was quenched, and the exposed epsilon amino functions were selectively lipidated as required before peptide cleavage. Crude peptides were purified chromatographically using 5 µm Agilent Polaris C8-A (mono-lipidated; Agilent, Santa Clara, CA, USA) or Waters XBridge C18 stationary phases (bis-lipidated; Waters, Antwerp, Belgium), and lyophilized. Purified peptides were characterized by single quadrupole liquid chromatography/mass spectrometry (LC/MS) with a Waters XBridge C18 stationary phase, using a generic linear binary gradient of 10–90% methyl cyanide (MeCN; 0.1% trifluoroacetic acid [TFA] v/v) in water and the Waters MassLynx 3100 platform (ESI + mode, monitoring 3 M + H and 4 M + H ions) to verify molecular mass. Analytical reverse-phase high-performance liquid chromatography (RP-HPLC) was conducted using an Agilent Polaris C8-A stationary phase (3 µm) at 1.5 mL min -1 with a linear binary gradient of 10–90% MeCN (0.1% TFA v/v) in water, and monitored by UV absorption at 210 nm. Overall yields of J211, J229 and MEDI7219 were greater than 50% based on initial resin functionalisation (0.24 mmol/g). Mass spectrometry data for all three peptides was consistent with calculated values (given below). J211 Requires: 3228.60 Da: 2 M +2 = 1615.30, 3 M +3 = 1077.20, 4 M +4 = 808.15 Found: 2 M +2 = 1615.55, 3 M +3 = 1077.15, 4 M +4 = 808.10 J229 Requires: 3930.45 Da: 2 M +2 = 1966.23, 3 M +3 = 1311.15, 4 M +4 = 983.61 Found: 2 M +2 = 1966.34, 3 M +3 = 1311.25, 4 M +4 = 983.75 MEDI7219 Requires: 4352.99 Da: 3 M +3 = 1451.99, 4 M +4 = 1089.25 Found: 3 M +3 = 1451.89, 4 M +4 = 1089.28 See Supplementary data for additional LC/MS information. Fasted-state simulated intestinal fluid/pancreatin assay Fresh FaSSIF and USP Pancreatin (FaSSIF/p; Sigma-Aldrich) was prepared according to Galia et al . and used immediately. Peptides were dissolved in pre-warmed FaSSIF before addition of pre-warmed FaSSIF/pancreatin with agitation. Samples were analyzed by analytical RP-HPLC to determine remaining intact peptide by area under the curve. EScalate equilibrium shift assay Binding of peptides to human plasma proteins was determined by the EScalate equilibrium shift assay (Sovicell, Leipzig, Germany), using five dilutions of plasma in phosphate buffered saline and an assumed binding protein concentration of 600 µM. Samples were incubated for 1 h at room temperature then centrifuged to remove the HSA-coated beads. Supernatant samples were analyzed using HPLC (3 µm Phenomenex Aeris Widepore XB-C18 stationary phase) coupled to an electrospray ionization quadrupole time-of-flight mass spectrometer in high resolution accurate mass mode (Agilent, Santa Clara, CA, USA). Unbound fractions were calculated from the concentration-dependent shift in binding equilibrium according to [12pt]{minimal}
$${f}_{u}=_{D}^{Plasma}}}$$ f u = 1 1 + P K D Plasma , where [12pt]{minimal}
$$P$$ P is the concentration of the binding protein in plasma and [12pt]{minimal}
$${K}_{D}^{Plasma}$$ K D Plasma is the dissociation constant of the compound from plasma proteins in solution. Cyclic adenosine monophosphate accumulation assay All reagents for cAMP assays were obtained from Sigma-Aldrich unless otherwise specified. CHO-K1 cells (ATCC) were stably transfected with a human GLP-1R expression plasmid and maintained in Dulbecco’s Modified Eagle Medium, 10% fetal bovine serum, 500 μg/mL geneticin and 400 μg/mL hygromycin B. Human EndoC-βH1 cells were kindly provided by Professor Raphael Scharfmann (Endocells, Paris, France), and were maintained in Dulbecco’s Modified Eagle Medium (low glucose), 2% BSA fraction V (Roche Diagnostics, Basel, Switzerland), 50 µM 2-mercaptoethanol, 10 mM nicotinamide, 5.5 µg/mL transferrin and 6.7 ng/mL sodium selenite. Peptide serial dilutions were prepared in assay buffer (Hank’s Balanced Salt Solution [HBSS] containing 25 mM HEPES and 0.5 mM IBMX; pH 7.4) supplemented with 0.1% BSA or 4.4% HSA, using an Echo 550 acoustic liquid handler (Labcyte Inc., Sunnyvale, CA, USA) to obtain an 11-point concentration–response curve. Cells were suspended in assay buffer and combined with serially diluted peptides at room temperature for 30 min. cAMP levels were measured using a cAMP dynamic 2 HTRF kit (Cisbio, Codolet, France), following the manufacturer’s two-step protocol, on an EnVision plate reader (PerkinElmer, Waltham, MA, USA). Data were transformed to % Delta F, as described in the manufacturer’s guidelines, and expressed as % activation, in which 80 nM native GLP-1 peptide (Bachem) defines maximum effect. The transformed data were analyzed by four-parameter logistic fit to determine EC 50 values using GraphPad Prism 6 (GraphPad Software, San Diego, CA, USA). In vivo potency of subcutaneously administered bis-lipidated peptides Acute food intake in C57Bl/6J mice Male C57Bl/6 J mice 8–10 weeks of age (Jackson Laboratories, Bar Harbor, ME, USA) were single-housed in the BioDAQ (Research Diets, New Brunswick, NJ, USA) food monitoring system with ad libitum access to standard chow and water. Mice were randomized into groups of 6–9 per group on baseline 24-h food intake. On the first study day, mice were fasted for 6 h and then received a single subcutaneous dose of test peptide or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0). Food intake was monitored over the next 48 h. Body weight, blood glucose and plasma insulin in diet-induced obese mouse model Male 20-week-old C57Bl/6 J mice were single-housed for approximately 14 weeks with ad libitum access to water and 60% high-fat diet (D12492, Research Diets). Mice were randomized into groups of 12 mice per group on baseline body weight, 6 h fasting glucose and 6 h fasting insulin. Over 21 days, mice received daily subcutaneous injections of 10 nmol/kg of test peptides or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0). Body weight was measured daily and fasting glucose and insulin levels were measured on day 14 following a 6-h fast. Blood was collected via tail-snip and glucose was measured with an Ascensia Breeze 2 glucometer (Bayer, Mishawaka, IN, USA). Insulin was measured in plasma using a Meso Scale rat/insulin kit (Meso Scale Discovery, Rockville, MD, USA). Dose–response study of MEDI7219 in diabetic db/db mouse model Male 7-week-old db / db mice (Charles River, Bristol, UK) were group-housed with ad libitum access to standard chow and water. Mice were randomized to groups of nine mice per group on baseline body weight, HbA 1C and 4-h fasting glucose (assessed in tail bleed samples using a Cobas c-111 analyzer [Roche Diagnostics, Indianapolis, IN, USA] and Nova StatStrip Xpress glucometer [DSI, St. Paul, MN, USA]). Insulin was measured in plasma from tail bleeds using a Meso Scale kit. Over 28 days, mice received daily subcutaneous doses of test peptides or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0). Selection of permeation enhancers for oral administration Caco-2 screen Caco-2 cells were trypsinized, suspended in medium and seeded to wells of a Millipore 96-well plate following standard procedures . Cells were fed at 2-day intervals for 3 weeks until a transepithelial electric resistance of ~ 1000 ohms/cm 2 was achieved. Test samples containing peptide and permeation enhancers (Supplementary Table ) were prepared in HBSS solution (pH 7.4). Lucifer Yellow and atenolol were added to the test samples as internal controls. The cells were incubated for 3 h with test samples on the apical side and blank media on the basolateral side. Media from the apical and basolateral sides were collected after 3 h and peptide content was evaluated . Data are expressed as apparent permeability (Papp): [12pt]{minimal}
$$Papp= _{0})}$$ P a p p = dQ dt · 1 A · C 0 where [12pt]{minimal}
$$dQ/dt$$ d Q / d t is the rate of permeation, [12pt]{minimal}
$${C}_{0}$$ C 0 is the initial concentration of test agent, and [12pt]{minimal}
$$A$$ A is the area of the monolayer. Oral bioavailability of GLP-1RAs with permeation enhancers in vivo Male Sprague Dawley rats (Charles River, Shrewsbury, MA, USA) weighing 250–275 g were housed with ad libitum access to standard chow and water. Test peptides were administered via either an intravenous or a duodenal catheter (4 rats per group) after overnight fasting, and food was returned following 4 h blood collection. Blood was collected via a jugular vein catheter at − 5, 15 and 30 min and 1, 2, 4, 8 and 24 h after intravenous dosing, or for intraduodenal groups at 15 min predose and 0.5, 1, 2, 4, 8, 24 and 48 h postdose. Blood was collected in K 2 EDTA tubes and kept on wet ice prior to 10 min centrifugation (3000 × g ) at 5 °C ± 3 °C. Plasma samples were stored at − 70 °C until analysis. Site of gastrointestinal absorption of stabilized GLP-1RA peptides in dogs Fasted male beagle dogs weighing 6–8 kg were pretreated with pentagastrin 6 μg/kg. After 30 min, dogs (5 per group) were administered with either: IntelliCap capsules (Medimetrics, Eindhoven, Netherlands) filled with 0.7 mL of peptide and permeation enhancer solution (J229 8 mg/mL, NaCDC 12 mg/mL); 0.7 mL equivalent oral gavage and 20 mL gavage rinse; J229 0.1 mg/mL intravenous injection; or 0.1 mg/mL subcutaneous injection. Blood was collected at 0.25, 0.5, 1, 2, 4, 8, 24 and 48 h for subcutaneous and oral gavage groups. Blood was collected at 0.083, 0.25, 0.5, 1, 2, 4, 8 and 24 h for the intravenous group. Blood collection in IntelliCap groups started after actuation of capsule content release. Blood was collected from the jugular vein in K 2 EDTA tubes and kept on wet ice. Plasma samples were stored at − 60 °C to − 90 °C until analysis. Oral bioavailability of MEDI7219 tablets Oral tablet formulation Tablets contained 0.5–10 mg of MEDI7219, 150 mg of permeation enhancers (50 mg NaCDC [Prodotti, Basaluzzo, Italy] and 100 mg PG [Guangzhou Hanfang Pharmaceutical, Guangzhou, China]), mannitol (Roquette, Keokuk, IA, USA) as filler, crospovidone (BASF, Ludwigshafen, Germany) as disintegrant, sodium stearyl fumarate (JRS Pharma, Rosenberg, Germany) as lubricant and hydrophobic fumed silica (Evonik, Parsippany, NJ, USA) as glidant, with a total weight of 245 mg per tablet. Placebo tablets were identical to active tablets, except for the absence of test peptide. Tablets were made by: sieving ingredients; blending in a Turbula mixer (WAB, Muttenz, Switzerland); dry granulation by compression in a pellet machine (Parr Instrument, Moline, IL, USA) and sieving (1 mm); blending with lubricant and glidant in a Turbula mixer; and compression at 50 N hardness on an NP-RD10 tablet press (Natoli, St Charles MO, USA). Finally, tablets were enteric coated with Eudragit polymer suspension (Evonik, Darmstadt, Germany) to achieve a 12.5% weight gain using a Vector LDCS3 pan coater (Freund-Vector, Marion, IA, USA). Oral bioavailability of MEDI7219 in dogs Fasted male beagle dogs weighing 8–13 kg (5 per group) were administered with enteric-coated oral tablets containing 10 mg test peptide and 300 mg permeation enhancers were administered. Blood samples were collected at 0.5, 0.5, 1, 1.5, 2, 2.5, 3.5, 4.5, 8, 24 and 48 h postdose. Effect of MEDI7219 oral tablets on weight and glucose control in a dog model of obesity and insulin resistance Eighteen male beagle dogs weighing an average of 10.9 ± 0.3 kg were housed at Charles River Laboratories (Worcester, MA, USA) and received two cups of 5A4J HFHF canine diet daily (20.5% protein, 52.9% fat, 26.6% carbohydrate, 18.9% fructose; ScottPharma Solutions, Marlborough, MA, USA) plus water ad libitum . For the single-dose study, dogs were randomized on baseline glucose levels to receive MEDI7219 1 mg or 10 mg or placebo tablets in the morning following an overnight fast (7–11 dogs per group). Ninety minutes after tablet administration, dogs received an oral glucose bolus (200 mg/mL at a 5 mL/kg volume calculated on body weight prior to HFHF feeding), and blood glucose (blood collected via peripheral vein) was measured with an AlphaTRAK glucometer system (Zoetis, Parsippany, NJ, USA) at –90, 0, 10, 20, 30, 40, 50, 60, 75, 90, 120, 180 and 240 min after glucose administration. Approximately 12 weeks later, dogs entered the multiple-dose study and received either MEDI7219 10 mg (n = 12) or placebo tablets (n = 6) once daily for 14 days. Dogs received two cups of HFHF canine diet per day, with feeding 3 h postdose during the 14-day study. Dogs had access to water ad libitum throughout the study. Food intake and body weight were monitored daily. On day 14, after overnight fasting, dogs received their final dose followed by an oral glucose and acetaminophen bolus 90 min after administration. Blood glucose was measured as described previously, and plasma acetaminophen levels were measured by LC/MS method at the same time points. Quantification of plasma concentrations of peptides Fifty or seventy μL aliquots of K 2 EDTA plasma samples were precipitated with 75% acetonitrile (Sigma-Aldrich) in water (J.T. Baker, Phillipsburg, NJ, USA) (v/v) and centrifuged at 2000 × g . The supernatant was dried under nitrogen at 60 °C, then cooled. Samples were reconstituted in 20% acetonitrile in water (v/v). The extracted samples were separated using a Waters Acquity UPLC BEH C18 column (2.1 × 100 mm) on a Shimadzu Nexera UHPLC at 60 °C with 0.7 mL/min flow rate, and detected using a SCIEX TripleTOF 6600 operating in full scan + MS2 positive ion mode or a SCIEX 5500 operating in MRM positive ion mode, or a Thermo TSQ Vantage operating in MRM mode. Gradient separation was performed with water and 0.2% formic acid (Thermo Fisher Scientific, Waltham, MA, USA) as mobile phase A, and acetonitrile with 0.2% formic acid as mobile phase B. The method was qualified for the quantification range of 1–1000 ng/mL with accuracy and precision of ± 20%, except for at the lower limit of quantification when the accuracy and precision were ± 25%. Plasma concentrations were subject to noncompartmental analysis consistent with the route of administration using Phoenix WinNonlin (version 7.0, Certara, Princeton, NJ, USA). Statistical analyses Sample sizes were calculated based on power analyses for pharmacodynamic endpoints. Statistical analyses were performed using GraphPad software (San Diego, CA, USA). Results are expressed as mean ± standard error of the mean unless otherwise stated. In vivo data were analyzed with one-way analysis of variance (ANOVA) followed by Tukey post hoc analysis (acute food intake, db / db HbA 1C data). Longitudinal data were analyzed by two-way ANOVA followed by Tukey post hoc analysis ( db / db glucose and DIO mouse data) or two-way ANOVA followed by Sidak or Bonferroni post hoc analysis (HFHF canine acute oral glucose tolerance test data and 14-day data). In all statistical tests P < 0.05 was considered significant. One animal in the single MEDI7219 10 mg dose group for the glucose tolerance test was excluded from analysis due to a likely error in dosing. In the analysis of the effect of MEDI7219 on body weight in HFHF fed dogs, one animal in the placebo group and one datapoint on day 10 in the MEDI7219 group were excluded due to errors in measurement. No other animals or data points were excluded from any of the in vivo study analyses.
The development program involved peptide optimization using in vitro models, and in vivo potency testing in mouse models and formulation testing using rat models. Methods are reported in accordance with the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines. Animal studies were conducted at AstraZeneca (Gaithersburg, MD, USA or Cambridge, UK), Charles River Laboratories (Shrewsbury, Wilmington or Worcester, MA; Mattawan, MI, USA) or Covance Laboratories (Madison, WI, USA). The study was conducted in accordance with the Animals (Scientific Procedures) Act 1986, under a Project Licence reviewed by the establishment Animal Welfare and Ethical Review Body (AWERB) and granted by the UK Home Office. Study protocols were approved by the Institutional Animal Care and Use Committee at AstraZeneca (Gaithersburg, MD, USA), Charles River Laboratories (Shrewsbury, Wilmington or Worcester, MA; Mattawan, MI) or Covance Laboratories (Madison, WI, USA), and were in compliance with national laws and regulations ensuring humane use and care of laboratory animals and the AstraZeneca Animal Welfare and Bioethics policies. In vivo studies were not blinded, confounders were not controlled for, and no criteria were set for including or excluding animals or data points from analyses.
Amino acid substitution and lipidation N -α-Fmoc-L-amino acids were from Bachem (Bubendorf, Switzerland), and α-methyl and other unnatural amino acids were from Iris Biotech (Marktredwitz, Germany), Pharmaron (Beijing, China) or PepTech (Burlington, MA, USA); solvents were from Merck (Darmstadt, Germany). Peptides J211, J229 and MEDI7219 (Fig. ) were prepared as C-terminal carboxamides on Novabiochem NovaSyn TentaGel Rink (Merck) synthesis resin using standard chemistry and coupling procedures , and reagents from Sigma-Aldrich (Gillingham, UK). Amino acids following α-methyl residues were coupled twice to ensure full incorporation. The N -terminal histidine residue of GLP-1 was incorporated as Boc-His(Trt)-OH to simplify peptide cleavage. At designated lipidation positions, Fmoc-L-Lys(Mmt)-OH was incorporated into the peptide backbone during automated assembly and the Mmt protecting groups were removed upon completion. The acidified resin was quenched, and the exposed epsilon amino functions were selectively lipidated as required before peptide cleavage. Crude peptides were purified chromatographically using 5 µm Agilent Polaris C8-A (mono-lipidated; Agilent, Santa Clara, CA, USA) or Waters XBridge C18 stationary phases (bis-lipidated; Waters, Antwerp, Belgium), and lyophilized. Purified peptides were characterized by single quadrupole liquid chromatography/mass spectrometry (LC/MS) with a Waters XBridge C18 stationary phase, using a generic linear binary gradient of 10–90% methyl cyanide (MeCN; 0.1% trifluoroacetic acid [TFA] v/v) in water and the Waters MassLynx 3100 platform (ESI + mode, monitoring 3 M + H and 4 M + H ions) to verify molecular mass. Analytical reverse-phase high-performance liquid chromatography (RP-HPLC) was conducted using an Agilent Polaris C8-A stationary phase (3 µm) at 1.5 mL min -1 with a linear binary gradient of 10–90% MeCN (0.1% TFA v/v) in water, and monitored by UV absorption at 210 nm. Overall yields of J211, J229 and MEDI7219 were greater than 50% based on initial resin functionalisation (0.24 mmol/g). Mass spectrometry data for all three peptides was consistent with calculated values (given below). J211 Requires: 3228.60 Da: 2 M +2 = 1615.30, 3 M +3 = 1077.20, 4 M +4 = 808.15 Found: 2 M +2 = 1615.55, 3 M +3 = 1077.15, 4 M +4 = 808.10 J229 Requires: 3930.45 Da: 2 M +2 = 1966.23, 3 M +3 = 1311.15, 4 M +4 = 983.61 Found: 2 M +2 = 1966.34, 3 M +3 = 1311.25, 4 M +4 = 983.75 MEDI7219 Requires: 4352.99 Da: 3 M +3 = 1451.99, 4 M +4 = 1089.25 Found: 3 M +3 = 1451.89, 4 M +4 = 1089.28 See Supplementary data for additional LC/MS information. Fasted-state simulated intestinal fluid/pancreatin assay Fresh FaSSIF and USP Pancreatin (FaSSIF/p; Sigma-Aldrich) was prepared according to Galia et al . and used immediately. Peptides were dissolved in pre-warmed FaSSIF before addition of pre-warmed FaSSIF/pancreatin with agitation. Samples were analyzed by analytical RP-HPLC to determine remaining intact peptide by area under the curve. EScalate equilibrium shift assay Binding of peptides to human plasma proteins was determined by the EScalate equilibrium shift assay (Sovicell, Leipzig, Germany), using five dilutions of plasma in phosphate buffered saline and an assumed binding protein concentration of 600 µM. Samples were incubated for 1 h at room temperature then centrifuged to remove the HSA-coated beads. Supernatant samples were analyzed using HPLC (3 µm Phenomenex Aeris Widepore XB-C18 stationary phase) coupled to an electrospray ionization quadrupole time-of-flight mass spectrometer in high resolution accurate mass mode (Agilent, Santa Clara, CA, USA). Unbound fractions were calculated from the concentration-dependent shift in binding equilibrium according to [12pt]{minimal}
$${f}_{u}=_{D}^{Plasma}}}$$ f u = 1 1 + P K D Plasma , where [12pt]{minimal}
$$P$$ P is the concentration of the binding protein in plasma and [12pt]{minimal}
$${K}_{D}^{Plasma}$$ K D Plasma is the dissociation constant of the compound from plasma proteins in solution. Cyclic adenosine monophosphate accumulation assay All reagents for cAMP assays were obtained from Sigma-Aldrich unless otherwise specified. CHO-K1 cells (ATCC) were stably transfected with a human GLP-1R expression plasmid and maintained in Dulbecco’s Modified Eagle Medium, 10% fetal bovine serum, 500 μg/mL geneticin and 400 μg/mL hygromycin B. Human EndoC-βH1 cells were kindly provided by Professor Raphael Scharfmann (Endocells, Paris, France), and were maintained in Dulbecco’s Modified Eagle Medium (low glucose), 2% BSA fraction V (Roche Diagnostics, Basel, Switzerland), 50 µM 2-mercaptoethanol, 10 mM nicotinamide, 5.5 µg/mL transferrin and 6.7 ng/mL sodium selenite. Peptide serial dilutions were prepared in assay buffer (Hank’s Balanced Salt Solution [HBSS] containing 25 mM HEPES and 0.5 mM IBMX; pH 7.4) supplemented with 0.1% BSA or 4.4% HSA, using an Echo 550 acoustic liquid handler (Labcyte Inc., Sunnyvale, CA, USA) to obtain an 11-point concentration–response curve. Cells were suspended in assay buffer and combined with serially diluted peptides at room temperature for 30 min. cAMP levels were measured using a cAMP dynamic 2 HTRF kit (Cisbio, Codolet, France), following the manufacturer’s two-step protocol, on an EnVision plate reader (PerkinElmer, Waltham, MA, USA). Data were transformed to % Delta F, as described in the manufacturer’s guidelines, and expressed as % activation, in which 80 nM native GLP-1 peptide (Bachem) defines maximum effect. The transformed data were analyzed by four-parameter logistic fit to determine EC 50 values using GraphPad Prism 6 (GraphPad Software, San Diego, CA, USA).
N -α-Fmoc-L-amino acids were from Bachem (Bubendorf, Switzerland), and α-methyl and other unnatural amino acids were from Iris Biotech (Marktredwitz, Germany), Pharmaron (Beijing, China) or PepTech (Burlington, MA, USA); solvents were from Merck (Darmstadt, Germany). Peptides J211, J229 and MEDI7219 (Fig. ) were prepared as C-terminal carboxamides on Novabiochem NovaSyn TentaGel Rink (Merck) synthesis resin using standard chemistry and coupling procedures , and reagents from Sigma-Aldrich (Gillingham, UK). Amino acids following α-methyl residues were coupled twice to ensure full incorporation. The N -terminal histidine residue of GLP-1 was incorporated as Boc-His(Trt)-OH to simplify peptide cleavage. At designated lipidation positions, Fmoc-L-Lys(Mmt)-OH was incorporated into the peptide backbone during automated assembly and the Mmt protecting groups were removed upon completion. The acidified resin was quenched, and the exposed epsilon amino functions were selectively lipidated as required before peptide cleavage. Crude peptides were purified chromatographically using 5 µm Agilent Polaris C8-A (mono-lipidated; Agilent, Santa Clara, CA, USA) or Waters XBridge C18 stationary phases (bis-lipidated; Waters, Antwerp, Belgium), and lyophilized. Purified peptides were characterized by single quadrupole liquid chromatography/mass spectrometry (LC/MS) with a Waters XBridge C18 stationary phase, using a generic linear binary gradient of 10–90% methyl cyanide (MeCN; 0.1% trifluoroacetic acid [TFA] v/v) in water and the Waters MassLynx 3100 platform (ESI + mode, monitoring 3 M + H and 4 M + H ions) to verify molecular mass. Analytical reverse-phase high-performance liquid chromatography (RP-HPLC) was conducted using an Agilent Polaris C8-A stationary phase (3 µm) at 1.5 mL min -1 with a linear binary gradient of 10–90% MeCN (0.1% TFA v/v) in water, and monitored by UV absorption at 210 nm. Overall yields of J211, J229 and MEDI7219 were greater than 50% based on initial resin functionalisation (0.24 mmol/g). Mass spectrometry data for all three peptides was consistent with calculated values (given below). J211 Requires: 3228.60 Da: 2 M +2 = 1615.30, 3 M +3 = 1077.20, 4 M +4 = 808.15 Found: 2 M +2 = 1615.55, 3 M +3 = 1077.15, 4 M +4 = 808.10 J229 Requires: 3930.45 Da: 2 M +2 = 1966.23, 3 M +3 = 1311.15, 4 M +4 = 983.61 Found: 2 M +2 = 1966.34, 3 M +3 = 1311.25, 4 M +4 = 983.75 MEDI7219 Requires: 4352.99 Da: 3 M +3 = 1451.99, 4 M +4 = 1089.25 Found: 3 M +3 = 1451.89, 4 M +4 = 1089.28 See Supplementary data for additional LC/MS information.
Fresh FaSSIF and USP Pancreatin (FaSSIF/p; Sigma-Aldrich) was prepared according to Galia et al . and used immediately. Peptides were dissolved in pre-warmed FaSSIF before addition of pre-warmed FaSSIF/pancreatin with agitation. Samples were analyzed by analytical RP-HPLC to determine remaining intact peptide by area under the curve.
Binding of peptides to human plasma proteins was determined by the EScalate equilibrium shift assay (Sovicell, Leipzig, Germany), using five dilutions of plasma in phosphate buffered saline and an assumed binding protein concentration of 600 µM. Samples were incubated for 1 h at room temperature then centrifuged to remove the HSA-coated beads. Supernatant samples were analyzed using HPLC (3 µm Phenomenex Aeris Widepore XB-C18 stationary phase) coupled to an electrospray ionization quadrupole time-of-flight mass spectrometer in high resolution accurate mass mode (Agilent, Santa Clara, CA, USA). Unbound fractions were calculated from the concentration-dependent shift in binding equilibrium according to [12pt]{minimal}
$${f}_{u}=_{D}^{Plasma}}}$$ f u = 1 1 + P K D Plasma , where [12pt]{minimal}
$$P$$ P is the concentration of the binding protein in plasma and [12pt]{minimal}
$${K}_{D}^{Plasma}$$ K D Plasma is the dissociation constant of the compound from plasma proteins in solution.
All reagents for cAMP assays were obtained from Sigma-Aldrich unless otherwise specified. CHO-K1 cells (ATCC) were stably transfected with a human GLP-1R expression plasmid and maintained in Dulbecco’s Modified Eagle Medium, 10% fetal bovine serum, 500 μg/mL geneticin and 400 μg/mL hygromycin B. Human EndoC-βH1 cells were kindly provided by Professor Raphael Scharfmann (Endocells, Paris, France), and were maintained in Dulbecco’s Modified Eagle Medium (low glucose), 2% BSA fraction V (Roche Diagnostics, Basel, Switzerland), 50 µM 2-mercaptoethanol, 10 mM nicotinamide, 5.5 µg/mL transferrin and 6.7 ng/mL sodium selenite. Peptide serial dilutions were prepared in assay buffer (Hank’s Balanced Salt Solution [HBSS] containing 25 mM HEPES and 0.5 mM IBMX; pH 7.4) supplemented with 0.1% BSA or 4.4% HSA, using an Echo 550 acoustic liquid handler (Labcyte Inc., Sunnyvale, CA, USA) to obtain an 11-point concentration–response curve. Cells were suspended in assay buffer and combined with serially diluted peptides at room temperature for 30 min. cAMP levels were measured using a cAMP dynamic 2 HTRF kit (Cisbio, Codolet, France), following the manufacturer’s two-step protocol, on an EnVision plate reader (PerkinElmer, Waltham, MA, USA). Data were transformed to % Delta F, as described in the manufacturer’s guidelines, and expressed as % activation, in which 80 nM native GLP-1 peptide (Bachem) defines maximum effect. The transformed data were analyzed by four-parameter logistic fit to determine EC 50 values using GraphPad Prism 6 (GraphPad Software, San Diego, CA, USA).
Acute food intake in C57Bl/6J mice Male C57Bl/6 J mice 8–10 weeks of age (Jackson Laboratories, Bar Harbor, ME, USA) were single-housed in the BioDAQ (Research Diets, New Brunswick, NJ, USA) food monitoring system with ad libitum access to standard chow and water. Mice were randomized into groups of 6–9 per group on baseline 24-h food intake. On the first study day, mice were fasted for 6 h and then received a single subcutaneous dose of test peptide or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0). Food intake was monitored over the next 48 h. Body weight, blood glucose and plasma insulin in diet-induced obese mouse model Male 20-week-old C57Bl/6 J mice were single-housed for approximately 14 weeks with ad libitum access to water and 60% high-fat diet (D12492, Research Diets). Mice were randomized into groups of 12 mice per group on baseline body weight, 6 h fasting glucose and 6 h fasting insulin. Over 21 days, mice received daily subcutaneous injections of 10 nmol/kg of test peptides or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0). Body weight was measured daily and fasting glucose and insulin levels were measured on day 14 following a 6-h fast. Blood was collected via tail-snip and glucose was measured with an Ascensia Breeze 2 glucometer (Bayer, Mishawaka, IN, USA). Insulin was measured in plasma using a Meso Scale rat/insulin kit (Meso Scale Discovery, Rockville, MD, USA). Dose–response study of MEDI7219 in diabetic db/db mouse model Male 7-week-old db / db mice (Charles River, Bristol, UK) were group-housed with ad libitum access to standard chow and water. Mice were randomized to groups of nine mice per group on baseline body weight, HbA 1C and 4-h fasting glucose (assessed in tail bleed samples using a Cobas c-111 analyzer [Roche Diagnostics, Indianapolis, IN, USA] and Nova StatStrip Xpress glucometer [DSI, St. Paul, MN, USA]). Insulin was measured in plasma from tail bleeds using a Meso Scale kit. Over 28 days, mice received daily subcutaneous doses of test peptides or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0).
Male C57Bl/6 J mice 8–10 weeks of age (Jackson Laboratories, Bar Harbor, ME, USA) were single-housed in the BioDAQ (Research Diets, New Brunswick, NJ, USA) food monitoring system with ad libitum access to standard chow and water. Mice were randomized into groups of 6–9 per group on baseline 24-h food intake. On the first study day, mice were fasted for 6 h and then received a single subcutaneous dose of test peptide or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0). Food intake was monitored over the next 48 h.
Male 20-week-old C57Bl/6 J mice were single-housed for approximately 14 weeks with ad libitum access to water and 60% high-fat diet (D12492, Research Diets). Mice were randomized into groups of 12 mice per group on baseline body weight, 6 h fasting glucose and 6 h fasting insulin. Over 21 days, mice received daily subcutaneous injections of 10 nmol/kg of test peptides or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0). Body weight was measured daily and fasting glucose and insulin levels were measured on day 14 following a 6-h fast. Blood was collected via tail-snip and glucose was measured with an Ascensia Breeze 2 glucometer (Bayer, Mishawaka, IN, USA). Insulin was measured in plasma using a Meso Scale rat/insulin kit (Meso Scale Discovery, Rockville, MD, USA).
Male 7-week-old db / db mice (Charles River, Bristol, UK) were group-housed with ad libitum access to standard chow and water. Mice were randomized to groups of nine mice per group on baseline body weight, HbA 1C and 4-h fasting glucose (assessed in tail bleed samples using a Cobas c-111 analyzer [Roche Diagnostics, Indianapolis, IN, USA] and Nova StatStrip Xpress glucometer [DSI, St. Paul, MN, USA]). Insulin was measured in plasma from tail bleeds using a Meso Scale kit. Over 28 days, mice received daily subcutaneous doses of test peptides or placebo (50 mM Tris–HCl, 150 mM mannitol, 0.02% polysorbate 80; pH 8.0).
Caco-2 screen Caco-2 cells were trypsinized, suspended in medium and seeded to wells of a Millipore 96-well plate following standard procedures . Cells were fed at 2-day intervals for 3 weeks until a transepithelial electric resistance of ~ 1000 ohms/cm 2 was achieved. Test samples containing peptide and permeation enhancers (Supplementary Table ) were prepared in HBSS solution (pH 7.4). Lucifer Yellow and atenolol were added to the test samples as internal controls. The cells were incubated for 3 h with test samples on the apical side and blank media on the basolateral side. Media from the apical and basolateral sides were collected after 3 h and peptide content was evaluated . Data are expressed as apparent permeability (Papp): [12pt]{minimal}
$$Papp= _{0})}$$ P a p p = dQ dt · 1 A · C 0 where [12pt]{minimal}
$$dQ/dt$$ d Q / d t is the rate of permeation, [12pt]{minimal}
$${C}_{0}$$ C 0 is the initial concentration of test agent, and [12pt]{minimal}
$$A$$ A is the area of the monolayer. Oral bioavailability of GLP-1RAs with permeation enhancers in vivo Male Sprague Dawley rats (Charles River, Shrewsbury, MA, USA) weighing 250–275 g were housed with ad libitum access to standard chow and water. Test peptides were administered via either an intravenous or a duodenal catheter (4 rats per group) after overnight fasting, and food was returned following 4 h blood collection. Blood was collected via a jugular vein catheter at − 5, 15 and 30 min and 1, 2, 4, 8 and 24 h after intravenous dosing, or for intraduodenal groups at 15 min predose and 0.5, 1, 2, 4, 8, 24 and 48 h postdose. Blood was collected in K 2 EDTA tubes and kept on wet ice prior to 10 min centrifugation (3000 × g ) at 5 °C ± 3 °C. Plasma samples were stored at − 70 °C until analysis.
Caco-2 cells were trypsinized, suspended in medium and seeded to wells of a Millipore 96-well plate following standard procedures . Cells were fed at 2-day intervals for 3 weeks until a transepithelial electric resistance of ~ 1000 ohms/cm 2 was achieved. Test samples containing peptide and permeation enhancers (Supplementary Table ) were prepared in HBSS solution (pH 7.4). Lucifer Yellow and atenolol were added to the test samples as internal controls. The cells were incubated for 3 h with test samples on the apical side and blank media on the basolateral side. Media from the apical and basolateral sides were collected after 3 h and peptide content was evaluated . Data are expressed as apparent permeability (Papp): [12pt]{minimal}
$$Papp= _{0})}$$ P a p p = dQ dt · 1 A · C 0 where [12pt]{minimal}
$$dQ/dt$$ d Q / d t is the rate of permeation, [12pt]{minimal}
$${C}_{0}$$ C 0 is the initial concentration of test agent, and [12pt]{minimal}
$$A$$ A is the area of the monolayer.
in vivo Male Sprague Dawley rats (Charles River, Shrewsbury, MA, USA) weighing 250–275 g were housed with ad libitum access to standard chow and water. Test peptides were administered via either an intravenous or a duodenal catheter (4 rats per group) after overnight fasting, and food was returned following 4 h blood collection. Blood was collected via a jugular vein catheter at − 5, 15 and 30 min and 1, 2, 4, 8 and 24 h after intravenous dosing, or for intraduodenal groups at 15 min predose and 0.5, 1, 2, 4, 8, 24 and 48 h postdose. Blood was collected in K 2 EDTA tubes and kept on wet ice prior to 10 min centrifugation (3000 × g ) at 5 °C ± 3 °C. Plasma samples were stored at − 70 °C until analysis.
Fasted male beagle dogs weighing 6–8 kg were pretreated with pentagastrin 6 μg/kg. After 30 min, dogs (5 per group) were administered with either: IntelliCap capsules (Medimetrics, Eindhoven, Netherlands) filled with 0.7 mL of peptide and permeation enhancer solution (J229 8 mg/mL, NaCDC 12 mg/mL); 0.7 mL equivalent oral gavage and 20 mL gavage rinse; J229 0.1 mg/mL intravenous injection; or 0.1 mg/mL subcutaneous injection. Blood was collected at 0.25, 0.5, 1, 2, 4, 8, 24 and 48 h for subcutaneous and oral gavage groups. Blood was collected at 0.083, 0.25, 0.5, 1, 2, 4, 8 and 24 h for the intravenous group. Blood collection in IntelliCap groups started after actuation of capsule content release. Blood was collected from the jugular vein in K 2 EDTA tubes and kept on wet ice. Plasma samples were stored at − 60 °C to − 90 °C until analysis.
Oral tablet formulation Tablets contained 0.5–10 mg of MEDI7219, 150 mg of permeation enhancers (50 mg NaCDC [Prodotti, Basaluzzo, Italy] and 100 mg PG [Guangzhou Hanfang Pharmaceutical, Guangzhou, China]), mannitol (Roquette, Keokuk, IA, USA) as filler, crospovidone (BASF, Ludwigshafen, Germany) as disintegrant, sodium stearyl fumarate (JRS Pharma, Rosenberg, Germany) as lubricant and hydrophobic fumed silica (Evonik, Parsippany, NJ, USA) as glidant, with a total weight of 245 mg per tablet. Placebo tablets were identical to active tablets, except for the absence of test peptide. Tablets were made by: sieving ingredients; blending in a Turbula mixer (WAB, Muttenz, Switzerland); dry granulation by compression in a pellet machine (Parr Instrument, Moline, IL, USA) and sieving (1 mm); blending with lubricant and glidant in a Turbula mixer; and compression at 50 N hardness on an NP-RD10 tablet press (Natoli, St Charles MO, USA). Finally, tablets were enteric coated with Eudragit polymer suspension (Evonik, Darmstadt, Germany) to achieve a 12.5% weight gain using a Vector LDCS3 pan coater (Freund-Vector, Marion, IA, USA). Oral bioavailability of MEDI7219 in dogs Fasted male beagle dogs weighing 8–13 kg (5 per group) were administered with enteric-coated oral tablets containing 10 mg test peptide and 300 mg permeation enhancers were administered. Blood samples were collected at 0.5, 0.5, 1, 1.5, 2, 2.5, 3.5, 4.5, 8, 24 and 48 h postdose.
Tablets contained 0.5–10 mg of MEDI7219, 150 mg of permeation enhancers (50 mg NaCDC [Prodotti, Basaluzzo, Italy] and 100 mg PG [Guangzhou Hanfang Pharmaceutical, Guangzhou, China]), mannitol (Roquette, Keokuk, IA, USA) as filler, crospovidone (BASF, Ludwigshafen, Germany) as disintegrant, sodium stearyl fumarate (JRS Pharma, Rosenberg, Germany) as lubricant and hydrophobic fumed silica (Evonik, Parsippany, NJ, USA) as glidant, with a total weight of 245 mg per tablet. Placebo tablets were identical to active tablets, except for the absence of test peptide. Tablets were made by: sieving ingredients; blending in a Turbula mixer (WAB, Muttenz, Switzerland); dry granulation by compression in a pellet machine (Parr Instrument, Moline, IL, USA) and sieving (1 mm); blending with lubricant and glidant in a Turbula mixer; and compression at 50 N hardness on an NP-RD10 tablet press (Natoli, St Charles MO, USA). Finally, tablets were enteric coated with Eudragit polymer suspension (Evonik, Darmstadt, Germany) to achieve a 12.5% weight gain using a Vector LDCS3 pan coater (Freund-Vector, Marion, IA, USA).
Fasted male beagle dogs weighing 8–13 kg (5 per group) were administered with enteric-coated oral tablets containing 10 mg test peptide and 300 mg permeation enhancers were administered. Blood samples were collected at 0.5, 0.5, 1, 1.5, 2, 2.5, 3.5, 4.5, 8, 24 and 48 h postdose.
Eighteen male beagle dogs weighing an average of 10.9 ± 0.3 kg were housed at Charles River Laboratories (Worcester, MA, USA) and received two cups of 5A4J HFHF canine diet daily (20.5% protein, 52.9% fat, 26.6% carbohydrate, 18.9% fructose; ScottPharma Solutions, Marlborough, MA, USA) plus water ad libitum . For the single-dose study, dogs were randomized on baseline glucose levels to receive MEDI7219 1 mg or 10 mg or placebo tablets in the morning following an overnight fast (7–11 dogs per group). Ninety minutes after tablet administration, dogs received an oral glucose bolus (200 mg/mL at a 5 mL/kg volume calculated on body weight prior to HFHF feeding), and blood glucose (blood collected via peripheral vein) was measured with an AlphaTRAK glucometer system (Zoetis, Parsippany, NJ, USA) at –90, 0, 10, 20, 30, 40, 50, 60, 75, 90, 120, 180 and 240 min after glucose administration. Approximately 12 weeks later, dogs entered the multiple-dose study and received either MEDI7219 10 mg (n = 12) or placebo tablets (n = 6) once daily for 14 days. Dogs received two cups of HFHF canine diet per day, with feeding 3 h postdose during the 14-day study. Dogs had access to water ad libitum throughout the study. Food intake and body weight were monitored daily. On day 14, after overnight fasting, dogs received their final dose followed by an oral glucose and acetaminophen bolus 90 min after administration. Blood glucose was measured as described previously, and plasma acetaminophen levels were measured by LC/MS method at the same time points.
Fifty or seventy μL aliquots of K 2 EDTA plasma samples were precipitated with 75% acetonitrile (Sigma-Aldrich) in water (J.T. Baker, Phillipsburg, NJ, USA) (v/v) and centrifuged at 2000 × g . The supernatant was dried under nitrogen at 60 °C, then cooled. Samples were reconstituted in 20% acetonitrile in water (v/v). The extracted samples were separated using a Waters Acquity UPLC BEH C18 column (2.1 × 100 mm) on a Shimadzu Nexera UHPLC at 60 °C with 0.7 mL/min flow rate, and detected using a SCIEX TripleTOF 6600 operating in full scan + MS2 positive ion mode or a SCIEX 5500 operating in MRM positive ion mode, or a Thermo TSQ Vantage operating in MRM mode. Gradient separation was performed with water and 0.2% formic acid (Thermo Fisher Scientific, Waltham, MA, USA) as mobile phase A, and acetonitrile with 0.2% formic acid as mobile phase B. The method was qualified for the quantification range of 1–1000 ng/mL with accuracy and precision of ± 20%, except for at the lower limit of quantification when the accuracy and precision were ± 25%. Plasma concentrations were subject to noncompartmental analysis consistent with the route of administration using Phoenix WinNonlin (version 7.0, Certara, Princeton, NJ, USA).
Sample sizes were calculated based on power analyses for pharmacodynamic endpoints. Statistical analyses were performed using GraphPad software (San Diego, CA, USA). Results are expressed as mean ± standard error of the mean unless otherwise stated. In vivo data were analyzed with one-way analysis of variance (ANOVA) followed by Tukey post hoc analysis (acute food intake, db / db HbA 1C data). Longitudinal data were analyzed by two-way ANOVA followed by Tukey post hoc analysis ( db / db glucose and DIO mouse data) or two-way ANOVA followed by Sidak or Bonferroni post hoc analysis (HFHF canine acute oral glucose tolerance test data and 14-day data). In all statistical tests P < 0.05 was considered significant. One animal in the single MEDI7219 10 mg dose group for the glucose tolerance test was excluded from analysis due to a likely error in dosing. In the analysis of the effect of MEDI7219 on body weight in HFHF fed dogs, one animal in the placebo group and one datapoint on day 10 in the MEDI7219 group were excluded due to errors in measurement. No other animals or data points were excluded from any of the in vivo study analyses.
Supplementary Information.
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The Genetic Determinants of | 5346cccc-399f-4a9a-8e08-5ad64662e6b1 | 11765107 | Microbiology[mh] | The genus Listeria is an important group of microorganisms in the food industry, now consisting of 27 officially recognized species. Based on recent findings, the genus has been divided into two clades: Listeria sensu stricto, which includes L. monocytogenes and species closely related to it, and Listeria sensu lato, which encompasses species that are more distantly related to L. monocytogenes . L. monocytogenes is pathogenic in both humans and animals . On rare occasions, other Listeria species, such as L. ivanovii , L. seeligeri, and L. innocua , have been associated with human diseases . Listeria spp. such as L. innocua are frequently employed as indicators of favorable conditions for the growth of L. monocytogenes . L. monocytogenes is a Gram-positive, rod-shaped, and facultative anaerobic bacterium . This bacterium is ubiquitous in the agricultural environment and has been found in soil, water, plants, and animals. L. monocytogenes has extraordinary adaptive abilities and can survive in extreme conditions that typically function to inhibit the proliferation of bacteria, such as the temperature range from 45 °C to −1.5 °C, which allows growth at refrigeration temperatures . In addition, this bacterium has the ability to proliferate over a wide pH range (4.4–9.6), low water activity (aw < 0.90), and high salt concentration (even 20%) and in the presence of disinfectants and preservatives . Furthermore, L. monocytogenes can form biofilms on both living and inanimate surfaces, protected from disinfectants, which further increases its ability to survive under difficult conditions . However, it is unable to withstand pasteurization temperatures, which is why contamination in food processing plants typically occurs during post-pasteurization processes . This causes L. monocytogenes to persist in food production plants, enter the food chain, and lead to contamination of many food products , such as raw and processed meat , fish, unpasteurized milk and dairy products, raw fruit and vegetables and ready-to-eat products . The main route of spread of L. monocytogenes to humans is the intake of highly contaminated food , with foodborne transmission accounting for as much as 99% . From these points of view, managing L. monocytogenes during industrial food processing presents significant challenges . L. monocytogenes is the causative agent of a serious foodborne illness called listeriosis . The symptoms of listeriosis are influenced by many factors, such as infectious dose, age, immune status of the consumer, and strain virulence . This disease can manifest in invasive or non-invasive forms . For individuals with a healthy immune system, a non-invasive form of listeriosis develops and can lead to mild gastroenteritis symptoms such as nausea, vomiting, diarrhea, and fever . In immunocompetent people, diseases are self-limiting, often resolved without the need for medical attention, resulting in undiagnosed cases and underreporting . An invasive form of listeriosis develops in susceptible people, such as pregnant women, newborns, and the elderly, as well as people with weakened immune systems, such as those who have received organ transplants. In these groups, listeriosis can lead to life-threatening symptoms such as sepsis, bacterial meningitis , or brain infections . In pregnant women, it can cause mother-to-fetus infections, resulting in spontaneous abortion, stillbirth, or premature birth . Generally, listeriosis causes high hospitalization rates (95%) and high mortality rates, reaching 20–30% . In contrast, infection with other common foodborne illnesses, such as campylobacteriosis and salmonellosis, seldom leads to deaths . For this reason, L. monocytogenes has been classified as one of the four foodborne pathogens considered the most significant threat to public health by the World Health Organization (WHO) since the early 1980s . L. monocytogenes has several molecular mechanisms that allow it to adapt throughout the various stages of its pathogenic lifecycle . The transition to an intracellular lifestyle for pathogens involves an upregulation of gene products that facilitate cell-to-cell spread and enhance bacterial replication within the host’s cytosol . After ingestion of contaminated food, L. monocytogenes must survive exposure to tough conditions in the host system, e.g., high acidity and bile salts. Surviving these conditions is crucial to the pathogenesis of this bacteria. Moreover, L. monocytogenes has the ability to cross three critical barriers in the human body: the intestinal epithelium, the blood–brain barrier, and the placenta . After binding to the epithelial cells of the gastrointestinal tract with the help of the internalin proteins InlA and InlB (encoded by inlA and inlB ), L. monocytogenes is engulfed by macrophages within an initial phagosomal vacuole . Once inside, L. monocytogenes escapes from the membrane-bound vacuole by secreting a pore-forming cytolysin called listeriolysin O (LLO) (encoded by hly ), along with two phospholipases (encoded by plcA and plcB ) that collectively dismantle the phagosome where the bacteria reside. Inside the cytosol of the host cell, the bacteria replicate by utilizing nutrients sourced from the host . L. monocytogenes then moves through the cytoplasm and invades neighboring cells, utilizing actin polymerization as a means of motility, which is directed by its surface protein actin assembly-inducing protein (ActA) (encoded by actA ) . All gene products involved in bacterial invasion, cytosolic entry, growth, intracellular movement, and spread to neighboring cells are regulated by the transcriptional regulator PrfA . The most important virulence determinants are clustered in the chromosome in pathogenicity islands, such as Listeria pathogenicity island 1 (LIPI-1), LIPI-3 and LIPI-4 . The incidence of listeriosis in Europe has been rising in recent years . Significant shifts in food production, processing, and distribution practices, along with the growing reliance on refrigeration as a primary method of preservation; alterations in dietary habits, especially an increased consumption of ready-to-eat (RTE) foods ; and demographic changes, such as a rise in the population at higher of for the disease because of aging are all proposed as potential factors contributing to the emergence of human foodborne listeriosis . Due to these factors, many countries, including the USA, enforce a strict zero-tolerance policy regarding the presence of L. monocytogenes in RTE foods. In contrast, the European Regulation on Microbiological Criteria for Foodstuffs No. 2073/2005 sets forth two different standards for L. monocytogenes in RTE foods based on considerations such as pH, water activity, and bacterial growth potential. One standard applies to RTE foods for infants and special medical purposes, banning L. monocytogenes in 25 g of food, while the other allows up to 100 cfu/g in RTE foods not intended for those purposes throughout the product’s shelf life . This highlights the need for the industry to use precise and reliable methods to detect L. monocytogenes in food products . In recent times, several techniques for detecting Listeria spp., including L. monocytogenes , in food have been developed. Advances in diagnostic technologies allow for more accurate and faster detection of L. monocytogenes bacteria. This means that more cases are identified, which increases the number of reported cases . These methods can be divided into two main groups: conventional methods, such as culture-based techniques, and alternative methods . Food laboratories commonly use conventional microbiological techniques for detecting Listeria spp., following guidelines from organizations such as the U.S. Food and Drug Administration (FDA) and the International Organization for Standardization (ISO). These methods include standards such as EN ISO 11290-1:2017 and EN ISO 11290-2:2017 , which involve steps such as pre-enrichment and enrichment in selective or differential media, such as Listeria Agar Ottaviani and Agosti (ALOA), Oxford, or PALCAM, followed by biochemical analysis, e.g., β-hemolysis test . Traditional culture-dependent methods remain the gold standard; however, they are time-intensive and significantly dependent on the phenotype that is subject to different environmental conditions . Consequently, faster alternative methods have emerged, employing various approaches. These include molecular techniques, such as polymerase chain reaction (PCR) and its variations, such as multiplex PCR and real-time PCR (RT-PCR), based on the detection of species-specific DNA sequences, including 16S rRNA genes and virulence genes, as well as immunological methods, which rely on antigen–antibody interactions, such as enzyme-linked immunosorbent assay (ELISA), along with microarrays and biosensors . Due to the fact that there are many strains of L. monocytogenes , further subtyping is necessary. Conventional subtyping methods include serotyping. L. monocytogenes strains can be recognized by specific combinations of somatic (O) and flagellar (H) antigens present on their cell surfaces . As of today, L. monocytogenes consists of four lineages (I, II, III, and IV) and 14 serotypes. Lineage I includes strains classified under serotypes 1/2b, 3b, 4b, 4d, 4e, 4h, and 7, while lineage II consists of strains belonging to serotypes 1/2a, 1/2c, 3a, and 3c. Lineage III encompasses strains from serotypes 4a and some 4b and 4c strains, whereas some 4a, 4b, and 4c strains have been characterized into lineage IV . However, 95% of isolates obtained from food and clinical cases of listeriosis in humans belong to three of these serotypes: 4b, 1/2a and 1/2b. This indicates that certain serotypes may exhibit higher virulence or a greater ability to adapt to the human host . More interestingly, serotype 1/2a is the most commonly isolated from food, while serotype 4b is primarily responsible for listeriosis infections . For the serotyping of L. monocytogenes , both standard agglutination methods with mono-/polyvalent antisera and PCR-based genoserotyping methods can be used . Other L. monocytogenes subtyping methods include methods based on the use of restriction enzymes, such as pulsed-field gel electrophoresis (PFGE), and subtyping methods based on PCR, such as random amplified polymorphic DNA (RAPD) or multilocus sequence typing (MLST) . Despite the great diversity of virulence of L. monocytogenes serotypes, in the European Union, including Poland, there is no obligation to identify the serotypes of this bacterium . As mentioned above, L. monocytogenes , as a non-spore-forming pathogen, has remarkable adaptive abilities to food stresses . The key role in the stress response is played by the two-component systems, such as LiaRS, LisRK, CesRK, AgrCA, and VirRS, controlled by σB (SigB), an alternative sigma factor that controls the general stress response in L. monocytogenes . L. monocytogenes ’ exceptional ability to withstand stressful conditions makes it a serious challenge in food processing and an ideal model organism for studying resistance mechanisms to stress factors found in food and food production environments. In this review, we will touch on the mechanisms of resistance to common stresses occurring in food processing plants, such as high and low temperatures, acidic pH, and osmolarity, and we will primarily concentrate on the genetic factors and mechanisms underlying L. monocytogenes ’ susceptibility and resistance to less-studied stress conditions, such as bacteriocins. Thermal treatment is a widely used and effective method for eliminating foodborne pathogens, as most are highly sensitive to elevated temperatures. However, it is important to note that the effectiveness of thermal treatments against L. monocytogenes is reduced due to its ability to survive and reproduce within a broad temperature range, from −0.4 °C to 45 °C . The heat resistance of L. monocytogenes is influenced by various factors, including prior environmental stresses, the food matrix, and internal characteristics such as serotypes. Previous studies have shown that strains of serotype 1/2a, the most prevalent in food, demonstrated relatively low heat tolerance, whereas serotype 4b strains, which are linked to human listeriosis, showed significant variability in their response to heat. The highest heat tolerance was observed in serotype 7 strain . At the molecular level, L. monocytogenes reacts to heat treatment by expressing genes associated with specific heat shock responses, such as the production of heat shock proteins (HSPs) . Class I heat shock genes, such as dnaK , dnaJ , grpE , groEL, and groES , produce heat shock proteins that act as chaperones to prevent the misfolding of proteins that can occur during environmental stress. These genes are controlled by the negative regulator HrcA . Class II HSP genes encode general stress proteins that are regulated by the alternative sigma factor SigB under various growth-inhibiting conditions . Additionally, class III heat shock genes encode ATP-dependent proteases, including ClpC, ClpP, and ClpE, controlled by the gene regulator CtsR. Class III is essential for degrading misfolded proteins under stress conditions such as elevated temperatures . Equally dangerous seems to be the resistance of L. monocytogenes to low, refrigerated temperature treatment. More concerning is the observation that the population of L. monocytogenes remained unchanged during freezing . Resistance to low temperatures is provided by several mechanisms. First of all, L. monocytogenes diminished metabolic functions by reducing intracellular enzyme activity to the essential minimum and modifying the expression of genes associated with the biosynthesis of nutrients, including lipids, carbohydrates, and amino acids, as well as those related to motility . Furthermore, L. monocytogenes alters its membrane lipid composition by increasing the concentration of unsaturated fatty acids, thereby achieving optimal membrane fluidity for transport across the membrane . Other adaptation mechanisms of L. monocytogenes to low temperatures have also been documented. One example of this mechanism is the expression of cold shock proteins called Csps . Csps are small proteins, acting as chaperones, responsible for supporting essential life processes in bacteria . Finally, L. monocytogenes increases the accumulation of cryoprotective substances such as carnitine, glycine betaine, and proline betaine . Chan et al. showed increased activity of L. monocytogenes at refrigeration temperature compared to human body temperature. The opuCABCD operon encodes a carnitine transporter, and gbuC encodes the binding protein of a glycine betaine transporter. These substances, which also function as osmolytes, have been found to play a role in osmotic stress resistance in L. monocytogenes . They help maintain proper turgor pressure and protect enzymes from degradation . The study by Schmid et al. also confirmed the involvement of Csps in the repair of DNA damaged by high concentrations of NaCl. These studies show the occurrence of simultaneous resistance to different stresses. The mechanism seems to further increase the problem of L. monocytogenes persistence in food processing plants. Another challenge faced by L. monocytogenes in food processing is acidification, which occurs during fermentation by lactic acid bacteria (LAB). These bacteria are naturally present in food, originating from raw materials, and are also intentionally introduced as starter cultures . L. monocytogenes employs several mechanisms to regulate its internal pH when exposed to acid stress. The main mechanism involved in the protection of bacteria against acidification stress is the glutamic acid decarboxylase (GAD) system. This system is composed of three gene products—GadA, GadB, and GadC (encoded by three genes gadD1 , gadD2 , and gadD3 )—that function by converting extracellular glutamate into γ-aminobutyrate (GABA) through an enzymatic reaction . This mechanism helps protect the bacteria in environments where the pH drops below 4.5. Another protective strategy involves the arginine and agmatine deiminase pathways . These systems play a key role in L. monocytogenes ’ response to extreme acidity, helping to regulate internal pH by converting arginine into ammonium through a series of reactions. The low pH adaptation systems mentioned above function simultaneously to ensure the survival and adaptation of L. monocytogenes under acid-stress conditions . L. monocytogenes has developed a range of mechanisms to withstand various stressors in food environments. It can deploy multiple strategies to combat the same type of stress or use a single mechanism to adapt to different stressors . Biopreservation offers an alternative control measure for improving the stability and safety of food products. It reduces the number of chemical preservatives needed and the intensity of heat treatments, both of which can negatively affect food quality . Using bacteriocins as biocontrol agents is a promising approach to managing pathogens like L. monocytogenes. Both Gram-positive and Gram-negative bacteria are capable of producing bacteriocins. Our main interest lies in the compounds synthesized by LAB . LAB are part of a broad group of Gram-positive, microaerophilic microbes known for producing lactic acid as the primary byproduct of glucose fermentation in dairy products, fermented meat products, and fermented vegetables . LAB consists of the following genera: Lactobacillus , Lactococcus , Pediococcus , Leuconostoc , Enterococcus , Streptococcus , Carnobacterium , and Weissella , and more peripheral genera such as Aerococcus , Tetragenococcus, and Oenococcus . They have been used for centuries in the production of fermented foods due to their positive impact on nutritional value, sensory qualities, and shelf life . This is due to the production of antimicrobial agents, including organic acids, carbon dioxide, ethanol, hydrogen peroxide, and bacteriocins, in particular . Bacteriocins produced by LAB are ribosomally synthesized antimicrobial peptides that exhibit bactericidal or bacteriostatic activity against strains of closely related bacteria . They are regarded as narrow-spectrum bacteriocins, although some bacteriocins have a broad spectrum of activity, including species unrelated to the producer, spoilage organisms, and food-borne pathogens such as L. monocytogenes . Activity against Gram-negative bacteria has been demonstrated, but typically only when the outer membrane’s integrity is compromised. Bacteriocin-producing organisms are resistant to their own antimicrobial peptides, a defense mediated by specific immunity proteins . Genes responsible for the synthesis of bacteriocins are grouped into gene operons, most often located on mobile genetic elements such as bacteriocinogenic plasmid. This opens up the possibility of bacteriocin synthesis in heterologous systems . The first classification, created by Klaenhammer , included four classes of bacteriocins. Today, bacteriocins are divided into three major classes based on biological activity. Bacteriocins produced by LAB are mainly classified into classes I and II. Class I bacteriocins include small, post-translationally modified peptides called lantibiotics . Bacteriocins of this class, as a result of post-translational modifications, acquire unusual amino acids such as lanthionine and/or methyllanthionine. The vast majority of class I bacteriocins are produced by Gram-positive bacteria belonging to the species of LAB. The most widely studied member of group I is nisin, produced by Lactococcus lactis . The biosynthesis of nisin is governed by an operon composed of 11 genes, regulated by the two-component NisRK system. This system functions as part of a quorum sensing (QS) mechanism, responding to the concentration of nisin . Class II bacteriocins are small (<10 kDa), thermostable, unmodified peptides. The characteristic feature of this class of bacteriocins is their bactericidal activity against the pathogen L. monocytogenes . For this reason, class II bacteriocins are often called listericidal bacteriocins . The structure of peptides of class IIa can be divided into two different regions separated by a flexible hinge. The cationic N-terminal region contains two cysteine residues joined by a disulfide bridge and a conserved YGNGVXC motif characteristic of bacteriocins of this class . The C-terminus is less conserved. Both regions of the bacteriocin contribute to its bactericidal activity: the N-terminus is involved in interacting with the target cell, while the C-terminus determines the specificity of the target cell . This class can be further divided into a few subclasses, namely subclass IIa (pediocin-like bacteriocins), subclass IIb (dipeptide bacteriocins), and subclass IIc (circular bacteriocins). The most well-known representative of class II bacteriocins is pediocin PA-1, which belongs to subclass IIa. Its gene operon is plasmid-encoded and consists of four genes: the structural gene pedA , the immunity gene pedB , and two additional genes, pedC and pedD , which encode an ABC transporter and an accessory protein, respectively . Like nisin, pediocin PA-1 requires a specific receptor on the surface of the target cell for its bactericidal activity. Class III bacteriocins are large, heat-sensitive protein molecules with molecular weights exceeding 30 kDa. Unlike other bacteriocins that remain stable at high temperatures, class III bacteriocins are prone to heat denaturation, which restricts their application in certain food processing scenarios. These bacteriocins function primarily by enzymatically degrading the cell walls of target bacteria, resulting in cell lysis. One example of a class III bacteriocin is helveticin J, which is produced by Lactobacillus helveticus . The classification of bacteriocins is presented in . Bacteriocins produced by LAB are of particular interest because many have a long history of safe use, and most LAB species are recognized as safe under the GRAS (Generally Recognized as Safe) and QPS (Qualified Presumption of Safety) classifications . Bacteriocins can be utilized as natural preservatives, and with the increasing consumer preference for more natural products, they offer a promising alternative to chemical preservatives . Bacteriocins possess numerous qualities that make them appealing as biopreservatives in food products. Defined as natural antimicrobial agents, they align with the increasing consumer preference for natural and minimally processed foods. Unlike many chemical preservatives, bacteriocins are non-toxic to humans; as protein compounds, they are degraded by proteolytic enzymes in the digestive system into simple, harmless components that are easily absorbed and metabolized. Due to their decomposition, they do not accumulate in the natural environment. As a result, they do not alter the composition of the gut microbiota and are non-cytotoxic and non-carcinogenic . One significant advantage of bacteriocins over chemical preservatives or traditional sanitization methods is their selectivity and specific spectrum of action. They often display bactericidal activity against foodborne pathogens such as L. monocytogenes , Staphylococcus aureus , and Clostridium spp., while generally remaining inactive against starter cultures used in the fermentation of foods and probiotic microorganisms . Bacteriocins exhibit both bacteriostatic and bactericidal effects on bacterial cells. The mechanisms underlying the inhibitory actions of bacteriocins from LAB toward target cells exhibit a substantial diversity. The cationic nature of bacteriocins facilitates their docking onto anionic elements of the bacterial cell surface and interaction with the bacterial cell membrane or a specific membrane receptor . In the next stage, bacteriocins induce permeabilization of the target bacterial cell membrane, which disrupts the proton motive force and depletes intracellular ATP, causing leakage of cell contents and, ultimately, cell death . To date, seven receptors have been identified. The first to be identified and the most studied is lipid II. Lipid II, located in the cytoplasmic membrane, is pivotal in constructing the cell wall by transporting peptidoglycan monomers from inside to outside . Lipid II is a crucial precursor targeted by nisin. Binding to lipid II, nisin disrupts cell wall synthesis and forms membrane pores, leading to bacterial cell death. Nisin also acts by blocking lipid II, inhibiting cell wall synthesis . The second receptor is the mannose-specific phosphotransferase system (Man-PTS), the primary mannose transport system in Firmicutes and Gammaproteobacteria . Man-PTS generally includes three proteins: enzyme I (EI), histidine phosphocarrier protein (HPr), and enzyme II (EII). EI and HPr, both cytoplasmic proteins, facilitate the transfer of a phosphate group to EII. EII comprises four subunits: IIA, IIB, IIC, and IID. IIA and IIB are found in the cytoplasm, while IIC and IID create a membrane-bound complex that allows sugar molecules to enter the cell . The membrane subunits IIC and IID of Man-PTS are vital for the bactericidal effect of class IIa bacteriocins like pediocin PA-1 . By binding to Man-PTS, pediocin-like bacteriocins cause cell membrane permeabilization, disrupt the proton motive force, and deplete ATP and intracellular substrates. This terminates all cellular biosynthesis, ultimately leading to cell death . Other receptors include undecaprenyl pyrophosphate phosphatase UppP, the APC family amino acid transporter, CorC protein, ABC maltose transporter, and zinc-dependent metallopeptidase YvjB . Receptor-dependent bacteriocins have a distinct, narrow range of activity, making them highly appealing for specific applications. Consequently, investigating receptor identification and bacteriocin-receptor interaction mechanisms is of paramount importance . L. monocytogenes from Food Bacteriocins produced by LAB are excellent for preserving food at risk of L. monocytogenes contamination. Especially promising is their potential to enhance the microbiological safety of minimally processed foods like dairy, meat, and various fruits and vegetables. Research has demonstrated that class IIa bacteriocins effectively reduce L. monocytogenes levels in many food products, making them a valuable tool in ensuring food safety . Bacteriocins from different species of LAB have shown both bactericidal and bacteriostatic effects on L. monocytogenes . For instance, a starter culture of Pediococcus acidilactici producing pediocin PA-1 reduced L. monocytogenes in poultry sausages by up to 2.6 log cfu/g . Similarly, pediocin PA-1 decreased L. monocytogenes in ripened cheese by up to 3 log cfu/g . In cold-smoked, vacuum-packed salmon, bactericidal effects were noted for bacteriocins produced by Carnobacterium species. Piscicocin VIa and VIb, both produced by Carnobacterium piscicola V1, showed bactericidal activity, while divercin V41 from Carnobacterium divergens V41 demonstrated bacteriostatic activity . Piscicolin 126, from Carnobacterium piscicola JG126, permanently reduced L. monocytogenes to undetectable levels in ham . Additionally, saccacin P from Lactobacillus sakei Lb790 inhibited L. monocytogenes in vacuum-packed chicken slices, remaining stable on cold cuts for 4 weeks ; it also had bactericidal activity in cold-smoked salmon . Enterocin A, produced by Enterococcus faecium strain CTC492, reduced L. monocytogenes by 1 log in dry fermented sausage and showed bactericidal activity when combined with enterocin B . These studies demonstrate that bacteriocins, especially those from class IIa, are highly effective against L. monocytogenes , making them a powerful tool in food safety. Bacteriocins can be incorporated into food through several methods and forms. One approach is to inoculate the food with a bacteriocin-producing strain . Another option is to add purified bacteriocins as food additives . Additionally, food can be processed using ingredients previously fermented with bacteriocin-producing strains. Bacteriocins may also serve as a component in bioactive packaging . The use of bacteriocins in food is one of the dynamically developing areas of biopreservation. However, the number of bacteriocins widely used in the food industry remains limited. Despite the discovery and study of numerous bacteriocins, only a few have been commercially implemented. To date, only two bacteriocins have been approved for widespread use in the food industry: nisin, marketed as Nisaplin ® with the active ingredient nisin A, and pediocin PA-1, sold under the brand name ALTA™2431. Therefore, most research in this area has focused on specific bacteriocins, such as nisin and some bacteriocins of class IIa . For a bacteriocin to be approved for general use, it must meet several key requirements. The first aspect is the efficiency of using bacteriocins. The bacteriocin must demonstrate a narrow spectrum of action and strong antimicrobial activity against target pathogens and, at the same time, should not affect technological microorganisms such as starter cultures or probiotics. The second aspect is safety. It must be non-toxic to humans and animals and not cause adverse effects . The third and most important aspect is the potential risks of resistance development . The development of highly tolerant or resistant strains is a significant concern, as it undermines the effectiveness of bacteriocins as biopreservatives . The global problem of resistant foodborne pathogens is exacerbated by the international trade of raw and processed foods. This facilitates the spread of resistant strains across borders, making it a significant public health concern . Numerous studies have explored the susceptibility of pathogenic bacteria, such as L. monocytogenes , to specific bacteriocins. However, comparing these studies can be challenging due to varying experimental methods and terminology. In the literature, bacteriocin resistance is often not clearly defined, and there is no consensus among researchers regarding what constitutes high, moderate, or low resistance levels . A key element in susceptibility tests is the bacteriocin solution itself. Some studies use purified preparations, such as nisin, measured in milligrams or international units (IU), while others use fermentates from producer organisms, such as pediocin PA-1, measured in activity units (AU) . In the study by Gravesen et al. , the resistance of L. monocytogenes to nisin was defined as a 10-fold increase in the minimum inhibitory concentration (MIC). If a pathogen could grow at concentrations higher than MIC, it was deemed resistant to the bacteriocin. Microorganisms exhibit different types of resistance to antimicrobials: innate, apparent, or acquired. Innate resistance is genetically controlled and naturally associated with the organism. Differences in resistance among species and strains under identical conditions are typically due to innate factors. Mechanisms include cellular barriers (such as teichoic acids in Gram-positive bacteria), efflux mechanisms (pumping out compounds), lack of biochemical targets, and antimicrobial inactivation by enzymes. Natural resistance to nisin in L. monocytogenes occurs at frequencies ranging from less than 10 −9 to less than 10 −5 . In contrast, resistance to class IIa bacteriocins has been observed in 1 to 8% of wild-type strains tested . Apparent resistance relates to assay or application conditions. Susceptibility varies based on application settings and interacting stress conditions (such as high temperatures, low pH, or high pressure), which can affect resistance. Acquired resistance results from genetic changes via mutations or acquiring genetic material from plasmids, altering the microbial cell’s response to antimicrobials. Acquired resistance to bacteriocins in L. monocytogenes may be the result of factors resulting from human practices. Overuse of antimicrobial compounds in food preservation and other branches, such as agriculture, veterinary, cosmetics, and medicine, may create selection pressure on bacteria, encouraging the development of resistant strains. Furthermore, the use of sublethal concentrations of bacteriocins allows bacteria to survive and adapt, enhancing resistance . Various genetic loci have been linked to these types of resistance . Understanding these genes’ roles in bacteriocin resistance is crucial for optimizing bacteriocin use and continues to attract research interest . The main mechanisms and genetic determinants associated with L. monocytogenes resistance to LAB bacteriocins are presented in . 6.1. Resistance via Changes in Receptor Expression As previously noted, for many bacteriocins to be effective in eliminating bacteria, they need to bind to specific receptors on the target cell’s surface. These receptors act as docking sites, allowing the bacteriocin to attach and exert its lethal effects. Without the presence of these specific receptors, the bacteriocins cannot effectively interact with the bacterial cell, rendering them less effective or even ineffective. The phenomenon of resistance to nisin, a class I bacteriocin, was described by Gravesen et al. . In this study, the researchers aimed to identify loci responsible for nisin resistance in L. monocytogenes . Their analysis revealed that the nisin-resistant mutant exhibited increased expression of a protein with strong homology to the glycosyltransferase domain of high-molecular-weight penicillin-binding proteins (PBPs). These membrane-bound proteins are crucial for cell wall biosynthesis through peptidoglycan chain extension and cross-linking. It was speculated that the increased expression and production of this protein might partially shield lipid II in the plasma membrane, thus reducing nisin’s efficacy by impeding its access to the binding site. The other authors observed a similar effect . Resistance to subclass IIa bacteriocins in L. monocytogenes often involves changes in receptor expression. This resistance can arise through either the reduced expression or even loss of the Man-PTS system, a key element involved in sugar uptake. According to Vadyvaloo et al. , wild-type strains demonstrated faster growth in the presence of glucose, whereas the class IIa bacteriocin-resistant strains exhibited quicker growth in the absence of glucose. The variations in growth between the wild-type and resistant mutants on different carbohydrates suggest that the sugar metabolism pathways might be altered in the resistant strains. The man-PTS system is encoded by the mptACD operon. The level of mptACD expression has been shown to correlate with the level of bacteriocin sensitivity . Survival of bacteria under stress conditions requires rapid changes in gene expression, which are controlled by the association of different alternative sigma factors. Previous studies reviewed by Bastos et al. have identified four types of sigma factors in L. monocytogenes : σB (SigB), σH , RpoD, and RpoN. The study by Robichon et al. linked resistance to subclass IIa bacteriocins to the regulatory gene rpoN , which encodes the alternative sigma factor σ54. It was proposed that the transcription factor σ54 might regulate the expression of the Man-PTS receptor, as mutants of L. monocytogenes lacking rpoN showed resistance to mesentericin Y105 (produced by Leuconostoc mesenteroides ) and related subclass IIa bacteriocins. σ54 is known to be involved in the regulation of PTS expression. The study by Dalet et al. discovered that the mannose family activator ManR and the PTS permease are essential for L. monocytogenes sensitivity to mesentericin Y105. σ54 activates the mptACD operon ( mptA , mptC , and mptD genes), which codes for EIIAB, EIIC, and EIID in L. monocytogenes , alongside ManR, the transcriptional activator for σ54 . Disruptions in the mptA or mptD genes led to resistance, and further in-frame deletions in the mptD gene were also linked to mesentericin Y105 resistance, suggesting that a specific domain of the MptD subunit is involved in target recognition by the bacteriocin. These findings were the first to suggest that EIIMan could serve as a receptor for subclass IIa bacteriocins . Mutations in rpoN led to the loss of mptACD expression, resulting in resistance to mesentericin Y105 . Similarly, mutations in ManR (encoded by manR ) rendered the cells resistant to subclass IIa bacteriocins . Both regulatory proteins, RpoN and ManR, are crucial for the active transcription of genes encoding the subclass IIa bacteriocin receptor. In the works of Gravesen et al. and Ramnath et al. , two different changes in PTS expression were correlated with the development of resistance to class IIa bacteriocins in L. monocytogenes . In the study by Ramnath et al. , a mutant of L. monocytogenes resistant to leucocin A (produced by Leuconostoc gelidum ) was found to lack the IIAB subunit of the mannose PTS permease. Conversely, Gravesen et al. identified that L. monocytogenes mutants resistant to pediocin PA-1 exhibited overexpression of the β-glucoside PTS permease. Gravesen et al. examined eight mutants of L. monocytogenes and found that all high-level resistance strains showed increased expression of two putative β-glucoside-specific PTS genes. Additionally, these strains failed to synthesize the MptA subunit of the mannose-specific PTS, EIIMan. This suggests that spontaneous resistance to class IIa bacteriocins in L. monocytogenes arises through a single mechanism (downregulation of the Man-PTS gene) that causes two distinct changes in PTS expression. However, disruption of these genes in the resistant mutant did not confer sensitivity to pediocin. This indicates that increased expression of β-glucoside PTS permease is not a direct cause of resistance but is probably a regulatory consequence of acquired resistance through the abolition of mptACD expression . Preventing mptACD expression directly confers resistance. Expression of mptACD could be prevented by mutations in all the factors mentioned earlier, e.g., rpoN , manR, or mptACD . Since the IIC and IID subunits of the mptACD operon are likely membrane-bound, they were hypothesized to be potential targets for class IIa bacteriocins. When the mptACD operon of L. monocytogenes was expressed in an insensitive species like Lactococcus lactis , this strain became sensitive to various class IIa bacteriocins. Individual expression of each gene from the mptACD operon in Lactococcus lactis revealed that expressing mptC alone was enough to confer sensitivity. Therefore, the IIC subunit was proposed as the target molecule for class IIa bacteriocins . Both Tessema et al. and Kjos et al. confirmed findings by Gravesen et al. that the primary mechanism of resistance in L. monocytogenes involves the downregulation of Man-PTS gene expression. This downregulation, caused by the lack of a functional mptACD , reduces or eliminates receptor proteins, leading to high resistance levels. Furthermore, both studies identified additional resistance mechanisms. Tessema et al found that resistant strains exhibited changes in carbon catabolite control, likely mediated by mptACD , along with cell envelope modifications and bacteriocin efflux through the TAT system, contributing to the resistance in sakacin P-resistant strains. Kjos et al. noted that cells with intermediate resistance had high Man-PTS gene expression, similar to wild-type cells. This was linked to metabolic shifts and suggested changes in cell surface properties that affect bacteriocin-receptor interactions. 6.2. Resistance Due to Changes in the Cell Envelope 6.2.1. Resistance Due to Changes in the Cell Wall Gram-positive bacteria, including the pathogenic L. monocytogenes , are characterized by the presence of peptidoglycan in their cell walls. This crucial component is a polymer made of sugars and amino acids, forming a protective layer outside the plasma membrane, which provides structural strength and rigidity. Peptidoglycan contains two types of anionic polymers: teichoic acids (TAs), which are covalently attached to the peptidoglycan, and lipoteichoic acids (LTAs), which consist of polyphosphoglycerol substituted with a D-alanyl (D-Ala) ester, anchored in the membrane by their glycolipid component . Those components cause the cell wall to carry an anionic charge due to deprotonated phosphate groups . Thus, altering the surface charge of the target cell wall emerges as a critical defense strategy against cationic bacteriocins. Changing the bacterial surface charge is likely to impact the initial electrostatic interaction between the peptide and the membrane, which is crucial for pore formation . The dlt operon, consisting of four genes ( dltA , dltB , dltC, and dltD ), was characterized in the study by Abachin et al. . These genes are responsible for incorporating D-alanine residues into cell-wall-associated LTAs. A mutant deficient in D-alanine, created by inactivating the dltA gene (which encodes a cytoplasmic D-alanine-D-alanyl carrier protein ligase), exhibited increased susceptibility to cationic peptides such as nisin. The study by Vadyvaloo et al. also emphasized that decreasing the negative charge of the cell wall contributes to resistance. This reduction is achieved by increasing the D-alanine content in teichoic acids, which lowers the cell wall’s negative charge and, consequently, its susceptibility to bacteriocins. Gravesen et al. demonstrated that a notable decrease in the expression of dltA , dal , and dat genes can reduce the availability of D-alanine. This shortage affects the incorporation of D-alanine into LTAs, TAs, and peptidoglycan. Collins et al. identified the lmo1967 locus in L. monocytogenes as key for innate nisin resistance. This locus is a homolog of the tellurite resistance gene telA . Mutant analysis revealed that mutants were four times more susceptible to nisin and twice as susceptible to certain antibiotics and tellurite. This study was the first to associate the telA gene with resistance to antimicrobials targeting the cell envelope. 6.2.2. Changes in the Fatty Acid Composition of the Cell Membrane Research has consistently demonstrated that alterations in the surface charge of the cell wall significantly contribute to L. monocytogenes ’ resistance to cationic bacteriocins. Additionally, it is hypothesized that this bacterium might adopt various cell membrane modifications to further bolster its resistance . In the study by Vadyvaloo et al. , the researchers focused on the first mechanism involving cell membranes: the alteration of membrane fluidity. The study examined the relationship between leucocin A, a class IIa bacteriocin, and the composition of the major phospholipid, phosphatidylglycerol (PG), in both susceptible and resistant strains of L. monocytogenes. The analysis revealed that resistant strains had an increased ratio of unsaturated to saturated and short to long PG acyl chains. This shift towards PGs with shorter, unsaturated acyl chains increased membrane fluidity. This decrease may hinder the insertion of class IIa bacteriocins into the membrane and affect the stability of the pore complex, contributing to resistance. Membrane adaptation is likely just one of several mechanisms involved in resistance, and other mechanisms are necessary for complete resistance. Ming and Daeschel also observed that a nisin-resistant mutant of L. monocytogenes had a higher proportion of straight-chain fatty acids compared to its parent strain, which exhibited a greater amount of branched-chain fatty acids. In addition, the resistant strain showed less phosphatidylglycerol and cardiolipin than the wild-type . In L. monocytogenes ATCC 700302, which is resistant to nisin, researchers observed comparable alterations in membrane fatty acid composition, including an increase in long-chain fatty acids, a decrease in short-chain fatty acids, and a reduction in the C15/C17 ratio . The observed changes in fatty acid composition suggest a decrease in cytoplasmic membrane fluidity. This increased stiffness likely impedes nisin from penetrating the membrane. Vadyvaloo et al. explored another mechanism behind bacteriocin resistance in L. monocytogenes : the alteration of membrane surface charge. The cationic nature of peptides allows them to interact with negatively charged cell surfaces, leading to membrane permeabilization . Altering the bacterial surface charge can thus impact the electrostatic interaction between the peptide and membrane . One method of charge modulation is through L-lysinylation of TA and LTAs in the cell wall. Vadyvaloo et al. found that highly resistant strains showed increased lysinylation of membrane phospholipids. Normally, phospholipids such as L-lysyl-PG and L-lysyl-cardiolipin are negatively charged, but adding L-lysine to produce lysylphosphatidylglycerol, a basic phospholipid , changes their net charge to positive, reducing the anionic properties of cell permeability barriers and thus decreasing susceptibility to cationic antimicrobial compounds. Verheul et al. demonstrated that modifications in the cytoplasmic membrane composition could contribute to lantibiotic resistance in L. monocytogenes . In their study, a nisin-resistant mutant of L. monocytogenes Scott A, developed through exposure to increasing concentrations of nisin, showed reduced diphosphatidylglycerol and increased phosphatidylglycerol production compared to the parent strain. Nisin penetrates diphosphatidylglycerol lipid monolayers more effectively than other lipids, including phosphatidylglycerol; thus, the resistance in the mutant strain was linked to the decreased diphosphatidylglycerol content in its cytoplasmic membrane. Additionally, factors such as the zwitterionic phosphatidylethanolamine content in the phospholipids of L. monocytogenes can influence the net surface charge . The lysinylation process requires the MprF protein, a membrane-localized lysylphosphatidylglycerol synthetase encoded by the mprF gene . When there is a mutation in the mprF gene, it interferes with the incorporation of lysine into membrane phospholipids. This results in an increased negative charge of the cell envelope, making the bacteria more vulnerable to bacteriocins and other cationic antimicrobial peptides (CAMPs) . The study by Mandin et al. underscored the importance of VirR, a response regulator in the two-component signal transduction system (2CS) VirRS, in L. monocytogenes . VirRS system proteins are encoded by vir operon that includes a response regulator gene ( virR ) and a histidine kinase gene ( virS ). VirR, as revealed through transcriptomic approaches, positively regulates the transcription of 12 genes, including mprF and dltACD operon, both involved in defense against bacteriocin. It has been demonstrated that inactivating VirR increases bacterial susceptibility to bacteriocins . Additionally, the VirRS system in L. monocytogenes is influenced by alternative sigma factors, SigB, which contributes to resistance to bacteriocins. Several other 2CSs play a role in bacteriocin resistance. One notable example is the AnrAB, an ATP-binding cassette (ABC) transporter in L. monocytogenes , which not only contributes to innate bacteriocin resistance but also provides protection against bacitracin and beta-lactam antibiotics . After dltA and mprF , anrB is identified as the third VirRS-regulated locus in L. monocytogenes linked to nisin resistance . Additionally, expression studies have shown that AnrAB is regulated by RpoN . It is hypothesized that AnrAB, VirRS, and Lmo1746-Lmo1747 form an antimicrobial sensing and detoxification system similar to the VraDE-BraSR-BraDE circuit in Staphylococcus aureus . The genes lmo1746-lmo1747 , also known as virAB , encode a putative ABC transporter crucial for VirR activity. The expression of virAB is essential for nisin resistance . Cotter et al. and Bergholz et al. described another significant example, the LisRK two-component system. This system in L. monocytogenes not only helps the bacterium respond to acidic and oxidative stress but also plays a crucial role in nisin resistance and the pathogen’s inherent resistance to cephalosporin antibiotics. 6.3. Role of Cations in Resistance Against Bacteriocins The studies by Abee et al. and Crandall and Montville highlight the significance of divalent cations in stabilizing the cytoplasmic membrane of nisin-resistant cells. This stabilization could involve interactions between the cations and envelope components such as negatively charged teichoic acids; however, it can also involve interfering with nisin’s binding. Abee et al. found that divalent cations (Mg 2+ and Ca 2+ ) decreased the rate of potassium (K + ) efflux from whole cells of L. monocytogenes. Scott A. Crandall and Montville suggested that divalent and trivalent cations might inhibit the electrostatic interactions between the positively charged nisin molecules and the negatively charged phospholipid headgroups. Similar results were obtained by Kaur et al. . Kaur et al. found that adding divalent cations (Mg 2+ , Ca 2+ , and Mn 2+ ) significantly decreased the inhibitory effects of nisin, pediocin 34, and enterocin FH99 against L. monocytogenes . However, when EDTA was added, the inhibitory activity was restored, indicating that divalent cations likely interfere with the initial electrostatic interaction between the positively charged bacteriocin and the negatively charged membrane phospholipids. The study by Kaur et al. also observed that resistant L. monocytogenes cells tended to form aggregates. This aggregation may lead to biofilm formation, serving as an additional resistance mechanism by reducing the contact surface area with bacteriocins, making it more difficult for the antimicrobial compounds to exert their effects. Biofilm formation is one of the resistance strategies of L. monocytogenes against bacteriocins. In response to nisin exposure, L. monocytogenes transitions from a planktonic (free-floating) state to a sessile organization, forming biofilms to better withstand environmental stress. Sublethal concentrations of nisin trigger the upregulation of proteins linked to biofilm formation in this species . Liu et al. discovered that the cell surface of pediocin-resistant L. monocytogenes variants exhibited increased hydrophobicity, potentially leading to greater cell aggregate formation. Likewise, Martínez and Rodríguez found that nisin-resistant L. monocytogenes Lm41 mutant displayed higher hydrophobicity compared to its wild-type strain. 6.4. Cross Resistance Related to Growth Conditions Elements such as bacterial growth phase, temperature, pH, and nutrient availability can influence resistance gene expression and overall bacterial resistance. L. monocytogenes demonstrates remarkable adaptability to the tough conditions in food processing environments, highlighting the importance of studying how stress conditions collectively enhance its resistance to bacteriocins. The study by Begley et al. demonstrated a link between nisin resistance and the ability of bacteria to adapt to acidic environments, highlighting the crucial role of the glutamate decarboxylase (GAD) system. This system converts glutamate to γ-aminobutyrate (GABA) and carbon dioxide, facilitated by the enzymes GadD1, GadD2, and GadD3. This conversion also generates ATP, boosting the bacterial cell’s energy reserves. In the next stage, GABA is exported from the cell by the proteins GadT1 and GadT2. Research indicated that bacteria lacking the GadD1 gene struggled to survive in the presence of nisin, showing a 40% reduction in ATP levels; thus, GadD1 is proposed to play a key role in maintaining ATP levels, countering nisin’s harmful effects, and supporting bacterial survival . Jydegaard et al. investigated the impact of the growth phase, osmotic shock, and low-temperature shock on the resistance of L. monocytogenes to the bacteriocins nisin and pediocin PA-1. They found that the growth phase significantly impacted resistance, with stationary phase bacteria showing higher resistance to both bacteriocins compared to those in the exponential phase. Additionally, cultures exposed to osmotic stress (6.5% NaCl) and cold stress (5 °C for 60–80 min) exhibited increased tolerance. Research has sought to clarify this phenomenon. It is likely attributed to changes in the electrostatic interactions between bacteriocins and the cell surface when ion concentrations are higher . Additionally, increased osmolarity in the culture medium can alter cell morphology, leading to modifications in the cell envelope . De Martinis et al. investigated the influence of salt, pH, and temperature on the effectiveness of nisin against L. monocytogenes. The research found that at temperatures 20 °C and 30 °C, resistance to nisin was stable regardless of pH and salt concentration. At 10 °C, nisin resistance decreased with lower pH and salt concentrations. Interestingly, low salt levels (2–3.5%) seemed to protect L. monocytogenes at 10 °C, confirming earlier findings by Cole et al. about optimal salt concentrations for bacterial growth at low temperatures. This suggests that salt can help more nisin-resistant colonies survive in cold environments. Furthermore, the study showed that nisin resistance remained stable after repeated exposure, highlighting that relying solely on nisin as a preservative could lead to the development of stable resistant mutants. Therefore, nisin should be used as part of a multi-hurdle approach to food preservation . These reports were confirmed in the study by Bergholz et al. . This study examined cross-resistance in L. monocytogenes to nisin under salt stress and low-temperature conditions. They found that exposure to salt stress at low temperatures significantly increased the pathogen’s resistance to nisin. This stress increased the expression of genes related to nisin resistance, including the response regulator LiaRS. By constructing liaR deletion mutations in seven strains and exposing them to 6% NaCl, they found that wild-type strains exhibited a marked increase in nisin resistance after salt exposure . Conversely, liaR mutants were more sensitive, showing that LiaFSR induction provides cross-protection against nisin. Additionally, LiaR-regulated genes such as lmo1746 and telA contributed to this resistance. These findings suggest that environmental stresses similar to those found in foods can influence L. monocytogenes ’ resistance to antimicrobials such as nisin, emphasizing the need to consider potential cross-protective effects when applying control measures against this pathogen . 6.5. Cross-Resistance to Multiple Bacteriocins Using a combination of multiple bacteriocins simultaneously can help mitigate the risk of resistance in L. monocytogenes. Therefore, it is crucial to study the potential for cross-resistance between different bacteriocins . The findings on cross-resistance in L. monocytogenes present varied outcomes reported no cross-resistance between nisin ( Lactococcus lactis ), pediocin PA-1 ( Pediococcus acidilactici ) and bavaricin A ( Lactobacillus bavaricus ), whereas Crandall and Montville reported that nisin resistance in L. monocytogenes conferred cross-resistance to pediocin PA-1. Similarly, Gravesen et al. identified cross-resistance between nisin and subclass IIa bacteriocins such as pediocin PA-1 and leucocin A. Another study by Crandall and Montville showed that a strain of L. monocytogenes exhibited cross-resistance to nisin, pediocin PA-1, and leuconocin S. Cross-resistance has been observed not only between different classes of bacteriocins but also within the same class. Crandall and Montville also observed complete cross-resistance among subclass IIa bacteriocins such as pediocin PA-1, leucocin A, and carnobacteriocin B2. As previously noted, for many bacteriocins to be effective in eliminating bacteria, they need to bind to specific receptors on the target cell’s surface. These receptors act as docking sites, allowing the bacteriocin to attach and exert its lethal effects. Without the presence of these specific receptors, the bacteriocins cannot effectively interact with the bacterial cell, rendering them less effective or even ineffective. The phenomenon of resistance to nisin, a class I bacteriocin, was described by Gravesen et al. . In this study, the researchers aimed to identify loci responsible for nisin resistance in L. monocytogenes . Their analysis revealed that the nisin-resistant mutant exhibited increased expression of a protein with strong homology to the glycosyltransferase domain of high-molecular-weight penicillin-binding proteins (PBPs). These membrane-bound proteins are crucial for cell wall biosynthesis through peptidoglycan chain extension and cross-linking. It was speculated that the increased expression and production of this protein might partially shield lipid II in the plasma membrane, thus reducing nisin’s efficacy by impeding its access to the binding site. The other authors observed a similar effect . Resistance to subclass IIa bacteriocins in L. monocytogenes often involves changes in receptor expression. This resistance can arise through either the reduced expression or even loss of the Man-PTS system, a key element involved in sugar uptake. According to Vadyvaloo et al. , wild-type strains demonstrated faster growth in the presence of glucose, whereas the class IIa bacteriocin-resistant strains exhibited quicker growth in the absence of glucose. The variations in growth between the wild-type and resistant mutants on different carbohydrates suggest that the sugar metabolism pathways might be altered in the resistant strains. The man-PTS system is encoded by the mptACD operon. The level of mptACD expression has been shown to correlate with the level of bacteriocin sensitivity . Survival of bacteria under stress conditions requires rapid changes in gene expression, which are controlled by the association of different alternative sigma factors. Previous studies reviewed by Bastos et al. have identified four types of sigma factors in L. monocytogenes : σB (SigB), σH , RpoD, and RpoN. The study by Robichon et al. linked resistance to subclass IIa bacteriocins to the regulatory gene rpoN , which encodes the alternative sigma factor σ54. It was proposed that the transcription factor σ54 might regulate the expression of the Man-PTS receptor, as mutants of L. monocytogenes lacking rpoN showed resistance to mesentericin Y105 (produced by Leuconostoc mesenteroides ) and related subclass IIa bacteriocins. σ54 is known to be involved in the regulation of PTS expression. The study by Dalet et al. discovered that the mannose family activator ManR and the PTS permease are essential for L. monocytogenes sensitivity to mesentericin Y105. σ54 activates the mptACD operon ( mptA , mptC , and mptD genes), which codes for EIIAB, EIIC, and EIID in L. monocytogenes , alongside ManR, the transcriptional activator for σ54 . Disruptions in the mptA or mptD genes led to resistance, and further in-frame deletions in the mptD gene were also linked to mesentericin Y105 resistance, suggesting that a specific domain of the MptD subunit is involved in target recognition by the bacteriocin. These findings were the first to suggest that EIIMan could serve as a receptor for subclass IIa bacteriocins . Mutations in rpoN led to the loss of mptACD expression, resulting in resistance to mesentericin Y105 . Similarly, mutations in ManR (encoded by manR ) rendered the cells resistant to subclass IIa bacteriocins . Both regulatory proteins, RpoN and ManR, are crucial for the active transcription of genes encoding the subclass IIa bacteriocin receptor. In the works of Gravesen et al. and Ramnath et al. , two different changes in PTS expression were correlated with the development of resistance to class IIa bacteriocins in L. monocytogenes . In the study by Ramnath et al. , a mutant of L. monocytogenes resistant to leucocin A (produced by Leuconostoc gelidum ) was found to lack the IIAB subunit of the mannose PTS permease. Conversely, Gravesen et al. identified that L. monocytogenes mutants resistant to pediocin PA-1 exhibited overexpression of the β-glucoside PTS permease. Gravesen et al. examined eight mutants of L. monocytogenes and found that all high-level resistance strains showed increased expression of two putative β-glucoside-specific PTS genes. Additionally, these strains failed to synthesize the MptA subunit of the mannose-specific PTS, EIIMan. This suggests that spontaneous resistance to class IIa bacteriocins in L. monocytogenes arises through a single mechanism (downregulation of the Man-PTS gene) that causes two distinct changes in PTS expression. However, disruption of these genes in the resistant mutant did not confer sensitivity to pediocin. This indicates that increased expression of β-glucoside PTS permease is not a direct cause of resistance but is probably a regulatory consequence of acquired resistance through the abolition of mptACD expression . Preventing mptACD expression directly confers resistance. Expression of mptACD could be prevented by mutations in all the factors mentioned earlier, e.g., rpoN , manR, or mptACD . Since the IIC and IID subunits of the mptACD operon are likely membrane-bound, they were hypothesized to be potential targets for class IIa bacteriocins. When the mptACD operon of L. monocytogenes was expressed in an insensitive species like Lactococcus lactis , this strain became sensitive to various class IIa bacteriocins. Individual expression of each gene from the mptACD operon in Lactococcus lactis revealed that expressing mptC alone was enough to confer sensitivity. Therefore, the IIC subunit was proposed as the target molecule for class IIa bacteriocins . Both Tessema et al. and Kjos et al. confirmed findings by Gravesen et al. that the primary mechanism of resistance in L. monocytogenes involves the downregulation of Man-PTS gene expression. This downregulation, caused by the lack of a functional mptACD , reduces or eliminates receptor proteins, leading to high resistance levels. Furthermore, both studies identified additional resistance mechanisms. Tessema et al found that resistant strains exhibited changes in carbon catabolite control, likely mediated by mptACD , along with cell envelope modifications and bacteriocin efflux through the TAT system, contributing to the resistance in sakacin P-resistant strains. Kjos et al. noted that cells with intermediate resistance had high Man-PTS gene expression, similar to wild-type cells. This was linked to metabolic shifts and suggested changes in cell surface properties that affect bacteriocin-receptor interactions. 6.2.1. Resistance Due to Changes in the Cell Wall Gram-positive bacteria, including the pathogenic L. monocytogenes , are characterized by the presence of peptidoglycan in their cell walls. This crucial component is a polymer made of sugars and amino acids, forming a protective layer outside the plasma membrane, which provides structural strength and rigidity. Peptidoglycan contains two types of anionic polymers: teichoic acids (TAs), which are covalently attached to the peptidoglycan, and lipoteichoic acids (LTAs), which consist of polyphosphoglycerol substituted with a D-alanyl (D-Ala) ester, anchored in the membrane by their glycolipid component . Those components cause the cell wall to carry an anionic charge due to deprotonated phosphate groups . Thus, altering the surface charge of the target cell wall emerges as a critical defense strategy against cationic bacteriocins. Changing the bacterial surface charge is likely to impact the initial electrostatic interaction between the peptide and the membrane, which is crucial for pore formation . The dlt operon, consisting of four genes ( dltA , dltB , dltC, and dltD ), was characterized in the study by Abachin et al. . These genes are responsible for incorporating D-alanine residues into cell-wall-associated LTAs. A mutant deficient in D-alanine, created by inactivating the dltA gene (which encodes a cytoplasmic D-alanine-D-alanyl carrier protein ligase), exhibited increased susceptibility to cationic peptides such as nisin. The study by Vadyvaloo et al. also emphasized that decreasing the negative charge of the cell wall contributes to resistance. This reduction is achieved by increasing the D-alanine content in teichoic acids, which lowers the cell wall’s negative charge and, consequently, its susceptibility to bacteriocins. Gravesen et al. demonstrated that a notable decrease in the expression of dltA , dal , and dat genes can reduce the availability of D-alanine. This shortage affects the incorporation of D-alanine into LTAs, TAs, and peptidoglycan. Collins et al. identified the lmo1967 locus in L. monocytogenes as key for innate nisin resistance. This locus is a homolog of the tellurite resistance gene telA . Mutant analysis revealed that mutants were four times more susceptible to nisin and twice as susceptible to certain antibiotics and tellurite. This study was the first to associate the telA gene with resistance to antimicrobials targeting the cell envelope. 6.2.2. Changes in the Fatty Acid Composition of the Cell Membrane Research has consistently demonstrated that alterations in the surface charge of the cell wall significantly contribute to L. monocytogenes ’ resistance to cationic bacteriocins. Additionally, it is hypothesized that this bacterium might adopt various cell membrane modifications to further bolster its resistance . In the study by Vadyvaloo et al. , the researchers focused on the first mechanism involving cell membranes: the alteration of membrane fluidity. The study examined the relationship between leucocin A, a class IIa bacteriocin, and the composition of the major phospholipid, phosphatidylglycerol (PG), in both susceptible and resistant strains of L. monocytogenes. The analysis revealed that resistant strains had an increased ratio of unsaturated to saturated and short to long PG acyl chains. This shift towards PGs with shorter, unsaturated acyl chains increased membrane fluidity. This decrease may hinder the insertion of class IIa bacteriocins into the membrane and affect the stability of the pore complex, contributing to resistance. Membrane adaptation is likely just one of several mechanisms involved in resistance, and other mechanisms are necessary for complete resistance. Ming and Daeschel also observed that a nisin-resistant mutant of L. monocytogenes had a higher proportion of straight-chain fatty acids compared to its parent strain, which exhibited a greater amount of branched-chain fatty acids. In addition, the resistant strain showed less phosphatidylglycerol and cardiolipin than the wild-type . In L. monocytogenes ATCC 700302, which is resistant to nisin, researchers observed comparable alterations in membrane fatty acid composition, including an increase in long-chain fatty acids, a decrease in short-chain fatty acids, and a reduction in the C15/C17 ratio . The observed changes in fatty acid composition suggest a decrease in cytoplasmic membrane fluidity. This increased stiffness likely impedes nisin from penetrating the membrane. Vadyvaloo et al. explored another mechanism behind bacteriocin resistance in L. monocytogenes : the alteration of membrane surface charge. The cationic nature of peptides allows them to interact with negatively charged cell surfaces, leading to membrane permeabilization . Altering the bacterial surface charge can thus impact the electrostatic interaction between the peptide and membrane . One method of charge modulation is through L-lysinylation of TA and LTAs in the cell wall. Vadyvaloo et al. found that highly resistant strains showed increased lysinylation of membrane phospholipids. Normally, phospholipids such as L-lysyl-PG and L-lysyl-cardiolipin are negatively charged, but adding L-lysine to produce lysylphosphatidylglycerol, a basic phospholipid , changes their net charge to positive, reducing the anionic properties of cell permeability barriers and thus decreasing susceptibility to cationic antimicrobial compounds. Verheul et al. demonstrated that modifications in the cytoplasmic membrane composition could contribute to lantibiotic resistance in L. monocytogenes . In their study, a nisin-resistant mutant of L. monocytogenes Scott A, developed through exposure to increasing concentrations of nisin, showed reduced diphosphatidylglycerol and increased phosphatidylglycerol production compared to the parent strain. Nisin penetrates diphosphatidylglycerol lipid monolayers more effectively than other lipids, including phosphatidylglycerol; thus, the resistance in the mutant strain was linked to the decreased diphosphatidylglycerol content in its cytoplasmic membrane. Additionally, factors such as the zwitterionic phosphatidylethanolamine content in the phospholipids of L. monocytogenes can influence the net surface charge . The lysinylation process requires the MprF protein, a membrane-localized lysylphosphatidylglycerol synthetase encoded by the mprF gene . When there is a mutation in the mprF gene, it interferes with the incorporation of lysine into membrane phospholipids. This results in an increased negative charge of the cell envelope, making the bacteria more vulnerable to bacteriocins and other cationic antimicrobial peptides (CAMPs) . The study by Mandin et al. underscored the importance of VirR, a response regulator in the two-component signal transduction system (2CS) VirRS, in L. monocytogenes . VirRS system proteins are encoded by vir operon that includes a response regulator gene ( virR ) and a histidine kinase gene ( virS ). VirR, as revealed through transcriptomic approaches, positively regulates the transcription of 12 genes, including mprF and dltACD operon, both involved in defense against bacteriocin. It has been demonstrated that inactivating VirR increases bacterial susceptibility to bacteriocins . Additionally, the VirRS system in L. monocytogenes is influenced by alternative sigma factors, SigB, which contributes to resistance to bacteriocins. Several other 2CSs play a role in bacteriocin resistance. One notable example is the AnrAB, an ATP-binding cassette (ABC) transporter in L. monocytogenes , which not only contributes to innate bacteriocin resistance but also provides protection against bacitracin and beta-lactam antibiotics . After dltA and mprF , anrB is identified as the third VirRS-regulated locus in L. monocytogenes linked to nisin resistance . Additionally, expression studies have shown that AnrAB is regulated by RpoN . It is hypothesized that AnrAB, VirRS, and Lmo1746-Lmo1747 form an antimicrobial sensing and detoxification system similar to the VraDE-BraSR-BraDE circuit in Staphylococcus aureus . The genes lmo1746-lmo1747 , also known as virAB , encode a putative ABC transporter crucial for VirR activity. The expression of virAB is essential for nisin resistance . Cotter et al. and Bergholz et al. described another significant example, the LisRK two-component system. This system in L. monocytogenes not only helps the bacterium respond to acidic and oxidative stress but also plays a crucial role in nisin resistance and the pathogen’s inherent resistance to cephalosporin antibiotics. Gram-positive bacteria, including the pathogenic L. monocytogenes , are characterized by the presence of peptidoglycan in their cell walls. This crucial component is a polymer made of sugars and amino acids, forming a protective layer outside the plasma membrane, which provides structural strength and rigidity. Peptidoglycan contains two types of anionic polymers: teichoic acids (TAs), which are covalently attached to the peptidoglycan, and lipoteichoic acids (LTAs), which consist of polyphosphoglycerol substituted with a D-alanyl (D-Ala) ester, anchored in the membrane by their glycolipid component . Those components cause the cell wall to carry an anionic charge due to deprotonated phosphate groups . Thus, altering the surface charge of the target cell wall emerges as a critical defense strategy against cationic bacteriocins. Changing the bacterial surface charge is likely to impact the initial electrostatic interaction between the peptide and the membrane, which is crucial for pore formation . The dlt operon, consisting of four genes ( dltA , dltB , dltC, and dltD ), was characterized in the study by Abachin et al. . These genes are responsible for incorporating D-alanine residues into cell-wall-associated LTAs. A mutant deficient in D-alanine, created by inactivating the dltA gene (which encodes a cytoplasmic D-alanine-D-alanyl carrier protein ligase), exhibited increased susceptibility to cationic peptides such as nisin. The study by Vadyvaloo et al. also emphasized that decreasing the negative charge of the cell wall contributes to resistance. This reduction is achieved by increasing the D-alanine content in teichoic acids, which lowers the cell wall’s negative charge and, consequently, its susceptibility to bacteriocins. Gravesen et al. demonstrated that a notable decrease in the expression of dltA , dal , and dat genes can reduce the availability of D-alanine. This shortage affects the incorporation of D-alanine into LTAs, TAs, and peptidoglycan. Collins et al. identified the lmo1967 locus in L. monocytogenes as key for innate nisin resistance. This locus is a homolog of the tellurite resistance gene telA . Mutant analysis revealed that mutants were four times more susceptible to nisin and twice as susceptible to certain antibiotics and tellurite. This study was the first to associate the telA gene with resistance to antimicrobials targeting the cell envelope. Research has consistently demonstrated that alterations in the surface charge of the cell wall significantly contribute to L. monocytogenes ’ resistance to cationic bacteriocins. Additionally, it is hypothesized that this bacterium might adopt various cell membrane modifications to further bolster its resistance . In the study by Vadyvaloo et al. , the researchers focused on the first mechanism involving cell membranes: the alteration of membrane fluidity. The study examined the relationship between leucocin A, a class IIa bacteriocin, and the composition of the major phospholipid, phosphatidylglycerol (PG), in both susceptible and resistant strains of L. monocytogenes. The analysis revealed that resistant strains had an increased ratio of unsaturated to saturated and short to long PG acyl chains. This shift towards PGs with shorter, unsaturated acyl chains increased membrane fluidity. This decrease may hinder the insertion of class IIa bacteriocins into the membrane and affect the stability of the pore complex, contributing to resistance. Membrane adaptation is likely just one of several mechanisms involved in resistance, and other mechanisms are necessary for complete resistance. Ming and Daeschel also observed that a nisin-resistant mutant of L. monocytogenes had a higher proportion of straight-chain fatty acids compared to its parent strain, which exhibited a greater amount of branched-chain fatty acids. In addition, the resistant strain showed less phosphatidylglycerol and cardiolipin than the wild-type . In L. monocytogenes ATCC 700302, which is resistant to nisin, researchers observed comparable alterations in membrane fatty acid composition, including an increase in long-chain fatty acids, a decrease in short-chain fatty acids, and a reduction in the C15/C17 ratio . The observed changes in fatty acid composition suggest a decrease in cytoplasmic membrane fluidity. This increased stiffness likely impedes nisin from penetrating the membrane. Vadyvaloo et al. explored another mechanism behind bacteriocin resistance in L. monocytogenes : the alteration of membrane surface charge. The cationic nature of peptides allows them to interact with negatively charged cell surfaces, leading to membrane permeabilization . Altering the bacterial surface charge can thus impact the electrostatic interaction between the peptide and membrane . One method of charge modulation is through L-lysinylation of TA and LTAs in the cell wall. Vadyvaloo et al. found that highly resistant strains showed increased lysinylation of membrane phospholipids. Normally, phospholipids such as L-lysyl-PG and L-lysyl-cardiolipin are negatively charged, but adding L-lysine to produce lysylphosphatidylglycerol, a basic phospholipid , changes their net charge to positive, reducing the anionic properties of cell permeability barriers and thus decreasing susceptibility to cationic antimicrobial compounds. Verheul et al. demonstrated that modifications in the cytoplasmic membrane composition could contribute to lantibiotic resistance in L. monocytogenes . In their study, a nisin-resistant mutant of L. monocytogenes Scott A, developed through exposure to increasing concentrations of nisin, showed reduced diphosphatidylglycerol and increased phosphatidylglycerol production compared to the parent strain. Nisin penetrates diphosphatidylglycerol lipid monolayers more effectively than other lipids, including phosphatidylglycerol; thus, the resistance in the mutant strain was linked to the decreased diphosphatidylglycerol content in its cytoplasmic membrane. Additionally, factors such as the zwitterionic phosphatidylethanolamine content in the phospholipids of L. monocytogenes can influence the net surface charge . The lysinylation process requires the MprF protein, a membrane-localized lysylphosphatidylglycerol synthetase encoded by the mprF gene . When there is a mutation in the mprF gene, it interferes with the incorporation of lysine into membrane phospholipids. This results in an increased negative charge of the cell envelope, making the bacteria more vulnerable to bacteriocins and other cationic antimicrobial peptides (CAMPs) . The study by Mandin et al. underscored the importance of VirR, a response regulator in the two-component signal transduction system (2CS) VirRS, in L. monocytogenes . VirRS system proteins are encoded by vir operon that includes a response regulator gene ( virR ) and a histidine kinase gene ( virS ). VirR, as revealed through transcriptomic approaches, positively regulates the transcription of 12 genes, including mprF and dltACD operon, both involved in defense against bacteriocin. It has been demonstrated that inactivating VirR increases bacterial susceptibility to bacteriocins . Additionally, the VirRS system in L. monocytogenes is influenced by alternative sigma factors, SigB, which contributes to resistance to bacteriocins. Several other 2CSs play a role in bacteriocin resistance. One notable example is the AnrAB, an ATP-binding cassette (ABC) transporter in L. monocytogenes , which not only contributes to innate bacteriocin resistance but also provides protection against bacitracin and beta-lactam antibiotics . After dltA and mprF , anrB is identified as the third VirRS-regulated locus in L. monocytogenes linked to nisin resistance . Additionally, expression studies have shown that AnrAB is regulated by RpoN . It is hypothesized that AnrAB, VirRS, and Lmo1746-Lmo1747 form an antimicrobial sensing and detoxification system similar to the VraDE-BraSR-BraDE circuit in Staphylococcus aureus . The genes lmo1746-lmo1747 , also known as virAB , encode a putative ABC transporter crucial for VirR activity. The expression of virAB is essential for nisin resistance . Cotter et al. and Bergholz et al. described another significant example, the LisRK two-component system. This system in L. monocytogenes not only helps the bacterium respond to acidic and oxidative stress but also plays a crucial role in nisin resistance and the pathogen’s inherent resistance to cephalosporin antibiotics. The studies by Abee et al. and Crandall and Montville highlight the significance of divalent cations in stabilizing the cytoplasmic membrane of nisin-resistant cells. This stabilization could involve interactions between the cations and envelope components such as negatively charged teichoic acids; however, it can also involve interfering with nisin’s binding. Abee et al. found that divalent cations (Mg 2+ and Ca 2+ ) decreased the rate of potassium (K + ) efflux from whole cells of L. monocytogenes. Scott A. Crandall and Montville suggested that divalent and trivalent cations might inhibit the electrostatic interactions between the positively charged nisin molecules and the negatively charged phospholipid headgroups. Similar results were obtained by Kaur et al. . Kaur et al. found that adding divalent cations (Mg 2+ , Ca 2+ , and Mn 2+ ) significantly decreased the inhibitory effects of nisin, pediocin 34, and enterocin FH99 against L. monocytogenes . However, when EDTA was added, the inhibitory activity was restored, indicating that divalent cations likely interfere with the initial electrostatic interaction between the positively charged bacteriocin and the negatively charged membrane phospholipids. The study by Kaur et al. also observed that resistant L. monocytogenes cells tended to form aggregates. This aggregation may lead to biofilm formation, serving as an additional resistance mechanism by reducing the contact surface area with bacteriocins, making it more difficult for the antimicrobial compounds to exert their effects. Biofilm formation is one of the resistance strategies of L. monocytogenes against bacteriocins. In response to nisin exposure, L. monocytogenes transitions from a planktonic (free-floating) state to a sessile organization, forming biofilms to better withstand environmental stress. Sublethal concentrations of nisin trigger the upregulation of proteins linked to biofilm formation in this species . Liu et al. discovered that the cell surface of pediocin-resistant L. monocytogenes variants exhibited increased hydrophobicity, potentially leading to greater cell aggregate formation. Likewise, Martínez and Rodríguez found that nisin-resistant L. monocytogenes Lm41 mutant displayed higher hydrophobicity compared to its wild-type strain. Elements such as bacterial growth phase, temperature, pH, and nutrient availability can influence resistance gene expression and overall bacterial resistance. L. monocytogenes demonstrates remarkable adaptability to the tough conditions in food processing environments, highlighting the importance of studying how stress conditions collectively enhance its resistance to bacteriocins. The study by Begley et al. demonstrated a link between nisin resistance and the ability of bacteria to adapt to acidic environments, highlighting the crucial role of the glutamate decarboxylase (GAD) system. This system converts glutamate to γ-aminobutyrate (GABA) and carbon dioxide, facilitated by the enzymes GadD1, GadD2, and GadD3. This conversion also generates ATP, boosting the bacterial cell’s energy reserves. In the next stage, GABA is exported from the cell by the proteins GadT1 and GadT2. Research indicated that bacteria lacking the GadD1 gene struggled to survive in the presence of nisin, showing a 40% reduction in ATP levels; thus, GadD1 is proposed to play a key role in maintaining ATP levels, countering nisin’s harmful effects, and supporting bacterial survival . Jydegaard et al. investigated the impact of the growth phase, osmotic shock, and low-temperature shock on the resistance of L. monocytogenes to the bacteriocins nisin and pediocin PA-1. They found that the growth phase significantly impacted resistance, with stationary phase bacteria showing higher resistance to both bacteriocins compared to those in the exponential phase. Additionally, cultures exposed to osmotic stress (6.5% NaCl) and cold stress (5 °C for 60–80 min) exhibited increased tolerance. Research has sought to clarify this phenomenon. It is likely attributed to changes in the electrostatic interactions between bacteriocins and the cell surface when ion concentrations are higher . Additionally, increased osmolarity in the culture medium can alter cell morphology, leading to modifications in the cell envelope . De Martinis et al. investigated the influence of salt, pH, and temperature on the effectiveness of nisin against L. monocytogenes. The research found that at temperatures 20 °C and 30 °C, resistance to nisin was stable regardless of pH and salt concentration. At 10 °C, nisin resistance decreased with lower pH and salt concentrations. Interestingly, low salt levels (2–3.5%) seemed to protect L. monocytogenes at 10 °C, confirming earlier findings by Cole et al. about optimal salt concentrations for bacterial growth at low temperatures. This suggests that salt can help more nisin-resistant colonies survive in cold environments. Furthermore, the study showed that nisin resistance remained stable after repeated exposure, highlighting that relying solely on nisin as a preservative could lead to the development of stable resistant mutants. Therefore, nisin should be used as part of a multi-hurdle approach to food preservation . These reports were confirmed in the study by Bergholz et al. . This study examined cross-resistance in L. monocytogenes to nisin under salt stress and low-temperature conditions. They found that exposure to salt stress at low temperatures significantly increased the pathogen’s resistance to nisin. This stress increased the expression of genes related to nisin resistance, including the response regulator LiaRS. By constructing liaR deletion mutations in seven strains and exposing them to 6% NaCl, they found that wild-type strains exhibited a marked increase in nisin resistance after salt exposure . Conversely, liaR mutants were more sensitive, showing that LiaFSR induction provides cross-protection against nisin. Additionally, LiaR-regulated genes such as lmo1746 and telA contributed to this resistance. These findings suggest that environmental stresses similar to those found in foods can influence L. monocytogenes ’ resistance to antimicrobials such as nisin, emphasizing the need to consider potential cross-protective effects when applying control measures against this pathogen . Using a combination of multiple bacteriocins simultaneously can help mitigate the risk of resistance in L. monocytogenes. Therefore, it is crucial to study the potential for cross-resistance between different bacteriocins . The findings on cross-resistance in L. monocytogenes present varied outcomes reported no cross-resistance between nisin ( Lactococcus lactis ), pediocin PA-1 ( Pediococcus acidilactici ) and bavaricin A ( Lactobacillus bavaricus ), whereas Crandall and Montville reported that nisin resistance in L. monocytogenes conferred cross-resistance to pediocin PA-1. Similarly, Gravesen et al. identified cross-resistance between nisin and subclass IIa bacteriocins such as pediocin PA-1 and leucocin A. Another study by Crandall and Montville showed that a strain of L. monocytogenes exhibited cross-resistance to nisin, pediocin PA-1, and leuconocin S. Cross-resistance has been observed not only between different classes of bacteriocins but also within the same class. Crandall and Montville also observed complete cross-resistance among subclass IIa bacteriocins such as pediocin PA-1, leucocin A, and carnobacteriocin B2. It is vital to grasp both the causes and mechanisms behind resistance development for effective bacteriocin management. Strategies are essential to minimize resistance risk while ensuring balanced bacteriocin use to maintain effectiveness. Simultaneously, monitoring bacterial populations for resistance is crucial for early detection and prompt responses . First, inappropriate use should be limited. Bacteriocins need to be used precisely and in a controlled manner to avoid overuse, thereby reducing the pressure on bacteria to develop resistance . Second, optimizing doses and schedules is crucial to maximize efficacy while minimizing the risk of selecting resistant strains. Additionally, rotating or cyclic use of different bacteriocins can reduce selection pressure, making it harder for bacteria to develop resistance . In food technology, combining bacteriocins with other preservatives also can be an effective strategy . By employing multiple bacteriocins with different mechanisms of action at the same time, the approach reduces the risk of resistance. Bacteria would need to develop resistance to several bacteriocins simultaneously, making it significantly more challenging for them to survive. For instance, combining nisin and pediocin PA-1 significantly lowered the occurrence of resistance development in L. monocytogenes . Moreover, the combined use of bacteriocins significantly reduced MIC, effectively lowering the required inhibitory dosage . Additionally, a multiple-hurdle preservation strategy, combining bacteriocins with other methods, can reduce selection pressure on bacteria . Kaur et al. discovered that L. monocytogenes mutants resistant to nisin, pediocin 34, and enterocin FH99 did not gain resistance to low pH, sodium chloride, or sodium nitrite; instead, these mutants were as sensitive or even more sensitive than the wild-type strain. Bergholz et al. indicated that salt stress at low temperatures may offer cross-protection to L. monocytogenes against nisin. Therefore, it is important to consider the potential for cross-protective effects when utilizing various hurdle technologies for food preservation. Other approaches involve developing new bacteriocins with unique mechanisms . This includes creating genetically engineered bacteriocins with improved stability, greater efficacy, and a lower likelihood of inducing resistance . For example, nisin A has been modified to nisin V through a single amino acid substitution, resulting in increased efficacy against L. monocytogenes compared to nisin A . Considering all approaches, bioengineering remains one of the most promising methods for enhancing the antimicrobial activity of bacteriocins . Monitoring and surveillance of resistance are critical. Regular checks on bacterial populations for resistance to bacteriocins allow for early detection and rapid response. Understanding the mechanisms and genetic determinants of resistance is vital for effective monitoring. To sum up, a holistic approach is necessary to minimize bacterial resistance to bacteriocins. Collaboration between scientists, the food industry, and healthcare is essential for managing and maintaining the effectiveness of bacteriocins in combating pathogenic bacteria . L. monocytogenes is a formidable foodborne pathogen due to its ability to adapt to harsh food processing conditions and its persistence in food products. Bacteriocins, particularly those produced by LAB, show promise as biocontrol agents to enhance food safety by eliminating L. monocytogenes . However, increasing resistance to these bacteriocins poses a significant challenge. Research on resistance mechanisms has primarily been conducted in laboratory settings . Since bacteriocins are mainly used for biopreserving food, further studies in food model systems are crucial to understanding resistance frequency and its impact on food microflora. The composition of food systems can affect bacteriocin activity and resistance development . Exploring the genetic determinants of resistance mechanisms can help develop strategies to enhance bacterial susceptibility and design new bacteriocins that circumvent resistance . Since resistance can spread to other bacteriocins, particularly within the same subclass, it is vital to avoid widespread use across multiple industries and limit usage to where they are most effective . Like antibiotic resistance, bacteriocin resistance can be equally detrimental, so careful consideration is necessary when using bacteriocins in daily applications. |
Environmental risk factors associated with the presence of | 43c40f9a-196f-4035-85a1-61160a435994 | 9469944 | Microbiology[mh] | Buruli ulcer (BU) is a neglected tropical disease, caused by the environmental pathogen Mycobacterium ulcerans (MU). Affecting all age groups, the disease causes severe destructive lesions of skin and soft tissue and results in significant morbidity, sometimes leading to long term disability and deformity . Endemic to more than 30 countries, the highest disease burden is in sub-Saharan Africa . Case numbers have increased in Australia , most markedly in the temperate, southern state of Victoria where case numbers increased from 32 in 2010 to a peak of 340 in 2018, with 217 cases in 2020 and 208 cases reported up to October 2021 . The endemic area is also expanding geographically, with new disease hotspots reported both in Geelong, Victoria’s second largest city and most recently in Melbourne’s inner suburbs . Previous studies have identified several risk factors and potential transmission routes. In Africa, BU foci are often associated with natural water bodies and in Victoria, an outbreak was linked to exposure to a contaminated water irrigation system at a golf course . In a questionnaire-based case control study in one Victorian hotspot, the risk of having BU was found to be increased in people who did not wash minor skin wounds immediately, did not frequently wear insect repellent or long trousers outdoors, and who received mosquito bites to the lower legs or arms . Molecular detection of MU in mosquitoes collected from several localities within the Victorian endemic area , and the demonstration that Ae . notoscriptus can act as mechanical vectors for BU in a mouse model suggests that mosquitoes may be involved with BU transmission in Victoria. Several studies have also suggested that MU may be a zoonotic pathogen in Victoria. Evidence of infection and disease has been reported in several native and non-native mammals [ – ], but there is increasing evidence that two common possum species may be acting as reservoir hosts in south east Australia . Both common brushtail (BT; Trichosurus vulpecula ) and common ringtail (RT; Pseudocheirus peregrinus ) possums can develop BU and possum feces are the environmental sample type most commonly PCR positive for MU in Victorian endemic areas . There is evidence of a clear geographic correlation between the presence of human cases and MU - positive possum feces . Here we present the environmental results from the first systematic, large-scale case-control study to encompass almost the entire Victorian endemic area. As the acquisition of MU infection is presumed to often occur at a case’s own residence, the environmental surveys were conducted at participants’ residential properties. By assessing the environmental characteristics of participants’ gardens and the distribution of MU in different environmental sample types (i.e. mammalian feces, biting insects, soil, plants and water) within these, we establish: (1) which environmental sample types are more predictive of the molecular presence of MU at the scale of the individual property (including predicting the presence of viable bacteria); and (2) what environmental features make a property more likely to be positive for MU or more likely to contain a human case of BU. These findings will aid public education around this disease and inform the development of intervention strategies to prevent disease.
Numbers sampled: Participants/Field surveys/samples/assays Of the 3,433 individuals contacted, 283/497 (56.9%) cases and 520/2936 (17.7%) controls participated in the case-control study. Of these, 256 (90.5%) case participants and 458 (88.1%) control participants agreed to be contacted about the property environmental surveys. Property environmental field surveys were conducted at 230 properties, comprising 115 case and 115 control properties, located across 20 postcodes ( ). Although lower than the original proposed samples size of 120 cases and 120 controls, this provided 85% power to detect a difference in the proportion of properties with environmental MU detection (environmental prevalence 25% at case properties, versus 10% at control properties, OR 3.0). A second field survey was carried out within three to nine months of the initial survey at 27 properties (13 case properties; 14 control properties), all located within three of the most severely impacted postcodes. A total of 4,363 environmental samples (excluding insect samples) were collected during the field surveys, 3,907 from initial surveys and 456 from return surveys ( ). Of these, 475 (10.9%) samples were ‘ IS2404 detected’ (highest for feces (20.5%) and soil (13.2%)) and 237 (5.4%) samples were ‘confirmed’, most commonly for feces in general (13.3%), and for fox and RT possum feces in particular (20.0% and 16.7% respectively)) ( ). None of the negative control Mains water samples were positive (i.e. IS2404 detected). Of ‘ IS2404 detected’ samples, considerably higher proportions of feces were also ‘confirmed’ compared to other sample types. Sixty-seven samples (1.5% of all samples) were ‘viable’. At least one sample from each sample type was IS2404 detected and confirmed, however only feces were ‘viable’–most frequently from RT possums (64 samples) but also from two BT possums and a fox. For the initial surveys, 157/230 (68.3%) properties were IS2404 detected, of which 103 (44.8%) were confirmed and 46 (20.0%) viable. For the second (return) surveys, 16/27 (59.3%) were IS2404 detected, nine (33.3%) confirmed and two (7.4%) viable. For initial visits case properties were visited between 45 to 296 days after disease notification (mean = 145 days; median = 130 days). Among case properties, the interval between case notification date and field collection date did not affect the odds of a property testing IS2404 detected, confirmed or viable ( ). At individual properties, a maximum of 10 samples were IS2404 detected, six samples were confirmed, and four samples were viable. Of the 20 postcodes in which properties were surveyed, at least one property was IS2404 detected in 17 postcodes, confirmed in 13 postcodes, and viable in ten postcodes ( ). Comparison of PCR assays Excluding insect samples (due to a single positive), IS2404 cycle threshold (C T) values differed significantly between the sample types (one-way ANOVA, p<0.001), although the ‘between sample type’ variance was considerably lower than the ‘within sample type’ variance (26.7% and 73.3% respectively). Fecal C T values were significantly lower (suggesting higher bacterial loads) (mean = 34.50) than those for all other sample types (mean = 38.23 combined, Tukey-Kramer test, p<0.05). There were no significant differences in C T values between the other sample types (means: plant = 38.66; soil = 38.0; water = 38.21). Lower IS2404 C T values were observed for confirmed samples (median = 33.69; IQR = 7.20) than unconfirmed samples (median = 38.79; IQR = 1.11), and for viable samples (median = 29.27; IQR = 6.77) versus non-viable samples (median = 38.08; IQR = 3.71). Only 8/238 (3.3%) of IS2404 -positive samples that were unconfirmed had C T values of <35, whilst 94/394 (23.9%) of IS2404 -positive samples that were considered not-viable had C T values of <35. Only 17.9% of viable samples had C T values >35. Positive samples by sample type associated with case properties Case properties were more likely to be ‘ IS2404 detected’ and ‘confirmed’ than control properties when considering all samples and when restricted to fecal samples or RT possum feces only ( ). No significant relationships were observed when the analysis was restricted to any other sample types or for the viability assay.
Of the 3,433 individuals contacted, 283/497 (56.9%) cases and 520/2936 (17.7%) controls participated in the case-control study. Of these, 256 (90.5%) case participants and 458 (88.1%) control participants agreed to be contacted about the property environmental surveys. Property environmental field surveys were conducted at 230 properties, comprising 115 case and 115 control properties, located across 20 postcodes ( ). Although lower than the original proposed samples size of 120 cases and 120 controls, this provided 85% power to detect a difference in the proportion of properties with environmental MU detection (environmental prevalence 25% at case properties, versus 10% at control properties, OR 3.0). A second field survey was carried out within three to nine months of the initial survey at 27 properties (13 case properties; 14 control properties), all located within three of the most severely impacted postcodes. A total of 4,363 environmental samples (excluding insect samples) were collected during the field surveys, 3,907 from initial surveys and 456 from return surveys ( ). Of these, 475 (10.9%) samples were ‘ IS2404 detected’ (highest for feces (20.5%) and soil (13.2%)) and 237 (5.4%) samples were ‘confirmed’, most commonly for feces in general (13.3%), and for fox and RT possum feces in particular (20.0% and 16.7% respectively)) ( ). None of the negative control Mains water samples were positive (i.e. IS2404 detected). Of ‘ IS2404 detected’ samples, considerably higher proportions of feces were also ‘confirmed’ compared to other sample types. Sixty-seven samples (1.5% of all samples) were ‘viable’. At least one sample from each sample type was IS2404 detected and confirmed, however only feces were ‘viable’–most frequently from RT possums (64 samples) but also from two BT possums and a fox. For the initial surveys, 157/230 (68.3%) properties were IS2404 detected, of which 103 (44.8%) were confirmed and 46 (20.0%) viable. For the second (return) surveys, 16/27 (59.3%) were IS2404 detected, nine (33.3%) confirmed and two (7.4%) viable. For initial visits case properties were visited between 45 to 296 days after disease notification (mean = 145 days; median = 130 days). Among case properties, the interval between case notification date and field collection date did not affect the odds of a property testing IS2404 detected, confirmed or viable ( ). At individual properties, a maximum of 10 samples were IS2404 detected, six samples were confirmed, and four samples were viable. Of the 20 postcodes in which properties were surveyed, at least one property was IS2404 detected in 17 postcodes, confirmed in 13 postcodes, and viable in ten postcodes ( ).
Excluding insect samples (due to a single positive), IS2404 cycle threshold (C T) values differed significantly between the sample types (one-way ANOVA, p<0.001), although the ‘between sample type’ variance was considerably lower than the ‘within sample type’ variance (26.7% and 73.3% respectively). Fecal C T values were significantly lower (suggesting higher bacterial loads) (mean = 34.50) than those for all other sample types (mean = 38.23 combined, Tukey-Kramer test, p<0.05). There were no significant differences in C T values between the other sample types (means: plant = 38.66; soil = 38.0; water = 38.21). Lower IS2404 C T values were observed for confirmed samples (median = 33.69; IQR = 7.20) than unconfirmed samples (median = 38.79; IQR = 1.11), and for viable samples (median = 29.27; IQR = 6.77) versus non-viable samples (median = 38.08; IQR = 3.71). Only 8/238 (3.3%) of IS2404 -positive samples that were unconfirmed had C T values of <35, whilst 94/394 (23.9%) of IS2404 -positive samples that were considered not-viable had C T values of <35. Only 17.9% of viable samples had C T values >35.
Case properties were more likely to be ‘ IS2404 detected’ and ‘confirmed’ than control properties when considering all samples and when restricted to fecal samples or RT possum feces only ( ). No significant relationships were observed when the analysis was restricted to any other sample types or for the viability assay.
Mean property size varied between the different study areas (ANOVA, p<0.05). Sampled properties in the Mornington Peninsula (n = 148 properties, postcodes 3930–3944, mean property size 1087m 2 ) were larger than those in Bayside (n = 56, postcodes 3190–3199, mean 695m 2 ) but did not differ significantly from sampled properties in Bellarine (n = 22, postcodes 3223–3227, mean = 890m 2 ) or the Surf Coast (n = 4, postcode 3231, mean = 677m 2 ). No significant differences were found between area and altitude, with average property elevation ranging between 13.5m (Bellarine) to 22.75m (Bayside). Univariate analysis of property characteristics and study outcomes ( IS2404 detected, confirmed, viable and case status) Univariate analyses are presented in (unadjusted OR) and . Means and proportions for each environmental characteristic are presented in . Due to the close association between garden type and the presence of selected native plant species, the former was not included in the multivariable models, despite properties with native gardens having higher odds of being IS2404 detected, confirmed and viable. Due to low sample size, the presence of rabbit feces was also not included in the multivariable models, even though properties with rabbit feces were more likely to have viable MU at the property. Two significant relationships that were observed in univariate analyses but not in multivariable analyses were the positive association between Melaleuca lanceolata and IS2404 detected, confirmed and viable properties, and the higher soil salinity associated with IS2404 detected and confirmed properties. Multivariable analysis of property characteristics and study outcomes ( IS2404 detected , confirmed, viable and case status) In multivariable analysis, the presence of selected plant species was associated with both increased odds of property status ( Leptospermum laevigatum for confirmed properties; M . lanceolata (Moonah) for viable properties) and decreased odds of property status ( M . lanceolata (Moonah) for case properties; Leucopogon parviflorus (coastal beard heath) for confirmed properties; and Pittosporum (cheesewoods) for IS2404 properties). Likewise, while presence of RT possums was associated with increased odds of a property being confirmed, BT possums were associated with decreased odds of a property being IS2404 detected. It is also important to note that all viable properties had RT possum feces present and thus adjustment for this factor was not included in the model. Increased property size and more alkaline soil were associated with being a confirmed property. Lower altitude was associated with a property being confirmed, while presence of overhead powerlines was associated with a property being IS2404 detected, confirmed and a case property. Return/Follow-up property field surveys A total of 27 properties were visited twice. These represented 11.7% of the total properties visited and 21.1% of all the properties visited in the three postcodes in which these return properties were located. Property status remained the same between visits for 19 (70.4%) properties based on IS2404 results, 22 (81.5%) for confirmed results and 23 (85.5%) for viability results ( ). At properties that remained positive, RT possum feces were the main sample type that remained positive at 10/14 (71.4%) properties for IS2404 , 8/9 (88.9%) for confirmed and 2/2 (100%) for viable. Other sample types that remained positive included 3 soil samples (21.4%) and 1 rodent feces (7.1%) for IS2404 , and 1 soil samples (11.1%) for confirmed. Under the assumption that properties with positive status at both visits were positive for the entire period between the two sampling visits, we documented one property that remained IS2404 detected for at least 8.7 months, which was also the longest time between visits for any property. Of properties that remained IS2404 detected, half (7/14) had an interval between sampling of over six months. For nine confirmed properties, five properties remained confirmed for over six months, with the longest sampling interval of 7.9 months. The two properties that remained positive for the viability assay were positive for over six months. Only for the IS2404 assay did any property become positive, with two properties that were initially IS2404 negative becoming positive at the second visit (7.4%; ); all other changes of property status were from positive at the first visit, to negative at the second visit ( ).
IS2404 detected, confirmed, viable and case status) Univariate analyses are presented in (unadjusted OR) and . Means and proportions for each environmental characteristic are presented in . Due to the close association between garden type and the presence of selected native plant species, the former was not included in the multivariable models, despite properties with native gardens having higher odds of being IS2404 detected, confirmed and viable. Due to low sample size, the presence of rabbit feces was also not included in the multivariable models, even though properties with rabbit feces were more likely to have viable MU at the property. Two significant relationships that were observed in univariate analyses but not in multivariable analyses were the positive association between Melaleuca lanceolata and IS2404 detected, confirmed and viable properties, and the higher soil salinity associated with IS2404 detected and confirmed properties.
IS2404 detected , confirmed, viable and case status) In multivariable analysis, the presence of selected plant species was associated with both increased odds of property status ( Leptospermum laevigatum for confirmed properties; M . lanceolata (Moonah) for viable properties) and decreased odds of property status ( M . lanceolata (Moonah) for case properties; Leucopogon parviflorus (coastal beard heath) for confirmed properties; and Pittosporum (cheesewoods) for IS2404 properties). Likewise, while presence of RT possums was associated with increased odds of a property being confirmed, BT possums were associated with decreased odds of a property being IS2404 detected. It is also important to note that all viable properties had RT possum feces present and thus adjustment for this factor was not included in the model. Increased property size and more alkaline soil were associated with being a confirmed property. Lower altitude was associated with a property being confirmed, while presence of overhead powerlines was associated with a property being IS2404 detected, confirmed and a case property.
A total of 27 properties were visited twice. These represented 11.7% of the total properties visited and 21.1% of all the properties visited in the three postcodes in which these return properties were located. Property status remained the same between visits for 19 (70.4%) properties based on IS2404 results, 22 (81.5%) for confirmed results and 23 (85.5%) for viability results ( ). At properties that remained positive, RT possum feces were the main sample type that remained positive at 10/14 (71.4%) properties for IS2404 , 8/9 (88.9%) for confirmed and 2/2 (100%) for viable. Other sample types that remained positive included 3 soil samples (21.4%) and 1 rodent feces (7.1%) for IS2404 , and 1 soil samples (11.1%) for confirmed. Under the assumption that properties with positive status at both visits were positive for the entire period between the two sampling visits, we documented one property that remained IS2404 detected for at least 8.7 months, which was also the longest time between visits for any property. Of properties that remained IS2404 detected, half (7/14) had an interval between sampling of over six months. For nine confirmed properties, five properties remained confirmed for over six months, with the longest sampling interval of 7.9 months. The two properties that remained positive for the viability assay were positive for over six months. Only for the IS2404 assay did any property become positive, with two properties that were initially IS2404 negative becoming positive at the second visit (7.4%; ); all other changes of property status were from positive at the first visit, to negative at the second visit ( ).
This study’s findings cast some light on (1) which environmental sample types are more predictive of MU presence at the household scale, namely RT possum, and (2) which environmental features make a property more likely to be positive for MU or more likely to contain a human case of BU. For the latter, the average MU property is a larger property located at lower altitudes with soil that is slightly alkaline. It has overhead powerlines and contains native vegetation, particularly coastal tea trees, which in turn support a healthy population of RT possums. In contrast, the ‘ideal’ case property has overhead powerlines present, is less likely to contain Moonahs, but more likely to contain MU-positive wild mammals, especially RT possums. The findings from this study support the hypothesis that BU may be a zoonotic disease in Australia, with native mammals, specifically species of possum, acting as reservoir hosts . Consistent with previous findings, fecal samples were the sample type most commonly positive for MU and had the highest bacterial loads . This was also the sample type most likely to remain positive at return properties and the only sample type that appeared to contain viable bacteria. In Australia, numerous species of both native and introduced mammals including feces from RT possum, BT possum and rodents have tested positive for MU in the past, . Alongside these species, our study also identified MU positive fecal samples from wild foxes ( Vulpes vulpes ) and rabbits ( Oryctolagus cuniculus ); a first report for both species, although laboratory rabbits have been infected experimentally . Fox feces collected during this study had the highest proportion of positives in IS2404 and confirmatory assays, suggesting that foxes may be playing a previously overlooked role in MU circulation. As foxes likely predate on possums, the presence of MU DNA in their feces is perhaps unsurprising and suggests that other predators of possums, such as the powerful owl would also be worthy of investigation. However, RT possum feces were the sample type with the second highest proportion of positives by both these assays, the primary sample type positive by the viability assay and the sample type most commonly collected in this study (>28% of all samples collected). Only feces from RT possums, BT possums and a single fox were found to be viable, suggesting that all three species may be involved in the transmission of MU. How and if humans acquire MU from this source remains unknown, although contamination of the skin with infected fecal material, followed by a puncturing injury (similar to the mechanism described in ) could represent a potential transmission route. RT possums were more likely to be found at confirmed and viable properties and their feces were more likely to be positive for MU at case properties. Previous studies have also found a correlation between the geographic location of cases and the presence of positive possum feces , supporting the reservoir host hypothesis. The findings from this study suggest that the presence of RT possums per se at a property does not increase the risk of the residents contracting BU, but the presence of RT possums positive for MU does (although it should also be noted that MU-positive RT possum feces and other samples were also found at many control properties). This intrinsically makes sense but requires effective communication to local residents to discourage the indiscriminate removal or translocation of possums, which are a protected species in Victoria. In the UK, removal of badgers as part of bovine tuberculosis (TB) control measures led to increased bovine TB prevalence in some regions. This was hypothesized to be because culling disrupted badger social organization, leading to long-distance movement and dispersal of individual badgers, resulting in increased TB transmission among badgers [ – ]. Increases in Leptospira carriage in rat populations subjected to indiscriminate lethal control methods in Vancouver, Canada have also been attributed to altered social structure and subsequent increases in aggressive interactions . As possums are territorial, removal or disturbance of individual resident animals impacts both social interactions and movement patterns , which may in part help explain the shifting dynamics of this disease and the expansion of the Victorian endemic area. Movement of MU into previously unaffected areas may also be facilitated by infected foxes, which demonstrate considerably larger home ranges than RT possums: individual foxes in a similar coastal habitat in New South Wales were found to have a mean home range of 135 ha , compared to <1ha for RT possums . However, further research into the role of foxes in BU transmission is needed. It is thought that MU can also persist outside of a vertebrate host, although the duration and the environmental conditions required have not been well defined . Overall, soil was the second most commonly positive sample type, and particular soil characteristics were associated with positive properties. It is possible that the higher conductivity, salinity and alkalinity detected at these properties may enhance environmental survival of MU and/or aid transmission between hosts. The link between MU and slightly alkaline soil was unexpected as these bacteria have been associated with mildly acidic pH conditions in two aquatic communities in Cameroon . Under laboratory conditions MU also appears to grow better at mildly acidic pH, although growth can also occur under mildly alkaline conditions . It is possible that in soil (in contrast to water), other biotic factors may interact with pH to make alkaline conditions more favorable to MU. However, as only a minority of IS2404 positive soil samples were confirmed positive and none were considered viable, the detection of MU in soil may represent the presence of DNA from non-viable, degrading MU. If this is the case, then these environmental conditions may favor the preservation of MU DNA rather than bacterial survival. There seemed to be little association between MU and water at the scale analyzed in this study. Very few water sources returned IS2404 positive results and only a single water source was confirmed positive (from a bucket). While this is consistent with the findings of one previous environmental survey in the region, which also found low rates of MU positivity in soil and water , other local studies have identified water sources in communal areas to be contaminated with MU, sometimes for considerable periods of time . There was also no association between property status and the number of water sources present or the presence of bore water. This suggests that in Victoria, at least at the scale of individual properties, water plays a limited role in determining the distribution of MU. Infection through puncturing injuries received from plants, biting insects and other objects contaminated with MU has also been hypothesized as a transmission pathway to humans . Relatively few insects were screened in this study making it difficult to assess associations with cases. However, one confirmed mosquito ( Aedes notoscriptus ) was detected in a case property, consistent with MU mosquito positivity reported in previous field surveys in this region . However, no association with mosquito or March fly presence and property status was observed. In addition, few plants tested positive by IS2404 for MU (32 spiky plants and five plants identified as possum food source plants) and only four samples were confirmed positive: one bromeliad ( Aechmea sp .), one rose ( Rosa sp .) and two yuccas ( Yucca sp .). There was also no association between any of the most common spiky plant types and either case or positive properties. This suggests that plants, similar to water, are unlikely to be a common source of infection in Victoria. However, the presence of certain native plant species was associated with the presence of MU at properties. Coastal tea tree ( L . laevigatum ) and Moonah ( M . lanceolata ) are both indigenous to parts of the Mornington and Bellarine Peninsulas , and are utilized heavily by possum species for denning and as food sources . Interestingly, Moonahs were less likely to be found at case properties, although this may be due to the tendency of local residents (particularly those personally affected by MU) to discourage possums from visiting their properties through environmental modification due to the perception that possums are carriers of these bacteria. Certainly, the gardens of some properties visited by the researchers had been re-landscaped or modified by their owners post BU diagnosis (K Blasdell, personal observation). As gardens containing native or mixed vegetation were more likely to be positive for MU than those containing mainly non-native vegetation, this suggests that native environments may promote better survival of the bacteria, potentially because they appear to support denser populations of native mammalian hosts, such as possums. To persist, possums require a suitable area of habitat containing sufficient resources. Habitat patches below a certain size (such as most urban and suburban gardens) are unlikely to provide these requirements unless they are well connected to other similar patches . For example, individual BT possums in Melbourne, Australia regularly foraged in several residential gardens despite denning in urban forest fragments , whilst in New Zealand, BT possum occupancy of urban gardens decreased with increasing housing density and decreasing green cover . Assuming that RT possums respond in a similar way, this may explain the association between larger properties and positive status. However, this could also be a geographic effect, as properties surveyed in the Mornington Peninsula (the current epicenter of BU in Victoria/Australia) were larger than those surveyed closer to Melbourne (Bayside area). Overhead powerlines were more likely to be found at IS2404 detected, confirmed and case properties. As possums regularly use overhead powerlines to travel around urban areas (K Blasdell, personal observation), this feature might promote connectivity between properties and facilitate the presence of these potential hosts. Similar to our study, BU prevalence was found to increase with decreasing elevation in Benin, with the authors proposing that MU survival might be promoted by the wetter conditions often found at lower altitudes . Although return surveys were only conducted at a small proportion of properties, the findings suggest that MU bacteria can remain at a specific location for a considerable period of time (>6 months). This has also been found in Cameroon, where a village water source remained positive for over two years . However, as each property was only sampled at two time points, it is possible that undetected changes may have occurred at properties during that interval, and additionally that a property might remain positive for MU for longer than the maximum 8.7 months observed here. Although it is unknown what factors changed between sampling points for those properties where MU status did alter, some environmental changes were observed at some of these properties that may have impacted the presence and survivability of MU. For example, at one property that became IS2404 positive at the return visit, de-vegetation and construction of a new house on the neighboring plot, which had previously been vacant and covered in native flora, may have resulted in the movement of infected wildlife onto the sampled plot. Most properties changed from positive to negative, which may suggest that the environmental disease risk in this region decreased slightly over the study period. At individual properties this may be because the resident infected possum (or other host) dies and is replaced by a non-infected individual, although this requires further exploration. However, two properties did become positive by IS2404 , demonstrating this is a dynamic situation. Study limitations The restriction of this study to environmental assessments of residential properties, based on the assumption that these are common locations of MU acquisition, means that links to environmental features relevant outside of these residences may have been missed. People often interact with the outside environment in their garden in a more prolonged and intensive way than other outside environments, leading to the assumption that residences represent a high exposure risk. However, this will not be true of everyone and at least some infections are likely to have been acquired outside of the residence, where other factors may play a role. One such factor could be the role played by larger water bodies, which are a common feature of both recreational and conserved areas. At least one previous Victorian outbreak has been associated with a water source in a communal area (a golf course irrigation system) , suggesting that by restricting the study to residences, the role of water sources may have been underestimated. Due to logistical reasons, another limitation of the study was the restriction placed on the number of samples collected and tested from each garden. Whilst 20 (or fewer) samples were sufficient for many gardens, more samples could have been collected from larger and more complex gardens, so some signal may have been lost. Despite this, we believe that most sample type associations are likely to have been detected due to the large number of samples and properties tested during this study. Although our findings suggest that MU may persist at a property for considerable time periods, again, for logistical reasons we were unable to return to most properties or to assess properties more than twice. To fully understand how MU persists at a location over time, a more detailed longitudinal study would be required, with samples collected both at multiple time points and more regularly. Another limitation of the study relates to the viability results and the sensitivity of the assay used to assess this. This assay is considerably less sensitive than the IS2404 assay and therefore may result in false negatives for samples containing lower bacterial loads (i.e. non-fecal samples). The results obtained from this assay may therefore underrepresent the number of samples and range of sample types that contain viable bacteria. A more sensitive RNA-based assay would need to be developed to address this issue. Finally, it is difficult to fully assess what risk the environmental sample types identified in the study actually pose to human health, without including a human behavioral component. However, it is an important starting point for both scientists and residents living in BU affected areas to understand where MU may be present and thus where it can potentially be acquired from. As at least some of these sources are likely to pose a risk of transmission, it is better to assume that all sample types with MU identified pose some risk and provide this information accordingly. While not reported here, human behavioral impacts on BU disease risk will be assessed through the analysis of the questionnaires collected as part of this case-control study ( to be published separately), which will hopefully help to further refine our understanding of the health risk. Conclusions This first large-scale, systematic, environmental case-control study of BU in Victoria has identified which environmental sample types are most likely to be MU-positive at residential properties (i.e. RT possum feces) and which environmental features are associated with MU-positive and BU case properties. The presence of RT possums, especially MU-infected animals, is a common theme for all of the above, providing additional evidence to support the hypothesis that MU is a zoonotic pathogen, at least in the Victorian endemic area. This study has also generated several additional novel findings, including the first evidence from Australia that certain environmental samples may contain viable MU bacteria. The detection of MU in rabbits and foxes, along with evidence of viability in one fox fecal sample, indicate that previously overlooked mammal species may also contribute to the circulation of this pathogen. Although caution should be taken around modifying native vegetation based on the finding that case properties are less likely to contain one indigenous plant species, the association between both native vegetation and overhead powerlines and MU presence are both novel findings and may be useful in the development of future intervention strategies.
The restriction of this study to environmental assessments of residential properties, based on the assumption that these are common locations of MU acquisition, means that links to environmental features relevant outside of these residences may have been missed. People often interact with the outside environment in their garden in a more prolonged and intensive way than other outside environments, leading to the assumption that residences represent a high exposure risk. However, this will not be true of everyone and at least some infections are likely to have been acquired outside of the residence, where other factors may play a role. One such factor could be the role played by larger water bodies, which are a common feature of both recreational and conserved areas. At least one previous Victorian outbreak has been associated with a water source in a communal area (a golf course irrigation system) , suggesting that by restricting the study to residences, the role of water sources may have been underestimated. Due to logistical reasons, another limitation of the study was the restriction placed on the number of samples collected and tested from each garden. Whilst 20 (or fewer) samples were sufficient for many gardens, more samples could have been collected from larger and more complex gardens, so some signal may have been lost. Despite this, we believe that most sample type associations are likely to have been detected due to the large number of samples and properties tested during this study. Although our findings suggest that MU may persist at a property for considerable time periods, again, for logistical reasons we were unable to return to most properties or to assess properties more than twice. To fully understand how MU persists at a location over time, a more detailed longitudinal study would be required, with samples collected both at multiple time points and more regularly. Another limitation of the study relates to the viability results and the sensitivity of the assay used to assess this. This assay is considerably less sensitive than the IS2404 assay and therefore may result in false negatives for samples containing lower bacterial loads (i.e. non-fecal samples). The results obtained from this assay may therefore underrepresent the number of samples and range of sample types that contain viable bacteria. A more sensitive RNA-based assay would need to be developed to address this issue. Finally, it is difficult to fully assess what risk the environmental sample types identified in the study actually pose to human health, without including a human behavioral component. However, it is an important starting point for both scientists and residents living in BU affected areas to understand where MU may be present and thus where it can potentially be acquired from. As at least some of these sources are likely to pose a risk of transmission, it is better to assume that all sample types with MU identified pose some risk and provide this information accordingly. While not reported here, human behavioral impacts on BU disease risk will be assessed through the analysis of the questionnaires collected as part of this case-control study ( to be published separately), which will hopefully help to further refine our understanding of the health risk.
This first large-scale, systematic, environmental case-control study of BU in Victoria has identified which environmental sample types are most likely to be MU-positive at residential properties (i.e. RT possum feces) and which environmental features are associated with MU-positive and BU case properties. The presence of RT possums, especially MU-infected animals, is a common theme for all of the above, providing additional evidence to support the hypothesis that MU is a zoonotic pathogen, at least in the Victorian endemic area. This study has also generated several additional novel findings, including the first evidence from Australia that certain environmental samples may contain viable MU bacteria. The detection of MU in rabbits and foxes, along with evidence of viability in one fox fecal sample, indicate that previously overlooked mammal species may also contribute to the circulation of this pathogen. Although caution should be taken around modifying native vegetation based on the finding that case properties are less likely to contain one indigenous plant species, the association between both native vegetation and overhead powerlines and MU presence are both novel findings and may be useful in the development of future intervention strategies.
Ethics The study was approved by the Victorian Department of Health (DH) Human Research Ethics Committee and the CSIRO Health and Medical Human Research Ethics Committee (application no. 10/18). Access to electoral information for medical research purposes was granted by the Australian Electoral Commission. Written informed consent was obtained for the property environmental field surveys. Study area The study was conducted in the known Buruli ulcer-endemic area of Victoria, Australia. This is primarily located around Port Phillip Bay, with the main concentration of recognized cases from the Mornington and Bellarine Peninsulas and the Melbourne regional (Bayside) area. Recruitment All laboratory confirmed BU cases aged ≥18 years notified to the Victorian DH between 12 th June 2018 and 11 th June 2020 were eligible to participate. Potential control participants (aged ≥18 years) were randomly selected from either the 2017 Victorian Population Health Survey (VPHS) or the Australian Electoral Roll. Participants were asked to complete a paper-based questionnaire ( to be reported elsewhere). Environmental surveys were conducted on a subset of case and control properties within the endemic area. Case properties had at least one resident with a laboratory-confirmed diagnosis of BU within the study period (12 th June 2018 to 11 th June 2020). Control properties had no residents diagnosed with BU within the study period or reported as having had BU prior to the study period. Cases who completed the study questionnaire were purposely selected by postcode to ensure a representative spread of sampling across the affected area based on reported BU prevalence (i.e. more properties were surveyed in postcodes with more cases). Control properties were then purposely selected based on postcode and matched 1:1 to case properties. The aim was to enroll 120 cases and 120 controls in the study, which would provide 87% power to detect a difference in the proportion of properties with environmental MU detection (environmental prevalence 25% at case-properties versus 10% at control-properties, OR 3.0). Property environmental field surveys Prior to an environmental field survey being conducted at a property, geocoordinates (latitude and longitude), altitude (all from https://www.google.com/maps ) and approximate property size ( https://www.freemaptools.com/area-calculator.htm ) were recorded and an outline of the property, including buildings was prepared. During the property visit, additional information was recorded, including presence of any key plant species (four indigenous species as representatives of native habitat ( Melaleuca lanceolata , Leptospermum laevigatum , Leucopogon parviflorus , Allocasuarina verticillata/littoralis ), and one non-native species commonly found in native gardens ( Pittosporum spp .; and File), garden type and samples collected ( and Figs, and Files). Garden type was visually categorized as Non-native (>60% non-native vegetation), Mixed (40–60% native/non-native) or Native (>60% native vegetation) based on visual estimation of the overall garden by two surveyors ( ). Five different sample types were collected as outlined in and File, namely soil, water, plants ( ), feces and biting insects. Soil texture was determined as per standard protocols ( https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0008/168866/texture-salinity.pdf ). Up to 20 environmental samples were collected per property. Two soil samples were collected per property, biting insects were collected opportunistically and the three remaining sample types were selected using a stratified random approach to try and represent what was present in the garden (see for details). In addition, a mains water sample was also collected from each property as a negative control, to validate sample collection techniques and detect potential contamination. The total number of observable water sources on a property was recorded, although samples were not always collected from all sources. The presence of mosquito larvae in any of the water sources was also recorded. To establish if MU positive properties remain positive and MU negative properties remain negative over time, a proportion of properties were visited twice. Return visits were made opportunistically, based on participant availability and willingness to participate. For these properties first visits were made between 5th August 2019 and 3rd March 2020, whilst return visits were made between 19th March 2020 and 23rd June 2020. The interval between visits was impacted by work and travel restrictions imposed during the COVID-19 pandemic. The number of days between visits varied between 92 days (~3 months) and 261 days (~8.7 months), showing a right-skewed distribution with a median of 147 days (~4.9 months; IQR = 92 days). For all return environmental field surveys at a property, the property outline from the initial visit was used to enable the same sample types to be collected from the same locations. Any different samples collected and significant environmental changes between the two field surveys were recorded. Samples collected during field surveys were transported at room temperature to the laboratory and maintained at either 4°C (soil samples for bulk density, pH and conductivity testing) or -70°C (all other samples) until processed. Laboratory processing and analysis Soil samples were processed individually to determine soil bulk density (g/cm 3 ), pH, conductivity (μS/cm) and salinity class. For soil bulk density, 50cm 3 of each soil sample was weighed before and after heating in an oven at 105°C for two hours and the dry weight divided by the soil volume. For pH and conductivity, soil was resuspended in distilled water at a 1:5 ratio, before testing with a VisionPlus pH/EC80 meter (Jenco). Soil salinity class was determined based on the meter reading for conductivity with reference to the soil texture type determined during the field survey ( https://www.agric.wa.gov.au/soil-salinity/measuring-soil-salinity ). All samples from the five sample types were processed individually. Prior to nucleic acid extraction samples were thawed and individually transferred to 2ml tubes containing approximately 2.4g of a mixture of 2.3mm and 0.5mm zirconia/silica beads (Bio Spec Products, Inc.). The quantity of DNA/RNA Shield (Zymo) and sample added was dependent on sample type. Water samples were added in 500μl volumes to 500μl of DNA/RNA Shield (Zymo). For plant, soil and fecal samples, approximately 0.2g (plants) or 0.1g (feces/soil) was added to 1ml of DNA/RNA Shield (Zymo). All samples were homogenized at 6500rpm for 30sec on a Precellys 24 (Bertin Technologies) and clarified for 5 mins at 16,000g. Total nucleic acid was extracted from 200μl of the cleared supernatant using the Kingfisher Flex benchtop automated extraction instrument (ThermoFisher) and the Quick DNA/RNA MagBead Pathogen kit (Zymo) as per the manufacturer’s instructions. All samples were subjected to the IS2404 real-time PCR assay, which is routinely used for the molecular diagnosis of MU infection in clinical samples and has been used previously on environmental samples . As this assay detects other mycolactone-producing Mycobacteria in addition to MU, any sample that tested positive by this assay (C T <40, threshold 0.02) was subjected to confirmatory testing using two MU specific assays ( IS2606 and KR ; ) as well as an RNA-based assay targeting the MU 16S rRNA to assess viability (i.e. the presence of RNA presumed to be generated by viable bacteria) . This viability assay can also detect some strains of M . marinum , although it is unlikely that this species would be present in most of the sample types collected. Although all samples testing positive by the IS2404 assay were subjected to the viability assay, only samples positive by this latter assay as well as all three DNA-based assays (i.e. IS2404 , IS2606 and KR assays) were considered viable. Based on the results of these assays, all samples were classified as negative ( IS2404 not detected or C T ≥40); IS2404 detected (C T <40, threshold 0.02); confirmed (MU detected by both IS2606 and KR assays as well as the ‘ IS2404 detected’); or viable (MU 16S rRNA detected as well as ‘confirmed’) ( ). A property was assigned an ‘ IS2404 not detected’ ‘status if IS2404 was not detected in any samples collected from that property or was classified as IS2404 detected / confirmed / viable if any samples collected from that property met these definitions (N.B. a ‘viable’ property would also be both ‘ IS2404 detected’ and ‘confirmed’; a ‘confirmed’ property would also be ‘ IS2404 detected’). Statistical analysis The relationship between the time from DH notification of BU to the time of environmental surveys for case properties (in 10-week intervals) with the property status study outcomes relating to the detection of MU was examined using generalised estimating equations (binomial distribution and logit link function) regression models to account for repeat visits to the same property. Chi-square tests were used to investigate if MU positive samples (overall and by sample type and sub-type; for IS2404 detected, confirmed and viable status) were more likely to be present at case properties versus control properties. ANOVA was used to identify differences in the environmental characteristics (property size and elevation) of properties in the different geographic localities (Mornington Peninsula, Bellarine Peninsula, Bayside and Surf coast) and to identify differences in IS2404 C T values between different sample types. We investigated relationships between each of the property outcomes ( IS2404 detected, confirmed, viable and case status) with environmental variables, the full list of which can be found in . For initial (univariate) analysis Fisher’s Exact (where expected values ≤5) and chi-square tests were used to compare categorical variables, and either Student’s t-test or one-way ANOVA with a post-hoc Tukey Kramer test were used to compare differences in mean values of continuous variables. Descriptive statistical tests were conducted using pre-prepared spreadsheets available from http://www.biostathandbook.com . For details of the specific test used for each environmental variable, please refer to . Logistic regression models were used to estimate the strength of the relationships between each of the selected environmental characteristics and i) properties with one or more sample positive for MU ( IS2404 detected, confirmed or viable), or ii) case status of the property in separate univariable and multivariable models with results expressed as unadjusted or adjusted odds ratios (OR) and 95% confidence intervals (95%CI). Multivariable models included all potentially associated characteristics, being variables that had an association at P<0.1 in the univariate analysis and which were identified in 30 or more properties. Models were checked for collinearity; garden type was omitted a priori due to the close association with individual plant species. Covariates in the models included the presence of plant species ( Melaleuca lanceolata , Leptospermum laevigatum , Leucopogon parviflorus , Pittosporum spp . and Spiky aloe succulents), the presence of animal faeces from ringtail possums, brushtail possums and rodents, property size, presence of overhead power lines, altitude, soil pH, soil salinity and the use of bore water, with consistent adjustment across models for each property status. Regression models were conducted using Stata 15 (Statacorp).
The study was approved by the Victorian Department of Health (DH) Human Research Ethics Committee and the CSIRO Health and Medical Human Research Ethics Committee (application no. 10/18). Access to electoral information for medical research purposes was granted by the Australian Electoral Commission. Written informed consent was obtained for the property environmental field surveys.
The study was conducted in the known Buruli ulcer-endemic area of Victoria, Australia. This is primarily located around Port Phillip Bay, with the main concentration of recognized cases from the Mornington and Bellarine Peninsulas and the Melbourne regional (Bayside) area.
All laboratory confirmed BU cases aged ≥18 years notified to the Victorian DH between 12 th June 2018 and 11 th June 2020 were eligible to participate. Potential control participants (aged ≥18 years) were randomly selected from either the 2017 Victorian Population Health Survey (VPHS) or the Australian Electoral Roll. Participants were asked to complete a paper-based questionnaire ( to be reported elsewhere). Environmental surveys were conducted on a subset of case and control properties within the endemic area. Case properties had at least one resident with a laboratory-confirmed diagnosis of BU within the study period (12 th June 2018 to 11 th June 2020). Control properties had no residents diagnosed with BU within the study period or reported as having had BU prior to the study period. Cases who completed the study questionnaire were purposely selected by postcode to ensure a representative spread of sampling across the affected area based on reported BU prevalence (i.e. more properties were surveyed in postcodes with more cases). Control properties were then purposely selected based on postcode and matched 1:1 to case properties. The aim was to enroll 120 cases and 120 controls in the study, which would provide 87% power to detect a difference in the proportion of properties with environmental MU detection (environmental prevalence 25% at case-properties versus 10% at control-properties, OR 3.0).
Prior to an environmental field survey being conducted at a property, geocoordinates (latitude and longitude), altitude (all from https://www.google.com/maps ) and approximate property size ( https://www.freemaptools.com/area-calculator.htm ) were recorded and an outline of the property, including buildings was prepared. During the property visit, additional information was recorded, including presence of any key plant species (four indigenous species as representatives of native habitat ( Melaleuca lanceolata , Leptospermum laevigatum , Leucopogon parviflorus , Allocasuarina verticillata/littoralis ), and one non-native species commonly found in native gardens ( Pittosporum spp .; and File), garden type and samples collected ( and Figs, and Files). Garden type was visually categorized as Non-native (>60% non-native vegetation), Mixed (40–60% native/non-native) or Native (>60% native vegetation) based on visual estimation of the overall garden by two surveyors ( ). Five different sample types were collected as outlined in and File, namely soil, water, plants ( ), feces and biting insects. Soil texture was determined as per standard protocols ( https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0008/168866/texture-salinity.pdf ). Up to 20 environmental samples were collected per property. Two soil samples were collected per property, biting insects were collected opportunistically and the three remaining sample types were selected using a stratified random approach to try and represent what was present in the garden (see for details). In addition, a mains water sample was also collected from each property as a negative control, to validate sample collection techniques and detect potential contamination. The total number of observable water sources on a property was recorded, although samples were not always collected from all sources. The presence of mosquito larvae in any of the water sources was also recorded. To establish if MU positive properties remain positive and MU negative properties remain negative over time, a proportion of properties were visited twice. Return visits were made opportunistically, based on participant availability and willingness to participate. For these properties first visits were made between 5th August 2019 and 3rd March 2020, whilst return visits were made between 19th March 2020 and 23rd June 2020. The interval between visits was impacted by work and travel restrictions imposed during the COVID-19 pandemic. The number of days between visits varied between 92 days (~3 months) and 261 days (~8.7 months), showing a right-skewed distribution with a median of 147 days (~4.9 months; IQR = 92 days). For all return environmental field surveys at a property, the property outline from the initial visit was used to enable the same sample types to be collected from the same locations. Any different samples collected and significant environmental changes between the two field surveys were recorded. Samples collected during field surveys were transported at room temperature to the laboratory and maintained at either 4°C (soil samples for bulk density, pH and conductivity testing) or -70°C (all other samples) until processed.
Soil samples were processed individually to determine soil bulk density (g/cm 3 ), pH, conductivity (μS/cm) and salinity class. For soil bulk density, 50cm 3 of each soil sample was weighed before and after heating in an oven at 105°C for two hours and the dry weight divided by the soil volume. For pH and conductivity, soil was resuspended in distilled water at a 1:5 ratio, before testing with a VisionPlus pH/EC80 meter (Jenco). Soil salinity class was determined based on the meter reading for conductivity with reference to the soil texture type determined during the field survey ( https://www.agric.wa.gov.au/soil-salinity/measuring-soil-salinity ). All samples from the five sample types were processed individually. Prior to nucleic acid extraction samples were thawed and individually transferred to 2ml tubes containing approximately 2.4g of a mixture of 2.3mm and 0.5mm zirconia/silica beads (Bio Spec Products, Inc.). The quantity of DNA/RNA Shield (Zymo) and sample added was dependent on sample type. Water samples were added in 500μl volumes to 500μl of DNA/RNA Shield (Zymo). For plant, soil and fecal samples, approximately 0.2g (plants) or 0.1g (feces/soil) was added to 1ml of DNA/RNA Shield (Zymo). All samples were homogenized at 6500rpm for 30sec on a Precellys 24 (Bertin Technologies) and clarified for 5 mins at 16,000g. Total nucleic acid was extracted from 200μl of the cleared supernatant using the Kingfisher Flex benchtop automated extraction instrument (ThermoFisher) and the Quick DNA/RNA MagBead Pathogen kit (Zymo) as per the manufacturer’s instructions. All samples were subjected to the IS2404 real-time PCR assay, which is routinely used for the molecular diagnosis of MU infection in clinical samples and has been used previously on environmental samples . As this assay detects other mycolactone-producing Mycobacteria in addition to MU, any sample that tested positive by this assay (C T <40, threshold 0.02) was subjected to confirmatory testing using two MU specific assays ( IS2606 and KR ; ) as well as an RNA-based assay targeting the MU 16S rRNA to assess viability (i.e. the presence of RNA presumed to be generated by viable bacteria) . This viability assay can also detect some strains of M . marinum , although it is unlikely that this species would be present in most of the sample types collected. Although all samples testing positive by the IS2404 assay were subjected to the viability assay, only samples positive by this latter assay as well as all three DNA-based assays (i.e. IS2404 , IS2606 and KR assays) were considered viable. Based on the results of these assays, all samples were classified as negative ( IS2404 not detected or C T ≥40); IS2404 detected (C T <40, threshold 0.02); confirmed (MU detected by both IS2606 and KR assays as well as the ‘ IS2404 detected’); or viable (MU 16S rRNA detected as well as ‘confirmed’) ( ). A property was assigned an ‘ IS2404 not detected’ ‘status if IS2404 was not detected in any samples collected from that property or was classified as IS2404 detected / confirmed / viable if any samples collected from that property met these definitions (N.B. a ‘viable’ property would also be both ‘ IS2404 detected’ and ‘confirmed’; a ‘confirmed’ property would also be ‘ IS2404 detected’).
The relationship between the time from DH notification of BU to the time of environmental surveys for case properties (in 10-week intervals) with the property status study outcomes relating to the detection of MU was examined using generalised estimating equations (binomial distribution and logit link function) regression models to account for repeat visits to the same property. Chi-square tests were used to investigate if MU positive samples (overall and by sample type and sub-type; for IS2404 detected, confirmed and viable status) were more likely to be present at case properties versus control properties. ANOVA was used to identify differences in the environmental characteristics (property size and elevation) of properties in the different geographic localities (Mornington Peninsula, Bellarine Peninsula, Bayside and Surf coast) and to identify differences in IS2404 C T values between different sample types. We investigated relationships between each of the property outcomes ( IS2404 detected, confirmed, viable and case status) with environmental variables, the full list of which can be found in . For initial (univariate) analysis Fisher’s Exact (where expected values ≤5) and chi-square tests were used to compare categorical variables, and either Student’s t-test or one-way ANOVA with a post-hoc Tukey Kramer test were used to compare differences in mean values of continuous variables. Descriptive statistical tests were conducted using pre-prepared spreadsheets available from http://www.biostathandbook.com . For details of the specific test used for each environmental variable, please refer to . Logistic regression models were used to estimate the strength of the relationships between each of the selected environmental characteristics and i) properties with one or more sample positive for MU ( IS2404 detected, confirmed or viable), or ii) case status of the property in separate univariable and multivariable models with results expressed as unadjusted or adjusted odds ratios (OR) and 95% confidence intervals (95%CI). Multivariable models included all potentially associated characteristics, being variables that had an association at P<0.1 in the univariate analysis and which were identified in 30 or more properties. Models were checked for collinearity; garden type was omitted a priori due to the close association with individual plant species. Covariates in the models included the presence of plant species ( Melaleuca lanceolata , Leptospermum laevigatum , Leucopogon parviflorus , Pittosporum spp . and Spiky aloe succulents), the presence of animal faeces from ringtail possums, brushtail possums and rodents, property size, presence of overhead power lines, altitude, soil pH, soil salinity and the use of bore water, with consistent adjustment across models for each property status. Regression models were conducted using Stata 15 (Statacorp).
S1 Fig Map of affected area, illustrating the MU status by suburb. Suburbs containing at least one ‘viable’ property were classified as viable. Suburbs without ‘viable’ properties but with at least one ‘confirmed’ property were classified as confirmed. Suburbs without ‘viable’ or ‘confirmed’ properties but with at least one ‘ IS2404 detected’ property were classified as ‘ IS2404 detected’. Suburbs without any ‘ IS2404 detected’ properties were classified as negative. N.B. Geographical boundaries are not available by postcode and some postcodes contain more than one suburb. Incorporates Geoscape Administrative Boundaries reprinted from https://data.gov.au/dataset/ds-dga-af33dd8c-0534-4e18-9245-fc64440f742e/distribution/dist-dga-4d6ec8bb-1039-4fef-aa58-6a14438f29b1/details?q= under a CC BY license, with permission from the Commonwealth of Australia, original copyright 2014. (TIF) Click here for additional data file. S2 Fig Key indigenous (panels A-D) and non-indigenous (panel E) plants recorded for each property. A–Melaleuca lanceolata (Moonah/black paperbark); B—Leptospermum laevigatum (coastal tea tree); C—Leucopogon parviflorus (coast beard heath/native currant); D–Allocasuarina verticillata/littoralis (Drooping and black sheoaks); E–Pittosporum spp. (cheesewoods). (TIF) Click here for additional data file. S3 Fig Flow diagram for environmental property surveys and sample collection. (TIF) Click here for additional data file. S4 Fig Example of a property outline with locations of key features and sample locations marked. Yellow sticky traps (YST) were placed at the majority of properties for additional insect capture. Results from these traps will be reported in a separate publication. (TIF) Click here for additional data file. S5 Fig Examples of plant samples collected. Panel A–selection of ‘spiky’ plants sampled; Panel B–selection of fruits with evidence of mammalian gnaw marks. (TIF) Click here for additional data file. S6 Fig Directed acyclic graph (DAG) used for assessing the potential for confounding by covariates and for identifying the appropriate confounders to be included in each adjusted model. (TIF) Click here for additional data file. S1 Table Univariate statistics: Environmental characteristics demonstrating significant relationships with at least one property type with numbers (and percentages) or mean values shown by property type. Significant relationships are shown in bold. (DOCX) Click here for additional data file. S2 Table Environmental categories investigated. (DOCX) Click here for additional data file. S1 File Results detailing the relationship between interval between case notification date and field collection date, and property outcome. (DOCX) Click here for additional data file. S2 File Fieldwork collection and sample processing protocols. (DOCX) Click here for additional data file. S3 File Property survey field collection sheet template. (DOCX) Click here for additional data file.
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Geographic variation in spatial accessibility of U.S. healthcare providers | b074d51f-751c-464d-812e-610cc50cb900 | 6456202 | Family Medicine[mh] | By the year 2020, the Health Resources and Services Administration (HRSA) estimates that there will be a shortage of 20,400 primary care physicians in the United States. Policymakers have long debated potential solutions to the national shortfall of physicians–of which, the most straightforward being to simply increase supply. However, approaches aimed at increasing the number of physicians graduating from medical schools neglect to consider the financial incentive for students to enter into procedural and surgical based non-primary care specialties and the forces that drive physicians to practice in already oversupplied locales. Interestingly, in part due to strategic efforts coupled with changes in professional education, advanced practice providers such as nurse practitioners (NPs) and physician assistants have played an increasingly important role in the U.S. healthcare workforce. In 2010, greater than 55,000 NPs were practicing primary care in the U.S., and the American Association of Nurse Practitioners estimates that of the greater than 23,000 NPs who graduated in 2015–2016, 85% were trained in primary care. Although sobering, national healthcare workforce projections, particularly for primary care, mask substantial geographic variation. The healthcare workforce is not distributed equally across the United States–while some areas struggle to provide basic healthcare services others have an abundance of healthcare providers. Such geographic imbalance in the healthcare workforce is not unique to the U.S.[ – ] and a common observation is the high concentration of providers within urban and/or affluent areas, versus a relative undersupply in rural and/or low-income areas. This has been clearly demonstrated in the distribution of U.S. surgical services. Likewise, the number of primary care physicians also increases with greater urbanization, from 39.8 per 100,000 residents in non-metropolitan areas to 53.3 in large central metropolitan areas. Financial incentives, recruitment, career development opportunities, infrastructure and staffing, workload and autonomy, and professional work environment have all been shown to affect where physicians practice. Yet, very little is known about the factors that influence where non-physicians such as nurse practitioners practice, nor the extent to which the workforce varies geographically. To date, previous studies that have examined geographic variation in the physician workforce have been limited to large area units (e.g., counties, hospital service regions, and primary care service areas) and rely on “per capita” measures expressed as a provider per population ratios, reflecting the availability of providers. Such measures have significant shortcomings in that they assume patients within regions have equal access and imply that administrative boundaries are impermeable (i.e., patients seek care only within the assigned regions).[ – ] Clearly, these are not realistic assumptions and the lack of accounting for the distance to services and boundary crossing affects the accuracy of the estimates for provider accessibility. The Variable distance Enhanced 2 step Floating Catchment Area (VE2SFCA) method is an approach to measuring spatial accessibility that was first developed by Luo and Wang and modified by others.[ – ] The VE2SFCA method accounts for provider availability, border crossing, and the effects for distance decay of utilization (i.e., adjusts for proximity to services). However, the VE2SFCA has only been applied to smaller geographic areas.[ , , , ] Accurate estimates of provider spatial accessibility on the national scale would be extremely valuable to policymakers. Therefore, we conducted a national study to compare spatial accessibility of key physician and non-physician groups using state of the art geospatial methods. Specifically, our objectives were twofold: (1) to describe spatial accessibility of physician and non-physician clinician groups using the VE2SFCA method and (2) to examine population factors associated with higher spatial accessibility. We specifically examine spatial accessibility of medical providers including primary care physicians (internal medicine and family medicine, separately), specialists, and nurse practitioners. As an example for a non-physician group that operates completely outside traditional medicine we also examine spatial accessibility of U.S. chiropractors.
We used a combination of national data on provider location and administrative claims to estimate spatial accessibility of primary care physicians (comparing internal medicine to family medicine), specialists, nurse practitioners, and chiropractors using the VE2SFCA method.[ – ] We then merged data from the U.S. Census Bureau to examine population factors associated with spatial accessibility. Identification of providers The 2014 National Plan and Provider Enumeration System (NPPES) was used to identify healthcare providers including: family medicine physicians, internal medicine physicians, specialists, nurse practitioners, and chiropractors. Provider types were classified based on the specialty codes reported in the NPPES, . Specialists included both surgical and medical specialties and subspecialties. In order to identify providers who were actively caring for patients, we linked all NPPES data to the 2014 Medicare Part B 20% sample claims file. Analyses were restricted to active providers based on the presence of one or more claims within the 20% Medicare Carrier file. Provider practice location was identified from the addresses in the NPPES and geocoded to transform the physical addresses to point feature data. Estimation of provider spatial accessibility We estimated provider spatial accessibility using the VE2SFCA method. This approach has distinct advantages over simple per capita estimates including: a decreased reliance on administrative boundaries; allowance for cross-border interactions; and an approximation for the effects for distance decay of utilization behavior. For the purposes of the study, spatial accessibility is based upon the concept of “potential spatial access”, described by Kahn as the availability of a service moderated by space, or the distance variable. Our measure was constructed based on both geocoded 2014 NPPES and 2010 US Census block level population data aggregated to the ZCTA level. To calculate a drive time-based service area for each practice location, we used an origin destination matrix describing the network based distance and time relationships with the health provider geocoded point location as the origin and the population weighted centroids for each ZCTA as the destination. Population weighted centroids were calculated for ZCTAs using nested 2010 US Census Block population data. ZCTA centroids were assigned the closest road segment for origin destination analysis. The origin destination matrix provided network based drive time and distance relationships for all geocoded practice locations and all ZCTA centroids within a 60-minute drive time threshold. Distance and drive time measures were calculated for automobiles using public roads exclusively. Speed limits and traffic restrictions were applied. Local traffic conditions such as day of the week and time of day were not considered in the analysis. For each geocoded point practice location, we aggregated all ZCTA populations whose centroids fell within an initial travel time (t 0 ) of 15 minutes. If the summed aggregate population value was less than 3,500 individuals, the initial travel time (t 0 ) was increased in 15-minute increments (t 0+15 minutes ) until the aggregated population reached the 3,500 threshold. For primary medical care, ratios below one provider per 3,500 persons (1:3,500) are considered health professional shortage areas as defined by the United States Department of Health and Human Services.[ , , ] The travel time at which the 1:3,500 threshold was satisfied was used to define the catchment area for the geocoded practice location of interest. To account for the decreasing likelihood that individuals utilize a resource as distance to the resource increases, we adapted distance decay weights W ij directly from Luo and Whippo, where t ij represents the travel time between population site i and provider location j . W i j = { 1 , 0.42 , 0.03 , i f t i j ≤ 15 m i n s i f 15 < t i j ≤ 30 m i n s i f 30 < t i j ≤ 60 m i n s In the first step, for each provider location, the provider to population ratio, Availability j , was calculated by summing the distance decay-weighted population for each ZCTA centroid, Pop i , which falls within the threshold travel time based catchment area. A v a i l a b i l i t y j = N P r o v i d e r ∑ i ∈ { t i j ≤ t t h r e s } W i j ( t i j ) * P o p i Then, for each ZCTA population weighted centroid, we considered all geocoded provider locations within an initial travel time t 0 (15 minutes) and summed the provider-to-population ratio (PPR) values for those provider locations within this initial travel time threshold. As was performed in step one, if the summed PPR value was less than 1:3,500, the initial travel time (t 0 ) was increased (t 0+15 minutes ) in 15 minute increments until the summed PPR exceeded the 1:3,500 threshold. The travel time at which the PPR threshold was satisfied was used to delineate the healthcare activity catchment area for the ZCTA population weighted centroid. Similar to step one, for 15, 30, and 60 minute drive time catchment areas we applied distance decay weights of 1, 0.42, and 0.03, respectively. To generate a final measure of provider accessibly for each ZCTA population weighted centroid, all PPRs within the health care activity space were summed applying the distance decay weights. P r o v i d e r A c c e s s i b i l i t y i = ∑ j ∈ { t i j ≤ t t h r e s W i j ( t i j ) * A v a i l a b i l i t y j Additional data To explore factors that may be associated with higher spatial accessibility of the various provider groups we collected population data, professional school locations, and U.S. Census designated urbanized area for our analyses. U.S. Census and rurality data Population data were collected at the ZCTA-level from the 2010 U.S. Census. Specifically, we gathered population estimates for percent aged 65 years and older, percent female, median household income, percent under the federal poverty limit, and racial/ethnic composition. U.S. ZCTAs were assigned to states and states were assigned to U.S. Census regions (i.e., Northwest, Midwest, South, West regions) based on if the ZCTA centroids fell within the corresponding geographic boundaries. Provider specific maps for each U.S. Census region are available in the accompanying supporting information ( – Figs). We also collected rural-urban community area code (RUCA) data that classify each ZCTA as being either “urban”, “large rural”, “small rural”, or “isolated”. Professional school data The location of professional schools is a known factor affecting choice of provider location.[ – ] To develop a roster of accredited professional schools for each provider type, we reviewed accreditation listings from the American Association of Medical Colleges, Association of Colleges of Osteopathic Medicine, the American Association of Colleges of Nursing, and the Association of Chiropractic Colleges. Addresses of accredited professional schools for each healthcare profession were geocoded as point data. The professional schools were aggregated to the ZCTA level. In all cases the professional school location intersected a ZCTA. ZCTAs were then assigned to counties based on if their population weighted centroid intersected a county. Statistical analyses In order to identify spatial clustering of high (and low) spatial accessibility, we calculated the Getis-Ord Gi* statistic for each ZCTA. An optimal fixed distance band analysis was used for conceptualization of spatial relationships. We found the average distance to the 30 nearest neighbors; this distance was approximately 25 miles. The Gi_Bin field was corrected using the FDR correction method for multiple testing and spatial dependence. ZCTAs with a Gi_Bin value of +3 or -3 were statistically significant at the 99% confidence level. We used simple descriptive statistics to examine select population characteristics for clustering of high versus low accessibility areas for each of the provider types. We calculated Spearman’s rank correlation coefficients (r s ) to compare spatial accessibility values between provider types. We used generalized linear models to examine associations between population characteristics and spatial accessibility for each provider type. For these analyses the unit of observation was ZCTAs and we assumed a Poisson distribution for the response variable. In our models we examined regional factors and population characteristics. Regional factors included the rurality of the ZCTA (urban, rural, versus isolated) and the presence of a professional school in the county in which the ZCTA was assigned. Population characteristics included sex (percent female), age (percent age 65 and older), minority race/ethnicity (percent all race and ethnicities versus Non-Hispanic White), poverty status (percent under the Federal Poverty Line), and education (percent with less than high school population among those age 25 and older). To improve interpretation of coefficients, we collapsed population age, minority race/ethnicity, poverty status, and education into terciles (representing low, medium, and high levels respectively). Coefficients were expressed as rate ratios and robust estimation methods were used to correct standard errors for deviation in response distributional assumption. P-values were adjusted for false discovery rate (FDR) to correct for multiple hypothesis tests. Geospatial analyses were conducted using ESRI ArcGIS, version 10.5 and StreetMap Premium, 2014 version 1 (Redlands, CA). U.S. Census Tiger Cartographic Boundary datasets were used in Figs and and – Analysis of NPPES and claims data were conducted using SAS, version 9.4 (Cary, NC). All analyses were based on complete case analysis and we assumed any missing values to be missing completely at random.
The 2014 National Plan and Provider Enumeration System (NPPES) was used to identify healthcare providers including: family medicine physicians, internal medicine physicians, specialists, nurse practitioners, and chiropractors. Provider types were classified based on the specialty codes reported in the NPPES, . Specialists included both surgical and medical specialties and subspecialties. In order to identify providers who were actively caring for patients, we linked all NPPES data to the 2014 Medicare Part B 20% sample claims file. Analyses were restricted to active providers based on the presence of one or more claims within the 20% Medicare Carrier file. Provider practice location was identified from the addresses in the NPPES and geocoded to transform the physical addresses to point feature data.
We estimated provider spatial accessibility using the VE2SFCA method. This approach has distinct advantages over simple per capita estimates including: a decreased reliance on administrative boundaries; allowance for cross-border interactions; and an approximation for the effects for distance decay of utilization behavior. For the purposes of the study, spatial accessibility is based upon the concept of “potential spatial access”, described by Kahn as the availability of a service moderated by space, or the distance variable. Our measure was constructed based on both geocoded 2014 NPPES and 2010 US Census block level population data aggregated to the ZCTA level. To calculate a drive time-based service area for each practice location, we used an origin destination matrix describing the network based distance and time relationships with the health provider geocoded point location as the origin and the population weighted centroids for each ZCTA as the destination. Population weighted centroids were calculated for ZCTAs using nested 2010 US Census Block population data. ZCTA centroids were assigned the closest road segment for origin destination analysis. The origin destination matrix provided network based drive time and distance relationships for all geocoded practice locations and all ZCTA centroids within a 60-minute drive time threshold. Distance and drive time measures were calculated for automobiles using public roads exclusively. Speed limits and traffic restrictions were applied. Local traffic conditions such as day of the week and time of day were not considered in the analysis. For each geocoded point practice location, we aggregated all ZCTA populations whose centroids fell within an initial travel time (t 0 ) of 15 minutes. If the summed aggregate population value was less than 3,500 individuals, the initial travel time (t 0 ) was increased in 15-minute increments (t 0+15 minutes ) until the aggregated population reached the 3,500 threshold. For primary medical care, ratios below one provider per 3,500 persons (1:3,500) are considered health professional shortage areas as defined by the United States Department of Health and Human Services.[ , , ] The travel time at which the 1:3,500 threshold was satisfied was used to define the catchment area for the geocoded practice location of interest. To account for the decreasing likelihood that individuals utilize a resource as distance to the resource increases, we adapted distance decay weights W ij directly from Luo and Whippo, where t ij represents the travel time between population site i and provider location j . W i j = { 1 , 0.42 , 0.03 , i f t i j ≤ 15 m i n s i f 15 < t i j ≤ 30 m i n s i f 30 < t i j ≤ 60 m i n s In the first step, for each provider location, the provider to population ratio, Availability j , was calculated by summing the distance decay-weighted population for each ZCTA centroid, Pop i , which falls within the threshold travel time based catchment area. A v a i l a b i l i t y j = N P r o v i d e r ∑ i ∈ { t i j ≤ t t h r e s } W i j ( t i j ) * P o p i Then, for each ZCTA population weighted centroid, we considered all geocoded provider locations within an initial travel time t 0 (15 minutes) and summed the provider-to-population ratio (PPR) values for those provider locations within this initial travel time threshold. As was performed in step one, if the summed PPR value was less than 1:3,500, the initial travel time (t 0 ) was increased (t 0+15 minutes ) in 15 minute increments until the summed PPR exceeded the 1:3,500 threshold. The travel time at which the PPR threshold was satisfied was used to delineate the healthcare activity catchment area for the ZCTA population weighted centroid. Similar to step one, for 15, 30, and 60 minute drive time catchment areas we applied distance decay weights of 1, 0.42, and 0.03, respectively. To generate a final measure of provider accessibly for each ZCTA population weighted centroid, all PPRs within the health care activity space were summed applying the distance decay weights. P r o v i d e r A c c e s s i b i l i t y i = ∑ j ∈ { t i j ≤ t t h r e s W i j ( t i j ) * A v a i l a b i l i t y j
To explore factors that may be associated with higher spatial accessibility of the various provider groups we collected population data, professional school locations, and U.S. Census designated urbanized area for our analyses.
Population data were collected at the ZCTA-level from the 2010 U.S. Census. Specifically, we gathered population estimates for percent aged 65 years and older, percent female, median household income, percent under the federal poverty limit, and racial/ethnic composition. U.S. ZCTAs were assigned to states and states were assigned to U.S. Census regions (i.e., Northwest, Midwest, South, West regions) based on if the ZCTA centroids fell within the corresponding geographic boundaries. Provider specific maps for each U.S. Census region are available in the accompanying supporting information ( – Figs). We also collected rural-urban community area code (RUCA) data that classify each ZCTA as being either “urban”, “large rural”, “small rural”, or “isolated”.
The location of professional schools is a known factor affecting choice of provider location.[ – ] To develop a roster of accredited professional schools for each provider type, we reviewed accreditation listings from the American Association of Medical Colleges, Association of Colleges of Osteopathic Medicine, the American Association of Colleges of Nursing, and the Association of Chiropractic Colleges. Addresses of accredited professional schools for each healthcare profession were geocoded as point data. The professional schools were aggregated to the ZCTA level. In all cases the professional school location intersected a ZCTA. ZCTAs were then assigned to counties based on if their population weighted centroid intersected a county.
In order to identify spatial clustering of high (and low) spatial accessibility, we calculated the Getis-Ord Gi* statistic for each ZCTA. An optimal fixed distance band analysis was used for conceptualization of spatial relationships. We found the average distance to the 30 nearest neighbors; this distance was approximately 25 miles. The Gi_Bin field was corrected using the FDR correction method for multiple testing and spatial dependence. ZCTAs with a Gi_Bin value of +3 or -3 were statistically significant at the 99% confidence level. We used simple descriptive statistics to examine select population characteristics for clustering of high versus low accessibility areas for each of the provider types. We calculated Spearman’s rank correlation coefficients (r s ) to compare spatial accessibility values between provider types. We used generalized linear models to examine associations between population characteristics and spatial accessibility for each provider type. For these analyses the unit of observation was ZCTAs and we assumed a Poisson distribution for the response variable. In our models we examined regional factors and population characteristics. Regional factors included the rurality of the ZCTA (urban, rural, versus isolated) and the presence of a professional school in the county in which the ZCTA was assigned. Population characteristics included sex (percent female), age (percent age 65 and older), minority race/ethnicity (percent all race and ethnicities versus Non-Hispanic White), poverty status (percent under the Federal Poverty Line), and education (percent with less than high school population among those age 25 and older). To improve interpretation of coefficients, we collapsed population age, minority race/ethnicity, poverty status, and education into terciles (representing low, medium, and high levels respectively). Coefficients were expressed as rate ratios and robust estimation methods were used to correct standard errors for deviation in response distributional assumption. P-values were adjusted for false discovery rate (FDR) to correct for multiple hypothesis tests. Geospatial analyses were conducted using ESRI ArcGIS, version 10.5 and StreetMap Premium, 2014 version 1 (Redlands, CA). U.S. Census Tiger Cartographic Boundary datasets were used in Figs and and – Analysis of NPPES and claims data were conducted using SAS, version 9.4 (Cary, NC). All analyses were based on complete case analysis and we assumed any missing values to be missing completely at random.
Provider spatial accessibility Using the combination of data from the NPPES and Medicare claims we identified 178,660 internal medicine physicians, 90,870 family medicine physicians, 391,621 specialists, 79,790 nurse practitioners, and 44,040 chiropractors who were actively treating patients in 2014. The distribution of spatial accessibility nationally by provider type is demonstrated in . Overall, for each provider type, spatial accessibility was not evenly distributed across ZCTAs. For example, in the case of family medicine physicians, ( ) an area of high spatial accessibility was concentrated in the Midwestern U.S., which is visually represented by the darker shading of ZCTAs, while the lighter shading observed across the western and southern U.S. represents ZCTAs with comparatively lower spatial accessibility values for family medicine physicians relative to other areas. While, in the case of internal medicine physicians and specialists, a higher spatial accessibility was observed in the Northeast Region. For nurse practitioners, spatial accessibility was lowest in the West and uniform across the Midwest, South, and Northeast regions. Lastly, among chiropractors, high spatial accessibility was observed in the Midwest Region and relatively lower spatial accessibility in the South and West regions. Getis-Ord Gi* analyses Getis-Ord Gi* analysis revealed unique patterns of higher and lower spatial accessibility among the different provider types. More specifically, family medicine physicians were observed to have clusters of high spatial accessibility that were spatially distinct in comparison to those seen for internal medicine physicians (r s = 0.2693, p < 0.001). Although there were clusters of high spatial accessibility distributed across the U.S., areas of family medicine physician high spatial accessibility were concentrated in the Midwestern U.S., with low spatial accessibility clusters located in the Northwestern U.S. and along the west coast ( ). In contrast, internal medicine physicians had high spatial accessibility clusters with locations that seemed to correspond with U.S. Census Bureau-designated urbanized areas ( ). This can be more easily visualized on the provider specific regional maps (see – Figs). This pattern of high spatial accessibility for internal medicine physicians near urbanized areas was similar to that of specialists (r s = 0.8082, p < 0.001). The spatial accessibility of nurse practitioners displayed a somewhat unique pattern that was most similar to that of family medicine physicians (r s = 0.4444, p < 0.001). Clusters of high spatial accessibility for nurse practitioner were observed along the Mississippi River Valley, Northeastern U.S., and the Midwest. However, there was a pattern of low spatial accessibility for nurse practitioners in the West. While chiropractors were noted to have a large cluster of high spatial accessibility in the Midwest, low spatial accessibility clusters were observed in the South and West. Provider spatial accessibility and population characteristics The characteristics of populations that live within the areas of high and low spatial accessibility also differed by provider group, . In our adjusted analyses independent factors associated with higher spatial accessibility were very similar between internal medicine physicians and specialists–presence of a medical school in the county was associated with approximately 70% higher spatial accessibility and higher spatial accessibility was associated with urban locales, . Higher spatial accessibility of these two provider groups was also associated with higher racial/ethnicity diversity and poverty. For instance among specialists, spatial accessibility was approximately 40% higher in high poverty areas compared to low (RR 1.43, 95% CI: 1.37, 1.49). Family medicine physicians and nurse practitioners were similar to each other in regards to predictors of higher spatial accessibility–higher spatial accessibility was associated with rural locales and less racial/ethnic diversity. Among all provider types, family medicine was the only provider type with higher spatial accessibility in isolated areas (as compared to urban). Chiropractors were somewhat unique, with higher spatial accessibility being associated with less racial/ethnic diversity, lower poverty, and a higher percentage of older adults.
Using the combination of data from the NPPES and Medicare claims we identified 178,660 internal medicine physicians, 90,870 family medicine physicians, 391,621 specialists, 79,790 nurse practitioners, and 44,040 chiropractors who were actively treating patients in 2014. The distribution of spatial accessibility nationally by provider type is demonstrated in . Overall, for each provider type, spatial accessibility was not evenly distributed across ZCTAs. For example, in the case of family medicine physicians, ( ) an area of high spatial accessibility was concentrated in the Midwestern U.S., which is visually represented by the darker shading of ZCTAs, while the lighter shading observed across the western and southern U.S. represents ZCTAs with comparatively lower spatial accessibility values for family medicine physicians relative to other areas. While, in the case of internal medicine physicians and specialists, a higher spatial accessibility was observed in the Northeast Region. For nurse practitioners, spatial accessibility was lowest in the West and uniform across the Midwest, South, and Northeast regions. Lastly, among chiropractors, high spatial accessibility was observed in the Midwest Region and relatively lower spatial accessibility in the South and West regions.
Getis-Ord Gi* analysis revealed unique patterns of higher and lower spatial accessibility among the different provider types. More specifically, family medicine physicians were observed to have clusters of high spatial accessibility that were spatially distinct in comparison to those seen for internal medicine physicians (r s = 0.2693, p < 0.001). Although there were clusters of high spatial accessibility distributed across the U.S., areas of family medicine physician high spatial accessibility were concentrated in the Midwestern U.S., with low spatial accessibility clusters located in the Northwestern U.S. and along the west coast ( ). In contrast, internal medicine physicians had high spatial accessibility clusters with locations that seemed to correspond with U.S. Census Bureau-designated urbanized areas ( ). This can be more easily visualized on the provider specific regional maps (see – Figs). This pattern of high spatial accessibility for internal medicine physicians near urbanized areas was similar to that of specialists (r s = 0.8082, p < 0.001). The spatial accessibility of nurse practitioners displayed a somewhat unique pattern that was most similar to that of family medicine physicians (r s = 0.4444, p < 0.001). Clusters of high spatial accessibility for nurse practitioner were observed along the Mississippi River Valley, Northeastern U.S., and the Midwest. However, there was a pattern of low spatial accessibility for nurse practitioners in the West. While chiropractors were noted to have a large cluster of high spatial accessibility in the Midwest, low spatial accessibility clusters were observed in the South and West.
The characteristics of populations that live within the areas of high and low spatial accessibility also differed by provider group, . In our adjusted analyses independent factors associated with higher spatial accessibility were very similar between internal medicine physicians and specialists–presence of a medical school in the county was associated with approximately 70% higher spatial accessibility and higher spatial accessibility was associated with urban locales, . Higher spatial accessibility of these two provider groups was also associated with higher racial/ethnicity diversity and poverty. For instance among specialists, spatial accessibility was approximately 40% higher in high poverty areas compared to low (RR 1.43, 95% CI: 1.37, 1.49). Family medicine physicians and nurse practitioners were similar to each other in regards to predictors of higher spatial accessibility–higher spatial accessibility was associated with rural locales and less racial/ethnic diversity. Among all provider types, family medicine was the only provider type with higher spatial accessibility in isolated areas (as compared to urban). Chiropractors were somewhat unique, with higher spatial accessibility being associated with less racial/ethnic diversity, lower poverty, and a higher percentage of older adults.
The objective of our study was to compare spatial accessibility of different healthcare provider types using current state of the art geospatial methodology and to examine factors associated with higher spatial accessibility. To our knowledge this is the first study to examine spatial accessibility at the ZCTA level using the VE2SFCA method across the contiguous U.S. Overall, we found spatial accessibility was not equally distributed across geographic areas among all of the five provider types examined–each were found to have distinct areas of concentrated high (and low) spatial accessibility. Most notably, we found that despite both being considered a “primary care physician”, spatial accessibility differed considerably between internal medicine and family medicine physicians (r s = 0.2693, p < 0.001). Internal medicine physicians more resembled specialists, being more likely to be in condensed urban locales and strongly associated with the presence of a medical school (r s = 0.8082, p < 0.001). Maldistribution of the healthcare workforce has been a widely recognized problem since the publication of the Graduate Medical Education National Advisory Committee report in 1980. Since that time, multiple studies have demonstrated the substantial variation in geographic accessibility to physicians. However, previous studies may have masked small-area variation in accessibility, due to their reliance on measuring accessibility using county, state, or even regional area units.[ , – ] While studies that measured small-areas were limited in their scale to examining specific cities, states, regions, or populations.[ , , , , ] The VE2SFCA method we used has several advantages over traditional provider-to-population ratios (i.e., “per capita”), which rely on administrative borders as the unit of analysis. Due to use of drive-time as a distance related impedance measure, the VE2SFCA method is less dependent on the aggregation of data into polygon-based administrative borders such as counties, cities, or ZIP codes. The VE2SFCA method also allowed us to examine small-area variation at the ZCTA level on a national scale. Application of the VE2SFCA method to national data on practice location revealed considerable differences. Internal medicine physicians had the highest spatial accessibility in population dense areas and spatial accessibility was associated with higher poverty and greater proportions of non-Hispanic black and Hispanic individuals. Associations between nurse practitioner spatial accessibility was highest in areas with an intermediate population density and racial/ethnic diversity, while family medicine physicians were most accessible in areas with the comparatively lowest population density and racial diversity. As a provider group outside of traditional medicine, chiropractors were the most unlike other provider types in regards to both their spatial accessibility pattern and their predictors of higher spatial accessibility. Examining spatial accessibility of non-physicians (i.e., nurse practitioners and chiropractors) is a particular strength of our study. Advanced practice providers, including nurse practitioners, are playing an increasingly important role in healthcare delivery. Our analyses demonstrate that nurse practitioners share some similarities to other groups yet have some distinct differences which may hint at providing care in underserved areas. While family medicine physicians and nurse practitioners shared some common predictors such as rural locales, their patterns were spatially distinct at the national scale–family medicine physicians had higher spatial accessibility in the upper Midwest whereas nurse practitioners had higher spatial accessibility in the South. Furthermore, unlike the predictors of spatial accessibility for family medicine physicians, nurse practitioner spatial accessibility was not higher in small or isolated rural areas compared to urban areas. This suggests that currently there may be workforce supply limits to the use of nurse practitioners to supplement physicians in these community areas.
There are several limitations that should be considered when interpreting the study findings. First, healthcare access represents more than spatial accessibility alone. The concept of access also includes acceptability (patient attitudes and beliefs), accommodation (wait times, provider workload), affordability (cost, insurance coverage), and availability (treatments and services offered). We chose to examine spatial accessibility because it is the fundamental requirement for the other components of access. Second, the VE2SFCA method assumes that all providers and populations that are located within a drive-time based catchment area have equal accessibility. We cede that even within small areas, healthcare accessibility is inequitable. For this reason, we have included sociodemographic population characteristics in the analysis, such as: age, sex, median household income, poverty level, and race/ethnicity. Third, a single PPR of 1:3,500 was used as the threshold value. We selected this value due to its real world use in defining primary care related health professional shortage areas by the U.S. Department of Health and Human Services. Ratios below this value are not felt to be adequate for providing primary care medical services. Forth, discrete distance decay weights were applied to differentiate travel time zones across provider types instead of a continuous function. To properly apply differing distance decay functions to each provider type, patient specific data of actual utilization of health services for each provider type would be necessary. Fifth, linear models examining associations between population characteristics and PRP utilized cross-sectional data and therefore their findings represent associations and we cannot rule out reverse causality. Sixth, provider practice locations were determined based on data from the NPPES and practice addresses were not confirmed for their accuracy. However, in a recent comparison study, the NPPES had the highest accuracy for provider contact information in comparison to other commonly used national sources such as the American Medical Association Physician Masterfile and the SK&A file. Lastly, some sparsely populated areas did not contain healthcare providers or sufficient numbers of residents to be included in the study analysis. These areas are typically located in small rural or remote frontier communities and their representation within the study may be underreported.
Disparities in access to primary care services greatly impacts population health. Through use of the VE2SFA method, we have estimated spatial accessibility to primary care providers on a national scale, at ZCTA-level resolution. Unlike, per-capita based provider-to-population rations, VE2SFA spatial accessibility measurements employ dynamic, drive-time based, catchment areas that incorporate population thresholds and an estimation of distance decay in utilization. Our findings indicate that the primary care workforce is unequally distributed across the nation, with internal medicine physicians, family medicine physicians, and nurse practitioners each displaying a unique pattern for their spatial accessibility. The characteristics of populations that live within the areas of high and low spatial accessibility also differed by provider type. In light of these findings, future programs and policies intended to address maldistribution of the primary care workforce may need to be individualized according to provider type, target population, and geographic location. Additional research is needed to explore the factors that influence geographic patterns of spatial accessibility and the interaction between primary care provider groups.
S1 Fig Internal medicine physician accessibility and Getis-Ord Gi* statistic by U.S. census region. (PDF) Click here for additional data file. S2 Fig Family medicine physician accessibility and Getis-Ord Gi* statistic by U.S. census region. (PDF) Click here for additional data file. S3 Fig Specialist physician accessibility and Getis-Ord Gi* statistic by U.S. census region. (PDF) Click here for additional data file. S4 Fig Nurse practitioner accessibility and Getis-Ord Gi* statistic by U.S. census region. (PDF) Click here for additional data file. S5 Fig Chiropractor accessibility and Getis-Ord Gi* statistic by U.S. census region. (PDF) Click here for additional data file. S1 File Minimum data set. (CSV) Click here for additional data file.
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Effect of combined application of inorganic nitrogen and phosphorus to an organic-matter poor soil on soil organic matter cycling | 8cb3bf50-678e-4592-a170-2c8ab4921c19 | 11380837 | Microbiology[mh] | The world’s soils hold the largest terrestrial reserves of C, which is two times higher than that in living biomass and three times than that in the atmosphere . Moreover, it is one end of the second largest exchange of C with the atmosphere after the one between oceans and the atmosphere . Consequently, small changes in this stock and the rate at which it exchanges with atmosphere entails large effects for global C cycle and the attendant global warming . There is a dual interest in storing soil organic C (SOC) in agroecosystems. First, enhancing SOC stocks by soaking up atmospheric CO 2 and keeping it in soils for long term may help in mitigating climate changes . Second, higher SOC improves soils’ physical, chemical and biological properties in a way that increases the agricultural and ecosystem services on sustainable basis . Addition of crop residues like rice and wheat stubbles or maize stalks is an important strategy to enhance SOC content as billions of tones of these are produced annually . However, numerous studies have indicated that repeated addition of crop residues does not necessarily increase SOC content as expected . There is a mineral nutrient cost of increasing SOC content that needs to be met for storing the added residues in soils . However, the interaction of two major mineral nutrients added in agroecosystems i.e ., N & P, in terms of C cycling is not clear. For instance, numerous studies have shown that the mineral N addition reduces soil respiration . This reduction in soil respiration is also linked with corresponding decrease in soil microbial biomass across biomes as shown in a meta-analysis of field studies . In contradiction to mineral N effects, addition of inorganic P has been shown to increase soil respiration and microbial biomass in many studies . For instance, supply of inorganic P increased soil respiration from surface layers of volcanic ash soil . Moreover, addition of inorganic P increased soil respiration in Oxisols under the forest in Costa Rica , in tropical forests on red soils in China and in beech forest soils of Germany . Most of these studies have attributed this increase in respiration and microbial biomass to the microbial alleviation of P limitation. However, desorption of soluble organic compounds by inorganic P, because of stronger sorptive capacity of the latter, makes greater amounts of substrate available for microbes thereby inducing higher respiration . Whatever the mechanism is, the contradictory response of soil respiration ( i.e ., soil C cycling) to addition of inorganic forms of N and P needs further exploration. In addition to modifying soil respiration and microbial biomass in opposite directions, the addition of inorganic N and P also differ vis-à-vis the decomposition of native SOC in response to external C inputs i.e ., priming of the extant SOC. Briefly, when N is added along with labile organic C, the decomposition of extant SOC is suppressed when compared to C only addition treatments . This indicates that the mineral N addition could help stabilize the external C inputs in the soil in addition to suppressing the extant SOC. However, addition of inorganic P along with labile C has been found to enhance mineralization of the extant SOC. For instance, found that addition of inorganic P along with glucose, phenol and oxalic acid further enhanced mineralization of the extant SOC than addition of labile C treatments. Similarly, in a four-year field experiment, inorganic P addition stimulated loss of the extant SOC via priming effect . Given this contradiction, the application of inorganic N and P, at rates higher than are required, for the sake of soil C sequestration cannot be a given. N and P are essential nutrients that, when applied together with litter especially in an organic matter poor soil, would provide a balanced nutrient environment for microbial communities. Increased or imbalanced nutrient availability for microbial growth and activity, desorption of organic matter from soil particles and pH alterations are immediate mechanisms known to influence SOM cycling in short-term studies. Hence, it is hypothesized that there is a significant role of nitrogen and phosphorus stoichiometry in switching between SOM mineralization and immobilization in soils naturally poor in soil organic matter. So, this study aims to explore, how do these aforementioned mechanisms differ between nitrogen and phosphorus addition in SOM poor soil? And is there any synergistic or antagonistic effect when both nutrients are applied together? Additionally, how does this system respond when fresh organic matter is supplied along with or without nutrients? We designed this study to explore the effects of addition of mineral N, P alone or in combination, in presence or absence of maize litter in an organic matter poor, calcareous soil. We hypothesized that N addition would suppress the soil C mineralization irrespective of litter addition, whereas P addition would suppress it in absence of litter owing to limited desorption of labile C from thin SOC contents while it may stimulate it in presence of litter.
Soil sampling and initial physico-chemical analyses Soil was collected from a field located at Ayub Agriculture Research Institute, Faisalabad, Pakistan (31°23′41″N, 73°3′0″E). The field is under wheat-fallow rotation for 12 years and irrigation agriculture is practiced. The wheat productivity stands at 3.95 ± 0.28 tons ha −1 . This area has a subtropical monsoon climate with 200 mm yearly average rainfall and soil type in an Aridisol. The effect of precipitation on soil processes is minimum owing to regular irrigation. Surface soil (0–15 cm) was collected randomly from five points with an auger (internal diameter 4.8 cm) and homogenized to make a composite sample. All the dead or live roots, plant debris and visible rocks were removed from the soil. After sieving with 2 mm mesh, it was stored at 4 °C in an airtight polythene bag. Soil pH was determined in 1:5 (soil: water, w/v) suspensions with a pre-calibrated pH meter (Model HANNA 210). Soil texture was determined by hydrometer method . Water holding capacity (WHC) of the soil was determined by the method of . For this, 50 g of air-dried and sieved soil was packed in plastic columns or containers that were closed with porous fabric to allow water to move up into the soil column through capillary action. They were placed in a tray filled with distilled water until soil saturation was achieved. Wet weight of the soil column was recorded after a period of drainage of excess water under gravity. Subsequently, the soil was oven dried and dry weight was recorded. WHC was calculated as the difference between dry and wet weights and expressed in percentage of dry weight of soil. Initial SOC was determined by Walkley Black method . For this, 1.0 g of fresh soil was digested with 1 N K 2 Cr 2 O 7 solution. A continuous stirring of 2 min was performed after addition of 20 mL of concentrated H 2 SO 4 . After a cooling off phase of about 30 mins, 200mL of distilled water was added to the mixture followed by addition of 10 mL of concentrated orthophosphoric acid after a gentle mixing. The remaining K 2 Cr 2 O 7 in the mixture was determined by titrating it against 0.5 M ferrous ammonium sulphate after addition of 10–15 drops of ferroin indicator. The titration was terminated when the color turned from blue to red. End point was achieved as violet blue to green. Experiment was performed in triplicates and triplicate blanks without soil were run in the same way. The SOC was estimated using the following formulae. [12pt]{minimal}
$${ SOC\; }( { \% } ) = 1.334{ \; } { \; }_{{ blank}}} - { \; }{{ V}_{{ sample}}}} ]{ \; } 0.3{ \; } 10} {{ Wt\; } { \; }{{ V}_{{ blank}}}}}$$ S O C = 1.334 × [ V b l a n k − V s a m p l e ] × 0.3 × 10 W t × V b l a n k where V blank and V sample are the volume of ferrous ammonium sulphate used for blank and samples respectively, and Wt is the dry weight of the soil digested for the analysis. After physico-chemical analyses described above it was found that the soil was a sandy clay loam and of alkaline nature (pH 8.32) with 31.7 percent water holding capacity . Moreover, soil was found to have 8.66 g C kg −1 soil, 600 mg N kg −1 soil, and 7.71 mg P kg −1 soil. The C: N of soil was 14.43 . Maize litter Fresh maize leaves were dried in an oven at 50 °C for three days. These were crushed and sieved through 1 mm mesh to be used for mixing with soils before incubation. The litter had 26.76% C and 1.25% N with a C: N of 21 . Soil incubation and respiration measurement Seventy grams of dry equivalent of soil were packed in a beaker at 60% WHC before placing it in a 1 L Mason jar. Twenty-four such microcosms were prepared and placed in an incubator at 25 °C for a week. This period of pre-incubation was meant for stabilizing and acclimatizing microbial activity before introducing experimental treatments. After pre-incubation, soil was amended with litter (1 g C kg −1 soil), N (120 kg N ha −1 in the form of (NH 4 ) 2 SO 4 ), and P (60 kg.P ha −1 in form of single super phosphate). This amount of mineral nutrients is recommended for wheat in the Faisalabad region from where the soil was sampled, whereas the amount of C added corresponds to the organic C entering in soil via below and aboveground residues at this site in one crop cycle. A completely randomized block design was used. Treatments were in triplicate and included nitrogen alone (N), phosphorus alone (P), nitrogen + phosphorus (NP), litter alone (L), nitrogen + litter (NL), phosphorus + litter (PL) and nitrogen + phosphorus + litter (NPL). Un-amended soil was used as control. While mixing the salts and/or litter in the soil, control soils were also mixed to mimic the similar disturbance to microbial activity. Amended and control soils at 60% WHC were kept in airtight 1 L mason jars along with 10 mL 1 N NaOH to capture CO 2 -C released from soils. A glass vial filled with 10 mL distilled water was also placed in jars to keep the inside atmosphere moist. Jars with 10 mL NaOH and 10 mL distilled water only served as blanks. Sealed airtight jars were incubated at 25 °C in the dark. The NaOH traps were harvested at appropriate time intervals ensuring that CO 2 absorption is below 10% of its total capacity of CO 2 absorption at the time of each harvest. The traps were replaced at days, 2, 3, 7, 9, 13, 16, 20, 23. The total amount of CO 2 trapped in NaOH was determined by titrating 5 mL of it against 1 N HCl after precipitating with excess BaCl 2 and using phenolphthalein as indicator . Soil moisture was adjusted at 60% WHC and fresh NaOH was placed after each respiration measure. Cumulative CO 2 evolution represents the total amount of CO 2 respired from soil over the entire incubation period and calculated by simply adding the daily measurements of CO 2 evolved. Water extractable organic C and microbial biomass At the end of the incubation period, soil from the incubation jars was collected and stored at 4 °C for further analyses. Water extractable organic carbon (WEOC) was determined using the method of . Briefly, WEOC was extracted by shaking 5 g soil from each replicate with 25 mL of distilled water at 150 rpm for 90 min. The mixture was then centrifuged at 10,000 × g for 5 min and supernatant was filtered through a Whatman filter # 42. The total organic C concentration in the extract was determined by following the modified Walkley-Black method . Microbial biomass carbon (MBC) was measured by chloroform fumigation extraction method . Briefly, 5 g of fresh soil from each replicate was fumigated in a desiccator under vacuum conditions for 24 h. Fumigated samples were extracted with 0.5 M K 2 SO 4 solution in 1:5 (soil: water) ratio. Another set of non-fumigated samples each containing 5 g soil from each replicate was also extracted following the same procedure. The total organic C concentration in the extract was determined following a modified Walkley-Black method . The difference of C concentrations between fumigated and non-fumigated samples after adjusting with the extraction factor of 0.35 was considered as microbial biomass. The microbial metabolic quotient ( q CO 2 ) was determined by dividing cumulative CO 2 evolution by MBC . Microbial metabolic quotient is an important metric to assess how efficiently microbes are utilizing soil organic matter for their growth and energy needs. Monitoring q CO 2 together with nutrient cycling aids us to study and predict equilibrium between immobilization and mineralization of soil organic matter that is crucial for soil organic matter storage . Enzymatic activity in soils Extracellular enzymes serve as a biomarker for microbial activity in soil. Studying enzyme activity allows estimation of rate and efficiency of SOM decomposition and nutrient release from SOM. Dehydrogenase activity was determined as reported by . Briefly, 5 g soil from each treatment was added to triphenyl tetrazolium chloride (TTC) solution (prepared by mixing 5 g of TTC in 0.2 M tris-HCl buffer, (pH 7.4)). The mixture was incubated for 12 h at 37 °C. Immediately after incubation, two drops of concentrated H 2 SO 4 were added to cease the reaction. This mixture was shaken at 250 rpm for 30 min after adding 5 mL of toluene. The resultant mixture was centrifuged at 4,500 rpm for 5 min for the extraction of 1,3,5-triphenylformazan (TPF). The absorbance of supernatant was measured at 492 nm with UV-vis spectrophotometer. The soil dehydrogenase activity was stated as µg TPF g −1 12 h −1 . Alkaline phosphatase activity was determined spectrophotometrically . A total of 1 g soil was mixed with 0.25 mL of toluene, 1 mL of p-nitrophenol phosphate solution and 4 mL MUB buffer (pH 11). The mixture was incubated for 1 h at 37 °C. One mL of CaCl 2 (0.5 M) and 4 mL of NaOH (0.5 M) were added to the mixture after incubation. This suspension was filtered with Whatman filter paper no. 42. Absorbance of filtrate was measured at 400 nm. The phosphatase activity was expressed as µg p-nitrophenol g −1 h −1 . Urease activity was estimated according to “urea remaining” method by . For this, 5 g soil was incubated with 5 mL of urea solution (10 mg urea/mL) for 5 h at 37 °C. After incubation, mixture was added with 50 mL of 2 M KC1-PMA. Suspension was shaken for 1 h and filtered with Whatman filter paper no. 42. Two mL of filtrate was added with 10 mL 2 M KC1-PMA and 30 mL coloring reagent (10 mL of 0.25% TSC in 500 mL acid reagent + 25 mL 2.5% DAM). For color development, this mixture was kept in water bath for 30 min followed by ice cold water bath for 15 min. Absorbance of this mixture was observed at 527 nm with UV-Vis spectrophotometer. Soil urease activity is expressed as μg. g −1 soil. h −1 . β- glucosidase activity was measured as described by . For this, 0.5 g soil was mixed with 0.1 mL of toluene. 10 mL distilled water was added after 10 min followed by addition of 1.5 mL of Mcilvain buffer and 0.6 mL of PNG. This mixture was incubated at 37 °C for 1 h after vortex for few seconds. After incubation, 8 mL of ethanol was added and swirled for few seconds. The mixture was filtered, and filtrate was added with 2 mL of tris-solution. The intensity of yellow color was measured at 400 nm on UV-Vis spectrophotometer. The p-nitrophenol content of treatments were calculated by standard calibration curve method with standards containing 0, 0.2, 10.4, 0.6, 0.8, and 1.0 μ M of p-nitrophenol. Statistical analysis One-way ANOVA was carried out to compare the effects of treatments on SOC mineralization (cumulative CO 2 and per day CO 2 evolution), water-extractable organic C, microbial biomass C, metabolic quotient and enzymatic activities of dehydrogenase, urease, β- glucosidase, and alkaline phosphatase. In case of a significant difference, a post-hoc least significant difference test was applied to determine the significantly different means ( n = 3) at 95% confidence interval. Data were assessed for normality before applying the ANOVA and log-transformed to acquire normality in case needed. All the statistical analysis was conducted using Statgraphics Plus.
Soil was collected from a field located at Ayub Agriculture Research Institute, Faisalabad, Pakistan (31°23′41″N, 73°3′0″E). The field is under wheat-fallow rotation for 12 years and irrigation agriculture is practiced. The wheat productivity stands at 3.95 ± 0.28 tons ha −1 . This area has a subtropical monsoon climate with 200 mm yearly average rainfall and soil type in an Aridisol. The effect of precipitation on soil processes is minimum owing to regular irrigation. Surface soil (0–15 cm) was collected randomly from five points with an auger (internal diameter 4.8 cm) and homogenized to make a composite sample. All the dead or live roots, plant debris and visible rocks were removed from the soil. After sieving with 2 mm mesh, it was stored at 4 °C in an airtight polythene bag. Soil pH was determined in 1:5 (soil: water, w/v) suspensions with a pre-calibrated pH meter (Model HANNA 210). Soil texture was determined by hydrometer method . Water holding capacity (WHC) of the soil was determined by the method of . For this, 50 g of air-dried and sieved soil was packed in plastic columns or containers that were closed with porous fabric to allow water to move up into the soil column through capillary action. They were placed in a tray filled with distilled water until soil saturation was achieved. Wet weight of the soil column was recorded after a period of drainage of excess water under gravity. Subsequently, the soil was oven dried and dry weight was recorded. WHC was calculated as the difference between dry and wet weights and expressed in percentage of dry weight of soil. Initial SOC was determined by Walkley Black method . For this, 1.0 g of fresh soil was digested with 1 N K 2 Cr 2 O 7 solution. A continuous stirring of 2 min was performed after addition of 20 mL of concentrated H 2 SO 4 . After a cooling off phase of about 30 mins, 200mL of distilled water was added to the mixture followed by addition of 10 mL of concentrated orthophosphoric acid after a gentle mixing. The remaining K 2 Cr 2 O 7 in the mixture was determined by titrating it against 0.5 M ferrous ammonium sulphate after addition of 10–15 drops of ferroin indicator. The titration was terminated when the color turned from blue to red. End point was achieved as violet blue to green. Experiment was performed in triplicates and triplicate blanks without soil were run in the same way. The SOC was estimated using the following formulae. [12pt]{minimal}
$${ SOC\; }( { \% } ) = 1.334{ \; } { \; }_{{ blank}}} - { \; }{{ V}_{{ sample}}}} ]{ \; } 0.3{ \; } 10} {{ Wt\; } { \; }{{ V}_{{ blank}}}}}$$ S O C = 1.334 × [ V b l a n k − V s a m p l e ] × 0.3 × 10 W t × V b l a n k where V blank and V sample are the volume of ferrous ammonium sulphate used for blank and samples respectively, and Wt is the dry weight of the soil digested for the analysis. After physico-chemical analyses described above it was found that the soil was a sandy clay loam and of alkaline nature (pH 8.32) with 31.7 percent water holding capacity . Moreover, soil was found to have 8.66 g C kg −1 soil, 600 mg N kg −1 soil, and 7.71 mg P kg −1 soil. The C: N of soil was 14.43 .
Fresh maize leaves were dried in an oven at 50 °C for three days. These were crushed and sieved through 1 mm mesh to be used for mixing with soils before incubation. The litter had 26.76% C and 1.25% N with a C: N of 21 .
Seventy grams of dry equivalent of soil were packed in a beaker at 60% WHC before placing it in a 1 L Mason jar. Twenty-four such microcosms were prepared and placed in an incubator at 25 °C for a week. This period of pre-incubation was meant for stabilizing and acclimatizing microbial activity before introducing experimental treatments. After pre-incubation, soil was amended with litter (1 g C kg −1 soil), N (120 kg N ha −1 in the form of (NH 4 ) 2 SO 4 ), and P (60 kg.P ha −1 in form of single super phosphate). This amount of mineral nutrients is recommended for wheat in the Faisalabad region from where the soil was sampled, whereas the amount of C added corresponds to the organic C entering in soil via below and aboveground residues at this site in one crop cycle. A completely randomized block design was used. Treatments were in triplicate and included nitrogen alone (N), phosphorus alone (P), nitrogen + phosphorus (NP), litter alone (L), nitrogen + litter (NL), phosphorus + litter (PL) and nitrogen + phosphorus + litter (NPL). Un-amended soil was used as control. While mixing the salts and/or litter in the soil, control soils were also mixed to mimic the similar disturbance to microbial activity. Amended and control soils at 60% WHC were kept in airtight 1 L mason jars along with 10 mL 1 N NaOH to capture CO 2 -C released from soils. A glass vial filled with 10 mL distilled water was also placed in jars to keep the inside atmosphere moist. Jars with 10 mL NaOH and 10 mL distilled water only served as blanks. Sealed airtight jars were incubated at 25 °C in the dark. The NaOH traps were harvested at appropriate time intervals ensuring that CO 2 absorption is below 10% of its total capacity of CO 2 absorption at the time of each harvest. The traps were replaced at days, 2, 3, 7, 9, 13, 16, 20, 23. The total amount of CO 2 trapped in NaOH was determined by titrating 5 mL of it against 1 N HCl after precipitating with excess BaCl 2 and using phenolphthalein as indicator . Soil moisture was adjusted at 60% WHC and fresh NaOH was placed after each respiration measure. Cumulative CO 2 evolution represents the total amount of CO 2 respired from soil over the entire incubation period and calculated by simply adding the daily measurements of CO 2 evolved.
At the end of the incubation period, soil from the incubation jars was collected and stored at 4 °C for further analyses. Water extractable organic carbon (WEOC) was determined using the method of . Briefly, WEOC was extracted by shaking 5 g soil from each replicate with 25 mL of distilled water at 150 rpm for 90 min. The mixture was then centrifuged at 10,000 × g for 5 min and supernatant was filtered through a Whatman filter # 42. The total organic C concentration in the extract was determined by following the modified Walkley-Black method . Microbial biomass carbon (MBC) was measured by chloroform fumigation extraction method . Briefly, 5 g of fresh soil from each replicate was fumigated in a desiccator under vacuum conditions for 24 h. Fumigated samples were extracted with 0.5 M K 2 SO 4 solution in 1:5 (soil: water) ratio. Another set of non-fumigated samples each containing 5 g soil from each replicate was also extracted following the same procedure. The total organic C concentration in the extract was determined following a modified Walkley-Black method . The difference of C concentrations between fumigated and non-fumigated samples after adjusting with the extraction factor of 0.35 was considered as microbial biomass. The microbial metabolic quotient ( q CO 2 ) was determined by dividing cumulative CO 2 evolution by MBC . Microbial metabolic quotient is an important metric to assess how efficiently microbes are utilizing soil organic matter for their growth and energy needs. Monitoring q CO 2 together with nutrient cycling aids us to study and predict equilibrium between immobilization and mineralization of soil organic matter that is crucial for soil organic matter storage .
Extracellular enzymes serve as a biomarker for microbial activity in soil. Studying enzyme activity allows estimation of rate and efficiency of SOM decomposition and nutrient release from SOM. Dehydrogenase activity was determined as reported by . Briefly, 5 g soil from each treatment was added to triphenyl tetrazolium chloride (TTC) solution (prepared by mixing 5 g of TTC in 0.2 M tris-HCl buffer, (pH 7.4)). The mixture was incubated for 12 h at 37 °C. Immediately after incubation, two drops of concentrated H 2 SO 4 were added to cease the reaction. This mixture was shaken at 250 rpm for 30 min after adding 5 mL of toluene. The resultant mixture was centrifuged at 4,500 rpm for 5 min for the extraction of 1,3,5-triphenylformazan (TPF). The absorbance of supernatant was measured at 492 nm with UV-vis spectrophotometer. The soil dehydrogenase activity was stated as µg TPF g −1 12 h −1 . Alkaline phosphatase activity was determined spectrophotometrically . A total of 1 g soil was mixed with 0.25 mL of toluene, 1 mL of p-nitrophenol phosphate solution and 4 mL MUB buffer (pH 11). The mixture was incubated for 1 h at 37 °C. One mL of CaCl 2 (0.5 M) and 4 mL of NaOH (0.5 M) were added to the mixture after incubation. This suspension was filtered with Whatman filter paper no. 42. Absorbance of filtrate was measured at 400 nm. The phosphatase activity was expressed as µg p-nitrophenol g −1 h −1 . Urease activity was estimated according to “urea remaining” method by . For this, 5 g soil was incubated with 5 mL of urea solution (10 mg urea/mL) for 5 h at 37 °C. After incubation, mixture was added with 50 mL of 2 M KC1-PMA. Suspension was shaken for 1 h and filtered with Whatman filter paper no. 42. Two mL of filtrate was added with 10 mL 2 M KC1-PMA and 30 mL coloring reagent (10 mL of 0.25% TSC in 500 mL acid reagent + 25 mL 2.5% DAM). For color development, this mixture was kept in water bath for 30 min followed by ice cold water bath for 15 min. Absorbance of this mixture was observed at 527 nm with UV-Vis spectrophotometer. Soil urease activity is expressed as μg. g −1 soil. h −1 . β- glucosidase activity was measured as described by . For this, 0.5 g soil was mixed with 0.1 mL of toluene. 10 mL distilled water was added after 10 min followed by addition of 1.5 mL of Mcilvain buffer and 0.6 mL of PNG. This mixture was incubated at 37 °C for 1 h after vortex for few seconds. After incubation, 8 mL of ethanol was added and swirled for few seconds. The mixture was filtered, and filtrate was added with 2 mL of tris-solution. The intensity of yellow color was measured at 400 nm on UV-Vis spectrophotometer. The p-nitrophenol content of treatments were calculated by standard calibration curve method with standards containing 0, 0.2, 10.4, 0.6, 0.8, and 1.0 μ M of p-nitrophenol.
One-way ANOVA was carried out to compare the effects of treatments on SOC mineralization (cumulative CO 2 and per day CO 2 evolution), water-extractable organic C, microbial biomass C, metabolic quotient and enzymatic activities of dehydrogenase, urease, β- glucosidase, and alkaline phosphatase. In case of a significant difference, a post-hoc least significant difference test was applied to determine the significantly different means ( n = 3) at 95% confidence interval. Data were assessed for normality before applying the ANOVA and log-transformed to acquire normality in case needed. All the statistical analysis was conducted using Statgraphics Plus.
Soil carbon mineralization Carbon mineralization rate (mg CO 2 -C kg −1 soil d −1 ) was modified by nutrient (N, P) and litter addition alone as well as in different combinations ( P < 0.05, ). Moreover, it varied over the course of incubation. Similarly, the cumulative CO 2 -C release (mg CO 2 -C kg −1 soil) was significantly modified by nutrients and litter addition ( P < 0.05, ). The N addition (N treatment) significantly lowered the C mineralization rate resulting in the lowest total cumulative CO 2 -C release by the end of the experiment . Phosphorus addition (P treatment) induced ~3 times increase in C mineralization rate two days after incubation . However, afterwards, the C mineralization rate in P treatment declined to that in control treatment for the entire duration of incubation. The total cumulative CO 2 -C released from P treatment was similar to that in control . Combined addition of N & P (NP treatment) induced higher (at times three-fold) release of CO 2 -C in the earlier stages of incubation leading to higher total cumulative CO 2 -C from NP treatment than control (41%) . The litter addition (L treatment) alone or in combination with one or both the nutrients significantly increased the C mineralization rate than control treatment . Until the 13 th day of incubation, the C mineralization rate in L treatment was significantly higher than in control, N, P or NP treatments. Afterwards, the C mineralization in L treatment declined towards those in control, P and NP treatments. Overall, the total cumulative CO 2 -C release was significantly higher in L treatment than N, P, NP and control treatments. Adding N along with L (NL treatment) did not influence C mineralization rate when compared to litter alone (L) treatment . Moreover, total cumulative CO 2 -C release was similar in NL and L treatments . Although adding P along with L (PL treatment) increased C mineralization rate in the early days of incubation , the total cumulative CO 2 -C release was similar in L and PL treatments by the end of the experiment . Adding two nutrients i.e ., N & P with L (NPL treatment) significantly increased the C mineralization rate on 2 nd day by 153%, 83% and 68% in comparison to PL, NL and L treatments respectively . It was still significantly higher on the third day by 39%, 26% & 26% in NPL treatment than PL, NL and L treatments respectively. Afterwards, NPL treatment showed a similar C mineralization rate as in PL, NL & L treatments. On the final day, all the litter amended soils (irrespective of the nutrient type and presence) showed similar C mineralization including NPL treatment. By the end of the experiment, the highest amount of cumulative CO 2 -C was released from the NPL treatment, which was 19% and 187% higher than L & control treatments, respectively . Water extractable organic C, microbial biomass C & metabolic quotient The treatments significantly modified the water extractable organic C (WEOC) content in soils . The N only treatment tended to lower the WEOC content although it was not significantly lower than that in control. On the contrary, addition of L with N (NL) treatment tended to increase WEOC. The three treatments i.e ., P, NP, & NPL maintained the WEOC content similar to those in control. However, the PL and L treatments significantly increased the WEOC content with respect to control whereby the highest increase, which was recorded in L treatment, was 76% higher than that in the control treatment. The microbial biomass carbon (MBC) was significantly influenced by the experimental treatments . The highest MBC was found in NL treatment that was 144% higher than control, whereas the N only treatment showed a non-significant increase of 22% only. The P only treatment significantly increased the MBC by 53% in comparison to control. However, the addition of L along with P (PL treatment) did not change the MBC. Addition of both the nutrients ( i.e ., NP) did not influence the MBC although it tended to increase. However, addition of L in combination with NP ( i.e ., NPL treatment) significantly increased the MBC by 105% with respect to control. The L treatment significantly increased the MBC by 59% in comparison to control. Metabolic quotient (qCO 2 ) decreased significantly in response to N or P only additions ( P < 0.05, ). It remained similar to control treatment in NP, L, NL and NPL treatments. However, it was significantly higher in PL treatment. Extracellular enzymatic assays The treatments significantly changed the activity of all the four enzymes assayed in the experiment . Briefly, dehydrogenase activity significantly decreased in response to N or P and NP additions as well as when phosphorus was added with litter (PL treatment). However, it increased significantly in L, NL and NPL treatments. It was highest in NL and NPL treatments. The N addition slightly but significantly increased the β-glucosidase activity whereas β-glucosidase activity remained unchanged in response to P or NP addition. It was 1.9, 2.1, 1.6 and 2.3 times higher in L, NL, PL and NPL treatments respectively when compared to control. N addition significantly reduced the urease activity when added alone (N), or in combination with phosphorus and/or litter (P, L & NPL treatments) . Addition of P and L (P & L treatments) significantly increased the urease activity by 1.46 and 1.11 times respectively, with respect to control. However, the combined addition of P and L (PL treatment) did not change urease activity. The alkaline phosphatase activity significantly decreased in response to P addition alone or in combination with N and/or L ( i.e ., NP, PL & NPL treatments). However, adding nitrogen and litter alone or in combination significantly increased the alkaline phosphatase activity.
Carbon mineralization rate (mg CO 2 -C kg −1 soil d −1 ) was modified by nutrient (N, P) and litter addition alone as well as in different combinations ( P < 0.05, ). Moreover, it varied over the course of incubation. Similarly, the cumulative CO 2 -C release (mg CO 2 -C kg −1 soil) was significantly modified by nutrients and litter addition ( P < 0.05, ). The N addition (N treatment) significantly lowered the C mineralization rate resulting in the lowest total cumulative CO 2 -C release by the end of the experiment . Phosphorus addition (P treatment) induced ~3 times increase in C mineralization rate two days after incubation . However, afterwards, the C mineralization rate in P treatment declined to that in control treatment for the entire duration of incubation. The total cumulative CO 2 -C released from P treatment was similar to that in control . Combined addition of N & P (NP treatment) induced higher (at times three-fold) release of CO 2 -C in the earlier stages of incubation leading to higher total cumulative CO 2 -C from NP treatment than control (41%) . The litter addition (L treatment) alone or in combination with one or both the nutrients significantly increased the C mineralization rate than control treatment . Until the 13 th day of incubation, the C mineralization rate in L treatment was significantly higher than in control, N, P or NP treatments. Afterwards, the C mineralization in L treatment declined towards those in control, P and NP treatments. Overall, the total cumulative CO 2 -C release was significantly higher in L treatment than N, P, NP and control treatments. Adding N along with L (NL treatment) did not influence C mineralization rate when compared to litter alone (L) treatment . Moreover, total cumulative CO 2 -C release was similar in NL and L treatments . Although adding P along with L (PL treatment) increased C mineralization rate in the early days of incubation , the total cumulative CO 2 -C release was similar in L and PL treatments by the end of the experiment . Adding two nutrients i.e ., N & P with L (NPL treatment) significantly increased the C mineralization rate on 2 nd day by 153%, 83% and 68% in comparison to PL, NL and L treatments respectively . It was still significantly higher on the third day by 39%, 26% & 26% in NPL treatment than PL, NL and L treatments respectively. Afterwards, NPL treatment showed a similar C mineralization rate as in PL, NL & L treatments. On the final day, all the litter amended soils (irrespective of the nutrient type and presence) showed similar C mineralization including NPL treatment. By the end of the experiment, the highest amount of cumulative CO 2 -C was released from the NPL treatment, which was 19% and 187% higher than L & control treatments, respectively .
The treatments significantly modified the water extractable organic C (WEOC) content in soils . The N only treatment tended to lower the WEOC content although it was not significantly lower than that in control. On the contrary, addition of L with N (NL) treatment tended to increase WEOC. The three treatments i.e ., P, NP, & NPL maintained the WEOC content similar to those in control. However, the PL and L treatments significantly increased the WEOC content with respect to control whereby the highest increase, which was recorded in L treatment, was 76% higher than that in the control treatment. The microbial biomass carbon (MBC) was significantly influenced by the experimental treatments . The highest MBC was found in NL treatment that was 144% higher than control, whereas the N only treatment showed a non-significant increase of 22% only. The P only treatment significantly increased the MBC by 53% in comparison to control. However, the addition of L along with P (PL treatment) did not change the MBC. Addition of both the nutrients ( i.e ., NP) did not influence the MBC although it tended to increase. However, addition of L in combination with NP ( i.e ., NPL treatment) significantly increased the MBC by 105% with respect to control. The L treatment significantly increased the MBC by 59% in comparison to control. Metabolic quotient (qCO 2 ) decreased significantly in response to N or P only additions ( P < 0.05, ). It remained similar to control treatment in NP, L, NL and NPL treatments. However, it was significantly higher in PL treatment.
The treatments significantly changed the activity of all the four enzymes assayed in the experiment . Briefly, dehydrogenase activity significantly decreased in response to N or P and NP additions as well as when phosphorus was added with litter (PL treatment). However, it increased significantly in L, NL and NPL treatments. It was highest in NL and NPL treatments. The N addition slightly but significantly increased the β-glucosidase activity whereas β-glucosidase activity remained unchanged in response to P or NP addition. It was 1.9, 2.1, 1.6 and 2.3 times higher in L, NL, PL and NPL treatments respectively when compared to control. N addition significantly reduced the urease activity when added alone (N), or in combination with phosphorus and/or litter (P, L & NPL treatments) . Addition of P and L (P & L treatments) significantly increased the urease activity by 1.46 and 1.11 times respectively, with respect to control. However, the combined addition of P and L (PL treatment) did not change urease activity. The alkaline phosphatase activity significantly decreased in response to P addition alone or in combination with N and/or L ( i.e ., NP, PL & NPL treatments). However, adding nitrogen and litter alone or in combination significantly increased the alkaline phosphatase activity.
Soil carbon mineralization and C pools Addition of inorganic P significantly stimulated soil C mineralization rate for a very brief duration followed by similar C mineralization rate as in control soils for most part of the incubation. Consequently, the total cumulative CO 2 -C release from P treatment was similar to that in control . This result is in partial contradiction to previous findings where inorganic P addition have been found to induce decrease in SOC by stimulating its mineralization . According to recent research, addition of P leads to desorption of simple organic compounds making them available for microorganisms thereby leading to higher soil respiration . Most of the studies reporting higher C mineralization in response to addition of inorganic P used soils having high SOC content ( i.e ., >1.5%) suggesting that high amounts of labile organic compounds were available for desorption in response to addition of inorganic P. However, our soil is poor in organic C ( i.e ., 0.87%, ) which explains the transitory stimulation in C mineralization after P addition. Later on, the labile compounds that could be desorbed from soil particles were most likely too low to sustain higher C mineralization rates. This is evident by the similar water extractable organic C . Moreover, increase in microbial biomass in P treatment indicates that the microbes used most of the desorbed organic compounds as well as the extra available P for growth . This suggests that P addition in this soil could build up microbial biomass thereby improving soil health. Mineral N addition significantly suppressed the total cumulative CO 2 -C release as well as the soil C mineralization rate for most part of the incubation . These results correspond to previous findings . However, in our study, there was rather an increase, albeit an insignificant one, in microbial biomass after N addition. We assume that the soil microbes were N-limited and switched to growth instead of C mineralization as soon as the mineral N was available. However, combined addition of N & P ( i.e ., NP treatment) induced significantly higher C mineralization whereas microbial biomass was higher (though not significantly) than control . Apparently, P presence in NP treatment made labile C available for microbial consumption as is shown by higher WEOC content in NP treatment than in N or P alone treatments thereby leading to higher C mineralization . Litter addition enhanced C mineralization since it ensures provision of labile substrates for soil microbes which are C limited in general due to lower accessibility of the SOC . Moreover, the studied soil is particularly poor in organic matter thereby increase in C mineralization in response to litter is intuitive. However, provision of N with litter ( i.e . NL treatment) did not cause an additional increase in C mineralization rate and cumulative CO 2 -C release in comparison to L only treatment, although this soil is N-deficient . Evidently, the microorganisms used extra available mineral N and labile C in NL treatment to build their biomass as shown by the highest microbial biomass in the said treatment . Moreover, as shown by the unchanged metabolic quotient in NL treatment, it is confirmed that microbes were more inclined to growth than decomposition. Indeed, mineral N availability in the presence of relatively labile substrate has been found to increase microbial biomass and suppress C mineralization . Addition of P with litter ( i.e . PL treatment) initially reduced C mineralization when compared to L only treatment, which is counterintuitive . Interestingly, microbial biomass in PL treatment decreased significantly when compared to L only treatment. Moreover, it was also significantly lower than that in P only treatment . The question is why microbial biomass decreased in response to combined addition of P and L where litter is a rich source of labile C, when addition of alone inorganic P stimulated microbial biomass? Apparently, the acute N limitation induced by excess availability of inorganic P in presence of litter can explain this result. Because, when N was also added i.e ., NPL treatment, this limitation was alleviated leading to the highest C mineralization and cumulative CO 2 -C release. These results indicate that addition of both nutrients in the recommended quantities alongside organic matter stimulates microbial activity. Litter addition significantly increased microbial biomass . However, addition of N ( i.e ., NL and NPL treatments) further increased this living component of SOC. This shows that microbes were facing N limitation and grew their biomass when it was available. This hypothesis is confirmed by the highest WEOC content in L treatment though the MBC in the same was significantly lower than NL & NPL treatments indicating incapacity of microbes to assimilate the extra available WEOC. Overall, the results of microbial biomass show that addition of nitrogen along with litter increases the living pool of SOC. Enzymatic activity Activity of C, N and P acquiring extracellular enzymes, i.e ., β-glucosidase, urease, and alkaline phosphatase respectively, was determined to link the effect of addition of litter, N, and P on soil processes involving cycling of these elements. Moreover, dehydrogenase activity was measured because it is linked with the active part of the microbial biomass given that it is an intracellular enzyme . Litter addition significantly stimulated dehydrogenase activity, except in PL treatment, evidently because the substrate availability activates microorganisms towards decomposition and growth. However, nutrient addition suppressed dehydrogenase activity presumably due to lowering of soil pH . We did not measure the soil pH post incubation. However, the salts we used to add inorganic N and P i.e ., ammonium sulphate and single super phosphate respectively, are highly acidic indicating the reduction in pH in these soils. Labile C input, litter input in our study, stimulates microbial activity and growth leading to higher microbial C demand . This enhances the enzyme production for co-metabolizing the SOC thereby leading to higher C degrading enzymatic activity as indicated by high β-glucosidase activity in all litter amended soils . Among all litter amended soils, PL showed the lowest β-glucosidase activity which corresponds to lower microbial biomass found in this treatment . Activity of C acquiring enzyme not only increased in the presence of litter but also in the presence of mineral N . Indeed, higher N availability allows microbes to invest N into enzyme synthesis thereby mining C for microbial growth . This is also confirmed by higher microbial biomass found in N treatment . An unchanged β-glucosidase activity in P treatment further confirms that the increase in microbial biomass in this treatment is because of desorption of labile organic compounds from soil particles instead of alleviation of microbial P limitation. Overall, β-glucosidase activity confirmed that adding mineral nutrients alongside organic matter (litter) in this organic matter poor soil promotes the growth soil C pools i.e ., microbial biomass in addition to stimulating the microbial activity. All the treatments where mineral N was added showed significantly lower urease activity than control . This indicates that the microbes were not investing in synthesis of enzymes aimed at N mining because they were getting mineral N from outside source . Instead, they were more focused on assimilating it along with labile C to increase their biomass . In all the other treatments where N was not added, except PL, urease activity was significantly higher than control indicating that microbes were investing on N acquisition because their C: N stoichiometry was highly imbalanced in the presence of excess C. A similar activity for meeting stoichiometric needs was observed in the case of P-acquiring enzyme i.e . where inorganic P was added, alkaline phosphatase activity was lower and vice versa . When a nutrient is limiting while other nutrients and substrate are available, it is common for microbes to synthesize enzymes to acquire the limiting nutrient . This stoichiometric response by the enzymes indicates that the provided nutrient contents in the soil were sufficient to fulfil the needs of the microorganisms thereby facilitating them in their activity and growth.
Addition of inorganic P significantly stimulated soil C mineralization rate for a very brief duration followed by similar C mineralization rate as in control soils for most part of the incubation. Consequently, the total cumulative CO 2 -C release from P treatment was similar to that in control . This result is in partial contradiction to previous findings where inorganic P addition have been found to induce decrease in SOC by stimulating its mineralization . According to recent research, addition of P leads to desorption of simple organic compounds making them available for microorganisms thereby leading to higher soil respiration . Most of the studies reporting higher C mineralization in response to addition of inorganic P used soils having high SOC content ( i.e ., >1.5%) suggesting that high amounts of labile organic compounds were available for desorption in response to addition of inorganic P. However, our soil is poor in organic C ( i.e ., 0.87%, ) which explains the transitory stimulation in C mineralization after P addition. Later on, the labile compounds that could be desorbed from soil particles were most likely too low to sustain higher C mineralization rates. This is evident by the similar water extractable organic C . Moreover, increase in microbial biomass in P treatment indicates that the microbes used most of the desorbed organic compounds as well as the extra available P for growth . This suggests that P addition in this soil could build up microbial biomass thereby improving soil health. Mineral N addition significantly suppressed the total cumulative CO 2 -C release as well as the soil C mineralization rate for most part of the incubation . These results correspond to previous findings . However, in our study, there was rather an increase, albeit an insignificant one, in microbial biomass after N addition. We assume that the soil microbes were N-limited and switched to growth instead of C mineralization as soon as the mineral N was available. However, combined addition of N & P ( i.e ., NP treatment) induced significantly higher C mineralization whereas microbial biomass was higher (though not significantly) than control . Apparently, P presence in NP treatment made labile C available for microbial consumption as is shown by higher WEOC content in NP treatment than in N or P alone treatments thereby leading to higher C mineralization . Litter addition enhanced C mineralization since it ensures provision of labile substrates for soil microbes which are C limited in general due to lower accessibility of the SOC . Moreover, the studied soil is particularly poor in organic matter thereby increase in C mineralization in response to litter is intuitive. However, provision of N with litter ( i.e . NL treatment) did not cause an additional increase in C mineralization rate and cumulative CO 2 -C release in comparison to L only treatment, although this soil is N-deficient . Evidently, the microorganisms used extra available mineral N and labile C in NL treatment to build their biomass as shown by the highest microbial biomass in the said treatment . Moreover, as shown by the unchanged metabolic quotient in NL treatment, it is confirmed that microbes were more inclined to growth than decomposition. Indeed, mineral N availability in the presence of relatively labile substrate has been found to increase microbial biomass and suppress C mineralization . Addition of P with litter ( i.e . PL treatment) initially reduced C mineralization when compared to L only treatment, which is counterintuitive . Interestingly, microbial biomass in PL treatment decreased significantly when compared to L only treatment. Moreover, it was also significantly lower than that in P only treatment . The question is why microbial biomass decreased in response to combined addition of P and L where litter is a rich source of labile C, when addition of alone inorganic P stimulated microbial biomass? Apparently, the acute N limitation induced by excess availability of inorganic P in presence of litter can explain this result. Because, when N was also added i.e ., NPL treatment, this limitation was alleviated leading to the highest C mineralization and cumulative CO 2 -C release. These results indicate that addition of both nutrients in the recommended quantities alongside organic matter stimulates microbial activity. Litter addition significantly increased microbial biomass . However, addition of N ( i.e ., NL and NPL treatments) further increased this living component of SOC. This shows that microbes were facing N limitation and grew their biomass when it was available. This hypothesis is confirmed by the highest WEOC content in L treatment though the MBC in the same was significantly lower than NL & NPL treatments indicating incapacity of microbes to assimilate the extra available WEOC. Overall, the results of microbial biomass show that addition of nitrogen along with litter increases the living pool of SOC.
Activity of C, N and P acquiring extracellular enzymes, i.e ., β-glucosidase, urease, and alkaline phosphatase respectively, was determined to link the effect of addition of litter, N, and P on soil processes involving cycling of these elements. Moreover, dehydrogenase activity was measured because it is linked with the active part of the microbial biomass given that it is an intracellular enzyme . Litter addition significantly stimulated dehydrogenase activity, except in PL treatment, evidently because the substrate availability activates microorganisms towards decomposition and growth. However, nutrient addition suppressed dehydrogenase activity presumably due to lowering of soil pH . We did not measure the soil pH post incubation. However, the salts we used to add inorganic N and P i.e ., ammonium sulphate and single super phosphate respectively, are highly acidic indicating the reduction in pH in these soils. Labile C input, litter input in our study, stimulates microbial activity and growth leading to higher microbial C demand . This enhances the enzyme production for co-metabolizing the SOC thereby leading to higher C degrading enzymatic activity as indicated by high β-glucosidase activity in all litter amended soils . Among all litter amended soils, PL showed the lowest β-glucosidase activity which corresponds to lower microbial biomass found in this treatment . Activity of C acquiring enzyme not only increased in the presence of litter but also in the presence of mineral N . Indeed, higher N availability allows microbes to invest N into enzyme synthesis thereby mining C for microbial growth . This is also confirmed by higher microbial biomass found in N treatment . An unchanged β-glucosidase activity in P treatment further confirms that the increase in microbial biomass in this treatment is because of desorption of labile organic compounds from soil particles instead of alleviation of microbial P limitation. Overall, β-glucosidase activity confirmed that adding mineral nutrients alongside organic matter (litter) in this organic matter poor soil promotes the growth soil C pools i.e ., microbial biomass in addition to stimulating the microbial activity. All the treatments where mineral N was added showed significantly lower urease activity than control . This indicates that the microbes were not investing in synthesis of enzymes aimed at N mining because they were getting mineral N from outside source . Instead, they were more focused on assimilating it along with labile C to increase their biomass . In all the other treatments where N was not added, except PL, urease activity was significantly higher than control indicating that microbes were investing on N acquisition because their C: N stoichiometry was highly imbalanced in the presence of excess C. A similar activity for meeting stoichiometric needs was observed in the case of P-acquiring enzyme i.e . where inorganic P was added, alkaline phosphatase activity was lower and vice versa . When a nutrient is limiting while other nutrients and substrate are available, it is common for microbes to synthesize enzymes to acquire the limiting nutrient . This stoichiometric response by the enzymes indicates that the provided nutrient contents in the soil were sufficient to fulfil the needs of the microorganisms thereby facilitating them in their activity and growth.
We conducted this study to find out the reason behind contradictory response of soil C mineralization and microbial biomass to addition of inorganic N and P. We found that increased C mineralization in response to addition of inorganic P, often found in literature, is indeed attributed to relatively high intrinsic SOC content from which labile desorbs thereby stimulating C mineralization. However, in an organic matter poor soil, like the one used in this study, limited desorption of labile C precludes stimulated C mineralization in response to inorganic P addition. Moreover, our study confirms that the mineral N addition could stabilize the existing as well as externally added organic carbon as shown by suppressed mineralization and increased microbial biomass. Moreover, our study reveals that co-application of inorganic N and P in SOC poor soils can lead to loss of the soil C. However, if they are coapplied alongside external organic matter, which is the case in natural as well as most managed ecosystems, they may improve the microbial activity that’s vital for soil health as well as help enhance soil C.
10.7717/peerj.17984/supp-1 Supplemental Information 1 The raw values and their calculations.
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Parenting Education to Improve Relational Health Through Pediatric Primary Care: A Scoping Review | e4bd4de1-9169-4dca-9cb2-e4e35c91d35d | 11632888 | Pediatrics[mh] | Pediatric primary care providers are the only professionals who regularly meet with children and their families from infancy through adolescence. Well-child care in particular is designed to focus on the prevention of disease, as well as the promotion of health and development. However, it is imperative to prioritize effective interventions given the limited amount of time for well-child care visits. Addressing Adverse Childhood Experiences ( ACEs ) may be an important topic for pediatricians to prioritize. As defined by the original CDC study, ACEs include family-relationship risk factors such as child maltreatment (physical, verbal, and sexual abuse; physical and emotional neglect) and household challenges (mental illness, substance abuse, intimate partner violence, incarceration, divorced, or separated parents). Research shows that exposure to 1 ACE increases the odds of additional ACEs, there is a dose-response relationship between ACEs and poor health, and ACEs increase risk of a wide range of physical, mental, and social problems. - In children, studies suggest that ACEs increase risk of behavior problems, developmental delays, somatic complaints, sleep disruption, injuries, unhealthy weight, asthma, and substance use. - A separate literature shows that safe, stable, and nurturing home environments promote optimal health and development. For example, recent reviews show that positive and collaborative parent-child relationships improve child mental health, including reduced depression, reduced aggression, and improved self-regulation. There is also evidence that the quality of parent-child relationships can impact physical health, such as inflammatory responses in children with asthma, glycemic control in patients with diabetes, and medical adherence across chronic health conditions. Studies of children with ACEs suggest that interventions that focus on promoting responsive parenting may affect cortisol regulation, brain development, epigenetic regulation, and autonomic nervous system functioning. In consideration of this literature, the American Academy of Pediatrics encourages universal interventions to promote relational health. Since interventions that improve relational health may reduce the negative consequences of ACEs, many pediatricians are searching for feasible, evidence-based parenting advice, materials, and programs to implement in their clinics. The goal of this review was to identify and present parenting interventions in such a way that pediatricians can make an informed choice about what to implement and with what resources. Therefore, our specific aims were: (1) To identify interventions that focused on parenting education about healthy parent-child relationships, involved a pediatric primary care practice, and measured child or parent-child outcomes; (2) To describe characteristics of effective interventions; and (3) To offer guidance regarding strategies to improve relational health and related outcomes. This review followed the reporting guidelines for the PRISMA extension for scoping reviews (PRISMA-ScR). A flow diagram of our literature search is illustrated in . In March 2021, we searched for systematic reviews of parenting education by pediatric providers published in English from January 2000 to December 2020. Key search terms were “Intervention” AND (“Parenting” or “Parent-child relations”) AND (“Pediatric primary care” or “Primary health care”). The search was performed in PubMed, PsychInfo, SocIndex and Web of Science. In July 2023, this search was repeated from January 2021 through June 2023. Systematic reviews were included if they contained primary studies of parenting education about healthy parent-child relationships in a pediatric primary care setting. The full-text of the systematic reviews were then evaluated by 2 independent reviewers. Primary studies were included if they (1) evaluated an intervention that focused on parenting education about healthy parent-child relationships, (2) involved a pediatric primary care practice (see column “pediatricians” for specific types of involvement); and (3) measured child or parent-child outcomes. All studies of parenting education through pediatric primary care were included, regardless of whether child ACEs were measured. Studies that did not isolate the impact of parenting education but combined with other interventions (such as pharmacotherapy) were excluded. In addition, descriptive studies and pilot work that did not report outcomes on a comparison group or did not demonstrate a statistically significant difference between groups due to low power were excluded. , Extracted data included key components of the intervention; research design; child physical, behavioral, and developmental outcomes; parent-child relationship and parent mental health outcomes. Disagreements among reviewers were discussed and resolved by consensus. For interventions with 2 or more publications, emails were sent to first authors to validate the accuracy of intervention descriptions and outcomes. Results were collated by statistically significant outcomes and qualitatively analyzed for patterns across intervention components and information content. In addition, a 2 × 2 matrix was used to stratify interventions by the extent to which pediatric clinical staff were involved in the intervention and the extent to which additional professionals were needed. We identified 35 systematic reviews of which 11 met inclusion criteria. Three additional systematic reviews were identified by reviewing reference lists of the first 11 reviews or personal libraries. - From these 14 systematic reviews, a total of 25 unique parenting education interventions met inclusion criteria. Four of these parenting interventions did not improve outcomes more than the comparison group. - provides a summary of intervention components for the remaining 21 interventions, provides a summary of information content, and provides a contrast and comparison of interventions. Three interventions were delivered specifically to pediatric patients with ACEs, , , 5 were delivered to pediatric patients with behavioral concerns, , , , , 2 were delivered to low education or income families, , and the remaining eleven were delivered to general pediatric populations. Additional information on all the interventions can be found in the . Interventions That Improved Child Physical Outcomes Four out of 8 (50%) of the studies that measured any type of child physical health outcome demonstrated a statistically significant difference from the comparison group. One pilot study of THRIVE (Teaching Healthy Responsive parenting during Infancy to promote Vital growth and rEgulation) for general pediatric patients age 0 to 6 months found improvement in infant conditional weight gain. This study used co-located psychology fellows to discuss responsive parenting at well-child care, including eating and sleep routines, and was compared to a control group that focused on mental health. Two interventions for children with ACEs reduced child injuries and assaults. One was a nurse home visiting program for infants which offered connection to community resources, parenting education, and social support. The other was the Safe Environment for Every Kid ( SEEK ) intervention for age 0 to 5 years and trained pediatricians to offer information and community resources related to depression, substance abuse, partner violence, and stress, in addition to making a social worker available. , The Minnesota Violence Prevention program reduced fight-related injuries. This program was for children age 7 to 15 years with behavioral health symptoms, and provided information about child development, positive parenting, discipline and decision-making using a parenting manual, videotapes, and weekly phone coaching over 6 weeks. Interventions That Improved Child Developmental Outcomes Four out of the 9 (44%) interventions that measured child developmental outcomes demonstrated improvements. The Video-taped Interaction Project ( VIP ) utilized a co-located developmental specialist who met with families individually and reinforced positive interactions, in addition to sharing written information, books, and toys. - A Caribbean Parenting Intervention utilized community health workers and nurses to discuss waiting room videos and message cards about topics that included showing love, comforting, talking, praising, bath time, reading, and playing. Both interventions improved cognitive development. VIP also improved expressive language, as did a program based upon Touchpoints that utilized parent coaches, handouts, videos, and follow-up home or telephone visits. A fourth intervention improved social-emotional development compared to the group who declined the intervention. This intervention by a pediatric psychologist was done at clinic or home-based visits and included parenting topics (such as discipline, sleep, feeding, and toileting), as well as information about developmental goals, play therapy, parent-child interaction therapy, and community resources. Interventions That Improved Child Behavioral Outcomes Eleven out of the 13 (84%) interventions that measured child behavior improved outcomes. Eight improved outcomes more than the comparison, including the Minnesota Violence Prevention program and VIP. The majority targeted children ages 2 years or older with parental concerns about child behavior. A self-directed intervention enhanced imitation and play for toddlers from low-income and/or low education families through monthly newsletters, learning materials, and developmental questionnaires. All of the other interventions that were superior to the comparison condition utilized support staff other than the pediatrician. The Child-Adult Relationship Enhancement in Primary Care ( PriCARE ) program utilized co-located mental health professionals to run weekly positive parenting groups over 6 weeks. , Primary Care Triple P (Positive Parenting Program) utilized nurses to run four 2-h group sessions, in addition to weekly telephone calls, tip sheets and videos related to child development, behaviors, and positive parenting. - In Healthy Steps, a developmental specialist provided guidance on child development, parent support, and community resources through parent groups, home visits, and phone follow-up. , In the Doctor Office Collaborative Care ( DOCC ) program, social workers met with individuals or groups over 6 months and provided information about managing stress, promoting positive behavior, anger control, and social skills. Parenting Matters utilized phone coaching by clinical psychology students weekly over 6 weeks and provided information about child development, behaviors, positive parenting and discipline. Interventions That Improved Parent-Child and/or Parent Mental Health Outcomes Eighteen out of 20 (90%) interventions that measured parent-child outcomes improved outcomes. Seventeen improved outcomes more than the comparison group, including Queensland Home Visits, SEEK, , Caribbean Parenting, Minnesota Violence Prevention, Building Blocks, - VIP, , - PriCARE, , DOCC, Primary Care Triple P, - and Healthy Steps. In addition, 4 interventions improved outcomes through counseling by pediatricians. The Care for Development Intervention trained pediatricians in use of a standardized interview at acute visits and teaching parent strategies for listening, observing, praising, playing, and making homemade toys. Play Nicely trained pediatricians to talk with parents about plans for discipline after they viewed a related video. - A third intervention focused on having pediatricians provide educational pamphlets, books, and videos at well-child care. , Another well-child care intervention focused on normal development and responsiveness to infant social behaviors. , Three additional interventions relied on support staff. Both the Baltimore Home Visits program which utilized nurse home visitors and the Toddlers without Tears program that utilized facilitated parenting groups improved emotional responsiveness and reduced harsh parenting. Also, a low-intensity intervention that had clinic staff provide finger puppets and a list of suggested activities at the 2-month well-child visit demonstrated increased cognitive stimulation, as well as reduced parental depression. , Ten of the 13 (77%) interventions that also measured parent mental health outcomes demonstrated reductions in parent stress, depression, anxiety, and/or smoking. , , , , , , , , , Four out of 8 (50%) of the studies that measured any type of child physical health outcome demonstrated a statistically significant difference from the comparison group. One pilot study of THRIVE (Teaching Healthy Responsive parenting during Infancy to promote Vital growth and rEgulation) for general pediatric patients age 0 to 6 months found improvement in infant conditional weight gain. This study used co-located psychology fellows to discuss responsive parenting at well-child care, including eating and sleep routines, and was compared to a control group that focused on mental health. Two interventions for children with ACEs reduced child injuries and assaults. One was a nurse home visiting program for infants which offered connection to community resources, parenting education, and social support. The other was the Safe Environment for Every Kid ( SEEK ) intervention for age 0 to 5 years and trained pediatricians to offer information and community resources related to depression, substance abuse, partner violence, and stress, in addition to making a social worker available. , The Minnesota Violence Prevention program reduced fight-related injuries. This program was for children age 7 to 15 years with behavioral health symptoms, and provided information about child development, positive parenting, discipline and decision-making using a parenting manual, videotapes, and weekly phone coaching over 6 weeks. Four out of the 9 (44%) interventions that measured child developmental outcomes demonstrated improvements. The Video-taped Interaction Project ( VIP ) utilized a co-located developmental specialist who met with families individually and reinforced positive interactions, in addition to sharing written information, books, and toys. - A Caribbean Parenting Intervention utilized community health workers and nurses to discuss waiting room videos and message cards about topics that included showing love, comforting, talking, praising, bath time, reading, and playing. Both interventions improved cognitive development. VIP also improved expressive language, as did a program based upon Touchpoints that utilized parent coaches, handouts, videos, and follow-up home or telephone visits. A fourth intervention improved social-emotional development compared to the group who declined the intervention. This intervention by a pediatric psychologist was done at clinic or home-based visits and included parenting topics (such as discipline, sleep, feeding, and toileting), as well as information about developmental goals, play therapy, parent-child interaction therapy, and community resources. Eleven out of the 13 (84%) interventions that measured child behavior improved outcomes. Eight improved outcomes more than the comparison, including the Minnesota Violence Prevention program and VIP. The majority targeted children ages 2 years or older with parental concerns about child behavior. A self-directed intervention enhanced imitation and play for toddlers from low-income and/or low education families through monthly newsletters, learning materials, and developmental questionnaires. All of the other interventions that were superior to the comparison condition utilized support staff other than the pediatrician. The Child-Adult Relationship Enhancement in Primary Care ( PriCARE ) program utilized co-located mental health professionals to run weekly positive parenting groups over 6 weeks. , Primary Care Triple P (Positive Parenting Program) utilized nurses to run four 2-h group sessions, in addition to weekly telephone calls, tip sheets and videos related to child development, behaviors, and positive parenting. - In Healthy Steps, a developmental specialist provided guidance on child development, parent support, and community resources through parent groups, home visits, and phone follow-up. , In the Doctor Office Collaborative Care ( DOCC ) program, social workers met with individuals or groups over 6 months and provided information about managing stress, promoting positive behavior, anger control, and social skills. Parenting Matters utilized phone coaching by clinical psychology students weekly over 6 weeks and provided information about child development, behaviors, positive parenting and discipline. Eighteen out of 20 (90%) interventions that measured parent-child outcomes improved outcomes. Seventeen improved outcomes more than the comparison group, including Queensland Home Visits, SEEK, , Caribbean Parenting, Minnesota Violence Prevention, Building Blocks, - VIP, , - PriCARE, , DOCC, Primary Care Triple P, - and Healthy Steps. In addition, 4 interventions improved outcomes through counseling by pediatricians. The Care for Development Intervention trained pediatricians in use of a standardized interview at acute visits and teaching parent strategies for listening, observing, praising, playing, and making homemade toys. Play Nicely trained pediatricians to talk with parents about plans for discipline after they viewed a related video. - A third intervention focused on having pediatricians provide educational pamphlets, books, and videos at well-child care. , Another well-child care intervention focused on normal development and responsiveness to infant social behaviors. , Three additional interventions relied on support staff. Both the Baltimore Home Visits program which utilized nurse home visitors and the Toddlers without Tears program that utilized facilitated parenting groups improved emotional responsiveness and reduced harsh parenting. Also, a low-intensity intervention that had clinic staff provide finger puppets and a list of suggested activities at the 2-month well-child visit demonstrated increased cognitive stimulation, as well as reduced parental depression. , Ten of the 13 (77%) interventions that also measured parent mental health outcomes demonstrated reductions in parent stress, depression, anxiety, and/or smoking. , , , , , , , , , The purpose of this review was to identify pediatric primary care interventions that focused on improving relational health and thereby might reduce the negative consequences of ACEs. Our results demonstrate that a range of low to high intensity interventions can improve relational health, such as decreased corporal punishment and psychological aggression, as well as increased maternal-child attachment, stimulating interactions, and sensitivity. Lower intensity interventions improved relational health simply through distribution of written materials, toys that encouraged interactive play, , or enhanced pediatrician counseling about parent-child interactions. , , , - Higher intensity interventions involved pediatricians through screening and/or team meetings, as well as collaboration with nurse home visitors, social workers, or parent coaches. - , , The 3 studies that demonstrated improved relational health in pediatric patients with known ACEs were high intensity in both pediatrician involvement and use of additional professionals. , , However, the majority of interventions that measured parent mental health demonstrated improvements, which suggests the potential for pediatric parenting interventions to reduce child exposure to ACEs and have clinical merit beyond the direct impact on the child. , , , , , , , Child behaviors were also improved by a range of low to high intensity interventions. For example, 3 interventions were not superior to the comparison because child behaviors were improved by the low intensity comparison, specifically handouts only, books only, and phone coaching as opposed to in person coaching. In addition, Building Blocks demonstrated enhanced child play and parent-child interactions, while lowering maternal depression, based only upon distribution of newsletters and learning materials. Thus, pediatric practices that have limited resources to add support staff should keep in mind that sharing written information with families about positive parenting and play can be impactful. By contrast, improving child development and reducing injuries required multicomponent interventions including support from additional professionals, such as developmental specialists, psychologists, social workers, parent coaches, and community health workers. In addition, all of the interventions that reduced child injuries , , and half of the interventions that improved child development , also focused on connecting families to community resources, including information about parent mental health. Positive parenting focuses on influencing child behavior through praise for positive behaviors and discipline strategies for negative behaviors. By contrast, responsive parenting focuses on building relationships between parents and children by listening to children, playing with them, and helping them to understand and manage their emotions. Of the interventions that improved child behavior and development, all included information about positive parenting strategies. Less than half of the interventions included responsive parenting content, and only 3 interventions included information specific to developing emotion regulation. Children affected by ACEs have been exposed to or are living with caregivers who have challenges with emotion regulation and stress management. Therefore, research is warranted to evaluate whether parenting education that incorporates information about responsive parenting is particularly helpful to reducing the negative consequences of ACEs. Some limitations should be considered when interpreting our results. First, our conclusions may overestimate the efficacy of interventions due to publication bias. We tried to address this by reaching out to authors and making sure that our results included both significant and non-significant findings. Second, our review treated all of the interventions as having equal validity although some have been evaluated more extensively, particularly Healthy Steps and VIP. Most studies also only examined short-term impact, although Healthy Steps and VIP are exceptions. Furthermore, a variety of other pediatric interventions may impact child or parent-child outcomes but were not included in this review because they do not focus on education about parent-child relationships. For example, Reach Out and Read does not focus on education about parent-child relationships so was not included in this review, but does focus on child development with studies demonstrating positive impacts on language development and parent-child interactions. The results of this review should be considered in the context of the broader literature on pediatric interventions. Our results demonstrate a lack of parenting interventions to date that measured child physical health outcomes or biomarkers. More studies are needed that specifically evaluate the impact of pediatric primary care parenting interventions for children with ACEs, and more studies are needed on samples of school-age and adolescent patients. In conclusion, this review provides a summary of pediatric primary care parenting intervention components and content which can be used by pediatricians to guide their selection of strategies to improve relational health and related outcomes. Our results highlight the potential for feasible, low-intensity interventions to improve relational health and child behaviors. Given that ACEs increase the risk for mental, physical, and developmental health issues across the lifespan, policies that support parents and access to parenting interventions are warranted, as is research funding to expand knowledge about how to foster healthier, more resilient communities. sj-docx-1-jpc-10.1177_21501319241306302 – Supplemental material for Parenting Education to Improve Relational Health Through Pediatric Primary Care: A Scoping Review Supplemental material, sj-docx-1-jpc-10.1177_21501319241306302 for Parenting Education to Improve Relational Health Through Pediatric Primary Care: A Scoping Review by Ariane Marie-Mitchell, Cindy Delgado and Rachel Gilgoff in Journal of Primary Care & Community Health |
The quest for the human ocular accommodation mechanism | efcedde4-fb9c-4b79-bfb9-2a132cf5c6da | 7004159 | Ophthalmology[mh] | Huygens seems to have coined the word ‘accommodation’ in ophthalmic optics by writing AD 1703 that the eye: ‘ita nunc ad has nunc ad illas res se accommodet’ (adapts itself now to this, now to yonder matter) (Huygens ). That is in essence what ocular accommodation means; the potential of an eye to change its refractive power to maintain a clear focus both on distant and nearby objects. For many years, people knew from daily experience that accommodation existed but could not establish its mechanism. The aim of this historical review is to show the difficulties they encountered while finding definite proof how accommodation functions.
The Greeks and the Romans had no idea about the refraction of light in the eye. The Greeks thought that we see by a ‘pneuma’ escaping from the eye in the shape of a cone or by ether that moved from objects to the eye. The symptoms of accommodation were known around 500–300 BC but people explained accommodation by efforts of a ‘soul’ in the eye, in analogy to a brain thinking about difficult questions (Magnus ). They considered accommodation paresis with pupillary dilatation to be due to fluid accumulation in the iris. In Galen's era, AD 200, senile accommodation loss was known, and also that accommodation is hampered by abuse of opium, mandrake or hyoscyamine (Magnus ). Galen assumed that there were seven external eye muscles inserted around the optic nerve. He explained accommodation by muscle activity of the seventh (non‐existent) external choanoides or retractor muscle. This muscle survived another 1300 years in medical texts and thus Vesalius still drew it in the middle of the 16th century (Fig. ) (Vesalius ; Magnus ). Over the years, the ciliary body became associated with accommodation, so we will first have a look at this body.
Duke‐Elder wrote that the name of this body stems from cilia, hair (Duke‐Elder ). Cilium is the Latin word for eyelid and Zinn mentioned that even before Galen, anatomists compared the ciliary body with an eyelid having lashes (Zinn ). He complained about the inconsequent nomenclature of many anatomists and used the term ciliary body that Falloppius had introduced (Falloppius ). Lucretius, just before the beginning of our era, considered this body a belt that connected different tissues and strengthened the eye wall. Vesalius named the ciliary body a tunic derived from the uvea, resembling eyelashes attached to the lens equator (Vesalius ). Kepler hypothesized that the ciliary processes contract during accommodation and become shorter, pulling the lateral parts of the eye inwards and thus elongating the eye (Kepler ). According to Duke‐Elder, Boerhaave mentioned in 1708 muscular fibres in the ciliary muscle and English scientists described these fibres before Brücke (Duke‐Elder ). Camper, however, did so already earlier (Camper ). Boerhaave described in the various editions of his published lectures muscle fibres in the iris and it remains unclear whether he saw these or assumed them to be there because of the pupillary reactions (Boerhaave ; Glauder ; Haller ). Porterfield refered to the muscularity of the ciliary ligament mentioned by many anatomists and did not find muscle fibres himself (Porterfield ). A century later, many animals, from fish to lynx and rhinoceros, were shown to have a ciliary ligament (Wallace ). Wallace could not obtain human eyes and surmised that contraction of these (hypothetical) muscle fibres compressed the ciliary veins, thus erecting and expanding the ciliary processes (Wallace ). He referred to Knox who wrote extensively on the ciliary muscle (the white ring as he called it) but also Knox could not find muscle fibres, even with a microscope (Knox ). Therefore, it seems that Brücke indeed described for the first time in the human eye the choroidal tensor muscle running in an axial direction in the ciliary body. This muscle was partly attached by an elastic mesh to the inner wall of Schlemm's canal and to the corneal basement membrane (Fig. a) (Brücke ). His teacher Müller added circular smooth muscle fibres parallel to the corneal limbus (Fig. b) (Müller ). The ciliary muscle seems to have three sections: a. on the scleral side a longitudinal layer running from the tendon attached to Schlemm's canal to the choroid; b. oblique fibres from the same tendon dividing in b1, towards the tails of the ciliary processes and b2 forming the smooth ring in the heads of these processes near Schlemm's canal (see g in Fig. b); c, meridional fibres running forward with subsections c1 going into the heads of the processes and c2 running into the iris (Duke‐Elder ). According to Donders, the ciliary muscle functions also as origin of the dilating muscle of the iris (Donders ).
In the early 17th century, the ciliary processes were accredited to move the vitreous and the lens forwards or backwards by contraction and relaxation and thus to flatten or bulge the lens, according to whether one is looking at objects far away or close by (Fig. ). Descartes considered accommodation a voluntary process, even when a person is unaware of the fact that he accommodates, because he intends to see close objects well. Van Leeuwenhoek, 100 years later, mistook fibres in the lens (and even fibres in the vitreous) for muscular fibre tendons (Van Leeuwenhoek ). This may have put subsequent researchers like Young & Brocklesby ( ) on the wrong track. Jurin hypothesised, spurred by a thesis of Pemberton, (Pemberton ) that ‘For many reasons the most advantageous and convenient method for the eye to be accommodated to near objects seems by rendring the anterior surface of the crystalline more convex, while the hinder surface grows flatter. But this surely is too great a change for a substance of such a consistence as the crystalline humour to admit of’ (Jurin ). Thus, he found ‘No satisfaction in any of the hypotheses above related’ and next focused on the cornea and uvea as the sites where accommodation took place. The Table gives an overview of the wide variation in hypotheses and results of animal and human research on accommodation. Home tore instead of cut the rectus muscles from a human eye after death. Thus, he found that the rectus tendons became broader on approaching the cornea, forming a circle of which the cornea seemed to be the central continuation. This explained in his view the change in corneal radius of curvature during accommodation (Fig. ) (Home ). Young & Brocklesby ( ) assumed that accommodation is a voluntary process leading to nerve impulses that ran via the lenticular ganglion and the ciliary processes to the crystalline muscle, making the lens more convex. In a later paper, Young described improvements on Porterfield's optometer, demonstrated that accommodation does not exist in aphakia, and excluded corneal, axial length or electrical changes as its mechanism. With data from his optometer, he predicted on theoretical grounds that during accommodation the axial length of the lens increases, leading to a greater relative convexity of the posterior lens surface than that of the anterior one. He thought that this expansion occurred by swelling of the muscular fibres in the lens (Young ).
In 1848, a contest in the Netherlands was organized to solve the accommodation mechanism. In order to see how researchers overcame the deadlock in contradictions (Table ), we have to go back 200 years. Scheiner described the reflection of a candle on the cornea (Scheiner ). Purkinje, a great (myopic) observer, discovered with bare eyes that there were, apart from this corneal image, more ocular candle reflections. These originated from the corneal endothelium and from the anterior lens surface, both acting as a convex mirror, as well as from the posterior lens or anterior vitreous surface (acting as a concave mirror) (Purkinje ). The endothelial image and more secondary images were hard to see. For practical purposes, authors restricted themselves to an upright image 1 from the corneal epithelium, upright image 2 from the anterior lens surface and an inverted image 3 from the posterior lens surface (Fig. ). Sanson independently re‐discovered images 2 and 3 and described how one could use these images to differentiate between vision loss due to cataract or to other causes deeper in the eye (Sanson ). Bear in mind that this was before the invention of the slitlamp or the ophthalmoscope. The German surgeon Langenbeck stressed a year later the diagnostic value of the size, colour and relative distance of the Purkinje‐Sanson images from each other. He examined, also bare‐eyed, these images with a candle in front of an eye instead of to its side, thus hampering their observation because the images were nearly superimposed. Langenbeck wrote about the (in humans non‐existent) ‘musculus compressor lentis accommodatorius,’ and mentioned that accommodation was due to a change in lens position but also that the anterior lens surface became more convex during accommodation (Langenbeck ). Donders calculated that displacement of the lens could not account for the normal range of accommodation and published his hypothesis that by carefully measuring the Purkinje images under telescopic magnification, one could solve the accommodation mystery. He predicted that during accommodation, the first and second Purkinje images would remain in place and that the third (middle one) would move, pointing to a change in curvature of the anterior lens surface (Fig. ) (Donders ). He wrote, ‘The mechanism of the accommodation capacity is still unclear. I believe I have sufficient reasons to position its origin inside the eye, without completely thus clarifying its mechanism. The hypothesis that the root of the accommodation capacity lies in the oblique eye muscles is unjustified’ (Donders ). Cramer published his preliminary results in the accommodation contest describing the increasing curvature of the anterior lens plane (Cramer ). In 1852, he received the first prize including a gold medal, and his prize winning manuscript was published in 1853, in which he wrote that hyperopic eyes cannot accommodate (Cramer ). Cramer, who acknowledged Donders's predictions in both publications, built an ‘ophthalmoscope’ (Fig. ) and performed many experiments to prove that the weak parts of the lens create the change in its anterior curvature during accommodation. Only then did it become clear that the 200‐year‐old hypotheses of Scheiner and Descartes and the one rejected by Jurin were correct. In addition, Langenbeck's observation now became better known to the public. Cramer found that in accommodation, the middle image becomes smaller indicating a smaller radius of curvature of the anterior lens surface. Donders had three modifications made of the ‘ophthalmoscope’ of Cramer, who died in 1855, (Swaagman ) and named these a ‘phacoidoscope.’ By using his phacoidoscope, Donders could see tiny changes in the distance of the posterior Purkinje image, sometimes approaching the corneal image, sometimes increasing its distance. The lens equator remained more or less in the same position during accommodation. Helmholtz started his article on accommodation by claiming priority over the discovery of Cramer and Donders because he discovered late in 1852 changes in the reflections of the anterior lens surface during accommodation and sent this discovery to the Academy of Sciences in Berlin (Helmholtz ). He went on, however, writing that he overlooked the earlier publications of Donders and Cramer as well as Langenbeck's one on this matter. ‘After obtaining Cramer's work by the kindness of Mr. Donders, I convinced myself that the enigma of accommodation, in which so many researchers have in vain practiced their ingenuity, mainly was solved, and the intended investigation left me little more to do’(Helmholtz ). Helmholtz measured more accurately the Purkinje images in the eyes of three humans aged 30–35 years with an ophthalmometer. Its construction was based on the heliometer of astronomers, by which he obtained an accuracy of 0.01 mm on a moving eye. He measured all he could; for example, the distance from the corneal apex to the pupillary plane was 3.7–4.0 mm and to the posterior lens surface, 6.9–7.1 mm. After death, lenses become thicker. During accommodation, the pupillary plane came 0.36–0.44 mm forwards. Helmholtz confirmed Cramer's reduction of the middle image and wrote that the posterior lens radius of curvature became a little smaller (Helmholtz ). Having reached consensus about the change in lenticular curvature during accommodation, there remained controversy about how exactly this took place. Helmholtz agreed with Young, Cramer and Donders that the corneal curvature does not change during accommodation. He thought together with Brücke that ciliary muscle contraction pulls the choroid and the zonules forward towards Descemet's membrane, receding the iris, slackening the zonules and thus the anterior lens surface bulges through its capsular elasticity. Helmholtz assumed that in the relaxed state of the eye while looking in the distance, the zonules are tightened and thus flatten the lens. He was uncertain whether the circular fibres in the ciliary muscle were the main active fibres and the radial fibres only auxiliary ones. His conclusion was: ‘So we hardly can deny the ciliary body some function in the accommodation process’ (Brücke ; Helmholtz ). The posterior surface of the lens remains in place, and the lens volume does not change, so the centre of the lens becomes thicker (Helmholtz ; Henke ). Donders was the first to show that even before puberty the accommodation range starts to diminish both in myopia, emmetropia and hyperopia (Donders ). After examining various bird eyes, Müller thought that the ciliary muscle increased in thickness by contraction of the longitudinal fibres, thus slackening the anterior part of the zonules together with pressure of the circular ciliary muscle and the iris on the peripheral lens part (Müller ; Duke‐Elder ). Donders did not believe in this pressure of the circular fibres and the iris on the lens rim and considered it essential to measure first the circumference of the lens during accommodation (Donders ). Cramer used electrical currents in the ciliary region of enucleated seal and bird eyes to show that changes during accommodation occurred as long as the iris was intact, but nothing happened when he removed the iris or made radial cuts in it. Weber and Von Graefe assumed that there was a separate positive accommodation mechanism in myopic eyes and a negative one in hyperopic ones (Weber ). Knapp found a high concordance between his measurements and the visual determination of accommodation (the push‐up method of Donders). Accommodation in aphakia was questionable, not only by his measurements but also by the various experiments of Donders in Utrecht in which Knapp could participate (Knapp ). Tscherning challenged Helmholtz's suspicion that the lens is flatter seeing in the distance through the pull of the zonules. He considered the function of the iris for accommodation not proven and mentioned that Von Graefe demonstrated intact accommodation in complete aniridia (Tscherning ). According to Tscherning, Helmholtz and Donders took insufficient account of the peculiar structure of the ciliary muscle. Henle stressed that the circular and meridional muscle fibres of the ciliary body had a separate function and Iwanoff, Arlt and Sattler, who found hypertrophy of the circular fibres in hyperopia and of the meridional fibres in myopia, confirmed this (Tscherning ). Tscherning also mentioned the lack of knowledge about innervation of the ciliary muscle. He thought that the oculomotor nerve and perhaps also the sympathetic nerve were the accommodation nerves (Tscherning ). Cramer thought that the trigeminal and sympathetic nerve were involved (Cramer ). At present, the parasympathetic nerve is considered to the main one for accommodation (Drexler et al. ). Tscherning postulated a downwards and backwards lens movement during accommodation as well as central vitreous liquefaction with dilation of Cloquet's canal (Tscherning ). At present, one finds in PubMed over 200 publications on the mechanism of the human ocular accommodation mechanism and these are beyond the scope of this review. Preliminary data, however, obtained with anterior segment optical coherent tomography showed the complexity of the human ciliary muscle action. During a 4 diopter accommodation stimulus, the maximum ciliary muscle thickness increased by 69.2 μ m (18.1 μ m per diopter) at about 1 mm posterior to the scleral spur but the muscle thickness decreased by 45.9 μ m (−12.0 μ m per diopter) at 3 mm from this spur. So indeed the portion of the ciliary body closest to the cornea bulges most. Unfortunately the zonules were absent on the images provided (Lossing ). The most sophisticated measuring instrument, a scanning partial coherence interferometer, found that in an emmetropic 30‐year‐old human eye, the anterior pole of the lens moved 228 μ m forwards and the posterior lens pole 75 μ m backwards when changing from distant vision to focusing on the near point. This ratio of three to one held for all 10 eyes tested (Drexler et al. ). Most remarkably, it seems that the absolute values found 160 years ago differed only by 0.1–0.2 mm from the present ones. Only recently a fascinating review on accommodation mechanisms in various animals appeared (Ott ). Nearly all options mentioned over the centuries for these mechanisms in humans (Table ) occur in the animal kingdom. They range from independent monocular accommodation between paired chameleon eyes, combined as well as independent accommodation between the two eyes of hawks and vultures, influence of retinal thickness on accommodation in small eyes, corneal changes and anterior lenticonus to shifting lens positions in cats. A sea otter is emmetropic above water and can see well under water because of a 60 diopter accommodation range. Humans and fish have a less perfect stimulus response function for accommodation than lizards and turtles (Ott ). It is no wonder that our predecessors were for so long groping in the dark, comparing animal eyes with human ones.
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Abortion assistance fund staff and volunteers as patient navigators following an abortion ban in Texas | 67bf2b2e-c70a-493c-a4f3-176ac277e777 | 10808264 | Patient-Centered Care[mh] | Federal and state‐level restrictions on abortion coverage in Medicaid and private insurance plans in the United States (US) make it difficult for patients seeking abortion—many of whom are racially and structurally disenfranchised—to pay the out‐of‐pocket costs for care. , , These expenses can be especially burdensome for patients who require care later in pregnancy or who must travel because the services they need are not available in their community. , , , In the absence of insurance coverage, national and local organizations that provide financial assistance for abortion‐related costs (i.e., assistance funds) constitute an important part of the healthcare safety net. There are two primary types of assistance funds: those that help pay for someone's abortion (i.e., abortion funds), and those that cover some of the costs related to travel, childcare, and other logistical needs (e.g., practical support funds). , , Some funds provide both types of assistance, and local assistance funds may also advocate for cultural and policy change that support reproductive autonomy, de‐stigmatize abortion, and center racial and economic justice. , , To provide financial support, abortion funds go through an extensive process of establishing agreements with individual abortion facilities to pay a fixed cost (i.e., pledge or voucher) for each patient, and then remit payments once someone has received care. Practical support funds coordinate with hotels for callers needing overnight stays and pools of volunteers who help with transportation. National abortion assistance funds have paid staff, whereas local funds may have one or two paid staff but rely largely (or exclusively) on volunteers who work directly with callers seeking assistance. The level of financial support provided and number of callers who receive assistance varies according to funds' operating budgets, which is based on grants and donations. Both national and local abortion assistance funds often collectively support callers to cover the cost of and coordinate care. Prior research of local abortion funds' work has largely focused on the level of funding provided and characteristics of those requesting assistance, demonstrating the financial needs of adolescents, Black and Latina women, and parents. , , , There has been more limited study of the ways in which abortion assistance fund staff and volunteers offer person‐centered support to callers who need help navigating an unfamiliar healthcare landscape, which has been made increasingly complex by other restrictions on abortion, such as waiting period requirements and gestational duration limits on abortion. Few studies have examined the work of practical support funds. Abortion assistance funds will play a growing role in bridging pregnant callers' connections to abortion care, as state policies that further constrain access and court decisions that undermine the protections established by Roe v. Wade widen geographic gaps in the availability of services. Therefore, expanding knowledge of abortion assistance funds' roles can inform future strategies that may support these organizations, and in turn, those needing assistance. Texas is a useful state to assess the role that assistance funds play in abortion access. There are nearly a dozen abortion assistance funds in Texas, many of which support pregnant callers within a specific geographic region in this large state. Even prior to the US Supreme Court's decision overturning Roe v. Wade and the implementation of Texas' trigger law banning nearly all abortions in 2022, the state had one of the most restrictive abortion policy environments in the United States. Among the dozens of state‐level restrictions that made abortion difficult to afford and obtain were prohibitions on abortion coverage in Medicaid, Marketplace plans, and private insurance except for rare circumstances; a requirement that patients make an in‐person visit for a mandatory ultrasound at least 24 h before their abortion; a requirement that minors obtain parental consent (or undergo a judicial bypass) before their abortion; and laws narrowing the gestational duration at which patients could obtain an abortion. , Additionally, following the 2013 implementation of an abortion law that included targeted restrictions on abortion providers, half of Texas abortion facilities closed; this left large areas of the state more than one hundred miles from the nearest provider and forced many Texans to travel out of state for care. , In this study, we explore how Texas' abortion assistance funds responded to a prior ban on abortion to support callers who faced difficulties obtaining in‐state abortion care following the onset of the COVID‐19 pandemic. On March 20, 2020, Texas Governor Greg Abbott issued an executive order that prohibited surgeries and procedures that were not considered immediately medically necessary for a period of 30 days, and the state's Attorney General, Ken Paxton, specified that this included abortion services. , While the order was being challenged in court, abortion facilities canceled and rescheduled hundreds of appointments to comply with changing legal decisions. During this time, many patients delayed care or obtained services out of state. , Situating the work of local abortion assistance funds in the frameworks of reproductive justice and health activism, , , we describe how staff and volunteers at these organizations function as “navigators” or lay members of a healthcare team who assist callers overcoming obstacles to displaced care. We also show how staff and volunteers work together with callers to co‐create a plan for their care that maintains a focus on autonomy and person‐centered support.
Recruitment and data collection In April 2020, shortly after the Texas governor issued the executive order, our research team organized a call with representatives from several Texas‐based abortion assistance funds to discuss approaches for capturing how the order was affecting pregnant Texans needing assistance. Following a series of meetings, we agreed to move forward with a qualitative study to explore how the executive order affected local abortion assistance funds' operations and how staff and volunteers worked to support callers during this time. Based on these conversations, we developed a draft interview guide and then elicited feedback from staff at two organizations who had attended the initial planning meetings to ensure the questions reflected the discussions. We revised the guide based on this feedback. Between June and September 2020, we used existing contacts and referrals to invite staff and volunteers at local abortion assistance funds to participate in an in‐depth interview. We contacted all nine abortion assistance funds that were operating in Texas at the time, as well as four abortion assistance funds in three other states that our contacts indicated had supported Texas residents seeking abortion care during the executive order. Although national abortion assistance funds also supported Texans during this time, we did not contact staff at these organizations for the study because we were interested in studying the local response to the executive order. We aimed to interview at least one respondent from each organization who could speak to operational matters and had experience with callers during the executive order. Owing to variation in the number of people involved with local abortion assistance funds and differences in scope of work, we interviewed between one and five respondents at each organization. After respondents described their tenure, role, and responsibilities at the organization, we asked them to discuss the types of changes they noticed after the order went into effect, including changes in call volume and types of requests, experiences with callers whose appointments had been canceled or who needed to go out of state, different approaches used to support callers, and effects of the pandemic on callers in general. We also asked respondents to discuss any changes in funding or organizational partnerships that transpired during this time. Members of the research team (OLW, AD) who collectively had graduate training in sociology, social work, and public affairs, prior qualitative research experience, and extensive contextual knowledge of Texas' abortion policies and assistance fund networks conducted the interviews by phone. Respondents provided their oral consent to participate and have their interview recorded. They received a $40 gift card for participating. Interviews lasted between 30 and 75 min (median duration: 48 min). We stopped interviewing after all organizations had participated or did not respond after three attempts. A professional transcription service transcribed the interview recordings, after which, research assistants reviewed the transcripts for accuracy and de‐identified information. The institutional review board at KW's university approved the study procedures. Analysis We conducted thematic analyses to examine respondents' strategies to support callers seeking abortion care during the executive order. The research team (AD, BW, KW, OLW, and another colleague) first reviewed all transcripts and developed a preliminary coding scheme consisting of deductive and inductive codes based on domains in the interview guide and group discussions about emerging themes. Five members of the team then independently coded two transcripts and met to compare coding, refine coding definitions, and add codes to capture emergent ideas. Then, they divided the remaining transcripts and used a double coding process: after two people coded each transcript independently, the pair met to compare the consistency of coding and reach consensus about the most appropriate code if there were coding discrepancies. All five coders also met regularly to discuss the coding process and ensure consistency across transcripts. We used NVivo 12 to code and organize the transcript data. Because many of the ways that local abortion assistance fund staff and volunteers supported callers aligned with the activities of patient navigators, who assist people overcoming obstacles to care, we organized codes into domains of navigation in the next stage of analysis. These included bridging information gaps, providing emotional support, coordinating logistics, and providing financial support. We separated logistics and financial support into two themes owing to the different focus of local abortion assistance funds' activities and to allow for a more thorough analysis of these efforts. We also included a theme related to intersecting structural oppressions because this commonly emerged in respondents' narratives about supporting callers. Our summary of themes describes both how the executive order and pandemic shaped interactions with callers and the administrative and organizational changes that were needed to respond to these events by those with local knowledge and cultural expertise. Below, we refer to local abortion assistance funds based on the predominant method of support they offered callers before the executive order.
In April 2020, shortly after the Texas governor issued the executive order, our research team organized a call with representatives from several Texas‐based abortion assistance funds to discuss approaches for capturing how the order was affecting pregnant Texans needing assistance. Following a series of meetings, we agreed to move forward with a qualitative study to explore how the executive order affected local abortion assistance funds' operations and how staff and volunteers worked to support callers during this time. Based on these conversations, we developed a draft interview guide and then elicited feedback from staff at two organizations who had attended the initial planning meetings to ensure the questions reflected the discussions. We revised the guide based on this feedback. Between June and September 2020, we used existing contacts and referrals to invite staff and volunteers at local abortion assistance funds to participate in an in‐depth interview. We contacted all nine abortion assistance funds that were operating in Texas at the time, as well as four abortion assistance funds in three other states that our contacts indicated had supported Texas residents seeking abortion care during the executive order. Although national abortion assistance funds also supported Texans during this time, we did not contact staff at these organizations for the study because we were interested in studying the local response to the executive order. We aimed to interview at least one respondent from each organization who could speak to operational matters and had experience with callers during the executive order. Owing to variation in the number of people involved with local abortion assistance funds and differences in scope of work, we interviewed between one and five respondents at each organization. After respondents described their tenure, role, and responsibilities at the organization, we asked them to discuss the types of changes they noticed after the order went into effect, including changes in call volume and types of requests, experiences with callers whose appointments had been canceled or who needed to go out of state, different approaches used to support callers, and effects of the pandemic on callers in general. We also asked respondents to discuss any changes in funding or organizational partnerships that transpired during this time. Members of the research team (OLW, AD) who collectively had graduate training in sociology, social work, and public affairs, prior qualitative research experience, and extensive contextual knowledge of Texas' abortion policies and assistance fund networks conducted the interviews by phone. Respondents provided their oral consent to participate and have their interview recorded. They received a $40 gift card for participating. Interviews lasted between 30 and 75 min (median duration: 48 min). We stopped interviewing after all organizations had participated or did not respond after three attempts. A professional transcription service transcribed the interview recordings, after which, research assistants reviewed the transcripts for accuracy and de‐identified information. The institutional review board at KW's university approved the study procedures.
We conducted thematic analyses to examine respondents' strategies to support callers seeking abortion care during the executive order. The research team (AD, BW, KW, OLW, and another colleague) first reviewed all transcripts and developed a preliminary coding scheme consisting of deductive and inductive codes based on domains in the interview guide and group discussions about emerging themes. Five members of the team then independently coded two transcripts and met to compare coding, refine coding definitions, and add codes to capture emergent ideas. Then, they divided the remaining transcripts and used a double coding process: after two people coded each transcript independently, the pair met to compare the consistency of coding and reach consensus about the most appropriate code if there were coding discrepancies. All five coders also met regularly to discuss the coding process and ensure consistency across transcripts. We used NVivo 12 to code and organize the transcript data. Because many of the ways that local abortion assistance fund staff and volunteers supported callers aligned with the activities of patient navigators, who assist people overcoming obstacles to care, we organized codes into domains of navigation in the next stage of analysis. These included bridging information gaps, providing emotional support, coordinating logistics, and providing financial support. We separated logistics and financial support into two themes owing to the different focus of local abortion assistance funds' activities and to allow for a more thorough analysis of these efforts. We also included a theme related to intersecting structural oppressions because this commonly emerged in respondents' narratives about supporting callers. Our summary of themes describes both how the executive order and pandemic shaped interactions with callers and the administrative and organizational changes that were needed to respond to these events by those with local knowledge and cultural expertise. Below, we refer to local abortion assistance funds based on the predominant method of support they offered callers before the executive order.
Of the 13 local abortion assistance funds we contacted, we were able to interview respondents from 11 organizations: six abortion funds and five practical support funds. Of the 23 respondents interviewed, 14 were volunteers and had spent 9 months to 5 years helping with caller intake, returning calls to those who left messages (i.e., warmlines), or providing transportation. The nine paid staff members we interviewed had worked at their organization between one and 6 years, and many had previously volunteered at their organization or another abortion assistance fund. Bridging information gaps The suspension of abortion services following the executive order and the changing court decisions created confusion about whether and what types of services were available in Texas. Respondents frequently commented that it was difficult to stay abreast of circumstances that “were flip‐flopping every day,” and while the resulting uncertainty placed challenges on clinics, it most directly affected callers needing care. An abortion fund staff member described the difficult situation in Spring 2020 saying, “Because they [clinics] were in this limbo, they were also putting callers in this limbo, and by the time they [callers] would reach us, they had heard different information or they just didn't know what was going on.” Staff reported staying in more regular communication with in‐ and out‐of‐state clinics and other assistance funds about the changing status of services and policies so they could “be on the forefront of knowledge of what's happening and what we can expect to happen next” and then pass the information on to other staff and volunteers responding to caller inquiries. In addition to communicating with other organizations, a staff member said their abortion fund increased the number of days they operated, “because we wanted to be able to meet people wherever they were. Things were constantly changing … so we want to be prepared for that, and the way we thought we could do that was to stay open more, be available for people to reach us more.” However, it was not possible for some local abortion assistance funds with asynchronous, volunteer‐based models to connect with all callers needing information because the volunteers could not reach some callers during volunteers' shifts. Recognizing their unique position in an increasingly fragmented system of care, local abortion assistance funds also worked to bridge the information gaps by sharing their knowledge about available assistance with callers and engaging in thought partnership so callers could plan their next steps. In the words of an abortion fund volunteer, calls became less “transactional… A lot of the calls during this time were much more problem solving. Where can you go?” A practical support fund volunteer echoed this shift, explaining, “It was definitely a crisis management time… If someone calls, we can't just tell them, ‘I'm sorry, you're out of luck.’ That's not what we do here. Our job is to figure out a way around the barriers.” Staff and volunteers informed callers that financial assistance for both abortion costs and practical support were available and co‐created a person‐centered plan for securing services; this involved assessing callers' access to childcare and need for privacy and weighing the pros and cons of waiting for the order to expire versus traveling out of state. Respondents emphasized the importance of callers' autonomy, noting that their role was to provide “all of the community resources available to you to make this decision” and for callers to “feel supported the entire time.” For example, an abortion fund staff member described reassuring a caller who did not feel that she could travel out of state that she might be able to obtain her abortion in Texas after the order expired: I did give her the reassurance that she was not that far along. She does still have the time that if … clinics open up, that she's still able to get her abortion. I did also let her know that if she does get far along and the abortion pricing increases that we will be able to accommodate that, that she still will be able to give us a call. Several respondents were more direct with callers, particularly those whose appointments had been repeatedly canceled or who were nearing Texas' 22‐week gestational limit. In these instances, they told callers that the most secure way to obtain an abortion was to travel out of state and helped connect them to a facility that could provide the services they needed. Most staff and volunteers also noted that it was important for callers with whom they interacted to understand that their difficulties securing an appointment in Texas reflected political decisions—rather than pandemic‐related changes—and their responses to callers' questions and frustrations drew upon their commitment to advocacy. Among these was a staff member at a practical support fund, who shared: Any time those questions [about why this was happening] would come up, I just was always like, “It's not your fault. You should not feel bad. This is just lawmakers who are intentionally trying to make it harder. It shouldn't be this hard. … but I am glad that you found out about us, and we can help you.” Providing emotional support to navigate uncertainty Respondents universally described the executive order period and onset of the pandemic as a time of great stress for callers because not only had their plans for care suddenly changed, but so had their broader life circumstances. Although some callers were “very determined” and “willing to do whatever they need to,” respondents frequently observed that more callers were “feeling really defeated and… like things were impossible.” Local abortion assistance fund staff and volunteers responded to callers' increased level of stress by offering emotional support so they could follow through with their abortion decision. A practical support fund staff member recalled that many of their interactions with callers involved, “[keeping] them motivated to hang in there, because as more time went by, many did freak out and said that they weren't ever going to be able to leave their house to have the consultation or the abortion or anything.” Many respondents commented that callers felt overwhelmed by the idea of traveling hundreds of miles to an unfamiliar city to obtain an abortion given their limited economic resources, work and caregiving responsibilities, transportation needs, and COVID‐19 safety concerns. Staff and volunteers from several local abortion assistance funds reported that they further offered reassurances that it was possible to overcome the numerous logistical hurdles. One of these respondents reflected on such conversations saying, “I just reassure[d] the patient like, “Don't worry, we'll get it done. If you're willing to make that travel, we'll make sure that we can get it done, and at any moment if you have any questions, … you text me, I'll definitely text you back.” Another practical support fund staff member described similar conversations and said telling callers that they were not the only ones driving at least 10 h one way by themselves to get to an out‐of‐state facility “really did help at least ease people's minds, just to be like ‘Okay, all I have to do is get there, get this over with, have my abortion and then go home and just move on.’” Another way in which staff and volunteers provided emotional support was by being more engaged with callers than they had been previously. Because the moment felt “more urgent” and circumstances were changing quickly, respondents often reported making more follow‐up calls and texts throughout callers' process of navigating care because callers needed greater reassurance. Respondents frequently reassured worried callers that the organization would still help cover the cost of their abortion at a different clinic or if they rescheduled a canceled appointment. Respondents were in frequent contact with callers to confirm they could use their voucher at the facility where they had secured an appointment and let them know that they had an open line of communication if something happened. For example, an abortion fund volunteer described how they enhanced the support they provided to callers saying: I [texted] clients a summary of like, “Hey, just letting you know, I sent your voucher to this clinic, this amount, this is the name, this is the appointment date.” … [And] at the end of that text you get to say like, “Hey, if anything gets weird or confusing or you need help or the voucher doesn't come, you have my number and here's the number to text if you need your voucher resent.” The ongoing communication provided the emotional support that callers needed, as this respondent went on to say, “Letting them know that you are there for that, I think is a really huge thing for people because there's not many steps along the way where I think folks feel empowered to be like, ‘This person is in my corner, and if something comes up, I can ask them.’” Coordinating more complex logistical needs Because a greater share of callers had to travel out of state during the executive order than before, coordinating travel logistics became more central to many abortion assistance funds' activities and increasingly complex. Callers needed more help with transportation because they did not have a reliable car or a support person who could accompany them on a multiday, long‐distance trip; some also needed assistance arranging overnight stays and even identifying an out‐of‐state clinic. In the words of a practical support fund staff member, “It's not as simple as getting from point A to point B. Now, there are all these other different things that have to also be taken care of to make sure someone really makes it to a clinic.” The pandemic's onset added to these challenges, as hotel vacancies and roadside restrooms and restaurants became limited because of service closures. These changes required abortion assistance fund staff and volunteers to co‐create the safest and most feasible travel plan with callers that would minimize callers' exposure to COVID‐19 and, in some instances, avoid unwanted disclosure of their abortion decision. An abortion fund staff member shared callers' questions and considerations, saying, “‘Am I putting myself at risk? Am I going to be putting my family at risk when I come back from being in a hotel for a few days?’ There's the costs if they took a plane, if they drove there, hotel, lodging, food, all that, while you're away from home. Those things add up.” In addition to developing relationships with other abortion assistance funds, out‐of‐state clinics and hotels that they may not have worked with previously, respondents at most local abortion assistance funds reported efforts to streamline inter‐organization communication to reduce burdens on callers and make the process for getting assistance more person centered. A practical support fund volunteer explained: Instead of them calling us, then calling another group, then calling another group, it's like, let's just all work together with the client and we'll just all together figure this out. “You need a plane ticket, you need a ride to the airport, when you get there, you need a hotel.” It was more just like this whole group communication. Respondents from a couple of abortion assistance funds also said that they helped other organizations with client intake. As a practical support fund volunteer noted, this reduced challenges for local abortion assistance funds that were less familiar working in other cities: So we just did the initial intake and they [another abortion assistance fund] organized the rest of it. It makes sense too because it would be impossible for somebody not from that area—not impossible, but time consuming—“Okay, here's the airport, let me google hotels, where are the clinics.” So, we just passed off the information, and they took care of the rest. Although respondents valued this more coordinated effort, some expressed that organizations needed to have even more robust channels of communication because many callers still had to contact both local and national abortion assistance funds, along with clinics, to secure and pay for care. Staff and volunteers also helped bridge logistical gaps by offering additional support to callers who were “concerned” and “terrified” at the prospect of traveling because they had never traveled outside their city or had never flown. Respondents helped callers who had limited technological knowledge or lacked smartphone access fill out online applications for assistance, book appointments, or download and use ride‐sharing apps. A practical support fund volunteer emphasized that the challenges that abortion restrictions placed on these callers should not be overlooked. They're flying for the first time. Many folks have never used an Uber. All these things I think that you don't realize. It's a privilege to understand how to navigate that and how to get yourself from one place to another. To help offset these challenges and reduce travelers' feelings of fear, stigma, and isolation in a new place or after a stressful trip, volunteers at two other practical support funds commented on the importance of continuing to transport callers from the airport during the pandemic. One volunteer highlighted additional measures to establish trust, since the person they were driving did not know them: It's just a nice step in the journey for that person to have someone that's a friendly volunteer rather than an anonymous Uber driver that contributes to the isolation, especially for the ride home from the airport. It felt nice to be able to send someone ahead of time, “Here's a selfie of me in front of my car; we'll be there when you get here.” Mobilizing to increase levels of financial support Respondents universally reported that callers' financial needs were greater after the executive order and onset of the pandemic. Increased economic uncertainty and costs of travel, layered over existing prohibitions on insurance coverage for abortion, exacerbated financial hardships. An abortion fund volunteer commented, “If you can't get together $725 for an abortion, you surely can't get together the $725 for an abortion and however much it would cost to do it [in another state], right?” A volunteer at another abortion fund elaborated that “the dimensions of what a gap is for a caller have really shifted” because they could not rely on others for assistance: “It's also the depletion of the resources in her broader social network and community… People who—maybe in other times—she might have been able to borrow 20 bucks from and get that much closer to paying the costs, maybe now do not have 20 dollars to spare and don't know when they would again.” Callers also faced potentially escalating procedure costs as care was delayed, which enhanced their need for assistance. The extent to which local abortion assistance funds could cover the larger gaps in callers' costs varied based on requests for assistance and the organization's operating budget. However, a single local abortion assistance fund could rarely meet all of a caller's financial needs. Staff recognized that additional efforts were required if they were going to support callers as much as possible during the crisis. One practical support fund staff member who recalled the need for cross‐fund collaboration said: We pretty much all had to come together, and were like, “Are we able to do… emergency funds outside of what we normally do? Because now we have to help these clients get to different states and places because there is nothing that we can do here.” So we were all trying to help each other at that point. Although many respondents noted that their organization was “just providing partial funds [and] not funding everybody,” there were opportunities for intensive collaboration across organizations that increased their collective impact. These collaborations were crucial for ensuring abortion remained an option for callers in complex social circumstances and who were facing high procedure and travel costs. Describing the multi‐fund coordination for a client in an abusive relationship who needed to travel for an abortion later in pregnancy, a practical support fund staff member relayed: “At this point I had pulled in a lot of other organizations to help with funding… I pulled in [three other local abortion funds], and they were able to cover her abortion at 100% between the [national abortion assistance organization] funding, and then [another practical support fund] helped pay for gas for her to get to New Mexico.” Supporting callers facing structural oppressions Respondents repeatedly acknowledged that some callers who contacted their organization confronted multiple structural barriers that considerably hindered their ability to get an abortion. Specifically, minors, women experiencing interpersonal violence, and immigrants who were undocumented often had limited control over their own finances, which made healthcare difficult to navigate. They were also less able to move freely even before the executive order was issued, and once COVID‐19 stay‐at‐home orders were put in place, these barriers made out‐of‐state travel more difficult. For example, a respondent noted that even if minors could find a way to leave Texas, they needed to have someone 18 years of age or older who could travel with them and check into a hotel. Callers who were undocumented—or whose travel companions were—and lived along the US‐Mexico border worried whether they would be able to travel and return home safely because they would encounter interior immigration checkpoints within 100 miles of the border. After noting that undocumented immigrants “have always had challenges being able to have jobs that allow them to sustain themselves, and their families, and have always had difficulties accessing health care services,” an abortion fund staff member said, “It's so much more difficult now to be able to receive an abortion, because people have to travel outside of the state… There is fear in traveling, and nobody should be afraid to possibly be deported because you're seeking an abortion.” Staff and volunteers described using a variety of strategies to identify callers in these circumstances and provide them with person‐centered support. This included posing questions in a way that could normalize the caller's situation and reduce potential fears and stigma associated with disclosure. Recognizing the many difficulties immigrants encounter, an abortion fund volunteer said she first let callers who might be undocumented know that some patients their organization supported do not have legal status, which often made callers “feel comfortable disclosing their status.” Then, she provided “a little bit of ‘Know Your Rights’ training over the phone,” so that if patients were stopped by law enforcement or immigration officials while traveling out of state, they knew that they did not have to answer questions and could request an attorney. Staff and volunteers also indicated that more callers experiencing interpersonal violence contacted their organizations during this period. These callers similarly needed to know that “a clinic is a safe place” to disclose their circumstances and that doing so was important in order to get the additional funding that was dedicated to patients experiencing violence. Although respondents described instances in which these types of callers ultimately obtained an abortion, they also mentioned that these intersecting barriers “were too astronomical” for some, likely leading them to continue unwanted pregnancies. Several staff and volunteers who supported Spanish‐speaking callers noted decreases in call volume during this period, and speculated that overwhelmed clinic staff may not have effectively shared information about the executive order or referred them to abortion assistance funds. A practical support fund staff member recounted the case of a caller in an abusive relationship who they had been supporting when her appointment was canceled after the stay‐at‐home and executive orders were issued. The staff member and caller co‐created a plan to secure a consultation appointment in Texas after the executive order expired because the caller could not travel out of state. However, when the staff member tried to re‐contact her, “my number was blocked [and] it seems to me that the partner did it… She had more freedom of movement before COVID. But once COVID happened, she was stuck with her partner and wasn't able to get the abortion after that.” Additionally, some respondents acknowledged that it could be difficult to offer all the resources a caller might need to overcome structural barriers because, in the words of one volunteer, there was “[lack] capacity to do that … we're such a small fund. It's not like any of us are getting paid to do this work.”
The suspension of abortion services following the executive order and the changing court decisions created confusion about whether and what types of services were available in Texas. Respondents frequently commented that it was difficult to stay abreast of circumstances that “were flip‐flopping every day,” and while the resulting uncertainty placed challenges on clinics, it most directly affected callers needing care. An abortion fund staff member described the difficult situation in Spring 2020 saying, “Because they [clinics] were in this limbo, they were also putting callers in this limbo, and by the time they [callers] would reach us, they had heard different information or they just didn't know what was going on.” Staff reported staying in more regular communication with in‐ and out‐of‐state clinics and other assistance funds about the changing status of services and policies so they could “be on the forefront of knowledge of what's happening and what we can expect to happen next” and then pass the information on to other staff and volunteers responding to caller inquiries. In addition to communicating with other organizations, a staff member said their abortion fund increased the number of days they operated, “because we wanted to be able to meet people wherever they were. Things were constantly changing … so we want to be prepared for that, and the way we thought we could do that was to stay open more, be available for people to reach us more.” However, it was not possible for some local abortion assistance funds with asynchronous, volunteer‐based models to connect with all callers needing information because the volunteers could not reach some callers during volunteers' shifts. Recognizing their unique position in an increasingly fragmented system of care, local abortion assistance funds also worked to bridge the information gaps by sharing their knowledge about available assistance with callers and engaging in thought partnership so callers could plan their next steps. In the words of an abortion fund volunteer, calls became less “transactional… A lot of the calls during this time were much more problem solving. Where can you go?” A practical support fund volunteer echoed this shift, explaining, “It was definitely a crisis management time… If someone calls, we can't just tell them, ‘I'm sorry, you're out of luck.’ That's not what we do here. Our job is to figure out a way around the barriers.” Staff and volunteers informed callers that financial assistance for both abortion costs and practical support were available and co‐created a person‐centered plan for securing services; this involved assessing callers' access to childcare and need for privacy and weighing the pros and cons of waiting for the order to expire versus traveling out of state. Respondents emphasized the importance of callers' autonomy, noting that their role was to provide “all of the community resources available to you to make this decision” and for callers to “feel supported the entire time.” For example, an abortion fund staff member described reassuring a caller who did not feel that she could travel out of state that she might be able to obtain her abortion in Texas after the order expired: I did give her the reassurance that she was not that far along. She does still have the time that if … clinics open up, that she's still able to get her abortion. I did also let her know that if she does get far along and the abortion pricing increases that we will be able to accommodate that, that she still will be able to give us a call. Several respondents were more direct with callers, particularly those whose appointments had been repeatedly canceled or who were nearing Texas' 22‐week gestational limit. In these instances, they told callers that the most secure way to obtain an abortion was to travel out of state and helped connect them to a facility that could provide the services they needed. Most staff and volunteers also noted that it was important for callers with whom they interacted to understand that their difficulties securing an appointment in Texas reflected political decisions—rather than pandemic‐related changes—and their responses to callers' questions and frustrations drew upon their commitment to advocacy. Among these was a staff member at a practical support fund, who shared: Any time those questions [about why this was happening] would come up, I just was always like, “It's not your fault. You should not feel bad. This is just lawmakers who are intentionally trying to make it harder. It shouldn't be this hard. … but I am glad that you found out about us, and we can help you.”
Respondents universally described the executive order period and onset of the pandemic as a time of great stress for callers because not only had their plans for care suddenly changed, but so had their broader life circumstances. Although some callers were “very determined” and “willing to do whatever they need to,” respondents frequently observed that more callers were “feeling really defeated and… like things were impossible.” Local abortion assistance fund staff and volunteers responded to callers' increased level of stress by offering emotional support so they could follow through with their abortion decision. A practical support fund staff member recalled that many of their interactions with callers involved, “[keeping] them motivated to hang in there, because as more time went by, many did freak out and said that they weren't ever going to be able to leave their house to have the consultation or the abortion or anything.” Many respondents commented that callers felt overwhelmed by the idea of traveling hundreds of miles to an unfamiliar city to obtain an abortion given their limited economic resources, work and caregiving responsibilities, transportation needs, and COVID‐19 safety concerns. Staff and volunteers from several local abortion assistance funds reported that they further offered reassurances that it was possible to overcome the numerous logistical hurdles. One of these respondents reflected on such conversations saying, “I just reassure[d] the patient like, “Don't worry, we'll get it done. If you're willing to make that travel, we'll make sure that we can get it done, and at any moment if you have any questions, … you text me, I'll definitely text you back.” Another practical support fund staff member described similar conversations and said telling callers that they were not the only ones driving at least 10 h one way by themselves to get to an out‐of‐state facility “really did help at least ease people's minds, just to be like ‘Okay, all I have to do is get there, get this over with, have my abortion and then go home and just move on.’” Another way in which staff and volunteers provided emotional support was by being more engaged with callers than they had been previously. Because the moment felt “more urgent” and circumstances were changing quickly, respondents often reported making more follow‐up calls and texts throughout callers' process of navigating care because callers needed greater reassurance. Respondents frequently reassured worried callers that the organization would still help cover the cost of their abortion at a different clinic or if they rescheduled a canceled appointment. Respondents were in frequent contact with callers to confirm they could use their voucher at the facility where they had secured an appointment and let them know that they had an open line of communication if something happened. For example, an abortion fund volunteer described how they enhanced the support they provided to callers saying: I [texted] clients a summary of like, “Hey, just letting you know, I sent your voucher to this clinic, this amount, this is the name, this is the appointment date.” … [And] at the end of that text you get to say like, “Hey, if anything gets weird or confusing or you need help or the voucher doesn't come, you have my number and here's the number to text if you need your voucher resent.” The ongoing communication provided the emotional support that callers needed, as this respondent went on to say, “Letting them know that you are there for that, I think is a really huge thing for people because there's not many steps along the way where I think folks feel empowered to be like, ‘This person is in my corner, and if something comes up, I can ask them.’”
Because a greater share of callers had to travel out of state during the executive order than before, coordinating travel logistics became more central to many abortion assistance funds' activities and increasingly complex. Callers needed more help with transportation because they did not have a reliable car or a support person who could accompany them on a multiday, long‐distance trip; some also needed assistance arranging overnight stays and even identifying an out‐of‐state clinic. In the words of a practical support fund staff member, “It's not as simple as getting from point A to point B. Now, there are all these other different things that have to also be taken care of to make sure someone really makes it to a clinic.” The pandemic's onset added to these challenges, as hotel vacancies and roadside restrooms and restaurants became limited because of service closures. These changes required abortion assistance fund staff and volunteers to co‐create the safest and most feasible travel plan with callers that would minimize callers' exposure to COVID‐19 and, in some instances, avoid unwanted disclosure of their abortion decision. An abortion fund staff member shared callers' questions and considerations, saying, “‘Am I putting myself at risk? Am I going to be putting my family at risk when I come back from being in a hotel for a few days?’ There's the costs if they took a plane, if they drove there, hotel, lodging, food, all that, while you're away from home. Those things add up.” In addition to developing relationships with other abortion assistance funds, out‐of‐state clinics and hotels that they may not have worked with previously, respondents at most local abortion assistance funds reported efforts to streamline inter‐organization communication to reduce burdens on callers and make the process for getting assistance more person centered. A practical support fund volunteer explained: Instead of them calling us, then calling another group, then calling another group, it's like, let's just all work together with the client and we'll just all together figure this out. “You need a plane ticket, you need a ride to the airport, when you get there, you need a hotel.” It was more just like this whole group communication. Respondents from a couple of abortion assistance funds also said that they helped other organizations with client intake. As a practical support fund volunteer noted, this reduced challenges for local abortion assistance funds that were less familiar working in other cities: So we just did the initial intake and they [another abortion assistance fund] organized the rest of it. It makes sense too because it would be impossible for somebody not from that area—not impossible, but time consuming—“Okay, here's the airport, let me google hotels, where are the clinics.” So, we just passed off the information, and they took care of the rest. Although respondents valued this more coordinated effort, some expressed that organizations needed to have even more robust channels of communication because many callers still had to contact both local and national abortion assistance funds, along with clinics, to secure and pay for care. Staff and volunteers also helped bridge logistical gaps by offering additional support to callers who were “concerned” and “terrified” at the prospect of traveling because they had never traveled outside their city or had never flown. Respondents helped callers who had limited technological knowledge or lacked smartphone access fill out online applications for assistance, book appointments, or download and use ride‐sharing apps. A practical support fund volunteer emphasized that the challenges that abortion restrictions placed on these callers should not be overlooked. They're flying for the first time. Many folks have never used an Uber. All these things I think that you don't realize. It's a privilege to understand how to navigate that and how to get yourself from one place to another. To help offset these challenges and reduce travelers' feelings of fear, stigma, and isolation in a new place or after a stressful trip, volunteers at two other practical support funds commented on the importance of continuing to transport callers from the airport during the pandemic. One volunteer highlighted additional measures to establish trust, since the person they were driving did not know them: It's just a nice step in the journey for that person to have someone that's a friendly volunteer rather than an anonymous Uber driver that contributes to the isolation, especially for the ride home from the airport. It felt nice to be able to send someone ahead of time, “Here's a selfie of me in front of my car; we'll be there when you get here.”
Respondents universally reported that callers' financial needs were greater after the executive order and onset of the pandemic. Increased economic uncertainty and costs of travel, layered over existing prohibitions on insurance coverage for abortion, exacerbated financial hardships. An abortion fund volunteer commented, “If you can't get together $725 for an abortion, you surely can't get together the $725 for an abortion and however much it would cost to do it [in another state], right?” A volunteer at another abortion fund elaborated that “the dimensions of what a gap is for a caller have really shifted” because they could not rely on others for assistance: “It's also the depletion of the resources in her broader social network and community… People who—maybe in other times—she might have been able to borrow 20 bucks from and get that much closer to paying the costs, maybe now do not have 20 dollars to spare and don't know when they would again.” Callers also faced potentially escalating procedure costs as care was delayed, which enhanced their need for assistance. The extent to which local abortion assistance funds could cover the larger gaps in callers' costs varied based on requests for assistance and the organization's operating budget. However, a single local abortion assistance fund could rarely meet all of a caller's financial needs. Staff recognized that additional efforts were required if they were going to support callers as much as possible during the crisis. One practical support fund staff member who recalled the need for cross‐fund collaboration said: We pretty much all had to come together, and were like, “Are we able to do… emergency funds outside of what we normally do? Because now we have to help these clients get to different states and places because there is nothing that we can do here.” So we were all trying to help each other at that point. Although many respondents noted that their organization was “just providing partial funds [and] not funding everybody,” there were opportunities for intensive collaboration across organizations that increased their collective impact. These collaborations were crucial for ensuring abortion remained an option for callers in complex social circumstances and who were facing high procedure and travel costs. Describing the multi‐fund coordination for a client in an abusive relationship who needed to travel for an abortion later in pregnancy, a practical support fund staff member relayed: “At this point I had pulled in a lot of other organizations to help with funding… I pulled in [three other local abortion funds], and they were able to cover her abortion at 100% between the [national abortion assistance organization] funding, and then [another practical support fund] helped pay for gas for her to get to New Mexico.”
Respondents repeatedly acknowledged that some callers who contacted their organization confronted multiple structural barriers that considerably hindered their ability to get an abortion. Specifically, minors, women experiencing interpersonal violence, and immigrants who were undocumented often had limited control over their own finances, which made healthcare difficult to navigate. They were also less able to move freely even before the executive order was issued, and once COVID‐19 stay‐at‐home orders were put in place, these barriers made out‐of‐state travel more difficult. For example, a respondent noted that even if minors could find a way to leave Texas, they needed to have someone 18 years of age or older who could travel with them and check into a hotel. Callers who were undocumented—or whose travel companions were—and lived along the US‐Mexico border worried whether they would be able to travel and return home safely because they would encounter interior immigration checkpoints within 100 miles of the border. After noting that undocumented immigrants “have always had challenges being able to have jobs that allow them to sustain themselves, and their families, and have always had difficulties accessing health care services,” an abortion fund staff member said, “It's so much more difficult now to be able to receive an abortion, because people have to travel outside of the state… There is fear in traveling, and nobody should be afraid to possibly be deported because you're seeking an abortion.” Staff and volunteers described using a variety of strategies to identify callers in these circumstances and provide them with person‐centered support. This included posing questions in a way that could normalize the caller's situation and reduce potential fears and stigma associated with disclosure. Recognizing the many difficulties immigrants encounter, an abortion fund volunteer said she first let callers who might be undocumented know that some patients their organization supported do not have legal status, which often made callers “feel comfortable disclosing their status.” Then, she provided “a little bit of ‘Know Your Rights’ training over the phone,” so that if patients were stopped by law enforcement or immigration officials while traveling out of state, they knew that they did not have to answer questions and could request an attorney. Staff and volunteers also indicated that more callers experiencing interpersonal violence contacted their organizations during this period. These callers similarly needed to know that “a clinic is a safe place” to disclose their circumstances and that doing so was important in order to get the additional funding that was dedicated to patients experiencing violence. Although respondents described instances in which these types of callers ultimately obtained an abortion, they also mentioned that these intersecting barriers “were too astronomical” for some, likely leading them to continue unwanted pregnancies. Several staff and volunteers who supported Spanish‐speaking callers noted decreases in call volume during this period, and speculated that overwhelmed clinic staff may not have effectively shared information about the executive order or referred them to abortion assistance funds. A practical support fund staff member recounted the case of a caller in an abusive relationship who they had been supporting when her appointment was canceled after the stay‐at‐home and executive orders were issued. The staff member and caller co‐created a plan to secure a consultation appointment in Texas after the executive order expired because the caller could not travel out of state. However, when the staff member tried to re‐contact her, “my number was blocked [and] it seems to me that the partner did it… She had more freedom of movement before COVID. But once COVID happened, she was stuck with her partner and wasn't able to get the abortion after that.” Additionally, some respondents acknowledged that it could be difficult to offer all the resources a caller might need to overcome structural barriers because, in the words of one volunteer, there was “[lack] capacity to do that … we're such a small fund. It's not like any of us are getting paid to do this work.”
Local abortion assistance funds fill a critical gap in the reproductive healthcare safety net created by federal and state restrictions on insurance coverage and clinical care for abortion. As demonstrated in prior studies, , these organizations help cover the cost of care for the many patients seeking abortion who live on low incomes and face high out‐of‐pocket costs. Our study extends the growing literature on abortion assistance funds by demonstrating the other ways in which these organizations, including practical support funds, help pregnant callers navigate an often‐unfamiliar sector of the healthcare system and the many obstacles that other abortion restrictions and structural oppressions put in their way. Although staff and volunteers often helped address callers' knowledge gaps about laws, policies, and resources for care before the executive order, we found that their roles shifted to more intensive patient navigation and, at times, greater emotional support during the period that the order was in effect. By working with callers to identify their economic needs and problem solve around risks and benefits of various options for care, respondents highlighted how they co‐created a plan for obtaining an abortion that honored callers' autonomy, much like patient navigators for other healthcare needs. , This is an especially important position in the context of abortion care where patients seeking services often experience intersecting barriers, along with internal and external stigma, , and is essential in a time of crisis when accurate information about policies and services can be difficult to obtain. Moreover, study respondents relayed interactions with callers that clearly reflected their sociopolitical lens and justice and activist orientation—explaining that targeted restrictions on abortion were making access unnecessarily difficult and informing callers of their rights—so patients could advocate for themselves inside and outside the clinic setting. Similar to lay patient navigators for cancer care, local abortion assistance funds can offer a culturally and person‐centered intervention to address disparities in access to care. Their work can help support minors, patients experiencing interpersonal violence, immigrants, and callers with non‐English language preference, who are among the most structurally disenfranchised. Having conducted our study after the onset of a pandemic and implementation of one of the most restrictive abortions bans at the time, our findings also reveal the organizational changes that were needed to offer callers this type of support. Respondents noted the need to strengthen existing connections and more closely coordinate information sharing with abortion facilities and other local and national abortion assistance funds. By bringing together organizations with complementary skills and resources, such as additional funding, local cultural expertise, knowledge of the area where callers were going for care and expertise in travel logistics, they were able to better meet callers' greater financial needs and address the increased complexity of out‐of‐state travel. These strategies are aligned with those that have been identified as facilitating effective crisis response in other emergency settings. , They are also strategies that abortion assistance funds deployed again to provide thousands of pregnant Texans a lifeline to financial and logistical assistance to travel out of state for abortion care after implementation of Texas Senate Bill 8 on September 1, 2021. , This crisis response and the level of support that Texas abortion patients needed in 2020 may provide lessons for how abortion assistance funds might have to operate as other abortion restrictions go into effect. As states continue to enact abortion bans following the US Supreme Court's Dobbs v. Jackson Women's Health Organization decision that overturned Roe v. Wade, more abortion patients will have to travel elsewhere for care. , As respondents in our study noted, greater financial and informational resources are needed to support both those working at abortion assistance funds and callers needing care. Practical support funds, especially, will require funding that corresponds to the increased level of need for support and coordination so as many patients can obtain care as possible. Additionally, abortion assistance funds will likely need legal protections and related financial assistance as some policymakers move to prohibit them from providing assistance to patients traveling out of state. It is also worth noting that the work of crisis response in abortion care is falling on a network of national and local non‐profit organizations—the latter of which often rely on volunteers—and their efforts to support access to essential reproductive healthcare may not be sustainable if these policy conditions are in effect long term. Our study has limitations. We conducted interviews with a small number of local abortion assistance funds that supported Texas residents needing abortion care in 2020. Although we have a sufficiently sized qualitative sample and participating organizations represented all Texas abortion assistance funds operating at the time, we did not interview staff at larger national organizations that also provide assistance for patients seeking abortion care. Therefore, the roles and actions that staff and volunteers undertook may not be relevant to other settings or times of crisis. Additionally, we interviewed respondents several months after Texas' executive order expired and accounts of their experiences may be subjected to recall bias. However, the time interval between the events and interviews was relatively short, thereby minimizing this bias. Our results also rely on the perspective of staff and volunteers who supported callers and therefore may not fully reflect the needs and experiences of callers seeking out‐of‐state abortion care. Further research from the pregnant patient's perspective may highlight other ways that abortion assistance funds can support callers' informational, emotional, and other needs.
Despite these limitations, this study provides a broader perspective on the important roles that local abortion assistance funds have in facilitating access to abortion care. Beyond bridging financial gaps, these organizations can offer essential knowledge and emotional support that enable callers seeking abortion to navigate around the obstacles they encounter in achieving reproductive autonomy. As additional abortion restrictions widen geographic gaps in care and place greater demands on this network of non‐profit organizations with a largely volunteer workforce, initiatives that bolster the infrastructure of abortion assistance funds will be essential.
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Effect of bioceramic-based and resin-based sealers on postoperative discomfort following root canal therapy: a systematic review and meta-analysis | 00a1191c-f46e-4c37-8717-5d71673c8c4e | 11531739 | Dentistry[mh] | Root canal therapy (RCT) is the principal approach to treating root canal infections . The selection of disinfection procedures and obturation materials may play a crucial role in ensuring treatment efficacy and minimizing complications . Postoperative discomfort is a commonly reported complication among patients after dental procedures, including root canal therapy . Physical trauma during treatment, inflammation, and bacterial extrusion are common causes of postoperative discomfort. Iatrogenic causes such as, the selection of instruments and working length or the root canal sealer, may also contribute to postoperative discomfort . The Likert-type scale is a widely recognized and invaluable instrument used to quantify pain and discomfort experienced by patients after endodontic treatment . It consists of two different scales, namely the Visual Analog Scale (VAS) and the Four-Point Pain Scale . While using the VAS requires patients to mark the intensity of their pain through a line, the Four-Point Pain Scale provides four different rates for the patient to choose their pain level . The reliability and efficacy of both scales in evaluating postoperative pain are two vital indicators for healthcare professionals to determine the appropriate course of treatment and manage patient expectations . Consequently, the use of Likert-type scales has been an increasingly accepted practice in endodontic therapy and other medical fields. The choice of obturation technique can significantly influence postoperative pain and discomfort, with the cold lateral compaction technique being the most effective in minimizing these issues . Several studies have investigated the relationship between root canal sealers and postoperative pain with various results . Evidence suggests that specific types of sealers, like resin-based sealers, might be linked to higher levels of postoperative discomfort compared to other sealers, such as zinc oxide eugenol-based sealers . The composition of the root canal sealers may play a key role in managing postoperative pain and discomfort. Bioceramic root canal sealers (BCS) have garnered considerable attention in recent years due to their remarkable sealing ability and biocompatibility. BCS synergistically create a highly bioactive and biocompatible substance by combining calcium silicates, monobasic calcium phosphate, zirconium oxide, filler particles, and a hydrophilic polymer. These components actively support tissue regeneration and effectively inhibit the growth of bacteria, fostering a conducive environment for optimal healing. Numerous studies have demonstrated that BCS can significantly reduce postoperative pain in root canal therapy by inhibiting bacterial growth and promoting tissue healing . Compared to patients treated with traditional zinc oxide eugenol-based or resin-based root canal sealers, patients treated with BCS experienced much less postoperative pain. Resin-based sealers have been shown to produce residual monomers and cause cytotoxicity, which can be uncomfortable even when they show good biocompatibility . These sealers consist of a combination of resin monomers, fillers such as quartz, silica, glass particles, and zirconium oxide, with additional additives to impart the necessary chemical and physical characteristics . In some circumstances, resin-based sealers might be suitable, especially if a patient is allergic to any of the chemicals in other kinds of sealers . Resin sealers can be used to avoid triggering allergic reactions in such cases. Additionally, resin-based sealers are more effective in sealing off microcracks and fissures in the root canal system. From the root canal issue highlighted, this systematic review and meta-analysis of relevant clinical studies aim to assess and compare the effects of bioceramic-based and resin-based root canal sealers in alleviating/preventing postoperative pain. The secondary aim was to evaluate the consumption of analgesics required to treat postoperative pain associated with the use of either bioceramic or resin-based sealers.
Registration and protocol A systematic review of the literature and meta-analysis was performed. This study followed the Preferred Reporting Items for Systematic Review (PRISMA 2020), the Cochrane Handbook for Systematic Reviews of Interventions, version 5.1.0, and the 4th Edition of the JBI Reviewer’s Manual. It was registered to PROSPERO under registration code CRD42022355506. Research question Using the “PICO” (PRISMA 2020) technique, this study sets a research question focusing on the effectiveness of bioceramic-based and conventional resin-based sealers in managing postoperative pain after root canal therapy based on relevant clinical trials. • Population: Individuals receiving non-surgical root canal therapy for their permanent teeth • Intervention: Root canal treatment using bioceramic sealers • Comparison: Root canal treatment using resin-based sealers • Outcomes: Post-operative pain scores and post-operative analgesic use Data sources The PICOS criteria were applied to screen potential research articles. Titles and abstracts were assessed independently by two reviewers; any discrepancies were discussed with a third reviewer. The Directory of Open Access Journals (DOAJ) and PubMed MEDLINE were among the electronic resources evaluated. Using precise keywords and MeSH phrases combined with Boolean operators, a thorough search was conducted that included articles published between January 2000 and August 2022, without language constraints . Eligibility criteria Research published between January 1, 2000, and August 30, 2022, that involved subjects receiving non-surgical root canal therapy on permanent teeth utilizing bioceramic and resin-based sealers were considered. A third reviewer arbitrated disagreements between the two reviewers after they had used the PICOS technique to assess entire texts and create inclusion and exclusion criteria . Selection of studies Two independent reviewers (M.S. and A.M.P.) conducted a critical assessment of the title and abstract of each study. The selection process involved: (i) Removing duplicate entries (ii) Assessing titles and abstracts to exclude irrelevant articles (iii) Retrieving full texts of potentially relevant articles (iv) Ensuring a comprehensive collection of relevant information (v) Full-text examination for eligibility criteria compliance (vi) Consulting researchers for eligibility clarifications if needed (vii) Determining inclusion criteria and data collection Data extraction Two reviewers (M.S. and A.M.P.) selected studies and extracted relevant data using a comprehensive checklist, including details like authors, year, study design, sample size, age group, gender, randomization, blinding, outcome assessment, results, and other pertinent data. Discrepancies were resolved through discussion or by consulting a third reviewer (D.A.W.) for final judgment. Data on publication and study, participants, interventions, comparators, outcome measures, research design, statistical analysis, and findings, as well as any other pertinent data ( e.g. , funding and conflicts of interest) were methodically collected from all selected studies. Two reviewers performed data extraction, and all primary outcomes were meticulously recorded in separate Excel sheets. Any differences of opinion between the two independent reviewers (M.S. and A.M.P.) during the selection of articles for the systematic review and meta-analysis were settled by discussion and agreement. When disagreements developed amongst the primary reviewers while selecting articles for inclusion in the systematic review and meta-analysis (SRMA), discussions were held to reach a solution. If consensus could not be reached, a third independent reviewer was entrusted to arbitrate and make a final judgment. The third reviewer (D.A.W.) was chosen for her subject knowledge and functioned as an unbiased adjudicator to settle concerns and ensure the selection process was rigorous and objective. Quality assessment Evaluation of the research quality was performed using the Cochrane Bias Risk-2 (ROB-2), clinical and randomized controlled trials tool, which includes areas such as random sequence generation, allocation concealment, participant blinding, inadequate outcome data, selective reporting, and other biases. Quality assessment was done using Review Manager version 5.4. Meta-analysis Meta-analysis was performed on trials with comparable results and periods between follow-ups. Standard deviations and mean instrumentation times were used to evaluate continuous data. While quantitative synthesis computed a combined estimate of the intervention impact, taking heterogeneity (I2) into account to apply a suitable effect model (fixed or random), descriptive synthesis offered an overview of the main research aspects. Review Manager 5.4 was utilized for conducting quantitative synthesis.
A systematic review of the literature and meta-analysis was performed. This study followed the Preferred Reporting Items for Systematic Review (PRISMA 2020), the Cochrane Handbook for Systematic Reviews of Interventions, version 5.1.0, and the 4th Edition of the JBI Reviewer’s Manual. It was registered to PROSPERO under registration code CRD42022355506.
Using the “PICO” (PRISMA 2020) technique, this study sets a research question focusing on the effectiveness of bioceramic-based and conventional resin-based sealers in managing postoperative pain after root canal therapy based on relevant clinical trials. • Population: Individuals receiving non-surgical root canal therapy for their permanent teeth • Intervention: Root canal treatment using bioceramic sealers • Comparison: Root canal treatment using resin-based sealers • Outcomes: Post-operative pain scores and post-operative analgesic use
The PICOS criteria were applied to screen potential research articles. Titles and abstracts were assessed independently by two reviewers; any discrepancies were discussed with a third reviewer. The Directory of Open Access Journals (DOAJ) and PubMed MEDLINE were among the electronic resources evaluated. Using precise keywords and MeSH phrases combined with Boolean operators, a thorough search was conducted that included articles published between January 2000 and August 2022, without language constraints .
Research published between January 1, 2000, and August 30, 2022, that involved subjects receiving non-surgical root canal therapy on permanent teeth utilizing bioceramic and resin-based sealers were considered. A third reviewer arbitrated disagreements between the two reviewers after they had used the PICOS technique to assess entire texts and create inclusion and exclusion criteria .
Two independent reviewers (M.S. and A.M.P.) conducted a critical assessment of the title and abstract of each study. The selection process involved: (i) Removing duplicate entries (ii) Assessing titles and abstracts to exclude irrelevant articles (iii) Retrieving full texts of potentially relevant articles (iv) Ensuring a comprehensive collection of relevant information (v) Full-text examination for eligibility criteria compliance (vi) Consulting researchers for eligibility clarifications if needed (vii) Determining inclusion criteria and data collection
Two reviewers (M.S. and A.M.P.) selected studies and extracted relevant data using a comprehensive checklist, including details like authors, year, study design, sample size, age group, gender, randomization, blinding, outcome assessment, results, and other pertinent data. Discrepancies were resolved through discussion or by consulting a third reviewer (D.A.W.) for final judgment. Data on publication and study, participants, interventions, comparators, outcome measures, research design, statistical analysis, and findings, as well as any other pertinent data ( e.g. , funding and conflicts of interest) were methodically collected from all selected studies. Two reviewers performed data extraction, and all primary outcomes were meticulously recorded in separate Excel sheets. Any differences of opinion between the two independent reviewers (M.S. and A.M.P.) during the selection of articles for the systematic review and meta-analysis were settled by discussion and agreement. When disagreements developed amongst the primary reviewers while selecting articles for inclusion in the systematic review and meta-analysis (SRMA), discussions were held to reach a solution. If consensus could not be reached, a third independent reviewer was entrusted to arbitrate and make a final judgment. The third reviewer (D.A.W.) was chosen for her subject knowledge and functioned as an unbiased adjudicator to settle concerns and ensure the selection process was rigorous and objective.
Evaluation of the research quality was performed using the Cochrane Bias Risk-2 (ROB-2), clinical and randomized controlled trials tool, which includes areas such as random sequence generation, allocation concealment, participant blinding, inadequate outcome data, selective reporting, and other biases. Quality assessment was done using Review Manager version 5.4.
Meta-analysis was performed on trials with comparable results and periods between follow-ups. Standard deviations and mean instrumentation times were used to evaluate continuous data. While quantitative synthesis computed a combined estimate of the intervention impact, taking heterogeneity (I2) into account to apply a suitable effect model (fixed or random), descriptive synthesis offered an overview of the main research aspects. Review Manager 5.4 was utilized for conducting quantitative synthesis.
The initial electronic database search yielded 6,461 titles from PubMed/MEDLINE, the Cochrane Library, DOAJ, Embase, SCOPUS and Google search. There were 638 duplicate articles. From the screening of the abstracts, two independent reviewers selected 254 relevant titles, and 5,666 were removed due to having an unrelated topic and publication year. Based on the reviewers’ decision, 19 articles were chosen for full-text evaluation. The manual search of the references from the selected studies yielded no matched articles. Following pre-screening, the articles were selected using inclusion and exclusion criteria. Then, based on the PICO questions, nine studies of the total search were included in the qualitative synthesis or data extraction. Meta-analysis of five selected studies was then conducted . Research characteristics Nine studies were selected for qualitative synthesis. Their general characteristics are presented in . All the studies that fulfilled the inclusion criteria of this systematic review were solely randomized controlled clinical trials. In total, 678 participants were involved in the analysis of the selected studies, generating a comprehensive examination of the subject matter. These studies were conducted in all parts of the world. All the studies reached a consistent conclusion that there was no notable distinction in the levels of postoperative pain between the two types of sealers. The qualitative summary included the research conducted by . In this investigation, 60 patients were randomized to have root canal therapy using either AH Plus, a resin-based sealer, or EnddoSequence BC Sealer, a bioceramic-based sealer. A visual analog scale (VAS) was used to measure postoperative pain at 6-, 12-, 24-, and 48-hours following treatment. The pain levels of the two sealer groups did not differ significantly at any stage during the study, according to the findings. Risk of bias applicability The Cochrane Risk of Bias Tool (ROB-2) was used for evaluating the quality of randomized controlled trials ( ; and ). Four studies exhibited a low risk of bias; two studies showed a moderate risk; and three studies displayed a high risk of bias. The absence of random sequence generation was not reported in three studies , contributing to the high risk of bias in these studies. All studies, except for ’s research, employed blinding techniques. Meta-analysis Meta-analysis was conducted on the following parameters: 1. Post-operative pain at 6 h, 12 h, 24 h and 48 h 2. Post-operative analgesic use after 24 h. Six studies were included in the meta-analysis. The statistic test used to quantify the inconsistency (heterogeneity) between studies was the I 2 . The results of the meta-analysis were then interpreted by the Cochrane Handbook for Systematic Reviews of Interventions. Effect sizes Effect sizes serve as quantitative measures that indicate the magnitude and direction of the impact interventions on outcomes. To find differences in continuous data (specifically mean values), effect sizes were calculated using information on the mean response, standard deviation, and number of participants within each group. Six-hour post-operative pain level Two studies evaluated post-operative pain after six hours of treatment. The pooled mean difference was 0.30 [−0.21, 0.80] indicating that the mean pain scores were greater with resin-based sealers than with bioceramic sealers at six hours. Heterogeneity (I2) was 0%, and a fixed effect model was used. The results were not statistically significant ( p > 0.05) . Twelve-hour post-operative pain level Two studies evaluated post-operative pain after 12 h of treatment. The pooled mean difference was 0.20 [−0.24, 0.64] indicating that mean pain scores were greater with resin-based sealers than with bioceramics sealers at 12 h. Heterogeneity (I2) was 0%, and a fixed effect model was used. The results were not statistically significant ( p > 0.05) . Twenty-four-hour post-operative pain level Five studies evaluated post-operative pain after 24 h of treatment. The pooled mean difference was 0.51 [0.16, 0.85] indicating that mean pain scores were greater with resin-based sealers than with bioceramics sealers at 24 h. Heterogeneity (I2) was 1%, and thus a fixed effect model was used. The results were not statistically significant ( p > 0.05) . Forty-eight-hour post-operative pain level Four studies evaluated postoperative pain after 48 h of treatment. The pooled mean difference was −0.27 [−1.12, 0.58] indicating that mean pain scores were greater with bioceramics sealers than with resin-based sealers at 48 h. Heterogeneity (I2) was 59%, thereby using a random effect model. The results were not statistically significant ( p > 0.05) . Analgesic use Four studies evaluated analgesic use after 24 h of treatment. The pooled risk ratio indicated that the risk of analgesic use with resin-based sealer was 1.89-fold (RR = 1.89 [0.61, 5.81]) more than with bioceramics-based sealer at 24 h of treatment. Heterogeneity (I2) was 59%, thereby utilizing a random effect model. The results were not statistically significant ( p > 0.05) .
Nine studies were selected for qualitative synthesis. Their general characteristics are presented in . All the studies that fulfilled the inclusion criteria of this systematic review were solely randomized controlled clinical trials. In total, 678 participants were involved in the analysis of the selected studies, generating a comprehensive examination of the subject matter. These studies were conducted in all parts of the world. All the studies reached a consistent conclusion that there was no notable distinction in the levels of postoperative pain between the two types of sealers. The qualitative summary included the research conducted by . In this investigation, 60 patients were randomized to have root canal therapy using either AH Plus, a resin-based sealer, or EnddoSequence BC Sealer, a bioceramic-based sealer. A visual analog scale (VAS) was used to measure postoperative pain at 6-, 12-, 24-, and 48-hours following treatment. The pain levels of the two sealer groups did not differ significantly at any stage during the study, according to the findings.
The Cochrane Risk of Bias Tool (ROB-2) was used for evaluating the quality of randomized controlled trials ( ; and ). Four studies exhibited a low risk of bias; two studies showed a moderate risk; and three studies displayed a high risk of bias. The absence of random sequence generation was not reported in three studies , contributing to the high risk of bias in these studies. All studies, except for ’s research, employed blinding techniques.
Meta-analysis was conducted on the following parameters: 1. Post-operative pain at 6 h, 12 h, 24 h and 48 h 2. Post-operative analgesic use after 24 h. Six studies were included in the meta-analysis. The statistic test used to quantify the inconsistency (heterogeneity) between studies was the I 2 . The results of the meta-analysis were then interpreted by the Cochrane Handbook for Systematic Reviews of Interventions.
Effect sizes serve as quantitative measures that indicate the magnitude and direction of the impact interventions on outcomes. To find differences in continuous data (specifically mean values), effect sizes were calculated using information on the mean response, standard deviation, and number of participants within each group.
Two studies evaluated post-operative pain after six hours of treatment. The pooled mean difference was 0.30 [−0.21, 0.80] indicating that the mean pain scores were greater with resin-based sealers than with bioceramic sealers at six hours. Heterogeneity (I2) was 0%, and a fixed effect model was used. The results were not statistically significant ( p > 0.05) .
Two studies evaluated post-operative pain after 12 h of treatment. The pooled mean difference was 0.20 [−0.24, 0.64] indicating that mean pain scores were greater with resin-based sealers than with bioceramics sealers at 12 h. Heterogeneity (I2) was 0%, and a fixed effect model was used. The results were not statistically significant ( p > 0.05) .
Five studies evaluated post-operative pain after 24 h of treatment. The pooled mean difference was 0.51 [0.16, 0.85] indicating that mean pain scores were greater with resin-based sealers than with bioceramics sealers at 24 h. Heterogeneity (I2) was 1%, and thus a fixed effect model was used. The results were not statistically significant ( p > 0.05) .
Four studies evaluated postoperative pain after 48 h of treatment. The pooled mean difference was −0.27 [−1.12, 0.58] indicating that mean pain scores were greater with bioceramics sealers than with resin-based sealers at 48 h. Heterogeneity (I2) was 59%, thereby using a random effect model. The results were not statistically significant ( p > 0.05) .
Four studies evaluated analgesic use after 24 h of treatment. The pooled risk ratio indicated that the risk of analgesic use with resin-based sealer was 1.89-fold (RR = 1.89 [0.61, 5.81]) more than with bioceramics-based sealer at 24 h of treatment. Heterogeneity (I2) was 59%, thereby utilizing a random effect model. The results were not statistically significant ( p > 0.05) .
The present investigation evaluated the effects of two root canal sealers on postoperative pain in single-visit endodontic treatment: resin-based sealers (RBS) and bioceramic-based sealers (BCS). Every study that was included completed the entire root canal procedure—including root canal preparation and obturation in a single visit. Endodontic procedures can induce patient anxiety, especially when complications and pain arise and thus exacerbate this anxiety . Severe pain after root canal treatment reflects intricate cellular-level physiological changes . At the start of endodontic therapy, three potential outcomes that may occur include no symptoms, manageable pain/pressure, or intense pain/swelling which needs an unscheduled clinical visit . Post-operative endodontic pain often stems from local inflammatory responses in periapical tissue, with biochemical mediators such as reactive oxygen species (ROS) contributed to the discomfort . Root canal sealers, including bioceramic-based sealers (BCS) and resin-based sealers (RBS), can induce post-operative discomfort by releasing ROS and activating trigeminal nociceptors and pain-sensitive sensory receptors. This activation may lead to increased irritation and discomfort, possibly exacerbated by the release of calcitonin gene-related peptides (CGRP) via nociceptor stimulation . Therefore, selecting the suitable sealer and applying it correctly is essential to minimize post-operative pain and discomfort. This study focused on comparing the frequency of postoperative pain associated with two distinct types of root canal sealers: BCS and RBS. BCS, composed of biocompatible and bioactive inorganic materials, offers high sealing qualities, biocompatibility, and antibacterial activity. In contrast, RBS, made of organic components, may exhibit lower biocompatibility and antibacterial activity but its high pH that can neutralize the root canal’s acidic environment and benefit periapical tissues . Notably, resin-based sealers like AH plus may release residual monomers, potentially triggering inflammation and discomfort, while BCS, with its biocompatible and bioactive inorganic materials, ensures a tight seal within the root canal, preventing bacterial entry and infection . Choosing a certain type of sealer may have a significant impact on postoperative patient comfort after endodontic procedures. A meta-analysis was conducted to assess postoperative pain levels at specific intervals of 6, 12, 24, and 48 h following dental procedures. The importance of evaluating pain at these particular time points is that it can significantly impact a patient’s comfort, function, and overall quality of life. An accurate understanding of pain duration, intensity and these critical intervals can help clinicians develop effective pain management strategies, minimize patient discomfort and promote optimal healing . Post-operative pain at six hours is a key indicator of immediate post-operative discomfort, while pain levels at 12 h signify the patient’s recovery . Two studies compared post-operative pain in patients using resin-based and bioceramic-based sealers at six and 12 h of interval. The pooled mean difference was 0.30, suggesting slightly higher pain scores in resin-based sealers. However, with low heterogeneity (I2 = 0%) and a significance level ( p = 0.25) greater than 0.05, the difference in pain scores between the two groups may not be substantial enough to cause different levels of pain. Post-operative pain at 24 h is a crucial marker in a patient’s recovery. Five studies assessed post-operative pain levels at the 24-hour interval were consistent with those at 6 and 12 h. Resin-based sealers consistently showed slightly higher pain scores than bioceramic sealers. Importantly, the analysis found no statistically significant difference in pain scores between the two groups (resin-based and bioceramic root canal sealers) as indicated by the obtained p -value ( p > 0.05). Patients who have undergone root canal therapy could experience pain at 48 h of post operation, which could indicate delated pain or complications. The postoperative pain after 48 h of operation was assessed in four studies . The bioceramic sealers were consistently reported resulting slightly higher pain scores than resin-based sealers. However, based on the statistical analysis with a p -value greater than 0.05, it was determined that there was no statistically significant distinction between the resin-based and bioceramic root canal sealers. The results showed that the analgesics were used in conjunction with root canal sealers to manage post-operative pain. A meta-analysis conducted examined the use of analgesics at 24 h after root canal therapy involving resin-based and bioceramic-based sealers. Data from four studies analyzed revealed that patients receiving resin-based sealers were 1.89 times more likely to require analgesics compared to those with bioceramic-based sealers. However, there was notable variability in the need of analgesics among the studies. Two of the nine selected studies concluded that pain after the use of bioceramic sealers was lower than that after the use of resin-based sealers . The other seven studies concluded that there was no difference between postoperative pain after the use of either bioceramic or resin-based sealers. The results align with the latter group of studies. The different approaches and methods used by the included studies present one possible research constraint. This might add heterogeneity into the analysis and compromise the validity and generalizability of the findings. Furthermore, the potential for publication bias and the dependence on published research may have an effect on the overall results and distort the conclusions. The generalizability of the results may be further limited by variations in participant demographics and cultural characteristics, as well as in the definition and measurement of postoperative pain. These limitations might be addressed by subgroup analyses to account for methodological variations. Sensitivity analysis and meta-regression are two further tools for managing heterogeneity. A thorough search approach that includes unpublished studies and grey literature, in addition to statistical measures like Egger’s test and funnel plots. It is essential to take cultural norms and healthcare systems into account when adapting conclusions to various populations and circumstances.
The pain levels for bioceramic sealers were less than resin-based sealers till 24 h post-operatively. However, after 48 h, the pain levels in the bioceramic group were greater than the resin-based sealers. The findings of this systematic review and meta-analysis suggest that postoperative pain levels with bioceramic sealers had no significant difference from those reported after the use of resin-based sealers.
10.7717/peerj.18198/supp-1 Supplemental Information 1 PRISMA checklist 10.7717/peerj.18198/supp-2 Supplemental Information 2 Rationale
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The PRIDE database at 20 years: 2025 update | 010b84a5-5636-473f-a297-eb9db676cfd4 | 11701690 | Biochemistry[mh] | Data sharing in the public domain has become the standard behavior for proteomics researchers and many scientific journals and funding agencies currently mandate open science practices, involving for instance the submission of proteomics datasets to public repositories ( , ). The PRoteomics IDEntifications (PRIDE) database ( https://www.ebi.ac.uk/pride/ ) at the European Bioinformatics Institute (EMBL-EBI, Hinxton, Cambridge, UK) enables public data deposition of mass spectrometry (MS)-based proteomics data, providing access to the experimental data described in scientific publications ( ). Started in 2004 ( ), PRIDE Archive (the archival component of PRIDE) is the largest data repository for proteomics data worldwide ( , ). PRIDE stores datasets coming from all MS-based proteomics experimental approaches, including quantitative data-dependent acquisition (DDA) and data-independent acquisition (DIA) bottom-up proteomics, but also, to a smaller extent, datasets generated from other workflows such as e.g. top-down, peptidomics (e.g. immunopeptidomics approaches) or crosslinking proteomics, in parallel with the trends in the field. PRIDE is one of the founders of the ProteomeXchange consortium ( https://www.proteomexchange.org ) ( , ) bringing together MS-based proteomics data resources worldwide. ProteomeXchange, formally established in 2012, provides globally coordinated standard data submission and dissemination pipelines for proteomics datasets, and promotes open data policies in the field. The resources PeptideAtlas ( ), including its related resource PASSEL (PeptideAtlas SRM Experiment Library) ( ), MassIVE ( ), jPOST ( ), iProX ( ) and Panorama Public ( ), are the members of the consortium in addition to PRIDE. ProteomeXchange provides a common accession number for every submitted dataset and a set of services for public data search and retrieval across the resources. In December 2022, ProteomeXchange resources were recognized in the initial list of Global Core Biodata Resources ( https://globalbiodata.org/what-we-do/global-core-biodata-resources/ ) by the Global Biodata Coalition, with the aim to highlight those essential biological resources for the scientific community. The PRIDE database is also a core data resource of ELIXIR ( http://www.elixir-europe.org ) ( ), recognizing its key role in the life sciences ecosystem in Europe. PRIDE, together with the other ProteomeXchange resources, supports the FAIR (Findable, Accessible, Interoperable, Reusable) data principles ( ). In the context of interoperability, the PRIDE team has (co)led within the PSI (Proteomics Standards Initiative) ( ), the development and implementation of several open standard formats such as mzTab ( ), mzIdentML ( , ), mzML ( ), ProForma version 2.0 ( ), the SDRF-Proteomics (Sample and Data Relationship File) format ( ) and the Universal Spectrum Identifiers (USIs) ( ), among others, to facilitate the storage, processing and visualization of the deposited proteomics data. PRIDE resources have two main missions: (i) support data deposition of all types of MS-based proteomics data supporting reproducible research and enabling public data reuse, implementing the FAIR data principles; and (ii) to bring proteomics data closer to life scientists by re-using, disseminating and integrating the data in other resources, including EMBL-EBI’s Ensembl ( ), UniProt ( ) and Expression Atlas ( ), among others. In this manuscript, we summarize the main PRIDE-related developments in the last three years, since the previous Nucleic Acids Research (NAR) database update manuscript was published ( ). We will discuss PRIDE Archive and related resources first but will also provide updated information about other ongoing activities including the updates in the data reuse context, performed to disseminate and integrate proteomics data in other resources.
The PRIDE database ecosystem is composed of a set of libraries, desktop tools, databases, large-scale pipelines, Restful APIs (Application Programming Interface) and web applications. Figure illustrates the current PRIDE ecosystem, including web services and data pipelines. Since 2022, the major focus of the PRIDE team in infrastructure-related topics has been put in three major areas: (i) data transfer, including the availability of a new protocol for uploading data to PRIDE Archive, the Globus file transfer service; (ii) Automatic validation and resubmission pipelines which enable to reduce the time it takes for every submitter to get a dataset accession number; and (iii) the development of new services to query and retrieve PRIDE data: PRIDE USI service ( https://www.ebi.ac.uk/pride/archive/usi ) and the PRIDE Crosslinking resource ( https://www.ebi.ac.uk/pride/archive/crosslinking ). A set of open-source Java libraries supported and maintained by the team enables the reading, validation, processing and storage of proteomics data encoded in PSI open file formats ( , ). PRIDE Archive data pipelines (validation, submission, resubmission and publication) make possible the validation and submission of datasets and files in the EMBL-EBI production file system. The team has increased the number of Restful APIs that enable querying the PRIDE data in multiple ways, including searching, retrieving, and streaming private and public datasets, and also to retrieve specific mass spectra using USIs ( ). There are four major web interfaces currently in PRIDE: PRIDE Archive ( https://www.ebi.ac.uk/pride/archive ), PRIDE Archive USI ( https://www.ebi.ac.uk/pride/archive/usi ), the PRIDE Crosslinking resource ( https://www.ebi.ac.uk/pride/archive/crosslinking ) and PRIDE spectral libraries ( https://www.ebi.ac.uk/pride/spectrumlibrary ). In addition, in Figure , it can be observed that PRIDE continues to provide metadata and different proteomics data types to other resources including Expression Atlas ( ), Omics Discovery Index ( , ), ProteomeCentral ( ) as the common search interface in ProteomeXchange, UniProt ( ), Ensembl ( ) and BioSamples ( ). In the following sections, new resources and improvements in existing services will be described in detail. Data submission PRIDE Archive data submission guidelines, aligned with the ProteomeXchange requirements ( ), mandate the inclusion of MS raw files and processed results (peptide/protein identification and quantification). Additional components may include peak list files, protein sequence databases or spectral libraries, scripts and other relevant metadata ( ). A tutorial on the submission process is available at the EMBL-EBI online training platform: ‘PRIDE Quick Tour’ ( https://www.ebi.ac.uk/training/online/courses/pride-quick-tour/ ). Data submissions are mostly performed using the stand-alone ProteomeXchange submission tool. The tool enables the provision of the required metadata for each dataset, including title, description and controlled vocabulary/ontology terms including information about species, mass spectrometers or diseases ( ), among other pieces of information. The PRIDE data policy explaining how datasets are handled is available at https://www.ebi.ac.uk/pride/markdownpage/datapolicy . Three major improvements have been implemented to facilitate the data submission process to PRIDE Archive: (i) improvements in the dataset resubmission process, (ii) enabling the data uploads using the Globus data transfer service and (iii) automatic validation and submission of datasets. More granularity in the dataset resubmission process During the manuscript review process, authors may have to add, modify, or remove files in their submitted datasets. Until recently, making changes to a private submission (i.e. under review) required to perform again a new resubmission of all the files included in the dataset, even if only one file needed to get changed/replaced, leading to unnecessary efforts. This approach was not a major issue when the resubmission process was originally designed (at the time submitted datasets averaged around 10 files, making it feasible to transfer the entire dataset again). However, this methodology has become increasingly impractical in time with the growing average number of samples and raw files per dataset. We have implemented a new resubmission system integrated into the ProteomeXchange submission tool (Figure ), involving a new dataset resubmission pipeline as well. PRIDE users can now select one of their existing private datasets using the submission tool and choose which files to update, delete, or add. Once the files are uploaded into PRIDE, the resubmission pipeline then validates only the new or modified files, while ensuring the integrity of the entire dataset. Since the release of this feature, it has been extensively used by submitters to modify ‘SEARCH’ files (processed results files from the search engines), which can be often updated during the review process. Globus-based submissions: complementing the FTP and Aspera data transfer protocols Until recently, data transfers to the PRIDE Archive were performed via FTP (File Transfer Protocol) or Aspera ( https://www.ibm.com/products/aspera ), with Aspera being the default option due to its faster file transfer speed. However, Aspera is not always accessible at research institutions, since its required ports are often blocked by internal/local IT regulations. Additionally, large datasets can still take several hours to transfer, depending on the users’ internet speed. In such cases, the ProteomeXchange submission tool may freeze, forcing users to restart the submission process. We have recently introduced a new submission mechanism using the Globus transfer service ( https://www.globus.org/data-transfer ), offering a third option for performing data submissions alongside the FTP and Aspera protocols. To begin, users should use the ProteomeXchange submission tool to generate the required submission.px file, which contains the submission metadata including also the list of files included in each dataset. The submission.px file, a checksum.txt file (needed to assess the file integrity after the file transfer) and all the files to be submitted, can then be transferred to PRIDE via Globus. Before starting, users must have an account in both PRIDE and Globus; then they must log-into the PRIDE web portal, request a new submission (Figure ), and provide their Globus account details. They will receive an email with a folder name for performing the file transfer. After installing and configuring Globus Connect Personal ( https://www.globus.org/globus-connect-personal ) and following the Globus tutorial, users can select their own created collection and the ‘PRIDE Submissions collection’ in the Globus File Manager. All files, including the checksum.txt and submission.px, should be uploaded to the designated PRIDE folder. Once the upload is complete, users must return to the PRIDE web portal to finalize their submission ( https://www.ebi.ac.uk/pride/markdownpage/globus ). We recommend using the Globus transfer protocol for large datasets and in institutions where it is not possible to use Aspera due to IT restrictions. Automatic dataset validation and submission After a dataset is submitted to PRIDE, two steps take place before a submitter receives the dataset accession number: dataset validation and submission. First, in the validation step, the metadata is checked including the controlled vocabularies used, metadata fields (e.g. title), and that the size and integrity of the files submitted are correct (checksum.txt). In the submission step, files are transferred from the staging (submission) area into a more permanent storage system. Metadata is then transferred to a database, enabling submitters to make changes during the manuscript review process without the need to transfer all the data again (see above). Finally, a dataset accession is requested from ProteomeXchange and sent to the submitter. Until the beginning of 2023, these two processes were manually triggered by a PRIDE curator. While this manual process ensured correctness, it also caused delays in obtaining an accession number due to e.g. increased number of submissions, and/or holiday periods. On average, dataset accessions were issued within 34 hours under this system. We have now introduced a new workflow that uses rules and natural language processing (NLP) pipelines to automate the validation and submission of datasets. This update has reduced the average time to finish data submissions to just 4 minutes. Continuing metadata deposition using the SDRF-Proteomics format Since 2022 PRIDE Archive has supported the submission of general sample metadata and experimental design information using the SDRF-Proteomics format ( , ). This standard tab-delimited format ( ) ( https://github.com/bigbio/proteomics-metadata-standard ) can capture the experimental design and details the relationship between the samples included in a dataset and the corresponding MS data files (raw files). Submitters can manually add SDRF-Proteomics files to their submitted datasets by selecting ‘EXPERIMENTAL DESIGN’ as the file type in the submission tool. The corresponding experimental design table is accessible through the PRIDE Archive web interface (e.g. dataset PXD047854, https://www.ebi.ac.uk/pride/archive/projects/PXD047854 ). In the last three years, various tools have enhanced the adoption of SDRF-Proteomics by enabling the annotation, export and reuse of SDRF-Proteomics data from PRIDE. First, lesSDRF ( ) is a web-based tool that enables submitters to create templates and annotate their datasets. Additionally, FragPipe ( ) enables the export of an SDRF-Proteomics draft file containing search parameters and file names, but not sample details. Furthermore, the quantms workflow ( ) facilitates the reuse of public proteomics data using deposited SDRF-Proteomics files. The PRIDE team continues to collaborate with other tool providers (e.g. MaxQuant, Proteome Discoverer) to improve the adoption of SDRF-Proteomics as a standard format for parameter input and experimental design output. PRIDE Archive Restful APIs: programmatic access to datasets The PRIDE RESTful API ( https://www.ebi.ac.uk/pride/ws/archive/v2/ ) enables users to query and access all data within PRIDE resources. The API allows for various queries, such as retrieving datasets by publication date, identifying specific proteins or locating a data file within a given dataset. Its powerful query language supports SQL-based searches by combining multiple keywords (project properties). Additionally, a Python package and tool ( https://github.com/PRIDE-Archive/pridepy ) have been developed to facilitate programmatic interaction with the PRIDE Archive RESTful API. Three new APIs have been integrated into PRIDE Archive’s main RESTful web service. The PRIDE file streaming API enables users to transfer files from public datasets using a streaming approach, which processes data in small, manageable chunks rather than loading entire files into memory. More information and a public benchmark comparing FTP, HTTPS and the streaming API can be found in the PRIDE documentation ( https://www.ebi.ac.uk/pride/markdownpage/pridefiledownload#benchmarking_data_downloads ). The PRIDE Archive USI API ( https://www.ebi.ac.uk/pride/molecules/ws/swagger-ui/index.html ) allows users to retrieve specific spectra from PRIDE Archive files from Thermo Scientific instruments (see section ‘PRIDEArchive USI: Accessing and Visualizing mass spectra’). Lastly, the PRIDE Crosslinking resource API ( https://www.ebi.ac.uk/pride/ws/archive/crosslinking/v2/docs ) provides access to data from ‘complete’ crosslinking submissions within the PRIDE Crosslinking resource (see section ‘PRIDE Crosslinking’). PRIDE Archive USI: accessing and visualizing mass spectra Direct access to the identified spectra (or PSMs, Peptide Spectrum Match) within a given dataset enables the evaluation of whether, e.g., novel peptide sequences, post-translational modifications (PTMs) or single amino acid variants (SAAVs) are supported by high-quality, well-annotated mass spectra ( , ). The introduction of USIs has significantly enhanced the transparency of the mass spectral evidence, offering a standardized method for accessing mass spectra data across ProteomeXchange resources. Previously, we developed a first version of the resource, which enabled the retrieval of identified spectra from ‘Complete’ submissions, providing access to over 540 million PSMs at the time. Although the goal was to offer real-time access to all spectra (and not only to those in open formats, as part of ‘Complete’ submissions), this was initially challenging due to PRIDE Archive’s architecture and the difficulty of accessing MS raw data files (from the different MS vendors) from Unix systems. The current PRIDE Archive USI ( https://www.ebi.ac.uk/pride/archive/usi ) allows the retrieval of most mass spectra in PRIDE Archive using a USI. Unlike the previous approach of indexing PSMs for ‘Complete’ submissions, the current system reads the provided USI and locates the specified scan directly in the MS raw files. The PRIDE Archive USI APIs leverage the ThermoRawFileParser ( ) to extract the scan from the MS raw files, providing access to over 80% of the stored MS raw files (those from Thermo Scientific instruments). Efforts are ongoing to expand access to spectra from other instrument vendors, such as Bruker and SCIEX. Additionally, the PRIDE Archive USI is integrated with the ProteomeCentral API, enabling access to MassIVE, the second-largest resource in ProteomeXchange. Various databases, including MatrisomeDB ( ), Scop3P ( ) and also ProteomeCentral USI ( ), utilize PRIDE Archive USIs to access and visualize PSMs, for peptide identifications included in reanalyzed datasets. PRIDE Crosslinking In the interface between proteomics and structural biology, crosslinking MS is one of the most popular approaches. Due to the increased relevance of structural biology approaches in proteomics, a first version of the PRIDE Crosslinking resource ( https://www.ebi.ac.uk/pride/archive/crosslinking ) has been developed and recently released, aiming to improve data access and visualization for crosslinking studies and to bridge proteomics and structural biology data. In that context, it provides cross-references to the Protein Data Bank (PDB), including PDBe (PDB in Europe) ( ), PDB-Dev and AlphaFoldDB (database of predicted protein structures) ( ). The tool xiVIEW ( ) has been integrated to enable the visualization of this type of dataset. As of August 2024, PRIDE Crosslinking includes 22 datasets coming from 9 different organisms, encompassing a total of 524 443 peptides coming from 4905 proteins. The number of datasets and overall functionality will grow as new relevant datasets become publicly available and are integrated into the resource (guidelines for submission are available at https://www.ebi.ac.uk/pride/markdownpage/crosslinking ). As mentioned above, PRIDE Crosslinking is complemented by an API ( https://www.ebi.ac.uk/pride/ws/archive/crosslinking/v2/docs ). PRIDE chatbot and PRIDE documentation Artificial intelligence (AI) approaches and Large Language Models (LLMs) are transforming every field where they can be used. We have developed a PRIDE chatbot ( https://www.ebi.ac.uk/pride/chatbot/ ) ( ) featuring a web service API, a user-friendly web interface and specialized open-source LLMs. The PRIDE Chatbot has been trained using the PRIDE external documentation. The overall idea is 2-fold: on one hand we aim to help PRIDE users navigate PRIDE documentation, therefore decreasing the time required for the team to reply to user support queries. On the other hand, we would like to improve the dataset search functionality. As of August 2024, two open-source models (Mixtral and llama2-13b-chat) are supported. During the development of the chatbot, the PRIDE external documentation was optimized by adding new topics and eliminating redundant information. Additionally, the several training videos have been made available, covering the submission process, the SDRF-Proteomics format and the broader ecosystem of PRIDE resources, including tools, web services and the web interface (e.g. https://www.youtube.com/watch?v=VRNumsnYVg0 ). Additional developments In addition to major advancements in infrastructure, other minor refinements have been implemented. Notably, PRIDE now operates on a complete microservice architecture, where all services—such as databases, file access and search and indexing systems—are provided through microservices (APIs). This architecture enables PRIDE to scale effectively and be deployed in cloud-based Kubernetes environments. The new design allows the PRIDE team to scale each API independently by increasing the number of instances as needed. Additionally, the ProteomeXchange submission tool now allows submitters to manually select and switch the submission protocol (FTP or Aspera) directly within the interface. In previous versions, users had to modify a configuration file to change the protocol, making the process cumbersome. The current version streamlines this by enabling protocol switching within the interface without requiring users to close the application, edit configuration files or restart the tool.
PRIDE Archive data submission guidelines, aligned with the ProteomeXchange requirements ( ), mandate the inclusion of MS raw files and processed results (peptide/protein identification and quantification). Additional components may include peak list files, protein sequence databases or spectral libraries, scripts and other relevant metadata ( ). A tutorial on the submission process is available at the EMBL-EBI online training platform: ‘PRIDE Quick Tour’ ( https://www.ebi.ac.uk/training/online/courses/pride-quick-tour/ ). Data submissions are mostly performed using the stand-alone ProteomeXchange submission tool. The tool enables the provision of the required metadata for each dataset, including title, description and controlled vocabulary/ontology terms including information about species, mass spectrometers or diseases ( ), among other pieces of information. The PRIDE data policy explaining how datasets are handled is available at https://www.ebi.ac.uk/pride/markdownpage/datapolicy . Three major improvements have been implemented to facilitate the data submission process to PRIDE Archive: (i) improvements in the dataset resubmission process, (ii) enabling the data uploads using the Globus data transfer service and (iii) automatic validation and submission of datasets. More granularity in the dataset resubmission process During the manuscript review process, authors may have to add, modify, or remove files in their submitted datasets. Until recently, making changes to a private submission (i.e. under review) required to perform again a new resubmission of all the files included in the dataset, even if only one file needed to get changed/replaced, leading to unnecessary efforts. This approach was not a major issue when the resubmission process was originally designed (at the time submitted datasets averaged around 10 files, making it feasible to transfer the entire dataset again). However, this methodology has become increasingly impractical in time with the growing average number of samples and raw files per dataset. We have implemented a new resubmission system integrated into the ProteomeXchange submission tool (Figure ), involving a new dataset resubmission pipeline as well. PRIDE users can now select one of their existing private datasets using the submission tool and choose which files to update, delete, or add. Once the files are uploaded into PRIDE, the resubmission pipeline then validates only the new or modified files, while ensuring the integrity of the entire dataset. Since the release of this feature, it has been extensively used by submitters to modify ‘SEARCH’ files (processed results files from the search engines), which can be often updated during the review process. Globus-based submissions: complementing the FTP and Aspera data transfer protocols Until recently, data transfers to the PRIDE Archive were performed via FTP (File Transfer Protocol) or Aspera ( https://www.ibm.com/products/aspera ), with Aspera being the default option due to its faster file transfer speed. However, Aspera is not always accessible at research institutions, since its required ports are often blocked by internal/local IT regulations. Additionally, large datasets can still take several hours to transfer, depending on the users’ internet speed. In such cases, the ProteomeXchange submission tool may freeze, forcing users to restart the submission process. We have recently introduced a new submission mechanism using the Globus transfer service ( https://www.globus.org/data-transfer ), offering a third option for performing data submissions alongside the FTP and Aspera protocols. To begin, users should use the ProteomeXchange submission tool to generate the required submission.px file, which contains the submission metadata including also the list of files included in each dataset. The submission.px file, a checksum.txt file (needed to assess the file integrity after the file transfer) and all the files to be submitted, can then be transferred to PRIDE via Globus. Before starting, users must have an account in both PRIDE and Globus; then they must log-into the PRIDE web portal, request a new submission (Figure ), and provide their Globus account details. They will receive an email with a folder name for performing the file transfer. After installing and configuring Globus Connect Personal ( https://www.globus.org/globus-connect-personal ) and following the Globus tutorial, users can select their own created collection and the ‘PRIDE Submissions collection’ in the Globus File Manager. All files, including the checksum.txt and submission.px, should be uploaded to the designated PRIDE folder. Once the upload is complete, users must return to the PRIDE web portal to finalize their submission ( https://www.ebi.ac.uk/pride/markdownpage/globus ). We recommend using the Globus transfer protocol for large datasets and in institutions where it is not possible to use Aspera due to IT restrictions. Automatic dataset validation and submission After a dataset is submitted to PRIDE, two steps take place before a submitter receives the dataset accession number: dataset validation and submission. First, in the validation step, the metadata is checked including the controlled vocabularies used, metadata fields (e.g. title), and that the size and integrity of the files submitted are correct (checksum.txt). In the submission step, files are transferred from the staging (submission) area into a more permanent storage system. Metadata is then transferred to a database, enabling submitters to make changes during the manuscript review process without the need to transfer all the data again (see above). Finally, a dataset accession is requested from ProteomeXchange and sent to the submitter. Until the beginning of 2023, these two processes were manually triggered by a PRIDE curator. While this manual process ensured correctness, it also caused delays in obtaining an accession number due to e.g. increased number of submissions, and/or holiday periods. On average, dataset accessions were issued within 34 hours under this system. We have now introduced a new workflow that uses rules and natural language processing (NLP) pipelines to automate the validation and submission of datasets. This update has reduced the average time to finish data submissions to just 4 minutes.
During the manuscript review process, authors may have to add, modify, or remove files in their submitted datasets. Until recently, making changes to a private submission (i.e. under review) required to perform again a new resubmission of all the files included in the dataset, even if only one file needed to get changed/replaced, leading to unnecessary efforts. This approach was not a major issue when the resubmission process was originally designed (at the time submitted datasets averaged around 10 files, making it feasible to transfer the entire dataset again). However, this methodology has become increasingly impractical in time with the growing average number of samples and raw files per dataset. We have implemented a new resubmission system integrated into the ProteomeXchange submission tool (Figure ), involving a new dataset resubmission pipeline as well. PRIDE users can now select one of their existing private datasets using the submission tool and choose which files to update, delete, or add. Once the files are uploaded into PRIDE, the resubmission pipeline then validates only the new or modified files, while ensuring the integrity of the entire dataset. Since the release of this feature, it has been extensively used by submitters to modify ‘SEARCH’ files (processed results files from the search engines), which can be often updated during the review process.
Until recently, data transfers to the PRIDE Archive were performed via FTP (File Transfer Protocol) or Aspera ( https://www.ibm.com/products/aspera ), with Aspera being the default option due to its faster file transfer speed. However, Aspera is not always accessible at research institutions, since its required ports are often blocked by internal/local IT regulations. Additionally, large datasets can still take several hours to transfer, depending on the users’ internet speed. In such cases, the ProteomeXchange submission tool may freeze, forcing users to restart the submission process. We have recently introduced a new submission mechanism using the Globus transfer service ( https://www.globus.org/data-transfer ), offering a third option for performing data submissions alongside the FTP and Aspera protocols. To begin, users should use the ProteomeXchange submission tool to generate the required submission.px file, which contains the submission metadata including also the list of files included in each dataset. The submission.px file, a checksum.txt file (needed to assess the file integrity after the file transfer) and all the files to be submitted, can then be transferred to PRIDE via Globus. Before starting, users must have an account in both PRIDE and Globus; then they must log-into the PRIDE web portal, request a new submission (Figure ), and provide their Globus account details. They will receive an email with a folder name for performing the file transfer. After installing and configuring Globus Connect Personal ( https://www.globus.org/globus-connect-personal ) and following the Globus tutorial, users can select their own created collection and the ‘PRIDE Submissions collection’ in the Globus File Manager. All files, including the checksum.txt and submission.px, should be uploaded to the designated PRIDE folder. Once the upload is complete, users must return to the PRIDE web portal to finalize their submission ( https://www.ebi.ac.uk/pride/markdownpage/globus ). We recommend using the Globus transfer protocol for large datasets and in institutions where it is not possible to use Aspera due to IT restrictions.
After a dataset is submitted to PRIDE, two steps take place before a submitter receives the dataset accession number: dataset validation and submission. First, in the validation step, the metadata is checked including the controlled vocabularies used, metadata fields (e.g. title), and that the size and integrity of the files submitted are correct (checksum.txt). In the submission step, files are transferred from the staging (submission) area into a more permanent storage system. Metadata is then transferred to a database, enabling submitters to make changes during the manuscript review process without the need to transfer all the data again (see above). Finally, a dataset accession is requested from ProteomeXchange and sent to the submitter. Until the beginning of 2023, these two processes were manually triggered by a PRIDE curator. While this manual process ensured correctness, it also caused delays in obtaining an accession number due to e.g. increased number of submissions, and/or holiday periods. On average, dataset accessions were issued within 34 hours under this system. We have now introduced a new workflow that uses rules and natural language processing (NLP) pipelines to automate the validation and submission of datasets. This update has reduced the average time to finish data submissions to just 4 minutes.
Since 2022 PRIDE Archive has supported the submission of general sample metadata and experimental design information using the SDRF-Proteomics format ( , ). This standard tab-delimited format ( ) ( https://github.com/bigbio/proteomics-metadata-standard ) can capture the experimental design and details the relationship between the samples included in a dataset and the corresponding MS data files (raw files). Submitters can manually add SDRF-Proteomics files to their submitted datasets by selecting ‘EXPERIMENTAL DESIGN’ as the file type in the submission tool. The corresponding experimental design table is accessible through the PRIDE Archive web interface (e.g. dataset PXD047854, https://www.ebi.ac.uk/pride/archive/projects/PXD047854 ). In the last three years, various tools have enhanced the adoption of SDRF-Proteomics by enabling the annotation, export and reuse of SDRF-Proteomics data from PRIDE. First, lesSDRF ( ) is a web-based tool that enables submitters to create templates and annotate their datasets. Additionally, FragPipe ( ) enables the export of an SDRF-Proteomics draft file containing search parameters and file names, but not sample details. Furthermore, the quantms workflow ( ) facilitates the reuse of public proteomics data using deposited SDRF-Proteomics files. The PRIDE team continues to collaborate with other tool providers (e.g. MaxQuant, Proteome Discoverer) to improve the adoption of SDRF-Proteomics as a standard format for parameter input and experimental design output.
The PRIDE RESTful API ( https://www.ebi.ac.uk/pride/ws/archive/v2/ ) enables users to query and access all data within PRIDE resources. The API allows for various queries, such as retrieving datasets by publication date, identifying specific proteins or locating a data file within a given dataset. Its powerful query language supports SQL-based searches by combining multiple keywords (project properties). Additionally, a Python package and tool ( https://github.com/PRIDE-Archive/pridepy ) have been developed to facilitate programmatic interaction with the PRIDE Archive RESTful API. Three new APIs have been integrated into PRIDE Archive’s main RESTful web service. The PRIDE file streaming API enables users to transfer files from public datasets using a streaming approach, which processes data in small, manageable chunks rather than loading entire files into memory. More information and a public benchmark comparing FTP, HTTPS and the streaming API can be found in the PRIDE documentation ( https://www.ebi.ac.uk/pride/markdownpage/pridefiledownload#benchmarking_data_downloads ). The PRIDE Archive USI API ( https://www.ebi.ac.uk/pride/molecules/ws/swagger-ui/index.html ) allows users to retrieve specific spectra from PRIDE Archive files from Thermo Scientific instruments (see section ‘PRIDEArchive USI: Accessing and Visualizing mass spectra’). Lastly, the PRIDE Crosslinking resource API ( https://www.ebi.ac.uk/pride/ws/archive/crosslinking/v2/docs ) provides access to data from ‘complete’ crosslinking submissions within the PRIDE Crosslinking resource (see section ‘PRIDE Crosslinking’).
Direct access to the identified spectra (or PSMs, Peptide Spectrum Match) within a given dataset enables the evaluation of whether, e.g., novel peptide sequences, post-translational modifications (PTMs) or single amino acid variants (SAAVs) are supported by high-quality, well-annotated mass spectra ( , ). The introduction of USIs has significantly enhanced the transparency of the mass spectral evidence, offering a standardized method for accessing mass spectra data across ProteomeXchange resources. Previously, we developed a first version of the resource, which enabled the retrieval of identified spectra from ‘Complete’ submissions, providing access to over 540 million PSMs at the time. Although the goal was to offer real-time access to all spectra (and not only to those in open formats, as part of ‘Complete’ submissions), this was initially challenging due to PRIDE Archive’s architecture and the difficulty of accessing MS raw data files (from the different MS vendors) from Unix systems. The current PRIDE Archive USI ( https://www.ebi.ac.uk/pride/archive/usi ) allows the retrieval of most mass spectra in PRIDE Archive using a USI. Unlike the previous approach of indexing PSMs for ‘Complete’ submissions, the current system reads the provided USI and locates the specified scan directly in the MS raw files. The PRIDE Archive USI APIs leverage the ThermoRawFileParser ( ) to extract the scan from the MS raw files, providing access to over 80% of the stored MS raw files (those from Thermo Scientific instruments). Efforts are ongoing to expand access to spectra from other instrument vendors, such as Bruker and SCIEX. Additionally, the PRIDE Archive USI is integrated with the ProteomeCentral API, enabling access to MassIVE, the second-largest resource in ProteomeXchange. Various databases, including MatrisomeDB ( ), Scop3P ( ) and also ProteomeCentral USI ( ), utilize PRIDE Archive USIs to access and visualize PSMs, for peptide identifications included in reanalyzed datasets.
In the interface between proteomics and structural biology, crosslinking MS is one of the most popular approaches. Due to the increased relevance of structural biology approaches in proteomics, a first version of the PRIDE Crosslinking resource ( https://www.ebi.ac.uk/pride/archive/crosslinking ) has been developed and recently released, aiming to improve data access and visualization for crosslinking studies and to bridge proteomics and structural biology data. In that context, it provides cross-references to the Protein Data Bank (PDB), including PDBe (PDB in Europe) ( ), PDB-Dev and AlphaFoldDB (database of predicted protein structures) ( ). The tool xiVIEW ( ) has been integrated to enable the visualization of this type of dataset. As of August 2024, PRIDE Crosslinking includes 22 datasets coming from 9 different organisms, encompassing a total of 524 443 peptides coming from 4905 proteins. The number of datasets and overall functionality will grow as new relevant datasets become publicly available and are integrated into the resource (guidelines for submission are available at https://www.ebi.ac.uk/pride/markdownpage/crosslinking ). As mentioned above, PRIDE Crosslinking is complemented by an API ( https://www.ebi.ac.uk/pride/ws/archive/crosslinking/v2/docs ).
Artificial intelligence (AI) approaches and Large Language Models (LLMs) are transforming every field where they can be used. We have developed a PRIDE chatbot ( https://www.ebi.ac.uk/pride/chatbot/ ) ( ) featuring a web service API, a user-friendly web interface and specialized open-source LLMs. The PRIDE Chatbot has been trained using the PRIDE external documentation. The overall idea is 2-fold: on one hand we aim to help PRIDE users navigate PRIDE documentation, therefore decreasing the time required for the team to reply to user support queries. On the other hand, we would like to improve the dataset search functionality. As of August 2024, two open-source models (Mixtral and llama2-13b-chat) are supported. During the development of the chatbot, the PRIDE external documentation was optimized by adding new topics and eliminating redundant information. Additionally, the several training videos have been made available, covering the submission process, the SDRF-Proteomics format and the broader ecosystem of PRIDE resources, including tools, web services and the web interface (e.g. https://www.youtube.com/watch?v=VRNumsnYVg0 ).
In addition to major advancements in infrastructure, other minor refinements have been implemented. Notably, PRIDE now operates on a complete microservice architecture, where all services—such as databases, file access and search and indexing systems—are provided through microservices (APIs). This architecture enables PRIDE to scale effectively and be deployed in cloud-based Kubernetes environments. The new design allows the PRIDE team to scale each API independently by increasing the number of instances as needed. Additionally, the ProteomeXchange submission tool now allows submitters to manually select and switch the submission protocol (FTP or Aspera) directly within the interface. In previous versions, users had to modify a configuration file to change the protocol, making the process cumbersome. The current version streamlines this by enabling protocol switching within the interface without requiring users to close the application, edit configuration files or restart the tool.
As of August 2024, PRIDE Archive stored 42 036 datasets—compared to the 23 168 datasets available in August 2021, which means that 44.9% of the datasets in PRIDE Archive have been submitted in the last three years. Figure shows the distribution of submitted datasets per month, species, disease and tissue in PRIDE Archive (January 2014 to August 2024), and the cumulative size of PRIDE Archive in terabytes. In 2023, the average number of submissions was 534 datasets per month. A new highest number of submissions in a single month was achieved in July 2024 (636 datasets) (Figure ). Approximately, 69% of the datasets in PRIDE Archive are public (29 039) and 31% private (still unreleased). The percentage of public datasets has steadily increased from 56% in 2019 ( ) to 64% in 2021 ( ), and now stands at 69%, reflecting our efforts to reduce the time for datasets to remain private. Two important factors that influence the design of the PRIDE Archive infrastructure are the continued increase in the volume (size) (Figure ) of datasets but also in the number of files per dataset. The size of the PRIDE Archive in March 2021 ( ) was 1.35 Petabytes. As of August 2024, that size had more than doubled to 285 Petabytes. As a result, PRIDE Archive is the third-largest omics Archive at EMBL-EBI only exceeded by the genomics resources ENA (European Nucleotide Archive) and EGA (European Genome-phenome Archive) ( ). More importantly, the average number of files per dataset continues to grow. As of August 2024, >10% of the datasets in PRIDE contained >100 MS raw files (Figure ). In December 2023, we processed the largest submission to PRIDE Archive to date (dataset PXD042233), containing 7444 raw files and >15 000 files in total ( ). In terms of taxonomy distribution, as of August 2024, the majority of datasets are from human origin, including those from cell lines (19 509 datasets, 46.4%), followed by mouse datasets (7 020 datasets, 16.7%) and the rest of the main model organisms (Figure ). These figures have not changed significantly over the years. The distribution of submitted datasets per disease shows that the majority of datasets are annotated as ‘disease-free (healthy/normal samples)’ followed by datasets generated in studies involving cancer, Alzheimer’s disease and Parkinson’s disease.
Enabling proteomics data reuse, following the FAIR data principles, has been one of the fundamental goals of PRIDE and ProteomeXchange ( , ). Data reuse of PRIDE datasets for multiple applications continuous to increasing. Multiple resources systematically reanalyze datasets from PRIDE including OpenProt ( ) (for proteogenomics data), MatrisomeDB ( ) (focused on the characterization of enriched extracellular matrix proteins), Scop3P ( ) (for PTM data), ProteomeHD ( ) (for protein co-expression networks) and PeptideAtlas ( ), among others. A recent review from our team ( ) shows the overlap in the number of datasets reanalyzed by all these databases. In this context of data reuse, it is also important to highlight the increased importance of PRIDE public datasets in the context of the development of machine learning/deep learning approaches, which are revolutionizing the field ( , ). Figure shows the number of reanalyzed datasets by counting their direct mentions (dataset accession numbers) in EuropePMC (Europe PubMedCentral) ( ). The majority of the datasets are mentioned between 2 and 5 times. However, some of the datasets are reanalyzed multiple times. Overall, the number of datasets mentioned as reanalyzed is <10% of the PRIDE public datasets. The volumes of data downloaded from PRIDE Archive show that on average (from January 2022 to July 2024) >100 TBs were downloaded every month (Figure ). In the context of in-house data reuse, as mentioned above, our focus has been mainly put in disseminating and integrating PRIDE data into added-value EMBL-EBI resources such as UniProt, Ensembl and Expression Atlas. The dissemination of public proteomics data into different resources has different goals depending on each specific resource. PRIDE large-scale proteogenomics reanalysis In 2019, we introduced a mechanism to register ‘TrackHubs’ containing proteomics data in Ensembl, each consisting of a BED file containing peptide coordinates at a genome level paired with the corresponding metadata. We generated ‘TrackHubs’ for over 4 million canonical peptide sequences from 184 PRIDE datasets. Recently, we have developed a new approach that allows PRIDE users to include BED files directly in their submitted datasets. These files can be manually uploaded and visualized into the Ensembl ( ) genome browser. To assist PRIDE submitters in converting their peptide identifications into BED files, including genome coordinates, we developed the PepGenome tool ( https://github.com/bigbio/pepgenome/ ), a Java command-line utility. PepGenome converts peptide identification files, such as mzIdentML, mzTab or tab-delimited files, into BED files. The tool supports mapping canonical peptide sequences (peptides with an exact match to the genome/proteome under study) as well as variant peptides, including those with one or more mismatches. Users can include the generated BED files in their data submissions, and after publication, a unique URL will be provided to facilitate loading the data into genome browsers (e.g. https://www.ebi.ac.uk/pride/archive/projects/PXD029362 ). We have been recently working on the development of large-scale data workflows for proteogenomics analysis, aiming to map non-canonical peptides, including variants and mutations, to genome coordinates. The quantms workflow ( ), an nf-core open-source tool based on OpenMS ( ) and DIA-NN ( ), enables the reanalysis of public data on cloud and HPC infrastructures using BioContainers packages ( , ). By leveraging custom proteogenomic databases generated with pypgatk ( https://github.com/bigbio/py-pgatk ) and quantms, we identified 43 501 non-canonical peptides and 786 variant peptide sequences across four public datasets ( ). All variant data, along with BED files, were made available in PRIDE Archive (datasets PXD029362 and PXD029360). Additionally, we have recently explored the identification of genome population variants (pangenome) in large-scale tissue proteomes ( ), investigating the potential impact of pangenomes on future proteomics experiments and the need for novel workflows to identify and validate non-canonical peptides. We managed to identify 4991 novel peptide sequences and 3921 SAAVs, corresponding to 2367 genes across five population groups. PRIDE data dissemination into UniProt We continue to work under the umbrella of the ‘PTMeXchange’ project ( https://www.proteomexchange.org/ptmexchange/ , in collaboration with UniProt, PeptideAtlas, Prof. Andy Jones’s team at the University of Liverpool and others), aiming to reanalyze, and disseminate high-quality PTM data from PRIDE and PeptideAtlas into UniProt. First of all, a methodology based on the use of decoy-amino acids was developed to provide a reliable way to calculate the False Localization Rate for phosphorylation ( ) and also applied to other PTMs. The data reanalysis work is organized in groups of datasets or ‘builds’, which correspond to the analysis of one particular PTM in one given species. As of August 2024, the builds already finished and integrated in UniProt are phosphorylation in two species: rice ( ) and Plasmodium falciparum ( ). There are other ongoing ‘builds’ at different stages of completion such as human, mouse and Saccharomyces cerevisiae phosphorylation, and also work in other PTMs such as human ubiquitination, SUMOyliation and lysine acetylation. PRIDE integration of quantitative datasets in Expression Atlas We have continued to increase the content of reanalyzed quantitative proteomics datasets in Expression Atlas. As of August 2024, Expression Atlas includes protein abundance results coming from 109 proteomics datasets. Most of the integrated datasets come from tissue samples generated in healthy/baseline conditions using DDA approaches. This includes data coming from human samples (32 organs represented) ( ), and from model organisms such as mouse (13 organs) and rat (8 organs) ( ), and farm pig (14 organs) ( ). Additionally, the second main focus comes from datasets generated from cell lines/cancer tissue ( ) (the first group of datasets integrated in Expression Atlas), also including a recent study involving the reanalysis of 12 datasets to detect biomarkers of colorectal cancer using public proteomics datasets ( ). There is also ongoing work to integrate an additional set of datasets coming from human baseline tissues, but this time generated using DIA approaches ( ), following a previous pilot study ( ). Data integration between transcriptomics and proteomics datasets in Expression Atlas is enabled because protein abundance is reported in a gene-centric manner.
In 2019, we introduced a mechanism to register ‘TrackHubs’ containing proteomics data in Ensembl, each consisting of a BED file containing peptide coordinates at a genome level paired with the corresponding metadata. We generated ‘TrackHubs’ for over 4 million canonical peptide sequences from 184 PRIDE datasets. Recently, we have developed a new approach that allows PRIDE users to include BED files directly in their submitted datasets. These files can be manually uploaded and visualized into the Ensembl ( ) genome browser. To assist PRIDE submitters in converting their peptide identifications into BED files, including genome coordinates, we developed the PepGenome tool ( https://github.com/bigbio/pepgenome/ ), a Java command-line utility. PepGenome converts peptide identification files, such as mzIdentML, mzTab or tab-delimited files, into BED files. The tool supports mapping canonical peptide sequences (peptides with an exact match to the genome/proteome under study) as well as variant peptides, including those with one or more mismatches. Users can include the generated BED files in their data submissions, and after publication, a unique URL will be provided to facilitate loading the data into genome browsers (e.g. https://www.ebi.ac.uk/pride/archive/projects/PXD029362 ). We have been recently working on the development of large-scale data workflows for proteogenomics analysis, aiming to map non-canonical peptides, including variants and mutations, to genome coordinates. The quantms workflow ( ), an nf-core open-source tool based on OpenMS ( ) and DIA-NN ( ), enables the reanalysis of public data on cloud and HPC infrastructures using BioContainers packages ( , ). By leveraging custom proteogenomic databases generated with pypgatk ( https://github.com/bigbio/py-pgatk ) and quantms, we identified 43 501 non-canonical peptides and 786 variant peptide sequences across four public datasets ( ). All variant data, along with BED files, were made available in PRIDE Archive (datasets PXD029362 and PXD029360). Additionally, we have recently explored the identification of genome population variants (pangenome) in large-scale tissue proteomes ( ), investigating the potential impact of pangenomes on future proteomics experiments and the need for novel workflows to identify and validate non-canonical peptides. We managed to identify 4991 novel peptide sequences and 3921 SAAVs, corresponding to 2367 genes across five population groups.
We continue to work under the umbrella of the ‘PTMeXchange’ project ( https://www.proteomexchange.org/ptmexchange/ , in collaboration with UniProt, PeptideAtlas, Prof. Andy Jones’s team at the University of Liverpool and others), aiming to reanalyze, and disseminate high-quality PTM data from PRIDE and PeptideAtlas into UniProt. First of all, a methodology based on the use of decoy-amino acids was developed to provide a reliable way to calculate the False Localization Rate for phosphorylation ( ) and also applied to other PTMs. The data reanalysis work is organized in groups of datasets or ‘builds’, which correspond to the analysis of one particular PTM in one given species. As of August 2024, the builds already finished and integrated in UniProt are phosphorylation in two species: rice ( ) and Plasmodium falciparum ( ). There are other ongoing ‘builds’ at different stages of completion such as human, mouse and Saccharomyces cerevisiae phosphorylation, and also work in other PTMs such as human ubiquitination, SUMOyliation and lysine acetylation.
We have continued to increase the content of reanalyzed quantitative proteomics datasets in Expression Atlas. As of August 2024, Expression Atlas includes protein abundance results coming from 109 proteomics datasets. Most of the integrated datasets come from tissue samples generated in healthy/baseline conditions using DDA approaches. This includes data coming from human samples (32 organs represented) ( ), and from model organisms such as mouse (13 organs) and rat (8 organs) ( ), and farm pig (14 organs) ( ). Additionally, the second main focus comes from datasets generated from cell lines/cancer tissue ( ) (the first group of datasets integrated in Expression Atlas), also including a recent study involving the reanalysis of 12 datasets to detect biomarkers of colorectal cancer using public proteomics datasets ( ). There is also ongoing work to integrate an additional set of datasets coming from human baseline tissues, but this time generated using DIA approaches ( ), following a previous pilot study ( ). Data integration between transcriptomics and proteomics datasets in Expression Atlas is enabled because protein abundance is reported in a gene-centric manner.
Public data deposition and dissemination have revolutionized the proteomics field since the first implementation of the ProteomeXchange data workflow. The proteomics community is widely embracing open data policies. At the same time, public proteomics data are being increasingly reused with multiple applications, with an increasing focus on ‘big data’ approaches. We next outline some of the main working areas for PRIDE in the near future. PRIDE is enhancing metadata annotation standards for submitted datasets by improving the adoption of the SDRF-Proteomics format, which is increasingly supported by workflows, bioinformatics tools and annotation platforms. SDRF-Proteomics now includes support for use cases such as crosslinking MS and top-down proteomics. Additionally, the proteomics community actively contributes to the annotation of existing PRIDE/ProteomeXchange public datasets within the SDRF-Proteomics file repository ( https://github.com/bigbio/proteomics-sample-metadata ). Furthermore, we will continue to contribute to other community initiatives such as ProteomicsML ( ), aimed at improving data reuse of public datasets for AI approaches. Additionally, we have recently started to develop a new section of PRIDE Archive for Affinity proteomics (AP) datasets, coming from technologies such as Olink or SomaScan. AP experiments are becoming very popular, especially for human plasma studies, and most datasets are currently not deposited in the public domain, which is a regrettable situation. We are currently working with potential submitters of AP experiments to get the first submissions into the system. In addition, we have started to work in a controlled-access infrastructure supporting sensitive human proteomics data. This development is needed in the field since there is an increasing number of datasets (including AP datasets) that cannot be made openly available in resources such as PRIDE (or in any other ProteomeXchange resource) due to different legal reasons, including risks related to the identifiability of individuals ( ), patient consent agreements and general legislation such as GDPR (Guidelines for Data Protection Regulation) in Europe and HIPPA (Health Insurance Portability and Accountability Act) in the USA ( ). We hope a first version of the resource will be available in 2025. Additionally, we aim to increasingly perform in-house data reuse (including data reanalysis) and disseminate high-quality proteomics data from PRIDE into EMBL-EBI resources. The Open Targets platform ( ) will be the next resource where PRIDE data will be integrated, starting with protein quantitative datasets. The team remains committed to developing tools, workflows, and perform studies that demonstrate how public proteomics data can be reanalyzed to uncover new biological insights. In this context, we have also been working recently in prototype open pipelines for the reanalysis and integration of proteoform-centric data coming from top-down proteomics datasets ( ), and data integration between PRIDE with the Human Proteoform Atlas ( ) and UniProt in this context remains a possibility for the future. To finalize, we recommend interested parties in PRIDE-related developments to follow the PRIDE X account (@pride_ebi). For regular announcements of all the new publicly available datasets, users can follow the ProteomeXchange X account (@proteomexchange).
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Social media trends in obstetrics and gynecology residency programs on Instagram and X (Twitter) | 0af82edc-7ac9-40e5-945a-0efc3cb0aafe | 11073692 | Gynaecology[mh] | Currently there are 4.62 billion social media users making up 58.4% of the world population. This number grew by more than 10% from 2021 to 2022 . This trend in social media use is paralleled in healthcare with up to 90% of workers having a social media account . Increased professional content on social media has been driven by the desire to stay connected to peers in the medical community, share accurate knowledge with patients, and develop a brand . An increase in social media influence has transformed the experience of residency trainees by impacting education, professional development, and academic scholarship . The COVID pandemic has further increased residency program presence on social media as it brought significant challenges to residency recruitment, interviewing, and away rotations . The number of programs on social media is rapidly expanding but remains variable on both Instagram (40.9% neurology to 96.6% plastic surgery residency programs) and X, formerly known as Twitter, (14% of dermatology programs to 44.1% otolaryngology residency programs) . Obstetrics and gynecology (OBGYN) residency programs have increased their presence on Instagram, specifically during the pandemic . Residency applicants report that a program’s social media presence influences their application, interview, and rank process. In studies with recruitment prior to 2020, around 12–29% of applicants note that social media presence influenced their recruitment . However, after 2020, around 60%-71% of applicants reported social media impacted their perceptions of residency programs . These studies, which are from a wide range of specialties including general surgery, anesthesia, and family medicine, have concluded that programs should consider investing resources into their social media . Social media platforms have become, and likely will remain, an integral part of professional life and residency recruitment. However, factors to help engage applicants and create an interactive social media residency account are relatively unknown. Our study was performed to examine social media trends in OBGYN residencies, analyze program and social media characteristics associated with program followers, and analyze social media content and post engagement. We performed a retrospective study to identify the extent of social media presence of OBGYN programs on both Instagram and X platforms as these were those most studied prior . Facebook was initially inquired, however, given low numbers, difficulty searching the programs, and American College of Obstetrics and Gynecology (ACOG) only utilizing Instagram and X for virtual residency showcase recruitment since 2020, this was deferred . Institutional IRB exemption (#13531) was obtained for this study from Indiana University Human Research Protection Program. We complied with both Instagram and X terms of use. An online search was performed in the fall of 2021 for all Accreditation Council of Graduate Medical Education (ACGME) approved OBGYN residency programs after initial residency recruitment to capture maximal engagement. Two individual observers (AC, CG) found programs online by searching for full and abbreviated program names in addition to the search terms “OBGYN”, “obstetrics”, and “gynecology” as previously described in the literature . For every social media account, the number of followers, following, and posts were obtained (October 27, 2021 for Instagram and December 3, 2021 for X) shortly after the submission deadline for residency applications. X posts, or formerly tweets, were not analyzed given total number are not easily available and content differs from Instagram. Instagram stories were not evaluated as this is temporary content for 24 hours and difficult to extract given the number of programs. Duration of social media account existence was abstracted from the date of the program’s first post on Instagram while X publicly posts this data. Program rank was determined using the Doximity residency navigator tool by reputation in 2022 . The FREIDA database was queried to determine the type of residency program: academic, community, or combined. Both FREIDA and Doximity were used to obtain the number of residents in the program. If these were not in congruence, the residency home page was visited, and number of residents counted manually. Doximity was used to determine the location of the program, and city size was extrapolated from the location using the U.S. Census Bureau’s statistical area . Populations were defined as large metropolitan (1.5 million or more people), metropolitan (500,000 to 1.5 million people), medium-size urban (200,000–500,000 people), and small urban (50,000–200,000 people). Inquiries were also sent to each program on Instagram by direct message by author CG to ask what type of program they identify as and who posts the content on their Instagram account. Informed consent to participate was obtained with a written response. If their program type direct message was incongruent with FREIDA, FREIDA was utilized for program type given this is a nationwide database. Reply time from direct messenger was recorded. The home institution of this study was excluded from this part of the analysis. Instagram program pages were also searched to identify if they had a highlight reel and if their biography indicated who posted content. Programs were recorded as having a diversity post if there was at least one post primarily regarding any of the following: gender, social and ethnic background, or sexual orientation. The thirty OBGYN programs with the most Instagram followers were identified. Their last thirty Instagram posts on and prior to October 27, 2021 were analyzed independently by two reviewers (AC, CG). The classification of these posts was adapted from Azoury et al and Abbas et al and changed to reflect specialty differences in content . Posts were categorized into educational, informational, awards/Match, social, wellness, surgical, class, research, advocacy, diversity, and other . Additionally, the top thirty program’s Instagram highlight reels were categorized by the same two reviewers. Separate classifications were given to these posts as they include video content: educational, research, informational, social, wellness, advocacy/diversity, rotations, location, biography, question & answer (Q&A), day in the life (DITL), and other . Disagreements between the reviewers were resolved by consensus. Summary statistics were provided for the characteristics of programs with an Instagram and/or X presence. Mean and standard deviation were presented for continuous variables and frequency and percentage for categorical variables. A multivariate linear regression model was used to evaluate the association of factors with the number of followers on both Instagram and X. A linear mixed model was used to evaluate the association of post content with the number of likes on Instagram with random intercept for the correlation of the repeated measures within the program. The linear mixed model also adjusted for the program size, city size, and type of program. False discovery rate was used for the adjustment of multiple comparisons and control for a possible false positive rate in the linear mixed model. All tests were two-sided and assessed for significance at the 5% level using SAS v9.4 (SAS Institute, Cary, NC). Of the ACGME accredited OBGYN residency programs, 88.5% (N = 262/296) programs were identified to have an Instagram account. Of the 34 that did not have an Instagram, 11 programs had just received their initial accreditation in 2021 and 7 were military programs. Fewer programs, 33.7% (N = 97/296), were found to have an X account. Notably, 28.8% (N = 28/97) X accounts and 1.5% (N = 4/262) of Instagram accounts were departmental and not specific to the OBGYN residency program. Most programs created an Instagram (60.3%, N = 158/262) or X (53.6%, N = 52/97) account in 2020. On Instagram, baseline characteristics were collected showing most programs had an average of 821.2 posts (Standard Deviation/SD = 370.5), were in large metropolitan areas (59.9%), classified themselves as academic programs (46.6%), and had a highlight reel (88.2%). Approximately 60% of programs had at least one post about diversity in any of their posts on Instagram. Most programs were run by residents (84.4%, N = 108/128). Of the 37% (N = 97) programs that responded, thirty-one percent of respondents identified their program as a different type from that listed in the FREIDA database . On Instagram, many factors were associated with increased number of followers . The number of followers increased with more residents, specifically 5.38 more followers per resident (Standard Error/SE = 1.64, p = 0.001). With one more month on Instagram, programs had 4.88 (SE = 1.34, p<0.001) more followers. Programs that followed more individuals had more followers (β estimate = 0.53, SE = 0.06, p<0.001). More posts were associated with more followers (β = 1.00, SE = 0.17, p<0.001). The frequency of posts, or number of posts per month, was not associated with increased followers (p = 0.721). More followers were observed in academic than community (β = 109.2, SE = 39.22, p = 0.006) or combined programs (β = 125.87, SE = 33.63, p = 0.001). The programs in the top quartile (or top 25%) on Doximity had more followers than those in the lower rankings (p = 0.001). The programs with a highlight reel (β = 146.46, SE = 36.56, p<0.001) or diversity post (β = 87.30, SE = 27.85, p = 0.002) had more followers. On X, the average number of followers was 467.0 (+/- 549.3) and duration on the platform was 34.1 months (+/- 33.6). Most programs were in large metropolitan areas (65.0%) and classified themselves as academic programs (67.0%) . The number of followers was significantly associated with duration in months on X since the first post, number following, and Doximity ranking . On average, programs had 5.31 more followers per month on X (SE = 0.99, p<0.001). As programs followed other social media users on X, they gained more followers (β = 1.55, SE = 0.18, p<0.001). The program in the top quartile on Doximity ranking had more followers than those in the lowest 50% of rankings (p = 0.029). An analysis of 900 posts from the top thirty most followed programs on Instagram demonstrated most of the content was biographical (18%) or social in nature (18%) (Figs and ). The least posted content overall was surgical (3%), research (3%), and advocacy (3%). In the top thirty programs, social content (97%) followed by information (90%) and class (90%) were posted at least once in their last thirty posts while surgical was the least common with only 37% of programs having a post related to surgery. Highlight reels for the top thirty programs were evaluated (Figs and ). One program had no highlight reels. Most of the content was information (17%) or related to DITL (15%). The least posted content overall was research (3%), Q&A (5%), and location (5%). Of the top thirty programs, informational content (70%) followed by DITL (60%) and social (53%) were the most common content posted by programs by having at least one highlight regarding this content while research, and rotations were least common with only 23% of programs having a highlight reel dedicated to these. Type of Instagram post content was significantly associated with the number of likes after controlling for other characteristics such as program size, program type, and city size (p<0.001) . Next, content was compared to one another to identify superiority after the false discovery rate adjustment for multiple comparisons between content. Advocacy posts had more likes than informational posts (p = 0.007). More likes were observed for awards/Match posts than advocacy, biography, class, diversity, informational, surgical, others, research, social, wellness, and educational (p<0.001). Biography posts had more likes than informational but less than class, and social posts (p≤0.007). More likes were detected for class posts than diversity, informational, research, and educational (p≤0.008). Social posts had more likes than diversity or educational posts (p<0.005). Less likes were seen for informational post than surgical, others, social, and wellness (p≤0.004) . Overall, posts about awards and/or Match received the most likes while informational received the least . Our study shows that most OBGYN residency programs (88.5%) have adopted Instagram while only 33.7% of programs adopted X. Most of these programs adopted social media during the COVID pandemic in 2020 as previously demonstrated . Instagram as a social platform may also be more popular amongst many residency specialties given increased usage of Instagram by applicants as seen in other specialties and the ability to more easily engage with photo and video content . This is the first study to establish that the number of followers, or popularity, on Instagram is positively correlated with larger residency program size and academic program type. Yadav et al is the only other published OBGYN study to evaluate popularity on Instagram and calculated Doximity ranking in relation to number of posts, followers, and likes on a program’s last three posts . Similar to our study, Doximity ranking of OBGYN programs was associated with a higher number of followers. However, Yadav et al did not evaluate content or followers in relation to other program traits . Our study sought to further explore modifiable social media factors that can be implemented by programs to attempt to increase followers as previously mentioned factors are likely related to reputation and accessibility to a greater population of users. Modifiable factors that are positively correlated with followers include number of posts for Instagram, following more accounts, and time on each platform, which is consistent with orthopedic and plastic surgery literature . Surprisingly, increased frequency of Instagram posts was not associated with more followers as expected given suspected mutual engagement. This is similar to plastic surgery literature showing only a weak correlation between number of posts and engagement . Likely, there is an optimal post frequency as seen in prior social media data . Further studies are needed to see if this changes over time. Lastly, biographical and social were the two most posted content types, also consistent with plastic surgery and orthopedic literature . Additionally, awards and/or the Match followed by social, class, and surgical were the most engaged content. Although not all categories were the same, our results are consistent with plastic surgery literature with social posts and accolades (like awards/match) being of high importance . The emphasis on social content may be a consequence of prohibited in-person interaction because of the COVID pandemic and may allow applicants to determine program ‘fit’. It is important to also highlight the least popular or engaged content includes advocacy, research, diversity, and wellness (Figs , and ). These items typically showcase unique program aspects that may distinguish programs from one another for applicants, but, unfortunately, are the least emphasized. Diversity, equity, and inclusion (DEI) has become integral in promoting and celebrating an environment of diversity for residents, faculty, staff, and patients which is promoted by ACOG DEI Excellence Workgroup . Despite this, 40% of all OBGYN programs did not have one Instagram post about diversity. This finding may reflect resident run accounts emphasizing a social atmosphere rather than the structured content one may expect from a content manager or faculty. In plastic surgery literature, it was shown that posts with a greater average Fitzpatrick skin type had a greater number of likes, the opposite of our study . However, as the authors point out, this is a subjective measure and did not evaluate diversity in its entirety. Our study sought to identify posts including many forms of diversity. Additionally, plastic surgery literature is congruent in our results showing wellness is in the minority posted, despite the recent emphasis on combating burnout in medicine . Ultimately, programs should consider including content that represents their program’s unique aspects and core values. Post accuracy also should be of great importance to programs. A negative impact on applicant’s perception of a residency program in both orthopedic and plastic surgery literature has been secondary to a program’s social media . Specifically, 11% of plastic surgery applicants never trusted a program’s social media information or posts . In our study, 31% of social media accounts reported a different program type than that listed on FREIDA. This either reflects an inaccuracy in the FREIDA database or those who post the content, 90% of which were resident run, among programs who responded. While this may reflect a poorly updated FREIDA database, it is important to ensure that there is accuracy in what is being posted online, especially if programs are placing this burden on residents. Unfortunately, social media training is variable and professional guidelines are lacking . The American College of Surgeons released a social media statement including a review of 7 national and international organizations, most notably American Medical Association (AMA) and ACOG, which highlights professional web page content and appropriate communication between physicians, patients, and colleagues on social media but not in regards to residency recruitment . Neither AMA nor National Resident Matching Program (NRMP) have defined appropriate social media interactions between applicants and programs. Despite this, social media has been used to vet residency applicants. In one study on focused on general surgery, 18% of program directors reported screening applicants through social media. Furthermore, 11% of program directors lowered or removed an applicant from their rank list due to unprofessional content . In another study, at least 15% of plastic surgery applicant respondents were concerned that engaging with a program’s social media would attract attention to their own . Overt bias and judgement related to social media content posted by trainees personal accounts can even be found in recent academic literature . A council of residency directors in Emergency Medicine was the first and only specialty to create social media guidelines in 2014 . These guidelines recommend content should be designated to a content manager, not a trainee, to ensure professional communications and accurate content as violations can interfere with privacy, patient confidentiality, and impartial recruitment, and to employ a uniform policy to screen applicants, if performed, to decrease bias . Program directors should heavily consider whether screening applicants’ social media is beneficial to recruitment and if residents should bear the responsibility of posting social media content . The authors believe all specialties should consider adopting social media guidelines. Our study is the first OBGYN study to evaluate residency posted content in relation to likes to assess what content is the most engaged instead of content to solely followers. It also uniquely examines highlight reels and diversity posts, both of which were associated with more followers. Our study has limitations. First, there was no way to distinguish a follower’s background or which users were liking content. Thus, our findings, while reflective of general popularity and engagement, do not necessarily reflect residency applicants’ interactions with social media. Further, some applicants may be afraid of having their own accounts discovered and change their social media profiles during recruitment season . Second, we were only able to ascertain who runs half of the total social media accounts identified either by direct message or as identified in their profile (N = 128/262). Therefore, although a majority were identified as resident run, this may not reflect all OBGYN accounts. Understanding what social media content attracts more followers and increases engagement is crucial as resident recruitment may be impacted by content posted by OBGYN programs. Programs should consider following more profiles and posting social and awards and/or the Match content as this may increase followers and engagement. Our findings highlight the need for social media content that accurately reflects residency and departmental mission statements, is pertinent to what applicants are seeking from a program and maintains professionalism. Ultimately, national bodies and residency programs should consider establishing professional social media guidelines for the protection of both residents and applicants. S1 Fig Definitions of post content. (DOCX) S2 Fig Definitions of highlight reel content. (DOCX) S1 Table Factors associated with likes on Instagram. Factors including program size, city size, program type, and content were evaluated to identify any association of likes for posts on Instagram. A multilinear regression model was used to calculate the beta estimate, or difference in likes per factor. (DOCX) S2 Table Content linear mixed model. False discovery rate (FDR) model showing multivariate comparisons between content with only significant associations included in the following table. (DOCX) S1 Data (XLSX) |
Connected device and therapeutic patient education to promote physical activity among women with localised breast cancer (DISCO trial): protocol for a multicentre 2×2 factorial randomised controlled trial | 400fae65-433a-43a1-bfa7-a3cfeb8bd62d | 8438826 | Patient Education as Topic[mh] | Breast cancer is the leading cause of cancer in women worldwide with 1.6 million new cases diagnosed each year, representing more than one-third of all new cancer cases in women. In France, breast cancer also represents the leading cause of cancer incidence and mortality among women, with approximately 58 000 new cases and 12 000 breast cancer deaths estimated in 2018. Despite a very good prognosis worldwide with overall survival of 85% at 5 years (87% in France) and 71% at 10 years (78% in France) for all stages combined, a large number of patients with breast cancer experience adverse effects of cancer and its treatments such as fatigue, impaired quality of life, anxiety or weight gain. In women with breast cancer, deteriorations of physical activity level and cardiorespiratory fitness are frequent. Physical activity is defined as any bodily movement produced by skeletal muscles that requires energy expenditure, including any daily life activity of household, occupation, recreation (eg, sports) or transportation. Exercise is a subset of physical activity that is planned, structured and repetitive, in the purpose of improving or maintaining physical fitness. After a breast cancer diagnosis, lack of physical activity, obesity and weight gain have been shown to increase the risk of cancer-related comorbidities and treatment adverse effects, to worsen long-term health and to cause poor prognosis. The benefits of physical activity have been well recognised in primary cancer prevention. Numerous studies have shown the safety and benefits of physical activity performed concomitantly with breast cancer treatments. These benefits include reduced fatigue and comorbidities, improved quality of life and physical functioning, as well as possibly reduced risk of recurrence and improved overall and specific survival with a positive dose–response relationship. Despite these benefits and international evidence-based guidelines of physical activity prescription for clinicians and their patients, accessibility to exercise programmes and implementing the guidelines in the cancer care process remain a challenge for patients and healthcare providers. While a growing number of facilities offer exercise programmes to patients with cancer, distance from home constitutes a barrier to regular exercise during cancer treatments. Successful exercise strategies during and beyond cancer treatment remain to be determined in clinical trials. The recent development of connected devices such as activity trackers offers a real opportunity in oncology to promote and monitor patients’ physical activity. While adherence to lifestyle interventions is a major challenge, connected activity trackers and smartphone applications enable structured monitoring of health parameters and provide feedback to patients. A systematic review of randomised controlled trials of physical activity interventions using new technologies such as activity trackers in patients with cancer (including five studies in breast cancer) has shown that patients significantly increased their number of steps per day in the majority of the studies. Recent reviews of intervention studies conducted among patients with breast cancer have also shown that patients increased their physical activity when they used activity trackers. Overall, connected activity trackers receive increasing interest for being systematically integrated into clinical oncology practice. Yet, more research is needed, especially clinical trials, to demonstrate the effectiveness of these tools and to respond to the preferences of patients with breast cancer. Therapeutic patient education has emerged in the 1990s in response to the recognition of the need to support patients in the self-management of their chronic diseases, such as diabetes and asthma. According to WHO, therapeutic patient education aims to ‘help patients acquire or maintain the skills they need to best manage their lives with a chronic disease’. In the cancer field, several cancer-specific programmes of therapeutic patient education have been set up to manage pain, fatigue, side effects of treatment (chemotherapy, surgery) or compliance to treatment. By enhancing relevant knowledge and skills, therapeutic patient education may greatly contribute to increasing patients’ autonomy in their disease management. Despite the performance in modifying long-term individual behaviours and adherence to cancer treatments, the benefits of therapeutic patient education on physical activity levels in patients with cancer early after diagnosis has been poorly investigated. The research on therapeutic patient education in the breast cancer and exercise context is limited to date and warrants further research. Several biological mechanisms have been proposed to explain the effects of physical activity on breast cancer risk and outcome. Preclinical and human studies have shown the influence of physical activity on several signalling pathways involved in tumour development, growth and progression, including the insulin signalling pathway (IGF-1, insulin), chronic inflammation (involving inflammatory cytokines such as interleukin 6 (IL-6), tumour necrosis factor alpha (TNFα), c-reactive protein (CRP)) and endocrine hormone regulation (oestrogens, adipokines). By affecting the endogenous systemic milieu, physical activity is believed to influence cellular processes and tumour growth, and therefore reduce the risk of recurrence, increase treatment efficacy and improve survival. Also, because vitamin D alters mechanisms implicated in cellular growth and proliferation, accumulating evidence suggests that normal-to-high ranges of serum vitamin D levels improve breast cancer prognosis and outcome. Based on the data in the literature, it is not possible to conclude a causal relationship between the metabolic effects of physical activity and the impact on breast cancer risk and survival. Biological effects of physical activity on these biomarkers of endogenous mechanisms interfering in cancer suppression or proliferation remain to be elucidated in order to better understand the benefit of physical activity during adjuvant treatment. In this context, given the accumulating evidence for the benefits and safety of regular exercise during treatments of localised breast cancer, it is necessary to systematically encourage patients to remain or become physically active from the time of diagnosis and to implement and assess the most appropriate strategies of physical activity in clinical practice. The aim of the ‘dispositif connecté', that is, connected device in English (DISCO) trial is to encourage engagement in exercise during breast cancer treatment through two innovative types of interventions, that is, to say a web-based connected device and therapeutic patient education, which aim to develop patients’ autonomy in their practice of physical activity. The primary objective of the DISCO trial is to evaluate the efficacy of two interventions, either single or combined, concomitant to adjuvant treatments, on the physical activity level of patients with breast cancer at the end of the 6-month interventions, compared with usual care: one is an exercise programme using a connected device (comprising an activity tracker linked to a smartphone application and a website and providing an individualised, semisupervised, technology-based exercise programme) and the other is a therapeutic patient education intervention. The research hypothesis is that patients participating in the 6-month exercise programme using the connected device or therapeutic education intervention are more likely to achieve the international physical activity recommendations, compared with women receiving physical activity recommendations only (usual care). The WHO recommendations to maintain or improve health, which applied when the study protocol was developed, are to do at least 150 min of moderate-intensity or 75 min of vigorous-intensity aerobic physical activity or an equivalent combination each week, and muscle-strengthening activities at least 2 days a week. Secondary objectives are: (1) to evaluate the adherence to the interventions; the impact of the interventions on physical fitness, physical activity profile, anthropometrics, quality of life, fatigue, biological parameters, occupational status and lifestyle factors; the efficacy of the 6-month interventions on physical activity level at 12 months; the representations and acceptability of activity tracker and therapeutic patient education and (2) to assess the cost-effectiveness of the interventions. If one of the interventions is individually effective, the efficacy of the combination of both interventions at 6 and 12 months will be evaluated.
Trial design The DISCO trial is a 2×2 prospective, multicentre, factorial, randomised, controlled and open-label study (phase III), conducted by the Léon Bérard comprehensive cancer centre (Lyon, France) among women receiving treatment for localised breast cancer. The clinical protocol was designed and written according to the Standard Protocol Items: Recommendations for Interventional Trials guidelines (see ). The flow chart of the study is presented in . Patients will be randomly assigned to one of the four arms of the study according to the 2×2 factorial design (1:1:1:1 ratio). They will all receive international recommendations on physical activity, and: (1) women allocated to the ‘connected device’ arm will benefit from a 6-month individualised, semisupervised exercise programme carried out autonomously. The programme consists of an evolving goal of daily numbers of steps using an activity tracker and two sessions of brisk walking and one session of muscle strengthening per week, using dedicated smartphone application and website; (2) women allocated to the ‘therapeutic patient education’ arm will benefit from four therapeutic education sessions on exercise; (3) women allocated to the ‘combined’ arm will benefit from both interventions in parallel and (4) women allocated to the ‘control’ arm will receive usual care. 10.1136/bmjopen-2020-045448.supp1 Supplementary data Eligibility criteria for participants Inclusion criteria include: being a female 18–75 years old; diagnosed with a first primary non-metastatic invasive breast carcinoma histologically confirmed; treated with curative surgery and requiring adjuvant treatment (chemotherapy, hormonotherapy and/or radiotherapy) that present at one of the investigating centres; providing a medical certificate of no contraindication to exercise; being available and willing to participate in the study for the duration of the interventions and follow-up; using a personal smartphone compatible with an application used for the intervention (iOS operating system from V.9.3, Android operating system from V.5.0, no Microsoft operating system) and having a computer with internet access; being able to understand, read and write French; and being affiliated with a social security scheme. Non-inclusion criteria include: recurrent, metastatic or inflammatory breast cancer; personal history or coexistence of other primary cancer (except for in situ cancer regardless of the site, basal cell skin cancer and non-mammary cancer in complete remission for more than 5 years); presenting a contraindication to exercise according to the investigator (such as cardiorespiratory or bone pathologies, non-stabilised chronic diseases such as diabetes, malnutrition, etc); presenting severe malnutrition according to the criteria of the French National Health Authority (ie, for women≤70 years: weight loss ≥15% in 6 months or ≥10% in 1 month; for women >70 years: weight loss ≥15% in 6 months or ≥10% in 1 month and body mass index (BMI) <18 kg/m²) ; being unable to be followed for medical, social, family, geographical or psychological reasons for the duration of the study; pregnant or breast feeding or of childbearing age without effective contraception for the duration of the study. Recruitment Recruitment started in May 2018. Participants will be recruited at several national comprehensive cancer centres, clinics or hospitals located in France, which will ensure adequate participant enrolment to reach the target sample size in a timely manner. Inclusion of patients will be carried out after surgery and confirmation of the indication of adjuvant treatment. The study will be proposed to patients at the postoperative, prechemotherapy or preradiotherapy consultation (by the surgeon, oncologist or radiotherapist investigator, respectively) depending on the patient’s treatment plan. At this visit, the investigator will check all eligibility criteria and propose to the eligible patients to participate in the study, explain the objectives and study process and give them an information notice. After sufficient time for reflection, eligible patients who agree to participate will date and sign an informed consent (see ) and will be included prior to the onset of adjuvant therapy (or within 1 month thereafter). The number of eligible patients refusing to participate in the study and the reason for non-participation will be recorded. 10.1136/bmjopen-2020-045448.supp2 Supplementary data Randomisation Prior to randomisation, participants will be asked to complete the Recent Physical Activity Questionnaire (RPAQ) to assess their level of physical activity. Their weight, body size and prescribed adjuvant treatments will be collected from the patient’s medical record. Participants will be randomised using EnnovClinical software (V.7.5.710.4, Ennov, Paris, France) into one of the four arms of the trial, by using the following minimisation criteria : BMI (<25 kg/m², ≥25 and<30 kg/m², ≥30 kg/m²), baseline physical activity level from RPAQ (<150 min/week, ≥150 min/week of moderate-to-vigorous physical activity) and prescribed adjuvant treatments at inclusion (ie, chemotherapy+hormone therapy±radiotherapy, hormone therapy±radiotherapy, chemotherapy±radiotherapy, radiotherapy only).
The DISCO trial is a 2×2 prospective, multicentre, factorial, randomised, controlled and open-label study (phase III), conducted by the Léon Bérard comprehensive cancer centre (Lyon, France) among women receiving treatment for localised breast cancer. The clinical protocol was designed and written according to the Standard Protocol Items: Recommendations for Interventional Trials guidelines (see ). The flow chart of the study is presented in . Patients will be randomly assigned to one of the four arms of the study according to the 2×2 factorial design (1:1:1:1 ratio). They will all receive international recommendations on physical activity, and: (1) women allocated to the ‘connected device’ arm will benefit from a 6-month individualised, semisupervised exercise programme carried out autonomously. The programme consists of an evolving goal of daily numbers of steps using an activity tracker and two sessions of brisk walking and one session of muscle strengthening per week, using dedicated smartphone application and website; (2) women allocated to the ‘therapeutic patient education’ arm will benefit from four therapeutic education sessions on exercise; (3) women allocated to the ‘combined’ arm will benefit from both interventions in parallel and (4) women allocated to the ‘control’ arm will receive usual care. 10.1136/bmjopen-2020-045448.supp1 Supplementary data
Inclusion criteria include: being a female 18–75 years old; diagnosed with a first primary non-metastatic invasive breast carcinoma histologically confirmed; treated with curative surgery and requiring adjuvant treatment (chemotherapy, hormonotherapy and/or radiotherapy) that present at one of the investigating centres; providing a medical certificate of no contraindication to exercise; being available and willing to participate in the study for the duration of the interventions and follow-up; using a personal smartphone compatible with an application used for the intervention (iOS operating system from V.9.3, Android operating system from V.5.0, no Microsoft operating system) and having a computer with internet access; being able to understand, read and write French; and being affiliated with a social security scheme. Non-inclusion criteria include: recurrent, metastatic or inflammatory breast cancer; personal history or coexistence of other primary cancer (except for in situ cancer regardless of the site, basal cell skin cancer and non-mammary cancer in complete remission for more than 5 years); presenting a contraindication to exercise according to the investigator (such as cardiorespiratory or bone pathologies, non-stabilised chronic diseases such as diabetes, malnutrition, etc); presenting severe malnutrition according to the criteria of the French National Health Authority (ie, for women≤70 years: weight loss ≥15% in 6 months or ≥10% in 1 month; for women >70 years: weight loss ≥15% in 6 months or ≥10% in 1 month and body mass index (BMI) <18 kg/m²) ; being unable to be followed for medical, social, family, geographical or psychological reasons for the duration of the study; pregnant or breast feeding or of childbearing age without effective contraception for the duration of the study.
Recruitment started in May 2018. Participants will be recruited at several national comprehensive cancer centres, clinics or hospitals located in France, which will ensure adequate participant enrolment to reach the target sample size in a timely manner. Inclusion of patients will be carried out after surgery and confirmation of the indication of adjuvant treatment. The study will be proposed to patients at the postoperative, prechemotherapy or preradiotherapy consultation (by the surgeon, oncologist or radiotherapist investigator, respectively) depending on the patient’s treatment plan. At this visit, the investigator will check all eligibility criteria and propose to the eligible patients to participate in the study, explain the objectives and study process and give them an information notice. After sufficient time for reflection, eligible patients who agree to participate will date and sign an informed consent (see ) and will be included prior to the onset of adjuvant therapy (or within 1 month thereafter). The number of eligible patients refusing to participate in the study and the reason for non-participation will be recorded. 10.1136/bmjopen-2020-045448.supp2 Supplementary data
Prior to randomisation, participants will be asked to complete the Recent Physical Activity Questionnaire (RPAQ) to assess their level of physical activity. Their weight, body size and prescribed adjuvant treatments will be collected from the patient’s medical record. Participants will be randomised using EnnovClinical software (V.7.5.710.4, Ennov, Paris, France) into one of the four arms of the trial, by using the following minimisation criteria : BMI (<25 kg/m², ≥25 and<30 kg/m², ≥30 kg/m²), baseline physical activity level from RPAQ (<150 min/week, ≥150 min/week of moderate-to-vigorous physical activity) and prescribed adjuvant treatments at inclusion (ie, chemotherapy+hormone therapy±radiotherapy, hormone therapy±radiotherapy, chemotherapy±radiotherapy, radiotherapy only).
At baseline, all participants will receive the international recommendations in terms of physical activity for promoting health in the general population, which will be delivered orally by a certified exercise instructor with the help of a leaflet. Intervention with a connected device Participants randomised to the ‘connected device’ arm will benefit from a 6-month exercise programme. The connected device consists of an activity tracker (connected wristband, LS417-F model, CARE Fitness, Bobigny, France) that participants will wear daily, a dedicated smartphone application and a dedicated website proposing an individualised, semisupervised exercise programme adapted to patients with cancer (developed by BIOMOUV, Paris, France). This automated web-based and mobile-based exercise programme will aim to support participants to enhance physical activity in two ways: doing structured exercise sessions and increasing daily physical activity (number of steps). Exercise sessions will be automatically generated by an algorithm based on the patient profile (described below). The participants will receive notifications informing them of a new structured exercise session available on the website or mobile application or alerting them when a session was not carried out, and inviting them to execute it when possible. Participants will receive a free 6-month subscription to the programme. Setting up the connected device At the end of the baseline assessment, the certified exercise instructor will introduce the customised exercise programme to the participants and will give them the activity tracker and a user guide for the connected device. Then, the certified exercise instructor will explain the functioning of the activity tracker, the dedicated smartphone application and the dedicated website, as well as assist the participants to instal the application on their smartphone. The participants will be registered in the customised exercise programme by the certified exercise instructor. The registration will consist of completing a web-based questionnaire about personal and health data to determine the participant profile (age, weight, height, level of aerobic and muscular strength, treatment, symptoms, availabilities for exercise sessions and sports materials). Baseline level of aerobic and muscular strength for the individualised exercise programme The physical fitness tests performed at baseline will be used to classify the participants at the start of the exercise programme according to their aerobic level (for the walking sessions) and their muscular strength level (for the strengthening sessions). The aerobic level categories will be determined by the distance performed during the 6 min walk test (6MWT): aerobic group 1 (<460 m), aerobic group 2 (460–580 m) and aerobic group 3 (>580 m). The muscular strength level categories will be determined by the number of sit-ups performed on a chair in 30 s during the Sit-to-stand test: muscular strength group 1 (≤10 repetitions), muscular strength group 2 (11–14 repetitions) and muscular strength group 3 (≥15 repetitions). Thresholds were based on average values reached by women receiving breast cancer treatments for the 6MWT (pooled mean value, 523 m) and the Sit-to-stand test (pooled mean value, 13 repetitions) from a previous study; these values were checked for consistency with percentile scores obtained at the 6MWT and Sit-to-stand test in community-dwelling older women, then the IQR was used to determine the thresholds for the three groups of this study. The level categories assigned will be entered by the exercise instructor in the baseline patient profile and will be used by the automated algorithm to set up the level of the first walking and muscle strengthening sessions. Exercise programme The 6-month exercise programme will be semisupervised by the certified exercise instructor through an individual follow-up of participants (see ‘Participant follow-up’ part and ‘Continuous monitoring’ part). It will be carried out autonomously by the participants at home by using the smartphone application and the website. The programme is based on three structured unsupervised sessions per week alternating two types of exercise: two walking sessions (by following oral instructions given via the smartphone application) and one muscle strengthening session (by using videos accessible on the website). The levels of the first walking and muscle strengthening sessions will be determined by the fitness tests performed at baseline (see ‘Baseline level’ part). Then, subsequent sessions will be planned according to the available days of the participant. Strengthening exercises will be adapted according to sports materials available at their home (eg, Swiss ball, sports mat, stick, weight, etc). Each session will include: (1) a warm-up period of 5 min; (2) a body session of 10–35 min of strengthening exercises or 10–50 min of walking (mixing continuous and/or intermittent effort); (3) a 5 min recovery period, consisting of stretching and relaxation during strengthening sessions or a cool down during walking sessions. Sessions will be of moderate-to-high intensity (≥3 and ≤9 METs). The three structured unsupervised exercise sessions per week are configured by a unique algorithm hosted by an accredited personal healthcare data host (Orange Business Services, Paris, France), to plan the exercise sessions and determine the exercise level in an adapted and progressive manner by increasing the duration and then intensity in accordance with principles of exercise training and progression. At the beginning of each session, the duration and intensity of the session will be determined according to the perceived difficulties (evaluated by a Borg scale) and emotional state (recorded by an emoji) of the participant in the previous session, and will be modified or postponed according to the level of fatigue (evaluated by a Borg scale), the level of dyspnoea (evaluated by a Borg scale), the presence or absence of unusual muscle pain and the presence or absence of unusual nausea/diarrhoea. In case of a severe adverse event related to disease or treatment (ie, joint disability, osteoarthritis, cachexia, hand-foot syndrome, aplasia, diuretic, axillary node dissection, pace-maker, chemotherapy, targeted therapy, hormone therapy, radiotherapy, chronic obstructive pulmonary disease (COPD), diabetes) or temporary contraindication to exercise, declared by the participant on her device, the programme and sessions will be adapted or suspended until the participant’s health improves. In addition, participants will have the opportunity to perform additional exercise sessions according to their preferences and lifestyle, outside the programme. Participants will be asked to record these sessions through the smartphone application or the website: type of activity (eg, walking, hiking, cycling) from a list adapted from Ainsworth’s Compendium, and its duration and intensity. Number of daily steps Participants will be advised to wear the activity tracker daily and to launch the application regularly (preferably daily), which will automatically synchronise with the activity tracker via Bluetooth connection and will collect the number of steps. The target number of steps will be 3000 steps per day at the programme onset, and then will be re-set based on the average number of daily steps during the first week after inclusion. The target number of daily steps will evolve automatically every 3 weeks based on the average number of daily steps achieved during the previous 3 weeks, and will be updated automatically in the application. Consistent with principles of exercise training and progression, after each 3-week cycle, if the goal of steps per day is reached by the participant, the target goal will increase by 15% during the following 3-week cycle, within a maximum target of 10 000 daily steps. If the average number of daily steps does not meet the goal, the target will remain unchanged in the next cycle. Participant follow-up Telephone follow-ups will be carried out by the certified exercise instructor at 10 days, 2 months and 4 months after the intervention onset to ensure the proper functioning of the connected device, review the use of the connected device, review the conduct of the sessions and answer the participants’ questions if they may have. Participants will be orally encouraged to remain physically active on a daily basis (reminder of the benefits and recommendations of physical activity, success and satisfaction during the exercise sessions). During the 6-month intervention, the participants will have the opportunity to contact the certified exercise instructor or the clinical research assistant at any time, by email (directly through the website) or by telephone for any question or assistance with the connected device. Continuous monitoring The certified exercise instructor will monitor the use of the connected device by the participants and their progress in the programme through a dedicated professional website that provides real-time access to the participants’ data. On this website, an automatically generated daily event table will inform the certified exercise instructor of the occurrence of disabilities reported by the participants that may lead to modifying their programme (eg, severe fatigue, dyspnoea, unusual muscle pain) or if participants have not performed their planned sessions or used their activity tracker for seven consecutive days. On these alerts, the certified exercise instructor will contact the participants to precisely analyse the reported disabilities, advise participants, identify the causes of non-use of the connected device, solve possible technical problems or reinforce participant’s motivation if necessary. End of the intervention At the end of the 6-month programme, participants will keep their activity tracker to be encouraged to continue regularly exercising in autonomy. On their request, continued subscription to the dedicated application and website will be offered for another 6 months, with no individual follow-up anymore. Intervention of therapeutic patient education Participants randomised to the therapeutic patient education arm will benefit from a therapeutic patient education intervention, in addition to receiving the international physical activity recommendations. The intervention is part of the therapeutic patient education programme set up at the Léon Bérard cancer centre and validated by the Regional Health Agency (‘Agence Régionale de Santé Rhône-Alpes’). It will be disseminated in the investigating centres according to the criteria of the Regional Health Agency. The therapeutic patient education intervention consists of four sessions that will be scheduled according to participants’ availability during their follow-up visits as part of their usual clinical management over a 6-month period. First, participants will be invited to an initial 1-hour individual face-to-face session of educational diagnosis with a health professional trained in therapeutic patient education. This session will assess their needs and establish a contract of objectives to reach. Then, participants will be invited to participate in two collective educational sessions (1h30 each with a group of 10 patients maximum per session). These sessions will be composed of theoretical and practical workshops to help them understand their physical activity in their daily life and implement the necessary means to practice regular exercise in autonomy. Finally, participants will be invited to another 1-hour individual session, where an educational evaluation will be conducted to identify whether they achieve their individual objectives set at the time of the educational diagnosis. Combined interventions Participants randomised to the ‘combined intervention’ arm will benefit from a combination of the connected device intervention and the therapeutic patient education intervention in parallel for 6 months.
Participants randomised to the ‘connected device’ arm will benefit from a 6-month exercise programme. The connected device consists of an activity tracker (connected wristband, LS417-F model, CARE Fitness, Bobigny, France) that participants will wear daily, a dedicated smartphone application and a dedicated website proposing an individualised, semisupervised exercise programme adapted to patients with cancer (developed by BIOMOUV, Paris, France). This automated web-based and mobile-based exercise programme will aim to support participants to enhance physical activity in two ways: doing structured exercise sessions and increasing daily physical activity (number of steps). Exercise sessions will be automatically generated by an algorithm based on the patient profile (described below). The participants will receive notifications informing them of a new structured exercise session available on the website or mobile application or alerting them when a session was not carried out, and inviting them to execute it when possible. Participants will receive a free 6-month subscription to the programme. Setting up the connected device At the end of the baseline assessment, the certified exercise instructor will introduce the customised exercise programme to the participants and will give them the activity tracker and a user guide for the connected device. Then, the certified exercise instructor will explain the functioning of the activity tracker, the dedicated smartphone application and the dedicated website, as well as assist the participants to instal the application on their smartphone. The participants will be registered in the customised exercise programme by the certified exercise instructor. The registration will consist of completing a web-based questionnaire about personal and health data to determine the participant profile (age, weight, height, level of aerobic and muscular strength, treatment, symptoms, availabilities for exercise sessions and sports materials). Baseline level of aerobic and muscular strength for the individualised exercise programme The physical fitness tests performed at baseline will be used to classify the participants at the start of the exercise programme according to their aerobic level (for the walking sessions) and their muscular strength level (for the strengthening sessions). The aerobic level categories will be determined by the distance performed during the 6 min walk test (6MWT): aerobic group 1 (<460 m), aerobic group 2 (460–580 m) and aerobic group 3 (>580 m). The muscular strength level categories will be determined by the number of sit-ups performed on a chair in 30 s during the Sit-to-stand test: muscular strength group 1 (≤10 repetitions), muscular strength group 2 (11–14 repetitions) and muscular strength group 3 (≥15 repetitions). Thresholds were based on average values reached by women receiving breast cancer treatments for the 6MWT (pooled mean value, 523 m) and the Sit-to-stand test (pooled mean value, 13 repetitions) from a previous study; these values were checked for consistency with percentile scores obtained at the 6MWT and Sit-to-stand test in community-dwelling older women, then the IQR was used to determine the thresholds for the three groups of this study. The level categories assigned will be entered by the exercise instructor in the baseline patient profile and will be used by the automated algorithm to set up the level of the first walking and muscle strengthening sessions. Exercise programme The 6-month exercise programme will be semisupervised by the certified exercise instructor through an individual follow-up of participants (see ‘Participant follow-up’ part and ‘Continuous monitoring’ part). It will be carried out autonomously by the participants at home by using the smartphone application and the website. The programme is based on three structured unsupervised sessions per week alternating two types of exercise: two walking sessions (by following oral instructions given via the smartphone application) and one muscle strengthening session (by using videos accessible on the website). The levels of the first walking and muscle strengthening sessions will be determined by the fitness tests performed at baseline (see ‘Baseline level’ part). Then, subsequent sessions will be planned according to the available days of the participant. Strengthening exercises will be adapted according to sports materials available at their home (eg, Swiss ball, sports mat, stick, weight, etc). Each session will include: (1) a warm-up period of 5 min; (2) a body session of 10–35 min of strengthening exercises or 10–50 min of walking (mixing continuous and/or intermittent effort); (3) a 5 min recovery period, consisting of stretching and relaxation during strengthening sessions or a cool down during walking sessions. Sessions will be of moderate-to-high intensity (≥3 and ≤9 METs). The three structured unsupervised exercise sessions per week are configured by a unique algorithm hosted by an accredited personal healthcare data host (Orange Business Services, Paris, France), to plan the exercise sessions and determine the exercise level in an adapted and progressive manner by increasing the duration and then intensity in accordance with principles of exercise training and progression. At the beginning of each session, the duration and intensity of the session will be determined according to the perceived difficulties (evaluated by a Borg scale) and emotional state (recorded by an emoji) of the participant in the previous session, and will be modified or postponed according to the level of fatigue (evaluated by a Borg scale), the level of dyspnoea (evaluated by a Borg scale), the presence or absence of unusual muscle pain and the presence or absence of unusual nausea/diarrhoea. In case of a severe adverse event related to disease or treatment (ie, joint disability, osteoarthritis, cachexia, hand-foot syndrome, aplasia, diuretic, axillary node dissection, pace-maker, chemotherapy, targeted therapy, hormone therapy, radiotherapy, chronic obstructive pulmonary disease (COPD), diabetes) or temporary contraindication to exercise, declared by the participant on her device, the programme and sessions will be adapted or suspended until the participant’s health improves. In addition, participants will have the opportunity to perform additional exercise sessions according to their preferences and lifestyle, outside the programme. Participants will be asked to record these sessions through the smartphone application or the website: type of activity (eg, walking, hiking, cycling) from a list adapted from Ainsworth’s Compendium, and its duration and intensity. Number of daily steps Participants will be advised to wear the activity tracker daily and to launch the application regularly (preferably daily), which will automatically synchronise with the activity tracker via Bluetooth connection and will collect the number of steps. The target number of steps will be 3000 steps per day at the programme onset, and then will be re-set based on the average number of daily steps during the first week after inclusion. The target number of daily steps will evolve automatically every 3 weeks based on the average number of daily steps achieved during the previous 3 weeks, and will be updated automatically in the application. Consistent with principles of exercise training and progression, after each 3-week cycle, if the goal of steps per day is reached by the participant, the target goal will increase by 15% during the following 3-week cycle, within a maximum target of 10 000 daily steps. If the average number of daily steps does not meet the goal, the target will remain unchanged in the next cycle. Participant follow-up Telephone follow-ups will be carried out by the certified exercise instructor at 10 days, 2 months and 4 months after the intervention onset to ensure the proper functioning of the connected device, review the use of the connected device, review the conduct of the sessions and answer the participants’ questions if they may have. Participants will be orally encouraged to remain physically active on a daily basis (reminder of the benefits and recommendations of physical activity, success and satisfaction during the exercise sessions). During the 6-month intervention, the participants will have the opportunity to contact the certified exercise instructor or the clinical research assistant at any time, by email (directly through the website) or by telephone for any question or assistance with the connected device. Continuous monitoring The certified exercise instructor will monitor the use of the connected device by the participants and their progress in the programme through a dedicated professional website that provides real-time access to the participants’ data. On this website, an automatically generated daily event table will inform the certified exercise instructor of the occurrence of disabilities reported by the participants that may lead to modifying their programme (eg, severe fatigue, dyspnoea, unusual muscle pain) or if participants have not performed their planned sessions or used their activity tracker for seven consecutive days. On these alerts, the certified exercise instructor will contact the participants to precisely analyse the reported disabilities, advise participants, identify the causes of non-use of the connected device, solve possible technical problems or reinforce participant’s motivation if necessary. End of the intervention At the end of the 6-month programme, participants will keep their activity tracker to be encouraged to continue regularly exercising in autonomy. On their request, continued subscription to the dedicated application and website will be offered for another 6 months, with no individual follow-up anymore.
At the end of the baseline assessment, the certified exercise instructor will introduce the customised exercise programme to the participants and will give them the activity tracker and a user guide for the connected device. Then, the certified exercise instructor will explain the functioning of the activity tracker, the dedicated smartphone application and the dedicated website, as well as assist the participants to instal the application on their smartphone. The participants will be registered in the customised exercise programme by the certified exercise instructor. The registration will consist of completing a web-based questionnaire about personal and health data to determine the participant profile (age, weight, height, level of aerobic and muscular strength, treatment, symptoms, availabilities for exercise sessions and sports materials).
The physical fitness tests performed at baseline will be used to classify the participants at the start of the exercise programme according to their aerobic level (for the walking sessions) and their muscular strength level (for the strengthening sessions). The aerobic level categories will be determined by the distance performed during the 6 min walk test (6MWT): aerobic group 1 (<460 m), aerobic group 2 (460–580 m) and aerobic group 3 (>580 m). The muscular strength level categories will be determined by the number of sit-ups performed on a chair in 30 s during the Sit-to-stand test: muscular strength group 1 (≤10 repetitions), muscular strength group 2 (11–14 repetitions) and muscular strength group 3 (≥15 repetitions). Thresholds were based on average values reached by women receiving breast cancer treatments for the 6MWT (pooled mean value, 523 m) and the Sit-to-stand test (pooled mean value, 13 repetitions) from a previous study; these values were checked for consistency with percentile scores obtained at the 6MWT and Sit-to-stand test in community-dwelling older women, then the IQR was used to determine the thresholds for the three groups of this study. The level categories assigned will be entered by the exercise instructor in the baseline patient profile and will be used by the automated algorithm to set up the level of the first walking and muscle strengthening sessions.
The 6-month exercise programme will be semisupervised by the certified exercise instructor through an individual follow-up of participants (see ‘Participant follow-up’ part and ‘Continuous monitoring’ part). It will be carried out autonomously by the participants at home by using the smartphone application and the website. The programme is based on three structured unsupervised sessions per week alternating two types of exercise: two walking sessions (by following oral instructions given via the smartphone application) and one muscle strengthening session (by using videos accessible on the website). The levels of the first walking and muscle strengthening sessions will be determined by the fitness tests performed at baseline (see ‘Baseline level’ part). Then, subsequent sessions will be planned according to the available days of the participant. Strengthening exercises will be adapted according to sports materials available at their home (eg, Swiss ball, sports mat, stick, weight, etc). Each session will include: (1) a warm-up period of 5 min; (2) a body session of 10–35 min of strengthening exercises or 10–50 min of walking (mixing continuous and/or intermittent effort); (3) a 5 min recovery period, consisting of stretching and relaxation during strengthening sessions or a cool down during walking sessions. Sessions will be of moderate-to-high intensity (≥3 and ≤9 METs). The three structured unsupervised exercise sessions per week are configured by a unique algorithm hosted by an accredited personal healthcare data host (Orange Business Services, Paris, France), to plan the exercise sessions and determine the exercise level in an adapted and progressive manner by increasing the duration and then intensity in accordance with principles of exercise training and progression. At the beginning of each session, the duration and intensity of the session will be determined according to the perceived difficulties (evaluated by a Borg scale) and emotional state (recorded by an emoji) of the participant in the previous session, and will be modified or postponed according to the level of fatigue (evaluated by a Borg scale), the level of dyspnoea (evaluated by a Borg scale), the presence or absence of unusual muscle pain and the presence or absence of unusual nausea/diarrhoea. In case of a severe adverse event related to disease or treatment (ie, joint disability, osteoarthritis, cachexia, hand-foot syndrome, aplasia, diuretic, axillary node dissection, pace-maker, chemotherapy, targeted therapy, hormone therapy, radiotherapy, chronic obstructive pulmonary disease (COPD), diabetes) or temporary contraindication to exercise, declared by the participant on her device, the programme and sessions will be adapted or suspended until the participant’s health improves. In addition, participants will have the opportunity to perform additional exercise sessions according to their preferences and lifestyle, outside the programme. Participants will be asked to record these sessions through the smartphone application or the website: type of activity (eg, walking, hiking, cycling) from a list adapted from Ainsworth’s Compendium, and its duration and intensity.
Participants will be advised to wear the activity tracker daily and to launch the application regularly (preferably daily), which will automatically synchronise with the activity tracker via Bluetooth connection and will collect the number of steps. The target number of steps will be 3000 steps per day at the programme onset, and then will be re-set based on the average number of daily steps during the first week after inclusion. The target number of daily steps will evolve automatically every 3 weeks based on the average number of daily steps achieved during the previous 3 weeks, and will be updated automatically in the application. Consistent with principles of exercise training and progression, after each 3-week cycle, if the goal of steps per day is reached by the participant, the target goal will increase by 15% during the following 3-week cycle, within a maximum target of 10 000 daily steps. If the average number of daily steps does not meet the goal, the target will remain unchanged in the next cycle.
Telephone follow-ups will be carried out by the certified exercise instructor at 10 days, 2 months and 4 months after the intervention onset to ensure the proper functioning of the connected device, review the use of the connected device, review the conduct of the sessions and answer the participants’ questions if they may have. Participants will be orally encouraged to remain physically active on a daily basis (reminder of the benefits and recommendations of physical activity, success and satisfaction during the exercise sessions). During the 6-month intervention, the participants will have the opportunity to contact the certified exercise instructor or the clinical research assistant at any time, by email (directly through the website) or by telephone for any question or assistance with the connected device.
The certified exercise instructor will monitor the use of the connected device by the participants and their progress in the programme through a dedicated professional website that provides real-time access to the participants’ data. On this website, an automatically generated daily event table will inform the certified exercise instructor of the occurrence of disabilities reported by the participants that may lead to modifying their programme (eg, severe fatigue, dyspnoea, unusual muscle pain) or if participants have not performed their planned sessions or used their activity tracker for seven consecutive days. On these alerts, the certified exercise instructor will contact the participants to precisely analyse the reported disabilities, advise participants, identify the causes of non-use of the connected device, solve possible technical problems or reinforce participant’s motivation if necessary.
At the end of the 6-month programme, participants will keep their activity tracker to be encouraged to continue regularly exercising in autonomy. On their request, continued subscription to the dedicated application and website will be offered for another 6 months, with no individual follow-up anymore.
Participants randomised to the therapeutic patient education arm will benefit from a therapeutic patient education intervention, in addition to receiving the international physical activity recommendations. The intervention is part of the therapeutic patient education programme set up at the Léon Bérard cancer centre and validated by the Regional Health Agency (‘Agence Régionale de Santé Rhône-Alpes’). It will be disseminated in the investigating centres according to the criteria of the Regional Health Agency. The therapeutic patient education intervention consists of four sessions that will be scheduled according to participants’ availability during their follow-up visits as part of their usual clinical management over a 6-month period. First, participants will be invited to an initial 1-hour individual face-to-face session of educational diagnosis with a health professional trained in therapeutic patient education. This session will assess their needs and establish a contract of objectives to reach. Then, participants will be invited to participate in two collective educational sessions (1h30 each with a group of 10 patients maximum per session). These sessions will be composed of theoretical and practical workshops to help them understand their physical activity in their daily life and implement the necessary means to practice regular exercise in autonomy. Finally, participants will be invited to another 1-hour individual session, where an educational evaluation will be conducted to identify whether they achieve their individual objectives set at the time of the educational diagnosis.
Participants randomised to the ‘combined intervention’ arm will benefit from a combination of the connected device intervention and the therapeutic patient education intervention in parallel for 6 months.
The initial assessment (T0) will be performed prior to randomisation for minimisation purposes. The other three evaluations will then be conducted at baseline (T1), 6 months (T2) and 12 months (T3). All study participants will then be followed at 6 months±1 month postrandomisation (corresponding to the end of participation in the interventions for women in the connected device, therapeutic patient education and combined arms) and at 12 months±1 month postrandomisation (corresponding to a follow-up period of 6 months postinterventions). Assessments will be carried out by a clinical research assistant and a certified exercise instructor. The clinical research assistant will contact participants by phone to invite them to follow-up visits and to promote participant retention and complete follow-up. Participants will have no compensation for participation and all study visits will be scheduled on days of their medical or health-related appointments. All evaluations (baseline, 6 and 12 months) will include physical fitness tests, anthropometric measures, self-administered questionnaires and a non-fasting blood draw (baseline and 6 months only). Data will be recorded using an electronic case report form (eCRF).
The study outcome measures and their schedule are summarised in . Sociodemographic and clinical data Sociodemographic and clinical data, including month/year of birth, age at diagnosis of breast cancer, family status, level of education, hormonal status, tumour histology and personal history of breast cancer will be collected at baseline. Family status, potential cancer progression and all treatments received for cancer will be collected at 6 and 12 months. All data will be extracted from patients’ electronic medical records, except family status and level of education that will be self-reported in a questionnaire. The occupational status will be assessed using a self-administered questionnaire asking employment status, occupation, size of the company, the perceived intensity of the physical effort at work, the evolution of employment status at return to work in case of sick leave. Anthropometrics and body composition The standing height (cm), body weight (kg) and waist (cm) and hip (cm) circumferences will be measured using standardised procedures and BMI will be calculated as the body weight in kilograms divided by the square of the height in metres (kg/m²). The waist circumference will be measured midway between the last floating rib and the iliac crest. The hip circumference will be measured at the tip of the pubis. Body composition will be measured by a bioelectrical impedance metre (Biody XPert ZM II, eBiody, eBIODY SAS, La Ciotat, France) to assess fat mass (in kg), lean body mass (in kg), muscle mass (in kg), dry lean mass (in kg), total body water (in L), intracellular fluid (in L) and extracellular fluid (in L). Physical fitness Cardiorespiratory fitness will be evaluated by the walking endurance during the 6MWT (distance covered in metres) with perceived difficulty using the Borg scale. During this test, participants will be asked to perform the maximum walk shuttle distance on a 30 m long flat corridor in 6 min. The lower limb muscle strength will be measured using the sit-to-stand test (number of sit-ups on a chair in 30 s). During this test, participants will be asked to sit down on a chair and get up as many times as possible during 30 s. Hand prehensile strength will be measured by the handgrip test using hand dynamometry (Jamar Plus Digital Hand Dynamometer, Patterson Medical, Huthwaite, UK), which is a validated index of the isometric strength of the hand and forearm muscles. During this hand-grip test, participants will be asked to squeeze the handgrip as strongly as possible to obtain the maximal force (in kg). Two measures will be performed on each hand and the best performance will be registered. The flexibility of lower limbs will be measured using the sit-and-reach flexibility test (Deluxe Baseline flexibility test, 3B Scientific, Bartenheim, France). In this test, participants will sit on the floor on a mat with their legs stretched out straight ahead. They will be asked to lean forward as far as possible and the distance between fingertips and toes will be measured (in cm) (ie, by considering the level of the feet as recording zero, any measure that does not reach the toes is negative and any measure beyond the toes is positive). The balance will be measured using the bilateral single-leg stance test. The participants will stand and be asked to lift a foot and hold the position for a maximum of 60 s, then to do the same exercise on the other foot (duration held in equilibrium, 2 times 60 s). Physical activity level, sitting time and achievement of physical activity recommendations The validated self-administered questionnaire RPAQ will be used to measure the self-reported physical activity. The RPAQ was designed to assess usual physical activity in the last 4 weeks, covering three activity domains: domestic physical activity, including sitting time that is a good proxy of sedentary behaviour; occupational physical activity, including transportation to and from work; and recreational physical activity. The RPAQ gives specific scores in the metabolic equivalent of task (MET) unit for activities of very low intensity (<1.5 METs, ie, sedentary activities), low intensity (1.5 to <3 METs), moderate intensity (3 to <6 METs) and high intensity (≥6 METs, ie, vigorous activities) within each domain during the past 4 weeks. Questions will be coded and converted in MET-minute per 4 weeks according to the Compendium of Physical Activities by multiplying the number of METs by the duration and frequency of each activity. Then, the global score of physical activity will be obtained by adding the number of MET-minutes per 4 weeks in each intensity and each domain. The physical activity profile will be defined as the time spent in physical activities of low, moderate and high intensities. The physical activity level will be defined by the overall weekly physical activity (average expressed in MET-hour/week). Achievement of international physical activity guidelines will be computed for each individual by dividing the time spent in moderate-to-vigorous physical activity (ie, ≥3 METs) into two categories : <150 min/week of moderate-to-vigorous physical activity (ie, under physical activity guidelines); ≥150 min/week of moderate-to-vigorous physical activity (ie, reaching physical activity guidelines). Patient-reported outcomes The quality of life will be measured using the European Organization for Research and Treatment of Cancer (EORTC) Quality-Of-Life Questionnaire (QLQ-C30) and its specific module for breast cancer (BR-23). The QLQ-C30 is a 30-item validated self-administered questionnaire that evaluates five functioning domains (ie, physical, role, emotional, cognitive and social), a global quality-of-life domain, three symptom domains (ie, pain, fatigue and nausea) and six single items (ie, dyspnoea, insomnia, anorexia, diarrhoea, constipation and financial impact). Each item is associated with a score ranging from 0 to 100. For the functioning and global quality-of-life scales, a higher score corresponds to a better functioning level. For scales related to symptoms, a lower score corresponds to a better functioning level. The BR-23 module gathers data about perceived body image, sexual functioning, sex enjoyment, arm symptoms, breast symptoms and systemic therapy side effects. The health-related quality of life will be assessed using the European Quality of Life-5 dimensions-5 levels (EQ-5D-5L) questionnaire. This standardised self-administered questionnaire describes five dimensions (ie, mobility, self-care, usual activities, pain/discomfort and anxiety/depression) being rated using five levels (ie, no, slight, moderate, severe and extreme problems), and comprises a 0–100 Visual Analogue Scale recording the self-rated health (where the endpoints are labelled ‘The best health you can imagine’ and ‘The worst health you can imagine’). Fatigue will be assessed using the Piper Fatigue Scale-12 (PFS-12), a 12-item self-reported questionnaire with four subscales (ie, behavioural, affective, sensory and cognitive/mood aspects of fatigue) : the higher the score, the worse the fatigue. All items together will produce a total score for fatigue that will be used to define categories as follows: no fatigue (score=0), mild fatigue (score 1–3), moderate fatigue (score 4–6) and severe fatigue (score 7–10). Social deprivation will be assessed using the EPICES (Evaluation of Deprivation and Inequalities in Health Examination Centres) score. The score will be computed by adding each question coefficient to the intercept whenever the answer is ‘yes’. The score ranges from 0 to 100 (ie, the higher the score, the greater the deprivation level) with the threshold for deprivation at 30. Lifestyle factors, assessed using a self-administered questionnaire, include tobacco status (ie, never, former, current smoker), lifetime and current tobacco use (expressed in pack-years) and alcohol intake over the past 6 months (usual frequency of consumption (ie, never, less than 1/month, 1–3 times/month, 1–6 times/week, daily) of different categories of alcoholic beverages (ie, wine, beer, cider, aperitif wine, cocktail/punch, aniseed alcohol, spirits) as well as the usual number of glasses). The amount of alcohol will be computed by multiplying the frequency of consumption by the number of glasses and alcohol content of each type of alcoholic beverage. The average daily alcohol intake over the past 6 months (in g/day) will be computed by summing the amount of alcohol from each beverage. Determinants of physical activity The 21-item self-administered questionnaire ‘Barriers to Being Active Quiz’ will be used to qualitatively assess barriers to the regular practice of physical activity. Uses, representations and motivation towards physical activity will be assessed within the study population using a self-administered questionnaire available online. Acceptability of connected devices and acceptability of therapeutic patient education will be assessed among participants randomised to the corresponding arms using a paper-based self-administered questionnaire. These questionnaires will be developed following the Unified Theory of Acceptance and Use of Technology, which is a specification of the Theory of Planned Behaviour designed to explain and predict the probability of behaviour change among individuals faced with new technologies. The Theory of Planned Behaviour has been massively used during the last two decades to promote health behaviours such as physical activity. Besides, item wording will be based on the results of individual and collective interviews conducted for that purpose and designed to identify social representations of health protection and physical activity incentive devices. Compliance with interventions Compliance with each intervention will be assessed at the 6-month evaluation only for patients randomised to the ‘connected device’, ‘therapeutic patient education’ and ‘combined’ arms. Compliance will be assessed by the number of days of use of the activity tracker, the participation rate in scheduled exercise sessions, the participation rate in scheduled therapeutic education sessions and the proportion of compliant patients, depending on the intervention allocated, following the recommendations of the protocol. Patients’ compliance and reasons for non-compliance during the intervention period (6 months) will be described for each arm. Biological assessments A non-fasting blood sample (one 10 mL EDTA tube and one 10 mL dry tube) will be collected at baseline and 6 months. In particular, blood will be drawn at baseline before the onset of adjuvant treatments, otherwise no blood samples will be collected. The following biological factors will be assessed in the blood samples: circulating serum levels of endocrine factors (IGF-1, insulin, estradiol), circulating plasma levels of inflammatory cytokines (IL-6, TNFα, CRP), circulating plasma levels of adipokines (adiponectin, leptin) and vitamin D status.
Sociodemographic and clinical data, including month/year of birth, age at diagnosis of breast cancer, family status, level of education, hormonal status, tumour histology and personal history of breast cancer will be collected at baseline. Family status, potential cancer progression and all treatments received for cancer will be collected at 6 and 12 months. All data will be extracted from patients’ electronic medical records, except family status and level of education that will be self-reported in a questionnaire. The occupational status will be assessed using a self-administered questionnaire asking employment status, occupation, size of the company, the perceived intensity of the physical effort at work, the evolution of employment status at return to work in case of sick leave.
The standing height (cm), body weight (kg) and waist (cm) and hip (cm) circumferences will be measured using standardised procedures and BMI will be calculated as the body weight in kilograms divided by the square of the height in metres (kg/m²). The waist circumference will be measured midway between the last floating rib and the iliac crest. The hip circumference will be measured at the tip of the pubis. Body composition will be measured by a bioelectrical impedance metre (Biody XPert ZM II, eBiody, eBIODY SAS, La Ciotat, France) to assess fat mass (in kg), lean body mass (in kg), muscle mass (in kg), dry lean mass (in kg), total body water (in L), intracellular fluid (in L) and extracellular fluid (in L).
Cardiorespiratory fitness will be evaluated by the walking endurance during the 6MWT (distance covered in metres) with perceived difficulty using the Borg scale. During this test, participants will be asked to perform the maximum walk shuttle distance on a 30 m long flat corridor in 6 min. The lower limb muscle strength will be measured using the sit-to-stand test (number of sit-ups on a chair in 30 s). During this test, participants will be asked to sit down on a chair and get up as many times as possible during 30 s. Hand prehensile strength will be measured by the handgrip test using hand dynamometry (Jamar Plus Digital Hand Dynamometer, Patterson Medical, Huthwaite, UK), which is a validated index of the isometric strength of the hand and forearm muscles. During this hand-grip test, participants will be asked to squeeze the handgrip as strongly as possible to obtain the maximal force (in kg). Two measures will be performed on each hand and the best performance will be registered. The flexibility of lower limbs will be measured using the sit-and-reach flexibility test (Deluxe Baseline flexibility test, 3B Scientific, Bartenheim, France). In this test, participants will sit on the floor on a mat with their legs stretched out straight ahead. They will be asked to lean forward as far as possible and the distance between fingertips and toes will be measured (in cm) (ie, by considering the level of the feet as recording zero, any measure that does not reach the toes is negative and any measure beyond the toes is positive). The balance will be measured using the bilateral single-leg stance test. The participants will stand and be asked to lift a foot and hold the position for a maximum of 60 s, then to do the same exercise on the other foot (duration held in equilibrium, 2 times 60 s).
The validated self-administered questionnaire RPAQ will be used to measure the self-reported physical activity. The RPAQ was designed to assess usual physical activity in the last 4 weeks, covering three activity domains: domestic physical activity, including sitting time that is a good proxy of sedentary behaviour; occupational physical activity, including transportation to and from work; and recreational physical activity. The RPAQ gives specific scores in the metabolic equivalent of task (MET) unit for activities of very low intensity (<1.5 METs, ie, sedentary activities), low intensity (1.5 to <3 METs), moderate intensity (3 to <6 METs) and high intensity (≥6 METs, ie, vigorous activities) within each domain during the past 4 weeks. Questions will be coded and converted in MET-minute per 4 weeks according to the Compendium of Physical Activities by multiplying the number of METs by the duration and frequency of each activity. Then, the global score of physical activity will be obtained by adding the number of MET-minutes per 4 weeks in each intensity and each domain. The physical activity profile will be defined as the time spent in physical activities of low, moderate and high intensities. The physical activity level will be defined by the overall weekly physical activity (average expressed in MET-hour/week). Achievement of international physical activity guidelines will be computed for each individual by dividing the time spent in moderate-to-vigorous physical activity (ie, ≥3 METs) into two categories : <150 min/week of moderate-to-vigorous physical activity (ie, under physical activity guidelines); ≥150 min/week of moderate-to-vigorous physical activity (ie, reaching physical activity guidelines).
The quality of life will be measured using the European Organization for Research and Treatment of Cancer (EORTC) Quality-Of-Life Questionnaire (QLQ-C30) and its specific module for breast cancer (BR-23). The QLQ-C30 is a 30-item validated self-administered questionnaire that evaluates five functioning domains (ie, physical, role, emotional, cognitive and social), a global quality-of-life domain, three symptom domains (ie, pain, fatigue and nausea) and six single items (ie, dyspnoea, insomnia, anorexia, diarrhoea, constipation and financial impact). Each item is associated with a score ranging from 0 to 100. For the functioning and global quality-of-life scales, a higher score corresponds to a better functioning level. For scales related to symptoms, a lower score corresponds to a better functioning level. The BR-23 module gathers data about perceived body image, sexual functioning, sex enjoyment, arm symptoms, breast symptoms and systemic therapy side effects. The health-related quality of life will be assessed using the European Quality of Life-5 dimensions-5 levels (EQ-5D-5L) questionnaire. This standardised self-administered questionnaire describes five dimensions (ie, mobility, self-care, usual activities, pain/discomfort and anxiety/depression) being rated using five levels (ie, no, slight, moderate, severe and extreme problems), and comprises a 0–100 Visual Analogue Scale recording the self-rated health (where the endpoints are labelled ‘The best health you can imagine’ and ‘The worst health you can imagine’). Fatigue will be assessed using the Piper Fatigue Scale-12 (PFS-12), a 12-item self-reported questionnaire with four subscales (ie, behavioural, affective, sensory and cognitive/mood aspects of fatigue) : the higher the score, the worse the fatigue. All items together will produce a total score for fatigue that will be used to define categories as follows: no fatigue (score=0), mild fatigue (score 1–3), moderate fatigue (score 4–6) and severe fatigue (score 7–10). Social deprivation will be assessed using the EPICES (Evaluation of Deprivation and Inequalities in Health Examination Centres) score. The score will be computed by adding each question coefficient to the intercept whenever the answer is ‘yes’. The score ranges from 0 to 100 (ie, the higher the score, the greater the deprivation level) with the threshold for deprivation at 30. Lifestyle factors, assessed using a self-administered questionnaire, include tobacco status (ie, never, former, current smoker), lifetime and current tobacco use (expressed in pack-years) and alcohol intake over the past 6 months (usual frequency of consumption (ie, never, less than 1/month, 1–3 times/month, 1–6 times/week, daily) of different categories of alcoholic beverages (ie, wine, beer, cider, aperitif wine, cocktail/punch, aniseed alcohol, spirits) as well as the usual number of glasses). The amount of alcohol will be computed by multiplying the frequency of consumption by the number of glasses and alcohol content of each type of alcoholic beverage. The average daily alcohol intake over the past 6 months (in g/day) will be computed by summing the amount of alcohol from each beverage.
The 21-item self-administered questionnaire ‘Barriers to Being Active Quiz’ will be used to qualitatively assess barriers to the regular practice of physical activity. Uses, representations and motivation towards physical activity will be assessed within the study population using a self-administered questionnaire available online. Acceptability of connected devices and acceptability of therapeutic patient education will be assessed among participants randomised to the corresponding arms using a paper-based self-administered questionnaire. These questionnaires will be developed following the Unified Theory of Acceptance and Use of Technology, which is a specification of the Theory of Planned Behaviour designed to explain and predict the probability of behaviour change among individuals faced with new technologies. The Theory of Planned Behaviour has been massively used during the last two decades to promote health behaviours such as physical activity. Besides, item wording will be based on the results of individual and collective interviews conducted for that purpose and designed to identify social representations of health protection and physical activity incentive devices.
Compliance with each intervention will be assessed at the 6-month evaluation only for patients randomised to the ‘connected device’, ‘therapeutic patient education’ and ‘combined’ arms. Compliance will be assessed by the number of days of use of the activity tracker, the participation rate in scheduled exercise sessions, the participation rate in scheduled therapeutic education sessions and the proportion of compliant patients, depending on the intervention allocated, following the recommendations of the protocol. Patients’ compliance and reasons for non-compliance during the intervention period (6 months) will be described for each arm.
A non-fasting blood sample (one 10 mL EDTA tube and one 10 mL dry tube) will be collected at baseline and 6 months. In particular, blood will be drawn at baseline before the onset of adjuvant treatments, otherwise no blood samples will be collected. The following biological factors will be assessed in the blood samples: circulating serum levels of endocrine factors (IGF-1, insulin, estradiol), circulating plasma levels of inflammatory cytokines (IL-6, TNFα, CRP), circulating plasma levels of adipokines (adiponectin, leptin) and vitamin D status.
The primary endpoint will be the proportion of women who achieve at 6 months the internationally recommended level of physical activity (at least 150 min/week of moderate-to-vigorous physical activity, ie, intensity ≥3 METs) assessed by the RPAQ self-administered questionnaire. Secondary endpoints will be: Assessment of the efficacy of the programmes at 12 months (ie, the proportion of women who achieve the internationally recommended level of physical activity). Assessment of the adherence to the interventions at 6 months (the proportion of participants who are compliant to the programme, participation rate in planned sessions). Assessment of the impact between baseline and 6 months and between 6 and 12 months of the interventions on physical activity profile (changes in time spent in different intensities of physical activity and time spent in sedentary activities), physical fitness (changes in results to the 6 MWT, hand-grip test, sit-to-stand test, sit-and-reach flexibility test and single-leg stance test), anthropometrics (changes in weight, waist and hip circumferences, BMI, fat mass, lean body mass, muscle mass, dry lean mass and body water), quality of life (changes in scores obtained from the EORTC QLQ-C30 questionnaire and its BR-23 module), fatigue condition (changes in scores obtained from the PFS-12 questionnaire), health-related quality of life (changes in scores obtained from the EQ-5D-5L questionnaire), social deprivation (changes in scores obtained from the EPICES self-administered questionnaire), occupational status (the proportion of participants who changed their employment status, with return to work and who perceived difficulty at work obtained from a self-administered questionnaire) and lifestyle factors (the proportion of participants who change their tobacco use and alcohol intake obtained from a self-administered questionnaire). Assessment of the impact of the interventions on biological parameters between baseline and 6 months (changes in serum circulating levels of endocrine factors (insulin, IGF1, estradiol), changes in plasma circulating levels of cytokines (inflammatory cytokines: IL-6, TNF and CRP; adipokines: adiponectin and leptin), the proportion of participants with a modification on vitamin D status). Assessment of the representations and acceptability of activity tracker and therapeutic patient education, at baseline, 6 and 12 months (proportions of participants who accept the connected device and who accept the therapeutic programme, according to scores obtained from a self-administered qualitative questionnaire used in social psychology science). Assessment of refusal rate among eligible patients (the proportion of patients who refuse to participate). Assessment of the cost–utility and the cost-effectiveness of implementing each intervention at 12 months, using clinical data (treatments received, patients’ diary on medical consultations), hospital costs (national data) and benefit in physical activity level.
Sample size determination The efficacy rate assumptions are μ=40 %, μ+μA=55% and μ+μB=65% for the ‘control’, ‘therapeutic patient education’ and ‘connected device’ arm modalities, respectively. The expected benefit in the ‘therapeutic patient education’ arm compared with the ‘control’ arm is 15% (40% efficacy in the ‘control’ arm vs 55% efficacy in the ‘therapeutic patient education’ arm). The expected benefit in the ‘connected device’ arm compared with the ‘control’ arm is 25% (40% efficacy in the ‘control’ arm vs 65% efficacy in the ‘connected device’ arm). The sample size is calculated to allow the two comparisons of interest to be tested bilaterally at the threshold of 0.025. Assuming that the ‘therapeutic patient education’ intervention and the ‘connected device’ intervention act independently (additive model), the sample size required to compare therapeutic patient education (ie, participants assigned to the ‘therapeutic patient education’ and ‘combined’ arms) vs no therapeutic patient education (ie, participants assigned to the ‘control’ and ‘connected device’ arms) is given by the following formula: [μ + (μ+μB)]/2, vs [(μ+μA) + (μ + μA + μB)/2], that is, (40%+65%)/2=52.5 %, versus (55%+80)/2=67.5% With a first species risk α=0.025 and a power of 80% in the bilateral situation, the number of patients to include per treatment arm to demonstrate the efficacy of the therapeutic patient education will be 108 (or 432 for the four treatment arms) (nQuery V.6.0, χ 2 test with continuity correction). This number of patients will also allow a power greater than 95% to evaluate the efficacy of the ‘connected device’ intervention, always with a risk α=0.025 in the bilateral situation. Data analysis plan The following populations will be defined for statistical analyses: (1) the intention-to-treat (ITT) population, which includes all randomised participants in the study; (2) the per-protocol population, which consists of a subgroup of participants from the ITT population, who has no major protocol violations and who follows the procedure for the duration of the study. Analyses in the ITT population will be performed for all the study endpoints; analyses in the per-protocol population will be performed for exploratory purposes. The randomisation date will be considered as the reference date in all delay calculations, unless any other way is specified. Baseline data will be described in the ITT population and presented by randomised arms. For the primary outcome, proportions will be estimated for the two targeted comparisons: (1) participants who received the connected device vs participants who did not; (2) participants who benefited from the therapeutic patient education intervention vs participants who did not. Results will be presented with their 95% CI. The use of a 2×2 factorial design will allow to test, respectively: the efficacy of the intervention with a connected device (compared with without a connected device); the efficacy of the therapeutic patient education intervention (compared with no therapeutic patient education); and the interest of two combined intervention modalities (ie, connected device and therapeutic patient education) compared with the single intervention with the connected device only or with therapeutic patient education only. The analysis strategy will, therefore, be as follows : (1) searching first for an interaction by a specific interaction test, performed at the significance level of 0.05 (χ 2 test or use of an interaction term in a logistic model); (2) in the absence of interaction, testing each of the two bilateral interest comparisons at the threshold of 0.025, namely the efficacy of the intervention with the connected device and the efficacy of the therapeutic patient education intervention; (3) in case of the efficacy of either one of the intervention modalities, evaluating the interest of the combination of the two interventions compared with the single intervention with the connected device only or with therapeutic patient education only. For secondary outcome variables, the efficacy of the programme at 12 months, as well as according to stratification criteria, will be analysed similarly to the primary outcome. The adherence to the interventions will be evaluated by the proportion of compliant participants and participation rate in planned sessions. Changes in physical activity profile, physical fitness, anthropometrics, quality of life, fatigue, social deprivation and biological parameters will be analysed by the absolute and/or relative variations in each of these endpoints; these variations will be compared between with and without each intervention, for each intervention, and between combined interventions and the single one, using a parametric test. Occupational status and lifestyle factors will be analysed by comparing the proportion of participants between interventions or their combination. Representations and acceptability of activity tracker and therapeutic patient education will be analysed by comparing the proportion of participants between randomisation and follow-up assessments. A method for imputing missing data will be considered if necessary. Statistical analyses will be performed using SAS software V.9.4 or later. Medico-economic analysis The cost-effectiveness analysis will be conducted alongside the trial using the French national health insurance perspective. Quantities of resources used (external consultations, hospital stays including diagnosis-related groups, drugs with extra payments and other healthcare-related costs) will be collected on the eCRF and multiplied by the respective unit costs. The intervention with therapeutic patient education and the intervention with connected device will be evaluated using a bottom-up microcosting approach. Using the diagnosis-related group, hospital stays will be evaluated based on the French National hospital costs study database. External consultations and wider examinations, community care (general practitioner visits, nurse visits, etc) will be valued on the basis of the general nomenclature of professional treatments (‘Nomenclature Générale des Actes Professionnels’). The cost of biological treatments will be estimated using the nomenclature of biological medical treatments (‘Nomenclature des Actes de Biologie Médicale’). The cost of technical treatments (eg, imaging) will be estimated using the common classification of medical treatments (‘Classification Commune des Actes Médicaux’). Acquisition costs for the most expansive drugs will be based on the list of common units of dispensation for supplementary medicines (‘liste des unités communes de dispensation prise en charge en sus’). Finally, costs of medical transport will be derived from the French Court of Audit’s report on medical transport expenses covered by the French National Health insurance. The time horizon will be 12 months. Hence, neither costs nor effectiveness will be discounted. Mean costs and effectiveness will be derived for all four strategies under consideration: connected device, therapeutic patient education, combined and control arms. Incremental cost-effectiveness ratios (ICERs) will be expressed in cost per quality-adjusted life-year gained using EQ-5D-5L to estimate utility, cost per life-year gained, cost per BMI unit lost and cost per centimetre of waist-to-hip circumference lost. One-way sensitivity analyses will be conducted by varying resource consumption and unit cost parameters and graphically illustrated in a Tornado diagram. The uncertainty surrounding the ICERs will be also captured by a probabilistic analysis using non-parametric bootstrap methods as recommended by the French National Authority for Health.
The efficacy rate assumptions are μ=40 %, μ+μA=55% and μ+μB=65% for the ‘control’, ‘therapeutic patient education’ and ‘connected device’ arm modalities, respectively. The expected benefit in the ‘therapeutic patient education’ arm compared with the ‘control’ arm is 15% (40% efficacy in the ‘control’ arm vs 55% efficacy in the ‘therapeutic patient education’ arm). The expected benefit in the ‘connected device’ arm compared with the ‘control’ arm is 25% (40% efficacy in the ‘control’ arm vs 65% efficacy in the ‘connected device’ arm). The sample size is calculated to allow the two comparisons of interest to be tested bilaterally at the threshold of 0.025. Assuming that the ‘therapeutic patient education’ intervention and the ‘connected device’ intervention act independently (additive model), the sample size required to compare therapeutic patient education (ie, participants assigned to the ‘therapeutic patient education’ and ‘combined’ arms) vs no therapeutic patient education (ie, participants assigned to the ‘control’ and ‘connected device’ arms) is given by the following formula: [μ + (μ+μB)]/2, vs [(μ+μA) + (μ + μA + μB)/2], that is, (40%+65%)/2=52.5 %, versus (55%+80)/2=67.5% With a first species risk α=0.025 and a power of 80% in the bilateral situation, the number of patients to include per treatment arm to demonstrate the efficacy of the therapeutic patient education will be 108 (or 432 for the four treatment arms) (nQuery V.6.0, χ 2 test with continuity correction). This number of patients will also allow a power greater than 95% to evaluate the efficacy of the ‘connected device’ intervention, always with a risk α=0.025 in the bilateral situation.
The following populations will be defined for statistical analyses: (1) the intention-to-treat (ITT) population, which includes all randomised participants in the study; (2) the per-protocol population, which consists of a subgroup of participants from the ITT population, who has no major protocol violations and who follows the procedure for the duration of the study. Analyses in the ITT population will be performed for all the study endpoints; analyses in the per-protocol population will be performed for exploratory purposes. The randomisation date will be considered as the reference date in all delay calculations, unless any other way is specified. Baseline data will be described in the ITT population and presented by randomised arms. For the primary outcome, proportions will be estimated for the two targeted comparisons: (1) participants who received the connected device vs participants who did not; (2) participants who benefited from the therapeutic patient education intervention vs participants who did not. Results will be presented with their 95% CI. The use of a 2×2 factorial design will allow to test, respectively: the efficacy of the intervention with a connected device (compared with without a connected device); the efficacy of the therapeutic patient education intervention (compared with no therapeutic patient education); and the interest of two combined intervention modalities (ie, connected device and therapeutic patient education) compared with the single intervention with the connected device only or with therapeutic patient education only. The analysis strategy will, therefore, be as follows : (1) searching first for an interaction by a specific interaction test, performed at the significance level of 0.05 (χ 2 test or use of an interaction term in a logistic model); (2) in the absence of interaction, testing each of the two bilateral interest comparisons at the threshold of 0.025, namely the efficacy of the intervention with the connected device and the efficacy of the therapeutic patient education intervention; (3) in case of the efficacy of either one of the intervention modalities, evaluating the interest of the combination of the two interventions compared with the single intervention with the connected device only or with therapeutic patient education only. For secondary outcome variables, the efficacy of the programme at 12 months, as well as according to stratification criteria, will be analysed similarly to the primary outcome. The adherence to the interventions will be evaluated by the proportion of compliant participants and participation rate in planned sessions. Changes in physical activity profile, physical fitness, anthropometrics, quality of life, fatigue, social deprivation and biological parameters will be analysed by the absolute and/or relative variations in each of these endpoints; these variations will be compared between with and without each intervention, for each intervention, and between combined interventions and the single one, using a parametric test. Occupational status and lifestyle factors will be analysed by comparing the proportion of participants between interventions or their combination. Representations and acceptability of activity tracker and therapeutic patient education will be analysed by comparing the proportion of participants between randomisation and follow-up assessments. A method for imputing missing data will be considered if necessary. Statistical analyses will be performed using SAS software V.9.4 or later.
The cost-effectiveness analysis will be conducted alongside the trial using the French national health insurance perspective. Quantities of resources used (external consultations, hospital stays including diagnosis-related groups, drugs with extra payments and other healthcare-related costs) will be collected on the eCRF and multiplied by the respective unit costs. The intervention with therapeutic patient education and the intervention with connected device will be evaluated using a bottom-up microcosting approach. Using the diagnosis-related group, hospital stays will be evaluated based on the French National hospital costs study database. External consultations and wider examinations, community care (general practitioner visits, nurse visits, etc) will be valued on the basis of the general nomenclature of professional treatments (‘Nomenclature Générale des Actes Professionnels’). The cost of biological treatments will be estimated using the nomenclature of biological medical treatments (‘Nomenclature des Actes de Biologie Médicale’). The cost of technical treatments (eg, imaging) will be estimated using the common classification of medical treatments (‘Classification Commune des Actes Médicaux’). Acquisition costs for the most expansive drugs will be based on the list of common units of dispensation for supplementary medicines (‘liste des unités communes de dispensation prise en charge en sus’). Finally, costs of medical transport will be derived from the French Court of Audit’s report on medical transport expenses covered by the French National Health insurance. The time horizon will be 12 months. Hence, neither costs nor effectiveness will be discounted. Mean costs and effectiveness will be derived for all four strategies under consideration: connected device, therapeutic patient education, combined and control arms. Incremental cost-effectiveness ratios (ICERs) will be expressed in cost per quality-adjusted life-year gained using EQ-5D-5L to estimate utility, cost per life-year gained, cost per BMI unit lost and cost per centimetre of waist-to-hip circumference lost. One-way sensitivity analyses will be conducted by varying resource consumption and unit cost parameters and graphically illustrated in a Tornado diagram. The uncertainty surrounding the ICERs will be also captured by a probabilistic analysis using non-parametric bootstrap methods as recommended by the French National Authority for Health.
All participants will continuously report the occurrence of adverse events regarding neuropathies and joint pain in their patient’s notebook, which will be collected at 6 and 12 months. Those equipped with the connected device will also report potential adverse events before and after each session of their exercise programme (see Connected device). The reported adverse events will then be graduated according the Common Terminology Criteria for Adverse Events (CTCAE) V.5. Due to the low risks associated with the interventions, this study is part of the so-called ‘intervention research with minimal risks and constraints’ in the French legislation and therefore only these adverse events arising within the framework of the study will be reported. In the occurrence of an adverse event regarding neuropathies and joint pain, the principal investigator will report it to the health authorities responsible for vigilance without delay. The promotor will also report the adverse events, as well as any safety measures to be proposed, to the French Ethics Committee and the investigators without delay.
The database for clinical data and randomisation will be created using EnnovClinical software. Its access will be secured (personal identification and password protection) for maintaining confidentiality at all times. Individual participants will not be identified in any reports of this trial. All data from the connected device will be merged to the clinical database at the end of the study. Investigators and data analysts will have access to the final dataset. Data monitoring will be provided by the trial steering committee, including overall project supervision, progress monitoring, advice on scientific credibility and ensuring the integrity and appropriate running of the project. The clinical research assistant will verify all consent forms, compliance with established protocol and procedures, and data quality in the eCRF. The research team will make biannual reports to the trial steering committee.
An association of breast cancer patients’ representatives (Europa Donna France, http://www.europadonna.fr/ ) was involved in preparing the conduct of interventions and evaluations, in particular by considering patients' expectations, experience and desire for global care. The association will be involved in plans to disseminate the study results to patients with breast cancer, study participants and wider patient communities concerned.
The study protocol was approved by the French ethics committee (Comité de Protection des Personnes Est I, ID RCB 2017-A03360-53, 1 February 2018) and its database was reported to the French National Commission for Data Protection and Liberties (CNIL, ref. MR-001 no. 2016177, 13 December 2016). Substantial protocol modifications will be submitted to the ethics committee for approval and protocol amendment. The study findings will be widely disseminated through the clinical community by publications in international, peer-reviewed journals and by presentations at national and international conferences. They will also be communicated to patients through associations of patients’ representatives and science-based information websites. They will be useful for improving the clinical care of patients with cancer and providing useful information for implementing exercise programmes for patients with cancer to health professionals, institutions and public authorities. The study sponsors will disseminate the study findings to their stakeholders.
This article presents the protocol for the DISCO trial, which aims to evaluate the efficacy of a web-based and mobile-based connected device intervention and of a therapeutic patient education intervention, either single or combined, on the physical activity levels of patients with breast cancer undergoing adjuvant treatment, as well as to assess the cost-effectiveness of the interventions. This multicentre study opened in May 2018 and recruitment is expected to end in Summer 2021. In the short term, the expected results are to develop the autonomy of patients with breast cancer in their practice of physical activity, as well as to identify the best strategies of physical activity during breast cancer adjuvant treatments to increase and sustain physical activity levels in patients, overall or in specific subgroups according to BMI, baseline physical activity level and type of adjuvant treatment. In the medium term, the goal of the DISCO trial is to disseminate innovative programmes in supportive cancer care, based on scientific evidence, to systematically integrate exercise in breast cancer cares. While an increasing number of studies have demonstrated the benefits of exercise in patients with breast cancer, the routine implementation in the cancer care process lacks behind evidence and practice guidelines. While the prescription of physical activity in supervised programmes has been shown superior compared with non-supervised programmes, semisupervised interventions seem to yield comparable or superior benefits to supervised programmes. Therefore, the semisupervised exercise programme of the DISCO trial through continuous follow-up has been designed according to the preferences of women with breast cancer so as not to leave patients in total autonomy. Connected devices are tools developed over the last 10 years that are very promising for promoting physical activity in the general population and in patients with chronic diseases such as cancer and for developing distance-based physical activity interventions. The semisupervised home-based physical activity programme of the DISCO trial using the connected device provides flexibility to patients that may facilitate adherence and to overcome barriers due to distance of facilities from women’s home and spatial inequalities of access. Connected devices allow proposing a tailored physical activity programme to patients regardless of their place of residence, and enable patients to practice physical activities of their choice, at any time that suits them. Therefore, they may reduce geographical and organisational barriers in the access of patients to exercise, a key issue to improve their engagement in regular and sustained physical activity. Previous studies in oncology have reported that the use of mobile devices has benefits to overcome motivational barriers to physical activity, which can help patients staying physically active over the medium and long term. Moreover, some studies have shown that patients with breast cancer achieved higher fitness levels during supervised training compared with unsupervised training, even low and medium levels of supervision have been effective, as less resource-intensive options for effective and longer-term behavioural change strategies based on exercises in patients with cancer and survivors. Activity trackers have become increasingly popular in recent years. Patients have reported positive feedback on using activity trackers such as pleasant to wear, easy to use and a strong motivational role through the real-time display of daily number of steps. Also, walking is an inexpensive activity that can be performed anywhere and does not require specific skills. A study on preferences for technology-supported interventions in breast cancer survivors has reported that 63% would like to use a physical activity mobile application and 90% would find a physical activity tracker useful to monitor and increase physical activity. Despite the potential benefits of connected devices in cancer care, their use may face several important issues. First, ethical challenges related to the security of sensitive data storage have been raised. To ensure that data transfer and storage guarantee informational privacy and patient safety, an activity tracker made in France (ie, allowing storing health data only in France) and an accredited national health data host were chosen for the DISCO trial. Particularly, ensuring medical data security is a reassuring choice for patients to participate in this new kind of medical research. Second, technical challenges have been raised, related to technological robustness, reliability of data collection and processing, and ease of use. Therefore, an activity tracker with a step display on the screen, a user-friendly interface, good reliability and a good price-performance ratio was chosen in the DISCO trial. Third, connected devices may create or exacerbate access disparities related to technological literacy and economic means, as well as reliable access to the internet in rural or isolated areas. Fourth, medical reasons are usually not easy to control in patients’ adherence to exercise programmes. Reliance on self-assessment of the participant’s fatigue, evaluation of the participant before and after each session on the remote monitoring, up as the source of information about the participant’s health, can result in the ignorance of aspects of the participant’s health that cannot easily be monitored. Therapeutic patient education has been suggested to increase physical activity level in patients with chronic diseases and to improve multiple health outcomes, together with behavioural interventions including physical activity. Therapeutic patient education interventions might be promising for promoting a physically active lifestyle in patients with cancer as it helps patients establish lifestyle changes and reinforce self-management. Therapeutic patient education differs from traditional patient education in its intrinsic structure. Traditional patient education is directed towards informing and teaching patients how to manage their condition or disease. In contrast, therapeutic patient education differs from traditional patient education in the self-management conferred on the patient. Therefore, therapeutic patient education is more broadly directed towards how the patient accepts his/her condition and manages his/her problems on a daily basis and the impact of the disease on personal, family, professional and social life. Yet, in oncology, few therapeutic patient education studies targeting pain, fatigue, toxicities or treatment adherence are ongoing, and evaluations are rarely conducted. To our knowledge, only one programme of therapeutic patient education specific to physical activity has been evaluated in patients with cancer. However, a recent qualitative study has shown the value of therapeutic patient education on the attitudes towards the physical activity of women with breast cancer to promote regular exercise, which is a guarantee of a better quality of life. In order to evaluate the efficacy of two interventions in the DISCO trial, the primary outcome measure will be based on the physical activity level of the participants with or without interventions compared with international recommendations. The RPAQ questionnaire will be used for the primary outcome measure on account of its easy implementation. The authors acknowledge that this declarative evaluation confers methodological limits to the study. But the RPAQ questionnaire has been validated against objective methods (ie, combined accelerometry and heart rate monitoring) to evaluate moderate-to-vigorous physical activities, which is relevant for the primary outcome. No objective measures of physical activity have been planned because of organisational and logistic difficulties to equip and follow participants for 1 week (ie, the usual duration of monitoring with an accelerometer such as Actigraph). Such a test would even be particularly overwhelming for patients with cancer during the demanding period of adjuvant treatment onset. Additionally, the number of daily steps reported by the activity tracker was not chosen as the primary outcome because the activity tracker used in the study was not validated for monitoring physical activity in research or for medical purposes when the study was designed, although its reliability was evaluated against other devices (data not shown). However, recently the performance and reliability of smart devices tend to be increasingly validated. To understand the results of the DISCO clinical study, it is essential to study beliefs about connected devices and their appropriation by the patients, particularly to understand why behaviours of the patients tend to fade over time. In therapeutic education, beliefs and representations are essential to the success of the intervention. Moreover, with the connected devices, only technical dimensions are not sufficient to understand and highlight why individuals adopt or misuse the connected devices. There is still limited evidence or contrasting conclusions surrounding the cost-effectiveness of interventions promoting physical activity among women with breast cancer from studies conducted in France, the Netherland and Australia. In various chronic conditions other than cancer, there is now clear evidence in favour of exercise-based programmes for the treatment of various chronic conditions such as musculoskeletal, rheumatological disorders and cardiovascular diseases. As more research is needed to evaluate the cost-effectiveness of physical activity in the treatment of cancers, particularly breast cancer, the economic evaluation planned in the DISCO trial will fill in the gap by adding useful information. In conclusion, the study findings will provide valuable information on the efficacy of exercise interventions during breast cancer treatments, overcoming current barriers of access to facilities. They will further guide the development of evidence-based innovative interventions, to systematically include physical activity in the breast cancer care process. Finally, the economic evaluation planned in the DISCO trial will provide useful information for decision-makers.
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Depletion of Mitochondrial Cyclophilin D in Endothelial and Smooth Muscle Cells Attenuates Vascular Dysfunction and Hypertension | 762e75bb-22e7-43ab-a7b3-efb1bfa1e42c | 11931617 | Cardiovascular System[mh] | Hypertension is a multifactorial disorder in response to alterations in neural, endocrine, and immune systems, hemodynamics, genetic factors, and maladaptive changes in the vasculature. There is an unmet need for the treatment of hypertension since only 25% of hypertensive patients have their blood pressure under control potentially due to the mechanisms that are not affected by current treatments. Vascular dysfunction plays a critical role in the development of hypertension and hypertensive end-organ damage. It is associated with mitochondrial dysfunction ; however, molecular mechanisms of mitochondrial dysfunction and its causative role in hypertension are not clear. Interestingly, mitochondria are a common target of cardiovascular risk factors such as age, diet, cigarette smoking, sedentary lifestyle, and metabolic conditions. Mitochondria are critical in cell metabolism and function, and, therefore, it is conceivable that mitochondrial impairment can drive vascular dysfunction and contribute to development of hypertension. Previous studies have identified multiple mitochondrial pathways linked to hypertension including apoptosis, calcium homeostasis, mitochondrial metabolism, and oxidative stress. Several enzymes can serve as a “master” regulator of mitochondrial function such as peroxisome proliferator–activated receptor γ coactivator 1α, nuclear respiratory factor 1, and deacetylase sirtuin 3. There is a new potential candidate, cyclophilin D (CypD). CypD is an important mitochondrial chaperone protein; however, its specific mechanisms of action remain unclear. CypD can act as a peptidyl-prolyl, cis-trans isomerase involved in mitochondrial protein folding. Indeed, CypD promotes the assembly of mitochondrial ATP synthase into synthasome supercomplex. Meanwhile, CypD interaction with ATP synthase β-subunit F1 is likely responsible for calcium-sensitive mitochondrial permeability transition pore (mPTP) opening, which is linked to mitochondrial swelling, cellular apoptosis, and necrosis. , Potential role of CypD in redox signaling includes ischemic preconditioning, regulated mitochondria superoxide production, pathogenic superoxide overproduction, and endothelial dysfunction. These data suggest that CypD is implicated in both mitochondrial homeostasis and mitochondrial dysfunction. These seamlessly contradictory functions of CypD can be potentially explained by post-translational modifications of CypD such as S-glutathionylation and acetylation, which can lead to a “gain of function” and switch from homeostatic to pathogenic function. Meanwhile, targeting CypD is hindered by the lack of specificity of known CypD blockers. Off-target effects of cyclosporine A paradoxically lead to increased sympathetic outflow, endothelin production, vasoconstriction, and hypertension, which are likely associated with calcineurin inhibition. CypD blocker sanglifehrin A attenuates hypertension, but it has off-target immunosuppressive effect and cannot be used orally. It is, therefore, unclear whether CypD inhibition is protective or detrimental to vascular functions due to nonspecific blockade of both homeostatic and pathogenic CypD functions. We hypothesized that cell-specific CypD depletion in endothelial and smooth muscle cells attenuates vascular dysfunction and hypertension. To test this hypothesis, we have developed tamoxifen-inducible endothelial-specific CypD knockout mice (Ec CypDKO ) and tamoxifen-inducible smooth muscle cell–specific CypD knockout mice (Smc CypDKO ). We performed studies of angiotensin II (Ang II)–induced hypertension, endothelial-dependent relaxation, endothelial barrier permeability, vascular superoxide production, vascular mitochondrial respiration and glycolysis, aortic hypertrophy, and fibrosis. Our data support a multifaceted role of CypD in the regulation of vascular oxidative stress, metabolism, and cellular functions.
The authors declare that all supporting data are available within the article and its online supplementary files. All methods have corresponding literature references. Additional protocol information is available from the corresponding author upon reasonable request. Reagents Cellular superoxide probe was supplied by Invitrogen (Grand Island, NY). CypD (ab110324) antibodies were from Abcam. SOD2 (sc30080) antibodies were from Santa Cruz Biotechnology. Secondary antibodies conjugated with horseradish peroxidase were purchased from Amersham (anti-Rabbit IgG NA934V or anti-Mouse IgG NA931V). All other reagents were obtained from Sigma (St Louis, MO). Animal Experiments To test the pathophysiological role of vascular CypD, we developed new endothelial cell–specific tamoxifen-inducible CypD knockout mice (Ec CypDKO ) by crossing CypD flox/flox mice (Jacson Labs, stock # 005737) with mice transgenic for Cre recombinase driven by a tamoxifen-inducible endothelium VeCad promoter provided by Dr Rolf Adam (University of Münster, Germany). To delete CypD in vascular smooth muscle cells, we crossed CypD lox/lox mice with mice transgenic for Cre recombinase driven by tamoxifen-inducible Cre in the vascular smooth muscle (inducible SMMHC Cre) provided by Prof. Stefan Offermanns (University of Heidelberg, Germany). To induce CypD deletion, mice double positive for floxed sequence and Cre were injected with a low dose of tamoxifen (2 mg/30 g) for 5 days starting at 3 months of age, which have minimal transient cardiovascular effect. Wild-type Cre-negative littermates were also treated with tamoxifen. Two weeks later, hypertension was induced by Ang II (0.7 mg/kg/day, 14 days) in 4- to 5-month-old male mice. Blood pressure was monitored by the telemetry and tail-cuff measurements as previously described. , Mice were housed in a temperature-controlled environment with 12-h light/dark cycles where they received food and water ad libitum. The Vanderbilt Institutional Animal Care and Use Committee approved the procedures (Protocol M1700207). Simple randomization was used to select animals for sham or Ang II for equal chance of being allocated to treatment groups. Superoxide Measurements Using HPLC Mouse aortic segments were loaded with superoxide probe dihydroethidium (DHE) (50 µ m ) in Krebs/HEPES buffer for 30-min incubation in a tissue culture incubator at 37°C. Then, the tissue was placed in methanol (300 µL) and homogenized with a glass pestle. The homogenate was passed through a 0.22 μm filter and filtrates were analyzed by . The superoxide-specific product mito-2-hydroxyethidium was detected using a C-18 reverse-phase column (Nucleosil 250 to 4.5 mm) and a mobile phase containing 0.1% trifluoroacetic acid and an acetonitrile gradient (from 37% to 47%) at a flow rate of 0.5 mL/min. DHE superoxide–specific product 2-hydroxyethidium was detected using a C-18 reverse-phase column (Nucleosil 250 to 4.5 mm) as described previously. Nitric Oxide Measurements by Electron Spin Resonance Endothelial nitric oxide was quantified by electron spin resonance (ESR) and colloid spin trap Fe(DETC) 2 . All ESR samples were placed in quartz Dewar (Corning, New York, NY) filled with liquid nitrogen. ESR spectra were recorded using an EMX ESR spectrometer (Bruker Biospin Corp., Billerica, MA) and a super-high Q microwave cavity. The ESR settings were as follows: field sweep, 160 gauss; microwave frequency, 9.42 GHz; microwave power, 10 mW; modulation amplitude, 3 gauss; scan time, 150 ms; time constant, 5.2 s; and receiver gain, 60 dB ( n = 4 scans). Western Blotting Mouse aortas were homogenized in RIPA lysis buffer (Sigma, R0278) with 2.0 mmol/L sodium orthovanadate (Na 3 VO 4 ), 1.0 m m fluoride phenylmethylsulfonyl containing inhibitors of proteolytic enzymes: 10 μg/mL aprotinin, 10 μg/mL leupeptin, and 10 μg/mL pepstatin (Sigma-Aldrich). The concentration of protein in lysates was determined using the protein assay kit (Bio-Rad). Protein (20 μg) separation was carried out in polyacrylamide gels (4%-12%) and transferred to PVDF membrane (Bio-Rad) at 4°C. Nonspecific binding sites on the membrane were blocked with 5% skim milk or 3% BSA in Tris-buffered saline solution with Tween for 1 h at room temperature and then membranes were incubated with anti-CypD (Abcam, ab110324, 1:1000) or anti-SOD2 (sc30080, 1:1000) overnight at 4°C. The next day, membranes were incubated with secondary antibodies conjugated with horseradish peroxidase. Pierce ECL Western Blotting Substrate (Thermo Fisher Scientific) was used for chemiluminescence-based detection. Final scans were performed using X-ray films or Azure c500 Western Blot Imaging System (Azure Biosystem). Densitometric analyses were performed using ImageJ software or ImageStudio software (LI-COR). Data were normalized by GAPDH levels. Vasodilatation Study Isometric tension studies were performed on 2-mm mouse aortic rings dissected free of perivascular fat. Studies were performed in a horizontal wire myograph (DMT, Aarhus, Denmark, models 610M and 620M) containing physiological salt solution with the composition of 118 m m NaCl, 4.7 m m KCl, 1.2 m m MgSO 4 , 1.2 m m KH 2 PO 4 , 25 m m NaHCO 3 , 11 m m glucose, and 1.8 m m CaCl 2 . The isometric tone of each vessel was recorded using LabChart Pro v7.3.7 (AD Instruments, Australia). The aortic rings and mesenteric arteries were equilibrated over 2 h by heating and stretching the vessels to an optimal baseline tension before contracting them with 60 m m KCl physiological saline solution. Endothelial-dependent and endothelial-independent vascular relaxation were tested after preconstriction with 1 µ m phenylephrine. Once the vessels reached a steady-state contraction, increasing concentrations of acetylcholine or sodium nitroprusside were administered, and the response to each concentration of drug was recorded. Endothelium-denuded Aorta Mice were euthanized with carbon dioxide and aortas were gently excised, placed in cold buffer. Fat and connective tissues were removed carefully. The aorta was opened longitudinally with scissors. This preparation preserves intact endothelial cell function as measured by endothelial nitric oxide. The endothelium was mechanically removed by gently rubbing the intimal surface. Lactate Measurements Vascular glycolysis rate was measured in aortas isolated from sham and Ang II–infused mice and the descending part of aorta (6 mg) was placed in (glucose 1 g/L) tissue culture for 24 h. Glucose uptake and lactate production were tested in dulbecco's modified eagle medium (DMEM) aliquots using the hexokinase/glucose-6-phosphate dehydrogenase enzymatic assay and the l -lactate colorimetric assay (abcam kit ab65331). High-resolution Respirometry on Isolated Aortas Measurements of respiration on isolated aortas were performed as previously described. Aortas were isolated from sham and Ang II–infused mice and sections (∼6-10 mg) were placed in ice-cold BIOPS buffer containing CaK 2 EGTA (2.77 m m ), K 2 EGTA (7.23 m m ), Na 2 ATP (5.77 m m ), MgCl 2 ·6H 2 O (6.56 m m ), Na 2 phosphocreatine (15 m m ), imidazole (20 m m ), taurine (20 m m ), and K-MES (50 m m ), pH 7.1. Aortas were then permeabilized in ice-cold BIOPS containing 50 µg/mL saponin for 30 min, then washed in respiration buffer Mir05 containing sucrose (110 m m ), K-lactobionate (60 m m ), HEPES (20 m m ), taurine (20 m m ), K 2 HPO 4 (10 m m ), MgCl 2 ·6H 2 O (3 m m ), EGTA (0.5 m m ), and fatty acid–free BSA (0.1%), pH 7.1. Aortas remained in fresh ice-cold Mir05 under gentle agitation until respiration analysis. Mitochondrial respiration was measured using the oxygraph O2k (Oroboros) with continuously stirred chambers maintained at 37°C. The oxygen consumption related to Krebs cycle/complex I–linked substrates, NADH donors (2 m m malate + 5 m m pyruvate), was measured in the presence of 2 m m ADP. The uncoupler CCCP was added after ADP to assess maximal uncoupled respiration (1 μ m ). Results are presented as oxygen flux normalized to wet tissue weight (pmol/s/mg weight). Statistics The normality of continuous variable distribution was examined with the Shapiro-Wilk test. Normally distributed data are expressed as mean ± SD and nonnormally distributed data are expressed as median (Q25-Q75). Comparisons of the normally distributed continuous variables were assessed by the 2-way analysis of variance (ANOVA) followed by a Tukey post hoc test. Otherwise, we used appropriate nonparametric tests (Mann-Whitney and Kruskal-Wallis for 2 and >2 group comparisons, respectively). For telemetry blood pressure measurements over time and aortic relaxation, a 2-way ANOVA with repeated measures was employed. All statistical analyses were done using GraphPad Prism 10. P values < .05 were considered significant.
Cellular superoxide probe was supplied by Invitrogen (Grand Island, NY). CypD (ab110324) antibodies were from Abcam. SOD2 (sc30080) antibodies were from Santa Cruz Biotechnology. Secondary antibodies conjugated with horseradish peroxidase were purchased from Amersham (anti-Rabbit IgG NA934V or anti-Mouse IgG NA931V). All other reagents were obtained from Sigma (St Louis, MO).
To test the pathophysiological role of vascular CypD, we developed new endothelial cell–specific tamoxifen-inducible CypD knockout mice (Ec CypDKO ) by crossing CypD flox/flox mice (Jacson Labs, stock # 005737) with mice transgenic for Cre recombinase driven by a tamoxifen-inducible endothelium VeCad promoter provided by Dr Rolf Adam (University of Münster, Germany). To delete CypD in vascular smooth muscle cells, we crossed CypD lox/lox mice with mice transgenic for Cre recombinase driven by tamoxifen-inducible Cre in the vascular smooth muscle (inducible SMMHC Cre) provided by Prof. Stefan Offermanns (University of Heidelberg, Germany). To induce CypD deletion, mice double positive for floxed sequence and Cre were injected with a low dose of tamoxifen (2 mg/30 g) for 5 days starting at 3 months of age, which have minimal transient cardiovascular effect. Wild-type Cre-negative littermates were also treated with tamoxifen. Two weeks later, hypertension was induced by Ang II (0.7 mg/kg/day, 14 days) in 4- to 5-month-old male mice. Blood pressure was monitored by the telemetry and tail-cuff measurements as previously described. , Mice were housed in a temperature-controlled environment with 12-h light/dark cycles where they received food and water ad libitum. The Vanderbilt Institutional Animal Care and Use Committee approved the procedures (Protocol M1700207). Simple randomization was used to select animals for sham or Ang II for equal chance of being allocated to treatment groups.
Mouse aortic segments were loaded with superoxide probe dihydroethidium (DHE) (50 µ m ) in Krebs/HEPES buffer for 30-min incubation in a tissue culture incubator at 37°C. Then, the tissue was placed in methanol (300 µL) and homogenized with a glass pestle. The homogenate was passed through a 0.22 μm filter and filtrates were analyzed by . The superoxide-specific product mito-2-hydroxyethidium was detected using a C-18 reverse-phase column (Nucleosil 250 to 4.5 mm) and a mobile phase containing 0.1% trifluoroacetic acid and an acetonitrile gradient (from 37% to 47%) at a flow rate of 0.5 mL/min. DHE superoxide–specific product 2-hydroxyethidium was detected using a C-18 reverse-phase column (Nucleosil 250 to 4.5 mm) as described previously.
Endothelial nitric oxide was quantified by electron spin resonance (ESR) and colloid spin trap Fe(DETC) 2 . All ESR samples were placed in quartz Dewar (Corning, New York, NY) filled with liquid nitrogen. ESR spectra were recorded using an EMX ESR spectrometer (Bruker Biospin Corp., Billerica, MA) and a super-high Q microwave cavity. The ESR settings were as follows: field sweep, 160 gauss; microwave frequency, 9.42 GHz; microwave power, 10 mW; modulation amplitude, 3 gauss; scan time, 150 ms; time constant, 5.2 s; and receiver gain, 60 dB ( n = 4 scans).
Mouse aortas were homogenized in RIPA lysis buffer (Sigma, R0278) with 2.0 mmol/L sodium orthovanadate (Na 3 VO 4 ), 1.0 m m fluoride phenylmethylsulfonyl containing inhibitors of proteolytic enzymes: 10 μg/mL aprotinin, 10 μg/mL leupeptin, and 10 μg/mL pepstatin (Sigma-Aldrich). The concentration of protein in lysates was determined using the protein assay kit (Bio-Rad). Protein (20 μg) separation was carried out in polyacrylamide gels (4%-12%) and transferred to PVDF membrane (Bio-Rad) at 4°C. Nonspecific binding sites on the membrane were blocked with 5% skim milk or 3% BSA in Tris-buffered saline solution with Tween for 1 h at room temperature and then membranes were incubated with anti-CypD (Abcam, ab110324, 1:1000) or anti-SOD2 (sc30080, 1:1000) overnight at 4°C. The next day, membranes were incubated with secondary antibodies conjugated with horseradish peroxidase. Pierce ECL Western Blotting Substrate (Thermo Fisher Scientific) was used for chemiluminescence-based detection. Final scans were performed using X-ray films or Azure c500 Western Blot Imaging System (Azure Biosystem). Densitometric analyses were performed using ImageJ software or ImageStudio software (LI-COR). Data were normalized by GAPDH levels.
Isometric tension studies were performed on 2-mm mouse aortic rings dissected free of perivascular fat. Studies were performed in a horizontal wire myograph (DMT, Aarhus, Denmark, models 610M and 620M) containing physiological salt solution with the composition of 118 m m NaCl, 4.7 m m KCl, 1.2 m m MgSO 4 , 1.2 m m KH 2 PO 4 , 25 m m NaHCO 3 , 11 m m glucose, and 1.8 m m CaCl 2 . The isometric tone of each vessel was recorded using LabChart Pro v7.3.7 (AD Instruments, Australia). The aortic rings and mesenteric arteries were equilibrated over 2 h by heating and stretching the vessels to an optimal baseline tension before contracting them with 60 m m KCl physiological saline solution. Endothelial-dependent and endothelial-independent vascular relaxation were tested after preconstriction with 1 µ m phenylephrine. Once the vessels reached a steady-state contraction, increasing concentrations of acetylcholine or sodium nitroprusside were administered, and the response to each concentration of drug was recorded.
Mice were euthanized with carbon dioxide and aortas were gently excised, placed in cold buffer. Fat and connective tissues were removed carefully. The aorta was opened longitudinally with scissors. This preparation preserves intact endothelial cell function as measured by endothelial nitric oxide. The endothelium was mechanically removed by gently rubbing the intimal surface.
Vascular glycolysis rate was measured in aortas isolated from sham and Ang II–infused mice and the descending part of aorta (6 mg) was placed in (glucose 1 g/L) tissue culture for 24 h. Glucose uptake and lactate production were tested in dulbecco's modified eagle medium (DMEM) aliquots using the hexokinase/glucose-6-phosphate dehydrogenase enzymatic assay and the l -lactate colorimetric assay (abcam kit ab65331).
Measurements of respiration on isolated aortas were performed as previously described. Aortas were isolated from sham and Ang II–infused mice and sections (∼6-10 mg) were placed in ice-cold BIOPS buffer containing CaK 2 EGTA (2.77 m m ), K 2 EGTA (7.23 m m ), Na 2 ATP (5.77 m m ), MgCl 2 ·6H 2 O (6.56 m m ), Na 2 phosphocreatine (15 m m ), imidazole (20 m m ), taurine (20 m m ), and K-MES (50 m m ), pH 7.1. Aortas were then permeabilized in ice-cold BIOPS containing 50 µg/mL saponin for 30 min, then washed in respiration buffer Mir05 containing sucrose (110 m m ), K-lactobionate (60 m m ), HEPES (20 m m ), taurine (20 m m ), K 2 HPO 4 (10 m m ), MgCl 2 ·6H 2 O (3 m m ), EGTA (0.5 m m ), and fatty acid–free BSA (0.1%), pH 7.1. Aortas remained in fresh ice-cold Mir05 under gentle agitation until respiration analysis. Mitochondrial respiration was measured using the oxygraph O2k (Oroboros) with continuously stirred chambers maintained at 37°C. The oxygen consumption related to Krebs cycle/complex I–linked substrates, NADH donors (2 m m malate + 5 m m pyruvate), was measured in the presence of 2 m m ADP. The uncoupler CCCP was added after ADP to assess maximal uncoupled respiration (1 μ m ). Results are presented as oxygen flux normalized to wet tissue weight (pmol/s/mg weight).
The normality of continuous variable distribution was examined with the Shapiro-Wilk test. Normally distributed data are expressed as mean ± SD and nonnormally distributed data are expressed as median (Q25-Q75). Comparisons of the normally distributed continuous variables were assessed by the 2-way analysis of variance (ANOVA) followed by a Tukey post hoc test. Otherwise, we used appropriate nonparametric tests (Mann-Whitney and Kruskal-Wallis for 2 and >2 group comparisons, respectively). For telemetry blood pressure measurements over time and aortic relaxation, a 2-way ANOVA with repeated measures was employed. All statistical analyses were done using GraphPad Prism 10. P values < .05 were considered significant.
Endothelial CypD Depletion Prevents Endothelial Dysfunction and Reduces Hypertension To test this hypothesis, we developed tamoxifen-inducible endothelial-specific CypD knockout mice (Ec CypDKO ). To delete CypD in endothelium, we crossed CypD lox/lox mice (Jackson Labs) with mice transgenic for Cre recombinase driven by a tamoxifen-inducible endothelium VeCad. The resultant homozygous male CypD lox/lox carrying Cre/VeCAD (Ec CypDKO ) were studied at 3-5 months of age. Endothelial CypD deletion was induced by injection of tamoxifen (2 mg/30 g of body weight) daily for 5 days. Tissue-specific CypD deletion was confirmed by Western blot analysis of isolated endothelial cells ( , insert). Two weeks after tamoxifen injections, mice had undergone telemetry unit placement surgery, and then 2 weeks later received osmotic minipump with Ang II (0.7 mg/kg/day) or saline as a vehicle. Analysis of systolic blood pressure at the end of the 14 days of Ang II infusion in wild-type littermates showed increased systolic blood pressure from 110 mm Hg (sham) to 155 mm Hg (Ang II). Meanwhile, Ang II–induced hypertension in Ec CypDKO mice was significantly attenuated, and systolic blood pressure was changed from 108 mm Hg (sham) to 137 mm Hg (Ang II), which was 18 mm Hg lower than in Ang II–infused wild-type mice ( ). To test whether endothelial CypD depletion reduces Ang II–induced vascular oxidative stress, we have measured vascular superoxide in aortas using superoxide probe DHE (50 μ m ) and performed high-performance liquid chromatography (HPLC) detection of superoxide-specific product, 2-hydroxyethidium. DHE/HPLC analysis showed a 2-fold increase in vascular superoxide in Ang II–infused wild-type littermates ( ), which is in line with previously reported data. , Interestingly, depletion of endothelial CypD in Ec CypDKO mice abolished the Ang II–induced superoxide overproduction ( ). We have tested whether reduced vascular oxidative stress in Ec CypDKO mice protects endothelial-dependent vasorelaxation. Indeed, analysis of acetylcholine-mediated aortic relaxation showed impairment of vasorelaxation in wild-type Ang II–infused mice; meanwhile, endothelial-dependent relaxation was completely preserved in Ang II–infused Ec CypDKO mice ( ). Endothelial nitric oxide plays an important role in blood pressure regulation, and vascular oxidative stress reduces nitric oxide levels. Ec CypDKO mice are protected from oxidative stress ( ); therefore, we tested whether endothelial CypD depletion preserves nitric oxide production. Endothelial nitric oxide was measured by specific spin trap Fe(DETC) 2 and ESR, as we have previously described. ESR analysis showed a significant decrease in endothelial nitric oxide by 52% in aortas from Ang II–infused wild-type mice. In contrast, Ang II infusion in Ec CypDKO mice reduced nitric oxide only by 15%, supporting that endothelial CypD depletion protects nitric oxide levels ( ). Endothelial CypD Depletion Attenuates Glycolytic Switch and Protects Mitochondrial Respiration We have recently reported that hypertension is linked to maladaptive metabolic switch to vascular glycolysis. We have tested whether endothelial CypD depletion prevents vascular glycolytic switch and protects mitochondrial function. Analysis of lactate production in isolated aortas showed that a 6-fold increase in vascular glycolysis and endothelial glycolysis (“intact” minus “denuded”) was increased by 8-fold in Ang II–infused wild-type mice. Meanwhile, endothelial CypD depletion in Ec CypDKO mice reduced vascular glycolysis by 45% and attenuated endothelial glycolysis by 210% ( ). These data demonstrate an important role of endothelial CypD in the maladaptive vascular metabolic alterations in hypertension. Vascular cells have balanced utilization of glycolysis and mitochondrial respiration, which are normally coupled, meaning that glycolysis product pyruvate is utilized by mitochondria. Oxidative stress increases pyruvate dehydrogenase kinase activity inhibiting pyruvate dehydrogenase, which can be a major metabolic step in vascular dysfunction. We have shown that endothelial CypD depletion prevents vascular oxidative stress ( ); therefore, we tested whether vascular mitochondrial respiration is preserved in Ang II–infused Ec CypDKO mice. Mitochondrial respiration in saponin-permeabilized aortas from Ang II–infused wild-type mice showed impairment of pyruvate-mediated respiration ( ). Interestingly, pyruvate-mediated respiration in aortas from Ang II–infused Ec CypDKO mice was not altered compared with sham Ec CypDKO and wild-type mice ( ). Depletion of Endothelial CypD Attenuates Ang II–induced Vascular Hyperpermeability It has previously been shown that glycolysis in endothelial cells promotes VE-cadherin endocytosis and proteolytic cleavage, leading to disruption of VE-cadherin cell-cell junctions, dysfunction of the endothelial barrier, and increased vascular permeability. We have shown that Ang II–induced endothelial glycolysis is attenuated in Ec CypDKO mice ( ); thus, we tested whether endothelial CypD depletion protects endothelial barrier function and prevents hypertensive vascular hyperpermeability. It was found that basal vascular permeability in sham Ec CypDKO mice was similar to wild-type littermates as measured by Miles assay and Evans Blue dye. Angiotensin II–infused wild-type mice increased vascular permeability by 2-fold; however, endothelial CypD depletion in Ec CypDKO mice significantly attenuated Ang II–induced vascular hyperpermeability ( ). These data are in line with previous reports that mitochondrial dysfunction reduces endothelial barrier integrity and increases vascular permeability. This can increase the access of cytokines and vasoactive substances to the tissue contributing to inflammation, hypertrophy, and end-organ damage, which could be potentially attenuated by CypD depletion. Depletion of Smooth Muscle CypD Attenuates Ang II–induced Vascular Dysfunction To test this hypothesis, we have investigated sham and Ang II–induced Smc CypDKO and wild-type mice. To delete CypD in vascular smooth muscle cells, we crossed CypD lox/lox mice (Jackson Labs) with mice transgenic for Cre recombinase driven by tamoxifen-inducible Cre in the vascular smooth muscle (inducible SMMHC Cre) provided by Prof. Stefan Offermanns (University of Heidelberg, Germany). The resultant homozygous male CypD lox/lox mice carrying Cre/SMMHC (Smc CypDKO ) were injected with tamoxifen (2 mg/30 g of body weight, daily for 5 days) at 3 months of age to induce smooth muscle CypD deletion. Tissue-specific CypD deletion was confirmed by Western blot. Two weeks after tamoxifen injections, mice had undergone telemetry unit placement, and 2 weeks later received osmotic minipump with Ang II (0.7 mg/kg/day) or saline as a vehicle. Analysis of systolic blood pressure at the end of the 14 days of Ang II infusion in wild-type littermates showed increased systolic blood pressure from 107 mm Hg (sham) to 155 mm Hg (Ang II). Ang II–induced hypertension in Smc CypDKO mice was partially attenuated, and systolic blood pressure was changed from 108 mm Hg (sham) to 145 mm Hg (Ang II), which was 10 mm Hg lower than in Ang II–infused wild-type mice ( ). It has been reported that global CypD depletion prevents Ang II–induced superoxide overproduction. In this work we tested whether smooth muscle–specific CypD deletion attenuates vascular oxidative stress. After 14 days of Ang II/sham treatment, mice were euthanized and aortas were isolated for analysis of vascular superoxide using superoxide probe DHE and HPLC. Ang II infusion in wild-type mice increased vascular superoxide levels by several fold, but depletion of smooth muscle CypD in Smc CypDKO mice prevents Ang II–induced superoxide overproduction ( ). We have tested whether reduced vascular oxidative stress in Smc CypDKO mice protects nitric oxide from inactivation and attenuates impairment of endothelial-dependent vasorelaxation. Indeed, Ang II–infused hypertension in wild-type mice was associated with a 2-fold decrease in vascular nitric oxide and impaired endothelial-dependent vasorelaxation ( and ), while depletion of smooth muscle CypD in Smc CypDKO mice partially protects nitric oxide levels and acetylcholine-induced relaxation ( and ; logEC 50 [Smc CypDKO ] = 7.3 and logEC 50 [Smc CypDKO + Ang II] = 6.7). Endothelial-independent relaxation was reduced in Ang II–infused wild-type mice, but it was protected in Smc CypDKO + Ang II aortas ( ). These data support the pathogenic role of CypD in smooth muscle cell oxidative stress in hypertension. It has previously been shown that vascular oxidative stress is associated with smooth muscle cell hypertrophy and vascular fibrosis. , , We have tested whether reduced vascular oxidative stress in Smc CypDKO mice attenuates hypertensive vascular remodeling. Histopathological analysis showed that Ang II infusion significantly increases aortic medial thickness and vascular fibrosis ( ). Meanwhile, smooth muscle CypD depletion attenuates Ang II–induced vascular hypertrophy (medial thickness) and reduces vascular fibrosis ( and ). These data support the pathogenic role of CypD in hypertensive vascular remodeling. Smooth Muscle Cell CypD Depletion Attenuates Ang II–induced Vascular Glycolysis Pathophysiological role of glycolytic switch in vascular smooth muscle cells promotes aortic aneurysms and vascular fibrosis, , and targeting of vascular glycolysis was proposed to reduce the aneurysmal formation and diminish mortality due to reduced aortic ruptures. , We have tested whether depletion of smooth muscle CypD reduces maladaptive switch to vascular glycolysis by lactate production in intact and denuded aortas isolated from sham and Ang II–induced Smc CypDKO and wild-type mice. Ang II infusion in wild-type littermates increased glycolysis in intact aortas by 5-fold and Ang II infusion in Smc CypDKO mice increased vascular glycolysis only by 2.8-fold ( ). Smooth muscle cell contribution in vascular glycolysis was measured in denuded aortas. Vascular glycolysis in denuded aortas was increased by 4.5-fold in Ang II–infused wild-type mice, and only a 2-fold increase was detected in Ang II–infused Smc CypDKO mice. These data demonstrate an important role of smooth muscle CypD in the maladaptive vascular glycolytic switch in hypertension.
To test this hypothesis, we developed tamoxifen-inducible endothelial-specific CypD knockout mice (Ec CypDKO ). To delete CypD in endothelium, we crossed CypD lox/lox mice (Jackson Labs) with mice transgenic for Cre recombinase driven by a tamoxifen-inducible endothelium VeCad. The resultant homozygous male CypD lox/lox carrying Cre/VeCAD (Ec CypDKO ) were studied at 3-5 months of age. Endothelial CypD deletion was induced by injection of tamoxifen (2 mg/30 g of body weight) daily for 5 days. Tissue-specific CypD deletion was confirmed by Western blot analysis of isolated endothelial cells ( , insert). Two weeks after tamoxifen injections, mice had undergone telemetry unit placement surgery, and then 2 weeks later received osmotic minipump with Ang II (0.7 mg/kg/day) or saline as a vehicle. Analysis of systolic blood pressure at the end of the 14 days of Ang II infusion in wild-type littermates showed increased systolic blood pressure from 110 mm Hg (sham) to 155 mm Hg (Ang II). Meanwhile, Ang II–induced hypertension in Ec CypDKO mice was significantly attenuated, and systolic blood pressure was changed from 108 mm Hg (sham) to 137 mm Hg (Ang II), which was 18 mm Hg lower than in Ang II–infused wild-type mice ( ). To test whether endothelial CypD depletion reduces Ang II–induced vascular oxidative stress, we have measured vascular superoxide in aortas using superoxide probe DHE (50 μ m ) and performed high-performance liquid chromatography (HPLC) detection of superoxide-specific product, 2-hydroxyethidium. DHE/HPLC analysis showed a 2-fold increase in vascular superoxide in Ang II–infused wild-type littermates ( ), which is in line with previously reported data. , Interestingly, depletion of endothelial CypD in Ec CypDKO mice abolished the Ang II–induced superoxide overproduction ( ). We have tested whether reduced vascular oxidative stress in Ec CypDKO mice protects endothelial-dependent vasorelaxation. Indeed, analysis of acetylcholine-mediated aortic relaxation showed impairment of vasorelaxation in wild-type Ang II–infused mice; meanwhile, endothelial-dependent relaxation was completely preserved in Ang II–infused Ec CypDKO mice ( ). Endothelial nitric oxide plays an important role in blood pressure regulation, and vascular oxidative stress reduces nitric oxide levels. Ec CypDKO mice are protected from oxidative stress ( ); therefore, we tested whether endothelial CypD depletion preserves nitric oxide production. Endothelial nitric oxide was measured by specific spin trap Fe(DETC) 2 and ESR, as we have previously described. ESR analysis showed a significant decrease in endothelial nitric oxide by 52% in aortas from Ang II–infused wild-type mice. In contrast, Ang II infusion in Ec CypDKO mice reduced nitric oxide only by 15%, supporting that endothelial CypD depletion protects nitric oxide levels ( ).
We have recently reported that hypertension is linked to maladaptive metabolic switch to vascular glycolysis. We have tested whether endothelial CypD depletion prevents vascular glycolytic switch and protects mitochondrial function. Analysis of lactate production in isolated aortas showed that a 6-fold increase in vascular glycolysis and endothelial glycolysis (“intact” minus “denuded”) was increased by 8-fold in Ang II–infused wild-type mice. Meanwhile, endothelial CypD depletion in Ec CypDKO mice reduced vascular glycolysis by 45% and attenuated endothelial glycolysis by 210% ( ). These data demonstrate an important role of endothelial CypD in the maladaptive vascular metabolic alterations in hypertension. Vascular cells have balanced utilization of glycolysis and mitochondrial respiration, which are normally coupled, meaning that glycolysis product pyruvate is utilized by mitochondria. Oxidative stress increases pyruvate dehydrogenase kinase activity inhibiting pyruvate dehydrogenase, which can be a major metabolic step in vascular dysfunction. We have shown that endothelial CypD depletion prevents vascular oxidative stress ( ); therefore, we tested whether vascular mitochondrial respiration is preserved in Ang II–infused Ec CypDKO mice. Mitochondrial respiration in saponin-permeabilized aortas from Ang II–infused wild-type mice showed impairment of pyruvate-mediated respiration ( ). Interestingly, pyruvate-mediated respiration in aortas from Ang II–infused Ec CypDKO mice was not altered compared with sham Ec CypDKO and wild-type mice ( ).
It has previously been shown that glycolysis in endothelial cells promotes VE-cadherin endocytosis and proteolytic cleavage, leading to disruption of VE-cadherin cell-cell junctions, dysfunction of the endothelial barrier, and increased vascular permeability. We have shown that Ang II–induced endothelial glycolysis is attenuated in Ec CypDKO mice ( ); thus, we tested whether endothelial CypD depletion protects endothelial barrier function and prevents hypertensive vascular hyperpermeability. It was found that basal vascular permeability in sham Ec CypDKO mice was similar to wild-type littermates as measured by Miles assay and Evans Blue dye. Angiotensin II–infused wild-type mice increased vascular permeability by 2-fold; however, endothelial CypD depletion in Ec CypDKO mice significantly attenuated Ang II–induced vascular hyperpermeability ( ). These data are in line with previous reports that mitochondrial dysfunction reduces endothelial barrier integrity and increases vascular permeability. This can increase the access of cytokines and vasoactive substances to the tissue contributing to inflammation, hypertrophy, and end-organ damage, which could be potentially attenuated by CypD depletion.
To test this hypothesis, we have investigated sham and Ang II–induced Smc CypDKO and wild-type mice. To delete CypD in vascular smooth muscle cells, we crossed CypD lox/lox mice (Jackson Labs) with mice transgenic for Cre recombinase driven by tamoxifen-inducible Cre in the vascular smooth muscle (inducible SMMHC Cre) provided by Prof. Stefan Offermanns (University of Heidelberg, Germany). The resultant homozygous male CypD lox/lox mice carrying Cre/SMMHC (Smc CypDKO ) were injected with tamoxifen (2 mg/30 g of body weight, daily for 5 days) at 3 months of age to induce smooth muscle CypD deletion. Tissue-specific CypD deletion was confirmed by Western blot. Two weeks after tamoxifen injections, mice had undergone telemetry unit placement, and 2 weeks later received osmotic minipump with Ang II (0.7 mg/kg/day) or saline as a vehicle. Analysis of systolic blood pressure at the end of the 14 days of Ang II infusion in wild-type littermates showed increased systolic blood pressure from 107 mm Hg (sham) to 155 mm Hg (Ang II). Ang II–induced hypertension in Smc CypDKO mice was partially attenuated, and systolic blood pressure was changed from 108 mm Hg (sham) to 145 mm Hg (Ang II), which was 10 mm Hg lower than in Ang II–infused wild-type mice ( ). It has been reported that global CypD depletion prevents Ang II–induced superoxide overproduction. In this work we tested whether smooth muscle–specific CypD deletion attenuates vascular oxidative stress. After 14 days of Ang II/sham treatment, mice were euthanized and aortas were isolated for analysis of vascular superoxide using superoxide probe DHE and HPLC. Ang II infusion in wild-type mice increased vascular superoxide levels by several fold, but depletion of smooth muscle CypD in Smc CypDKO mice prevents Ang II–induced superoxide overproduction ( ). We have tested whether reduced vascular oxidative stress in Smc CypDKO mice protects nitric oxide from inactivation and attenuates impairment of endothelial-dependent vasorelaxation. Indeed, Ang II–infused hypertension in wild-type mice was associated with a 2-fold decrease in vascular nitric oxide and impaired endothelial-dependent vasorelaxation ( and ), while depletion of smooth muscle CypD in Smc CypDKO mice partially protects nitric oxide levels and acetylcholine-induced relaxation ( and ; logEC 50 [Smc CypDKO ] = 7.3 and logEC 50 [Smc CypDKO + Ang II] = 6.7). Endothelial-independent relaxation was reduced in Ang II–infused wild-type mice, but it was protected in Smc CypDKO + Ang II aortas ( ). These data support the pathogenic role of CypD in smooth muscle cell oxidative stress in hypertension. It has previously been shown that vascular oxidative stress is associated with smooth muscle cell hypertrophy and vascular fibrosis. , , We have tested whether reduced vascular oxidative stress in Smc CypDKO mice attenuates hypertensive vascular remodeling. Histopathological analysis showed that Ang II infusion significantly increases aortic medial thickness and vascular fibrosis ( ). Meanwhile, smooth muscle CypD depletion attenuates Ang II–induced vascular hypertrophy (medial thickness) and reduces vascular fibrosis ( and ). These data support the pathogenic role of CypD in hypertensive vascular remodeling.
Pathophysiological role of glycolytic switch in vascular smooth muscle cells promotes aortic aneurysms and vascular fibrosis, , and targeting of vascular glycolysis was proposed to reduce the aneurysmal formation and diminish mortality due to reduced aortic ruptures. , We have tested whether depletion of smooth muscle CypD reduces maladaptive switch to vascular glycolysis by lactate production in intact and denuded aortas isolated from sham and Ang II–induced Smc CypDKO and wild-type mice. Ang II infusion in wild-type littermates increased glycolysis in intact aortas by 5-fold and Ang II infusion in Smc CypDKO mice increased vascular glycolysis only by 2.8-fold ( ). Smooth muscle cell contribution in vascular glycolysis was measured in denuded aortas. Vascular glycolysis in denuded aortas was increased by 4.5-fold in Ang II–infused wild-type mice, and only a 2-fold increase was detected in Ang II–infused Smc CypDKO mice. These data demonstrate an important role of smooth muscle CypD in the maladaptive vascular glycolytic switch in hypertension.
This study provides the first evidence that cell-specific CypD depletion in endothelial and smooth muscle cells attenuates vascular dysfunction and hypertension. Animal studies in the Ang II–induced model of hypertension showed that cell-specific CypD knockout in endothelial cells prevents vascular oxidative stress, preserves endothelial-dependent relaxation, protects endothelial nitric oxide production, and attenuates Ang II–induced vascular hyperpermeability, indicating that endothelial CypD depletion protects the endothelial function (Figures 1 and ). As expected, endothelial CypD depletion protects vascular mitochondrial respiration and significantly reduces maladaptive switch of vascular metabolism to glycolysis ( ). Protection of endothelial function and metabolism in Ec CypDKO mice was coupled with diminished Ang II–induced hypertension ( ). Studies of Smc CypDKO mice showed that smooth muscle CypD depletion inhibits vascular superoxide overproduction, reduces inactivation of endothelial nitric oxide, diminishes impairment of endothelial-dependent relaxation, and attenuates Ang II–induced vascular hypertrophy and fibrosis (Figures 4 and ). It was found that smooth muscle CypD depletion diminished Ang II–induced vascular metabolic switch to glycolysis ( ). Protection of smooth muscle cell metabolism and function in Smc CypDKO mice was associated with partial attenuation of Ang II–induced hypertension ( ). These data support the pathogenic role of mitochondrial CypD in vascular dysfunction and hypertension. It has previously been suggested that CypD can act as a master regulator of mitochondrial function. Indeed, CypD acts as a scaffold protein by binding to multiple mitochondrial proteins. It regulates coupling of the electron transport chain and ATP synthesis. Constitutive global CypD depletion in CypD −/− mice showed acetylation of fatty acid oxidation proteins associated with inhibition of fatty acid oxidation in the cardiac mitochondria isolated from CypD −/− mice. This suggests a novel link between CypD and mitochondrial acetylation, and it was proposed that CypD modulates mitochondrial acetylome. This creates a potential paradox since CypD −/− mice are protected against ischemic injury, but cardiac CypD depletion can alter metabolism and promote heart failure. On one hand, CypD can induce mitochondrial permeability pore opening, mitochondrial swelling, and cell death. On the other hand, CypD supports mitochondrial homeostasis. We think there are several explanations for this CypD paradox. First, constitutive CypD deletion may lead to the developmental problems and cause the adaptive epigenetic and metabolic changes in CypD −/− mice. Second, our clinical studies and basic medical research did not show significant alterations in CypD expression; however, CypD S-glutathionylation and CypD-acetylation are increased in vascular dysfunction and hypertension, suggesting a pathogenic role of CypD post-translational modifications, which can lead to switch from homeostatic to pathogenic “gain of function.” This raises the question whether conditional blocking of CypD is detrimental. Our data did not show any deleterious effects of conditional CypD depletion in tamoxifen inducible in Ec CypDKO and Smc CypDKO mice. Inducible CypD depletion in endothelial and smooth muscle cells did not affect the basal metabolism, endothelial nitric oxide, vasorelaxation, blood pressure, and basal heart rate ( ). Mitochondria have tremendous metabolic plasticity, and our data suggest that CypD is dispensable in adult homeostatic functions. We suggest that conditional CypD depletion or pharmacological inhibition of CypD can be effectively compensated by other mitochondrial pathways. Meanwhile, blocking CypD can be beneficial to prevent CypD switch from homeostatic to pathogenic “gain of function” in pathological conditions. In this work, we studied tamoxifen-inducible Ec CypDKO and Smc CypDKO male mice using the Ang II model of hypertension. There are several limitations of this experimental approach. First, our study was limited by the analysis of the male mice and did not include the female mice. Unfortunately, breeding transgenic mice with inducible SMMHC Cre located in the Y chromosome provides only Smc CypDKO male mice. A new smooth muscle tamoxifen-inducible Cre mice with Myh11-driven smooth muscle cells expression integrated in chromosome 2 (Jackson Laboratory, strain # 037658) allows studies in both male and female mice. Previous animal studies showed attenuated Ang II–induced hypertension in female mice compared with male littermates. This makes it difficult to study the protective effect of CypD depletion in females, which have already significant protection. We did not notice sex differences in CypD expression. Previous studies did not reveal sex differences in body weight, lifespan, and behavioral activity in response to CypD depletion. Other studies found that global CypD deletion can impair fatty acid β-oxidation and stimulate glucose metabolism. Women utilize fatty acids more as a primary energy source, while men rely more on carbohydrates for energy, and mitochondria from females have lower oxidative stress than males suggesting a potential sex difference in CypD function. Proteomic studies showed very little difference between males and females in mitochondrial antioxidant proteins and fatty acid oxidation enzymes, which may suggest a potential role for the post-translational modifications in sex-specific mitochondrial functions. We suggest that future studies must elucidate the potential sex differences in the pathogenic CypD post-translational modifications such as cysteine S-glutathionylation and lysine acetylation. , The second limitation of this study is dealing with the use of the Ang II model. Future studies must be directed to test the CypD function in volume-mediated DOCA-salt hypertension and salt-induced hypertension. The third limitation of this study deals with the focus on aortic physiology, which does not reflect the microvascular function. Meanwhile, resistant vessels such as arteries and microvasculature define the vascular peripheral resistance and, therefore, arterial pressure in hypertension. Previous studies showed impaired endothelial-dependent relaxation both in microvasculature, resistant arteries and conduit vessels such as aorta (see ). We have recently shown that protection from mitochondrial oxidative stress preserves endothelial-dependent relaxation in mesenteric arteries in the Ang II model of hypertension. Meanwhile, the recovery of endothelial function may vary due to distinct metabolic conditions of these vessels and differences in the regulation of endothelial-dependent dilation. Future studies are needed to define the role of CypD in the pathophysiological alterations of relaxation/contraction of resistant vessels and microvasculature. Fourth, our studies were limited to 3- to 5-month-old mice having CypD depletion for 2 months only. Future studies must test the potential off-target and systemic effects of long-term CypD depletion or CypD inhibition in adult and aged animals. Other limitations include the weakness of the data in respiration studies ( ) due to a low number of samples in denuded aortas groups, the lack of blood pressure tracing for the entire period of the study, and the lack of whole vessel images in Ec CypDKO and Smc CypDKO studies ( ). Future studies should include more than 6 samples per group in metabolic studies, analysis of blood pressure during the entire study period, and more thorough histopathological analysis. Endothelial-smooth muscle cell interaction is important in vascular homeostasis, blood vessel tone, and blood pressure regulation. , This is mediated by direct cell-to-cell contact and through paracrine signaling. Our data showed an intriguing “metabolic” crosstalk between endothelial and smooth muscle cells. We found that depletion of endothelial CypD reduces Ang II–induced endothelial glycolysis (intact aorta minus denuded aorta) by 2.1-fold and diminishes smooth muscle cell glycolysis (denuded aortas) by 1.34-fold. Interestingly, depletion of smooth muscle CypD was also not limited to the effect on smooth muscle glycolysis (2.3-fold), but it also reduced endothelial cell glycolysis (1.53-fold). It is not clear whether this is a direct metabolic interaction or a result of redox crosstalk. Oxidative stress in smooth muscle cells promotes redox alterations in endothelial cells, and vice versa endothelial oxidative stress promotes redox-dependent smooth muscle cell activation, differentiation, and hypertrophy. Vascular oxidative stress was inhibited in both Ec CypDKO and Smc CypDKO mice; therefore, cell-specific CypD depletion had the “global” antioxidant effect on the entire vasculature. This antioxidant effect of CypD depletion can attenuate the Ang II–induced glycolysis not only in specific cells but in the entire vasculature due to direct redox regulation of HIF-1α and glycolysis. Meanwhile, recent studies showed that increased lactate can directly affect vascular cell functions, and diminished lactate production in endothelial or smooth muscle cells can substantially reduce total vascular levels of lactate and, therefore, attenuate the lactate-mediated vascular alterations. , Interestingly, males exhibit higher glycolytic activity in blood vessels compared with females, which is in line with higher mitochondrial activity, lower oxidative stress, and renin–angiotensin–aldosterone system , in females compared with males. Meanwhile, the specific role of mitochondria and CypD in these redox and metabolic vascular alterations needs further investigation. Despite significant progress in mitochondrial studies, there are many critical gaps in knowledge, which hinder clinical translation of targeting CypD. In this work, we used a preventive model and showed that endothelial and smooth muscle cell CypD depletion significantly prevents Ang II–induced vascular dysfunction. Meanwhile, we do not know whether CypD depletion or CypD inhibition after onset of hypertension is beneficial. We may anticipate that blocking CypD can stop disease progression; however, it is not clear whether this would rescue or improve vascular function. We have described that CypD depletion or CypD deacetylation attenuates endothelial dysfunction and hypertension , ; however, we do not know the specific molecular mechanisms of CypD activation. It is conceivable that targeting “activated” CypD can be more beneficial rather than blocking all CypD in the whole body. Preventive studies using CypD depletion do not allow us to define the causative role of specific pathogenic mechanisms. Development of animal models with “activated” CypD can provide invaluable information regarding specific mitochondrial and cellular pathogenic pathways. This would allow to define the causative role of specific CypD post-translational modifications and help us with the development of pharmacological approaches to specific targeting of “activated” CypD. Nonimmunosuppressive CypD blockers based on cyclosporine derivatives were developed by Novartis and NeuroVive Pharmaceutical, which are promising in cardiovascular clinical studies. Clinical translation of these drugs was hindered by off-target effects, potentially, due to inhibition of CypD peptidyl-prolyl cis-trans isomerase activity. CypD acetylation leads to a “gain of function” promoting mPTP opening, and specific targeting of acetylated CypD may be beneficial in cardiovascular disease. It is possible that specific binding to the CypD acetylation site can block the detrimental CypD functions without an off-target effect on the CypD homeostatic role. This can provide an important basis for the development of new nonimmunosuppressive CypD inhibitors such as NV556, which can be promising for future clinical studies. Mitochondrial dysfunction is associated with hypertension and cardiovascular conditions; however, the specific molecular mechanisms of mitochondrial dysfunction and their causative role are not clear. Understanding these molecular mechanisms is important for the development of new therapies. Mitochondria are critical in cellular metabolism and function, and a new concept suggests that mitochondria are a common pathobiological target for multiple cardiovascular risk factors. Multiple pathophysiological pathways, therefore, cooperatively induce mitochondrial dysfunction leading to metabolic alterations and oxidative stress, driving vascular epigenetic and phenotypic dysregulation. In this respect, alterations of “master” regulators of mitochondrial function such as CypD can provide both mechanistic insight and novel therapeutic targets. We suggest that strategies directed to block pathogenic CypD pathways may have therapeutic potential in vascular dysfunction, hypertension, and hypertensive end-organ damage.
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Variation in the gut microbiota during the early developmental stages of common carp ( | 52e429e0-ccdb-48d9-9b0d-87f32628a50a | 11468302 | Microbiology[mh] | The vertebrate gut microbiota has been widely studied in recent years, and a series of studies have shown that the host gut microbe systems are large and constantly changing . As ancient vertebrates, fish were initially thought to be aquatic animals without stable endogenous microorganisms. However, with the development of DNA sequencing and bioinformatics technology, relevant studies on the gut microbiota of various fish have been reported, which have shown that changes in the fish gut microbiota are a complex process . After hatching, the microbiota can colonize in gut, and the composition, abundance and diversity of the fish gut microbiota also change with development . The specialized gut microbiota and related gut morphology enable fish species to tolerate resource fluctuations differently . Fish gut microbiota has a variety of functions, including nutritional effects , barrier effects , immune effects , influence on fish disease outbreaks , promotion of host development and other functions . Factors that affect the gut microbiota of fish include developmental stage , dietary composition , habitat and the surrounding environment . Studies on fish gut microbiota have also revealed the effects of gut microbiota on fish growth and metabolism , reproduction and behavior , providing new insights for the improvement of related fish farming issues . Therefore, it is of great significance to explore the patterns of fish gut microbiota change. As one of the factors affecting the gut microbiota of fish, developmental process has been reported in a variety of species, including zebrafish ( Danio rerio ) , cardinalfish ( Ostorhinchus fasciatus ) , channel catfish ( Ictalurus punctatus ) , Atlantic cod ( Gadus morhua ) , Nile tilapia ( Oreochromis niloticus ) , grass carp ( Ctenopharyngodon idella ), Chinese perch ( Siniperca chuatsi ), and southern catfish ( Silurus meridionalis ) . Studies have shown that, compared with other developmental stages, the larvae and juveniles of common carp are more susceptible to factors such as living environment (mainly pond water and pond bottom sediment), feed conversion and disease outbreak, resulting in considerable changes in the gut microbiota . The composition and succession of the gut microbiota in larval and juvenile common carp affect their nutrition, immunity, growth and development, which has important research value and significance . Bakke et al. reported the composition of gut microbiota during the development of juvenile Atlantic cod, and found that gut microbiota changes with age, which may be caused by different selection pressures during gut system development . Giatsis et al. reported the correlation between intestinal flora and environmental factors during the growth of juvenile tilapia, and found that compared with the microorganisms in feed, the flora in water environment is more similar to intestinal flora, and there are more OTUs . Meanwhile, Giatsis et al. elucidated the changes in gut microbiota during the development of juvenile tilapia in different aquaculture systems, and found significant differences in gut microbiota composition among different aquaculture systems . Recently, many factors have been reported to influence the gut microbiota of common carp, including intestinal tapeworms , deltamethrin , and dechlorane . However, there are few reports on the influence of the early developmental stage of common carp on the composition of the gut microbiota. In this study, 9 time points during the early development of common carp were selected to study the composition of the gut microbiota at different stages and its correlation with the microbial flora in feed and pond water. Our study provides evidence for changes in the gut microbiota of common carp during early development, highlighting the influence of fish developmental stages on the gut microbiota .
Incubation and rearing of experimental fish All the larvae and juvenile fish used in the study were obtained from the Jinan Agricultural Technology Extension Service Center, where the fertilization, hatching and breeding of the broodstock were completed. Ten pairs of healthy common carp broodstock were selected and injected with chorionic gonadotropin and luteinizing hormone-releasing hormone A2 under the pectoral fin to promote egg spawning and fertilization. The common carp broodstock injected with hormones were placed in a breeding pond with sterilized brown flakes as substrate for oviposition. The fertilized eggs were incubated naturally in the pond. Most larvae were fed cooled sterilized soy milk on the second day after hatching, fine-grain flour feed on the seventh day after initial feeding, large-grain flour feed on the 28th day after initial feeding, and conventional commercial feed on the 50th day after initial feeding until the end of sampling.
All the larvae and juvenile fish used in the study were obtained from the Jinan Agricultural Technology Extension Service Center, where the fertilization, hatching and breeding of the broodstock were completed. Ten pairs of healthy common carp broodstock were selected and injected with chorionic gonadotropin and luteinizing hormone-releasing hormone A2 under the pectoral fin to promote egg spawning and fertilization. The common carp broodstock injected with hormones were placed in a breeding pond with sterilized brown flakes as substrate for oviposition. The fertilized eggs were incubated naturally in the pond. Most larvae were fed cooled sterilized soy milk on the second day after hatching, fine-grain flour feed on the seventh day after initial feeding, large-grain flour feed on the 28th day after initial feeding, and conventional commercial feed on the 50th day after initial feeding until the end of sampling.
Fertilized eggs, larvae and juveniles of common carp at different stages of development were collected from the pond (Fig. A). About 8 h after fertilization of the fish eggs, they were quickly treated with 0.1% benzalkonium bromide for 1 min, washed 3 times with 0.68% NaCl disinfection solution for 3 min each time, and frozen at -80℃ for later use. Common carp larvae that were in the yolk sac stage approximately 24 h after hatching and larvae and juvenile fish on the 1,3,7 and 14 days after initial feeding were rapidly treated with 0.1% benzalkonium bromide for 1 min. Then like fish eggs, juvenile fish washed three times with sterilized 0.68% NaCl solution for 3 min each time and frozen for use at -80℃. Larval and juvenile carp on the 21, 28, 42, and 63 days after initial feeding were cleaned with 0.68% NaCl and their body surface was wiped with 75% ethanol, and then anesthetized by immersion in a 100 mg/L solution of MS222 (Sigma). The intestinal tract was dissected aseptically and frozen at -80 °C for use after the intestinal contents were collected. Pond water was taken at the key time points of larval and juvenile common carp development, which were the fertilized egg stage, soy milk pouring period (7 days after initial feeding), pond phytoplankton foraging period (14 days after initial feeding), flour feeding period (21 days after initial feeding), pond settling period (28 days after initial feeding), and feed feeding period (63 days after initial feeding). 1500 ml water was extracted from 0.5 m below the surface at three different positions in the pond and taken to the laboratory in a sterilized bottle. The bacteria were recovered by centrifugation at 4 °C and 13,000 rpm for 15 min, and frozen at -80 °C. In the feed conversion period, fine-grain flour feed, large-grain flour feed and conventional commercial feed were collected, divided into sterilization tubes and frozen for use at -80℃. The statistics for the different samples are shown in Table .
The work was performed by Suzhou Jinweizhi Biotechnology Co., Ltd. Bacterial genomic DNA was extracted using a Tiangen soil genome extraction kit, and DNA concentration and quality were determined by a Qubit 2.0 fluorometer. PCR amplification was performed with the forward primer CCTACGGRRBGCASCAGKVRVGAAT and reverse primer GGACTACNVGGGTWTCTAATCC targeting the V3–V4 variable regions of the 16 S gene. The quality of the amplification product was assessed using an Agilent 2100 bioanalyzer, and the library concentration was detected by a Qubit 2.0 fluorometer and PE300 sequencing was performed by the Illumina MiSeq sequencing platform.
The forward and reverse reads obtained by Paired-end sequencing were first assembled and connected in pairs, and then the sequencing data were quality-controlled. Sequences less than 200 bp in length and chimeric sequences were removed, and the final sequences were assigned to operational taxonomic units (OTUs). VSEARCH was used to perform cluster analysis of sequences with 97% similarity as the threshold (the 16 S rRNA reference database used for comparison was SILVA), and the representative OTU sequences were analyzed by species taxonomy using the RDP classifier Bayesian algorithm. Based on the OTU analysis results, the data were analyzed informatically. A rank– abundance plot was constructed using R language, and a rarefaction curve was plotted using QIIME. The abundance of flora was calculated using the ACE ( http://www.mothur.org/wiki/ACE ) and Chao1 ( http://www.mothur.org/wiki/Chao ) indices. The flora diversity was calculated with the Shannon ( http://www.mothur.org/wiki/Shannon ) and Simpson ( http://www.mothur.org/wiki/Simpson ) indices. Good’s coverage ( http://www.mothur.org/wiki/Coverage ) was used for sequencing depth calculation, and the software for analysis was QIIME. Statistical analysis Statistical significance was assessed using one-way analysis of t-tests in GraphPad Prism 6. All data were normally distributed, and P < 0.05 was considered statistically significant.
Statistical significance was assessed using one-way analysis of t-tests in GraphPad Prism 6. All data were normally distributed, and P < 0.05 was considered statistically significant.
The diversity and abundance of the gut bacterial community in common carp at the early developmental stage In this study, common carp at the fertilized egg stage, yolk sac stage, and 1, 3, 14, 21, 28, 42 and 63 days after initial feeding were selected as samples (Fig. A-K). Genomic DNA was extracted from common carp, feed and pond water samples under different treatments (Table ). The concentration and quality of genomic DNA in the samples was measured and met the requirements (Table ). The final effective sequences were obtained by removing primers and linker sequences, bases with mass values less than 20 at both ends, sequences with lengths less than 200 bp, and chimeric sequences (Table ). The length statistics of effective sequences showed that most of the effective sequences ranged from 430 to 470 bp, among which the number of sequences between 435 and 445 bp and 455–465 bp was the highest (Fig. A). We classified the valid data as OTUs, and the number of OTUs varied greatly among different samples. The number of species in feed samples was the lowest, followed by fish samples, and the number of species in pond water samples was the highest (Table ). The rarefaction curve was plotted by taking the number of effective sequences of samples as the abscissa and the OTU type classified by effective sequences as the ordinate (Fig. B). With the increase in the number of samples, the rarefaction curve of all samples tended to flatten off, indicating that the amount of sequencing data of samples was reasonable and could reflect the composition of bacteria in the samples. Based on the OTU analysis results, informatics analysis was conducted, and a rank– abundance plot (Fig. B) was constructed. The curve width of the feed group was narrower, and the declining trend was faster. The curve width of pond water samples was larger, and the declining trend was slower. The carp samples were intermediate between the feed group and the pond water group in terms of declining trend and curve width. The results showed that the species abundance of pond water samples was the highest, the species evenness of the feed group was the highest, and the carp samples were in the intermediate position. We also calculated alpha-diversity index statistics for different samples (Table ) and constructed boxplots of Shannon index and Chao1 index differences among sample groups (Fig. C and D). The results showed that the diversity and abundance of the samples varied with the development process.
In this study, common carp at the fertilized egg stage, yolk sac stage, and 1, 3, 14, 21, 28, 42 and 63 days after initial feeding were selected as samples (Fig. A-K). Genomic DNA was extracted from common carp, feed and pond water samples under different treatments (Table ). The concentration and quality of genomic DNA in the samples was measured and met the requirements (Table ). The final effective sequences were obtained by removing primers and linker sequences, bases with mass values less than 20 at both ends, sequences with lengths less than 200 bp, and chimeric sequences (Table ). The length statistics of effective sequences showed that most of the effective sequences ranged from 430 to 470 bp, among which the number of sequences between 435 and 445 bp and 455–465 bp was the highest (Fig. A). We classified the valid data as OTUs, and the number of OTUs varied greatly among different samples. The number of species in feed samples was the lowest, followed by fish samples, and the number of species in pond water samples was the highest (Table ). The rarefaction curve was plotted by taking the number of effective sequences of samples as the abscissa and the OTU type classified by effective sequences as the ordinate (Fig. B). With the increase in the number of samples, the rarefaction curve of all samples tended to flatten off, indicating that the amount of sequencing data of samples was reasonable and could reflect the composition of bacteria in the samples. Based on the OTU analysis results, informatics analysis was conducted, and a rank– abundance plot (Fig. B) was constructed. The curve width of the feed group was narrower, and the declining trend was faster. The curve width of pond water samples was larger, and the declining trend was slower. The carp samples were intermediate between the feed group and the pond water group in terms of declining trend and curve width. The results showed that the species abundance of pond water samples was the highest, the species evenness of the feed group was the highest, and the carp samples were in the intermediate position. We also calculated alpha-diversity index statistics for different samples (Table ) and constructed boxplots of Shannon index and Chao1 index differences among sample groups (Fig. C and D). The results showed that the diversity and abundance of the samples varied with the development process.
To investigate the changes in the gut microbiota during the early development of common carp, we analyzed the taxonomic changes in the gut microbiota at the phylum, genus and species levels during development from fertilized eggs to 63 days after initial of feeding. At the taxonomic level of phyla (Fig. A), Proteobacteria, Cyanobacteria, Firmicutes and Actinobacteria occurred in all fish samples, but their relative abundances changed with the development process. For example, Proteobacteria and Firmicutes increased first and then decreased twice in a row with common carp development. The species with high abundances also changed at different developmental stages. For example, from Bacteroidetes and Proteobacteria at the CCE and CCY stages to Proteobacteria at CC1, CC3, CC14, from Proteobacteria and Cyanobacteria at CC21, to Proteobacteria and Fusobacteria at CC28. There were also some differences in the number of taxa in different developmental stages. The CC1 and CC3 stages had the most taxa (20 taxa each), the CC14 and CC28 stages had the fewest taxa (12 and 11 taxa, respectively), and the remaining stages had 13–15 taxa. At the genus level (Fig. B), only Pseudomonas occurred in all fish samples, but the relative abundance of Pseudomonas varied greatly at different developmental stages, showing a first increasing and then decreasing trend two consecutive times. Excluding unclassified and ambiguous taxa, the relative abundances of most genera varied with developmental stage. At the species level (Fig. C), there were different types of gut microbiota at different stages, with relatively few species at CCY, CC63 and CC28. Moreover, the species with high abundance varied in different developmental stages. For example, Sphingomonas sp. LYH-20 and Chroococcopsis gigantean SAG 12.99 occurred in the CCE stage. The species found in the CCY stage was Gyrodactylus salaris (gyrodactylosis fluke), and those found in the CC1 stage were Shewanella putrefaciens , Comamonas testosteroni , Comamonas aquatica , Oryza meyeriana and Exiguobacterium undae . The results showed that the composition of the gut microbiota changed with development.
Subsequently, the similarities and differences of the samples were analyzed. The heatmap analysis was conducted based on the 30 OTUs with the highest abundance (Fig. A). It was found that the similarity among pond water samples was high, and the similarity between CCE and CCY samples was high, and these samples clustered together with pond water samples. The similarity among feed samples was also high, and CC1 and feed samples were clustered together. The remaining fish samples were more similar and clustered together. Subsequently, we conducted UPGMA tree analysis (Fig. ), weighted UniFrac distance matrix analysis (Fig. B), principal coordinate analysis (PCoA) (Fig. A), and non-metric multidimensional scaling (NMDS) analysis (Fig. B) for the common carp-related samples. UPGMA tree analysis showed that the difference between the microbiota in the gut, pond water and feed was reflected in the fact that the common carp samples were clustered with pond water samples and then with feed samples. Except for 9 samples from CC28, CC42 and CC63, the common carp samples were clustered first within groups and then between groups. On the one hand, the differences between groups were greater than the differences within groups. On the other hand, the common carp samples were different from the pond water samples and feed samples, reflecting the difference between the carp samples and other nonbiological samples. The weighted UniFrac distance matrix heatmap (Fig. C) showed that the differences between the common carp samples and other samples were significantly higher than the differences among the common carp samples, indicating that the differences between the common carp samples and other samples were more significant than the differences among different developmental stages. PCoA and NMDS analysis showed that pond water samples were clustered together, feed samples were clustered together, and carp samples were basically clustered together. However, the CCE, CCY and CC1 samples were more concentrated and closer to the pond water samples, reflecting the difference between the carp samples and environmental samples. The most likely reason for this difference was host selection pressure, which is consistent with previous reports . The comparative analysis between the common carp samples and the pond water samples showed that the gut microbiota of larval and juvenile common carp was different from that of pond water (Table ). Common carp samples, pond water samples and feed samples were further combined, and intergroup analysis of similarities (ANOSIM) showed that the composition of microbiota between common carp samples and pond water samples and between carp samples and feed samples were significantly different (Fig. A-C), indicating that the construction of the gut microbiota of fish was more influenced by the host during development. Thus, the microbiota structure was related to the host development stage, and environmental factors, including the pond water and feed, had less influence on the fish gut microbiota than the host. This result was consistent with the research of gibel carp . To further explore the differences between groups of common carp samples at adjacent developmental stages, we analyzed the differences in the five bacterial genera with the largest differences between groups at two adjacent developmental stages (Fig. A-H). Core microbiota in the intestinal tract of juvenile common carp during development A petal diagram of common bacteria in all common carp samples were made (Fig. A). There was only one common OTU in all common carp samples, which was annotated to the class Gammaproteobacteria, but the abundance in different samples varied significantly (one-way ANOVA, P < 0.0001). This bacterium played an important role in juvenile common carp, but it could not be identified to the species level, so it was difficult to determine its specific role in the development, nutrition and immunity of common carp. As the differences within groups were significantly smaller than the differences between groups, the results of the petal diagram of carp samples at each sampling time point (Fig. B) showed that there were 26 OTUs, among which 3 were annotated to species, 10 to genus, 11 to family, 1 to order, and 1 to class. The number of reads with common OTUs accounted for 49.1% of the total. Shewanella putrefaciens was one of the common microorganisms with different abundances in samples at different times. CC1 and CC3 had the highest S. putrefaciens abundances. However, this bacterial species was not detected in feed samples, and only pond water sample W63 contained a very small amount of this bacterium, indicating that S. putrefaciens occurs in fish samples, and its relative abundance changed continuously during development. As S. putrefaciens was present as the core bacterium in this study, it must play an important role in the early development of juvenile common carp. The petals diagram of OTUs in the pond water samples (Fig. C) showed that there are 62 species of OTUs in all the pond water samples. The average number of reads contained in 62 OTUs accounted for 48.5% of the total reads, and there were some differences among different samples, ranging from 28.1 to 68.1%. There are 15 common OTUs annotated to species, 21 to genus, 20 to family, 4 to order, and 2 to class.
A petal diagram of common bacteria in all common carp samples were made (Fig. A). There was only one common OTU in all common carp samples, which was annotated to the class Gammaproteobacteria, but the abundance in different samples varied significantly (one-way ANOVA, P < 0.0001). This bacterium played an important role in juvenile common carp, but it could not be identified to the species level, so it was difficult to determine its specific role in the development, nutrition and immunity of common carp. As the differences within groups were significantly smaller than the differences between groups, the results of the petal diagram of carp samples at each sampling time point (Fig. B) showed that there were 26 OTUs, among which 3 were annotated to species, 10 to genus, 11 to family, 1 to order, and 1 to class. The number of reads with common OTUs accounted for 49.1% of the total. Shewanella putrefaciens was one of the common microorganisms with different abundances in samples at different times. CC1 and CC3 had the highest S. putrefaciens abundances. However, this bacterial species was not detected in feed samples, and only pond water sample W63 contained a very small amount of this bacterium, indicating that S. putrefaciens occurs in fish samples, and its relative abundance changed continuously during development. As S. putrefaciens was present as the core bacterium in this study, it must play an important role in the early development of juvenile common carp. The petals diagram of OTUs in the pond water samples (Fig. C) showed that there are 62 species of OTUs in all the pond water samples. The average number of reads contained in 62 OTUs accounted for 48.5% of the total reads, and there were some differences among different samples, ranging from 28.1 to 68.1%. There are 15 common OTUs annotated to species, 21 to genus, 20 to family, 4 to order, and 2 to class.
The gut microbiota plays an important role in the nutrition, immunity and development of fish. However, there are few reports on the changes of gut microbiota at early developmental stages of common carp. Thus, the gut microbiota of common carp during the early developmental stages and its correlation with the feed and pond water flora were studied in the present study, which may be helpful for the disease prevention and healthy farming of common carp. The results showed that the gut microbiota of common carp changed continuously and mildly during the early stages of development. Similar results were found in Atlantic salmon ( Salmo salar ) and gibel carp ( Carassius auratus gibelio ) , however, the changes of gut microbiota tended to be stable in the adult stages of gibel carp and zebrafish . Bledsoe et al. found that during early development the gut microbiota diversity of channel catfish showed a significant difference between 3 days and 65 days after hatching and between 65 days and 125 days after hatching . Giatsis et al. also found that there were significant differences in the gut microbiota of the juvenile at different developmental stages in a circulating aquaculture system . These results showed that the gut microbiota of juvenile fish had a series of dynamic changes along with the development process. Proteobacteria, Cyanobacteria, Firmicutes and Actinomycetes were present in all samples of common carp, but their relative abundance changed with the development process of fish. This finding is similar to the composition of gut microbiota in the early developmental stages of Atlantic salmon ( Salmo salar ) and pikeperch ( Sander lucioperca ) , indicating that Proteobacteria is a necessary part of the gut microbiota in the early development process of fish. According to the results of PCoA and NMDS analysis, the microflora composition of CCE, CCY and CC1 samples of common carp was more similar to that of pond water samples. 66.5% of OTUs in CCE also appeared in WE, and the number of reads contained in CCE accounted for 95.9% of the total reads, indicating that the water environment played an important role in the gut microbiota of common carp. The results were consistent with the reports of many kinds of other fishes . In the early development process of common carp, the abundance of Cyanobacteria showed a trend of first increasing and then decreasing. Meanwhile, Cyanobacteria were the main bacterial species in the feed, indicating that the feed flora have an impact on the gut microbiota of fish, and have an important impact on the health of fish . However, the host selection plays a dominant role with the development of common carp, and the gut microbiota composition of common carp gradually shows significant differences from the environmental flora. This finding is also consistent with the development trend of intestinal bacterial communities in Southern Catfish .
The gut microbiota of common carp changed dynamically with the development of juvenile fish, and the changes continued until at least 63 days after initial feeding. The early gut microbiota may come from external environment. The similarity between gut microbiota and water environment flora decreased with the development process, and there was a certain core flora in the gut of common carp, indicating that the gut of common carp had a selective effect on environmental flora, and host selection pressure was an important factor affecting gut microbiota. Therefore, the study provided basic data for the changes of intestinal flora in the early stage of carp development. Furthermore, the fish microbiota can be changed through adding of related prebiotics in the early stage of development, which may treatment for fish related diseases and improve fish health .
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
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Histological ageing of fractures in infants: a practical algorithm for assessing infants suspected of accidental or non‐accidental injury | b087a3b7-757f-4b61-9684-cf71cb0bb31f | 6618162 | Pathology[mh] | Recognition of fractures in life and at autopsy is a key element in the assessment of infants believed to have suffered accidental or non‐accidental injury. Radiological skeletal survey (SS) is the current method of choice in detecting fractures in life. Follow‐up SS increases the likelihood of fracture detection in live children, , but as progressive healing does not occur post‐mortem, radiological detection of recent fractures post‐mortem is more challenging, although more sensitive techniques that require doses of radiation that could not be given to live infants [e.g. whole‐body computerised tomography (CT)] can be employed. , However, while radiology detects overt and unsuspected fractures in dead infants, many may be missed. , , , Significantly, it is fractures that most closely correlate with NAI (e.g. posterior rib and metaphyseal) that are commonly missed. , , Further evidence of fracture can be obtained at autopsy, , but naked eye examination also misses key fractures. Part of the full investigation of fractures detected/suspected at autopsy is histological examination of the bone in order to: decide if bone injury has occurred; age fractures relative to the time of death; and determine whether there is an abnormality of the bone (e.g. osteogenesis imperfecta, osteoporosis, vitamin D deficiency) that might make bones more easily fractured. It is accepted that post‐mortem histological examination of infant bones can detect fractures not seen radiologically. , , , Optimising detection of fractures is key, as multiple fractures and fractures of certain bones/parts of bones (e.g. posterior ribs, limb bone metaphyses) carry a high correlation with NAI and have causational implications. , , , , The causational significance of demonstrating fracture types is well reported, , , and we recently demonstrated how routine sampling of apparently unfractured bones might disclose key, unsuspected fractures. Ageing fractures is complementary to their detection. In the absence of underlying bone disease, fractures of multiple ages strongly correlate with NAI. Distinguishing ante‐ from post‐mortem fractures and placing fractures within a temporal landscape can assist in testing witness statements and contribute to understanding the chronology of events prior to death. However, while there are time‐lines for the processes of fracture healing in experimental animals and experiential evidence of similar timelines in humans, , , , there are no systematic studies documented in such a way as to help histopathologists with limited knowledge of histological bone biology to age fractures in infants. Here we describe the results of a 32‐year study to generate a practical tabular database allowing recognition of histological characteristics of fracture healing for assessing fracture age. The starting point was a data set of eligible fractures from cases received in the University of Manchester's Osteoarticular Pathology laboratory (UMOAP) from January 1985 to December 1998, analysed in 1999. Thereafter cases were added and the accumulated data analysed every 2 years. This paper describes the final data set from the 2017 audit. The study was terminated at the end of 2016, as there had been no material changes in the data set for three consecutive audits (i.e. since 2011).
Fractures from infants (≦12 months) were sent to UMOAP by forensic and paediatric pathologists. In every case employed in this study the age of the fracture (the interval between fracturing event and death) was documented. This took the form of a precise history and fractures confirmed radiologically. It is very uncommon to acquire such evidence in cases of NAI, but less so in real or claimed accidental injury. All cases were documented anonymised of all patient details except age and fracture site (bone and position within that bone) by one specialist osteoarticular pathologist (A.F.). They included single and multiple fractures from the same individual, including individuals with fractures of different known ages. The data set analysed in 1999 consisted of 99 fractures from 27 infants. During the subsequent 18 years a further 70 fractures were added from 25 infants. The rarity of having timed fracturing events in cases of NAI, and accidental injuries being uncommon in this age group, is reflected in there being only 169 fractures in this study from post‐mortem examination of ~3200 fractures of infants in UMOAP during the same period. In some cases, in any one infant, evidenced timing was available for a proportion of the fractures only and in some for more than one episode of fracturing. All tissue was decalcified in 10% formic acid under radiological control, and resultant tissue blocks were sectioned and stained with H&E and MSB. Underlying bone disease that might affect the rate of healing (e.g. osteoporosis/vitamin D deficiency) was excluded histologically. From 1985, all eligible fractures were documented for the presence of histological features , , , that, from animal studies and reported cases in adults and infants, reflected the progressive processes of fracture healing. These were: Haemorrhage in and around the fracture line Visible strands of fibrin in/adjacent to the fracture line Polymorph infiltrate between the bone ends and within haemorrhage Macrophage infiltrate in the fracture line/adjacent marrow Granulation tissue formation Osteocyte loss Osteoclasts removing cortical/trabecular bone at fracture sites Condensation of mesenchyme Early woven bone formation Distinct bone trabeculae and cartilage nodules Calcification Fracture union Organisation of primary callus and deposition of lamellar bone Normal bone structure restored Data were tabulated to show the time prior to death at which each feature was seen and the proportion of fractures from each time‐point showing the feature. The time‐points were largely self‐selecting by the number of fractures, each time‐point having to have at least four fractures from at least two infants. After 1998, all data (including new cases added in period) were summated every 2 years and an audit performed comparing the ‘new database’ with that of 2 years earlier. While this led to changes in consecutive databases, most of the changes were caused by the increasing number of samples resulting in increased numbers of time‐points. However, from the 2011 audit (cases to December 2010), no changes at all were made to the database despite adding further cases. As per the original protocol, the study was terminated after three successive unchanged 2‐yearly audits at the end of 2016.
The age of the infants did not conform to a conventional Gaussian distribution, two‐thirds being less than 6 months old. The median was 4.1 months and the range 3 weeks to 11.9 months (M:F = 28:24). Data from the Tabulated Analyses The full 2017 data set recording the appearance, presence and disappearance of each histological feature and the number of cases showing that feature tabulated against time from death in Figure . The data indicate a reproducible and universal sequence of histologically defined events as healing progresses, including haemorrhage; clot formation; inflammatory cell infiltration; granulation tissue formation; stimulation of mesenchymal stem cells; production of matrix: appositional (on pre‐existing bone surfaces), de‐novo (in fibrous tissue) or endochondral (on surface of cartilage‐like callus); osteoclastic/osteoblastic bone remodelling with lamellar bone formation; and return of a more normal structure. Features of progression varied between cases, presumably through biological variation, but were remarkably consistent in different fractures from the same individual. A Review of the Histological Features Originally Used for the Study Haemorrhage The presence of RBC within the fracture line (Figure A) is used to assess if a fracture is ante‐ or post‐mortem [it is generally accepted that post‐mortem fractures (including CPR‐induced) do not bleed significantly]. Notably, some fractures occurring shortly before death had no RBC in the cortical component of the fracture line, but showed haemorrhage into, and distorting, immediately adjacent marrow and/or periosteal/subperiosteal tissues. Never having seen haemorrhage displace marrow or penetrate the periosteum in post‐mortem or CPR‐induced fractures, or loss of RBC in the presence of identifiable fibrin, we hypothesise that RBC in unclotted blood may be lost from the cortical component of the fracture site as part of tissue removal and processing, but that this does not indicate a post‐mortem fracture. Based on these findings, we have redefined ante‐mortem haemorrhage to include significant medullary or periosteal haemorrhage with or without RBC in the cortical fracture line. Osteocyte loss In keeping with the literature, osteocyte loss occurred in fractures at 7 days. However, our findings highlight osteocyte necrosis in cortical/trabecular bone at fracture edges from 1 h following fracture (see Figures and B). Our experience is that this pattern of osteocyte loss is never seen in post‐mortem fractures, thus osteocyte loss indicates an ante‐mortem fracture. Fibrin formation Distinct strands (pink on H&E, orange‐red on MSB) are universally seen at 12 h, increasing appreciably over 24 h (Figure A,C), and thereafter disappearing as other processes become dominant. Polymorph infiltrate This could be difficult to appreciate in its early stages because of marrow and blood neutrophils, but was very noticeable at the periphery of areas of haemorrhage by 18 h. It is short‐lived. Macrophage infiltrate Macrophages appeared between bone ends as blood clot transitioned into true callus. It is not a universal finding, and adds little to the assessment of ageing in fractures. Granulation tissue formation Fibroblast ingrowth was the earliest evidence of granulation tissue formation, followed by capillary proliferation and increasing collagen deposition. Osteoclasis Osteoclasis is variable. There was a consistent burst of osteoclastic bone erosion throughout the fracture from days 3–7. However, in infants with metaphyseal fractures, cortical osteoclasis occurred much earlier (24–36 h; Figure D). Mesenchymal condensation and woven bone formation Mesenchymal condensation and stromal cell proliferation occurred in the medulla (Figure E,F) and periosteum (Figure C). This was followed by more distinct non‐mineralised bone‐like tissue formed into crude trabeculae, on bone surfaces and de‐novo (Figure G). Some had a hybrid osteochondral morphology, consistent with previous findings. While visible on H&E‐stained sections, new osteoid was more obvious with MSB, standing out from background tissue as pale blue cords (Figure F,G). It was seen universally by 5 days, increasing to 14 days. Bony trabeculae and cartilage nodules Transition from indistinct cords of woven osteoid/osteochondral material to trabeculae of bone and cartilage nodules (Figure H,I) occurred by 8–14 days, increasing to 21 days. Cartilage was particularly prominent in rib fractures and occasionally was the only periosteal callus material adjacent to fracture lines. Calcification Calcification leads to variation in the colour within osteoid trabeculae in H&E sections (pink, mottled ‘dirty’ grey/pink, or blue/pink) (Figure I,J). It was seen in most fractures between 15 and 21 days and in all by 22–28 days. Fracture union All cases showed bridging periosteal bony/cartilaginous fracture callus by 22–28 days. Early remodelling Deposition of lamellar bone on pre‐existing woven bone or cartilage nodules was taken as the first sign of remodelling towards a normal bone microstructure. Best identified in polarising light (Figure K1), lamellar bone was never seen before 28 days and always by 36 days, increasing thereafter. Lamellar bone also exhibited surface osteoblasts and appeared red/blue on MSB (Figure K2). Evidence of bone restoration towards a normal structure Return towards the structure of ‘normal’ bone was clearly established by 92 days after fracture, after which differential histological ageing became difficult. Mobile fracture sites Mobile fractures, particularly rib fractures, often showed healing reactions of different ages. We hypothesise that this is due to recurrent trauma at the fracture site consequent upon motion. In this setting, we found that the periosteal healing reaction away from the fracture line most accurately reflected the fracture's age. Refractures Refractures are recognised by a fracture line passing completely through existing fracture callus (Figure L). While the complexity of combined fracture responses means that it is not always possible to age a refracture, by definition the presence of refracture indicates a second, later fracturing event. Metaphyseal fractures Many fractures were metaphyseal, typically of anterior and posterior ribs and the long limb bones. The metaphysis contains a cartilage/bone interface, a site of weakness. Forceful pulling and twisting can cause fractures along the interface, which are well described in the literature. , , , There are two features that need stressing when ageing metaphyseal fractures: fractures through the growth plate cartilage do not show features of repair and cannot be aged; and most metaphyseal fractures propagated through bone at their periphery. Here the healing process was identical to bone elsewhere (Figure M,N,O). Periosteum The periosteum was frequently damaged during fracturing, and healing responses appeared to have exactly the same histological progression to those in the medulla. A periosteal reaction was sometimes seen in the absence of fracturing.
The full 2017 data set recording the appearance, presence and disappearance of each histological feature and the number of cases showing that feature tabulated against time from death in Figure . The data indicate a reproducible and universal sequence of histologically defined events as healing progresses, including haemorrhage; clot formation; inflammatory cell infiltration; granulation tissue formation; stimulation of mesenchymal stem cells; production of matrix: appositional (on pre‐existing bone surfaces), de‐novo (in fibrous tissue) or endochondral (on surface of cartilage‐like callus); osteoclastic/osteoblastic bone remodelling with lamellar bone formation; and return of a more normal structure. Features of progression varied between cases, presumably through biological variation, but were remarkably consistent in different fractures from the same individual.
Haemorrhage The presence of RBC within the fracture line (Figure A) is used to assess if a fracture is ante‐ or post‐mortem [it is generally accepted that post‐mortem fractures (including CPR‐induced) do not bleed significantly]. Notably, some fractures occurring shortly before death had no RBC in the cortical component of the fracture line, but showed haemorrhage into, and distorting, immediately adjacent marrow and/or periosteal/subperiosteal tissues. Never having seen haemorrhage displace marrow or penetrate the periosteum in post‐mortem or CPR‐induced fractures, or loss of RBC in the presence of identifiable fibrin, we hypothesise that RBC in unclotted blood may be lost from the cortical component of the fracture site as part of tissue removal and processing, but that this does not indicate a post‐mortem fracture. Based on these findings, we have redefined ante‐mortem haemorrhage to include significant medullary or periosteal haemorrhage with or without RBC in the cortical fracture line. Osteocyte loss In keeping with the literature, osteocyte loss occurred in fractures at 7 days. However, our findings highlight osteocyte necrosis in cortical/trabecular bone at fracture edges from 1 h following fracture (see Figures and B). Our experience is that this pattern of osteocyte loss is never seen in post‐mortem fractures, thus osteocyte loss indicates an ante‐mortem fracture. Fibrin formation Distinct strands (pink on H&E, orange‐red on MSB) are universally seen at 12 h, increasing appreciably over 24 h (Figure A,C), and thereafter disappearing as other processes become dominant. Polymorph infiltrate This could be difficult to appreciate in its early stages because of marrow and blood neutrophils, but was very noticeable at the periphery of areas of haemorrhage by 18 h. It is short‐lived. Macrophage infiltrate Macrophages appeared between bone ends as blood clot transitioned into true callus. It is not a universal finding, and adds little to the assessment of ageing in fractures. Granulation tissue formation Fibroblast ingrowth was the earliest evidence of granulation tissue formation, followed by capillary proliferation and increasing collagen deposition. Osteoclasis Osteoclasis is variable. There was a consistent burst of osteoclastic bone erosion throughout the fracture from days 3–7. However, in infants with metaphyseal fractures, cortical osteoclasis occurred much earlier (24–36 h; Figure D). Mesenchymal condensation and woven bone formation Mesenchymal condensation and stromal cell proliferation occurred in the medulla (Figure E,F) and periosteum (Figure C). This was followed by more distinct non‐mineralised bone‐like tissue formed into crude trabeculae, on bone surfaces and de‐novo (Figure G). Some had a hybrid osteochondral morphology, consistent with previous findings. While visible on H&E‐stained sections, new osteoid was more obvious with MSB, standing out from background tissue as pale blue cords (Figure F,G). It was seen universally by 5 days, increasing to 14 days. Bony trabeculae and cartilage nodules Transition from indistinct cords of woven osteoid/osteochondral material to trabeculae of bone and cartilage nodules (Figure H,I) occurred by 8–14 days, increasing to 21 days. Cartilage was particularly prominent in rib fractures and occasionally was the only periosteal callus material adjacent to fracture lines. Calcification Calcification leads to variation in the colour within osteoid trabeculae in H&E sections (pink, mottled ‘dirty’ grey/pink, or blue/pink) (Figure I,J). It was seen in most fractures between 15 and 21 days and in all by 22–28 days. Fracture union All cases showed bridging periosteal bony/cartilaginous fracture callus by 22–28 days. Early remodelling Deposition of lamellar bone on pre‐existing woven bone or cartilage nodules was taken as the first sign of remodelling towards a normal bone microstructure. Best identified in polarising light (Figure K1), lamellar bone was never seen before 28 days and always by 36 days, increasing thereafter. Lamellar bone also exhibited surface osteoblasts and appeared red/blue on MSB (Figure K2). Evidence of bone restoration towards a normal structure Return towards the structure of ‘normal’ bone was clearly established by 92 days after fracture, after which differential histological ageing became difficult. Mobile fracture sites Mobile fractures, particularly rib fractures, often showed healing reactions of different ages. We hypothesise that this is due to recurrent trauma at the fracture site consequent upon motion. In this setting, we found that the periosteal healing reaction away from the fracture line most accurately reflected the fracture's age. Refractures Refractures are recognised by a fracture line passing completely through existing fracture callus (Figure L). While the complexity of combined fracture responses means that it is not always possible to age a refracture, by definition the presence of refracture indicates a second, later fracturing event. Metaphyseal fractures Many fractures were metaphyseal, typically of anterior and posterior ribs and the long limb bones. The metaphysis contains a cartilage/bone interface, a site of weakness. Forceful pulling and twisting can cause fractures along the interface, which are well described in the literature. , , , There are two features that need stressing when ageing metaphyseal fractures: fractures through the growth plate cartilage do not show features of repair and cannot be aged; and most metaphyseal fractures propagated through bone at their periphery. Here the healing process was identical to bone elsewhere (Figure M,N,O). Periosteum The periosteum was frequently damaged during fracturing, and healing responses appeared to have exactly the same histological progression to those in the medulla. A periosteal reaction was sometimes seen in the absence of fracturing.
The presence of RBC within the fracture line (Figure A) is used to assess if a fracture is ante‐ or post‐mortem [it is generally accepted that post‐mortem fractures (including CPR‐induced) do not bleed significantly]. Notably, some fractures occurring shortly before death had no RBC in the cortical component of the fracture line, but showed haemorrhage into, and distorting, immediately adjacent marrow and/or periosteal/subperiosteal tissues. Never having seen haemorrhage displace marrow or penetrate the periosteum in post‐mortem or CPR‐induced fractures, or loss of RBC in the presence of identifiable fibrin, we hypothesise that RBC in unclotted blood may be lost from the cortical component of the fracture site as part of tissue removal and processing, but that this does not indicate a post‐mortem fracture. Based on these findings, we have redefined ante‐mortem haemorrhage to include significant medullary or periosteal haemorrhage with or without RBC in the cortical fracture line.
In keeping with the literature, osteocyte loss occurred in fractures at 7 days. However, our findings highlight osteocyte necrosis in cortical/trabecular bone at fracture edges from 1 h following fracture (see Figures and B). Our experience is that this pattern of osteocyte loss is never seen in post‐mortem fractures, thus osteocyte loss indicates an ante‐mortem fracture.
Distinct strands (pink on H&E, orange‐red on MSB) are universally seen at 12 h, increasing appreciably over 24 h (Figure A,C), and thereafter disappearing as other processes become dominant.
This could be difficult to appreciate in its early stages because of marrow and blood neutrophils, but was very noticeable at the periphery of areas of haemorrhage by 18 h. It is short‐lived.
Macrophages appeared between bone ends as blood clot transitioned into true callus. It is not a universal finding, and adds little to the assessment of ageing in fractures.
Fibroblast ingrowth was the earliest evidence of granulation tissue formation, followed by capillary proliferation and increasing collagen deposition.
Osteoclasis is variable. There was a consistent burst of osteoclastic bone erosion throughout the fracture from days 3–7. However, in infants with metaphyseal fractures, cortical osteoclasis occurred much earlier (24–36 h; Figure D).
Mesenchymal condensation and stromal cell proliferation occurred in the medulla (Figure E,F) and periosteum (Figure C). This was followed by more distinct non‐mineralised bone‐like tissue formed into crude trabeculae, on bone surfaces and de‐novo (Figure G). Some had a hybrid osteochondral morphology, consistent with previous findings. While visible on H&E‐stained sections, new osteoid was more obvious with MSB, standing out from background tissue as pale blue cords (Figure F,G). It was seen universally by 5 days, increasing to 14 days.
Transition from indistinct cords of woven osteoid/osteochondral material to trabeculae of bone and cartilage nodules (Figure H,I) occurred by 8–14 days, increasing to 21 days. Cartilage was particularly prominent in rib fractures and occasionally was the only periosteal callus material adjacent to fracture lines.
Calcification leads to variation in the colour within osteoid trabeculae in H&E sections (pink, mottled ‘dirty’ grey/pink, or blue/pink) (Figure I,J). It was seen in most fractures between 15 and 21 days and in all by 22–28 days.
All cases showed bridging periosteal bony/cartilaginous fracture callus by 22–28 days.
Deposition of lamellar bone on pre‐existing woven bone or cartilage nodules was taken as the first sign of remodelling towards a normal bone microstructure. Best identified in polarising light (Figure K1), lamellar bone was never seen before 28 days and always by 36 days, increasing thereafter. Lamellar bone also exhibited surface osteoblasts and appeared red/blue on MSB (Figure K2).
Return towards the structure of ‘normal’ bone was clearly established by 92 days after fracture, after which differential histological ageing became difficult.
Mobile fractures, particularly rib fractures, often showed healing reactions of different ages. We hypothesise that this is due to recurrent trauma at the fracture site consequent upon motion. In this setting, we found that the periosteal healing reaction away from the fracture line most accurately reflected the fracture's age.
Refractures are recognised by a fracture line passing completely through existing fracture callus (Figure L). While the complexity of combined fracture responses means that it is not always possible to age a refracture, by definition the presence of refracture indicates a second, later fracturing event.
Many fractures were metaphyseal, typically of anterior and posterior ribs and the long limb bones. The metaphysis contains a cartilage/bone interface, a site of weakness. Forceful pulling and twisting can cause fractures along the interface, which are well described in the literature. , , , There are two features that need stressing when ageing metaphyseal fractures: fractures through the growth plate cartilage do not show features of repair and cannot be aged; and most metaphyseal fractures propagated through bone at their periphery. Here the healing process was identical to bone elsewhere (Figure M,N,O).
The periosteum was frequently damaged during fracturing, and healing responses appeared to have exactly the same histological progression to those in the medulla. A periosteal reaction was sometimes seen in the absence of fracturing.
We present here a 32‐year study of histological findings and their relative time of occurrence in 169 fractures of known age from 52 infants. An initial tabulated data set based on 99 fractures from 26 infants was drawn up in 1999 and a rolling audit performed for a further 18 years. This study was conducted to provide histopathologists examining fractures from cases of accidental or non‐accidental injury with a practical tool to age traumatic injuries of bones. While others have given valuable data on ageing fractures based on clinical observation, , , , this is the first study to provide background data tabulated by fracture age, histological feature and the proportion of cases showing that feature at defined time‐points following fracture. The tabulated data can be considered an algorithm which, if one or more of the features described is recognised and then singly or in combination mapped onto the table, can be used to define an age range within which the fracture occurred. Similarly, if a feature is not present, the fracture has either not reached, or has passed, the age at which that specific feature becomes universally seen or disappears. Data presented here indicate that all fractures appear to go through similar linear patterns of histological changes, with biological variation influencing differences in the rate of healing between individuals. Because it is not possible to know where within the biological spectrum an individual might lie fractures cannot be aged exactly, but our data indicate that a time range, during which the fracture occurred, can be given with a high degree of certainty. Age ranges for fractures of different ages can overlap; however, from examination of fractures of different known ages from the same individual, histology allows fractures to be clearly recognised as being of different ages. In addition to producing a novel dating algorithm for infant fractures we report other new findings. We have shown: loss of osteocytes from bone at the periphery of very early fractures (1–2 h). All our observational data suggest that this cell death is energy‐requiring, conforming with current understanding of bone cell biology where osteocyte apoptosis is a necessary precursor of osteoclast‐driven bone remodelling; , while metaphyseal fractures are difficult to age, if they involve bone the bone‐healing process matches that of fractures in other sites. Fractures involving only cartilage or non‐vascularised primary spongiosa cannot be aged with any certainty; and periosteum can be injured without fracturing and heals with the same processes over the same time‐frame as periosteal reactions associated with fractures.
None. Professor Freemont has presented evidence in writing and in court based on these data.
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We Need to Know: A Call for Interdisciplinary Education on COVID-19 | 3be0ff20-0ef5-4330-a85f-d7d95e249aaa | 7905425 | Patient Education as Topic[mh] | The 2019 novel coronavirus (COVID-19) is quickly changing the way we live our day-to-day lives. While the pandemic has impacted everyone, one cannot ignore the physiologic consequences of the lockdown. In particular, older adults constitute a vulnerable population that tends to be more severely impacted by social distancing, isolation, and quarantine ( ). Ongoing research brings to light an array of symptomatology in older COVID-19 patients including frailty syndrome and symptoms of loneliness such as depression, cognitive dysfunction, and disability ( , ). Prolonged periods of rest and immobility result in cachexia and sarcopenia ( ) and, in older adults, the chronic inflammation and susceptibility to frailty leave them at a higher risk for developing these symptoms. Additionally, social isolation puts older adults at a greater risk of developing depression and anxiety ( ). As research uncovers the various impacts of this pandemic, there is a need to provide up-to-date, interdisciplinary information to the general public and healthcare professionals in a way that is safe and efficient. One such solution is a webinar, which can help lift the veil of uncertainty and misinformation by providing reliable facts ( , ). Webinars can shape the way professionals practice medicine — a value that is more important now than ever before ( , ). With their remote nature and ease of access, webinars serve as an essential tool for education and healthcare promotion during a pandemic.
Thirteen students from seven universities, recruited through the Geriatric Workforce Enhancement Programs nationwide, comprised the planning committee for COVID: Decoded. The committee met via Zoom for nine weeks, selected seven topics, and explored experts in each field as potential speakers. Table represents the selected topics and speakers. The advertising committee collaborated with a graphic designer to create a flyer disseminated through email and social media platforms. The targeted audience included students in undergraduate and graduate programs across the nation from a wide variety of fields. The committee emphasized the interdisciplinary aspect of the webinar as a key component to illustrate how COVID-19 has affected and continues to impact all social determinants of health. The conference utilized Zoom’s Webinar feature, under Saint Louis University’s license, which allowed up to 1,000 participants. The conference occurred from 10 am to 5 pm CST. The keynote speaker was allotted 35 minutes to speak, with all subsequent speakers assigned 20 minutes. Each speaker had a 10 minute Q&A following their presentation, followed by 10 minutes of flexible time. At lunch, the committee presented a student-made personal protective equipment (PPE) educational video. The conference concluded with a full-panel Q&A, in which all participant questions were submitted through Zoom’s Q&A feature and moderated by members of the committee throughout the day. An assigned timekeeper monitored the clock. The committee attached pre-conference surveys (PrCS) as part of the conference registration. Post-conference surveys were distributed via email and were optional. Respondents were matched by email address to analyze pre- and post-conference variables. The variables analyzed included feeling overwhelmed by COVID-19, the perceived bias of the conference, confidence discussing COVID-19 with friends and family, and the six of the seven topics individually addressed by each presenter. These variables were compared using paired sample t-tests with 95% confidence intervals on SAS→ Studio 9.4.
The pre-conference survey was completed by 250 individuals, representing graduate students (34%), professional degree-seeking students (31.7%), or undergraduate students (24.5%) from 43 different universities across every region of the United States and seven additional countries. The PrCS data indicated that prior to the webinar, over half (53.1%) of registrants agreed with the statement: “I feel overwhelmed when thinking about COVID-19.” When responding to the statement “I feel confident discussing COVID-19 with friends and family”, over one-third (35.3%) selected either neutral, disagree, or strongly disagree. Additionally, more than 2 in 3 registrants (69.9%) agreed with the statement, “I think there is a lot of information about COVID-19 and it is difficult to know whom to trust.” The survey asked individuals to evaluate their knowledge on COVID-19’s impact on various topics using a 5-point Likert scale. These results are shown in Figure and only include those individuals who also responded to the post-conference survey (PoCS) for comparison. Of the 250 PrCS responders, 57 completed the PoCS yielding a response rate of 22.8% and represented a similar demographic of students: graduate students (31.6%), professional degree-seeking students (38.6%), and undergraduate students (15.8%). Nearly three-quarters of the 57 individuals (73.6%) felt neutral or overwhelmed by COVID-19 before the conference, but half of these individuals then disagreed or strongly disagreed with feeling overwhelmed by COVID-19 afterward (Figure ). Nearly all (98.2%) felt confident to some degree discussing COVID-19 with friends and family following conference attendance, a 60% increase from PrCS data. The conference was felt to be a trusted source of information, as 54 participants (94.7%) did not feel there was an obvious bias or political agenda present in the presentations. As seen in Figure , the mean Likert score of all six topics increased with statistical significance following participation in the conference (p<0.0005). Lastly, all respondents (100%) would recommend either part (31.6%) or the entire conference (68.4%) to a friend or colleague.
Based on the conference registration survey data, it is evident that there is a need for interdisciplinary education on COVID-19. The majority of our registrants felt overwhelmed when thinking about COVID-19 and felt it was difficult to know who to trust for valid information. The analysis of this data found a statistically significant increase in knowledge across the six topics that were discussed in the webinar. Of the registrants who completed both surveys, there was a 50% reduction in the number of individuals who felt overwhelmed when thinking about COVID-19. These results indicate that clear and unbiased information increased confidence in discussing the virus and decreased feelings of being overwhelmed when thinking about COVID-19. Utilizing an online webinar medium (i.e. Zoom) and advertising on numerous social media platforms led to successful recruitment and advertising efforts. COVID: Decoded reached students across the nation and international cities as it was accessible for participants in different time zones and provided flexibility in joining via telephone or computer. The conference encountered minimal technical difficulties, which can be attributed to specific areas in planning and execution. For example, speakers had an opportunity to participate in a practice session to gain comfort with Zoom’s features. Attendee user functions were restricted to minimize distractions. In addition, designating roles within the planning committee, such as Q&A moderators, technical support, and timekeepers, ensured a smooth transition throughout the entire conference. Suggestions that were provided by respondents included increasing time for speakers and Q&A sessions and limiting presentation duration to allow for more in-depth discussion. It is important to note that the analysis of collected data was limited due to a post-conference survey response rate of 22.8% and the erroneous omission of gerontology in both surveys.
There is a wealth of information surrounding the current COVID-19 pandemic, however, the response to this pandemic is attenuated by the misinformation and conflicting information spreading through various avenues, particularly on social media. While this is not uncommon during global pandemics, the lack of reliable information undermines public health efforts to follow good health and hygiene practices, which puts everyone at risk, particularly the vulnerable populations, including the geriatric population. Hence, the committee deemed it crucial to organize an interdisciplinary virtual conference to tackle the challenge of providing extensive, up-to-date information surrounding COVID-19. By addressing common coronavirus myths and elaborating on its impact on different spheres of society, the hope was to alleviate fears, increase authentic information about the pandemic from experts, and promote proper use of PPE to prevent the spread of the virus amongst the general population, which protects our vulnerable and immunocompromised groups. Our data analysis concluded that the webinar increased the level of comfort in confronting issues surrounding the ongoing pandemic by creating awareness about the virus attributes, PPE, economic impacts, and the widespread social pressures due to distancing from loved ones. COVID: Decoded was able to accomplish this by providing a platform for participants to learn and engage with a trusted source. Furthermore, COVID:Decoded’s online nature facilitated its widespread reach across national and international audiences. In the future, should a webinar be utilized to disperse COVID-19 related information, it is recommended that the presentation be limited as an overview to allot more time for Q&A to foster dialogue between participants and invited speakers. The increased interaction can allow for the topics most unclear to participants to be further explained.
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Incidence and Temporal Dynamics of Combined Infections in SARS-CoV-2-Infected Patients With Risk Factors for Severe Complications | 1797cb17-852e-496e-8042-008cd3af4db6 | 11932828 | Pathologic Processes[mh] | Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed an enormous global threat and is expected to remain an endemic infection. The clinical presentation of COVID-19 is diverse, and its severity ranges from asymptomatic cases to critical conditions associated with mortality. Risk factors associated with severe complications and fatality of COVID-19, such as age, obesity, smoking status and various underlying diseases, have been studied. Combined infection by microorganisms other than SARS-CoV-2 in COVID-19 patients has also been reported to be associated with increased mortality. COVID-19 renders infected patients vulnerable to infection by bacteria, fungi and other viruses due to impairment of the immune system by the infection itself and damage to the lung, in addition to the use of certain therapeutics, including steroids and antibiotics, for COVID-19 treatment. The overall combined infection rate in COVID-19 patients has been reported to be 0.6–45%. This wide variation stems from the various types of infections and causative pathogens, as well as geographic and demographic factors, which differ between studies. Coinfections at the initial presentation or secondary infectious complications during the clinical course are important in predicting and properly managing patients. Therefore, precisely defining the characteristics of combined infections in COVID-19 patients may improve the quality of care available for COVID-19 patients and determine the unique features of SARS-CoV-2 infection. This study aimed to characterize such combined infections in terms of their temporal sequence and type of infection by applying the most objective diagnostic methods in COVID-19 patients who had risk factors for severe complications and were hospitalized by national policy in South Korea.
Study design and subjects All patients who were aged ≥ 19 years with COVID-19, which was officially confirmed by SARS-CoV-2 real-time reverse transcription polymerase chain reaction (RT–PCR) or a rapid antigen assay, and who were hospitalized at four study hospitals (National Medical Center, Seoul Medical Center, Boramae Medical Center and Veterans Health Service Medical Center in Seoul, Korea) between May 1st, 2021, and April 30th, 2022, according to the government mandate (for patients who had severe COVID-19 at presentation or risk factors for severe complication such as underlying diseases and advanced age) were enrolled for screening. There were two Korean peak epidemics (4th and 5th waves) of COVID-19 during the study period, and the most prevalent variants were the delta and omicron variants, respectively. The clinical decision regarding patient care was made solely by the physicians in charge. Patients who underwent subsequent laboratory-based microbiologic tests within 3 months of hospitalization were screened among the initially enrolled patients, and the patients with positive test results were ultimately included in the final analysis. We excluded patients with a prior history of COVID-19 and those whose clinical course could not be followed because they were transferred from other hospitals at least 3 days after admission or because they were transferred to other hospitals during hospitalization. The tests used were blood culture, Mycobacterium tuberculosis tests (smear, culture and PCR), Aspergillus antigen assays, cytomegalovirus (CMV) PCR or antigenemia assays, and Pneumocystis jirovecii PCR. Data collection All the data were retrospectively collected from medical records. A positive microbiological test was interpreted as a true positive if the physician decided that the test was significant, and the patient was offered specific therapy ( ). Demographics such as age, sex, underlying disease status, and temporal data regarding the onset of COVID-19 symptoms, hospitalization and discharge were collected. The specific or ancillary medications for COVID-19 treatment, including corticosteroids and other antimicrobial agents, were reviewed. Definition The ‘combined infection’ encompassed both the infectious disease(s) presenting together with COVID-19 at admission (coinfection), which indicates an independent dual presence, and secondary infectious complications during the clinical course in COVID-19 patients. Bacteremia was defined if the usual pathogenic bacteria were isolated from at least one pair of blood cultures. In the case of the isolation of common contaminants, true bacteremia was defined when the physicians in charge treated the patients as having clinically meaningful bacteremia. Tuberculosis (TB) was defined as a positive culture or nucleic acid amplification test for M. tuberculosis in samples from clinically compatible patients. CMV disease was defined as positive CMV antigenemia or quantitative CMV PCR tests resulting in the administration of anti-CMV antiviral agents. P. jirovecii pneumonia (PJP) was defined as a positive PCR test for P. jirovecii in patients treated with trimethoprim-sulfamethoxazole or alternatives due to clinically suspected PJP. Invasive pulmonary aspergillosis (IPA) was defined as a positive aspergillosis antigen assay (galactomannan, GM) with an optical density ≥ 0.5 in blood sample combined with clinically suspected aspergillosis and compatible radiological findings, leading to the therapeutic administration of antifungal agents. The diagnostic criteria largely used Biomarkers-based Aspergillosis in Intensive Care Unit (ICU) diagnostic algorithm (BM-AspICU), but the cut-off of GM index in blood sample was 0.5 rather than 1.0. The diagnostic date of the coexisting infections was defined as the date when the sample with diagnostic value was obtained. The coinfections were categorized into three groups—community-acquired (≤ 2 days), early hospital-onset (> 2 and ≤ 30 days) and late hospital-onset (> 30 and ≤ 90 days)—regarding the date of hospital admission. The anti-COVID-19 drugs included nirmatrelvir/ritonavir, molnupiravir, remdesivir, regdanvimab, tocilizumab and baricitinib, which were available and permitted for use during the study period in South Korea. Statistical analysis For the statistical analysis, Student’s t -test was used for continuous variables, and the χ 2 test or Fisher’s exact test was used for categorical variables. The distribution of coinfections was analyzed using a box plot (IBM SPSS Statistics for Windows, version 26; IBM Corp., Armonk, NY, USA). All tests were two-tailed, and a P value < 0.05 was considered to indicate statistical significance. Ethics statement This study was approved by the Institutional Review Boards of Boramae Medical Center (No. 20-2021-53) and the other participating centers. The requirement for informed consent was waived because of the retrospective nature of this investigation and the minimal risk to the study subjects. Personal identifiers were removed before data processing, and this study complied with the tenets of the Declaration of Helsinki.
All patients who were aged ≥ 19 years with COVID-19, which was officially confirmed by SARS-CoV-2 real-time reverse transcription polymerase chain reaction (RT–PCR) or a rapid antigen assay, and who were hospitalized at four study hospitals (National Medical Center, Seoul Medical Center, Boramae Medical Center and Veterans Health Service Medical Center in Seoul, Korea) between May 1st, 2021, and April 30th, 2022, according to the government mandate (for patients who had severe COVID-19 at presentation or risk factors for severe complication such as underlying diseases and advanced age) were enrolled for screening. There were two Korean peak epidemics (4th and 5th waves) of COVID-19 during the study period, and the most prevalent variants were the delta and omicron variants, respectively. The clinical decision regarding patient care was made solely by the physicians in charge. Patients who underwent subsequent laboratory-based microbiologic tests within 3 months of hospitalization were screened among the initially enrolled patients, and the patients with positive test results were ultimately included in the final analysis. We excluded patients with a prior history of COVID-19 and those whose clinical course could not be followed because they were transferred from other hospitals at least 3 days after admission or because they were transferred to other hospitals during hospitalization. The tests used were blood culture, Mycobacterium tuberculosis tests (smear, culture and PCR), Aspergillus antigen assays, cytomegalovirus (CMV) PCR or antigenemia assays, and Pneumocystis jirovecii PCR.
All the data were retrospectively collected from medical records. A positive microbiological test was interpreted as a true positive if the physician decided that the test was significant, and the patient was offered specific therapy ( ). Demographics such as age, sex, underlying disease status, and temporal data regarding the onset of COVID-19 symptoms, hospitalization and discharge were collected. The specific or ancillary medications for COVID-19 treatment, including corticosteroids and other antimicrobial agents, were reviewed.
The ‘combined infection’ encompassed both the infectious disease(s) presenting together with COVID-19 at admission (coinfection), which indicates an independent dual presence, and secondary infectious complications during the clinical course in COVID-19 patients. Bacteremia was defined if the usual pathogenic bacteria were isolated from at least one pair of blood cultures. In the case of the isolation of common contaminants, true bacteremia was defined when the physicians in charge treated the patients as having clinically meaningful bacteremia. Tuberculosis (TB) was defined as a positive culture or nucleic acid amplification test for M. tuberculosis in samples from clinically compatible patients. CMV disease was defined as positive CMV antigenemia or quantitative CMV PCR tests resulting in the administration of anti-CMV antiviral agents. P. jirovecii pneumonia (PJP) was defined as a positive PCR test for P. jirovecii in patients treated with trimethoprim-sulfamethoxazole or alternatives due to clinically suspected PJP. Invasive pulmonary aspergillosis (IPA) was defined as a positive aspergillosis antigen assay (galactomannan, GM) with an optical density ≥ 0.5 in blood sample combined with clinically suspected aspergillosis and compatible radiological findings, leading to the therapeutic administration of antifungal agents. The diagnostic criteria largely used Biomarkers-based Aspergillosis in Intensive Care Unit (ICU) diagnostic algorithm (BM-AspICU), but the cut-off of GM index in blood sample was 0.5 rather than 1.0. The diagnostic date of the coexisting infections was defined as the date when the sample with diagnostic value was obtained. The coinfections were categorized into three groups—community-acquired (≤ 2 days), early hospital-onset (> 2 and ≤ 30 days) and late hospital-onset (> 30 and ≤ 90 days)—regarding the date of hospital admission. The anti-COVID-19 drugs included nirmatrelvir/ritonavir, molnupiravir, remdesivir, regdanvimab, tocilizumab and baricitinib, which were available and permitted for use during the study period in South Korea.
For the statistical analysis, Student’s t -test was used for continuous variables, and the χ 2 test or Fisher’s exact test was used for categorical variables. The distribution of coinfections was analyzed using a box plot (IBM SPSS Statistics for Windows, version 26; IBM Corp., Armonk, NY, USA). All tests were two-tailed, and a P value < 0.05 was considered to indicate statistical significance.
This study was approved by the Institutional Review Boards of Boramae Medical Center (No. 20-2021-53) and the other participating centers. The requirement for informed consent was waived because of the retrospective nature of this investigation and the minimal risk to the study subjects. Personal identifiers were removed before data processing, and this study complied with the tenets of the Declaration of Helsinki.
Study subjects A total of 16,967 patients with confirmed COVID-19 were hospitalized for one year during the study period at the four study hospitals. Among them, 2,432 (14.3%) patients underwent the specified microbiological tests according to the clinical decisions of the physicians in charge, 195 patients had positive test results, and 0.55% (94/16,967) of patients had clinically meaningful infections; consequently, these patients were administered specific antimicrobial treatment ( ) and were included in the final analysis. The median age was 71.5 (interquartile range [IQR], 61.75–78) years, and at least one comorbidity was present in 92.6% of the patients ( ). The severity scores showed that the median National Early Warning Score 2 (NEWS2) score at admission was 6 (IQR, 3–10), and the National Institutes of Health (NIH) severity scale score was above moderate for 85.0% of the patients, while 63.8% of the patients were critically ill. At least one anti-COVID-19 drug was administered to 83.0% of the patients, and dexamethasone 6 mg or an equivalent dose of other steroids was used in 81.9% of the patients. The in-hospital mortality rate was 46.8% (44/94). The 30-day mortality rate was 43.6% (i.e., 41 of the 76 patients followed). The 30-day mortality rate for the patients who had positive tests but were considered not to have clinically meaningful combined infections categorized in the study was 17.8% (18/101) which was lower than that of the study patients (46.8%, 44/94; P < 0.01). Combined infections The infections concurrently diagnosed in the COVID-19 patients at admission or during the hospital course included 70 cases of bacteremia (74.5%), 17 cases of fungemia (18.1%), 7 cases of CMV disease (18.1%), 7 cases of PJP (7.4%), 5 cases of TB (5.3%) and 4 cases of IPA (4.3%) ( ). Two or more coinfections were diagnosed in 12 (12.8%) patients. The proportions of patients with community-acquired (≤ 2 days), early hospital-onset (> 2 & ≤ 30 days), and late hospital-onset (> 30 & ≤ 90 days) infections were 11.7% (11/94), 72.3% (68/94) and 16.0% (15/94), respectively. The median duration from admission to the diagnosis of combined infections was 15 (IQR, 5–25) days. TB and bacteremia began to be identified in the early stages of hospitalization ( ). The median time from admission to TB diagnosis was 4 (IQR, 0–8.5) days. Only pulmonary TB was confirmed. Compared to the other combined infections, the TB group had a lower body mass index (mean 18.53, P = 0.027), lower NEWS2 score (mean 2.8, P = 0.041) and a greater percentage of patients with a low (asymptomatic to mild) NIH score ( P = 0.028) at admission ( ). The median time from admission to the onset of the 1st bacteremia episode was 9 (IQR, 1–19) days, and 77.1% (54/70) of the bacteremia cases were categorized as early hospital-onset (> 2 & ≤ 30 days) ( ). The infection foci of bacteremia were identified as primary bacteremia (26 cases, 37.1%), central line associated bloodstream infection (BSI, 21 cases, 30.0%), pneumonia (12 cases, 17.1%), urinary tract infection (UTI, 8 cases, 11.4%), intraabdominal infection (3 cases, 4.3%) and bone & joint infection (2 cases, 2.9%). No significant difference from the other combined infection groups in terms of patient characteristics, severity or COVID-19 treatment regimen was observed at admission ( ). Commonly isolated bacteria included coagulase-negative staphylococci (22%), Escherichia coli (13.4%), enterococci (13.4%), Klebsiella pneumoniae (12.2%), Staphylococcus aureus (11.0%), Pseudomonas aeruginosa (9.8%) and Acinetobacter baumannii (7.3%) in the order of frequency. Among the gram-negative bacteria, 41.5% (17/41) were multidrug resistant, and 12.2% (5/41) were carbapenem-resistant Enterobacterales . The proportion of multidrug-resistant gram-negative bacteria was 18.8% (3/16) in the community-acquired group, 56.5% (13/23) in the early hospital-onset group and 50% (1/2) in the late hospital-onset group. The were 3 cases having subsequent 2nd episode of bacteremia which were 1st methicillin-resistant S. aureus (MRSA) to 2nd methicillin-sensitive S. aureus , 1st Enterococcus to 2nd MRSA and 1st K. pneumoniae to 2nd vancomycin-sensitive Enterococcus respectively. The other combined infections tended to occur in the later phase of hospitalization ( ). Fungemia consisted of mostly candidemia (16 cases) and one case of Cryptococcus neoformans ( ). The earliest onset of fungemia occurred on the 6th day of hospitalization, and the median time from hospitalization to fungemia onset was 24 (IQR, 16.5–37.5) days. There were no significant differences in the characteristics of patients or the severity of COVID-19 or COVID-19 specific treatment regimens between patients with fungemia and those with other combined infections ( ). The median time from hospitalization to CMV disease diagnosis was 32 (IQR, 19–35) days. Compared with the other combined infection groups, the CMV group had a greater percentage of patients who used baricitinib for COVID-19 treatment (57.1%, P < 0.001) and a longer total hospital stay (mean 66.6 days, P = 0.018). The median time from hospitalization to PJP diagnosis was 31 (IQR, 15–33) days. Compared with the other combined infection groups, the PJP group had a lower mean age (52.7 years, P = 0.024) and included one human immunodeficiency virus (HIV) patient ( P < 0.001) and one end stage renal disease patient ( P = 0.021). The median time from hospitalization to IPA diagnosis was 16.5 (IQR, 10.8–17) days. Compared with those who received other combined infections, the percentage of patients who received baricitinib for COVID-19 treatment was greater (50%, P = 0.005), and the mean hospital stay was longer (97.3 days, P = 0.033).
A total of 16,967 patients with confirmed COVID-19 were hospitalized for one year during the study period at the four study hospitals. Among them, 2,432 (14.3%) patients underwent the specified microbiological tests according to the clinical decisions of the physicians in charge, 195 patients had positive test results, and 0.55% (94/16,967) of patients had clinically meaningful infections; consequently, these patients were administered specific antimicrobial treatment ( ) and were included in the final analysis. The median age was 71.5 (interquartile range [IQR], 61.75–78) years, and at least one comorbidity was present in 92.6% of the patients ( ). The severity scores showed that the median National Early Warning Score 2 (NEWS2) score at admission was 6 (IQR, 3–10), and the National Institutes of Health (NIH) severity scale score was above moderate for 85.0% of the patients, while 63.8% of the patients were critically ill. At least one anti-COVID-19 drug was administered to 83.0% of the patients, and dexamethasone 6 mg or an equivalent dose of other steroids was used in 81.9% of the patients. The in-hospital mortality rate was 46.8% (44/94). The 30-day mortality rate was 43.6% (i.e., 41 of the 76 patients followed). The 30-day mortality rate for the patients who had positive tests but were considered not to have clinically meaningful combined infections categorized in the study was 17.8% (18/101) which was lower than that of the study patients (46.8%, 44/94; P < 0.01).
The infections concurrently diagnosed in the COVID-19 patients at admission or during the hospital course included 70 cases of bacteremia (74.5%), 17 cases of fungemia (18.1%), 7 cases of CMV disease (18.1%), 7 cases of PJP (7.4%), 5 cases of TB (5.3%) and 4 cases of IPA (4.3%) ( ). Two or more coinfections were diagnosed in 12 (12.8%) patients. The proportions of patients with community-acquired (≤ 2 days), early hospital-onset (> 2 & ≤ 30 days), and late hospital-onset (> 30 & ≤ 90 days) infections were 11.7% (11/94), 72.3% (68/94) and 16.0% (15/94), respectively. The median duration from admission to the diagnosis of combined infections was 15 (IQR, 5–25) days. TB and bacteremia began to be identified in the early stages of hospitalization ( ). The median time from admission to TB diagnosis was 4 (IQR, 0–8.5) days. Only pulmonary TB was confirmed. Compared to the other combined infections, the TB group had a lower body mass index (mean 18.53, P = 0.027), lower NEWS2 score (mean 2.8, P = 0.041) and a greater percentage of patients with a low (asymptomatic to mild) NIH score ( P = 0.028) at admission ( ). The median time from admission to the onset of the 1st bacteremia episode was 9 (IQR, 1–19) days, and 77.1% (54/70) of the bacteremia cases were categorized as early hospital-onset (> 2 & ≤ 30 days) ( ). The infection foci of bacteremia were identified as primary bacteremia (26 cases, 37.1%), central line associated bloodstream infection (BSI, 21 cases, 30.0%), pneumonia (12 cases, 17.1%), urinary tract infection (UTI, 8 cases, 11.4%), intraabdominal infection (3 cases, 4.3%) and bone & joint infection (2 cases, 2.9%). No significant difference from the other combined infection groups in terms of patient characteristics, severity or COVID-19 treatment regimen was observed at admission ( ). Commonly isolated bacteria included coagulase-negative staphylococci (22%), Escherichia coli (13.4%), enterococci (13.4%), Klebsiella pneumoniae (12.2%), Staphylococcus aureus (11.0%), Pseudomonas aeruginosa (9.8%) and Acinetobacter baumannii (7.3%) in the order of frequency. Among the gram-negative bacteria, 41.5% (17/41) were multidrug resistant, and 12.2% (5/41) were carbapenem-resistant Enterobacterales . The proportion of multidrug-resistant gram-negative bacteria was 18.8% (3/16) in the community-acquired group, 56.5% (13/23) in the early hospital-onset group and 50% (1/2) in the late hospital-onset group. The were 3 cases having subsequent 2nd episode of bacteremia which were 1st methicillin-resistant S. aureus (MRSA) to 2nd methicillin-sensitive S. aureus , 1st Enterococcus to 2nd MRSA and 1st K. pneumoniae to 2nd vancomycin-sensitive Enterococcus respectively. The other combined infections tended to occur in the later phase of hospitalization ( ). Fungemia consisted of mostly candidemia (16 cases) and one case of Cryptococcus neoformans ( ). The earliest onset of fungemia occurred on the 6th day of hospitalization, and the median time from hospitalization to fungemia onset was 24 (IQR, 16.5–37.5) days. There were no significant differences in the characteristics of patients or the severity of COVID-19 or COVID-19 specific treatment regimens between patients with fungemia and those with other combined infections ( ). The median time from hospitalization to CMV disease diagnosis was 32 (IQR, 19–35) days. Compared with the other combined infection groups, the CMV group had a greater percentage of patients who used baricitinib for COVID-19 treatment (57.1%, P < 0.001) and a longer total hospital stay (mean 66.6 days, P = 0.018). The median time from hospitalization to PJP diagnosis was 31 (IQR, 15–33) days. Compared with the other combined infection groups, the PJP group had a lower mean age (52.7 years, P = 0.024) and included one human immunodeficiency virus (HIV) patient ( P < 0.001) and one end stage renal disease patient ( P = 0.021). The median time from hospitalization to IPA diagnosis was 16.5 (IQR, 10.8–17) days. Compared with those who received other combined infections, the percentage of patients who received baricitinib for COVID-19 treatment was greater (50%, P = 0.005), and the mean hospital stay was longer (97.3 days, P = 0.033).
This was a multicenter study involving four major public referral hospitals dedicated to the care of a large volume of COVID-19 patients during the pandemic in South Korea and with the capability of intensive care. Our study revealed that among the study patients who had severe COVID-19 at presentation or who were minimally symptomatic but had risk factors for severe complications, such as underlying disease and advanced age, 14.3% of the patients needed further investigation for BSIs, TB, CMV disease, PJP and IPA, and clinically meaningful coinfections were diagnosed and treated in 0.55% of the patients. The combined infections were diagnosed within 2 days in 11.7% of the patients, between 2 and 30 days in 72.3% of the patients, and between 1 and 3 months in 16.0% of the patients. Bacteremia was a main issue of infection in our study. Several studies reported a bacteremia rate of 1.6% or 1.7% in COVID-19 patients, which was higher than that in COVID-19-negative patients. The incidence of bacteremia may be influenced by several factors, such as differences in severity or the presence of different risk factors in the study population. Community-acquired (10 cases, 14.3%) and early hospital-onset (54 cases, 77.1%) comprised 91.4% of the 70 bacteremia cases in our study. The source of bacteremia was assessed as primary bacteremia (26 cases, 37.1%), central line associated BSI (21 cases, 30.0%), pneumonia (12 cases, 17.1%), UTI (8 cases, 11.4%), intraabdominal infection (3 cases, 4.3%) and bone & joint infection (2 cases, 2.9%). Old age (median 71.5 years), presence of comorbidity (92.6%) and NIH severity above moderate at admission (85.0%) suggested that combined symptomatic infection of community origin with COVID-19 might lead to early hospital visit. However, the large proportion of primary bacteremia (26 cases, 37.1%) at admission pointed out that the clinicians need more effort to appropriately evaluate the diagnosis. The antibiotics resistance in each temporal stage might reflect the status of the community or of individual hospitals. Extended-spectrum beta-lactamase (ESBL)-producing E. coli bacteremia diagnosed within 2 days of hospitalization may reflect the ESBL-producing E. coli proportion of 24.6% among community-acquired UTI cases in South Korea. Early hospital-onset (< 2 & ≤ 30 days) bacteremia included antibiotic-resistant pathogens such as MRSA, vancomycin-resistant enterococci and multidrug-resistant gram-negative bacteria, which may be related with the length of hospitalization. In this study, the proportion of multidrug-resistant organisms (MDRO) increased with the duration of hospitalization. Witt et al. attribute this to factors such as increased use of medical devices, overuse of antibiotics and the strain on healthcare systems, which led to lapses in standard infection control practices and inadequate MDRO screening. These challenges have been reported as significant contributors to the rise in MDRO infections observed during and after the COVID-19 pandemic. The incidence of fungemia in COVID-19 patients also varies greatly from 0.14% to 34.9% according to the study population. Our study revealed no cases of fungemia within 48 hours of admission, and the mean time to onset of fungemia was 26.8 days after admission. This finding is consistent with previous studies indicating the correlation of fungemia with an increasing length of hospitalization. One case of cryptococcal fungemia was observed in the early-onset period of our study. Considering the quarantined hospitalization of the patient, COVID-19 itself or the related treatment might have triggered this overt presentation. TB and COVID-19 markedly differ in the chronicity of the pathogenesis. There is no evidence that TB enhances SARS-CoV-2 infection, and vice versa. The combined presence of active TB with COVID-19 is known to be a risk factor for increased mortality. TB has also been diagnosed simultaneously with or subsequent to a COVID-19 diagnosis. While some studies have reported increased severity of known active TB before COVID-19, there is controversy regarding whether TB diagnosed simultaneously with or subsequent to COVID-19 infection is a risk factor for severe complications. In our study, 20% (1/5) of pulmonary TB cases were diagnosed simultaneously (within 2 days) with COVID-19, and the others were diagnosed a median of 4 days after admission. The TB incidence in five of the 16,967 enrolled patients in the general population in South Korea was close to the total TB incidence. Our data indicate that coincidental occurrence of TB in COVID-19 patients is not unusual, but vigilant suspicion of TB is needed to avoid a missed diagnosis. Reactivation of CMV in COVID-19 patients may be due to direct injury to cellular immunity caused by SARS-CoV-2 infection as well as the use of immunosuppressive treatment. The use of corticosteroids for more than 15 days or the use of high-dose corticosteroids in COVID-19 was a risk factor for CMV reactivation/disease during ICU stays. In our study, the mean duration of steroid use in CMV-treated patients was 15.6 days, and 71.4% of CMV-treated patients received ≥ 6 mg dexamethasone. Univariate analysis showed that 57.1% of CMV-treated patients received baricitinib ( P < 0.001). CMV disease was reported to be related to the use of baricitinib in rheumatoid arthritis patients. Baricitinib has been known to be associated with serious infections as the mechanism of pharmacologic action implies, and CMV disease and IPA were such examples. However, the real-world data of baricitinib related infections are awaiting further investigations. Combined use of other immunosuppressive agents such as steroids and severe viral infection itself in COVID-19 must be considered in the interpretation of CMV disease or IPA under baricitinib use. The longer hospital stay in our patients with CMV disease or IPA might be related to the indication of baricitinib in COVID-19 which implies critical severity. The risk of PJP is known to be greater in patients with cancer, organ or hematopoietic stem cell transplant recipients, patients receiving treatment for rheumatoid disease or patients with impaired cell-mediated immunity. In non-HIV patients, the use of glucocorticoids is a well-known risk factor for PJP. In our study, all patients coinfected with PJP not only received corticosteroids for COVID-19 treatment but also included patients with HIV or solid organ transplant recipients. Chong et al. reported that the overall mortality in COVID-19 patients with PJP was 41.6%, whereas it was 14.3% in our study. COVID-19 and PJP are difficult to differentiate due to their similar clinical presentations. Since we used PCR to detect P. jirovecii , we might have overestimated the rate of PJP, resulting in a lower mortality rate. The younger age of our patients in the univariate analysis might be biased due to their immunosuppressive underlying diseases such HIV, connective tissue disease and kidney transplantation in young patients. Viral infection itself can cause coinfection involving IPA, and influenza and severe fever with thrombocytopenia syndrome are such examples. Current evidence indicates that SARS-CoV-2 infection is also associated with IPA. One study reported that the prevalence of IPA was 0–34.3% among COVID-19 patients in the ICU, with a mean prevalence of 10%. Black fungus or mucormycosis is also a key complication of COVID-19, but our study did not collect relevant data. Several studies on the combined infections in COVID-19 patients have been reported in South Korea. These studies included laboratory screening studies on combined respiratory pathogens in the same specimens, the evaluation of risk factors for MDRO in COVID-19 pneumonia, a case report of fatal fungal coinfection, bacterial coinfection in a single center (n = 367) and the analysis of risk factors for secondary infections (n = 348). Our study had the largest study population and analyzed combined infections and their time-dependent relationship in a multicenter setting. Our study may provide clinicians with a useful predictive tool for serious coinfections in COVID-19 care in a time progressive manner. We included BSI, TB, CMV disease, IPA and PJP in the analysis combined with the final clinical decision of physicians in the real-world practice. This study had a few limitations. First, we underestimated the overall incidence of combined infections in COVID-19 patients. However, our result for combined infection might represent the minimum value for each infection because we used the most objective diagnostic criteria. As we limited the number of target infections to five categories and used laboratory results as a diagnostic minimum, we underestimated the number of real combined infections, excluding other infections and clinically diagnostic infections. The diagnostic ambiguity and relatively low clinical significance of these methods in some infections led us to concentrate on several problematic infections. Both overestimation and underestimation are also possible for CMV, PJP and aspergillosis. As COVID-19 is not a classic host factor for these opportunistic infections, the current diagnostic criteria may not be applicable to COVID-19 patients. A physical barrier to performing timely relevant tests in patients who were strictly quarantined for COVID-19 was one of the clinical difficulties in the peak pandemic period. Therefore, our results need to be interpreted in the context of relative incidence. Second, the small number of our patients with positive combined infections led to insufficient statistical comparisons between the positive subgroups; consequently, our results were presented mostly descriptively. Nevertheless, most studies on combined infections in patients with COVID-19 have been case studies, and systematic analyses have only been published for a few types of combined infections. Our study has the advantage of being a multicenter study covering a large COVID-19 population. In summary, 14.3% of hospitalized COVID-19 patients with risk factors for severe complications needed further laboratory evaluation for combined infections, and laboratory-confirmed combined infections were detected in 0.55% of the patients. The combined infections included common community and nosocomial pathogens in relation to the length of hospitalization and the epidemiology of the community or hospital in addition to unusual pathogens such as CMV disease, PJP and IPA. Predicting the causative organisms based on the timing of coinfection and conducting appropriate clinical evaluations could help reduce COVID-19-related complications.
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Electronic medical records – The good, the bad and the ugly | 66382ad4-82ea-45cd-b591-5b8f51d6c4f3 | 7043175 | Ophthalmology[mh] | Medical records have a history of 4000 years in evolution and, in some form, have existed since the beginning of the practice of medicine. Some of the first medical records date back to Hippocrates in the 5 th century BC and medieval physicians. Formal medical records appeared in the nineteenth century in Europe in major teaching hospitals and were quickly adopted across the world. The modern medical record was developed in the 20 th century – data about each patient, including clinical data, was recorded, organized in a standardized format and stored. Major problems with traditional paper medical records include lack of standardization across physicians and healthcare facilities, poor searchability and loss of information. EMR has been in evolution for several decades now but continues to grossly miss the intended mark of efficient and personalized patient care. The first EMR was developed in 1972 by the Regenstreif Institute in the United States and was then welcomed as a major advancement in medical practice. The uptake, however, was low, the cost being a major constraint. The vital push came through the American Recovery and Reinvestment Act 2009, spearheaded by Barack Obama, which envisaged incentives to EMR users. Several EMR packages have since been developed and have become widely available across the world.
EMR is considered potentially one of the drivers for the transformation of healthcare. From a patient care perspective, EMR is expected to improve the accuracy of the information, support clinical decision-making and improve the accessibility of information for continuity of care. From an operational perspective, EMR should generate essential health care statistics crucial to the planning and management of health care services. User expectations from a good EMR are several – meticulous patient documentation, common templates and order sets, disease coding and billing, regulatory compliance, prevention of medication errors, clinical pathway utilization, optimized workflow, medico-legal defensibility, adaptive learning capability, simplicity, multiple input interfaces (notes, voice transcription, drawings, etc), incorporation of clinical images, seamless connectivity with clinical investigation platforms, input speed at the point of entry, and most importantly, data compilation for analysis and research, all with time-efficiency, and a user- and patient-friendly interface. Ideally, EMR should be on a single platform nationwide to enable interoperability and portability horizontally and vertically across the referral chain. Are computers and clinicians uneasy bedfellows? Probably not. Every sphere of life, including the practice of medicine, has seen extensive computerization and the present generation of doctors are extremely comfortable with digital technology. The uptake of EMR is on the rise and it is here to stay. In the United States, ophthalmologists have almost quadrupled their EMR use, from 19% in 2008 to 72% in 2016. The use of EMR is still in its infancy in India. The Government of India intends to introduce a uniform system of EMR. An expert committee set up by the government has developed “Electronic Health Record Standards for India”. With this as the background, there is an immense nascent potential for EMR in India. With major Indian ophthalmic institutes having developed their EMRs and using them in their routine daily practice, and their residents and fellows having been “trained on EMRs”, its use is only likely to increase.
The chief complaint against EMR is that it has undermined personalized face-to-face patient care and the vital doctor-patient interaction - the very soul of medicine - into a new check box-based doctor-computer-patient interaction. Abraham Verghese calls this an “iPatient” phenomenon. EMR was never designed to facilitate a personalized human narrative, logical thinking, and experience-based clinical analysis. Clinical reasoning being the backbone of a traditional doctor-patient interaction, “a medical record—whether paper or digital—must preserve the information that the physician carefully and thoughtfully elicits from the patient in a form that, above all, facilitates clinical reasoning.” Current EMRs do not. A new report from the National Academy of Medicine is revealing – on an average, nurses and doctors spend 50 percent of their workday treating the screen, not the patient, and the increased work burden associated with EMRs is one of the factors for physician burnout. A study of emergency room doctors revealed that putting information into the computer consumed more of their time than any other activity. Using a “click” of the computer mouse as the standard of measure, a doctor needed to make 6 clicks of the mouse to order an aspirin, 8 clicks to get a chest x-ray, 15 clicks to provide a prescription, etc., Over 40% of a typical 10-hour emergency room shift was devoted to data entry and 4,000 clicks of the computer mouse. Immense information on EMR results in high (data) noise to (clinical) signals ratio. Arnold Relman, former editor-in-chief of the New England Journal of Medicine and a physician with 6 decades of experience found EMR “lacking in coherent descriptions of his medical progress, or his complaints and state of mind” when he was a patient himself. EMRs seem to have adversely affected the clinical training as Ober and Applegate state, “Our residents often resemble air traffic controllers, focusing more on the logistics of arrivals and departures than on understanding the patient's journey”. They go on to quote a resident, “Education, rapport, compassion, bedside clinical reasoning, the physical exam, all seem to take a back seat in the current system”. EMRs seem to be badly designed to the do the job they are meant to do and seem to have failed to make patient care better, more efficient, or more satisfying for the patient or the doctor.
As there can never be a perfect spouse, there can never be a perfect EMR. EMRs must evolve and the potential users synchronously need to retrain themselves and change their mindset until a sweet spot is reached. “To develop an EMR that meets the needs of the physicians who will use it, we need to better understand how the physicians work, and develop the software with an eye toward solving real problems in practices rather than developing a solution looking for a problem.” Fortunately, India seems to be leading in the development of stand-alone ophthalmology EMRs, and that too with significant contributions from the users' right at the stage of EMR development. Sankara Nethralaya and Tata Consultancy Services (TCS) have together developed a comprehensive EMR system from scratch. It is natural for people to forget, but Anthony Vipin Das must remember that it took us a lot of effort to initiate and carry forward an in-house coding and development of EMR at the LV Prasad Eye Institute (LVPEI) about 10 years ago. It was meant to be a smart EMR, developed by the ophthalmologists and for the ophthalmologists, appropriately called eyeSmart. I feel redeemed that the seed that I had a small part is sowing and initially nurturing has now grown to be a fruit-bearing tree and is seamlessly used across the LVPEI network for patient care, administration and research. The current issue of the Indian Journal of Ophthalmology carries an article from the LVPEI group reporting their 8-year experience with eyeSmart and the accompanying commentary puts things in perspective. Robert Wachter states in his book The Digital Doctor – ”One of the great challenges in healthcare technology is that medicine is at once an enormous business and an exquisitely human endeavor; it requires the ruthless efficiency of the modern manufacturing plant and the gentle hand-holding of the parish priest; it is about science, but also about art; it is eminently quantifiable and yet stubbornly not.” An ideal EMR should harmoniously bring together the soul of medicine and cutting-edge informatics.
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Beyond surgery: Pre‐ and post‐operative care in children with ankyloglossia | 395e0bc9-c869-4771-b05d-d0c952014730 | 11788522 | Surgical Procedures, Operative[mh] | INTRODUCTION Ankyloglossia or tongue‐tie is a congenital condition, which occurs when the lingual frenulum is short, tight or thick, leading to restricted tongue movements and associated functional limitations during feeding, swallowing, articulation and breathing. , Ankyloglossia is reported in approximately 7% to 10% of infants, , and surgical intervention is often recommended to release tension of the lingual frenulum to improve tongue mobility and function. , Surgical intervention may involve frenotomy (incision to the frenulum), frenectomy (frenulum is removed) or frenuloplasty (frenulum is elongated). Historically, paediatricians, otolaryngologists and midwives would manage and treat ankyloglossia. In contemporary practice, there has been a significant increase in the use of laser‐assisted dental surgery for labial or lingual frenectomy surgical procedures by paediatric dentists. Although laser‐assisted surgery is considered safe and effective to resolve ankyloglossia, it can be associated with complications, such as pain, scarring, infection and re‐attachment of the lingual frenulum. , These complications may impact healing and outcomes for feeding and articulation. Pre‐ and post‐operative care is reported to improve the wound healing process. Wound healing has three phases: the inflammatory, proliferative and remodelling phases. During these phases, primary or secondary wound healing occurs. Primary healing refers to the close approximation of wound edges leading to closure and healing with minimal scarring. The goal of post‐operative wound care in ankyloglossia is to expedite complication‐free healing, to achieve optimal tongue mobility to facilitate functional improvements for feeding. Active wound management, in the form of stretching and strengthening exercises, can contribute to effective healing and reduce re‐attachment, leading to improved function and tongue mobility. Pre‐ and post‐operative care regimens are reported to improve wound healing and subsequent symptom resolution. Merkel‐Walsh and Overland highlighted the importance of two phases of post‐frenectomy care. The first stage includes active wound management by the surgeon to maintain wound integrity and prevent re‐attachment of tissues back to the original anatomy. The second component is neuromuscular re‐education, administered by therapists using different care regimens to help improve range of motion and reduce compensatory patterns due to fascial restrictions to subsequently reduce or resolve symptoms. Different types of care regimens include myofunctional exercises and therapy, stretching, chiropractic care, craniosacral therapy or bodywork and massage before and following surgery. , , Nevertheless, given the lack of a universally accepted protocol, exercises are inconsistently described in the literature, with limited high‐quality evidence available to select the most suitable care regime. , The lack of well‐established protocols and the corresponding lack of outcomes are evident contribute to healthcare provider confusion, and undermine the confidence of healthcare professionals in the effectiveness and reliability of pre‐ and/or post‐operative treatment plans. This makes it difficult for healthcare providers to assess the success or failure of these regimens, and hinders the ability to make informed decisions about patient care. A survey of paediatric otolaryngologists reported insufficient evidence to support any single post‐operative care regimen. Some clinicians prescribed pre‐ and/or post‐operative care regimens, whereas others did not, and the protocols prescribed by clinicians were inconsistent, , with no standard care regimen recommended. Although there is general acknowledgement that pre‐ and/or post‐surgical regimens may be effective to facilitate symptom resolution, there is a significant gap in knowledge and consensus with respect to the clinical protocols that are currently being utilised, as well as the accepted confidence and effectiveness of these various pre‐ and post‐operative care regimens. Previous reviews have discussed the outcomes of different surgical interventions for ankyloglossia ; no review to date, however, has amalgamated types of pre‐ and post‐operative care in ankyloglossia management, including healing and recovery outcomes. This scoping review aimed to summarise pre‐ and post‐operative care for ankyloglossia described in the literature to guide paediatric dentists and clinicians supporting children with ankyloglossia. 1.1 Objectives The objectives of this review were as follows: To summarise pre‐ and post‐operative care for paediatric clients who have undergone ankyloglossia surgery and To explore the relationship between pre‐ and post‐operative care and recovery outcomes in paediatric patients.
Objectives The objectives of this review were as follows: To summarise pre‐ and post‐operative care for paediatric clients who have undergone ankyloglossia surgery and To explore the relationship between pre‐ and post‐operative care and recovery outcomes in paediatric patients.
MATERIALS AND METHODS A scoping review was conducted to identify studies describing pre‐ and/or post‐operative care for ankyloglossia surgery in participants from birth to 18 years. A scoping review was selected as the most appropriate methodology to obtain an understanding of the diverse range of pre‐ and post‐operative care described. This review was conducted using Arksey's and O'Malley's five‐stage framework and reported following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses extension for Scoping Reviews (PRISMA‐ScR). Ethics approval was not required for this review. 2.1 Search strategy Four electronic databases were searched for articles published before August 2022, with no limit on the date of publication: Ovid Medline, ProQuest, Scopus, and Maternity and Infant Care. Search terms were tailored to the syntax requirements of each database, with keywords for the population age (e.g. ‘newborn’ or ‘infant’ or ‘paediatric’ or ‘adolescent’), diagnosis (e.g. ‘tongue‐tie’ or ‘ankyloglossia’ or ‘sublingual restriction’ or ‘lingual restriction’), surgical intervention (e.g. ‘frenotomy’ or ‘frenectomy’ or ‘frenuloplasty’ or ‘lingualplasty’), and pre and post‐operative care (e.g. ‘pre‐operative’ or ‘post‐operative’ or ‘wound care’ or ‘stretch’). Forward and backward searches of reference lists were completed. A full search strategy is included in Appendix . 2.2 Inclusion and exclusion criteria Peer‐reviewed articles reporting on human participants aged between birth and 18 years who had undergone ankyloglossia surgery were considered for inclusion. Studies were required that described pre‐ and/or post‐operative care prescribed to participants and reported quantitative or qualitative outcomes. There were no limitations on classification or type of ankyloglossia, surgical approach, post‐surgery duration or type of care prescribed, to ensure that the present review captured all articles related to pre‐ and post‐operative care. Studies were required to provide specific details about the course of care prescribed to ensure that findings could be accurately synthesised, for example stating that ‘A course of lingual exercises was prescribed’ was not considered sufficient. No limits were placed on study location or date of publication. All peer‐reviewed intervention or experimental studies were included to ensure all forms of pre‐ and post‐operative care were included. Only papers written in English were considered for inclusion due to associated translation costs. Commentary articles, letters, animal studies and review papers were excluded. 2.3 Data extraction Following title and abstract, then full‐text screening, articles that met criteria were independently analysed by two members of the research team. For each paper, the following data were extracted and charted: authors, date, study location, study design (including whether the relationship between care and outcomes was tested), sample population and size, length of time post‐surgery, type of pre‐ and post‐operative care, pre‐ and post‐operative care adherence, data collection methods, outcome measures, key results, conclusions drawn regarding the relationship between pre‐ and post‐operative care and outcomes, and study limitations. 2.4 Assessment of methodological quality The quality of each study was independently assessed by two members of the research team using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields . This tool allows for appraisal of primary studies using a 14‐item checklist for quantitative studies, and a 10‐item checklist for qualitative studies. Each item is scored according to whether it is present in the article, as ‘yes’ (2), ‘partial’ (1), ‘no’ (0) or not applicable. A summary score was then calculated for each study following the removal of all ‘not applicable’ items by dividing the sum of scores by the total possible score and converting this into a percentage. Overall study quality was described as strong (>80%), good (70% to 80%), adequate (50% to 70%) or limited (<50%). Any discrepancies between the two raters were resolved through consultation with a third member of the research team.
Search strategy Four electronic databases were searched for articles published before August 2022, with no limit on the date of publication: Ovid Medline, ProQuest, Scopus, and Maternity and Infant Care. Search terms were tailored to the syntax requirements of each database, with keywords for the population age (e.g. ‘newborn’ or ‘infant’ or ‘paediatric’ or ‘adolescent’), diagnosis (e.g. ‘tongue‐tie’ or ‘ankyloglossia’ or ‘sublingual restriction’ or ‘lingual restriction’), surgical intervention (e.g. ‘frenotomy’ or ‘frenectomy’ or ‘frenuloplasty’ or ‘lingualplasty’), and pre and post‐operative care (e.g. ‘pre‐operative’ or ‘post‐operative’ or ‘wound care’ or ‘stretch’). Forward and backward searches of reference lists were completed. A full search strategy is included in Appendix .
Inclusion and exclusion criteria Peer‐reviewed articles reporting on human participants aged between birth and 18 years who had undergone ankyloglossia surgery were considered for inclusion. Studies were required that described pre‐ and/or post‐operative care prescribed to participants and reported quantitative or qualitative outcomes. There were no limitations on classification or type of ankyloglossia, surgical approach, post‐surgery duration or type of care prescribed, to ensure that the present review captured all articles related to pre‐ and post‐operative care. Studies were required to provide specific details about the course of care prescribed to ensure that findings could be accurately synthesised, for example stating that ‘A course of lingual exercises was prescribed’ was not considered sufficient. No limits were placed on study location or date of publication. All peer‐reviewed intervention or experimental studies were included to ensure all forms of pre‐ and post‐operative care were included. Only papers written in English were considered for inclusion due to associated translation costs. Commentary articles, letters, animal studies and review papers were excluded.
Data extraction Following title and abstract, then full‐text screening, articles that met criteria were independently analysed by two members of the research team. For each paper, the following data were extracted and charted: authors, date, study location, study design (including whether the relationship between care and outcomes was tested), sample population and size, length of time post‐surgery, type of pre‐ and post‐operative care, pre‐ and post‐operative care adherence, data collection methods, outcome measures, key results, conclusions drawn regarding the relationship between pre‐ and post‐operative care and outcomes, and study limitations.
Assessment of methodological quality The quality of each study was independently assessed by two members of the research team using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields . This tool allows for appraisal of primary studies using a 14‐item checklist for quantitative studies, and a 10‐item checklist for qualitative studies. Each item is scored according to whether it is present in the article, as ‘yes’ (2), ‘partial’ (1), ‘no’ (0) or not applicable. A summary score was then calculated for each study following the removal of all ‘not applicable’ items by dividing the sum of scores by the total possible score and converting this into a percentage. Overall study quality was described as strong (>80%), good (70% to 80%), adequate (50% to 70%) or limited (<50%). Any discrepancies between the two raters were resolved through consultation with a third member of the research team.
RESULTS Following duplicate removal, 597 unique articles were identified through database searches, illustrated in Figure . Reference lists of identified studies and reviews were manually searched, and no additional studies were identified. Following screening of titles, abstracts and full texts, 23 articles met the inclusion criteria. , , , , , , , , , , , , , , , , , , , , , , The primary reasons for exclusion at full‐text screening were articles containing no information regarding pre‐ or post‐operative care or containing extremely limited descriptions of the care prescribed ( N = 138), focussing on irrelevant topics such as lip‐tie rather than ankyloglossia ( N = 61), or sampling from an adult population ( N = 16). 3.1 Study characteristics Participants from the 23 included studies were recruited from 10 different countries (Italy, United States, India, Spain, United Kingdom, Brazil, Mexico, Malaysia, Canada and Switzerland). All studies were quantitative, including prospective cohort studies ( N = 10), case reports ( N = 6), case series ( N = 2), transversal descriptive studies ( N = 2), randomised controlled trials ( N = 2) and retrospective cohort studies ( N = 1). The 23 studies included a total of 1296 paediatric participants who underwent ankyloglossia surgery, ranging in age from birth to 18 years. Eight studies examined infants under 12 months of age, , , , , , , , and the remaining 15 studies explored children aged one to 18 years. , , , , , , , , , , , , , , 3.2 Pre‐ and Post‐operative protocols A wide range of pre‐ and post‐operative care protocols were reported. A full description of pre‐ and post‐operative protocols is outlined in Table . Of the 23 included intervention studies, seven incorporated a course of both pre‐ and post‐operative care, whereas the remaining 16 studies included post‐operative care only. Adherence rates to pre‐ and post‐operative care were reported for five studies only , , , , and ranged from 43.5% to 100%. Across studies, pre‐operative care included (either individually or in combination) lingual exercises/myofunctional therapy ( N = 5), wound massage ( N = 2) and breastfeeding sessions ( N = 3). Post‐operative care included (individually or in combination) lingual exercises/myofunctional therapy ( N = 22); application of antiseptic, gauze or analgesics ( N = 8); wound massage ( N = 7); speech therapy ( N = 5); breastfeeding sessions ( N = 3); and generic oral hygiene and dietary recommendations ( N = 2). Forms of post‐operative care incorporating lingual exercises or myofunctional therapy were typically the most comprehensively described across studies. Protocols also differed significantly in the exercise dosage, frequency and duration of care prescribed. 3.3 Quality assessment There was significant variability in the quality of the 23 papers. Quality assessment scores ranged from 36% to 96%, with 11 studies rated as ‘strong’, two rated as ‘good’, seven rated as ‘adequate’ and three rated as ‘limited’ and are outlined in Table . Shared areas of weakness across studies included lacking information regarding data collection methods and/or poorly defined outcome measures, such as lacking descriptions of how adherence data was collected or how ‘good healing’ was defined. Other areas of weakness included lacking specific details of the care prescribed, small sample sizes, lacking consideration of confounding variables (e.g. post‐operative care adherence) and/or lacking a control group to draw appropriate conclusions regarding the effectiveness of pre‐ and post‐operative care. 3.4 Post‐surgical outcomes A variety of outcome measures, including speech articulation, breastfeeding, sleep, tongue structure and function, wound healing, weight gain, pain, reflux, posture and post‐surgical complications, were used to assess the effectiveness of pre‐ and post‐operative care across studies (Table ). Frenotomy in combination with pre‐ and/or post‐operative care was associated with post‐surgical improvements in functional outcomes such as breastfeeding (e.g. duration, breastmilk intake and maternal nipple pain), speech articulation, sleep, tongue mobility, tongue structure (e.g. degree of ankyloglossia and frenulum length), weight gain, reflux, wound healing and posture. Of the 23 included studies, only three were designed to explicitly investigate the relationship between post‐operative care and post‐surgical outcomes through the inclusion of a control group who did not engage in pre‐ or post‐operative care. , , One of these studies was conducted in infants under 60 days old, and the other two were in children aged 6 to 12 years. , Across these three studies, study groups engaging in post‐frenotomy wound massage (5), isotonic tongue exercises and speech therapy rehabilitation in the form of lingual exercises achieved better recovery outcomes than control groups who received frenectomy only. The remaining 19 studies did not explicitly evaluate the relationship between pre‐ or post‐operative care and ankyloglossia surgery outcomes. Most studies provided recommendations for implementing post‐operative care, regardless of whether the relationship between care and post‐surgical outcomes had been explicitly evaluated. Only one article recommended against the use of post‐operative care (massage) due to a nonsignificant difference between the study and control groups. Amongst the studies in this review, few negative outcomes were reported following ankyloglossia surgery in combination with pre‐ and/or post‐operative care, with low ankyloglossia recurrence rates and minor complications such as infection. Although Ferres‐Amat et al. did not set out to examine the link between orofacial rehabilitation and frenotomy outcomes, a portion of participants did not adhere to post‐operative care recommendations (21.8%). Lacking adherence was found to be the only statistically significant predictor of poorer recovery outcomes.
Study characteristics Participants from the 23 included studies were recruited from 10 different countries (Italy, United States, India, Spain, United Kingdom, Brazil, Mexico, Malaysia, Canada and Switzerland). All studies were quantitative, including prospective cohort studies ( N = 10), case reports ( N = 6), case series ( N = 2), transversal descriptive studies ( N = 2), randomised controlled trials ( N = 2) and retrospective cohort studies ( N = 1). The 23 studies included a total of 1296 paediatric participants who underwent ankyloglossia surgery, ranging in age from birth to 18 years. Eight studies examined infants under 12 months of age, , , , , , , , and the remaining 15 studies explored children aged one to 18 years. , , , , , , , , , , , , , ,
Pre‐ and Post‐operative protocols A wide range of pre‐ and post‐operative care protocols were reported. A full description of pre‐ and post‐operative protocols is outlined in Table . Of the 23 included intervention studies, seven incorporated a course of both pre‐ and post‐operative care, whereas the remaining 16 studies included post‐operative care only. Adherence rates to pre‐ and post‐operative care were reported for five studies only , , , , and ranged from 43.5% to 100%. Across studies, pre‐operative care included (either individually or in combination) lingual exercises/myofunctional therapy ( N = 5), wound massage ( N = 2) and breastfeeding sessions ( N = 3). Post‐operative care included (individually or in combination) lingual exercises/myofunctional therapy ( N = 22); application of antiseptic, gauze or analgesics ( N = 8); wound massage ( N = 7); speech therapy ( N = 5); breastfeeding sessions ( N = 3); and generic oral hygiene and dietary recommendations ( N = 2). Forms of post‐operative care incorporating lingual exercises or myofunctional therapy were typically the most comprehensively described across studies. Protocols also differed significantly in the exercise dosage, frequency and duration of care prescribed.
Quality assessment There was significant variability in the quality of the 23 papers. Quality assessment scores ranged from 36% to 96%, with 11 studies rated as ‘strong’, two rated as ‘good’, seven rated as ‘adequate’ and three rated as ‘limited’ and are outlined in Table . Shared areas of weakness across studies included lacking information regarding data collection methods and/or poorly defined outcome measures, such as lacking descriptions of how adherence data was collected or how ‘good healing’ was defined. Other areas of weakness included lacking specific details of the care prescribed, small sample sizes, lacking consideration of confounding variables (e.g. post‐operative care adherence) and/or lacking a control group to draw appropriate conclusions regarding the effectiveness of pre‐ and post‐operative care.
Post‐surgical outcomes A variety of outcome measures, including speech articulation, breastfeeding, sleep, tongue structure and function, wound healing, weight gain, pain, reflux, posture and post‐surgical complications, were used to assess the effectiveness of pre‐ and post‐operative care across studies (Table ). Frenotomy in combination with pre‐ and/or post‐operative care was associated with post‐surgical improvements in functional outcomes such as breastfeeding (e.g. duration, breastmilk intake and maternal nipple pain), speech articulation, sleep, tongue mobility, tongue structure (e.g. degree of ankyloglossia and frenulum length), weight gain, reflux, wound healing and posture. Of the 23 included studies, only three were designed to explicitly investigate the relationship between post‐operative care and post‐surgical outcomes through the inclusion of a control group who did not engage in pre‐ or post‐operative care. , , One of these studies was conducted in infants under 60 days old, and the other two were in children aged 6 to 12 years. , Across these three studies, study groups engaging in post‐frenotomy wound massage (5), isotonic tongue exercises and speech therapy rehabilitation in the form of lingual exercises achieved better recovery outcomes than control groups who received frenectomy only. The remaining 19 studies did not explicitly evaluate the relationship between pre‐ or post‐operative care and ankyloglossia surgery outcomes. Most studies provided recommendations for implementing post‐operative care, regardless of whether the relationship between care and post‐surgical outcomes had been explicitly evaluated. Only one article recommended against the use of post‐operative care (massage) due to a nonsignificant difference between the study and control groups. Amongst the studies in this review, few negative outcomes were reported following ankyloglossia surgery in combination with pre‐ and/or post‐operative care, with low ankyloglossia recurrence rates and minor complications such as infection. Although Ferres‐Amat et al. did not set out to examine the link between orofacial rehabilitation and frenotomy outcomes, a portion of participants did not adhere to post‐operative care recommendations (21.8%). Lacking adherence was found to be the only statistically significant predictor of poorer recovery outcomes.
DISCUSSION This scoping review delineates the diverse range of pre‐ and post‐operative care provided for infants and children undergoing ankyloglossia. Several types of surgical methods were used, and seven main types of pre‐ and post‐operative care were reported, including speech‐language pathology, myofunctional therapy/lingual exercises/stretching, application of antiseptic, gauze or analgesics, massage, breastfeeding, and generic oral hygiene and dietary recommendations. There was significant variability in the age of participants, assessment of compliance and pre‐ and post‐operative care regimens, including exercise dosage, frequency, duration and specific care procedure implemented or the types of exercises. Post‐operative care was prescribed in all studies, whereas pre‐operative care was only prescribed in seven studies. The most common and comprehensively form of care described was myofunctional therapy or lingual exercises. Improvements in outcomes such as breastfeeding, speech or articulation, sleep, tongue structure/function, weight gain, reflux, wound healing and posture were reported following frenotomy in combination with all types of pre‐ or post‐operative care. Frenotomy in combination with all types of pre‐ and post‐operative care was associated with low ankyloglossia recurrence rates and only minor post‐operative complications. Significant heterogeneity in study designs, outcome measures and care protocols leads to challenges in drawing comparisons across studies. All studies included in this review explicitly examining the link between care and frenotomy outcomes prescribed post‐operative care only. It is therefore difficult to determine whether the addition of pre‐operative care may be beneficial in maximising any positive outcomes, although it appears that pre‐operative care does not result in any negative effects. Pre‐operative care may well have significant nonfunctional effects on parental readiness, comfort of the infant or child with manual manipulation of the tongue and other factors that could make post‐frenotomy care easier, and this review did not consider those studies. Therefore, our conclusion does not say that pre‐surgery care is not beneficial, only that the current literature does not provide evidence to say that pre‐operative care is essential. Sfasciotti's study of four‐ to 12‐year‐old children included different forms of post‐frenectomy care across groups (myofunctional therapy only, or combined with speech therapy and/or gauze), and compared them with a control group (no surgery or care regimen), making it impossible to separate out the therapeutic effects of the frenectomy from that of post‐surgical care. In addition to variability in the types of post‐operative care prescribed, the timing of post‐operative care varied and was not sufficiently reported. Post‐operative care time periods ranged from days to 3 months of post‐surgery, with some studies reporting ‘several weeks’ of care. Although repetitive post‐operative care is often recommended as best practice, there is a lack of consensus regarding the most efficacious timing, frequency, type and intensity of post‐operative care. Future studies should utilise standardised outcome measures at key time points before, during and after pre‐operative care, surgery and post‐operative care. Consistent and standardised data collection would demonstrate the clinical effectiveness of such treatments alone, or in conjunction with one another, and would clarify whether adjunctive therapies are necessary before surgery only, after surgery only or both before and after frenotomy surgery. The age of participants is a crucial factor to consider because the cooperation and ability of the subjects is relevant to the success of the pre‐ or post‐operative care regimen. Eight studies examined infants under 12 months of age, and 15 studies explored children aged one to 18 years. Of the three studies examining the link between post‐operative care and outcomes, two supported the use of post‐operative care following frenotomy. , Both studies found that groups engaging in post‐frenotomy care (lingual exercises) performed significantly better in measures of lingual function than control groups receiving frenotomy only. , In contrast, Bhandarkar et al. recommended against post‐operative wound massage, due to nonsignificant differences in breastfeeding outcomes between the study and control groups. Age of the participants is one explanation for this lack of congruence in these studies. Better outcomes were obtained for participants who could comply with instructions, for example children aged four to 16 years compared with infants under 60 days old. Future studies should employ designs that address the quality of efficacious post‐operative care for age and may reveal varying degrees of improvement based on the child's age, as older children may have a higher capacity to adhere to therapy compared with infants. Another key factor is compliance of the parents, therapists and patients with the administration of active wound management, which can significantly affect functional outcome measures. Parents play a critical role in pre‐ and post‐operative care, as they are responsible for ensuring that the child follows prescribed exercises and reporting any adverse reactions, and pre‐ and post‐operative care requires close collaboration between therapists and parents. Therapists play a crucial role in providing professional expertise and guidance, whereas parents provide daily care and support. Within Bhandarkar's wound massage group, 56.6% of parents did not adhere to post‐operative massage recommendations. Reasons cited for nonadherence included uncertainty regarding massage‐related harms, lacking information about the benefits of massage and conflicting advice received from healthcare professionals surrounding post‐frenotomy massage. Other studies did not report compliance rates related to administration of post‐operative care. Since there are currently no clear standards for pre‐ and post‐operative care, inconsistent recommendations are being provided by clinicians, with some recommending no care at all. This highlights the impact that a lack of evidence and inconsistent recommendations may have on patients and the need for further research to develop consistent clinical guidelines. It also highlights the confounding role parent compliance and post‐operative care quality may play in outcome measurement. Future studies should focus on quantifying parental compliance and assessing the actual quality of the care regimen delivered. This review did not specifically assess the appropriateness of surgical interventions for ankyloglossia but aimed to transparently document the surgical technique used alongside pre‐ and post‐operative care. Despite reported positive outcomes, the absence of standardised findings underscores the imperative for future research to ascertain the efficacy and necessity of various surgical procedures combined with pre‐ and/post‐operative care for the treatment of ankyloglossia in paediatric patients. Preliminary research indicates that pre‐ and post‐operative care may influence frenotomy outcomes, but further research is needed to explore this relationship. The inclusion criteria specified the necessity for studies to detail pre‐ or post‐operative care procedures, potentially introducing bias by excluding articles demonstrating successful outcomes without such care. This selective inclusion may have also limited the comprehensiveness of the observed frenotomy outcomes, since papers with vague descriptions of care protocols were excluded. Therefore, the true frequency of each care type may be underrepresented. This highlights the need for more comprehensive descriptions of pre‐ and post‐operative care protocols within future publications, to allow for evaluation and replication. This review highlights that pre‐ and post‐frenotomy care regimens can positively influence frenotomy outcomes and does not lead to negative outcomes; further research, however, is needed to clarify the significance of these effects. This review found that the timing of pre‐ and post‐surgical care, age of participants, severity of ankyloglossia, and parental compliance and adherence as three significant variables that should be considered in future studies and the potential inter‐relatedness of variables require further exploration. Further research is also needed to determine the most optimal combination of pre‐ and post‐operative care in conjunction with frenotomy, with the inclusion of a control group that does not receive any pre‐ or post‐operative care (surgery‐only control group). This would help determine which form of care is most effective in improving healing and functional outcomes following frenotomy. This will assist the development of evidence‐based clinical guidelines for pre‐ and post‐operative care, to ensure patients receive consistent recommendations that lead to optimal post‐frenotomy outcomes.
R.T. and S.S. conceived the idea; H.G. collected the data; H.G., S.S. and R.T. analysed the data; and S.S., H.G. and R.T. contributed to the writing.
The corresponding author or co‐authors do not have any financial or nonfinancial disclosures regarding this study.
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Bioconversion of Alpha-Cembratriene-4,6-diol into High-Value Compound Farnesal Through Employment of a Novel | 73d86724-d326-43d4-b2b6-f92dcc9830ae | 11901948 | Microbiology[mh] | Cembranoids are a class of naturally occurring diterpenoids that are commonly found in various plant families such as Solanaceae (e.g., Nicotiana tabacum ) and Pinaceae , marine corals (Li et al. 2006), and some animals . Over 300 cembranoid compounds have been identified from various natural sources, with α-CBT-diol being the most abundant in nature . Arnarp et al. utilized Tripterygium wilfordii cells harvested from different growth stages as biocatalysts to explore the bioconversion products of α-CBT-diol. Their research revealed that α-CBT-diol can produce various products due to its susceptibility to epoxidation and hydroxylation at the C-10, C-12, and C-13 positions . Farnesal is an FDA-approved flavoring agent and adjuvant used in forming farnesal-loaded pH-sensitive polymeric micelles to prevent and treat dental caries . Farnesal is a precursor of farnesol , a bioactive compound used in various industries, including food, cosmetics, and perfumes . More specifically, farnesol demonstrates antimicrobial, anti-tumor, cardioprotective, hepatoprotective, and neuroprotective properties (in Alzheimer’s and Parkinson’s diseases) . Furthermore, farnesol has also been shown to be active against allergic asthma, diabetes, atherosclerosis, obesity, and hyperlipidemia . In this study, the S. maltophilia H3-1 strain, which efficiently converts α-CBT-diol from tobacco to farnesal, was isolated, characterized, and described from the soil. Subsequently, the fermentation conditions were optimized for the efficient conversion of α-CBT-diol into farnesal and the optimal growth of the S. maltophilia H3-1 strain. The cellular localization of the α-CBT-diol-degrading enzymes expressed in S. maltophilia H3-1 was also determined, and a mechanism for converting α-CBT-diol into farnesal was proposed. To our knowledge, this is the first study to report the bioconversion of α-CBT-diol into farnesal through the use of a microbe.
2.1. Isolation, Identification, and Characterization of α-CBT-diol Biodegrading Bacteria This study systematically isolated and purified a single S. maltophilia H3-1 strain colony from the soil. The morphological characterization revealed that colonies of the S. maltophilia H3-1 strain on LB medium were light yellow and round, with a bright surface and raised center ( A). This type of appearance of the colonies is consistent with previous studies that describe the typical morphology of S. maltophilia colonies on LB medium . This appearance is linked to the production of extracellular enzymes and bioactive compounds, contributing to the strain’s adaptability to environmental conditions . Gram staining showed that the S. maltophilia H3-1 strain cells were thin rods, flagella-less, and had a size of 0.2–0.3 × 0.7–1.0 μm ( B). The lack of flagella indicates a reduced need for motility in its native soil environment. This suggests that biofilm formation is an alternative mode of adaptation, a common trait among Stenotrophomonas species . To identify and classify the bacterial strain isolated from the soil, we sequenced its 16S rDNA, which was 1497 bp in length. The sequence was then compared with previously sequenced bacterial 16S rDNAs using BLAST (2.14.0) homology. The results showed that the 16S rDNA had high similarity with S. maltophilia KT580582T (99.8%), Stenotrophomonas chelatiphaga HQ219979T (99.8%), and Stenotrophomonas acidaminiphila LT223687T (99.8%). The high sequence similarity with the strains above suggests that our isolated strain belongs to the Stenotrophomonas genus. This genus is known for its broad range of metabolic capabilities, which allows it to adapt to various environmental conditions . A phylogenetic tree based on the 16S rDNA sequences of the isolated strain was constructed. The tree showed that the H3-1 strain formed a distinct phyletic line with S. maltophilia and is located on a separate branch ( C). The placement of S. maltophilia H3-1 on a separate branch represents its distinct lineage while indicating a close evolutionary relationship with S. maltophilia strains . Initially, the ability of S. maltophilia H3-1 to biodegrade α-CBT-diol into farnesal was determined by growing it in a selective medium containing α-CBT-diol as the sole carbon source. The conversion of α-CBT-diol to farnesal was confirmed by the compound retention index (RI) and GC-MS analysis ( D). The successful conversion of CBT-diol to farnesal by S. maltophilia H3-1 highlights its potential ability to transform complex organic compounds . 2.2. Growth and α-CBT-diol Bioconversion Curves of S. maltophilia H3-1 Strain The growth curve of the S. maltophilia H3-1 strain was constructed by recording the optical density at OD 600 nm. The optical data show that the H3-1 strain grew slower during the first 20 h of the growth period, but after that, it rapidly started growing and consuming a large amount of α-CBT-diol ( A). S. maltophilia H3-1 strain started consuming α-CBT-diol (non-natural carbon source) for growth due to the selective pressure. It achieved growth optima at the 36th hour, which indicates that the number of cells producing and decaying were in equilibrium ( A). Moreover, it also shows that the H3-1 strain took 36 h to adapt to consuming α-CBT-diol as a carbon source for growth. Consequently, the bioconversion of α-CBT-diol became visible at the 36th hour of the growth period of the S. maltophilia H3-1 strain. The extended lag phase represents the period during which the S. maltophilia H3-1 strain adjusted to the novel carbon source , demonstrating its potential applications in bioremediation. 2.3. Optimization of Growth Parameters and Concentration of α-CBT-diol S. maltophilia H3-1 strain demonstrated a high α-CBT-diol bioconversion rate; however, an increase in the initial concentration of α-CBT-diol led to a corresponding decrease in the bioconversion capacity of the H3-1 strain ( B). The results of this study show that the optimum concentration of α-CBT-diol is 1 mg/mL. A concentration higher than this negatively affected the strain’s bioconversion capacity ( B). This finding suggests that the S. maltophilia H3-1 strain efficiently biodegrades α-CBT-diol into farnesal but is sensitive to high substrate concentrations, which may have saturated the enzymes responsible for degrading α-CBT-diol. This accumulation could have resulted in reduced growth and an overall decrease in the bioconversion rate . The S. maltophilia H3-1 strain was cultured at different temperatures, including 25 °C, 30 °C, 35 °C, 40 °C, 45 °C, and 50 °C, to determine the optimal temperature at which this strain demonstrates the highest α-CBT-diol bioconversion rate. The results showed that the S. maltophilia H3-1 strain degraded α-CBT-diol at the lowest rate (~57.6%) at 25 °C, but the bioconversion rate increased reciprocally with the temperature rise. The optimal temperature was 40 °C, at which S. maltophilia H3-1 degraded ~88.7% of α-CBT-diol in the growth medium and accumulated the maximum amount of biomass, reflected in an OD 600 value of 0.73. As the temperature increases, the kinetic energy of molecules rises, enhancing enzyme–substrate interactions and thereby increasing reaction rates . However, the α-CBT-diol bioconversion rates decreased to 83.1% and 78.3%, respectively, when S. maltophilia H3-1 was grown at 45 °C and 50 °C ( A). The enzymes are prone to denaturation when their thermal stability is exceeded, causing a loss of their three-dimensional structure and catalytic function. In addition to enzyme denaturation, excessive heat can disrupt cell membranes and other critical cellular components, impairing overall metabolic function . S. maltophilia H3-1 strain is not thermophilic; therefore, temperatures above 40 °C could inflict damaging effects on the enzymatic machinery responsible for the bioconversion of α-CBT-diol into farnesal and the heat-labile cellular components of this microorganism. Consequently, we selected 40 °C as the optimum temperature for further fermentation experiments. The synergistic effect of different carbon sources, including glucose, fructose, maltose, sucrose, lactose, and β-Cyclodextrin, on the bioconversion rate of α-CBT-diol was determined by growing the S. maltophilia H3-1 strain in growth media, each containing one of these carbon sources (1 g/L,). The tested carbon sources demonstrated a synergistic effect on the bioconversion rate of α-CBT-diol in the following order: maltose > fructose > glucose > sucrose > β-Cyclodextrin > lactose ( B). Maltose exerted the most substantial positive synergistic effect, achieving an 86.8% α-CBT-diol bioconversion rate when S. maltophilia H3-1 was grown in a growth medium containing 2 g/L maltose as a complementary carbon source ( A). The optical density, representing biomass accumulation, was 0.65, higher than other carbon sources except for glucose. Although the S. maltophilia H3-1 strain exhibited higher growth in the medium containing glucose, it demonstrated a lower α-CBT-diol bioconversion rate ( B). The findings suggest that the choice of carbon source is pivotal for maximizing the efficiency of S. maltophilia H3-1 in degrading α-CBT-diol. The positive synergistic effect of maltose may be attributed to its ability to enhance the expression of specific catabolic enzymes or improve the strain’s overall metabolic activity in utilizing this carbon source . Future studies could further explore the mechanisms behind the enzymatic pathways activated by different carbon sources to enhance the bioconversion processes of α-CBT-diol. The α-CBT-diol bioconversion rate and optical density decreased when maltose concentrations higher than 2 g/L were used to grow S. maltophilia H3-1. However, as the concentration continued to increase beyond 2 g/L, both the bioconversion rate and OD 600 value declined sharply ( A). This reduction was likely due to the high maltose concentration causing increased osmotic pressure in the medium, which inhibited bacterial growth and the synthesis of degradative enzymes . The effect of organic and inorganic nitrogen sources, such as ammonium sulfate, sodium nitrate, potassium nitrate, yeast extract, peptone, and urea, on the bioconversion rate of α-CBT-diol was evaluated by growing the S. maltophilia H3-1 strain in a medium containing one of the nitrogen sources separately at a concentration of 1 g/L. It was observed that inorganic nitrogen sources had a significantly stronger stimulating effect on the rate of α-CBT-diol bioconversion compared to organic nitrogen sources ( C). Notably, the use of 2 g/L ammonium sulfate as the sole nitrogen source in the fermentation medium strongly promoted the bioconversion rate of α-CBT-diol and biomass production (OD 600 ), recorded at 86.5% and 0.74, respectively ( B). The order of the effect of nitrogen sources on the bioconversion rate of α-CBT-diol was as follows: ammonium sulfate > sodium nitrate > potassium nitrate > yeast powder > peptone > urea. ( C) However, the addition of urea to the growth medium as the nitrogen source demonstrated the worst effect on the bioconversion rate of α-CBT-diol (56.5%) and biomass production (0.35). Ammonium sulfate significantly enhanced the bioconversion rate of α-CBT-diol by the S. maltophilia H3-1 strain. This is likely due to the rapid release and assimilation of ammonium ions compared to other nitrogen sources tested in this study, which are readily available for microbial metabolism and promote the enzyme production necessary for the bioconversion of α-CBT-diol . When the S. maltophilia H3-1 strain was grown in a medium containing ammonium sulfate higher than 2g/L, it did not further enhance the optical density and bioconversion rate of α-CBT-diol ( B). Overall, the use of ammonium sulfate as a nitrogen source demonstrated a positive impact on the growth and bioconversion of α-CBT-diol by the S. maltophilia H3-1 strain. The pH of the fermentation medium plays a crucial role in generating the high-yield production of the desired product; therefore, we also studied the effect of different pH values on the bioconversion rate of α-CBT-diol and biomass production. Our results showed that the S. maltophilia H3-1 strain grew very slowly in an acidic growth medium. The bioconversion rate of α-CBT-diol and biomass production increased proportionally with a rise in the pH value of the fermentation medium. We observed the maximum bioconversion rate of α-CBT-diol (87.5%) and biomass production (0.73) at pH 8. However, both the bioconversion rate and biomass production were severely affected when the pH exceeded 8 in the fermentation medium. This indicates that an overly alkaline pH is not suitable for the bioconversion of α-CBT-diol and the growth of the S. maltophilia H3-1 strain. Therefore, we selected pH 8 as the optimal initial pH of the fermentation medium ( D). It is well established that pH influences the ionization state of the medium, which can directly affect the solubility and availability of nutrients as well as the structural stability of enzymes involved in bioconversion . The slower growth observed at acidic pH levels suggests that the S. maltophilia H3-1 strain may be less efficient at regulating internal pH, leading to a reduced metabolic rate and lower enzyme production . The proportional increase in the bioconversion rate and biomass production with rising pH values reflects the optimal enzyme activity in a slightly alkaline environment, as seen with pH 8. This is consistent with other studies showing that many microbial strains exhibit higher metabolic activity under mildly alkaline conditions . However, the detrimental effect of pH values higher than 8 may be attributed to enzyme denaturation or the disruption of cellular processes due to excess alkalinity, which can impair the overall bioconversion process. The optimal liquid culture conditions for S. maltophilia H3-1 were determined as follows: a bioconversion time of 36 h, a temperature of 40 °C, a pH of 8, 2 g/L maltose as the carbon source, and 2 g/L ammonium sulfate as the nitrogen source, based on the bioconversion rate of α-CBT-diol. Under these conditions, the bioconversion rate of α-CBT-diol reached 93.3%, resulting in a theoretical farnesal production of 201 mg/L, assuming a 1:1 molar conversion. The results indicate that the strain exhibited its highest bioconversion efficiency under these optimized growth conditions. 2.4. Confirmation of Membrane Association of Enzymes Catalyzing the Conversion of α-CBT-diol into Farnesal To confirm the localization of the enzymes catalyzing the conversion of α-CBT-diol into farnesal, reaction mixtures were prepared with α-CBT-diol and the cytosolic and membrane components of S. maltophilia H3-1. A,B, and c illustrate that α-CBT-diol gradually degraded over time and nearly completed bioconversion after approximately 3 h in the test tube experiment. The bioconversion was accompanied by forming a newly found compound, indicating the enzymatic breakdown of α-CBT-diol. Enzymatic activity was detected exclusively in the membrane component, while no bioconversion activity was observed in the cytosolic fraction. This suggests that the enzymes responsible for α-CBT-diol bioconversion are associated with the plasma membrane. This localization of the enzymes to the membrane is consistent with many other microbial bioconversion systems, where membrane-bound enzymes often catalyze the bioconversion of hydrophobic or membrane-associated compounds. The membrane environment likely facilitates the accessibility of α-CBT-diol, which could interact more efficiently with the enzymes due to its lipid-like structure . The newly found compound was isolated using UPLC and identified using GC-MS . After vacuum concentration and freeze-drying, a white powdery substance was obtained. The structure of this newly found compound was determined using nuclear magnetic resonance (NMR) analysis . As shown in A, the pink-shadowed peak represents the newly found compound produced from α-CBT-diol. In this study, we predicted that the bioconversion pathway of α-CBT-diol to farnesal involves a series of enzymatic reactions. In the first step, CBT-hydroxylase, likely a monooxygenase encoded by the cbtA gene, catalyzes the hydroxylation of α-CBT-diol, producing hydroxylated α-CBT-diol. This step introduces a hydroxyl group to the substrate, increasing its hydrophilicity, and consumes NADH/NADPH as an electron donor to activate molecular oxygen. In the second step, dehydratase, encoded by the cbtB gene, catalyzes the removal of a water molecule (dehydration) and an oxidation reaction, forming oxidized α-CBT-diol, a compound with a conjugated double-bond system. This step reduces NAD⁺ to NADH, contributing to the cofactor balance. The third step involves aldehyde synthase (encoded by cbtC), which processes the oxidized intermediate through a cleavage reaction to generate farnesal precursor, a compound containing an aldehyde group. This step does not directly involve the consumption or production of NADH. In the final step, oxidoreductase, encoded by the cbtD gene, catalyzes the oxidation of the farnesal precursor to yield farnesal, a high-value aromatic aldehyde. This step also reduces NAD⁺ to NADH. Overall, the pathway consumes one molecule of NADH/NADPH during hydroxylation (Step 1) and produces two molecules of NADH during oxidation reactions (Steps 2 and 4), effectively driving the conversion of α-CBT-diol into farnesal. This pathway highlights the enzymatic efficiency and cofactor utilization in transforming a complex diterpenoid into a commercially valuable compound ( B).
This study systematically isolated and purified a single S. maltophilia H3-1 strain colony from the soil. The morphological characterization revealed that colonies of the S. maltophilia H3-1 strain on LB medium were light yellow and round, with a bright surface and raised center ( A). This type of appearance of the colonies is consistent with previous studies that describe the typical morphology of S. maltophilia colonies on LB medium . This appearance is linked to the production of extracellular enzymes and bioactive compounds, contributing to the strain’s adaptability to environmental conditions . Gram staining showed that the S. maltophilia H3-1 strain cells were thin rods, flagella-less, and had a size of 0.2–0.3 × 0.7–1.0 μm ( B). The lack of flagella indicates a reduced need for motility in its native soil environment. This suggests that biofilm formation is an alternative mode of adaptation, a common trait among Stenotrophomonas species . To identify and classify the bacterial strain isolated from the soil, we sequenced its 16S rDNA, which was 1497 bp in length. The sequence was then compared with previously sequenced bacterial 16S rDNAs using BLAST (2.14.0) homology. The results showed that the 16S rDNA had high similarity with S. maltophilia KT580582T (99.8%), Stenotrophomonas chelatiphaga HQ219979T (99.8%), and Stenotrophomonas acidaminiphila LT223687T (99.8%). The high sequence similarity with the strains above suggests that our isolated strain belongs to the Stenotrophomonas genus. This genus is known for its broad range of metabolic capabilities, which allows it to adapt to various environmental conditions . A phylogenetic tree based on the 16S rDNA sequences of the isolated strain was constructed. The tree showed that the H3-1 strain formed a distinct phyletic line with S. maltophilia and is located on a separate branch ( C). The placement of S. maltophilia H3-1 on a separate branch represents its distinct lineage while indicating a close evolutionary relationship with S. maltophilia strains . Initially, the ability of S. maltophilia H3-1 to biodegrade α-CBT-diol into farnesal was determined by growing it in a selective medium containing α-CBT-diol as the sole carbon source. The conversion of α-CBT-diol to farnesal was confirmed by the compound retention index (RI) and GC-MS analysis ( D). The successful conversion of CBT-diol to farnesal by S. maltophilia H3-1 highlights its potential ability to transform complex organic compounds .
The growth curve of the S. maltophilia H3-1 strain was constructed by recording the optical density at OD 600 nm. The optical data show that the H3-1 strain grew slower during the first 20 h of the growth period, but after that, it rapidly started growing and consuming a large amount of α-CBT-diol ( A). S. maltophilia H3-1 strain started consuming α-CBT-diol (non-natural carbon source) for growth due to the selective pressure. It achieved growth optima at the 36th hour, which indicates that the number of cells producing and decaying were in equilibrium ( A). Moreover, it also shows that the H3-1 strain took 36 h to adapt to consuming α-CBT-diol as a carbon source for growth. Consequently, the bioconversion of α-CBT-diol became visible at the 36th hour of the growth period of the S. maltophilia H3-1 strain. The extended lag phase represents the period during which the S. maltophilia H3-1 strain adjusted to the novel carbon source , demonstrating its potential applications in bioremediation.
S. maltophilia H3-1 strain demonstrated a high α-CBT-diol bioconversion rate; however, an increase in the initial concentration of α-CBT-diol led to a corresponding decrease in the bioconversion capacity of the H3-1 strain ( B). The results of this study show that the optimum concentration of α-CBT-diol is 1 mg/mL. A concentration higher than this negatively affected the strain’s bioconversion capacity ( B). This finding suggests that the S. maltophilia H3-1 strain efficiently biodegrades α-CBT-diol into farnesal but is sensitive to high substrate concentrations, which may have saturated the enzymes responsible for degrading α-CBT-diol. This accumulation could have resulted in reduced growth and an overall decrease in the bioconversion rate . The S. maltophilia H3-1 strain was cultured at different temperatures, including 25 °C, 30 °C, 35 °C, 40 °C, 45 °C, and 50 °C, to determine the optimal temperature at which this strain demonstrates the highest α-CBT-diol bioconversion rate. The results showed that the S. maltophilia H3-1 strain degraded α-CBT-diol at the lowest rate (~57.6%) at 25 °C, but the bioconversion rate increased reciprocally with the temperature rise. The optimal temperature was 40 °C, at which S. maltophilia H3-1 degraded ~88.7% of α-CBT-diol in the growth medium and accumulated the maximum amount of biomass, reflected in an OD 600 value of 0.73. As the temperature increases, the kinetic energy of molecules rises, enhancing enzyme–substrate interactions and thereby increasing reaction rates . However, the α-CBT-diol bioconversion rates decreased to 83.1% and 78.3%, respectively, when S. maltophilia H3-1 was grown at 45 °C and 50 °C ( A). The enzymes are prone to denaturation when their thermal stability is exceeded, causing a loss of their three-dimensional structure and catalytic function. In addition to enzyme denaturation, excessive heat can disrupt cell membranes and other critical cellular components, impairing overall metabolic function . S. maltophilia H3-1 strain is not thermophilic; therefore, temperatures above 40 °C could inflict damaging effects on the enzymatic machinery responsible for the bioconversion of α-CBT-diol into farnesal and the heat-labile cellular components of this microorganism. Consequently, we selected 40 °C as the optimum temperature for further fermentation experiments. The synergistic effect of different carbon sources, including glucose, fructose, maltose, sucrose, lactose, and β-Cyclodextrin, on the bioconversion rate of α-CBT-diol was determined by growing the S. maltophilia H3-1 strain in growth media, each containing one of these carbon sources (1 g/L,). The tested carbon sources demonstrated a synergistic effect on the bioconversion rate of α-CBT-diol in the following order: maltose > fructose > glucose > sucrose > β-Cyclodextrin > lactose ( B). Maltose exerted the most substantial positive synergistic effect, achieving an 86.8% α-CBT-diol bioconversion rate when S. maltophilia H3-1 was grown in a growth medium containing 2 g/L maltose as a complementary carbon source ( A). The optical density, representing biomass accumulation, was 0.65, higher than other carbon sources except for glucose. Although the S. maltophilia H3-1 strain exhibited higher growth in the medium containing glucose, it demonstrated a lower α-CBT-diol bioconversion rate ( B). The findings suggest that the choice of carbon source is pivotal for maximizing the efficiency of S. maltophilia H3-1 in degrading α-CBT-diol. The positive synergistic effect of maltose may be attributed to its ability to enhance the expression of specific catabolic enzymes or improve the strain’s overall metabolic activity in utilizing this carbon source . Future studies could further explore the mechanisms behind the enzymatic pathways activated by different carbon sources to enhance the bioconversion processes of α-CBT-diol. The α-CBT-diol bioconversion rate and optical density decreased when maltose concentrations higher than 2 g/L were used to grow S. maltophilia H3-1. However, as the concentration continued to increase beyond 2 g/L, both the bioconversion rate and OD 600 value declined sharply ( A). This reduction was likely due to the high maltose concentration causing increased osmotic pressure in the medium, which inhibited bacterial growth and the synthesis of degradative enzymes . The effect of organic and inorganic nitrogen sources, such as ammonium sulfate, sodium nitrate, potassium nitrate, yeast extract, peptone, and urea, on the bioconversion rate of α-CBT-diol was evaluated by growing the S. maltophilia H3-1 strain in a medium containing one of the nitrogen sources separately at a concentration of 1 g/L. It was observed that inorganic nitrogen sources had a significantly stronger stimulating effect on the rate of α-CBT-diol bioconversion compared to organic nitrogen sources ( C). Notably, the use of 2 g/L ammonium sulfate as the sole nitrogen source in the fermentation medium strongly promoted the bioconversion rate of α-CBT-diol and biomass production (OD 600 ), recorded at 86.5% and 0.74, respectively ( B). The order of the effect of nitrogen sources on the bioconversion rate of α-CBT-diol was as follows: ammonium sulfate > sodium nitrate > potassium nitrate > yeast powder > peptone > urea. ( C) However, the addition of urea to the growth medium as the nitrogen source demonstrated the worst effect on the bioconversion rate of α-CBT-diol (56.5%) and biomass production (0.35). Ammonium sulfate significantly enhanced the bioconversion rate of α-CBT-diol by the S. maltophilia H3-1 strain. This is likely due to the rapid release and assimilation of ammonium ions compared to other nitrogen sources tested in this study, which are readily available for microbial metabolism and promote the enzyme production necessary for the bioconversion of α-CBT-diol . When the S. maltophilia H3-1 strain was grown in a medium containing ammonium sulfate higher than 2g/L, it did not further enhance the optical density and bioconversion rate of α-CBT-diol ( B). Overall, the use of ammonium sulfate as a nitrogen source demonstrated a positive impact on the growth and bioconversion of α-CBT-diol by the S. maltophilia H3-1 strain. The pH of the fermentation medium plays a crucial role in generating the high-yield production of the desired product; therefore, we also studied the effect of different pH values on the bioconversion rate of α-CBT-diol and biomass production. Our results showed that the S. maltophilia H3-1 strain grew very slowly in an acidic growth medium. The bioconversion rate of α-CBT-diol and biomass production increased proportionally with a rise in the pH value of the fermentation medium. We observed the maximum bioconversion rate of α-CBT-diol (87.5%) and biomass production (0.73) at pH 8. However, both the bioconversion rate and biomass production were severely affected when the pH exceeded 8 in the fermentation medium. This indicates that an overly alkaline pH is not suitable for the bioconversion of α-CBT-diol and the growth of the S. maltophilia H3-1 strain. Therefore, we selected pH 8 as the optimal initial pH of the fermentation medium ( D). It is well established that pH influences the ionization state of the medium, which can directly affect the solubility and availability of nutrients as well as the structural stability of enzymes involved in bioconversion . The slower growth observed at acidic pH levels suggests that the S. maltophilia H3-1 strain may be less efficient at regulating internal pH, leading to a reduced metabolic rate and lower enzyme production . The proportional increase in the bioconversion rate and biomass production with rising pH values reflects the optimal enzyme activity in a slightly alkaline environment, as seen with pH 8. This is consistent with other studies showing that many microbial strains exhibit higher metabolic activity under mildly alkaline conditions . However, the detrimental effect of pH values higher than 8 may be attributed to enzyme denaturation or the disruption of cellular processes due to excess alkalinity, which can impair the overall bioconversion process. The optimal liquid culture conditions for S. maltophilia H3-1 were determined as follows: a bioconversion time of 36 h, a temperature of 40 °C, a pH of 8, 2 g/L maltose as the carbon source, and 2 g/L ammonium sulfate as the nitrogen source, based on the bioconversion rate of α-CBT-diol. Under these conditions, the bioconversion rate of α-CBT-diol reached 93.3%, resulting in a theoretical farnesal production of 201 mg/L, assuming a 1:1 molar conversion. The results indicate that the strain exhibited its highest bioconversion efficiency under these optimized growth conditions.
To confirm the localization of the enzymes catalyzing the conversion of α-CBT-diol into farnesal, reaction mixtures were prepared with α-CBT-diol and the cytosolic and membrane components of S. maltophilia H3-1. A,B, and c illustrate that α-CBT-diol gradually degraded over time and nearly completed bioconversion after approximately 3 h in the test tube experiment. The bioconversion was accompanied by forming a newly found compound, indicating the enzymatic breakdown of α-CBT-diol. Enzymatic activity was detected exclusively in the membrane component, while no bioconversion activity was observed in the cytosolic fraction. This suggests that the enzymes responsible for α-CBT-diol bioconversion are associated with the plasma membrane. This localization of the enzymes to the membrane is consistent with many other microbial bioconversion systems, where membrane-bound enzymes often catalyze the bioconversion of hydrophobic or membrane-associated compounds. The membrane environment likely facilitates the accessibility of α-CBT-diol, which could interact more efficiently with the enzymes due to its lipid-like structure . The newly found compound was isolated using UPLC and identified using GC-MS . After vacuum concentration and freeze-drying, a white powdery substance was obtained. The structure of this newly found compound was determined using nuclear magnetic resonance (NMR) analysis . As shown in A, the pink-shadowed peak represents the newly found compound produced from α-CBT-diol. In this study, we predicted that the bioconversion pathway of α-CBT-diol to farnesal involves a series of enzymatic reactions. In the first step, CBT-hydroxylase, likely a monooxygenase encoded by the cbtA gene, catalyzes the hydroxylation of α-CBT-diol, producing hydroxylated α-CBT-diol. This step introduces a hydroxyl group to the substrate, increasing its hydrophilicity, and consumes NADH/NADPH as an electron donor to activate molecular oxygen. In the second step, dehydratase, encoded by the cbtB gene, catalyzes the removal of a water molecule (dehydration) and an oxidation reaction, forming oxidized α-CBT-diol, a compound with a conjugated double-bond system. This step reduces NAD⁺ to NADH, contributing to the cofactor balance. The third step involves aldehyde synthase (encoded by cbtC), which processes the oxidized intermediate through a cleavage reaction to generate farnesal precursor, a compound containing an aldehyde group. This step does not directly involve the consumption or production of NADH. In the final step, oxidoreductase, encoded by the cbtD gene, catalyzes the oxidation of the farnesal precursor to yield farnesal, a high-value aromatic aldehyde. This step also reduces NAD⁺ to NADH. Overall, the pathway consumes one molecule of NADH/NADPH during hydroxylation (Step 1) and produces two molecules of NADH during oxidation reactions (Steps 2 and 4), effectively driving the conversion of α-CBT-diol into farnesal. This pathway highlights the enzymatic efficiency and cofactor utilization in transforming a complex diterpenoid into a commercially valuable compound ( B).
3.1. Isolation of S. maltophilia H3-1 Strain from Soil S. maltophilia H3-1 strain was isolated from soil (at a depth of 3–7 cm) collected from Sanmenxia City, Henan Province, China. We weighed 10 g of the soil sample, shook it on an ultra-clean workbench to break it up, and then added it to a triangular flask containing 100 mL of sterile water. Afterward, a 1:10 sample suspension was prepared by soaking it overnight. Then, using a sterilized pipette, 1 mL of the soil sample was transferred into 100 mL of Czapek–Dox medium {(K 2 HPO 4 (1.00 g/L), MgSO 4 ·7H 2 O (0.50 g/L), KCl (0.50 g/L), NaNO 3 (3.00 g/L), FeSO 4 ·7H 2 O (0.01 g/L), sucrose (30.00 g/L)}. The Czapek–Dox medium containing the soil sample was incubated at 30 °C in a rotary incubator set at 150 rpm for 24 h to allow bacterial growth. The S. maltophilia H3-1 strain was subsequently isolated by adding 1 mL of the bacterial culture obtained from the Czapek–Dox medium into 100 mL of selective medium {(MgSO 4 ·7H 2 O (0.500 g/L), FeSO 4 ·7H 2 O (0.005 g/L), NaCl (0.500 g/L), KH 2 PO 4 (0.650 g/L), K 2 HPO 4 (1.000 g/L), MnSO 4 (0.001 g/L), (NH 4 ) 2 ·SO 4 (0.500 g/L), Na 2 MoO 4 ·2H 2 O (0.005 g/L), CaCl 2 ·2H 2 O (0.100 g/L)} containing α-CBT-diol (0.3 g/L) and incubated at 30 °C in a rotary incubator set at 150 rpm for 2 days. This study used the fermentation medium (selective medium with α-CBT-diol) without the bacterial inoculum as a blank. The bacterial strain, which degraded the α-CBT-diol, was identified by monitoring the change in the color of the fermentation media and analyzing the sample by GC-MS. The 1 mL culture of the α-CBT-diol-degrading bacterial strain was inoculated in the sterilized LB medium {(peptone (10 g/L), NaCl (10 g/L), yeast powder (5 g/L)}, which was then incubated at 30 °C in a rotary incubator set at 150 rpm for 24 h. The bacterial culture was then serially diluted in 10 −2 , 10 −4 , and 10 − ⁶ dilutions and spread on plates of separation medium {(selective medium with α-CBT-diol (0.3 g/L) and ager (20 g/L)} in triplicate and incubated at 30 °C for 2 days. The single colonies with a well-defined shape and transparent zones were selected for further purification by repeated streaking until no mixed colonies were visible on the plate. The single colonies were then re-screened using the separation medium. The colonies with clear transparent zones were inoculated into 100 mL of fermentation medium incubated at 30 °C in a rotary incubator set at 150 rpm for 2 days. GC-MS detected the bioconversion products of α-CBT-diol. We analyzed the product’s structure using NMR to verify the resulting product. The isolated S. maltophilia H3-1 strain was then stored in 60% ( w / v ) glycerol (glycerol to strain ratio of 1:1) and preserved at −80 °C. All inoculations were performed on an ultra-clean workbench. 3.2. Morphological and Phylogenetic Classification of S. maltophilia H3-1 Strain The cell morphology of the S. maltophilia H3-1 strain was analyzed and characterized using a confocal microscope (LEIKA ICC50, Leica Microsystems, Wetzlar, Germany). The gram staining was performed to classify the S. maltophilia strain H3-1 as a Gram-negative bacterium. The genomic DNA of S. maltophilia strain H3-1 was isolated after culturing the strain in an LB medium for 12 h. The bacterial genomic DNA isolation kit (Norgen Biotek Corp, Thorold, ON, Canada) was used as per the manufacturer’s protocol. The primers (forward) 5′-CAGAGTTTGATCCTGGCT-3′ and (reverse) 5′-AGGAGGTGATCCAGCCGCA-3′ were used to amplify the 16s rDNA using genomic DNA as a template. Shanghai Bioengineering Co., Ltd., Shanghai, China, performed the sequencing of PCR products. The 16S rDNA sequences of Stenotrophomonas genus strains were downloaded from NCBI for the phylogenetic analysis of the bacterial strain isolated in this study. The BLAST was used for sequence comparison, and the maximum likelihood method was employed to construct phylogenetic trees using MEGA11. The 16S rDNA sequence of S. maltophilia strain H3-1 was submitted with accession number QQ588742. 3.3. Optimization of Growth Parameters of S. maltophilia H3-1 Strain To achieve the optimal growth and efficient bioconversion of α-CBT-diol, several growth parameters were optimized, including (i) the initial concentration of α-CBT-diol, (ii) the fermentation time, (iii) the fermentation temperature, (iv) the carbon source and content, (v) the nitrogen source and content, and (vi) the initial pH of the fermentation medium to support the growth of S. maltophilia strain H3-1. The optimum fermentation time was determined by sampling the culture of S. maltophilia strain H3-1 grown in a fermentation medium at different times: 0 h, 6 h, 12 h, 18 h, 24 h, 30 h, 36 h, 42 h, 48 h, 54 h, 60 h, 66 h, 72 h, 78 h and 84 h. The rotation speed of the rotary incubators for all experiments was set at 150 rpm, and the temperature was maintained at 30 °C, except during the temperature optimization experiment. The OD₆₀₀ was measured using a UV-1700 UV-Vis Spectrophotometer (Shanghai Macylab Instrument Co. Shanghai, China). A sterile fermentation medium was used as a blank control, and the measurements were repeated three times. Subsequently, we optimized the following growth parameters: the initial concentration of α-CBT-diol (1 mg/mL, 2 mg/mL, 3 mg/mL, 4 mg/mL, 5 mg/mL, 6 mg/mL, 7 mg/mL, 8 mg/mL); temperature (25 °C, 30 °C, 35 °C, 40 °C, 45 °C and 50 °C); carbon source (glucose, fructose, maltose, sucrose, lactose β-Cyclodextrin); carbon source concentration (0.5 g/L, 1 g/L, 2 g/L, 4 g/L, 6 g/L, 8 g/L, 16 g/L); nitrogen source (ammonium sulfate, sodium nitrate, potassium nitrate, yeast powder, peptone, urea); nitrogen source concentration (0.5 g/L, 1 g/L, 2 g/L, 4 g/L, 6 g/L, 8 g/L, 16 g/L); and initial pH (5, 6, 7, 8, 9, 10). 3.4. Evaluate the Cellular Localization of Enzymes Catalyzing Bioconversion of α-CBT-diol into Farnesal A 1% inoculum of S. maltophilia strain H3-1 was added to 100 mL of LB medium and grown for 24 h in a rotary incubator set at 150 rpm and 30 °C. The cell pellet was obtained by centrifuging the cell culture at 12,857× g for 20 min at 4 °C and was washed three times with BPS buffer (pH 7). The cells were disrupted using a sonicator, which was operated with a 2 s ON and 4 s OFF cycle for 15 min. The cell suspension temperature was maintained at 4 °C, and 66.7% power was applied. The cytosolic and membrane components, including the plasma membrane, were separated by centrifuging the suspension at 12,857× g for 10 min at 4 °C. The presence of the enzymes capable of degrading α-CBT-diol was determined by mixing 0.3 g/L of α-CBT-diol with the cytosolic and membrane components dissolved in 5 mL of PBS. The reaction mixtures were incubated separately for 4 h in a shaking incubator set at 150 rpm and 30 °C. Samples of 1.5 mL were taken at 1 h, 2 h, and 3 h and centrifuged at 12,857× g at 4 °C for 5 min. The supernatants were collected and filtered using a 0.22 μm filter for ultra-high-performance liquid chromatography (UPLC) analysis to monitor the bioconversion reaction. Chromatographic separation was performed on an ACQUITY UPLC BEH C18 column (2.1 mm × 100 mm; 1.7 μm particle size) using an ACQUITY UPLC System with 2D LC Technology (Waters, Milford, MA, USA) equipped with a UV-Vis detector. The mobile phase consisted of acetonitrile (solvent A) and ultrapure water (solvent B), following a gradient program: 0–10 min, 70% A; 6–11 min, 100% A; and 11–16 min, 80% A/20% B. The flow rate was set at 0.3 mL/min, and the column temperature was maintained at 35 °C. The bioconversion product of α-CBT-diol was identified and confirmed by GC-MS. 3.5. Determination of Bioconversion Rate of α-CBT-diol The bioconversion rate of α-CBT-diol was determined by preparing a starter culture of S. maltophilia strain H3-1. A 0.5% inoculum of this strain was grown in 100 mL LB medium for 24 h. Following this, 1% of the starter culture was transferred to a 100 mL fermentation medium and incubated at 30 °C in a rotary incubator set at 150 rpm. The experiment was conducted in triplicate. At various time intervals (6 h, 12 h, 18 h, 24 h, 30 h, 36 h, 42 h, 48 h, 54 h, 60 h, 66 h, and 72 h), the optical density (OD) at 600 nm was recorded, and the remaining culture was centrifuged at 12,857× g . The bioconversion product (farnesal) of α-CBT-diol and non-degraded α-CBT-diol were extracted from the supernatant using dichloromethane. The content of non-degraded α-CBT-diol was detected and quantified using GC-MS. The bioconversion rate was calculated using the following formula: B i o c o n v e r s i o n r a t e o f α − C B T − d i o l = D e c r e a s e d c o n c e n t r a t i o n o f α − C B T − d i o l O r i g i n a l c o n c e n t r a t i o n o f α − C B T − d i o l × 100 % 3.6. Extraction and Detection of Bioconversion of α-CBT-diol to Farnesal The S. maltophilia strain H3-1 was grown in 100 mL of fermentation medium for 48 h and centrifuged at 12,857× g for 20 min. The supernatant was used to extract the bioconversion product, farnesal, from α-CBT-diol using 100 mL of CH 2 Cl 2 . The supernatant and CH 2 Cl 2 were mixed evenly for 10 min using a vortex, and this process was repeated five times. The organic phase was collected and dried using a rotary evaporator . An HP-5 MS column (5% phenyl methyl silox, dimensions: 30 m × 0.25 mm × 0.25 μm) was used with helium gas as the carrier at a 1 mL/min flow rate in the GC-MS. The GC-MS program was designed as follows: the temperature was raised from 50 °C to 200 °C at a rate of 5 °C/min and then increased to 260 °C at a rate of 3 °C/min. The inlet temperature was set to 280 °C, with a split ratio 3:1, and the sample volume was 1 μL. The GC-MS (Agilent 6890 a/5975 c, Agilent Technologies Inc., Santa Clara, CA, USA) was operated in full scan mode. The MS conditions were as follows: the transmission line temperature was 280 °C; the ion source temperature was 280 °C; the quadrupole temperature was 150 °C; the ionization mode was electron ionization (EI) with an electron energy of 70 eV; the solvent delay time was 8 min; and the scanning range ( m / z ) was 35–550 u. The 99.98% pure standard of farnesal was used for detection and confirmation.
S. maltophilia H3-1 Strain from Soil S. maltophilia H3-1 strain was isolated from soil (at a depth of 3–7 cm) collected from Sanmenxia City, Henan Province, China. We weighed 10 g of the soil sample, shook it on an ultra-clean workbench to break it up, and then added it to a triangular flask containing 100 mL of sterile water. Afterward, a 1:10 sample suspension was prepared by soaking it overnight. Then, using a sterilized pipette, 1 mL of the soil sample was transferred into 100 mL of Czapek–Dox medium {(K 2 HPO 4 (1.00 g/L), MgSO 4 ·7H 2 O (0.50 g/L), KCl (0.50 g/L), NaNO 3 (3.00 g/L), FeSO 4 ·7H 2 O (0.01 g/L), sucrose (30.00 g/L)}. The Czapek–Dox medium containing the soil sample was incubated at 30 °C in a rotary incubator set at 150 rpm for 24 h to allow bacterial growth. The S. maltophilia H3-1 strain was subsequently isolated by adding 1 mL of the bacterial culture obtained from the Czapek–Dox medium into 100 mL of selective medium {(MgSO 4 ·7H 2 O (0.500 g/L), FeSO 4 ·7H 2 O (0.005 g/L), NaCl (0.500 g/L), KH 2 PO 4 (0.650 g/L), K 2 HPO 4 (1.000 g/L), MnSO 4 (0.001 g/L), (NH 4 ) 2 ·SO 4 (0.500 g/L), Na 2 MoO 4 ·2H 2 O (0.005 g/L), CaCl 2 ·2H 2 O (0.100 g/L)} containing α-CBT-diol (0.3 g/L) and incubated at 30 °C in a rotary incubator set at 150 rpm for 2 days. This study used the fermentation medium (selective medium with α-CBT-diol) without the bacterial inoculum as a blank. The bacterial strain, which degraded the α-CBT-diol, was identified by monitoring the change in the color of the fermentation media and analyzing the sample by GC-MS. The 1 mL culture of the α-CBT-diol-degrading bacterial strain was inoculated in the sterilized LB medium {(peptone (10 g/L), NaCl (10 g/L), yeast powder (5 g/L)}, which was then incubated at 30 °C in a rotary incubator set at 150 rpm for 24 h. The bacterial culture was then serially diluted in 10 −2 , 10 −4 , and 10 − ⁶ dilutions and spread on plates of separation medium {(selective medium with α-CBT-diol (0.3 g/L) and ager (20 g/L)} in triplicate and incubated at 30 °C for 2 days. The single colonies with a well-defined shape and transparent zones were selected for further purification by repeated streaking until no mixed colonies were visible on the plate. The single colonies were then re-screened using the separation medium. The colonies with clear transparent zones were inoculated into 100 mL of fermentation medium incubated at 30 °C in a rotary incubator set at 150 rpm for 2 days. GC-MS detected the bioconversion products of α-CBT-diol. We analyzed the product’s structure using NMR to verify the resulting product. The isolated S. maltophilia H3-1 strain was then stored in 60% ( w / v ) glycerol (glycerol to strain ratio of 1:1) and preserved at −80 °C. All inoculations were performed on an ultra-clean workbench.
The cell morphology of the S. maltophilia H3-1 strain was analyzed and characterized using a confocal microscope (LEIKA ICC50, Leica Microsystems, Wetzlar, Germany). The gram staining was performed to classify the S. maltophilia strain H3-1 as a Gram-negative bacterium. The genomic DNA of S. maltophilia strain H3-1 was isolated after culturing the strain in an LB medium for 12 h. The bacterial genomic DNA isolation kit (Norgen Biotek Corp, Thorold, ON, Canada) was used as per the manufacturer’s protocol. The primers (forward) 5′-CAGAGTTTGATCCTGGCT-3′ and (reverse) 5′-AGGAGGTGATCCAGCCGCA-3′ were used to amplify the 16s rDNA using genomic DNA as a template. Shanghai Bioengineering Co., Ltd., Shanghai, China, performed the sequencing of PCR products. The 16S rDNA sequences of Stenotrophomonas genus strains were downloaded from NCBI for the phylogenetic analysis of the bacterial strain isolated in this study. The BLAST was used for sequence comparison, and the maximum likelihood method was employed to construct phylogenetic trees using MEGA11. The 16S rDNA sequence of S. maltophilia strain H3-1 was submitted with accession number QQ588742.
To achieve the optimal growth and efficient bioconversion of α-CBT-diol, several growth parameters were optimized, including (i) the initial concentration of α-CBT-diol, (ii) the fermentation time, (iii) the fermentation temperature, (iv) the carbon source and content, (v) the nitrogen source and content, and (vi) the initial pH of the fermentation medium to support the growth of S. maltophilia strain H3-1. The optimum fermentation time was determined by sampling the culture of S. maltophilia strain H3-1 grown in a fermentation medium at different times: 0 h, 6 h, 12 h, 18 h, 24 h, 30 h, 36 h, 42 h, 48 h, 54 h, 60 h, 66 h, 72 h, 78 h and 84 h. The rotation speed of the rotary incubators for all experiments was set at 150 rpm, and the temperature was maintained at 30 °C, except during the temperature optimization experiment. The OD₆₀₀ was measured using a UV-1700 UV-Vis Spectrophotometer (Shanghai Macylab Instrument Co. Shanghai, China). A sterile fermentation medium was used as a blank control, and the measurements were repeated three times. Subsequently, we optimized the following growth parameters: the initial concentration of α-CBT-diol (1 mg/mL, 2 mg/mL, 3 mg/mL, 4 mg/mL, 5 mg/mL, 6 mg/mL, 7 mg/mL, 8 mg/mL); temperature (25 °C, 30 °C, 35 °C, 40 °C, 45 °C and 50 °C); carbon source (glucose, fructose, maltose, sucrose, lactose β-Cyclodextrin); carbon source concentration (0.5 g/L, 1 g/L, 2 g/L, 4 g/L, 6 g/L, 8 g/L, 16 g/L); nitrogen source (ammonium sulfate, sodium nitrate, potassium nitrate, yeast powder, peptone, urea); nitrogen source concentration (0.5 g/L, 1 g/L, 2 g/L, 4 g/L, 6 g/L, 8 g/L, 16 g/L); and initial pH (5, 6, 7, 8, 9, 10).
A 1% inoculum of S. maltophilia strain H3-1 was added to 100 mL of LB medium and grown for 24 h in a rotary incubator set at 150 rpm and 30 °C. The cell pellet was obtained by centrifuging the cell culture at 12,857× g for 20 min at 4 °C and was washed three times with BPS buffer (pH 7). The cells were disrupted using a sonicator, which was operated with a 2 s ON and 4 s OFF cycle for 15 min. The cell suspension temperature was maintained at 4 °C, and 66.7% power was applied. The cytosolic and membrane components, including the plasma membrane, were separated by centrifuging the suspension at 12,857× g for 10 min at 4 °C. The presence of the enzymes capable of degrading α-CBT-diol was determined by mixing 0.3 g/L of α-CBT-diol with the cytosolic and membrane components dissolved in 5 mL of PBS. The reaction mixtures were incubated separately for 4 h in a shaking incubator set at 150 rpm and 30 °C. Samples of 1.5 mL were taken at 1 h, 2 h, and 3 h and centrifuged at 12,857× g at 4 °C for 5 min. The supernatants were collected and filtered using a 0.22 μm filter for ultra-high-performance liquid chromatography (UPLC) analysis to monitor the bioconversion reaction. Chromatographic separation was performed on an ACQUITY UPLC BEH C18 column (2.1 mm × 100 mm; 1.7 μm particle size) using an ACQUITY UPLC System with 2D LC Technology (Waters, Milford, MA, USA) equipped with a UV-Vis detector. The mobile phase consisted of acetonitrile (solvent A) and ultrapure water (solvent B), following a gradient program: 0–10 min, 70% A; 6–11 min, 100% A; and 11–16 min, 80% A/20% B. The flow rate was set at 0.3 mL/min, and the column temperature was maintained at 35 °C. The bioconversion product of α-CBT-diol was identified and confirmed by GC-MS.
The bioconversion rate of α-CBT-diol was determined by preparing a starter culture of S. maltophilia strain H3-1. A 0.5% inoculum of this strain was grown in 100 mL LB medium for 24 h. Following this, 1% of the starter culture was transferred to a 100 mL fermentation medium and incubated at 30 °C in a rotary incubator set at 150 rpm. The experiment was conducted in triplicate. At various time intervals (6 h, 12 h, 18 h, 24 h, 30 h, 36 h, 42 h, 48 h, 54 h, 60 h, 66 h, and 72 h), the optical density (OD) at 600 nm was recorded, and the remaining culture was centrifuged at 12,857× g . The bioconversion product (farnesal) of α-CBT-diol and non-degraded α-CBT-diol were extracted from the supernatant using dichloromethane. The content of non-degraded α-CBT-diol was detected and quantified using GC-MS. The bioconversion rate was calculated using the following formula: B i o c o n v e r s i o n r a t e o f α − C B T − d i o l = D e c r e a s e d c o n c e n t r a t i o n o f α − C B T − d i o l O r i g i n a l c o n c e n t r a t i o n o f α − C B T − d i o l × 100 %
The S. maltophilia strain H3-1 was grown in 100 mL of fermentation medium for 48 h and centrifuged at 12,857× g for 20 min. The supernatant was used to extract the bioconversion product, farnesal, from α-CBT-diol using 100 mL of CH 2 Cl 2 . The supernatant and CH 2 Cl 2 were mixed evenly for 10 min using a vortex, and this process was repeated five times. The organic phase was collected and dried using a rotary evaporator . An HP-5 MS column (5% phenyl methyl silox, dimensions: 30 m × 0.25 mm × 0.25 μm) was used with helium gas as the carrier at a 1 mL/min flow rate in the GC-MS. The GC-MS program was designed as follows: the temperature was raised from 50 °C to 200 °C at a rate of 5 °C/min and then increased to 260 °C at a rate of 3 °C/min. The inlet temperature was set to 280 °C, with a split ratio 3:1, and the sample volume was 1 μL. The GC-MS (Agilent 6890 a/5975 c, Agilent Technologies Inc., Santa Clara, CA, USA) was operated in full scan mode. The MS conditions were as follows: the transmission line temperature was 280 °C; the ion source temperature was 280 °C; the quadrupole temperature was 150 °C; the ionization mode was electron ionization (EI) with an electron energy of 70 eV; the solvent delay time was 8 min; and the scanning range ( m / z ) was 35–550 u. The 99.98% pure standard of farnesal was used for detection and confirmation.
In this study, S. maltophilia H3-1 was successfully isolated from soil and identified through 16S rDNA sequencing. The strain demonstrated high efficiency in the bioconversion of α-CBT-diol into farnesal, a valuable compound widely used in the fragrance, flavor, pharmaceutical, and agricultural industries. By optimizing growth conditions such as the temperature, pH, and carbon and nitrogen sources, we achieved an α-CBT-diol bioconversion rate of 93.27% within 36 h at a temperature of 40 °C, a pH of 8, and using maltose and ammonium sulfate, which resulted in the production of farnesal. The enzymes catalyzing the bioconversion of α-CBT-diol into farnesal were found to be localized to the plasma membrane of the S. maltophilia H3-1 strain, with no activity detected in the cytosolic components.
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Inflammatory Modulation of Toll-like Receptors in Periodontal Ligament Stem Cells: Implications for Periodontal Therapy | b66a8c41-5344-4902-a677-36d98f1c62a7 | 11941712 | Pathologic Processes[mh] | The periodontal tissues, vital for supporting and anchoring teeth within the alveolar bone, are frequently subjected to various immunological challenges . Periodontal disease is initiated by a dysbiotic microbial biofilm that triggers an exaggerated host immune response, leading to persistent inflammation and progressive destruction of the periodontium . The inflammatory microenvironment in periodontitis is characterized by elevated levels of cytokines, including interleukin-1β (IL-1β), tumor necrosis factor-alpha (TNF-α), and interferon-gamma (IFN-γ), which contribute to the breakdown of the extracellular matrix and alveolar bone loss . This pathological process disrupts tissue homeostasis and impairs the natural regenerative capacity of periodontal structures . In this context, periodontal ligament mesenchymal stem/progenitor cells (PDLSCs) are key cellular players, actively interacting with the surrounding inflammatory microenvironment to regulate immune responses and promote tissue repair . PDLSCs possess unique immunomodulatory properties that allow them to modulate both innate and adaptive immune mechanisms through interactions with inflammatory cytokines, immune cells, and pathogen-associated molecular patterns (PAMPs) . Under physiological conditions, PDLSCs contribute to periodontal homeostasis by differentiating into fibroblasts, osteoblasts, and cementoblasts, supporting the structural integrity of the periodontium . However, inflammatory stimuli can significantly alter PDLSC behavior, affecting their ability to self-renew, differentiate, and exert immunosuppressive functions . This interaction between inflammation and PDLSC-mediated regeneration plays a crucial role in determining the progression or resolution of periodontal disease . Recent studies further emphasize the significant role of PDLSCs in driving various molecular and biological processes at sites of tissue damage or regeneration [ , , ]. PDLSCs not only contribute to tissue remodeling but also interact with immune cells such as macrophages and T cells , influencing the balance between pro-inflammatory and anti-inflammatory responses . Their ability to regulate immune signaling pathways suggests that PDLSCs may serve as potential therapeutic targets for modulating periodontal inflammation and enhancing regenerative outcomes . Toll-like receptors (TLRs) serve as crucial links between the innate and adaptive immune responses by detecting pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) . Ten functional TLRs, both extracellular and intracellular, have been identified and characterized in humans . These receptors exhibit significant immune-modulatory and regenerative capabilities, as TLR activation can influence cellular stemness, differentiation, and immune responses within the local microenvironment . While specific TLR expression profiles have been documented for various mesenchymal stem cells derived from the oral cavity, highlighting distinct differences based on their tissue of origin [ , , , , ], a comprehensive TLR expression profile for periodontal ligament stem cells (PDLSCs) has not yet been established . Furthermore, there is a lack of information regarding how inflammation, particularly in the context of periodontal disease, influences TLR expression in these cells. This study aims to characterize, for the first time, the complete TLR expression profile of PDLSCs and to investigate how a standardized cytokine-mediated microinflammatory condition, associated with periodontal disease, could modulate this profile.
2.1. Isolation and Culture of PDLSCs The isolation and culture of periodontal ligament mesenchymal stem/progenitor cells (PDLSCs) were conducted in alignment with established protocols for oral mesenchymal stem cells (MSCs) using the tissue explant method . Third molars from six individuals (age in years and gender: 19♂, 19♀, 21♂, 22♂, 23♂, 35♀) were surgically extracted at the community practice of Dr. Kerscher, Dr. Körner, and Föge in Kiel (Ethical Committee IRB-Approval D513/17). Following extraction, the teeth were immediately transferred into sterile 50 mL tubes (Sarstedt AG, Nümbrecht, Germany) containing 15 mL of the basic medium. This medium consisted of Minimum Essential Medium Eagle Alpha Modification (α-MEM, Sigma-Aldrich GmbH, Hamburg, Germany) supplemented with antibiotics (100 U/mL penicillin, 100 µg/mL streptomycin), 1% amphotericin, 400 mmol/mL L-glutamine (all from Biochrom AG, Berlin, Germany) and 15% fetal calf serum (FCS, HyClone, Logan, UT, USA). Subsequent processing took place in the cell culture laboratory of the Clinic for Conservative Dentistry and Periodontology of Kiel University under a safety cabinet (Hera Safe, Thermo Fisher Scientific, Waltham, MA, USA). The basal medium was removed (Vacusafe Comfort, IBS Integra Biosciences, Chur, Switzerland), and the teeth were washed three times with phosphate-buffered saline (PBS) (Biochrom), briefly disinfected with 70% ethanol, and washed again with PBS. The periodontal ligament tissue was carefully dissected from the tooth root using sterile instruments into approximately 3 mm pieces and allowed to adhere to the bottom of dry 75 mL culture flasks (Sarstedt AG, Nümbrecht, Germany) for 30 min. The samples were then covered with the basic medium and incubated undisturbed at 37 °C with 5% CO 2 for one week in an incubator (Binder GmbH, Tuttlingen, Germany), and the medium was renewed thrice a week. When the cells reached 80% confluence, they were passaged. Cells were separated using magnetically activated cell sorting (MACS), which involved attaching STRO-1 surface markers to anti-STRO-1 antibodies and anti-IgM Micro Beads ( ) according to the manufacturers’ protocols. MACS positively sorted cells, identified as periodontal mesenchymal stem/progenitor cells (PDLSCs) were expanded in culture and utilized up to passage 5 to ensure cellular viability and consistency. For all experiments, individual cell lines were maintained separately to preserve their distinct biological characteristics and avoid cross-contamination. 2.2. Colony-Forming Units (CFUs) PDLSCs were seeded at a density of 1.63 cells/cm 2 and cultured under standard conditions. A colony was identified as a cluster containing 50 or more cells. After 12 days, representative samples were fixed with 4% formalin and stained with 0.1% crystal violet. The remaining PDLSCs that formed CFUs were individually isolated using cell scrapers, transferred to new 75 mL flasks, and further cultured under standard conditions. 2.3. Flow Cytometric Analysis of MSCs Surface Markers When PDLSCs reached 80% confluence, their predefined surface markers were analyzed using flow cytometry, following the guidelines established by Dominici et al. and similar to previous investigations . Standard procedures were employed, including the use of FcR Blocking Reagent (Miltenyi Biotec) to prevent non-specific Fc receptor binding, ensuring accurate antibody-target interaction. The cells were incubated with fluorochrome-conjugated monoclonal antibodies, including CD73, CD90, and CD105 as positive MSC markers and CD14, CD34, and CD45 as negative markers ( ). Corresponding isotype controls were used to establish the baseline fluorescence and exclude non-specific binding ( ). The stained cells were analyzed using the FACSCalibur E6370 system (Becton Dickinson, Heidelberg, Germany), and data acquisition was performed with FACSComp 5.1.1 software. The gating strategy was implemented to ensure accurate and reproducible results. Initially, forward scatter (FSC) and side scatter (SSC) parameters were used to gate viable cells while excluding debris and dead cells. To further refine the analysis, 7-AAD was applied as a live/dead stain, ensuring that only live cells were included. Single-cell gating was then performed by plotting FSC height (FSC-H) against FSC area (FSC-A), thereby eliminating doublets and cell aggregates. Following the selection of viable single cells, isotype control staining was used to set the fluorescence threshold and define the negative population for each marker. Fluorescence intensity shifts were measured to confirm the positive expression of MSC markers. Cells expressing CD73, CD90, and CD105 were gated as MSC-like populations, whereas cells displaying CD14, CD34, and CD45 were considered hematopoietic and excluded. 2.4. Multilineage Differentiation of PDLSCs To evaluate the osteogenic differentiation potential, 2 × 10 4 third passage PDLSCs were plated on 6-well culture plates and cultured in an osteogenic induction medium (PromoCell, Heidelberg, Germany). For comparison, identical samples were simultaneously cultured in a basic medium. After two weeks, calcified deposits were stained with Alizarin Red (Sigma-Aldrich), and the expression of runt-related transcription factor 2 (RUNX) and alkaline phosphatase (ALP) and Osteonectin (SPARC) was assessed using real-time polymerase chain reaction (PCR; LightCycler; Roche Molecular Biochemicals, Indianapolis, IN, USA). For adipogenic differentiation, 3 × 10 5 third passage PDLSCs were cultured on 6-well plates in an adipogenic induction medium (PromoCell), with control samples maintained in a basic medium. Lipid droplet accumulation was detected using Oil Red O staining (Sigma-Aldrich), and the expression of peroxisome proliferator-activated receptor gamma (PPARγ) and lipoprotein lipase (LPL) was measured using PCR after 21 days. Chondrogenic differentiation was initiated by culturing micro-masses of 3 × 10 4 third passage PDLSCs in a chondrogenic induction medium (PromoCell) on 6-well plates (Sarstedt). Control samples were cultured in a basic medium. On day 35, cells were stained with Alcian Blue (Sigma-Aldrich) to visualize the produced glycosaminoglycans, and aggrecan (ACAN) mRNA expression, a cartilage-specific proteoglycan core protein, was analyzed. The induction medium was refreshed three times a week. All primers were provided by Roche ( ). 2.5. Inflammatory Medium To analyze the TLR expression profile of PDLSCs in a standardized inflammatory microenvironment, the cells were exposed to the basic medium supplemented with 25 ng/mL IL-1β, 10 3 U/mL IFN-γ, 50 ng/mL TNF-α, and 3 × 10 3 U/mL IFN-α (PeproTech, Hamburg, Germany) for 18 h as previously described (PDLSCs-i). The control group received only the basic medium (PDLSCs). 2.6. TLR Expression at Gene Level To evaluate the gene expression levels of TLRs in PDLSCs and PDLSCs-i, messenger RNA (mRNA) was extracted from PDLSCs for each patient in both examined groups using the RNeasy kit (Qiagen, Hilden, Germany). Complementary DNA (cDNA) was synthesized from RNA (1 μg/μL) through reverse transcription, utilizing the QuantiTect Reverse Transcription Kit (Qiagen, Hilden, Germany) in accordance with the manufacturer’s instructions. Real-time polymerase chain reaction (PCR) was conducted using a LightCycler 96 system (Roche Diagnostics, Mannheim, Germany) in a total reaction volume of 20 μL, which included 4 pmol TLR primer, 10 μL Fast Start Essential DNA Probes Master (Roche Diagnostics, Mannheim, Germany), and 5 μL sample cDNA. Real-Time Ready Assays ( ) were employed following the manufacturer’s guidelines. Phosphoglycerate kinase 1 (PGK1) served as the reference gene, based on previous studies , which demonstrated its stable expression by testing 19 candidate reference genes in both stimulated and unstimulated gingival MSCs using NormFinder analysis. Relative gene expression was quantified using the 2 −ΔΔCt method, where ΔCt is defined as Ct (target gene)—Ct (PGK1), as described in previous studies [ , , ]. All experiments were performed in triplicate and the results were averaged. 2.7. TLR Expression at Protein Level PDLSCs and PDLSCs-i were analyzed for their protein-level expression of TLRs 1–10, using flow cytometry similar to previous investigations [ , , ]. The cells were fixed and permeabilized using Cytofix/Cytoperm (BD Biosciences, Franklin Lakes, NJ, USA). Viability staining was conducted with VioBlue (Miltenyi Biotec). The binding of primary antibodies and their isotype controls (all listed in ) was performed using 1% FCS. Consequently, results were evaluated with FACSCalibur E6370 and FACSComp 5.1.1 software (Becton Dickinson, Heidelberg, Germany). 2.8. Null Hypothesis This study was conducted under the null hypothesis (H 0 ) that inflammatory stimulation does not significantly alter the expression of TLRs in PDLSCs at the mRNA and protein levels. The alternative hypothesis (H 1 ) proposed that inflammatory conditions would lead to significant modulation of TLR expression, reflecting the adaptive immune responses of PDLSCs in an inflamed periodontal microenvironment. 2.9. Statistical Analysis The Kolmogorov–Smirnov Test was performed to test for the normality of the data. Data were not normally distributed. Differences between PDLSCs and PDLSCs-i were evaluated using the non-parametric Wilcoxon Signed Rank test using SPSS software (Version 28.0, IBM Corporation, Armonk, NY, USA). The level of significance was set at p = 0.05.
The isolation and culture of periodontal ligament mesenchymal stem/progenitor cells (PDLSCs) were conducted in alignment with established protocols for oral mesenchymal stem cells (MSCs) using the tissue explant method . Third molars from six individuals (age in years and gender: 19♂, 19♀, 21♂, 22♂, 23♂, 35♀) were surgically extracted at the community practice of Dr. Kerscher, Dr. Körner, and Föge in Kiel (Ethical Committee IRB-Approval D513/17). Following extraction, the teeth were immediately transferred into sterile 50 mL tubes (Sarstedt AG, Nümbrecht, Germany) containing 15 mL of the basic medium. This medium consisted of Minimum Essential Medium Eagle Alpha Modification (α-MEM, Sigma-Aldrich GmbH, Hamburg, Germany) supplemented with antibiotics (100 U/mL penicillin, 100 µg/mL streptomycin), 1% amphotericin, 400 mmol/mL L-glutamine (all from Biochrom AG, Berlin, Germany) and 15% fetal calf serum (FCS, HyClone, Logan, UT, USA). Subsequent processing took place in the cell culture laboratory of the Clinic for Conservative Dentistry and Periodontology of Kiel University under a safety cabinet (Hera Safe, Thermo Fisher Scientific, Waltham, MA, USA). The basal medium was removed (Vacusafe Comfort, IBS Integra Biosciences, Chur, Switzerland), and the teeth were washed three times with phosphate-buffered saline (PBS) (Biochrom), briefly disinfected with 70% ethanol, and washed again with PBS. The periodontal ligament tissue was carefully dissected from the tooth root using sterile instruments into approximately 3 mm pieces and allowed to adhere to the bottom of dry 75 mL culture flasks (Sarstedt AG, Nümbrecht, Germany) for 30 min. The samples were then covered with the basic medium and incubated undisturbed at 37 °C with 5% CO 2 for one week in an incubator (Binder GmbH, Tuttlingen, Germany), and the medium was renewed thrice a week. When the cells reached 80% confluence, they were passaged. Cells were separated using magnetically activated cell sorting (MACS), which involved attaching STRO-1 surface markers to anti-STRO-1 antibodies and anti-IgM Micro Beads ( ) according to the manufacturers’ protocols. MACS positively sorted cells, identified as periodontal mesenchymal stem/progenitor cells (PDLSCs) were expanded in culture and utilized up to passage 5 to ensure cellular viability and consistency. For all experiments, individual cell lines were maintained separately to preserve their distinct biological characteristics and avoid cross-contamination.
PDLSCs were seeded at a density of 1.63 cells/cm 2 and cultured under standard conditions. A colony was identified as a cluster containing 50 or more cells. After 12 days, representative samples were fixed with 4% formalin and stained with 0.1% crystal violet. The remaining PDLSCs that formed CFUs were individually isolated using cell scrapers, transferred to new 75 mL flasks, and further cultured under standard conditions.
When PDLSCs reached 80% confluence, their predefined surface markers were analyzed using flow cytometry, following the guidelines established by Dominici et al. and similar to previous investigations . Standard procedures were employed, including the use of FcR Blocking Reagent (Miltenyi Biotec) to prevent non-specific Fc receptor binding, ensuring accurate antibody-target interaction. The cells were incubated with fluorochrome-conjugated monoclonal antibodies, including CD73, CD90, and CD105 as positive MSC markers and CD14, CD34, and CD45 as negative markers ( ). Corresponding isotype controls were used to establish the baseline fluorescence and exclude non-specific binding ( ). The stained cells were analyzed using the FACSCalibur E6370 system (Becton Dickinson, Heidelberg, Germany), and data acquisition was performed with FACSComp 5.1.1 software. The gating strategy was implemented to ensure accurate and reproducible results. Initially, forward scatter (FSC) and side scatter (SSC) parameters were used to gate viable cells while excluding debris and dead cells. To further refine the analysis, 7-AAD was applied as a live/dead stain, ensuring that only live cells were included. Single-cell gating was then performed by plotting FSC height (FSC-H) against FSC area (FSC-A), thereby eliminating doublets and cell aggregates. Following the selection of viable single cells, isotype control staining was used to set the fluorescence threshold and define the negative population for each marker. Fluorescence intensity shifts were measured to confirm the positive expression of MSC markers. Cells expressing CD73, CD90, and CD105 were gated as MSC-like populations, whereas cells displaying CD14, CD34, and CD45 were considered hematopoietic and excluded.
To evaluate the osteogenic differentiation potential, 2 × 10 4 third passage PDLSCs were plated on 6-well culture plates and cultured in an osteogenic induction medium (PromoCell, Heidelberg, Germany). For comparison, identical samples were simultaneously cultured in a basic medium. After two weeks, calcified deposits were stained with Alizarin Red (Sigma-Aldrich), and the expression of runt-related transcription factor 2 (RUNX) and alkaline phosphatase (ALP) and Osteonectin (SPARC) was assessed using real-time polymerase chain reaction (PCR; LightCycler; Roche Molecular Biochemicals, Indianapolis, IN, USA). For adipogenic differentiation, 3 × 10 5 third passage PDLSCs were cultured on 6-well plates in an adipogenic induction medium (PromoCell), with control samples maintained in a basic medium. Lipid droplet accumulation was detected using Oil Red O staining (Sigma-Aldrich), and the expression of peroxisome proliferator-activated receptor gamma (PPARγ) and lipoprotein lipase (LPL) was measured using PCR after 21 days. Chondrogenic differentiation was initiated by culturing micro-masses of 3 × 10 4 third passage PDLSCs in a chondrogenic induction medium (PromoCell) on 6-well plates (Sarstedt). Control samples were cultured in a basic medium. On day 35, cells were stained with Alcian Blue (Sigma-Aldrich) to visualize the produced glycosaminoglycans, and aggrecan (ACAN) mRNA expression, a cartilage-specific proteoglycan core protein, was analyzed. The induction medium was refreshed three times a week. All primers were provided by Roche ( ).
To analyze the TLR expression profile of PDLSCs in a standardized inflammatory microenvironment, the cells were exposed to the basic medium supplemented with 25 ng/mL IL-1β, 10 3 U/mL IFN-γ, 50 ng/mL TNF-α, and 3 × 10 3 U/mL IFN-α (PeproTech, Hamburg, Germany) for 18 h as previously described (PDLSCs-i). The control group received only the basic medium (PDLSCs).
To evaluate the gene expression levels of TLRs in PDLSCs and PDLSCs-i, messenger RNA (mRNA) was extracted from PDLSCs for each patient in both examined groups using the RNeasy kit (Qiagen, Hilden, Germany). Complementary DNA (cDNA) was synthesized from RNA (1 μg/μL) through reverse transcription, utilizing the QuantiTect Reverse Transcription Kit (Qiagen, Hilden, Germany) in accordance with the manufacturer’s instructions. Real-time polymerase chain reaction (PCR) was conducted using a LightCycler 96 system (Roche Diagnostics, Mannheim, Germany) in a total reaction volume of 20 μL, which included 4 pmol TLR primer, 10 μL Fast Start Essential DNA Probes Master (Roche Diagnostics, Mannheim, Germany), and 5 μL sample cDNA. Real-Time Ready Assays ( ) were employed following the manufacturer’s guidelines. Phosphoglycerate kinase 1 (PGK1) served as the reference gene, based on previous studies , which demonstrated its stable expression by testing 19 candidate reference genes in both stimulated and unstimulated gingival MSCs using NormFinder analysis. Relative gene expression was quantified using the 2 −ΔΔCt method, where ΔCt is defined as Ct (target gene)—Ct (PGK1), as described in previous studies [ , , ]. All experiments were performed in triplicate and the results were averaged.
PDLSCs and PDLSCs-i were analyzed for their protein-level expression of TLRs 1–10, using flow cytometry similar to previous investigations [ , , ]. The cells were fixed and permeabilized using Cytofix/Cytoperm (BD Biosciences, Franklin Lakes, NJ, USA). Viability staining was conducted with VioBlue (Miltenyi Biotec). The binding of primary antibodies and their isotype controls (all listed in ) was performed using 1% FCS. Consequently, results were evaluated with FACSCalibur E6370 and FACSComp 5.1.1 software (Becton Dickinson, Heidelberg, Germany).
This study was conducted under the null hypothesis (H 0 ) that inflammatory stimulation does not significantly alter the expression of TLRs in PDLSCs at the mRNA and protein levels. The alternative hypothesis (H 1 ) proposed that inflammatory conditions would lead to significant modulation of TLR expression, reflecting the adaptive immune responses of PDLSCs in an inflamed periodontal microenvironment.
The Kolmogorov–Smirnov Test was performed to test for the normality of the data. Data were not normally distributed. Differences between PDLSCs and PDLSCs-i were evaluated using the non-parametric Wilcoxon Signed Rank test using SPSS software (Version 28.0, IBM Corporation, Armonk, NY, USA). The level of significance was set at p = 0.05.
3.1. Phase Contrast Inverted Microscopy and Colony Forming Units Following the initial adherence of the periodontal ligament soft tissue masses, cells began to proliferate out of them, forming adherent fibroblast-like clusters. By the twelfth day, PDLSCs demonstrated colony-forming units (CFUs; A). 3.2. Multilineage Differentiation Potential and PDLSCs Characterization PDLSCs stimulated with osteogenic differentiation medium exhibited calcified deposits, as indicated by Alizarin Red staining, in contrast to control samples. These cells also showed significantly higher expression levels (Median gene copies/PGK1 copies, Q25/Q75) of RUNX (0.0894, 0.0459/0.2365) and ALP (0.0076, 0.0034/0.0105) and SPARC (5.217, 3.546/9.464) compared to controls (RUNX: 0.0246, 0.0139/0.0486; ALP: 0.0015, 0.0003/0.0032; SPARC: 2.950, 1.778/4.320) ( B). In the adipogenic differentiation assay, PDLSCs formed lipid droplets, which were positively stained with Oil Red O, unlike the control samples, and exhibited significantly higher expression of PPARγ (0.0012, 0.0009/0.0017) and LPL (0.0128, 0.0076/0.0457) compared to controls (PPARγ: 0.0003, 0.0002/0.0004; LPL: 0.0000, 0.0000/0.0001) ( C). Chondrogenic differentiation led to the production of glycosaminoglycans in PDLSCs, positively stained with Alcian Blue, in contrast to controls. The expression of ACAN (0.0000, 00/7703793) was higher than that of control samples (0.0000, 0.0000/5154252) ( D). PDLSCs were CD14 − , CD34 − , CD45 − , CD73 + , CD90 + , and CD105 + ( E). 3.3. TLR Expression in PDLSCs and PDLSCs-i PDLSCs and PDLSC-i exhibited different expressions of TLRs on the gene level (Median TLR gene copies/PGK1 copies, Q25/Q75) as shown in ( ), with significant upregulation in TLRs 1 and 2 and a significant downregulation in TLR10 ( p < 0.05). At the protein level, flow cytometric analysis revealed TLR expressions (Median Δfluorescence intensity, Q25/Q75) in both PDLSCs and PDLSC-i, as presented in ( ), with no significant differences observed between the two groups.
Following the initial adherence of the periodontal ligament soft tissue masses, cells began to proliferate out of them, forming adherent fibroblast-like clusters. By the twelfth day, PDLSCs demonstrated colony-forming units (CFUs; A).
PDLSCs stimulated with osteogenic differentiation medium exhibited calcified deposits, as indicated by Alizarin Red staining, in contrast to control samples. These cells also showed significantly higher expression levels (Median gene copies/PGK1 copies, Q25/Q75) of RUNX (0.0894, 0.0459/0.2365) and ALP (0.0076, 0.0034/0.0105) and SPARC (5.217, 3.546/9.464) compared to controls (RUNX: 0.0246, 0.0139/0.0486; ALP: 0.0015, 0.0003/0.0032; SPARC: 2.950, 1.778/4.320) ( B). In the adipogenic differentiation assay, PDLSCs formed lipid droplets, which were positively stained with Oil Red O, unlike the control samples, and exhibited significantly higher expression of PPARγ (0.0012, 0.0009/0.0017) and LPL (0.0128, 0.0076/0.0457) compared to controls (PPARγ: 0.0003, 0.0002/0.0004; LPL: 0.0000, 0.0000/0.0001) ( C). Chondrogenic differentiation led to the production of glycosaminoglycans in PDLSCs, positively stained with Alcian Blue, in contrast to controls. The expression of ACAN (0.0000, 00/7703793) was higher than that of control samples (0.0000, 0.0000/5154252) ( D). PDLSCs were CD14 − , CD34 − , CD45 − , CD73 + , CD90 + , and CD105 + ( E).
PDLSCs and PDLSC-i exhibited different expressions of TLRs on the gene level (Median TLR gene copies/PGK1 copies, Q25/Q75) as shown in ( ), with significant upregulation in TLRs 1 and 2 and a significant downregulation in TLR10 ( p < 0.05). At the protein level, flow cytometric analysis revealed TLR expressions (Median Δfluorescence intensity, Q25/Q75) in both PDLSCs and PDLSC-i, as presented in ( ), with no significant differences observed between the two groups.
Periodontitis is a chronic inflammatory condition that affects the periodontal ligament, gingiva, and alveolar bone . It is primarily initiated by microbial dysbiosis, wherein the oral microbiome shifts towards a pathogenic bacterial composition, leading to an exaggerated host immune response . This prolonged immune activation results in the progressive destruction of the periodontium and, if left untreated, ultimately leads to tooth loss . As a global health concern, periodontitis not only contributes to oral morbidity but has also been strongly associated with systemic conditions such as cardiovascular diseases, diabetes, and adverse pregnancy outcomes . The periodontium harbors various mesenchymal stem cell (MSC) populations, including periodontal ligament stem/progenitor cells (PDLSCs), gingival mesenchymal stem cells (G-MSCs), and alveolar bone mesenchymal stem cells (AB-MSCs) . These cells play a critical role in maintaining periodontal tissue homeostasis and facilitating tissue repair following inflammation and injury . Their regenerative capabilities enable differentiation into essential periodontal cell types—osteoblasts, cementoblasts, and fibroblasts—necessary for tissue restoration . Additionally, these MSCs are integral in modulating immune responses to limit inflammatory damage and promote healing . Recent studies have underscored the potential of targeting MSC populations in regenerative approaches for periodontitis, reinforcing the notion that successful therapeutic strategies must address both microbial dysbiosis and stem cell-mediated regeneration to achieve effective and long-lasting periodontal healing . Toll-like receptors (TLRs) are essential modulators of MSC function, playing key roles in pathogen recognition and immune responses within inflamed periodontal tissues . Certain TLRs have been identified as regulators of MSC processes, including differentiation, migration, and immunomodulation—functions vital for tissue repair in inflammatory environments . This study is the first to comprehensively characterize the TLR expression profile of PDLSCs under both inflamed and non-inflamed conditions. PDLSCs were isolated using anti-STRO-1 antibodies and exhibited typical MSC markers, expressing CD90, CD105, and CD73, while lacking CD14, CD34, and CD45. Their regenerative potential was confirmed through colony formation, multilineage differentiation, and adherence to culture plastic. To simulate the complex inflammatory microenvironment seen in periodontal disease, PDLSCs were exposed to a standardized cytokine cocktail . At the mRNA level, PDLSCs expressed TLRs 1, 2, 3, 4, and 10 under baseline conditions, with TLR10 and TLR3 exhibiting the highest expression. Following inflammatory cytokine stimulation, TLR1, TLR2, and TLR4 were significantly upregulated, whereas TLR3 and TLR10 were downregulated. At the protein level, all ten TLRs were expressed in PDLSCs, with TLR7 and TLR3 exhibiting high expression. The discrepancy between mRNA and protein levels is consistent with known cellular regulatory mechanisms, including post-transcriptional modifications, mRNA stability, and protein degradation . These factors contribute to differential protein expression, influencing the persistence and functional impact of TLRs. Under inflammatory conditions, the protein levels of TLR1, TLR2, TLR5, TLR6, TLR7, TLR8, and TLR9 increased, whereas TLR3, TLR4, and TLR10 levels decreased. Although these changes were not statistically significant, they suggest that TLR protein expression dynamics may require extended exposure to inflammation for substantial modulation or may be regulated by intricate post-translational mechanisms . Comparisons between PDLSCs and other MSCs ( ) indicate that certain TLRs, such as TLR1, TLR2, and TLR4, are consistently expressed across multiple MSC populations in the oral cavity and function as primary bacterial sensors, detecting key periodontal pathogens like Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans . The upregulation of these TLRs reinforces their role in amplifying immune responses during early-stage periodontitis . Interestingly, PDLSCs exhibited uniquely high baseline expression of TLR3 and TLR10. TLR3, which detects viral RNA, has been implicated in regulating MSC function by suppressing inflammatory mediators and promoting osteogenic differentiation, thereby facilitating tissue maturation and regeneration, as seen in G-MSCs . Conversely, TLR10 remains poorly understood but is suggested to have an anti-inflammatory role , potentially acting as a regulatory modulator to maintain periodontal tissue homeostasis . The observed downregulation of TLR3 and TLR10 in inflamed PDLSCs suggests a shift from anti-inflammatory functions of the cells to a bacterially driven pro-inflammatory phenotype, which is characteristic of periodontal disease progression . This aligns with findings that chronic TLR activation by bacterial PAMPs sustains cytokine release, exacerbating tissue destruction and disease progression . Despite the significant mRNA downregulation of TLR3 and TLR10, their proteins remained detectable, suggesting possible post-transcriptional regulatory mechanisms that enable PDLSCs to flexibly adapt their inflammatory responses. These findings emphasize the complex interplay of TLR signaling in PDLSCs in different stages of periodontitis. The upregulation of TLR1 and TLR2 in inflamed PDLSCs enhances periodontal pathogen recognition and immune activation in the initial stages of the disease , but their sustained expression may contribute to chronic inflammation through prolonged cytokine production , NF-κB signaling, and the inhibition of osteogenesis , leading to bone resorption and periodontal destruction . In addition, the downregulation of TLR3 and TLR10 in inflamed PDLSCs suggests a loss of its proposed anti-inflammatory function, which may otherwise counteract excessive immune activation . This reduced expression could contribute to heightened inflammation and further periodontal breakdown, as well as potential systemic complications in the later stages of the disease . These observations suggest that targeting TLR pathways, either by inhibiting TLR-mediated inflammation or enhancing TLRs‘ anti-inflammatory activity, could offer promising therapeutic approaches for periodontitis management. Given the detrimental effects of chronic PDLSCs’ TLR1 and TLR2 activation in an inflammatory milieu, selective inhibition or modulation of these receptors, as well as other periodontitis-associated TLRs, such as TLR4 , may help prevent excessive inflammation while preserving necessary antimicrobial defense mechanisms. TLR antagonists or small-molecule inhibitors that downregulate TLR1/2 and TLR4 activity could reduce pro-inflammatory cytokine production, mitigating inflammation-induced bone loss and restoring immune balance . Additionally, this inhibition has been demonstrated to enhance osteogenic differentiation of PDLSCs under inflammatory conditions, thereby promoting periodontal regeneration [ , , ]. Another strategy could be the modulation of downstream signaling pathways, such as MAPK or NF-κB [ , , ], which could further regulate hyperinflammatory responses while maintaining appropriate pathogen recognition. TLR3 activation may also provide regenerative potential in periodontitis. Studies indicate that synthetic agonists like Poly(I:C) can stimulate TLR3 in MSCs, enhancing anti-inflammatory properties and promoting tissue repair . Pharmacological strategies that reinforce TLR3 expression in PDLSCs could counteract its downregulation during inflammation and further enhance tissue regeneration. This could potentially be achieved by incorporating natural bioactive compounds, such as thymoquinone and polyphenols , as adjunctive periodontal therapies, as suggested by other investigations. Combining these molecular approaches with conventional periodontal treatments, such as professional mechanical plaque removal and novel adjunctive therapies like platelet derivatives , may provide a comprehensive strategy that not only controls inflammation but also supports periodontal regeneration. Furthermore, enhancing TLR10 function could restore immune-regulatory balance , reducing tissue-destructive inflammation and promoting long-term periodontal stability. Future research should explore therapeutic strategies to activate or mimic TLR10 function, investigating its role as a key modulator in preventing immune hyperresponsiveness in periodontitis. As periodontal research advances, a deeper understanding of TLR-mediated immune responses will be crucial in developing targeted therapies that effectively control inflammation while fostering tissue repair and long-term periodontal health. Yet, although this study offers insights into TLR expression in PDLSCs under inflammatory and non-inflammatory microenvironment conditions, several limitations are noteworthy. First, inflammation was modeled using a standardized short-term cytokine exposure, which may not capture the chronic nature of periodontitis. Since periodontitis is a prolonged condition, long-term inflammatory effects on TLR expression and PDLSC function, including potential adaptive responses or cell exhaustion, were not addressed here. Additionally, while in vitro models provide valuable mechanistic insights, the expression of TLRs in cultured PDLSCs may not fully reflect their in vivo behavior. In the periodontal niche, PDLSCs interact dynamically with immune cells, extracellular matrix components, and microbial biofilms, all of which contribute to TLR signaling and modulation . These interactions introduce regulatory mechanisms that are absent in isolated cell cultures, potentially influencing TLR expression in a manner not replicated in vitro. Moreover, external factors such as oxygen tension , mechanical loading , and cytokine gradients play a role in modulating TLR expression and were not accounted for in this study. Another key limitation is the absence of continuous microbial stimulation, a defining feature of the periodontal environment . The oral cavity is constantly exposed to bacterial ligands that shape TLR responses, affecting immune activation and tissue homeostasis . The lack of such microbial interactions in our in vitro model may lead to differences in TLR regulation compared to natural conditions, emphasizing the need for translational models that more closely mimic the in vivo periodontal setting. Despite these limitations, PDLSC cultures remain a powerful tool for dissecting molecular mechanisms underlying TLR regulation. However, to bridge the gap between in vitro observations and clinical relevance, future studies should consider 3D tissue-engineered constructs or co-culture models that integrate microbial and immune system interactions. Such approaches will provide a more comprehensive understanding of TLR-mediated immune responses in periodontitis and enhance the translational potential of PDLSC-based therapies.
This study identifies distinct TLR expression patterns in PDLSCs in basic and inflammatory microenvironments, advocating a key role of TLRs in immune regulation and repair/regeneration within the process of periodontal disease. Future research on specific TLR modulation may advance further understanding of periodontal disease processes with potential therapeutic strategies to enhance periodontal healing and inflammatory response modulation in periodontitis.
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Influence of three different closure techniques on leakage pressures and leakage location following partial cystectomies in normal dogs | 690fe452-497d-4875-ade2-53f2a8325bb6 | 10357280 | Suturing[mh] | INTRODUCTION Neoplastic disease affecting the canine urinary bladder accounts for approximately 2% of all reported neoplasms with transitional cell carcinoma (TCC) identified as the most common form affecting the canine urinary bladder (Knapp et al., ; Mutsaers et al., ). While the trigonal region of the urinary bladder is the most frequent site of TCC reported in dogs, TCC has also been associated with urethral involvement in 56% and the prostate in 29% of clinically affected dogs (Knapp et al., ; Mutsaers et al., ;). The apex of the urinary bladder is also a location affected by TCC in dogs, with this location being amenable to surgical removal via partial cystectomy (Norris et al., ; Stone et al., ). Although curative intent surgery is often not possible, partial cystectomy has been advocated as an important treatment option for use in targeted multimodal therapy to address nontrigonal TCC. Partial cystectomy is performed to alleviate the clinical signs associated with the apical mass lesion such as dysuria, haematuria and pollakuria with the intent of achieving local control of the tumour and delay onset of metastasis if not already present at the time of surgery (Norris et al., ; Stone et al., ). Partial cystectomy for the sole management of canine TCC has been shown to extend median survival time (MST) by approximately 365 days when complete excision of a nonmetastatic lesion is achieved and by approximately 120 days if ≥50% of the lesion is excised (Marvel et al., ; Norris et al., ). Bradbury et al. ( ) found that when partial cystectomy was used adjunctively with concurrent medical management including chemotherapy and or a COX inhibitor, MST was extended to 498 days. Following open partial cystectomy, the urinary bladder heals quickly with full‐thickness defects returning to inherent native tissue strength at approximately 14–21 days (Bellah, ; Daniel & Richard, ). Radasch et al. ( ) demonstrated that use of a single layer appositional pattern during closure established a watertight seal that resisted cystic physiologic pressures and had comparable wound strength to two‐layer closure techniques (Lipscomb, ; Thieman‐Mankin et al., ). Since seeding of neoplastic cells to other intraabdominal tissues can occur following contamination from urinary bladder leakage, it is imperative that bladder wall closure must be able to withstand physiologic intraluminal pressures in awake dogs, especially those encountered during micturition (Marvel et al., ; Norris et al., ). Mean intraluminal bladder pressures in nonanaesthetised dogs ranged from 10.9 to 12.3 mm Hg; however, the pressures can vary dramatically during detrusor muscle contraction (McCafferty et al. ). Surgical stapling devices have been utilised for a wide variety of applications in veterinary surgery involving the pulmonary, gastrointestinal, vascular, and hepatobiliary systems (Bellah, ; Borenstein et al., ; Brissot et al., ; Clark & Pavletic ; Coolman et al., , ; Corti et al., ; Duffy et al., , ; Larue et al., ; Lewis et al., ). Benefits associated with use of stapling devices include but are not limited to decreased intraoperative times, preservation of local vasculature, decreased abdominal contamination, creation of an immediate luminal seal, and increased bursting strength compared to hand‐sewn sutured anastomoses (Ballantyne et al., ; Tobias ; Ullman et al., ; White ). Comparison of closure techniques in an ex vivo canine typhlectomy model showed that stapled closures resulted in leakage pressures ∼2.5× greater than hand‐sewn closures (Duffy et al., ). One recent study evaluating staple line closure following open canine partial gastrectomy demonstrated that stapled closures augmented with suture reinforcement along the stapled line showed similar maximum leakage pressures compared to closures using a double‐layer suture closure technique (Duffy et al., ). This information is of importance to small animal surgeons performing partial cystectomy for apical TCC to allow informed decision making for the use of staple devices and assess their effect on cystic leakage pressures in dogs. Use of a linear stapling device may also have the advantages of en‐bloc resection in an open or laparoscopic setting which may decrease the occurrence of cellular metastasis to the abdominal cavity. To our knowledge, partial canine cystectomy closure using a surgical stapling device has not been described to date. The objective of this study was to compare the initial leakage pressure (ILP), maximum leakage pressure (MLP), and leakage location between three different closure methods for partial cystectomy closure in an ex vivo model. Our null hypothesis was that there would be no difference in ILP, MLP and leakage location regardless of closure techniques for closure of partial cystectomy sites in dogs.
MATERIALS AND METHODS 2.1 Specimens preparation Intact canine lower urinary tracts including the bladder, proximal urethra and distal ureters were harvested from 42 healthy adult dogs weighing between 24–34 kg. Dogs were serially obtained following consented donation from a local animal shelter immediately following IV euthanasia of 1 mL/5 Kg sodium pentobarbital (Euthasol; Virbac AH, Fort Worth, TX) for reasons unrelated to this study. An IACUC protocol was not required by our institution for this study due to secondary use of cadaveric tissues. Dogs were excluded from the study if there was any history of cystic disease (cystic calculi, urinary tract infection, cystic neoplasia, bladder trauma) within 2 months of specimen collection or there was visual evidence of urinary tract pathology. Following bladder collection, all residual urine was evacuated from the lumen, and specimens were wrapped in saline (0.9% NaCl) soaked gauze, and individually stored within a thermostatically controlled environment at 4°C based on the results of a prior study in dogs (Duffy et al., ). Prior to testing, all bladders were allowed to reach room temperature (21°C) and were tested within 24 h following euthanasia. 2.2 Study randomisation A total of 42 ( n = 42) intact urinary bladders were used during the study. Six ( n = 6) intact bladders were assigned to a control group for assessment of procedural methodology and specimen testing. Thirty‐six canine urinary bladders were randomly assigned to 1 of 3 equally sized experimental groups ( n = 12/group) using computer software (Research Randomizer; Lancaster, PA. Available at: randomizer.org. Accessed Aug 6, 2020. 2.3 Surgical procedure After careful dissection and removal of periurethral fat and periureteral dissection, any bladder with visual defects or an insufficient trigonal region were excluded. A connecting tubing adapter (PFLLAL, SurgiVet; Smiths Medical ASD, St Paul, MN) was then inserted into the trigone of the urinary bladders and secured using 2 circumferential sutures of 2‐0 polydioxanone (0 PDS; Ethicon, Somerville, NY). A surgeon's knot was placed using a total of 4 throws to secure the adapter in place and suture cut 0.5 cm from the knot. Both ureters were then ligated 1 cm from their respective insertions into the trigone using the same methodology. For the sutured group, two atraumatic Doyen clamps were placed at the junction of the cranial one‐third and the caudal two‐thirds of the evacuated canine urinary bladder. The urinary bladder was then transected between the adjacent Doyen clamps using straight Metzenbaum scissors. The partial cystectomy site was closed using 3‐0 USP monofilament copolymer of glycolic acid and trimethylene carbonate (Biosyn; Medtronic, Mansfield, MA) on a swaged SH 22 mm ½ circle taper needle in a simple continuous appositional pattern with bites 2–3 mm apart and 2–3 mm from the edge of the incision. Square knots were performed followed by 3 throws at the initiation and termination of the suture line. For the stapled alone group, a 60 mm linear GIA stapling device (DST Series; Medtronic, Mansfield, MA) preloaded with a blue 3.5 mm staple cartridge (Medtronic, Mansfield, MA) was positioned transversely across the junction of the cranial one‐third and the caudal two‐thirds of the undistended bladder. Once the stapling handpiece was fully engaged and the stapler handpiece seated, manual pressure was applied to close and lock the jaws in place for a precompression time of 10 s. The manual firing knob was then pushed cranially which ejected 2 staggered rows of staples that compressed tissues to 1.5 mm. The integrated knife was used to cut between the two separate rows of staples. Following stapled partial cystectomy, the staple line was evaluated for evidence of staple malformation or failure of the partial cystectomy as would be performed in clinical cases. For the stapled plus oversew group, partial cystectomies were performed as described for the staple group alone. Following stapled partial cystectomy closure using the stapling hand piece, the staple line was then oversewn using monofilament 3‐0 Biosyn (Biosyn; Medtronic, Mansfield, MA) on a swaged SH 22 mm ½ circle taper needle placed using a Cushing (inverting) suture pattern placed 2 mm distal to the staple line. All sutures were placed 2–3 mm apart and a square knot followed by 3 throws was used to start and finish the suture line in the oversew. If required during suturing, inversion of the staple line was performed by the use of mosquito haemostats. For control specimens, no partial cystectomy was performed. Control specimens were used to evaluate intraluminal pressures resulting in catastrophic bladder failure for assessment of intraluminal pressure testing methods. A single board‐certified small animal surgeon (D.J.D.) familiar with and trained on the use of stapling devices performed all partial cystectomies and resultant closures regardless of randomised group assignment and was assisted by a trained surgical assistant. Tissues were kept moist during testing with room temperature (21°C) 0.9% NaCl administered from a spray bottle. 2.4 Evaluation of bladder leakage and failure location Partial cystectomy site closures were tested after being connected to a 3‐way stopcock (Disconfix; Braun Medical, Bethlehem, PA) adjoined to a tubing adaptor that had been previously placed in the urethral trigone (Duffy et al., ). The remaining ports were connected to a fluid line (Hospira, Elk Grove Village, IL) that was used to infuse the urinary bladder while the other was connected to a pressure transducer (Deltran II; Utah Medical Products, Midvale, UT) to allow assessment of intraluminal pressures. A 5 L bag of electrolyte solution (Vetivex; Dechra Veterinary Products, Overland Park, KS) to which 10 mL of coloured blue dye (Methylene blue; Kordon LLC, Hayward, CA) had been added was connected to a fluid pump (HESKA VET/IV 2.2; Heska, Loveland, CO). The pressure transducer was serially connected to a Passport 12 pressure monitor (Mindray North America, Mahwah, NJ) and zeroed/calibrated at the same level as the bladder at the start of each test. Fluid was infused at a rate of 999 mL/h based on the methods of prior studies (Chu et al., ; Duffy et al., , ; Hansen & Monnet ; Spiller et al., ). During fluid infusion, the cystectomy site and urinary bladder surface were monitored for leakage by a single study investigator. The ILP and MLP were recorded in mm Hg. ILP was defined as the intraluminal pressure at which the coloured saline solution was first observed to leak extraluminally. MLP was defined as the intraluminal pressure that caused catastrophic failure where there was an acute drop of >30% mm Hg or there was plateau of the intraluminal pressure readings for >8 s in duration. The location of leakage was defined as the location at which dyed fluid was observed to leak extraluminally at the level of the suture holes, staple holes, along the incisional line, or due to rupture of the bladder wall. 2.5 Statistical analysis A pilot study was performed to determine the methods for canine bladder collection, preparation and dissection, partial cystectomy regardless of group, suturing, and determination of ILP, MLP and leakage location which was then refined for use in the current study. A prospective power analysis determined that a sample size of ≥10 specimens per group was required to detect a difference of ≥20 ± 5 mm Hg leakage pressure between groups, using a power of 80%, a confidence interval of 95% and an alpha‐error rate of 5%. Data was assessed for normality using the Shapiro–Wilk test. Comparison of ILP and MLP within groups was performed using Scheffe's adjustment. Specimen weight (g) was compared using analysis of variance. Summary statistics for ILP (mm Hg) and MLP (mm Hg) were reported as median (range). A Fisher's exact test was used to assess differences in leakage location by group, with a p value of ≤0.05 considered statistically significant. Computed analysis was performed using Stata/SE v.15.0 (StataCorp; College Station, TX).
Specimens preparation Intact canine lower urinary tracts including the bladder, proximal urethra and distal ureters were harvested from 42 healthy adult dogs weighing between 24–34 kg. Dogs were serially obtained following consented donation from a local animal shelter immediately following IV euthanasia of 1 mL/5 Kg sodium pentobarbital (Euthasol; Virbac AH, Fort Worth, TX) for reasons unrelated to this study. An IACUC protocol was not required by our institution for this study due to secondary use of cadaveric tissues. Dogs were excluded from the study if there was any history of cystic disease (cystic calculi, urinary tract infection, cystic neoplasia, bladder trauma) within 2 months of specimen collection or there was visual evidence of urinary tract pathology. Following bladder collection, all residual urine was evacuated from the lumen, and specimens were wrapped in saline (0.9% NaCl) soaked gauze, and individually stored within a thermostatically controlled environment at 4°C based on the results of a prior study in dogs (Duffy et al., ). Prior to testing, all bladders were allowed to reach room temperature (21°C) and were tested within 24 h following euthanasia.
Study randomisation A total of 42 ( n = 42) intact urinary bladders were used during the study. Six ( n = 6) intact bladders were assigned to a control group for assessment of procedural methodology and specimen testing. Thirty‐six canine urinary bladders were randomly assigned to 1 of 3 equally sized experimental groups ( n = 12/group) using computer software (Research Randomizer; Lancaster, PA. Available at: randomizer.org. Accessed Aug 6, 2020.
Surgical procedure After careful dissection and removal of periurethral fat and periureteral dissection, any bladder with visual defects or an insufficient trigonal region were excluded. A connecting tubing adapter (PFLLAL, SurgiVet; Smiths Medical ASD, St Paul, MN) was then inserted into the trigone of the urinary bladders and secured using 2 circumferential sutures of 2‐0 polydioxanone (0 PDS; Ethicon, Somerville, NY). A surgeon's knot was placed using a total of 4 throws to secure the adapter in place and suture cut 0.5 cm from the knot. Both ureters were then ligated 1 cm from their respective insertions into the trigone using the same methodology. For the sutured group, two atraumatic Doyen clamps were placed at the junction of the cranial one‐third and the caudal two‐thirds of the evacuated canine urinary bladder. The urinary bladder was then transected between the adjacent Doyen clamps using straight Metzenbaum scissors. The partial cystectomy site was closed using 3‐0 USP monofilament copolymer of glycolic acid and trimethylene carbonate (Biosyn; Medtronic, Mansfield, MA) on a swaged SH 22 mm ½ circle taper needle in a simple continuous appositional pattern with bites 2–3 mm apart and 2–3 mm from the edge of the incision. Square knots were performed followed by 3 throws at the initiation and termination of the suture line. For the stapled alone group, a 60 mm linear GIA stapling device (DST Series; Medtronic, Mansfield, MA) preloaded with a blue 3.5 mm staple cartridge (Medtronic, Mansfield, MA) was positioned transversely across the junction of the cranial one‐third and the caudal two‐thirds of the undistended bladder. Once the stapling handpiece was fully engaged and the stapler handpiece seated, manual pressure was applied to close and lock the jaws in place for a precompression time of 10 s. The manual firing knob was then pushed cranially which ejected 2 staggered rows of staples that compressed tissues to 1.5 mm. The integrated knife was used to cut between the two separate rows of staples. Following stapled partial cystectomy, the staple line was evaluated for evidence of staple malformation or failure of the partial cystectomy as would be performed in clinical cases. For the stapled plus oversew group, partial cystectomies were performed as described for the staple group alone. Following stapled partial cystectomy closure using the stapling hand piece, the staple line was then oversewn using monofilament 3‐0 Biosyn (Biosyn; Medtronic, Mansfield, MA) on a swaged SH 22 mm ½ circle taper needle placed using a Cushing (inverting) suture pattern placed 2 mm distal to the staple line. All sutures were placed 2–3 mm apart and a square knot followed by 3 throws was used to start and finish the suture line in the oversew. If required during suturing, inversion of the staple line was performed by the use of mosquito haemostats. For control specimens, no partial cystectomy was performed. Control specimens were used to evaluate intraluminal pressures resulting in catastrophic bladder failure for assessment of intraluminal pressure testing methods. A single board‐certified small animal surgeon (D.J.D.) familiar with and trained on the use of stapling devices performed all partial cystectomies and resultant closures regardless of randomised group assignment and was assisted by a trained surgical assistant. Tissues were kept moist during testing with room temperature (21°C) 0.9% NaCl administered from a spray bottle.
Evaluation of bladder leakage and failure location Partial cystectomy site closures were tested after being connected to a 3‐way stopcock (Disconfix; Braun Medical, Bethlehem, PA) adjoined to a tubing adaptor that had been previously placed in the urethral trigone (Duffy et al., ). The remaining ports were connected to a fluid line (Hospira, Elk Grove Village, IL) that was used to infuse the urinary bladder while the other was connected to a pressure transducer (Deltran II; Utah Medical Products, Midvale, UT) to allow assessment of intraluminal pressures. A 5 L bag of electrolyte solution (Vetivex; Dechra Veterinary Products, Overland Park, KS) to which 10 mL of coloured blue dye (Methylene blue; Kordon LLC, Hayward, CA) had been added was connected to a fluid pump (HESKA VET/IV 2.2; Heska, Loveland, CO). The pressure transducer was serially connected to a Passport 12 pressure monitor (Mindray North America, Mahwah, NJ) and zeroed/calibrated at the same level as the bladder at the start of each test. Fluid was infused at a rate of 999 mL/h based on the methods of prior studies (Chu et al., ; Duffy et al., , ; Hansen & Monnet ; Spiller et al., ). During fluid infusion, the cystectomy site and urinary bladder surface were monitored for leakage by a single study investigator. The ILP and MLP were recorded in mm Hg. ILP was defined as the intraluminal pressure at which the coloured saline solution was first observed to leak extraluminally. MLP was defined as the intraluminal pressure that caused catastrophic failure where there was an acute drop of >30% mm Hg or there was plateau of the intraluminal pressure readings for >8 s in duration. The location of leakage was defined as the location at which dyed fluid was observed to leak extraluminally at the level of the suture holes, staple holes, along the incisional line, or due to rupture of the bladder wall.
Statistical analysis A pilot study was performed to determine the methods for canine bladder collection, preparation and dissection, partial cystectomy regardless of group, suturing, and determination of ILP, MLP and leakage location which was then refined for use in the current study. A prospective power analysis determined that a sample size of ≥10 specimens per group was required to detect a difference of ≥20 ± 5 mm Hg leakage pressure between groups, using a power of 80%, a confidence interval of 95% and an alpha‐error rate of 5%. Data was assessed for normality using the Shapiro–Wilk test. Comparison of ILP and MLP within groups was performed using Scheffe's adjustment. Specimen weight (g) was compared using analysis of variance. Summary statistics for ILP (mm Hg) and MLP (mm Hg) were reported as median (range). A Fisher's exact test was used to assess differences in leakage location by group, with a p value of ≤0.05 considered statistically significant. Computed analysis was performed using Stata/SE v.15.0 (StataCorp; College Station, TX).
RESULTS All partial cystectomies were successfully performed and leakage pressure testing was accomplished without observed technical error during specimen harvest, partial cystectomy and assigned closure method. No specimens were rejected at the time of collection with all bladders included in the final statistical model. Mean canine bladder weight was 23.88 ± 4.36 g with no difference between groups ( p = 0.819). 3.1 Leakage pressure testing There was a difference in ILP among groups ( p < 0.0001). Stapled partial cystectomy augmented with an inverting Cushing suture pattern leaked at higher ILP when compared to sutured ( p < 0.0001) or stapled closures ( p < 0.0001) alone, respectively (Figure ). ILP was greater for stapled alone compared to sutured partial cystectomy closures ( p < 0.001). The ILP of control specimens were greater compared to all experimental groups ( p < 0.0001). ILP can be seen in Table . MLP differed among experimental groups ( p < 0.0001). Stapled closures augmented with a sutured oversew had significantly greater MLP compared to sutured ( p < 0.0001) or stapled ( p < 0.005) partial cystectomy closure alone, respectively. There was no difference in MLP between sutured versus stapled closures alone ( p = 0.059; Figure ). MLP of control specimens was greater compared to all other groups ( p < 0.0001). MLP can be seen in Table . 3.2 Leakage location Leakage location differed among groups ( p < 0.001) and all leakage locations were recorded at the time that ILP was recorded. Partial cystectomies leaked from the incisional line in 10 of 36 (28%) constructs, from a suture hole in 13 of 36 (36%) constructs and from a staple hole in 12 of 36 (33%) constructs. There was no observed leakage occurring in one (3%) of the experimental constructs with failure seen in this construct due to a full‐thickness bladder wall rupture immediately adjacent to the trigone. Leakage occurred from a suture hole in 12 of 12 (100%) constructs in the sutured closure group and at one or more staple holes in 12 of 12 (100%) constructs in the stapled only group. Leakage occurred from the incisional line in 10 of 12 (83%) and by full‐thickness bladder wall rupture in 1 of 12 (8%) of constructs in the stapled partial cystectomy closure augmented with an inverting Cushing suture. Six of six (100%) specimens in the control group failed by bladder wall rupture.
Leakage pressure testing There was a difference in ILP among groups ( p < 0.0001). Stapled partial cystectomy augmented with an inverting Cushing suture pattern leaked at higher ILP when compared to sutured ( p < 0.0001) or stapled closures ( p < 0.0001) alone, respectively (Figure ). ILP was greater for stapled alone compared to sutured partial cystectomy closures ( p < 0.001). The ILP of control specimens were greater compared to all experimental groups ( p < 0.0001). ILP can be seen in Table . MLP differed among experimental groups ( p < 0.0001). Stapled closures augmented with a sutured oversew had significantly greater MLP compared to sutured ( p < 0.0001) or stapled ( p < 0.005) partial cystectomy closure alone, respectively. There was no difference in MLP between sutured versus stapled closures alone ( p = 0.059; Figure ). MLP of control specimens was greater compared to all other groups ( p < 0.0001). MLP can be seen in Table .
Leakage location Leakage location differed among groups ( p < 0.001) and all leakage locations were recorded at the time that ILP was recorded. Partial cystectomies leaked from the incisional line in 10 of 36 (28%) constructs, from a suture hole in 13 of 36 (36%) constructs and from a staple hole in 12 of 36 (33%) constructs. There was no observed leakage occurring in one (3%) of the experimental constructs with failure seen in this construct due to a full‐thickness bladder wall rupture immediately adjacent to the trigone. Leakage occurred from a suture hole in 12 of 12 (100%) constructs in the sutured closure group and at one or more staple holes in 12 of 12 (100%) constructs in the stapled only group. Leakage occurred from the incisional line in 10 of 12 (83%) and by full‐thickness bladder wall rupture in 1 of 12 (8%) of constructs in the stapled partial cystectomy closure augmented with an inverting Cushing suture. Six of six (100%) specimens in the control group failed by bladder wall rupture.
DISCUSSION In this study, we evaluated the effect of three different closure techniques following partial cystectomy in a canine ex vivo model. We failed to reject our null hypothesis, as there was a significant difference in ILP, MLP and leakage location based upon closure method of experimental partial cystectomy. Stapled closures augmented with a suture oversew in a Cushing pattern had an ILP that were 1.7‐fold and 1.3‐fold greater than sutured or stapled closures alone, respectively. Suture augmented stapled partial cystectomy had MLP that were 1.5‐fold and 1.2‐fold greater than sutured or stapled closures alone, respectively. Leakage location differed between groups with leakage exclusively at the suture holes in the sutured closure group, exclusively at the staple holes in the stapled closure group, and primarily at the incisional line in stapled closures augmented with a suture oversew. A single layer appositional closure of the canine urinary bladder is effective at creating a watertight seal (Brissot et al., ; Lipscomb, ; McCafferty et al., ). Due to the potential for abdominal seeding from free‐floating TCC cells in the urine or tissues, there has been an emphasis on the need for minimal to no leakage at the time of surgery in the peri‐ or postoperative period in dogs (Lipscomb ; Marvel et al., ; Norris et al., ; Radasch et al., ; Thieman‐Mankin et al., ). In our study, there was a 1.3‐fold increase in ILP when a stapling device was used compared to sutured closures alone. Furthermore, stapled closures augmented with a suture oversew using a Cushing pattern had significantly higher ILP when compared to sutured or stapled closure methods alone, with a 1.7‐fold and 1.3‐fold increase, respectively. These findings are in agreement with previous studies evaluating various closure techniques utilising staple line reinforcement in both human and dogs (Duffy et al., , ; Karakoyun et al., ). Postulated reasons for these observed findings may be due to the use of a GIA stapler leading to an inverting closure that is then augmented with an oversew using a Cushing pattern which then further establishes serosal‐to‐serosal contact that further strengthens the watertight seal (Ellison et al., ; Hany & Ibrahim ; Ser et al., ). Stapled closures augmented with a suture oversew using a Cushing pattern had significantly higher MLP when compared to sutured or stapled closures alone with a 1.5‐fold and 1.2‐fold increase in MLP, respectively. In our experiment there was no difference in MLP between sutured or stapled closures alone. Since the urinary bladder is a variable pressure system, with relatively low pressures during the bladder filling and greater pressures encountered during active micturition and detrusor muscle contraction, increases in MLP may further decrease the risk of partial cystectomy site dehiscence and resultant leakage. Although postoperative decompression may include placement of an indwelling urinary catheter to minimise intraluminal pressures during the initial phases of wound healing, dislodgement of the catheter or concern for urothelial irritation at the partial cystectomy site make MLP values of interest clinically. Suture augmentation following stapled partial cystectomy closures should be considered to ensure maximal resistance to leakage of urine and decrease the occurrence of seeding TCC cells to the peritoneal cavity. The effect of laparoscopic partial cystectomy closure using a stapling device on minimising abdominal contamination and its effect on en‐bloc resection in attempts to decrease intraabdominal metastasis remains unknown and is an area for future investigation. Although intraluminal pressure within the normal canine urinary bladder are typically low, ranging from 0 to 12.3 mm Hg, differences among breeds, bladder pathology, rate of luminal filling, hydration status, and renal filtration pressures may contribute to a wide range of intraluminal pressures being encountered during active micturition and urination (Conzemius et al., ; Fetner & Prittie, ; Hill, ; McCafferty et al., ). In order to allow for storage of urine within the intact urinary bladder between micturition events, the urinary epithelium and connective tissues within the bladder wall stretch with smooth muscle restructuring and resultant urine accommodation (Duffy et al., ). These physiologic variables allow for low intraluminal pressures to prevent vesicoureteral backflow of urine during storage (Hill, ). In our study, none of the experimental constructs leaked <14 mm Hg, signifying that all closure methods may be sufficient in resisting physiologic pressures encountered during luminal filling in normal healthy dogs. Stapled closure of partial cystectomy sites may be advantageous in the treatment of dogs with apical bladder TCC because the increase in ILP decreases the risk of urine leakage leading to TCC seeding throughout the abdomen. Use of a GIA stapling device deploys two staggered rows of staples on either side of the partial cystectomy site, which may decrease the risk of urine leakage not only from the remaining urinary bladder but also from the resected tissue edge. Stapling devices have been used with increased frequency in canine intestinal surgery with advantages including but not limited to; shorter surgical times, consistent staple placement, decreased iatrogenic tissue trauma, preservation of local blood supply, and ease and repeatability of use with novice surgeons (Ellison et al., ; Jardel et al., ; Kieves et al., ; Tobias, ; Ullman et al., ). Based on our study, augmentation of the staple line with suture following partial cystectomy may further increase resistance of the urinary bladder closure to extraluminal leakage. Although subjectively assessed, addition of the suture oversew was associated with additional procedural time that would likely be clinically irrelevant in vivo. We recognise that oversewing of the staple line may decrease the functional bladder volume, reservoir capacity of the bladder, and that secondary effects such as pollakiuria, stranguria or haematuria due to internalisation of the partial cystectomy site into the bladder lumen are possible and require further study in dogs. In our study, leakage location differed among partial cystectomy closure techniques. Partial cystectomy sites closed with suture leaked exclusively from suture holes at sites of needle penetration which is in agreement with the results of prior investigators (Duffy et al., , , ; Kieves & Krebs, ; Kieves et al., ; Montel et al., ). The relevance of these findings and resultant leakage location remains unclear in ex vivo models since the effect of an early fibrin seal development and early mucosal regeneration are not able to be assessed. Leakage location in the stapled only group was observed in partial cystectomy closures following deployment of a 3.5 mm stapling cartridge with leakage circumferentially around the staple holes. Our results are similar to those of prior leakage pressure assessments in comparative gastrointestinal studies in dogs and people (Chu et al., ; Duffy et al., , ; Karakoyun et al., ). Closure of canine partial cystectomy sites using a stapling device followed by suture augmentation demonstrated leakage primarily along the length of the incisional line rather than at sites of needle or staple penetration, which mirrors prior studies investigating closure techniques in luminal tissues in dogs (Jardel et al., ; Sumner et al., ). This finding is likely due to the inverting nature of the initial staple line followed by augmentation using suture involuting the cut edge of the partial cystectomy into the bladder lumen. We recognised in vivo that bleeding from the internalised staple line into the bladder lumen may occur but this was unable to be assessed. It should be noted that the GIA DST stapling device deploys staples in an inverting configuration, which further increases serosal‐to‐serosal contact and therefore strengthens the watertight seal (Ellison et al., ). In a setting of apical bladder pathology, it is plausible that mucosal inversion into the bladder lumen may be important since neoplastic cells can be found histologically throughout the entire bladder mucosa. Exposure of neoplastic tissue may predispose to abdominal adhesion formation and to possible spread of TCC cells to abdominal viscera. These speculative hypotheses, however, require further evaluation in vivo. This study is inherently limited in its application to in vivo studies since evaluation of normal physiologic processes such as fibrin seal development and its contribution to initial wound strength, inflammation, coagulation, and stages of wound healing cannot be assessed using cadaveric models. It is important to note that we utilised canine urinary bladders free of gross disease or pathology. Alteration of urinary bladder wall architecture by neoplastic involvement may decrease the inherent strength of cystic tissues at the incisional line leading to leakage at lower pressures compared to those observed in our model. Avoidance of urine leakage into the peritoneum is crucial for decreasing the prevalence of TCC translocation, thus, further studies evaluating leakage pressures in either grossly or microscopically affected tissue and live tissue is required prior to consideration and safe application of these stapling methods in vivo. Unlike sutured partial cystectomy techniques using absorbable suture materials, staples used in this study were nonabsorbable and implanted into the bladder wall. We recognise that use of these devices may serve as a reservoir for bacterial adherence, biofilm development and predisposition to cystic calculi formation or urinary tract infection, potentially contributing to increased morbidity postoperatively in vivo. These implants may also limit the ability to use staging modalities such as computed tomographic evaluation by causing imaging artefacts such as beam hardening and scatter, motion, and edge effects. The rate of luminal filling during leak pressure testing was much faster than that encountered during normal physiologic filling of the urinary bladder in dogs. In the normal canine urinary bladder, the urinary epithelium and connective tissues within the bladder wall stretch and smooth muscle restructures leading to urine accommodation within the bladder lumen, this could not be assessed during our study. An additional limitation in this study is that partial cystectomy closures with suture alone leaked solely at the needle holes which was likely due to the needle penetrating the urinary bladder mucosa during suture placement. The authors recognise that in live patients, care is taken to not penetrate the mucosa during closure to avoid this complication. Although stapled partial cystectomy closures also involved penetrating the urinary bladder mucosa, ILP was shown to be significantly higher in stapled closures versus sutured closures. Further studies are needed to compare partial cystectomy closure with sutures that do not penetrate the urinary bladder mucosa versus stapled closures in order to understand whether the strength of stapled closures might offset the concern that the urinary bladder mucosa is penetrated. In conclusion, the results of this in vitro study evaluating canine partial cystectomy closure using a 3.5 mm GIA DST stapling device augmented within a Cushing suture increased ILP and MLP compared to sutured or stapled closures alone and may represent a possible closure method following partial cystectomy in dogs. A Cushing suture pattern to augment stapled closure improved the ability of partial cystectomies to sustain intravesicular pressures and increased ILP by 1.7‐fold and 1.3‐fold and MLP by 1.5‐fold and 1.3‐fold respectively compared to use of sutured or stapled closure techniques alone. These results provide evidence to support placement of a Cushing suture pattern to augment the staple line following stapled partial cystectomy in dogs. In vivo studies are required to determine the clinical significance of these findings and the role of stapling equipment for laparoscopic partial cystectomy in dogs.
Jason Haas: Visualisation (equal); writing – original draft preparation (lead); writing – review & editing (equal). Daniel Duffy: Conceptualisation (lead); data curation (equal); funding acquisition (lead); investigation (equal); methodology (lead); project administration (lead); resources (lead); supervision (lead); validation (lead); visualisation (equal); writing – original draft preparation (supporting); writing – review & editing (equal). Allison Kendall: Conceptualisation (supporting). Yi‐Jen Chang: Data curation (equal); investigation (equal); methodology (supporting). George Moore: Formal analysis (lead).
The authors declare that there are no financial relationships that may affect the results of this study.
The authors declare that they have no conflicts of interest.
The authors confirm that the ethical policies of the journal, as noted on the journal's author guidelines page, have been adhered to. No ethical approval was required as this study was performed with the secondary use of cadaveric tissues.
The peer review history for this article is available at https://publons.com/publon/10.1002/vms3.1137 .
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Zygoma Bone Shell Technique: A Proof‐of‐Concept Surgical Protocol in Human Cadaver for Bone Reconstruction After Zygomatic Implant Failure | efd27b2e-2377-4e05-8964-5fd0123a4349 | 11910187 | Dentistry[mh] | Introduction Zygomatic implants (ZI), introduced by Prof. P‐I Brånemark in the late 1980s (Brånemark et al. ), represented a paradigm shift in the field of oral and maxillofacial surgery. Initially they were designed to address the intricate challenges posed by severe maxillary bone atrophies and partial or complete maxillectomy defects due to oncologic resection, not suitable for conventional dental implant placement, and providing stable prosthesis retention. The original Brånemark protocol included one implant in each zygoma, traversing the sinus, in combination with two to four anterior conventional implants. In the last two decades, ZI have undergone substantial evolution to accommodate a spectrum of clinical complexities. The quad zygomatic implant concept, where two ZI are inserted on each side, was introduced to provide acceptable antero‐posterior implant positioning for force distribution, in patients without adequate anterior maxillary bone (Lan et al. ). Clinical indications were recently reviewed by the ITI consensus (Al‐Nawas et al. ) reporting that zygomatic implants are an evidence‐based treatment option to support fixed or removable prostheses and restore partially or completely edentulous maxillae, with high survival rates when splinted to other implants. Zygomatic implants are an alternative when the maxillary bone is completely or partially absent, secondary to benign or malignant tumor resection, trauma or congenital defects, or when the maxillary bone is completely or partially absent, secondary to failure of previously placed implants and/or bone grafts (Al‐Nawas et al. ). Nowadays ZI are commonly used to support fixed dental implant prosthesis when traditional dental implants cannot be placed, offering to patients a viable alternative to extensive hard and soft tissue reconstructions (Parel et al. ). However, zygomatic implants require advanced surgical skills due to the proximity of vital anatomical structures, such as the orbit, the infratemporal fossa, the infraorbital nerve and the zygomaticofacial nerve and restorative expertise to address all the potential difficulties. Moreover, the placement of long zygomatic implants with limited view of the surgical field and irregular shape of the zygoma can be challenging (Polido et al. ). Although still considered a complex procedure with significant surgical risk and potential for complications, the use of zygomatic implants has grown exponentially, with documented high survival rates, even comparable to conventional implants when used for reconstruction of the atrophic maxilla, as short implants, tilted implants, and implants placed in grafted sinuses (Aparicio et al. ; Gracher et al. ; Agliardi et al. ; Brennand Roper et al. ; Agliardi et al. ; Del Fabbro et al. ). However, intra‐ and postoperative complications can occur, and they demand meticulous attention (Chrcanovic et al. ; Moraschini et al. ; Vrielinck et al. ). The most reported long‐term biological complication was maxillary sinusitis, that may be successfully treated through antibiotics. In the absence of resolution, refractory maxillary sinus infections may need exploration of the patency of the osteo‐meatal complex and other paranasal sinuses. If these therapies are unsuccessful, the ZI may be lost. Oro‐antral fistula, peri‐implant infection of the soft tissues, peri‐implant mucositis and peri‐implantitis, oral vestibular dehiscence, implant fracture, zygomatic bone and orbit fracture, implant overextension, subperiosteal infections due to debris accumulation during site preparation, or local osteonecrosis determined by inadequate flushing of bone debris or excessive implant torque, highlight the critical nature of precise surgical techniques and adherence to established protocols (Kämmerer et al. ; Bedrossian and Bedrossian ; Tran et al. ; Vrielinck et al. ). Patient education in oral hygiene maintenance is paramount. Replacing a failing zygomatic implant with a new ZI requires a proper clinical examination, a cone‐beam computer tomography (CBCT) with 3D reconstruction of the area, a detailed assessment of the residual bone anatomy and a rendering of the bone shell dimension, positioning and fixation. (Figures , , ) In most of the cases a staged approach is needed because of the presence of bone and soft tissue infection. Indeed, the ZI and even more the quad zygoma failure can result in severe defects extending up to the entire height of the zygomatic bone pyramid which could infringe the immediate or delayed placement of new ZIs, requiring complex surgical procedures to restore the integrity of the zygomatic bone anatomy (Bedrossian and Bedrossian ; Tran et al. ; Vrielinck et al. ; Davó et al. ; Xue et al. ; Chu et al. ; Heredia‐Alcalde et al. ; Modabber et al. ). This article aims to present a proof‐of‐concept surgical technique for the immediate reconstruction of zygomatic bone following ZI failure and complications and illustrate the related clinical steps in a cadaver specimen. The protocol should be considered where the failure of zygomatic implants has resulted in a significant destruction of the supporting bone, making the placement of a new implant particularly challenging.
Methods The zygomatic bone shell technique is a proof‐of‐concept surgical protocol for immediate bone reconstruction after zygomatic implant failure. The “three‐dimensional” reconstruction or shell technique is a specific form of GBR using a thin cortical plate harvested from the external oblique line of the mandible (Khoury and Hanser ). The bone shell surgical technique was introduced to address minor horizontal and vertical bone defects and its favorable application to zygomatic implant is tightly dependent on the extension of the defect. Even though composite bone shells reconstruction with multiple bone laminas may be used in larger defects. After a meticulous mechanical debridement of the zygomatic bone defect resulted from the removal of the ZI, a thin cortical bone block was harvested from the mandibular ramus. The resulting bone defect was filled with autogenous bone chips and the thin bone shell was secured with a bone fixation screw to restore the contours of the zygomatic pyramid ridge. 2.1 Step‐by‐Step Surgical Protocol 2.1.1 Recipient Site Preparation The failed zygomatic implants were removed, and the resulting bone deformities mechanically cleared by any debris and remnants with a surgical curette (Lucas‐Martin Bone Curette, KLS Martin, Germany). The recipient sites were extensively irrigated with saline solution and antibiotic solution (Rifampicin Ready Made Solution 50 mg/mL) (Figures , , ). 2.1.2 Harvesting Procedure The harvesting area was selected after a careful CBCT assessment of the volume of the zygomatic bone and the area of the buccal shell and mandibular ramus. An Artificial Intelligence (AI) driven software (Iconix, Xnav Technologies, USA) for automatic segmentation of CBCT data was used to generate an accurate 3D model (Carosi et al. ) of the preoperative zygomatic implant failure bone loss (Tao et al. ). The 3D rendering was used to simulate bone anatomy deformity residual to the implant removal and, the bone shell shape and dimensions needed to reconstruct the zygomatic anatomy morphology. Software allowed to plan for the bone shell fixation screw placement through the residual zygomatic bone. After the reflection of a mucoperiosteal flap, from the first molar to all extension external oblique line of the mandible, an area of 2 cm in length, 1 cm in height was marked with a sterile pencil. A dedicated piezoelectric insert (Ot12, Mectron, Italy) was used to sculpt the bone shell that was detached from the mandible with a chisel. The block had a thickness of about 5 mm and composed of cortical and trabecular bone (Figures , , , , ). 2.1.3 Grafting The recipient site was prepared to house the bone shell and allow its primary mechanical retention. The zygomatic bone defects were filled by autologous bone particles before securing the shell with a self‐tapping bone fixation screw (creos bone fixation screws, 1.5 × 12 mm, NobelBiocare, Switzerland). The recipient site of the screw was prepared by means of a Rounded Drill Ø 1.8 to create a notch on the shell surface, a Twist Drill with Tip 2 mm × 7–10 mm to countersink and prepare the housing of the screw head, and Guided Twist Drill Ø 1.2 × 20 mm to achieve a bi‐cortical anchorage of the screw. The fixation screw was placed in the center of the graft, to ensure excellent stability in the inter‐defect septum and allow a bi‐cortical contact between the graft and the residual zygomatic bone (Figures , , , , , , ). The zygomatic bone graft was protected by the buccal fat pad. 2.1.4 Suturing The suturing of the donor and recipient sites was achieved with a 3‐0 PTFE suture after detaching the muscular insertion and releasing the tension from the flaps.
Step‐by‐Step Surgical Protocol 2.1.1 Recipient Site Preparation The failed zygomatic implants were removed, and the resulting bone deformities mechanically cleared by any debris and remnants with a surgical curette (Lucas‐Martin Bone Curette, KLS Martin, Germany). The recipient sites were extensively irrigated with saline solution and antibiotic solution (Rifampicin Ready Made Solution 50 mg/mL) (Figures , , ). 2.1.2 Harvesting Procedure The harvesting area was selected after a careful CBCT assessment of the volume of the zygomatic bone and the area of the buccal shell and mandibular ramus. An Artificial Intelligence (AI) driven software (Iconix, Xnav Technologies, USA) for automatic segmentation of CBCT data was used to generate an accurate 3D model (Carosi et al. ) of the preoperative zygomatic implant failure bone loss (Tao et al. ). The 3D rendering was used to simulate bone anatomy deformity residual to the implant removal and, the bone shell shape and dimensions needed to reconstruct the zygomatic anatomy morphology. Software allowed to plan for the bone shell fixation screw placement through the residual zygomatic bone. After the reflection of a mucoperiosteal flap, from the first molar to all extension external oblique line of the mandible, an area of 2 cm in length, 1 cm in height was marked with a sterile pencil. A dedicated piezoelectric insert (Ot12, Mectron, Italy) was used to sculpt the bone shell that was detached from the mandible with a chisel. The block had a thickness of about 5 mm and composed of cortical and trabecular bone (Figures , , , , ). 2.1.3 Grafting The recipient site was prepared to house the bone shell and allow its primary mechanical retention. The zygomatic bone defects were filled by autologous bone particles before securing the shell with a self‐tapping bone fixation screw (creos bone fixation screws, 1.5 × 12 mm, NobelBiocare, Switzerland). The recipient site of the screw was prepared by means of a Rounded Drill Ø 1.8 to create a notch on the shell surface, a Twist Drill with Tip 2 mm × 7–10 mm to countersink and prepare the housing of the screw head, and Guided Twist Drill Ø 1.2 × 20 mm to achieve a bi‐cortical anchorage of the screw. The fixation screw was placed in the center of the graft, to ensure excellent stability in the inter‐defect septum and allow a bi‐cortical contact between the graft and the residual zygomatic bone (Figures , , , , , , ). The zygomatic bone graft was protected by the buccal fat pad. 2.1.4 Suturing The suturing of the donor and recipient sites was achieved with a 3‐0 PTFE suture after detaching the muscular insertion and releasing the tension from the flaps.
Recipient Site Preparation The failed zygomatic implants were removed, and the resulting bone deformities mechanically cleared by any debris and remnants with a surgical curette (Lucas‐Martin Bone Curette, KLS Martin, Germany). The recipient sites were extensively irrigated with saline solution and antibiotic solution (Rifampicin Ready Made Solution 50 mg/mL) (Figures , , ).
Harvesting Procedure The harvesting area was selected after a careful CBCT assessment of the volume of the zygomatic bone and the area of the buccal shell and mandibular ramus. An Artificial Intelligence (AI) driven software (Iconix, Xnav Technologies, USA) for automatic segmentation of CBCT data was used to generate an accurate 3D model (Carosi et al. ) of the preoperative zygomatic implant failure bone loss (Tao et al. ). The 3D rendering was used to simulate bone anatomy deformity residual to the implant removal and, the bone shell shape and dimensions needed to reconstruct the zygomatic anatomy morphology. Software allowed to plan for the bone shell fixation screw placement through the residual zygomatic bone. After the reflection of a mucoperiosteal flap, from the first molar to all extension external oblique line of the mandible, an area of 2 cm in length, 1 cm in height was marked with a sterile pencil. A dedicated piezoelectric insert (Ot12, Mectron, Italy) was used to sculpt the bone shell that was detached from the mandible with a chisel. The block had a thickness of about 5 mm and composed of cortical and trabecular bone (Figures , , , , ).
Grafting The recipient site was prepared to house the bone shell and allow its primary mechanical retention. The zygomatic bone defects were filled by autologous bone particles before securing the shell with a self‐tapping bone fixation screw (creos bone fixation screws, 1.5 × 12 mm, NobelBiocare, Switzerland). The recipient site of the screw was prepared by means of a Rounded Drill Ø 1.8 to create a notch on the shell surface, a Twist Drill with Tip 2 mm × 7–10 mm to countersink and prepare the housing of the screw head, and Guided Twist Drill Ø 1.2 × 20 mm to achieve a bi‐cortical anchorage of the screw. The fixation screw was placed in the center of the graft, to ensure excellent stability in the inter‐defect septum and allow a bi‐cortical contact between the graft and the residual zygomatic bone (Figures , , , , , , ). The zygomatic bone graft was protected by the buccal fat pad.
Suturing The suturing of the donor and recipient sites was achieved with a 3‐0 PTFE suture after detaching the muscular insertion and releasing the tension from the flaps.
Discussion The zygomatic bone, comprising 98% of a cortical component and minimal trabecular tissue, presents a viable therapeutic option for implant‐supported rehabilitations. Unlike the maxillary bone, the zygomatic bone is less susceptible to resorption, making it suitable for implant support (Brånemark et al. ). A failing zygomatic implant and even more a quad zygoma failure can result in a severe bone defect affecting the entire height of the zygomatic bone pyramid. Such bone deformities may infringe the immediate and delayed placement of new ZIs, requiring complex surgical procedures to restore the integrity of the zygomatic bone anatomy. This article aims to present a proof‐of‐concept surgical technique and illustrate its clinical application on a cadaver specimen for the immediate reconstruction of zygomatic bone after ZI failure and the related complications. The three‐dimensional reconstruction of zygomatic bone defect was achieved by a specific form of guided bone regeneration or shell technique, using a thin cortical plate harvested from external oblique line of the mandible. The Zygoma Bone Shell technique should be considered where the failure of zygomatic implants has resulted in a significant destruction of the supporting bone, rendering the placement of a new implant particularly challenging. The bone shell surgical technique was introduced to address minor horizontal and vertical bone defects and its favorable application to zygomatic implant failure is tightly dependent on the extension of the defect. Even though composite bone shells reconstruction with multiple bone laminas may be used in larger defects. Autogenous bone graft is osteoinductive, osteogenic and osteoconductive, with significant regeneration capacity, representing the gold standard in case of large augmentation procedures (Misch , ; Pozzi and Mura ). However, the most serious problems with autogenous full block transplants reported are the resorption rates of 21%‐25%. The shell technique according to Khoury was developed to circumvent this problem (Khoury and Hanser ). The “three‐dimensional” reconstruction of the shell technique determined an accelerated vascularization in the bone box and the greater volume stability of the avascular cortical thin plate reduces bone resorption to under 10% (Khoury and Hanser ). In cases of zygomatic implant failure, various therapeutic alternatives have been proposed. Hirano et al. (Rigolizzo et al. ). demonstrated successful reconstruction using hydroxyapatite, after surgical removal of intraosseous hemangioma in the zygomatic bone. However, this technique may not be applicable in the absence of bone peaks and containing defects resulting from zygomatic implant failure. Xue et al. (Hirano et al. ). utilized 3D printing for orbital‐maxillary‐zygomatic reconstruction, providing precise preoperative planning and accurate postoperative results. While effective, this technique may be more complex than the proposed protocol. Chu et al. (Xue et al. ). evaluated the efficacy of CAD/CAM techniques in reconstructing complex zygomatic defects, achieving consistent results. However, the complexity and applicability of this protocol should be considered, and the need to stage the reconstruction after the implant removal to execute a cone beam computed tomography (CBCT) that allows the ideal 3D visibility of the zygomatic defect. Extra‐oral grafting approaches as single free fibula flap microsurgery (Chu et al. ), and computer‐assisted zygoma reconstruction with vascularized iliac crest bone graft (Heredia‐Alcalde et al. ), should be considered only to address extensive defect interesting also the maxillary bone and the zygomatic arch. Mommaerts et al. (Modabber et al. ). discussed challenges in achieving perfect adaptation of the zygomatic grafts, emphasizing the importance of symmetrical shaping and fixation to prevent complications. Intraoral mandibular harvesting emerged as a preferential surgical option to address complications associated with zygomatic implant failure, bringing forth a range of distinctive advantages. A pivotal consideration is the diminished incidence of postoperative complications associated with intraoral mandibular harvesting (Vandeputte et al. ). Furthermore, the increased convenience for the patient is a noteworthy consideration. The intraoral nature of mandibular harvesting reduces the invasiveness of the procedure, enhancing patient comfort and expediting recovery times. This characteristic could substantially contribute to rendering the overall surgical experience more manageable for individuals undergoing the treatment. Finally, the favorable aspect is the comparable composition between mandibular and zygomatic bone, particularly in the cortical region. This anatomical resemblance facilitates optimal structural compatibility, fostering seamless integration of the bone graft into the zygomatic area (Mommaerts et al. ).
Conclusion Within the limitations of this proof‐of‐concept, the zygoma bone shell technique may offer a viable surgical procedure for immediate bone reconstruction after zygomatic implant failure. Translating the previously reported clinical outcomes of bone shell technique, it may be used same day of failing implant removal to achieve reconstruction of zygomatic anatomy with limited risk of postoperative complications. The achieved three‐dimensional reconstruction of the zygomatic anatomy could offer a precise solution with potential low risk of postoperative complications. Further clinical studies are needed to confirm its predictability, reliability and anticipated patient benefits.
E.L.A and A.P. conceived study aims and design, and developed the surgical technique E.G led the writing.
The authors declare no conflicts of interest.
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Hypertension and DMFT: insights from the PERSIAN Guilan Cohort Study | 65e5a76a-fcca-414a-8f8a-2aa31b5d7aa1 | 11607915 | Dentistry[mh] | Hypertension is known as a significant risk factor for cardiovascular disease (CVD), which can be prevented and is also counted as a major global public health issue . Hypertension is commonly referred to as “the silent killer” since it typically shows no signs or symptoms, causing many individuals to remain unaware of their condition . In 2015, hypertension’s global prevalence was estimated at 1.3 billion cases . By 2025, it is projected that the number of individuals experiencing hypertension will reach 1.56 billion . Hypertension annually leads to a mortality rate of 7 million . The global prevalence of hypertension is increasing due to the ageing population and greater exposure to lifestyle risk factors such as unhealthy diets (such as low potassium and high sodium intake) and insufficient physical activity . The prevalence of hypertension among the adult population in Iran was 26.26% . In the PERSIAN Guilan cohort study, the prevalence of hypertension was found to be 43.2% . While hypertension itself does not have recognized oral manifestations, antihypertensive medications can frequently lead to side effects such as xerostomia, gingival hyperplasia, gingivitis, periodontitis, swelling or pain in the salivary glands, lichenoid drug reactions, erythema multiforme, altered taste sensation, and paresthesia. As a result of taking medications, xerostomia is expected, which leads to extensive caries and oral infections . Oral health is a crucial public health component closely linked to overall well-being. The Decayed, Missing, and Filled Teeth (DMFT) index measures the number of decayed teeth, the number of missing teeth, and the number of teeth filled due to decay . This study evaluates the correlation between hypertension and the DMFT index in the PERSIAN Guilan Cohort Study (PGCS). The study results are expected to provide baseline data on our population, facilitating the improvement of oral health with evidence-based recommendations.
Setting The present study is a cross-sectional study of PGCS (PERSIAN Guilan Cohort Study) performed from October 8, 2014, to January 20, 2017. 10,520 individuals aged 35 to 70 years old were included in the Prospective Epidemiological Research Studies in Iran (PERSIAN) in Guilan Province, Northern Iran. The criteria for exclusion from the study included the inability to attend the clinic for a physical examination, the presence of an intellectual disability, and a lack of willingness to participate in the research . Eligible subjects were reached via phones by trained interviewers proficient in the region’s native language to communicate with participants. After obtaining informed consent, calibrated research colleagues recorded data encompassing clinical, laboratory, and demographic characteristics . 2 midwives performed oral examinations to collect DMFT and oral health data. They were educated and supervised by a dentist. Also, the methodology suggested by WHO (Oral Health Surveys Basic Methods) was followed in all clinical procedures . Variables Blood pressure was measured twice in each arm at 10-minute intervals using Richter auscultatory mercury sphygmomanometers (MTM Munich, Germany). Participants were seated with their backs supported, legs uncrossed, and arms at heart level. Measurements were taken in a quiet room at 10-minute intervals between each, ensuring the cuff size was appropriately adjusted. The mean of the measurements was used for analysis. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, a prior diagnosis of hypertension by a health professional, or being on antihypertensive medication . DMFT, a discrete variable, was used to evaluate oral health conditions. Interviewers obtained the DMFT score by examining individuals. The DMFT score was determined by counting the number of decayed (D), missing (M), and filled (F) teeth. The mean DMFT for all samples is calculated by dividing the total sum of all DMFT scores by the number of participants. Variables, such as sex (male or female), age (35–44, 45–55, or > 55), years of education (illiterate, 1–5 years of schooling, 6–12 years of schooling, or university/college), SES (low, moderate, or high), physical activity (low, moderate, high), Smoking status (smoker, non-smoker), use of drugs, or alcohol (yes/no), BMI (< 18.5, 18.5–24.9, 25–29.9, > 30), use of mouthwash or floss (yes/no), tooth brushing frequency (once daily, twice or more daily, others, Irregular and No brushing), and co-morbid diseases (none, one, two, or more) were analyzed in individuals with or without hypertension to assess which factors were risk indicators . Hookah, also referred to as a water pipe, shisha, or qualyan, is a device utilized for the consumption of tobacco. This device functions by passing the smoke through water before inhalation. It is estimated that approximately 100 million individuals globally engage in the use of hookahs . Participants’ SES was assessed using a developed household wealth measure. Participants were asked about ownership of certain durable assets, such as a PC/laptop, CD/DVD player, cellphone, refrigerator, freezer, dishwasher, 3D TV, automobile, vacuum cleaner, sewing machine, air conditioner, oven, motorcycle, the number of rooms per capita, and the type of home residency. Additionally, they were asked about access to infrastructure services, such as piped drinking water and the Internet. We used principal component analysis (PCA) to construct the wealth index based on this information . Co-morbid diseases were defined as one of the following: ischemic heart disease, diabetes mellitus, history of MI (myocardial infarction), history of stroke, kidney failure, fatty liver, hepatitis B or C, chronic lung diseases, thyroid diseases, kidney stones or gall bladder, rheumatism diseases, chronic headaches, and epilepsy . Statistical analysis The Kolmogorov-Smirnov test evaluated the normality of variables. The ANOVA test was employed to investigate variations in the mean DMFT indices across the three groups. Additionally, the T-test assessed differences in the mean DMFT between the two groups. To compare two quantitative variables, the Pearson correlation coefficient was utilized. Multiple linear regression was utilized to determine risk factors influencing changes in DMFT. All analyses were conducted using IBM SPSS Statistics software, version 27. A significance level of less than 0.05 was used for all tests.
The present study is a cross-sectional study of PGCS (PERSIAN Guilan Cohort Study) performed from October 8, 2014, to January 20, 2017. 10,520 individuals aged 35 to 70 years old were included in the Prospective Epidemiological Research Studies in Iran (PERSIAN) in Guilan Province, Northern Iran. The criteria for exclusion from the study included the inability to attend the clinic for a physical examination, the presence of an intellectual disability, and a lack of willingness to participate in the research . Eligible subjects were reached via phones by trained interviewers proficient in the region’s native language to communicate with participants. After obtaining informed consent, calibrated research colleagues recorded data encompassing clinical, laboratory, and demographic characteristics . 2 midwives performed oral examinations to collect DMFT and oral health data. They were educated and supervised by a dentist. Also, the methodology suggested by WHO (Oral Health Surveys Basic Methods) was followed in all clinical procedures .
Blood pressure was measured twice in each arm at 10-minute intervals using Richter auscultatory mercury sphygmomanometers (MTM Munich, Germany). Participants were seated with their backs supported, legs uncrossed, and arms at heart level. Measurements were taken in a quiet room at 10-minute intervals between each, ensuring the cuff size was appropriately adjusted. The mean of the measurements was used for analysis. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, a prior diagnosis of hypertension by a health professional, or being on antihypertensive medication . DMFT, a discrete variable, was used to evaluate oral health conditions. Interviewers obtained the DMFT score by examining individuals. The DMFT score was determined by counting the number of decayed (D), missing (M), and filled (F) teeth. The mean DMFT for all samples is calculated by dividing the total sum of all DMFT scores by the number of participants. Variables, such as sex (male or female), age (35–44, 45–55, or > 55), years of education (illiterate, 1–5 years of schooling, 6–12 years of schooling, or university/college), SES (low, moderate, or high), physical activity (low, moderate, high), Smoking status (smoker, non-smoker), use of drugs, or alcohol (yes/no), BMI (< 18.5, 18.5–24.9, 25–29.9, > 30), use of mouthwash or floss (yes/no), tooth brushing frequency (once daily, twice or more daily, others, Irregular and No brushing), and co-morbid diseases (none, one, two, or more) were analyzed in individuals with or without hypertension to assess which factors were risk indicators . Hookah, also referred to as a water pipe, shisha, or qualyan, is a device utilized for the consumption of tobacco. This device functions by passing the smoke through water before inhalation. It is estimated that approximately 100 million individuals globally engage in the use of hookahs . Participants’ SES was assessed using a developed household wealth measure. Participants were asked about ownership of certain durable assets, such as a PC/laptop, CD/DVD player, cellphone, refrigerator, freezer, dishwasher, 3D TV, automobile, vacuum cleaner, sewing machine, air conditioner, oven, motorcycle, the number of rooms per capita, and the type of home residency. Additionally, they were asked about access to infrastructure services, such as piped drinking water and the Internet. We used principal component analysis (PCA) to construct the wealth index based on this information . Co-morbid diseases were defined as one of the following: ischemic heart disease, diabetes mellitus, history of MI (myocardial infarction), history of stroke, kidney failure, fatty liver, hepatitis B or C, chronic lung diseases, thyroid diseases, kidney stones or gall bladder, rheumatism diseases, chronic headaches, and epilepsy .
The Kolmogorov-Smirnov test evaluated the normality of variables. The ANOVA test was employed to investigate variations in the mean DMFT indices across the three groups. Additionally, the T-test assessed differences in the mean DMFT between the two groups. To compare two quantitative variables, the Pearson correlation coefficient was utilized. Multiple linear regression was utilized to determine risk factors influencing changes in DMFT. All analyses were conducted using IBM SPSS Statistics software, version 27. A significance level of less than 0.05 was used for all tests.
10,520 individuals aged between 35 and 70 participated in the PERSIAN Guilan cohort study, of which 5 of them did not have a DMFT score. Among the 10,520 subjects who participated in the study, 4,887 (46.5%) were male. The mean age of the study population was 51.51 ± 8.8 years, and 5,907 (56.1%) resided in rural areas. The mean DMFT of all participants and those with and without hypertension is presented in Table . All participants’ mean and standard deviation (SD) DMFT was 14.57 ± 8.78 (See Table ). The T-test analysis results indicated that the differences in mean DMFT, mean M, and mean F between participants with hypertension and those without hypertension were statistically significant ( P -values: <0.001, < 0.001, < 0.001, respectively). Table presents the results of the T-test for age, sex, education level, SES, BMI, and co-morbid diseases in participants with and without hypertension. The results of the T-test analysis of smoking status, using alcohol, hookah and drugs are shown in Table . T-test analysis were conducted for tooth brushing frequency and using floss and mouthwash. The results are displayed in Table . Based on the Pearson correlation, Table revealed the correlation between the glucose, LDL, HDL, and TG levels in blood and DMFT. According to the table, there is a significant decrease in DMFT with increasing blood TG levels in individuals with hypertension. The finding is statistically significant with a p-value of 0.037. The results of multiple linear regression indicated that for participants with hypertension, factors such as older age, lower levels of education, lower BMI, not flossing, smoking, alcohol use, infrequent teeth brushing, and living in the city were associated with an increased DMFT index (See Fig. ). Similarly, for participants without hypertension, factors such as older age, lower levels of education, lower BMI, not flossing, smoking, alcohol use, infrequent teeth brushing, using hookah, not using mouthwash and lower socioeconomic status were associated with an increased DMFT index (See Fig. ).
Our study evaluates the correlation between hypertension and the Decayed, Missing, and Filled Teeth (DMFT) index in the PERSIAN Guilan Cohort Study (PGCS). The results provide baseline data on the population, facilitating the improvement of oral health with evidence-based recommendations. Results indicate a significant difference in mean DMFT scores between participants with and without hypertension. This correlation is consistent with prior studies illustrating the link between cardiovascular conditions and oral health issues. For example, Holmlund et al. observed an inverse relationship between the number of remaining teeth and fatal cardiovascular events, as well as death from coronary heart disease . Age has been identified as a significant factor affecting DMFT scores in both hypertensive and non-hypertensive groups. This observation is consistent with the progressive nature of dental diseases. Kassebaum et al. emphasized the global burden of untreated caries, stressing that dental issues become more prevalent as individuals age . Interestingly, our study revealed a reverse correlation between BMI and DMFT scores. This discovery contradicts findings from some previous studies. Östberg and colleagues reported positive associations between obesity and poor oral health, indicating that higher BMI is linked to an increased risk of dental caries and periodontal disease . Further research is required to clarify this relationship and investigate potential confounding factors. Higher education is associated with lower DMFT scores, indicating a link between education and improved oral health. According to Watt and colleagues educational attainment is a critical factor in promoting oral health . Lifestyle factors such as smoking and alcohol consumption were found to be linked to higher DMFT scores. In a study by Tomar and Asma, it was reported that current smokers were more likely to have poor oral health than non-smokers, with a higher prevalence of periodontal diseases and tooth loss . Similarly, a study by Rooban et al. discovered that alcohol use was associated with a higher prevalence of periodontal diseases, further supporting our findings . On the other hand, positive oral hygiene habits such as regular tooth brushing and flossing were connected to lower DMFT scores, emphasizing the importance of oral health education and promotion. It’s important to note that while hypertension itself may not have recognized oral manifestations, antihypertensive medications can cause side effects such as dry mouth, gingival enlargement, and changes in taste sensation, which can indirectly impact oral health. Torpet et al. reported different oral side effects of antihypertensive medications, including an increased risk of dental caries and periodontal disease due to reduced saliva production . The study also examined the relationship between blood glucose, LDL, HDL, and TG levels and DMFT scores. Notably, there was a significant decrease in DMFT with increasing blood TG levels in individuals with hypertension. This finding suggests a potential protective effect of higher triglyceride levels on dental health, although the underlying mechanisms remain unclear and warrant further investigation. The study’s strengths include a large sample size and a comprehensive assessment of potential confounding factors. However, its cross-sectional nature limits causal inferences. Longitudinal studies are necessary to establish temporal relationships and potential mechanisms linking hypertension and oral health.
This research offers proof of a notable link between hypertension and inadequate oral health in the Iranian population. The results underscore the importance of comprehensive healthcare strategies that consider both overall and oral health. Subsequent research should clarify the biological mechanisms behind this connection and investigate potential interventions that could address cardiovascular and oral health concurrently.
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A documentary analysis of Victorian Government health information assets’ websites to identify availability of documentation for data sharing and reuse in Australia | 901a946a-b0c5-49a9-b371-ac44bd227591 | 11705755 | Psychiatry[mh] | In an infodemic, where very large volumes of both accurate/reliable and inaccurate data and information are circulated, appropriate “infodemic management” is critical to minimise its potential adverse impacts, especially to public health ( ). Misinformation in this context can result in confusion and widespread mistrust of health leaders and scientific data. Despite the voluminous generation of health data arising from digital health and the risks of misinformation, there are driving forces towards enhancing data linkage to facilitate information sharing between, and across, health agencies ( ). “The power of our data to solve key policy challenges grows exponentially as we make it more complete, more joined up and more available” (Australian Government Department of Health and Aged Care, 2022a: 2). The sharing and reuse of data does not occur in isolation. In Australia, health data are collected in specific contexts for explicit purposes by governments, registries and health agencies at local, state and federal levels. Much of the person-level health data that are provided to governments is a by-product of the clinician–patient information exchange. Transformation occurs as these data progress through multiple extraction, clinical coding and reporting processes, until they are finalised as an information asset at the relevant state and territory Department of Health. By this point in the journey, they have already become secondary data, consistent with proposed “law of medical information.” That is, the further data are removed from their original context and the more diverse purposes for which they may be used, the greater the task “to disentangle it from the context of its production” ( : 51). During the early stages of the development of data quality research, : 15) identified the importance of “knowing-why. . . behind routine data production activities” as it empowered data consumers to understand and question data quality issues and provide solutions. Awareness of the need for appropriate infrastructure (i.e. documentation, processes, technology) for sharing and reuse of data became even more apparent during the subsequent decade with the establishment of the Open Data Charter in 2015 ( ). Experts from universities, funding organisations, publishers and data scientists collaborated to develop the infrastructure requirements for effective sharing and reuse of data. This resulted in the development of the FAIR principles (findability, accessibility, interoperability and reusability) to promote good data management and reuse of data ( ). More recently, the extensive and variable resources and requirements needed to transform data to an interoperable and reusable level have been identified ( ; ; ,). concluded that improved data quality and explanatory documentation surrounding datasets led to increased satisfaction in the reuse process for researchers. In their systematic review, identified considerable inconsistency between researchers’ understanding of what makes data ready for research. While not specifically focusing on reuse of data, : 1) identified five characteristics necessary for data to be defined as research-ready: “(a) available, (b) broad, (c) curated, (d) documented and (e) enhanced for research purposes.” These authors found that documentation describing key characteristics of the data focused on the availability and transparenc y of information including context, purpose, creation and processing, coverage, quality and completeness, limitations, user guides, data governance and access, and use in research. Previous studies have identified the difficulties in navigating the minefield of information to understand and access data for reuse purposes. For example, : 623) described the journey as clinician-academics in obtaining access to routine healthcare data as involving: “nine . . .stakeholders from four . . .organisations [who] took almost 3 years, including 15 initial or revised applications, assessments or agreements.” and described the difficulty in undertaking data linkage with multiple datasets, and across jurisdictions, due to inconsistencies in access policies, variable skill levels of both researchers and custodian/data owner staff, resourcing issues concerning time, staff, and money, data limitations, and restrictive and siloed policies and practices. In researching data reuse, : xvi) observed that “researchers lacked knowledge they desired about data [which] . . . frequently had a negative impact on their research.” There is a gap in Australian research on the provision of available and transparent documentation (i.e. trustworthy guidelines) for “research-ready” government health information assets for reuse purposes. Therefore, the aim of this study was to analyse selected government health information asset websites to ascertain the extent of explanatory documentation readily available for researcher access and reuse of these data.
Study design Documentary analysis ( ; ) in the form of an audit of website explanatory content was undertaken in March and April, 2023. This enabled the investigation of the type of documentation about a selected sample of government health information assets that was readily and publicly available to support the appropriate reuse of these datasets by researchers. The terms “information assets” and “datasets” have been used interchangeably in this article. Sample and exclusion criteria identified 28 datasets that were reported in the Victorian Department of Health information asset register in March 2019. These datasets, both administrative and population-health based, included person-level data and were associated with at least one peer-reviewed publication between 2008 and 2020. The websites of these information assets formed the basis of the current study (see ). Any of the within-scope datasets that had subsequently become inactive or had been replaced by a new dataset were excluded. Development of audit tool and data collection An abstraction audit template was created based on recommendations from previous studies ( ; ; ) and the Data Access Policy. Sixteen information-categories recognised by these authors to be important for meaningful reuse of data were selected (see Supplemental Table S1 ). Audit information-categories included information on governance structures, funding source(s), purpose, scope, nature of collection (mandatory or voluntary), quality controls and data quality statements, participant privacy/confidentiality and security of data provision, meta-data, limitations, access process, access fee, review of outputs before release, list of research requests or outputs publicly available, website address and comments. An audit data dictionary was compiled to assist with data collection (see Supplemental Table S2 ). One reviewer completed the abstraction. To validate the data abstraction and completion of the audit tool, a sample of five datasets (20%) was utilised to determine inter-rater agreement between the primary reviewer and a second reviewer. This article focuses on the availability of documentation for 9 of the 16 categories for which data were abstracted; these relate to “research-readiness” (i.e. data custodian, context, data dictionary, quality controls, data quality statement, limitations, access process, privacy/confidentiality and security, and research requests or outputs). Each of the dataset websites was broadly categorised into administrative and population-based, as defined in , for the analyses of information-categories. Datasets were also categorised into two groups based upon their data custodianship (i.e. “government-curated” and “other agency-curated”). Each dataset website was also anonymised and categorised into government, research and other for comparison of the individual information-categories. Analysis Manifest content analysis, as described by , was used to summarise the main findings of the document audit. This approach involved the systematic investigation of large volumes of easily observable textual data, often incorporating “surface-level analysis [which] assumes there is objective truth in the data that can be revealed with very little interpretation” ( : 128). Fisher’s exact test, α = 0.05, was calculated in OpenEpi Version 3.01 ( ), to identify associations for categorical variables where cell numbers were <5. Cohen’s Kappa was calculated to determine inter-rater reliability between the sample extraction for both reviewers ( ). The interpretation of Cohen’s Kappa was used to describe agreement levels: 0–0.2 ( slight agreement ), 0.21–0.40 ( fair agreement ), 0.41–0.60 ( moderate agreement ), 0.61–0.80 ( substantial agreement ) and 0.81–1.0 ( almost perfect to perfect agreement ). Ethics No ethical approval was required for this study as all documents utilised were available in the public domain.
Documentary analysis ( ; ) in the form of an audit of website explanatory content was undertaken in March and April, 2023. This enabled the investigation of the type of documentation about a selected sample of government health information assets that was readily and publicly available to support the appropriate reuse of these datasets by researchers. The terms “information assets” and “datasets” have been used interchangeably in this article.
identified 28 datasets that were reported in the Victorian Department of Health information asset register in March 2019. These datasets, both administrative and population-health based, included person-level data and were associated with at least one peer-reviewed publication between 2008 and 2020. The websites of these information assets formed the basis of the current study (see ). Any of the within-scope datasets that had subsequently become inactive or had been replaced by a new dataset were excluded.
An abstraction audit template was created based on recommendations from previous studies ( ; ; ) and the Data Access Policy. Sixteen information-categories recognised by these authors to be important for meaningful reuse of data were selected (see Supplemental Table S1 ). Audit information-categories included information on governance structures, funding source(s), purpose, scope, nature of collection (mandatory or voluntary), quality controls and data quality statements, participant privacy/confidentiality and security of data provision, meta-data, limitations, access process, access fee, review of outputs before release, list of research requests or outputs publicly available, website address and comments. An audit data dictionary was compiled to assist with data collection (see Supplemental Table S2 ). One reviewer completed the abstraction. To validate the data abstraction and completion of the audit tool, a sample of five datasets (20%) was utilised to determine inter-rater agreement between the primary reviewer and a second reviewer. This article focuses on the availability of documentation for 9 of the 16 categories for which data were abstracted; these relate to “research-readiness” (i.e. data custodian, context, data dictionary, quality controls, data quality statement, limitations, access process, privacy/confidentiality and security, and research requests or outputs). Each of the dataset websites was broadly categorised into administrative and population-based, as defined in , for the analyses of information-categories. Datasets were also categorised into two groups based upon their data custodianship (i.e. “government-curated” and “other agency-curated”). Each dataset website was also anonymised and categorised into government, research and other for comparison of the individual information-categories.
Manifest content analysis, as described by , was used to summarise the main findings of the document audit. This approach involved the systematic investigation of large volumes of easily observable textual data, often incorporating “surface-level analysis [which] assumes there is objective truth in the data that can be revealed with very little interpretation” ( : 128). Fisher’s exact test, α = 0.05, was calculated in OpenEpi Version 3.01 ( ), to identify associations for categorical variables where cell numbers were <5. Cohen’s Kappa was calculated to determine inter-rater reliability between the sample extraction for both reviewers ( ). The interpretation of Cohen’s Kappa was used to describe agreement levels: 0–0.2 ( slight agreement ), 0.21–0.40 ( fair agreement ), 0.41–0.60 ( moderate agreement ), 0.61–0.80 ( substantial agreement ) and 0.81–1.0 ( almost perfect to perfect agreement ).
No ethical approval was required for this study as all documents utilised were available in the public domain.
Of the 28 within-scope information assets, 25 datasets were included in the audit (see ). Criteria for exclusion included datasets that had been replaced with new service providers and/or data collection processes ( n = 2), and one dataset that no longer actively collected data at the time of website extraction. Based on a sample of five datasets, there was fair to perfect agreement between two reviewers, on the availability of each information-category on dataset websites. Of the nine information-categories, six had perfect agreement (data custodian, contextual information, quality controls, limitations, privacy/confidentiality/security, requests/outputs publicly available), two had moderate to substantial agreement (data quality information and data dictionary respectively) and one information-category (access process) had fair agreement ( ). highlights the variability in the number of information-categories available on websites for both the administrative and population-health datasets. Overall, the websites for most datasets included information on the data custodian, context, and privacy/confidentiality and security. Proportionally, more administrative (than population-based) dataset websites contained information on data dictionary and quality controls, while the websites for the population-health datasets contained more information on the access process. Both administrative and population-health based datasets contained limited information on data quality statements (0% and 6% respectively) or dataset limitations (11% and 6% respectively). Compared with administrative datasets, population-health datasets provided significantly more information on research requests or outputs (0% vs 56%, p = 0.024). provides a comparison of selected information-categories available on data custodian websites by government-held status. Based on both data custodianship types, the majority of websites for both government- and other agency-curated datasets provided information on data custodian (93% and 100% respectively) and contextual information (93% and 90% respectively). Compared with government, other agency-curated datasets were more likely to hold publicly available information on research requests or outputs (7% vs 80%; p < 0.001). There was variability in the availability of specific information-categories provided by curating organisation ( ). Only 11 (44%) of the website datasets provided information on six or more of the categories. The highest number of available information-categories (i.e. eight) was provided on websites related to datasets curated by other agencies. No dataset websites included information on all categories. The websites with the lowest number of available information-categories were all government-curated datasets. There was considerable variation in the number of information-categories available for each of the government-curated administrative datasets (Gov1-admin to Gov9-admin). Of these nine datasets, four (44%) included 6/9 of the information-categories (67%) compared to only one (17%) of the government-curated population-health datasets (Gov10-pop to Gov15-pop), which included 6/9 of the information-categories. The information-categories that were well reported (by more than half of the within-scope datasets) included data custodian, contextual information, data dictionary, access process and measures for ensuring privacy/confidentiality and security.
It is well documented that successful reuse of data requires the availability of appropriate infrastructure and documentation to provide data reusers with sufficient knowledge to manage and analyse the data ( ; ). Under the Victorian Protective Data Security Standards V2.0 , government organisations are required to maintain an information asset register ( ), with the aim to ensure “consistent identification . . . for public sector information across its lifecycle” ( : 11). A recommended information asset register template is provided by the , which contains provision for a number of the information-categories that we have identified as essential for appropriate documentation for reuse of government health information assets. Despite the provision of such a template, our findings demonstrated there was considerable inconsistency in the documentation available on government health information asset websites. Purpose of datasets and curating organisations Most of the within-scope datasets were curated by three categories of organisations (specifically, research centres, government, industry associations). Each reflected a different approach to database management dependent upon the organisational curation processes. : 1) identified this lack of cross-organisational conformity as “one of the major challenges facing data curation today.” This was reflected in our audit of information-categories available on dataset websites. The most obvious outcome, the lack of standardisation of the available documentation, supported findings on the inconsistency of information available on specific information assets. Grouping these datasets for analysis and categorising them as either administrative or population-health, or by curator (government or other agency), proved unhelpful. There was only one statistically significant outcome between these groupings (i.e. datasets curated by “other agency” were more likely to provide information on research requests or research outputs). It proved more valuable to analyse the information-categories for each dataset separately. Some dataset websites demonstrated the availability of most of the specified information-categories to assist researcher knowledge in the use of their datasets, whereas others provided very little information. The lack of some information-categories on the websites of administrative datasets is not surprising. Despite governments’ calls for increased open data sharing across services, many administrative datasets are not set up for reuse for research ( ; ). Our analysis of the government administrative datasets identified four that provided six information-categories on their website; these possibly represented administrative datasets that are well utilised. previously identified that only 4 of the 28 Department of Health (DoH) information assets under study were associated with over half of the resultant 756 publications, thereby supporting advice from the DataVic Access Policy Guidelines that “high-value datasets should be prioritised” ( ). Not all government information assets are provided with the same curation resources, highlighting that some datasets will be more “research-ready” than others ( ). Data access, privacy and confidentiality and security The ability to locate and easily access a dataset is a fundamental contributor to a researcher’s decision on whether or not to reuse it ( ). Data access issues have historically been one of the major barriers in the reuse of government data ( ; ). Almost 70% of datasets included in this study provided information on the access process on their websites and almost all contained details of the data custodian. There was one government administrative dataset that contained neither data custodian nor access process. Despite the absence of this information on the specific website of interest, had previously identified that this information asset had been utilised in more than 50 publications between 2008 and 2020, demonstrating that information on websites is not the only avenue through which researchers can access information. In their data discovery research, : 3) identified that “social networks and word of mouth are the most used sources of discovering/collecting data by researchers.” Our audit identified that almost 70% of the datasets provided information about privacy/confidentiality and/or security issues for release of data, regardless of whether the dataset in question was administrative or population-health focused. Most organisations indicated their data were covered under a range of ethical (e.g. National Statement on Ethical Conduct in Human Research) or legal (e.g. Privacy Principles, Health Records Act, Privacy and Data Protection Act) requirements, guidelines and principles. Identification of participants/patients in provision of government health data to researchers is a major concern for governments in their role as data custodian ( ). Many of the information asset websites provided assurance that only aggregated or de-identified data would be released to researchers, unless there were exceptions outlined in Australian Privacy Principle 6, “Use or disclosure of personal information” ( ). Knowledge and use of information asset documentation : 3) identified that researcher data discovery behaviour often involved exploration of data attributes (e.g. “measurement, level of granularity, quantity and coverage. . .. suitability of data formats, and quality of metadata”) prior to accessing data. identified the importance of available and transparent documentation for dataset “research-readiness.” Results reported from our study focused on contextual information, meta-data dictionary, data quality statements (information) and limitations documentation. Contextual information Understanding context is an essential requirement for data reuse as insight into the purpose for which something is collected impacts upon how it is interpreted ( ; ). This understanding is confirmed from our documentation audit where all but one of the datasets provided contextual information on the relevant websites. Meta-data dictionary (meta-data) One of the underlying pillars of the FAIR principles ( ) is the interoperability of data. Effective data reuse necessitates a standardised approach to data structure and definitions ( ); this is the role of meta-data ( ). The document audit identified that almost 60% of datasets included a data dictionary on their website. While this demonstrates a significant proportion of agencies that identify the importance of meta-data in the promotion of data use, there is still some way to go before we reach a higher level of interoperability. Data quality statement or information : 3) concluded that “data quality was the most critical data attribute [identified] by researchers in their data discovery efforts.” Our audit of within-scope information assets identified a large proportion (83%) of datasets that did not provide data quality information. From an analysis of the peer-reviewed publications of 28 government population-health information assets, discovered that 11 had published studies on the data quality of their information. The websites of these datasets were included in this document audit; however, none of these dataset websites referred to these data quality publications or provided links to the studies. Researcher knowledge of information asset data quality would be enhanced by the provision of links on the respective websites to these publications or by the provision of data quality statements/information, as recommended by the Victorian Public Service Information Management Framework ( ). Data limitation documentation Only one dataset provided information on the limitations of its data. The provision of this information is central to understanding how the data can be meaningfully reused for research ( ). Data provided for reuse purposes are significantly different from primary data, which are collected by a researcher for their own use ( ). : 2) posited the “data creators” advantage, specifically that those who create data have “intimate and tacit knowledge” that data reusers do not have. Either the data creator needs to collaborate with the data reuser to provide this knowledge, or appropriate documentation that outlines the strengths and limitations of the dataset needs to be provided so the reuser has an accurate understanding of the research possibilities in reuse of the dataset ( ). Research transparency : 8) identified that “it is . . . important that there is a transparency in how the administrative data has been used in research.” Providing examples on how various datasets have been utilised in research not only provides guidance for researchers seeking to potentially use the data, but it may also prevent duplication and increase efficiency. If information is readily available on outputs that have been obtained from research requests, then, other researchers will not need to address the same issues or may directly connect with those who have already gathered the information. Other agency-curated datasets in our audit were transparent in providing their research outputs. The government-curated datasets need to improve significantly in this area to match the other organisations. Limitations This study was limited to a selected number of information assets in the Australian state of Victoria. Between-state or between-country variations in outcomes may exist. The selection of pre-defined information-categories used to assess the level of detail and availability of information on dataset websites was limited to a subjective sample of topic areas that had been identified from the existing literature ( ; ; ; ). Reviewer bias may exist in the extraction of data for information-categories from dataset websites; however, the kappa statistics demonstrated strong inter-rater agreement on the availability of eight of the nine information-categories. The presence of information-categories on a website does not imply evaluation of the usefulness of its content. This needs to be considered in any further evaluations of documentation provided for data reuse. It is recommended that: Data quality information is made readily available for high-value datasets to aid ease of reuse, including links to any published data quality articles. Government-curated information assets should provide a publicly accessible list of research requests or outputs obtained from reuse of their data; and Regular review of information asset website content be implemented to ensure the availability of up-to-date and meaningful documentation (i.e. trustworthy guidelines) to assist accessing and reusing data.
Most of the within-scope datasets were curated by three categories of organisations (specifically, research centres, government, industry associations). Each reflected a different approach to database management dependent upon the organisational curation processes. : 1) identified this lack of cross-organisational conformity as “one of the major challenges facing data curation today.” This was reflected in our audit of information-categories available on dataset websites. The most obvious outcome, the lack of standardisation of the available documentation, supported findings on the inconsistency of information available on specific information assets. Grouping these datasets for analysis and categorising them as either administrative or population-health, or by curator (government or other agency), proved unhelpful. There was only one statistically significant outcome between these groupings (i.e. datasets curated by “other agency” were more likely to provide information on research requests or research outputs). It proved more valuable to analyse the information-categories for each dataset separately. Some dataset websites demonstrated the availability of most of the specified information-categories to assist researcher knowledge in the use of their datasets, whereas others provided very little information. The lack of some information-categories on the websites of administrative datasets is not surprising. Despite governments’ calls for increased open data sharing across services, many administrative datasets are not set up for reuse for research ( ; ). Our analysis of the government administrative datasets identified four that provided six information-categories on their website; these possibly represented administrative datasets that are well utilised. previously identified that only 4 of the 28 Department of Health (DoH) information assets under study were associated with over half of the resultant 756 publications, thereby supporting advice from the DataVic Access Policy Guidelines that “high-value datasets should be prioritised” ( ). Not all government information assets are provided with the same curation resources, highlighting that some datasets will be more “research-ready” than others ( ).
The ability to locate and easily access a dataset is a fundamental contributor to a researcher’s decision on whether or not to reuse it ( ). Data access issues have historically been one of the major barriers in the reuse of government data ( ; ). Almost 70% of datasets included in this study provided information on the access process on their websites and almost all contained details of the data custodian. There was one government administrative dataset that contained neither data custodian nor access process. Despite the absence of this information on the specific website of interest, had previously identified that this information asset had been utilised in more than 50 publications between 2008 and 2020, demonstrating that information on websites is not the only avenue through which researchers can access information. In their data discovery research, : 3) identified that “social networks and word of mouth are the most used sources of discovering/collecting data by researchers.” Our audit identified that almost 70% of the datasets provided information about privacy/confidentiality and/or security issues for release of data, regardless of whether the dataset in question was administrative or population-health focused. Most organisations indicated their data were covered under a range of ethical (e.g. National Statement on Ethical Conduct in Human Research) or legal (e.g. Privacy Principles, Health Records Act, Privacy and Data Protection Act) requirements, guidelines and principles. Identification of participants/patients in provision of government health data to researchers is a major concern for governments in their role as data custodian ( ). Many of the information asset websites provided assurance that only aggregated or de-identified data would be released to researchers, unless there were exceptions outlined in Australian Privacy Principle 6, “Use or disclosure of personal information” ( ).
: 3) identified that researcher data discovery behaviour often involved exploration of data attributes (e.g. “measurement, level of granularity, quantity and coverage. . .. suitability of data formats, and quality of metadata”) prior to accessing data. identified the importance of available and transparent documentation for dataset “research-readiness.” Results reported from our study focused on contextual information, meta-data dictionary, data quality statements (information) and limitations documentation. Contextual information Understanding context is an essential requirement for data reuse as insight into the purpose for which something is collected impacts upon how it is interpreted ( ; ). This understanding is confirmed from our documentation audit where all but one of the datasets provided contextual information on the relevant websites. Meta-data dictionary (meta-data) One of the underlying pillars of the FAIR principles ( ) is the interoperability of data. Effective data reuse necessitates a standardised approach to data structure and definitions ( ); this is the role of meta-data ( ). The document audit identified that almost 60% of datasets included a data dictionary on their website. While this demonstrates a significant proportion of agencies that identify the importance of meta-data in the promotion of data use, there is still some way to go before we reach a higher level of interoperability. Data quality statement or information : 3) concluded that “data quality was the most critical data attribute [identified] by researchers in their data discovery efforts.” Our audit of within-scope information assets identified a large proportion (83%) of datasets that did not provide data quality information. From an analysis of the peer-reviewed publications of 28 government population-health information assets, discovered that 11 had published studies on the data quality of their information. The websites of these datasets were included in this document audit; however, none of these dataset websites referred to these data quality publications or provided links to the studies. Researcher knowledge of information asset data quality would be enhanced by the provision of links on the respective websites to these publications or by the provision of data quality statements/information, as recommended by the Victorian Public Service Information Management Framework ( ). Data limitation documentation Only one dataset provided information on the limitations of its data. The provision of this information is central to understanding how the data can be meaningfully reused for research ( ). Data provided for reuse purposes are significantly different from primary data, which are collected by a researcher for their own use ( ). : 2) posited the “data creators” advantage, specifically that those who create data have “intimate and tacit knowledge” that data reusers do not have. Either the data creator needs to collaborate with the data reuser to provide this knowledge, or appropriate documentation that outlines the strengths and limitations of the dataset needs to be provided so the reuser has an accurate understanding of the research possibilities in reuse of the dataset ( ).
Understanding context is an essential requirement for data reuse as insight into the purpose for which something is collected impacts upon how it is interpreted ( ; ). This understanding is confirmed from our documentation audit where all but one of the datasets provided contextual information on the relevant websites.
One of the underlying pillars of the FAIR principles ( ) is the interoperability of data. Effective data reuse necessitates a standardised approach to data structure and definitions ( ); this is the role of meta-data ( ). The document audit identified that almost 60% of datasets included a data dictionary on their website. While this demonstrates a significant proportion of agencies that identify the importance of meta-data in the promotion of data use, there is still some way to go before we reach a higher level of interoperability.
: 3) concluded that “data quality was the most critical data attribute [identified] by researchers in their data discovery efforts.” Our audit of within-scope information assets identified a large proportion (83%) of datasets that did not provide data quality information. From an analysis of the peer-reviewed publications of 28 government population-health information assets, discovered that 11 had published studies on the data quality of their information. The websites of these datasets were included in this document audit; however, none of these dataset websites referred to these data quality publications or provided links to the studies. Researcher knowledge of information asset data quality would be enhanced by the provision of links on the respective websites to these publications or by the provision of data quality statements/information, as recommended by the Victorian Public Service Information Management Framework ( ).
Only one dataset provided information on the limitations of its data. The provision of this information is central to understanding how the data can be meaningfully reused for research ( ). Data provided for reuse purposes are significantly different from primary data, which are collected by a researcher for their own use ( ). : 2) posited the “data creators” advantage, specifically that those who create data have “intimate and tacit knowledge” that data reusers do not have. Either the data creator needs to collaborate with the data reuser to provide this knowledge, or appropriate documentation that outlines the strengths and limitations of the dataset needs to be provided so the reuser has an accurate understanding of the research possibilities in reuse of the dataset ( ).
: 8) identified that “it is . . . important that there is a transparency in how the administrative data has been used in research.” Providing examples on how various datasets have been utilised in research not only provides guidance for researchers seeking to potentially use the data, but it may also prevent duplication and increase efficiency. If information is readily available on outputs that have been obtained from research requests, then, other researchers will not need to address the same issues or may directly connect with those who have already gathered the information. Other agency-curated datasets in our audit were transparent in providing their research outputs. The government-curated datasets need to improve significantly in this area to match the other organisations.
This study was limited to a selected number of information assets in the Australian state of Victoria. Between-state or between-country variations in outcomes may exist. The selection of pre-defined information-categories used to assess the level of detail and availability of information on dataset websites was limited to a subjective sample of topic areas that had been identified from the existing literature ( ; ; ; ). Reviewer bias may exist in the extraction of data for information-categories from dataset websites; however, the kappa statistics demonstrated strong inter-rater agreement on the availability of eight of the nine information-categories. The presence of information-categories on a website does not imply evaluation of the usefulness of its content. This needs to be considered in any further evaluations of documentation provided for data reuse. It is recommended that: Data quality information is made readily available for high-value datasets to aid ease of reuse, including links to any published data quality articles. Government-curated information assets should provide a publicly accessible list of research requests or outputs obtained from reuse of their data; and Regular review of information asset website content be implemented to ensure the availability of up-to-date and meaningful documentation (i.e. trustworthy guidelines) to assist accessing and reusing data.
This study adopted an evidence-based approach to determine the extent of documentation (i.e. trustworthy guidelines) available on selected DoH information asset websites to support reuse of these data for research purposes. The findings have demonstrated inconsistency in the available website information, despite the provision of a recomm-ended OVIC information asset register template. While contextual information, data custodian, access process, and privacy/confidentiality and security measures were found to be well to reasonably well reported, there was an overwhelming lack of information provided on the data quality or the limitations of the datasets for most websites and a lack of information on research requests or outputs for government-curated websites. Given that the DataVic Access Policy Guidelines recommend the use of a data quality statement ( ), and have provided a data quality statement template, the lack of this information points to widespread omissions in appropriate data quality documentation provided for dataset reuse. There was also a lack of readily available information on the limitations of information assets to assist researchers in making correctly informed analyses of the data they use.
sj-docx-1-him-10.1177_18333583231197756 – Supplemental material for A documentary analysis of Victorian Government health information assets’ websites to identify availability of documentation for data sharing and reuse in Australia Supplemental material, sj-docx-1-him-10.1177_18333583231197756 for A documentary analysis of Victorian Government health information assets’ websites to identify availability of documentation for data sharing and reuse in Australia by Merilyn F. Riley, Kerin Robinson, Monique F Kilkenny and Sandy G. Leggat in Health Information Management Journal
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Survey of Obstetrician-Gynecologists about Giardiasis | abea894f-a934-4d81-bb9f-96f066dae4bc | 1939915 | Gynaecology[mh] | Giardiasis is a parasitic disease caused by the protozoan parasite Giardia intestinalis (Giardia lamblia) . Giardia is the most frequently reported enteric parasite in the United States and is responsible for numerous food-associated outbreaks and illnesses [ – ] as well as for waterborne disease [ – ]. Through stool examination, the prevalence of the parasite ranges from 2% to 5% in industrialized countries up to 20% to 30% in developing countries largely due to a lack of adequate sanitation and hygiene . In the United States, giardiasis is responsible for the hospitalization of nearly 5000 people annually , and between 1992 and 1997 the Centers for Disease Control and Prevention (CDC) estimated that more than 2.5 million cases of giardiasis occurred annually . In 2005, over 15 400 cases were reported in the United States making it the most frequently reported enteric parasitic disease . The reason for the discrepancy between estimated cases and reported cases is that many persons with milder illness do not seek medical care or are not tested for Giardia . Giardia can be carried by a wide variety
of hosts and can be found in many
different environments including water, soil, food, and surfaces that have been
contaminated with feces from an infected human or animal . The main route of exposure is fecal-oral,
examples include consuming water contaminated with Giardia , oral contact with an item contaminated with the parasite,
eating undercooked contaminated food
[ , , ], and in some cases oral-anal
contact
[ , , ].
Giardiasis has long been associated with
drinking contaminated water or with children and workers
in daycare centers . The Environmental Protection Agency found Giardia intestinalis cysts in
approximately 81% of the raw water samples collected from streams, lakes, and
ponds, and in 17% of filtered water samples . Fortunately most Americans do not
consume raw water and are recipients of water from treatment systems that
greatly decrease the chance of exposure to cysts. However, it is possible to find cysts in
treated water that is inadequately filtered because of a relative resistance to
chlorine . The prevalence of Giardia is as high as 35% in children
attending daycare centers . A previous study of children attending
daycare centers in Denver, Colorado, suggests that attending a daycare center
alone is a risk factor for contracting giardiasis . Giardiasis can be
difficult to diagnose. The illness has
symptoms that are associated with a variety of parasitic, bacterial, and viral
diseases; however, giardiasis should be considered when gastrointestinal
symptoms last beyond several days . Symptoms can include diarrhea, malaise,
flatulence, greasy stools, stomach cramps, and nausea; diarrhea and
malabsorption may lead to dehydration and weight loss
[ , , , ]. Another characteristic of giardiasis that can
make the disease hard to identify is that cysts and trophozoites are shed on a
periodic basis and stool examination may not always be performed during the
time period the organism is being shed . However, tests using ELISA or direct
fluorescent antibody to detect antigen in the stool are more sensitive than
microscopy and are now commonly available and used in the United States. In 2005, a survey
was conducted by The American College of Obstetricians and Gynecologists (ACOG)
in collaboration with CDC on knowledge about common parasitic diseases
. The survey showed that many practitioners
were not certain how to correctly prescribe medication for many of these
diseases, especially which medications are safe for pregnant women . The current study takes the previous survey a
step further to determine knowledge about how to diagnose and treat cases of
giardiasis. Malabsorption and diarrhea
in pregnant women caused by giardiasis may be harmful to the fetus . Along with correct diagnosis, correct
treatment helps to ensure the safety of the fetus. In addition, some medications used for
giardiasis may have side effects that could affect fetal development
.
A questionnaire about two common parasitic diseases (giardiasis and
toxoplasmosis) and their diagnosis and treatment by obstetrician-gynecologists
was developed by ACOG and CDC and was distributed nationally by ACOG. For the purpose of this paper, we will focus
on the giardiasis portion of the survey.
The survey was pilot-tested by obstetrician-gynecologists in the Washington, DC,
area in December 2005. ACOG mailed the survey to a random sample of 1200 out of 33 354
fellows in February 2006. To ensure the
highest response rate possible, four mailing cycles were completed ending in
June 2006. Data from returned surveys
were assembled at the ACOG facility in Washington,
DC, using SPSS
. Data analysis was performed at the CDC using
SAS 9.1 . Frequencies with confidence intervals using
binomial proportions were used to convey the percentages for the survey's
multiple-choice answers. The mean ages
of the total population and survey sample were compared with the Z test;
other demographic variable proportions were compared with the chi-square. The survey was reviewed and exempted by human
subjects staff at ACOG and CDC.
Of the 1200 ACOG fellows who were mailed the survey, 502 responded for a response
rate of 42%. displays the
demographics for the participants including gender, location, and type of
practice, as well as statistical differences between the survey population and
the ACOG member population. The survey
population had a slightly lower mean age than the ACOG member population (46
years versus 47 years, resp., P = .001). Generally, the participants answered the survey questions correctly, although for a few questions
there was a lot of uncertainty. Medication used for the treatment of giardiasis was one area where fewer
of the participants indicated the most correct answer. Approximately half (49.6%) of the
participants chose metronidazole, which is used for treatment of giardiasis;
however many participants did not recognize that mebendazole is not a primary
treatment of giardiasis, and that tinidazole and nitazoxanide can also be used
for treatment. The participants also did
not usually select the safest medication to use for pregnant women in the first
trimester. The majority (75.8%) believed
metronidazole to be the safest, while in actuality paromomycin is the safest
treatment in the first trimester (although less effective). The practitioners (66.8%) also believed that
the treatment of asymptomatic carriers is recommended, however it is not the recommended practice in most cases. shows the distributions for each
survey question.
The objective of this study was to create a concise survey that would cover the
basics in knowledge about giardiasis.
Through this survey, we found that the majority of
obstetrician-gynecologists provided correct information regarding giardiasis; however,
the survey also showed areas where further education is needed. Most physicians correctly answered questions
about how the disease is transmitted, prevention methods, and outcomes of the
disease. However, one of the most
important issues concerning the disease is treatment and many of the
participants might benefit from further education in this area ( ).
Gardner and Hill provide a thorough review of drugs for treatment of giardiasis including medications for the use in pregnant women. The largest class of agents to treat Giardia is the nitroimidazoles, which includes metronidazole and tinidazole. Metronidazole is the most common drug used to treat giardiasis worldwide
. It has been found to have an efficacy of 85%–90% in adult and pediatric patients
. Tinidazole is one of the drugs with potential for the greatest compliance since it has a longer half-life and can be taken in one dose [ , , ]. In 2004, tinidazole was approved for use in the United States . Studies have shown the drug to have a median efficacy of 92%, and up to 100% for a one-dose regimen . Nitazoxanide was approved for treatment of Giardia in the US in 2003 . A study in Mexico found nitazoxanide to have an efficacy rate of 56%–74%, while other studies have found efficacy rates as high as 80% . An in vitro study showed that nitazoxanide is
more potent than albendazole and metronidazole, 2.5 and 50 times, respectively
. Clinical trials with mebendazole have given varying results, and thus other therapies are preferentially recommended
[ , – ]. Trials comparing mebendazole to metronidazole showed that mebendazole was less effective against giardial infections
[ – ]. In the survey, the best answer was to recognize that mebendazole is not the preferred method of treatment (in “all except mebendazole” was chosen by 45.7%). However, many participants (49.6%) chose metronidazole as the medication to use for treatment, which is correct, as well as tinidazole (chosen by 0.2%). Therefore, 95.6% of participants indicated at least one of the correct medications for treatment of giardiasis.
Metronidazole has been found to be carcinogenic in rats and mice but has not been proven so in
humans . Metronidazole rapidly enters the fetal
circulation after absorption by the mother, which raises concerns about the use
during pregnancy
. Some studies have shown no harmful effects to
the fetus
, and the drug falls in FDA
pregnancy category B for teratogenic effects
. Many studies have found metronidazole to be
safe for treatment during the second and third trimesters
[ , , ]. Over 75%
of the participants believed metronidazole to be the safest medication
for use in the first trimester. Since
tinidazole is in the same family as metronidazole, it displays similar side
effects
. A case-control study of oral tinidazole
treatment has shown placental transfer;
it is not generally recommended for use in the first trimester of pregnancy
much like its relative, metronidazole
. Of the respondents in our survey 6.7%
considered tinidazole to be the safest treatment in the first trimester. Albendazole is in the same family as mebendazole and has also shown inconsistencies in its
effectiveness when used alone . Albendazole has been found to be teratogenic in mice and rats and is not generally recommended for use in pregnant women,
especially during the first trimester . In the current survey, 1.3% of the participants considered albendazole to
be the safest medication for treatment in pregnant women. Paromomycin is considered the safest to use
for treatment in the first trimester because it is poorly absorbed from the intestine
and nearly 100% is excreted unchanged;
therefore, little if any of the drug reaches the fetus
. In addition, no teratogenicity has been found
with this treatment
. Paromomycin has been found to have an
efficacy of 55%–90%
. Approximately 16% of respondents indicated
that paramomycin was the safest medication to use in the first trimester of
pregnancy. Although paromomycin is
theoretically the safest treatment in the first trimester, it is not necessarily
the least expensive or most available.
Screening and treatment of asymptomatic carriers is not generally recommended but depends on the specific situation in which the patient resides. It is often not desirable to treat asymptomatic persons because people often become recolonized
, and even with intensive
investigation and treatment in daycare centers outbreaks can recur
. However, it may be necessary to treat if the disease contributes to underdevelopment in children. In the United States, most children have good
nutritional status and in turn may not have any adverse health effects from
colonization; however, treatment should be considered if spread of the disease
is likely, for example, in a household when it has spread from person to person
. Resistance is another consideration for not
treating asymptomatic carriers. The
overuse of a drug may cause resistance
which could affect treatment
courses in the future.
One limitation of the survey results is the low response rate (42%). Respondents who are more knowledgeable about giardiasis may have been more likely to complete the questionnaire, leading to
an overestimate of knowledge. Nevertheless, the study population was similar to the overall ACOG
membership and we were able to identify subject areas where continuing
education would be beneficial. Another
limitation is the lack of a fixed denominator.
For some questionnaires, not all participants completed all the
questions. This could also affect the
estimate of the knowledge of the physicians.
Through the survey, we found that over 41% of obstetrician-gynecologists use journals as
their main source of new information. Approximately, half of the participants also expressed interest in featured articles by ACOG as a way to impart educational material. Results from our survey will be used to inform ACOG fellows through reports such as this one.
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Characterizing the effect of impeller design in plant cell fermentations using CFD modeling | 9b50dad4-dc5f-4b73-98c8-c4efcf591be1 | 11920266 | Cytology[mh] | Plant cell cultures have been established to be a potential source for consistent and continuous production of diverse high value low volume phytochemicals for a wide variety of industrial applications , . However, mass cultivation of plant cell cultures in bioreactors for maximum biomass productivity is still considered challenging. The relatively large size of plant cells, and its ability to form aggregates results in wall adhesion, insufficient mixing and cell settling in the bioreactors. High-density plant cell cultivations may exhibit non-Newtonian rheology which could warrant higher agitation rates which is limited by plant cell shear sensitivity . With the aim to maximize plant cell biomass productivity, initially shake flask cultivation is generally done for cell line development where the suitable media and environmental parameters such as initial pH and temperature are optimized. The cultivation is then translated to the bioreactor for optimizing the reactor operating parameters for maximizing biomass productivity overcoming nutrient limitations. But unlike in microbial fermentations, in plant cell cultivations it is observed that the biomass productivities generally reduces when we translate from shake flask to conventional reactor systems – . In order to overcome growth limitations and obtain at least comparable biomass productivities in the bioreactor to that of shake flask, hit and trial methods are employed. It includes the use of modified impellers in stirred bioreactors – or the use of modified reactor geometrical configurations such as orbitally shaken bioreactors and wave bioreactors . With the numerous impeller designs and reactor configurations to choose from, and the relatively slow growing nature of plant cell cultures, with a doubling time of approximately 2 to 3 days and a batch time ranging from 3 to 4 weeks, any hit and trial method for a given plant species can be highly time consuming, laborious, incurring huge costs. Therefore, there is a need for a systematic and predictive approach for choosing suitable reactor design and operating conditions in silico. This can be achieved using computational fluid dynamics (CFD) which is an excellent tool where the governing equations of fluid flow are solved to provide quantitative and qualitative insights into mixing, mass transfer and the prevailing shear environment in bioreactors . This can facilitate in silico design of bioreactors suitable for plant cell cultivation that can offer good mixing and mass transfer at low shear . In spite of the development of few novel plant cell bioreactor designs, and use of pneumatically driven airlift and bubble column bioreactors for plant cell cultivation, stirred tank bioreactors often are the preferred choice as they have well-established scale up principles and facilitate excellent mixing and overcoming mass transfer limitations during scale up of high-density viscous plant cell suspension cultures . Previously, the well-known commonly used Rushton impeller that exhibits radial flow has been used for successful lab scale cultivation of Sphaeralcea angustifolia and Helianthus annuus . However, Treat et al. observed that during cultivation of soybean and slash pine using stirred bioreactor with Rushton impeller, though biomass productivity was as expected, the cell viability was reduced by 85%. Further, Panax ginseng was successfully grown in 50 L bioreactor with marine impeller at an agitation rate of 420 rpm . A specially designed setric impeller has been adopted to successfully cultivate Podophyllum hexandrum , Azadirachta indica and Linum album in lab scale bioreactors. With impeller choice being species specific, dependent on cell morphology, cell density and shear sensitivity, it can be beneficial to identify a suitable impeller by characterizing the hydrodynamic environment associated with it in terms of mixing, mass transfer and shear during plant cell cultivation. Hence, this study aims to characterize and quantify these key parameters in the three impellers (Rushton, marine and setric impeller) using CFD modeling for rationally choosing a suitable impeller for plant cell cultivation. Previously, Liu et al. had addressed the effect of shear on plant cells using CFD and assumed that the bubble induced shear forces on plant cell is negligible due to its large size, justifying their use of a single-phase simulation. This study aims to evaluate effect of impellers in stirred bioreactors in terms of hydrodynamics and oxygen mass transfer. Consequently, the system was modeled comprising of two phases: air and the plant cell suspension which accounts for the non-Newtonian nature of plant cells. Further, the developed model was applied onto a lab scale bioreactor as the computational domain and cultivation of Viola odorata plant cell suspension cultures was considered as a model system for the said CFD analysis. This is the first study characterizing hydrodynamics in bioreactors using CFD for a plant cell suspension with non-Newtonian characteristics to the best of the knowledge of the authors.
Development of the CFD model for stirred tank bioreactor The section first presents the governing equations that were employed to obtain the fluid flow in a stirred bioreactor for plant cell cultures. Further, the description of the computational domain and boundary conditions applied are discussed. The discretization schemes and the numerical methods used for solving the governing equations are also presented. Modeling governing equations for the two-phase fluid flow The fluid properties of the plant cell suspension were determined experimentally as described in section “Experimental determination of viscosity and average aggregate size of V. odorata cell suspension”. It was defined as the primary phase, while the sparged air was defined as the dispersed secondary phase with properties defined at temperature 26.6 ℃ as this temperature was previously established to be the optimum temperature for maximum biomass productivity in V. odorata cell cultures . The two phases were assumed to be incompressible and considered as independently interacting fluid continuum and modeled using the two-phase Eulerian model. The average size of the air bubbles was determined by the Sauter mean diameter correlation ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{d}_{b}$$\end{document} ) modeled by Kazakis et al. for a porous sparger as given by: 1 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{{d}_{b}}{{d}_{s}}=7.35\:{\left[{We}^{-1.7}{Re}^{0.1}{Fr}^{1.8}{\frac{{d}_{p}}{{d}_{s}}}^{1.7}\right]}^{0.2}$$\end{document} where We , Re and Fr corresponds to the Weber, Reynolds and Froude numbers respectively, \documentclass[12pt]{minimal}
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\begin{document}$$\:{d}_{p}$$\end{document} correspond to diameter and pore size of the sparger, respectively. The volume \documentclass[12pt]{minimal}
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\begin{document}$$\:{(V}_{q})\:$$\end{document} occupied by phase q, in the system is given by Eq. ( ), as follows: 2 \documentclass[12pt]{minimal}
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\begin{document}$$\:{V}_{q}={\int\:}_{V}^{\:}{\alpha\:}_{q}dV\:$$\end{document} such that \documentclass[12pt]{minimal}
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\begin{document}$$\:{\alpha\:}_{q}$$\end{document} , the volume fraction of phase q in a single computational element is a continuous function in space and time. Hence the sum of volume fractions of air and the plant cell suspension phases in a single computational cell is equal to 1 as defined by phasic volume fraction given by Eq. ( ), as follows: 3 \documentclass[12pt]{minimal}
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\begin{document}$$\:\sum\:_{q=1}^{2}{\alpha\:}_{q}=1$$\end{document} The effective density of phase q in every computational cell is defined as \documentclass[12pt]{minimal}
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\begin{document}$$\:\widehat{{\rho\:}_{q}}=\:{\alpha\:}_{q}{\rho\:}_{q}$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:{\rho\:}_{q}$$\end{document} is the physical density of phase q. The impeller Reynolds number ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re})\:$$\end{document} of the overall system was calculated to be 3000 as per following equation: 4 \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re}=\:\left(\frac{{\rho\:}_{w}N{{d}_{I}}^{2}}{{\mu\:}_{w}}\right)$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:{\mu\:}_{w}$$\end{document} refers to the dynamic viscosity of water. It is generally considered that for a system to be turbulent if the \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re}\:$$\end{document} for a bioreactor is greater than 10000, while laminar if the \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re}$$\end{document} is less than 4 . Though flow in this system may fall under transitional regime, modeling the flow as fully turbulent resulted in closer alignment with the experimental data. Hence, the Reynolds-averaged Navier-Stokes (RANS) equations were solved for the two-phase system in this study. A similar approach has also been adopted by Sarkar et al. where they defined the critical Reynolds number as 4200 for their system. The multiple reference frame method was adopted to solve the governing equations for the bioreactor . Briefly, the continuity and momentum equations were solved in the stationary reference frame for the bulk region and in the rotating reference frame for the region surrounding the impeller, wherein the instantaneous velocity and pressure values are replaced by the sum of time averaged mean and fluctuating components. The continuity equation was solved for the secondary phase, air, as given by: 5 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{1}{{\rho\:}_{ra}}\left(\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{a}{\rho\:}_{a}\:\right)+\frac{\partial\:}{\partial\:{\text{x}}_{i}}\left({\alpha\:}_{a}{\rho\:}_{a}\:{u}_{ia}\right)\right)=0$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:{u}_{a}$$\end{document} refers to velocity of air. The solution of Eq. ( ) for \documentclass[12pt]{minimal}
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\begin{document}$$\:{\alpha\:}_{a}$$\end{document} was used to calculate volume fraction of V. odorata ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{\alpha\:}_{v}$$\end{document} ) from Eq. ( ). The momentum equation was solved for both phases individually and is given by: 6 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{q}{\rho\:}_{q}\:{u}_{qi}\right)+\:\frac{\partial\:}{\partial\:{\text{x}}_{j}}\left({\alpha\:}_{q}{\rho\:}_{q}\:{u}_{qi}{u}_{qj}\right)=\:-{\alpha\:}_{q}\frac{\partial\:p}{\partial\:{x}_{i}}+\frac{\partial\:}{\partial\:{x}_{j}}\left( \bar{\bar{\tau }} \right)+\:{\alpha\:}_{q}{\rho\:}_{q}g+{K}_{av}\:\left({u}_{ai}-{u}_{vi}\right)$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\bar{\bar{\tau }}={\alpha\:}_{q}{\mu\:}_{q}\left(\frac{\partial\:{u}_{i}}{\partial\:{x}_{j}}+\frac{\partial\:{u}_{j}}{\partial\:{x}_{i}}\right)-{\mu\:}_{t,q}\left(\frac{\partial\:{u}_{i}}{\partial\:{x}_{j}}+\frac{\partial\:{u}_{j}}{\partial\:{x}_{i}}-\frac{2}{3}{\delta\:}_{ij}\frac{\partial\:{u}_{k}}{\partial\:{x}_{k}}\right)-\:\frac{2}{3}{{\alpha\:}_{q}\rho\:}_{q}{\kappa\:}_{q}{\delta\:}_{ij}$$\end{document} where the turbulent viscosity ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{\mu\:}_{t,q}=\frac{{\kappa\:}^{2}}{{\epsilon\:}_{q}}{\rho\:}_{q}{C}_{\mu\:}\kappa\:{\delta\:}_{ij}$$\end{document} Here, \documentclass[12pt]{minimal}
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\begin{document}$$\:{C}_{\mu\:}$$\end{document} is a constant defined as 0.09. \documentclass[12pt]{minimal}
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\begin{document}$$\:{u}_{vi}$$\end{document} in Eq. ( ) refer to velocities of air and V. odorata suspension respectively and \documentclass[12pt]{minimal}
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\begin{document}$$\:{K}_{av}$$\end{document} refers to the interphase momentum exchange coefficient model between the two phases which is modeled as 9 \documentclass[12pt]{minimal}
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\begin{document}$$\:{K}_{av}=\:\frac{{\rho\:}_{a}f}{6{\tau\:}_{p}}{d}_{b}{A}_{I}$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:{\tau\:}_{p}$$\end{document} models the particulate relaxation time. The interfacial area density for the dispersed phase is modeled as the ratio of surface to volume for a spherical air bubble multiplied by the volume fraction of air which is given by 10 \documentclass[12pt]{minimal}
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\begin{document}$$\:{A}_{I}=\frac{6{\alpha\:}_{a}}{{d}_{b}}$$\end{document} Maluta et al. previously reported that the additives in fermentation fluids prevent bubbles from coalescing, leading to a narrow distribution of bubble sizes. This assumption has also been corroborated by Sharifi et al. who successfully simulated two-phase air-pseudoplastic fluid in bioreactors using the Schiller and Naumann model for modeling the drag force between the fluids. This formed the basis for the choice of the Schiller and Naumann model for the drag function in this study. The drag function \documentclass[12pt]{minimal}
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\begin{document}$$\:f=\:\frac{{C}_{D}{Re}_{r}}{24},$$\end{document} where the drag coefficient \documentclass[12pt]{minimal}
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\begin{document}$$\:{C}_{D}=\:\frac{24\:\left(1+0.15{{Re}_{r}}^{0.687}\right)}{{Re}_{r}}\:\:\:\:\:\:\text{f}\text{o}\text{r}\:{Re}_{r}\le\:1000$$\end{document} and 13 \documentclass[12pt]{minimal}
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\begin{document}$$\:{Re}_{r},$$\end{document} the relative Reynolds number between the primary and secondary phases was calculated by relative velocities of primary and secondary phases. It is given by 14 \documentclass[12pt]{minimal}
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\begin{document}$$\:\left|\:\right|$$\end{document} refers to the absolute value of the difference of relative velocity magnitudes. The particulate relaxation time ( \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} turbulence model was employed in this study. The standard \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} model has been widely employed as a general turbulence model and has been demonstrated to have sufficient accuracy to model turbulence in a stirred tank bioreactor comprising a two-phase system, consisting of air and a shear thinning fluid , . Further, the model has also been applied for modeling the turbulence in plant cell culture systems in bioreactors . The successful implementation of \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{v}{\rho\:}_{v}{\kappa\:}_{v}\right)+\nabla\:.\left({\alpha\:}_{v}{\rho\:}_{v}{\kappa\:}_{v}{u}_{v}\right)=\:\nabla\:.\left({\alpha\:}_{v}\left({\mu\:}_{v}+\:\frac{{\mu\:}_{t,v}}{{\sigma\:}_{k}}\right)\nabla\:{k}_{v}\right)+{{\alpha\:}_{v}G}_{\kappa\:,v}-{\alpha\:}_{v}{\rho\:}_{v}{ \epsilon }_{v}$$\end{document} 17 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{v}{\rho\:}_{v}{\epsilon\:}_{v}\right)+\nabla\:.\left({\alpha\:}_{v}{\rho\:}_{v}{\epsilon\:}_{v}{u}_{v}\right)=\:\nabla\:.\left({\alpha\:}_{v}\left({\mu\:}_{v}+\:\frac{{\mu\:}_{t,v}}{{\sigma\:}_{\epsilon\:}}\right)\nabla\:{\epsilon\:}_{w}\right)+{\alpha\:}_{v}\frac{{\epsilon\:}_{v}}{{k}_{v}}\left({C}_{1\epsilon\:}{\:G}_{k,v}-{C}_{2\epsilon\:}{\rho\:}_{v}{\epsilon\:}_{v}\:\right)$$\end{document} Here, \documentclass[12pt]{minimal}
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\begin{document}$$\:{C}_{2\epsilon\:}$$\end{document} are defined as constant values 1.44 and 1.92 respectively, as generally modeled. Since the volume fraction of the secondary phase is very low compared to the primary phase, air was modeled using the dispersed \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} turbulence model in this study. The parameters for the dispersed phase were calculated by assuming homogenous turbulence using the Tchen theory of dispersion of discrete particles . Further, to predict the velocity gradient at the boundary layer without the use of very fine meshes (with increased computational time), the near wall treatment was modeled using standard wall functions which has been found to be suitable for most flows . Details of the bioreactor geometry and computational domain The geometry of the stirred tank bioreactor was created using ANSYS SpaceClaim 2019R2 (ANSYS, Inc, United States) based on the measurements of a 3.1 L dished bottom glass bioreactor (Applikon Biotechnology B.V, Netherlands) as shown in Fig. (a). Dished bottom bioreactors are generally recommended for plant cells for better cell lifting capabilities . The tank has a diameter of 130 mm and a total height of 250 mm. The liquid working volume was 2.4 L which corresponded to a tank height of 200 mm. This was taken to be the maximum height of the computational domain in the CFD model to reduce computational effort. A single impeller was employed in this study and the setric, Rushton and marine impeller with design as shown in Fig. (b)-(d), were placed with an impeller clearance length of 65 mm for adequate mixing of the cell suspension in independent simulations. The choice of the impeller clearance length was based on the experimental setup of Babu and Srivastava . The setric impeller was custom made previously at Indian Institute of Technology Madras, and has four blades each inclined at an angle of 60° with a diameter of 45 mm, blade length 49 mm and width of 12 mm. The Rushton and marine impellers were standard impellers provided by Applikon Biotechnology B.V, Netherlands for a 3.1 L bioreactor. The Rushton impeller was employed with six blades each at an angle of 90° with the central disk, with a diameter of 45 mm, blade length of 10 mm and width of 10 mm. The marine impeller was employed with three blades at an angle of 45° with the central disk, with a diameter of 45 mm and a maximum blade length of 42 mm, and maximum width of 24 mm. A porous sparger has been used for sparging air in this study as it has the capacity to generate small bubbles with increased oxygen exchange area at low gas rates suitable for plant cell cultivation . The sparger (Applikon Biotechnology B.V, Netherlands) with diameter of 6 mm (Fig. (e)) and a pore size of 15 μm was placed 4 mm below the shaft of the impeller. Three baffles of length 139 mm and width 12 mm were placed in the bioreactor to prevent vortex formation. The fluid domain was only considered for the simulation and the solid components were removed from the fluid domain as void spaces using the split body option in SpaceClaim software. In order to model the rotation of the impeller using multiple reference frames, a cylindrical fluid domain 1.25 times the impeller diameter called the rotating domain was created enclosing the impeller, as shown in Fig. (a). The region outside the rotating domain was considered stationary. To achieve a conformal meshing between the rotating and stationary domain, topology was shared between the two bodies. The computational domain was then discretized into finite volumes using ANSYS Meshing 2019 R2 (ANSYS, Inc, United States). The geometry was meshed using an unstructured tetrahedral meshing with refinement near the impeller region. A grid size of 0.68 million computational cells was chosen after a grid sensitivity study was performed for three grid sizes ranging from 0.2 to 2.5 million to ascertain that the obtained results are independent of the mesh (supplementary Fig. S1). In addition, the grid convergence index was calculated to confirm the asymptotic convergence of the chosen grids (supplementary Table TS1). This mesh was used for further simulations and the computational domain used is shown in Fig. (f). The mesh quality was ascertained and specifically the mesh had an average skewness and orthogonality of 0.25 and 0.75 respectively and a maximum aspect ratio of 4. Definition of boundary conditions and numerical methods for solving the governing equations The governing equations were constrained by boundary conditions at the computational domain limits. The liquid level (maximum limit of the computational domain) was considered to be a degassing boundary. This boundary condition is valid when modeling low-pressure systems such as fermentations in bioreactors, making it sufficient to model only the liquid phase without the air headspace above the liquid – . Since plant cell suspension in this study is a low-pressure system, the degassing boundary allows the dispersed gas bubbles to escape while retaining the primary phase . The walls of the bioreactor vessel, shaft, impeller and the sparger wall were considered to be under no-slip condition for both air and the plant cell suspension. The inlet region of sparger was considered to be the input surface for air bubbles at an aeration rate of 0.2 vvm (volume of air per unit volume of culture medium per minute) and the impeller cell zone was set to an agitation rate of 85 rpm. This condition was adopted from cultivation conditions of V. odorata cell cultures to compare the hydrodynamics in all three impellers. Since the temperature of the system is maintained constant for plant cell growth, and being an incompressible flow, the pressure-based solver was used to solve the governing equations. Here, the pressure corrector equation, phase coupled-SIMPLE algorithm was used to correct the velocity to overcome the constraint of solving Eq. ( ) simultaneously with Eq. ( ). The gradient term was spatially discretized using least squares cell-based algorithm. The pressure equation was discretized to second order and the other governing equations were discretized to first order accuracy. The temporal discretization was performed with implicit integration with first order accuracy. Initially, a single phase (water only) simulation was carried out. The single-phase steady state results were used to initialize air-water simulation which was further used to initialize the air- V. odorata simulation to overcome convergence difficulties. The time step was taken to be 1.5 ms with maximum 20 iterations per time step. The governing equations of the model with appropriate boundary conditions were solved numerically using the commercially available code, ANSYS Fluent 2019R2 (ANSYS, Inc, United States) in a high-performance computing cluster environment. Convergence was defined to be attained when the residuals reached an order of 10 −5 for all equations and a constant volume averaged value of k L a, energy dissipation rate and liquid velocity magnitude were achieved through subsequent time steps. Modeling of volumetric liquid phase oxygen mass transfer coefficient Volumetric mass transfer coefficient of oxygen (k L a) is a parameter generally used to characterize the mass transfer of oxygen from the air to the liquid phase in stirred tank bioreactors. It is calculated as the product of the liquid mass transfer coefficient \documentclass[12pt]{minimal}
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\begin{document}$$\:{D}_{L}$$\end{document} is the molecular diffusivity of oxygen in liquid. For a non-Newtonian fluid, Eq. ( ) was modified by Kawase and Moo as given by 19 \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}=\frac{2}{\sqrt{\pi\:}}C\:\sqrt{{D}_{L}}{\left(\frac{\epsilon\:\rho\:}{K}\right)}^{\frac{1}{2(1+n)}}$$\end{document} Here C was taken as 0.15 . The interfacial area available for mass transfer between phases was calculated as given in Eq. ( ). Here, K and n refers to the consistency and flow behavior index respectively. This equation was incorporated in Fluent using a custom field function. Modeling of shear stress acting on plant cell cultures Plant cells are exposed to shear stress based on its relative size to the Kolmogorov length scale. The Kolmogorov length ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{\tau\:}_{t}=\mu\:{\left(\frac{\epsilon\:}{\upsilon\:}\right)}^{0.5}$$\end{document} Unlike microbial and mammalian cells, plant cells tend to form aggregates and if the aggregate size is larger than \documentclass[12pt]{minimal}
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\begin{document}$$\:{\eta\:}_{k}$$\end{document} , potentially ranging from 0.1 to 2 mm in diameter , the cells are subjected to shear due to velocity differences across the diameter of the cell aggregate. This shear stress can be calculated as given in the following Eq. ( ) 21 \documentclass[12pt]{minimal}
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\begin{document}$$\:{d}_{cell}$$\end{document} refers to the diameter of the cell aggregate. These equations were incorporated in Fluent using a custom field function. Experimental determination of volumetric mass transfer coefficient for model validation In this study, \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}a$$\end{document} for setric impeller was experimentally determined using dynamic gassing in method . Briefly, the bioreactor (3.1 L) with setric impeller was autoclaved with 2.4 L working volume of water and connected to the DO sensor for polarization. After cooling, the bioreactor was aerated to constant oxygen concentration at 125 rpm and 2 vvm. One point calibration at 100% was performed after the saturation was sufficiently reached. The bioreactor was then stripped off oxygen completely by purging nitrogen gas. Once the dissolved oxygen concentration reached less than 2%, filtered compressed air was sparged in the reactor at the simulated operating conditions until steady state saturation was reached. The measurements of dissolved oxygen were recorded as a function of time using a polographic oxygen sensor (Applikon Biotechnology B.V, Netherlands). The probe response time of the O 2 sensor used in this study was 5 s which was significantly less than 1/ k L a (689 s). Therefore, the effect of the delay in the O 2 sensor on the measurement was neglected – . To calculate the rate of oxygen transfer from gas to liquid, the mass balance for the dissolved oxygen in the bioreactor was considered and is given by: 22 \documentclass[12pt]{minimal}
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\begin{document}$$\:ln\left(\frac{{C}^{*}-{C}_{L}}{{C}^{*}-{{C}_{L}}_{t=0}}\right)$$\end{document} as a function of t from Eq. ( ) using linear regression in Microsoft office excel 2019. Experimental determination of viscosity and average aggregate size of V. odorata cell suspension V. odorata VOP-4 callus was previously established by Narayani et al. and was maintained by periodic subculturing. The cell suspension culture was developed as described by Babu and Srivastava . Briefly, the maintained callus (6 gDWL -1 ) was suspended in 50 mL woody plant medium (Himedia Laboratories) with 3% (w/v) sucrose and 3 mg L − 1 of 2,4-dichlorophenoxy acetic acid at an initial pH of 5.8. The cells were grown in an orbital shaker in conical flasks for 14 days at 23℃ with a photoperiod of 16/8 h light/dark cycle. Further, the cells were filtered using a Buchner funnel to obtain a synchronous fine cell suspension which was used as inoculum for cultivation of V. odorata in bioreactors . In order to bring the CFD model closer to reality, the rheological parameters of the cell suspension were characterised experimentally. V. odorata cell suspension was subjected to varying shear rates ( \documentclass[12pt]{minimal}
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\begin{document}$$\:\dot{\gamma\:}$$\end{document} ) from 0.0095 to 1000 s − 1 to determine the corresponding shear stress \documentclass[12pt]{minimal}
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\begin{document}$$\:\left(\tau\:\right)$$\end{document} using the rheometer AntonPaar MCR502 at 25℃. The flow behavior (n) and consistency index (K) were determined correlated by the Ostwald de Waele equation given by 23 \documentclass[12pt]{minimal}
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\begin{document}$$\:\pm\:$$\end{document} standard error. The experimentally determined rheological parameters of V. odorata presented in Table was used to model the liquid properties in the CFD simulation. With a flow behavior index less than 1, V. odorata cell suspension was found to be pseudoplastic in nature. This characteristic is similar to other plant cell species which also exhibit pseudoplastic behaviour – . The non-Newtonian behavior of plant cells is generally attributed to cell elongation in suspension and the ability of plant cells to grow in high cell densities due to its comparatively lower oxygen demand . Further, in order to obtain the average cell aggregate size of V. odorata in suspension, 20 \documentclass[12pt]{minimal}
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\begin{document}$$\:\mu\:$$\end{document} L of the suspension was pipetted using cut tips onto a glass slide and was observed under an Olympus IX83 inverted fluorescence microscope. The images were then processed using the software ImageJ to determine the range and average cell aggregate size, tabulated in Table .
The section first presents the governing equations that were employed to obtain the fluid flow in a stirred bioreactor for plant cell cultures. Further, the description of the computational domain and boundary conditions applied are discussed. The discretization schemes and the numerical methods used for solving the governing equations are also presented. Modeling governing equations for the two-phase fluid flow The fluid properties of the plant cell suspension were determined experimentally as described in section “Experimental determination of viscosity and average aggregate size of V. odorata cell suspension”. It was defined as the primary phase, while the sparged air was defined as the dispersed secondary phase with properties defined at temperature 26.6 ℃ as this temperature was previously established to be the optimum temperature for maximum biomass productivity in V. odorata cell cultures . The two phases were assumed to be incompressible and considered as independently interacting fluid continuum and modeled using the two-phase Eulerian model. The average size of the air bubbles was determined by the Sauter mean diameter correlation ( \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{{d}_{b}}{{d}_{s}}=7.35\:{\left[{We}^{-1.7}{Re}^{0.1}{Fr}^{1.8}{\frac{{d}_{p}}{{d}_{s}}}^{1.7}\right]}^{0.2}$$\end{document} where We , Re and Fr corresponds to the Weber, Reynolds and Froude numbers respectively, \documentclass[12pt]{minimal}
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\begin{document}$$\:{\alpha\:}_{q}$$\end{document} , the volume fraction of phase q in a single computational element is a continuous function in space and time. Hence the sum of volume fractions of air and the plant cell suspension phases in a single computational cell is equal to 1 as defined by phasic volume fraction given by Eq. ( ), as follows: 3 \documentclass[12pt]{minimal}
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\begin{document}$$\:{\mu\:}_{w}$$\end{document} refers to the dynamic viscosity of water. It is generally considered that for a system to be turbulent if the \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re}\:$$\end{document} for a bioreactor is greater than 10000, while laminar if the \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re}$$\end{document} is less than 4 . Though flow in this system may fall under transitional regime, modeling the flow as fully turbulent resulted in closer alignment with the experimental data. Hence, the Reynolds-averaged Navier-Stokes (RANS) equations were solved for the two-phase system in this study. A similar approach has also been adopted by Sarkar et al. where they defined the critical Reynolds number as 4200 for their system. The multiple reference frame method was adopted to solve the governing equations for the bioreactor . Briefly, the continuity and momentum equations were solved in the stationary reference frame for the bulk region and in the rotating reference frame for the region surrounding the impeller, wherein the instantaneous velocity and pressure values are replaced by the sum of time averaged mean and fluctuating components. The continuity equation was solved for the secondary phase, air, as given by: 5 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{1}{{\rho\:}_{ra}}\left(\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{a}{\rho\:}_{a}\:\right)+\frac{\partial\:}{\partial\:{\text{x}}_{i}}\left({\alpha\:}_{a}{\rho\:}_{a}\:{u}_{ia}\right)\right)=0$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:{u}_{a}$$\end{document} refers to velocity of air. The solution of Eq. ( ) for \documentclass[12pt]{minimal}
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\begin{document}$$\:{\alpha\:}_{a}$$\end{document} was used to calculate volume fraction of V. odorata ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{\alpha\:}_{v}$$\end{document} ) from Eq. ( ). The momentum equation was solved for both phases individually and is given by: 6 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{q}{\rho\:}_{q}\:{u}_{qi}\right)+\:\frac{\partial\:}{\partial\:{\text{x}}_{j}}\left({\alpha\:}_{q}{\rho\:}_{q}\:{u}_{qi}{u}_{qj}\right)=\:-{\alpha\:}_{q}\frac{\partial\:p}{\partial\:{x}_{i}}+\frac{\partial\:}{\partial\:{x}_{j}}\left( \bar{\bar{\tau }} \right)+\:{\alpha\:}_{q}{\rho\:}_{q}g+{K}_{av}\:\left({u}_{ai}-{u}_{vi}\right)$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\bar{\bar{\tau }}={\alpha\:}_{q}{\mu\:}_{q}\left(\frac{\partial\:{u}_{i}}{\partial\:{x}_{j}}+\frac{\partial\:{u}_{j}}{\partial\:{x}_{i}}\right)-{\mu\:}_{t,q}\left(\frac{\partial\:{u}_{i}}{\partial\:{x}_{j}}+\frac{\partial\:{u}_{j}}{\partial\:{x}_{i}}-\frac{2}{3}{\delta\:}_{ij}\frac{\partial\:{u}_{k}}{\partial\:{x}_{k}}\right)-\:\frac{2}{3}{{\alpha\:}_{q}\rho\:}_{q}{\kappa\:}_{q}{\delta\:}_{ij}$$\end{document} where the turbulent viscosity ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{\mu\:}_{t,q}=\frac{{\kappa\:}^{2}}{{\epsilon\:}_{q}}{\rho\:}_{q}{C}_{\mu\:}\kappa\:{\delta\:}_{ij}$$\end{document} Here, \documentclass[12pt]{minimal}
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\begin{document}$$\:{K}_{av}=\:\frac{{\rho\:}_{a}f}{6{\tau\:}_{p}}{d}_{b}{A}_{I}$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:{\tau\:}_{p}$$\end{document} models the particulate relaxation time. The interfacial area density for the dispersed phase is modeled as the ratio of surface to volume for a spherical air bubble multiplied by the volume fraction of air which is given by 10 \documentclass[12pt]{minimal}
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\begin{document}$$\:{A}_{I}=\frac{6{\alpha\:}_{a}}{{d}_{b}}$$\end{document} Maluta et al. previously reported that the additives in fermentation fluids prevent bubbles from coalescing, leading to a narrow distribution of bubble sizes. This assumption has also been corroborated by Sharifi et al. who successfully simulated two-phase air-pseudoplastic fluid in bioreactors using the Schiller and Naumann model for modeling the drag force between the fluids. This formed the basis for the choice of the Schiller and Naumann model for the drag function in this study. The drag function \documentclass[12pt]{minimal}
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\begin{document}$$\:{C}_{D}=\:\frac{24\:\left(1+0.15{{Re}_{r}}^{0.687}\right)}{{Re}_{r}}\:\:\:\:\:\:\text{f}\text{o}\text{r}\:{Re}_{r}\le\:1000$$\end{document} and 13 \documentclass[12pt]{minimal}
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\begin{document}$$\:{Re}_{r},$$\end{document} the relative Reynolds number between the primary and secondary phases was calculated by relative velocities of primary and secondary phases. It is given by 14 \documentclass[12pt]{minimal}
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\begin{document}$$\:\left|\:\right|$$\end{document} refers to the absolute value of the difference of relative velocity magnitudes. The particulate relaxation time ( \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} turbulence model was employed in this study. The standard \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} model has been widely employed as a general turbulence model and has been demonstrated to have sufficient accuracy to model turbulence in a stirred tank bioreactor comprising a two-phase system, consisting of air and a shear thinning fluid , . Further, the model has also been applied for modeling the turbulence in plant cell culture systems in bioreactors . The successful implementation of \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} model in relevant previous studies provided the rationale for its selection in this investigation. The transport equations for turbulent kinetic energy, \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} for primary phase is given by: 16 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{v}{\rho\:}_{v}{\kappa\:}_{v}\right)+\nabla\:.\left({\alpha\:}_{v}{\rho\:}_{v}{\kappa\:}_{v}{u}_{v}\right)=\:\nabla\:.\left({\alpha\:}_{v}\left({\mu\:}_{v}+\:\frac{{\mu\:}_{t,v}}{{\sigma\:}_{k}}\right)\nabla\:{k}_{v}\right)+{{\alpha\:}_{v}G}_{\kappa\:,v}-{\alpha\:}_{v}{\rho\:}_{v}{ \epsilon }_{v}$$\end{document} 17 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{v}{\rho\:}_{v}{\epsilon\:}_{v}\right)+\nabla\:.\left({\alpha\:}_{v}{\rho\:}_{v}{\epsilon\:}_{v}{u}_{v}\right)=\:\nabla\:.\left({\alpha\:}_{v}\left({\mu\:}_{v}+\:\frac{{\mu\:}_{t,v}}{{\sigma\:}_{\epsilon\:}}\right)\nabla\:{\epsilon\:}_{w}\right)+{\alpha\:}_{v}\frac{{\epsilon\:}_{v}}{{k}_{v}}\left({C}_{1\epsilon\:}{\:G}_{k,v}-{C}_{2\epsilon\:}{\rho\:}_{v}{\epsilon\:}_{v}\:\right)$$\end{document} Here, \documentclass[12pt]{minimal}
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\begin{document}$$\:{C}_{2\epsilon\:}$$\end{document} are defined as constant values 1.44 and 1.92 respectively, as generally modeled. Since the volume fraction of the secondary phase is very low compared to the primary phase, air was modeled using the dispersed \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} turbulence model in this study. The parameters for the dispersed phase were calculated by assuming homogenous turbulence using the Tchen theory of dispersion of discrete particles . Further, to predict the velocity gradient at the boundary layer without the use of very fine meshes (with increased computational time), the near wall treatment was modeled using standard wall functions which has been found to be suitable for most flows . Details of the bioreactor geometry and computational domain The geometry of the stirred tank bioreactor was created using ANSYS SpaceClaim 2019R2 (ANSYS, Inc, United States) based on the measurements of a 3.1 L dished bottom glass bioreactor (Applikon Biotechnology B.V, Netherlands) as shown in Fig. (a). Dished bottom bioreactors are generally recommended for plant cells for better cell lifting capabilities . The tank has a diameter of 130 mm and a total height of 250 mm. The liquid working volume was 2.4 L which corresponded to a tank height of 200 mm. This was taken to be the maximum height of the computational domain in the CFD model to reduce computational effort. A single impeller was employed in this study and the setric, Rushton and marine impeller with design as shown in Fig. (b)-(d), were placed with an impeller clearance length of 65 mm for adequate mixing of the cell suspension in independent simulations. The choice of the impeller clearance length was based on the experimental setup of Babu and Srivastava . The setric impeller was custom made previously at Indian Institute of Technology Madras, and has four blades each inclined at an angle of 60° with a diameter of 45 mm, blade length 49 mm and width of 12 mm. The Rushton and marine impellers were standard impellers provided by Applikon Biotechnology B.V, Netherlands for a 3.1 L bioreactor. The Rushton impeller was employed with six blades each at an angle of 90° with the central disk, with a diameter of 45 mm, blade length of 10 mm and width of 10 mm. The marine impeller was employed with three blades at an angle of 45° with the central disk, with a diameter of 45 mm and a maximum blade length of 42 mm, and maximum width of 24 mm. A porous sparger has been used for sparging air in this study as it has the capacity to generate small bubbles with increased oxygen exchange area at low gas rates suitable for plant cell cultivation . The sparger (Applikon Biotechnology B.V, Netherlands) with diameter of 6 mm (Fig. (e)) and a pore size of 15 μm was placed 4 mm below the shaft of the impeller. Three baffles of length 139 mm and width 12 mm were placed in the bioreactor to prevent vortex formation. The fluid domain was only considered for the simulation and the solid components were removed from the fluid domain as void spaces using the split body option in SpaceClaim software. In order to model the rotation of the impeller using multiple reference frames, a cylindrical fluid domain 1.25 times the impeller diameter called the rotating domain was created enclosing the impeller, as shown in Fig. (a). The region outside the rotating domain was considered stationary. To achieve a conformal meshing between the rotating and stationary domain, topology was shared between the two bodies. The computational domain was then discretized into finite volumes using ANSYS Meshing 2019 R2 (ANSYS, Inc, United States). The geometry was meshed using an unstructured tetrahedral meshing with refinement near the impeller region. A grid size of 0.68 million computational cells was chosen after a grid sensitivity study was performed for three grid sizes ranging from 0.2 to 2.5 million to ascertain that the obtained results are independent of the mesh (supplementary Fig. S1). In addition, the grid convergence index was calculated to confirm the asymptotic convergence of the chosen grids (supplementary Table TS1). This mesh was used for further simulations and the computational domain used is shown in Fig. (f). The mesh quality was ascertained and specifically the mesh had an average skewness and orthogonality of 0.25 and 0.75 respectively and a maximum aspect ratio of 4. Definition of boundary conditions and numerical methods for solving the governing equations The governing equations were constrained by boundary conditions at the computational domain limits. The liquid level (maximum limit of the computational domain) was considered to be a degassing boundary. This boundary condition is valid when modeling low-pressure systems such as fermentations in bioreactors, making it sufficient to model only the liquid phase without the air headspace above the liquid – . Since plant cell suspension in this study is a low-pressure system, the degassing boundary allows the dispersed gas bubbles to escape while retaining the primary phase . The walls of the bioreactor vessel, shaft, impeller and the sparger wall were considered to be under no-slip condition for both air and the plant cell suspension. The inlet region of sparger was considered to be the input surface for air bubbles at an aeration rate of 0.2 vvm (volume of air per unit volume of culture medium per minute) and the impeller cell zone was set to an agitation rate of 85 rpm. This condition was adopted from cultivation conditions of V. odorata cell cultures to compare the hydrodynamics in all three impellers. Since the temperature of the system is maintained constant for plant cell growth, and being an incompressible flow, the pressure-based solver was used to solve the governing equations. Here, the pressure corrector equation, phase coupled-SIMPLE algorithm was used to correct the velocity to overcome the constraint of solving Eq. ( ) simultaneously with Eq. ( ). The gradient term was spatially discretized using least squares cell-based algorithm. The pressure equation was discretized to second order and the other governing equations were discretized to first order accuracy. The temporal discretization was performed with implicit integration with first order accuracy. Initially, a single phase (water only) simulation was carried out. The single-phase steady state results were used to initialize air-water simulation which was further used to initialize the air- V. odorata simulation to overcome convergence difficulties. The time step was taken to be 1.5 ms with maximum 20 iterations per time step. The governing equations of the model with appropriate boundary conditions were solved numerically using the commercially available code, ANSYS Fluent 2019R2 (ANSYS, Inc, United States) in a high-performance computing cluster environment. Convergence was defined to be attained when the residuals reached an order of 10 −5 for all equations and a constant volume averaged value of k L a, energy dissipation rate and liquid velocity magnitude were achieved through subsequent time steps. Modeling of volumetric liquid phase oxygen mass transfer coefficient Volumetric mass transfer coefficient of oxygen (k L a) is a parameter generally used to characterize the mass transfer of oxygen from the air to the liquid phase in stirred tank bioreactors. It is calculated as the product of the liquid mass transfer coefficient \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}$$\end{document} by Sarkar et al. and Amer et al. for air-water fluid pairs given by 18 \documentclass[12pt]{minimal}
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\begin{document}$$\:{D}_{L}$$\end{document} is the molecular diffusivity of oxygen in liquid. For a non-Newtonian fluid, Eq. ( ) was modified by Kawase and Moo as given by 19 \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}=\frac{2}{\sqrt{\pi\:}}C\:\sqrt{{D}_{L}}{\left(\frac{\epsilon\:\rho\:}{K}\right)}^{\frac{1}{2(1+n)}}$$\end{document} Here C was taken as 0.15 . The interfacial area available for mass transfer between phases was calculated as given in Eq. ( ). Here, K and n refers to the consistency and flow behavior index respectively. This equation was incorporated in Fluent using a custom field function. Modeling of shear stress acting on plant cell cultures Plant cells are exposed to shear stress based on its relative size to the Kolmogorov length scale. The Kolmogorov length ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{\tau\:}_{t}=\mu\:{\left(\frac{\epsilon\:}{\upsilon\:}\right)}^{0.5}$$\end{document} Unlike microbial and mammalian cells, plant cells tend to form aggregates and if the aggregate size is larger than \documentclass[12pt]{minimal}
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\begin{document}$$\:{\eta\:}_{k}$$\end{document} , potentially ranging from 0.1 to 2 mm in diameter , the cells are subjected to shear due to velocity differences across the diameter of the cell aggregate. This shear stress can be calculated as given in the following Eq. ( ) 21 \documentclass[12pt]{minimal}
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\begin{document}$$\:{d}_{cell}$$\end{document} refers to the diameter of the cell aggregate. These equations were incorporated in Fluent using a custom field function.
The fluid properties of the plant cell suspension were determined experimentally as described in section “Experimental determination of viscosity and average aggregate size of V. odorata cell suspension”. It was defined as the primary phase, while the sparged air was defined as the dispersed secondary phase with properties defined at temperature 26.6 ℃ as this temperature was previously established to be the optimum temperature for maximum biomass productivity in V. odorata cell cultures . The two phases were assumed to be incompressible and considered as independently interacting fluid continuum and modeled using the two-phase Eulerian model. The average size of the air bubbles was determined by the Sauter mean diameter correlation ( \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{{d}_{b}}{{d}_{s}}=7.35\:{\left[{We}^{-1.7}{Re}^{0.1}{Fr}^{1.8}{\frac{{d}_{p}}{{d}_{s}}}^{1.7}\right]}^{0.2}$$\end{document} where We , Re and Fr corresponds to the Weber, Reynolds and Froude numbers respectively, \documentclass[12pt]{minimal}
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\begin{document}$$\:{(V}_{q})\:$$\end{document} occupied by phase q, in the system is given by Eq. ( ), as follows: 2 \documentclass[12pt]{minimal}
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\begin{document}$$\:{\alpha\:}_{q}$$\end{document} , the volume fraction of phase q in a single computational element is a continuous function in space and time. Hence the sum of volume fractions of air and the plant cell suspension phases in a single computational cell is equal to 1 as defined by phasic volume fraction given by Eq. ( ), as follows: 3 \documentclass[12pt]{minimal}
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\begin{document}$$\:\sum\:_{q=1}^{2}{\alpha\:}_{q}=1$$\end{document} The effective density of phase q in every computational cell is defined as \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re})\:$$\end{document} of the overall system was calculated to be 3000 as per following equation: 4 \documentclass[12pt]{minimal}
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\begin{document}$$\:{\mu\:}_{w}$$\end{document} refers to the dynamic viscosity of water. It is generally considered that for a system to be turbulent if the \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re}\:$$\end{document} for a bioreactor is greater than 10000, while laminar if the \documentclass[12pt]{minimal}
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\begin{document}$$\:{N}_{Re}$$\end{document} is less than 4 . Though flow in this system may fall under transitional regime, modeling the flow as fully turbulent resulted in closer alignment with the experimental data. Hence, the Reynolds-averaged Navier-Stokes (RANS) equations were solved for the two-phase system in this study. A similar approach has also been adopted by Sarkar et al. where they defined the critical Reynolds number as 4200 for their system. The multiple reference frame method was adopted to solve the governing equations for the bioreactor . Briefly, the continuity and momentum equations were solved in the stationary reference frame for the bulk region and in the rotating reference frame for the region surrounding the impeller, wherein the instantaneous velocity and pressure values are replaced by the sum of time averaged mean and fluctuating components. The continuity equation was solved for the secondary phase, air, as given by: 5 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{1}{{\rho\:}_{ra}}\left(\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{a}{\rho\:}_{a}\:\right)+\frac{\partial\:}{\partial\:{\text{x}}_{i}}\left({\alpha\:}_{a}{\rho\:}_{a}\:{u}_{ia}\right)\right)=0$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:{\alpha\:}_{a}$$\end{document} was used to calculate volume fraction of V. odorata ( \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{q}{\rho\:}_{q}\:{u}_{qi}\right)+\:\frac{\partial\:}{\partial\:{\text{x}}_{j}}\left({\alpha\:}_{q}{\rho\:}_{q}\:{u}_{qi}{u}_{qj}\right)=\:-{\alpha\:}_{q}\frac{\partial\:p}{\partial\:{x}_{i}}+\frac{\partial\:}{\partial\:{x}_{j}}\left( \bar{\bar{\tau }} \right)+\:{\alpha\:}_{q}{\rho\:}_{q}g+{K}_{av}\:\left({u}_{ai}-{u}_{vi}\right)$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\bar{\bar{\tau }}={\alpha\:}_{q}{\mu\:}_{q}\left(\frac{\partial\:{u}_{i}}{\partial\:{x}_{j}}+\frac{\partial\:{u}_{j}}{\partial\:{x}_{i}}\right)-{\mu\:}_{t,q}\left(\frac{\partial\:{u}_{i}}{\partial\:{x}_{j}}+\frac{\partial\:{u}_{j}}{\partial\:{x}_{i}}-\frac{2}{3}{\delta\:}_{ij}\frac{\partial\:{u}_{k}}{\partial\:{x}_{k}}\right)-\:\frac{2}{3}{{\alpha\:}_{q}\rho\:}_{q}{\kappa\:}_{q}{\delta\:}_{ij}$$\end{document} where the turbulent viscosity ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{K}_{av}=\:\frac{{\rho\:}_{a}f}{6{\tau\:}_{p}}{d}_{b}{A}_{I}$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:{A}_{I}=\frac{6{\alpha\:}_{a}}{{d}_{b}}$$\end{document} Maluta et al. previously reported that the additives in fermentation fluids prevent bubbles from coalescing, leading to a narrow distribution of bubble sizes. This assumption has also been corroborated by Sharifi et al. who successfully simulated two-phase air-pseudoplastic fluid in bioreactors using the Schiller and Naumann model for modeling the drag force between the fluids. This formed the basis for the choice of the Schiller and Naumann model for the drag function in this study. The drag function \documentclass[12pt]{minimal}
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\begin{document}$$\:{Re}_{r},$$\end{document} the relative Reynolds number between the primary and secondary phases was calculated by relative velocities of primary and secondary phases. It is given by 14 \documentclass[12pt]{minimal}
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\begin{document}$$\:{Re}_{r}=\:\frac{{\rho\:}_{w}\left|{u}_{vi}-\:{u}_{ai}\right|{d}_{a}}{{\mu\:}_{v}}$$\end{document} where \documentclass[12pt]{minimal}
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\begin{document}$$\:\left|\:\right|$$\end{document} refers to the absolute value of the difference of relative velocity magnitudes. The particulate relaxation time ( \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} turbulence model was employed in this study. The standard \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} model has been widely employed as a general turbulence model and has been demonstrated to have sufficient accuracy to model turbulence in a stirred tank bioreactor comprising a two-phase system, consisting of air and a shear thinning fluid , . Further, the model has also been applied for modeling the turbulence in plant cell culture systems in bioreactors . The successful implementation of \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} model in relevant previous studies provided the rationale for its selection in this investigation. The transport equations for turbulent kinetic energy, \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} for primary phase is given by: 16 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{v}{\rho\:}_{v}{\kappa\:}_{v}\right)+\nabla\:.\left({\alpha\:}_{v}{\rho\:}_{v}{\kappa\:}_{v}{u}_{v}\right)=\:\nabla\:.\left({\alpha\:}_{v}\left({\mu\:}_{v}+\:\frac{{\mu\:}_{t,v}}{{\sigma\:}_{k}}\right)\nabla\:{k}_{v}\right)+{{\alpha\:}_{v}G}_{\kappa\:,v}-{\alpha\:}_{v}{\rho\:}_{v}{ \epsilon }_{v}$$\end{document} 17 \documentclass[12pt]{minimal}
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\begin{document}$$\:\frac{\partial\:}{\partial\:t}\left({\alpha\:}_{v}{\rho\:}_{v}{\epsilon\:}_{v}\right)+\nabla\:.\left({\alpha\:}_{v}{\rho\:}_{v}{\epsilon\:}_{v}{u}_{v}\right)=\:\nabla\:.\left({\alpha\:}_{v}\left({\mu\:}_{v}+\:\frac{{\mu\:}_{t,v}}{{\sigma\:}_{\epsilon\:}}\right)\nabla\:{\epsilon\:}_{w}\right)+{\alpha\:}_{v}\frac{{\epsilon\:}_{v}}{{k}_{v}}\left({C}_{1\epsilon\:}{\:G}_{k,v}-{C}_{2\epsilon\:}{\rho\:}_{v}{\epsilon\:}_{v}\:\right)$$\end{document} Here, \documentclass[12pt]{minimal}
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\begin{document}$$\:{\:G}_{k,v}$$\end{document} refers to the production of turbulence kinetic energy due to mean velocity gradients. \documentclass[12pt]{minimal}
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\begin{document}$$\:{C}_{2\epsilon\:}$$\end{document} are defined as constant values 1.44 and 1.92 respectively, as generally modeled. Since the volume fraction of the secondary phase is very low compared to the primary phase, air was modeled using the dispersed \documentclass[12pt]{minimal}
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\begin{document}$$\:\epsilon\:$$\end{document} turbulence model in this study. The parameters for the dispersed phase were calculated by assuming homogenous turbulence using the Tchen theory of dispersion of discrete particles . Further, to predict the velocity gradient at the boundary layer without the use of very fine meshes (with increased computational time), the near wall treatment was modeled using standard wall functions which has been found to be suitable for most flows .
The geometry of the stirred tank bioreactor was created using ANSYS SpaceClaim 2019R2 (ANSYS, Inc, United States) based on the measurements of a 3.1 L dished bottom glass bioreactor (Applikon Biotechnology B.V, Netherlands) as shown in Fig. (a). Dished bottom bioreactors are generally recommended for plant cells for better cell lifting capabilities . The tank has a diameter of 130 mm and a total height of 250 mm. The liquid working volume was 2.4 L which corresponded to a tank height of 200 mm. This was taken to be the maximum height of the computational domain in the CFD model to reduce computational effort. A single impeller was employed in this study and the setric, Rushton and marine impeller with design as shown in Fig. (b)-(d), were placed with an impeller clearance length of 65 mm for adequate mixing of the cell suspension in independent simulations. The choice of the impeller clearance length was based on the experimental setup of Babu and Srivastava . The setric impeller was custom made previously at Indian Institute of Technology Madras, and has four blades each inclined at an angle of 60° with a diameter of 45 mm, blade length 49 mm and width of 12 mm. The Rushton and marine impellers were standard impellers provided by Applikon Biotechnology B.V, Netherlands for a 3.1 L bioreactor. The Rushton impeller was employed with six blades each at an angle of 90° with the central disk, with a diameter of 45 mm, blade length of 10 mm and width of 10 mm. The marine impeller was employed with three blades at an angle of 45° with the central disk, with a diameter of 45 mm and a maximum blade length of 42 mm, and maximum width of 24 mm. A porous sparger has been used for sparging air in this study as it has the capacity to generate small bubbles with increased oxygen exchange area at low gas rates suitable for plant cell cultivation . The sparger (Applikon Biotechnology B.V, Netherlands) with diameter of 6 mm (Fig. (e)) and a pore size of 15 μm was placed 4 mm below the shaft of the impeller. Three baffles of length 139 mm and width 12 mm were placed in the bioreactor to prevent vortex formation. The fluid domain was only considered for the simulation and the solid components were removed from the fluid domain as void spaces using the split body option in SpaceClaim software. In order to model the rotation of the impeller using multiple reference frames, a cylindrical fluid domain 1.25 times the impeller diameter called the rotating domain was created enclosing the impeller, as shown in Fig. (a). The region outside the rotating domain was considered stationary. To achieve a conformal meshing between the rotating and stationary domain, topology was shared between the two bodies. The computational domain was then discretized into finite volumes using ANSYS Meshing 2019 R2 (ANSYS, Inc, United States). The geometry was meshed using an unstructured tetrahedral meshing with refinement near the impeller region. A grid size of 0.68 million computational cells was chosen after a grid sensitivity study was performed for three grid sizes ranging from 0.2 to 2.5 million to ascertain that the obtained results are independent of the mesh (supplementary Fig. S1). In addition, the grid convergence index was calculated to confirm the asymptotic convergence of the chosen grids (supplementary Table TS1). This mesh was used for further simulations and the computational domain used is shown in Fig. (f). The mesh quality was ascertained and specifically the mesh had an average skewness and orthogonality of 0.25 and 0.75 respectively and a maximum aspect ratio of 4.
The governing equations were constrained by boundary conditions at the computational domain limits. The liquid level (maximum limit of the computational domain) was considered to be a degassing boundary. This boundary condition is valid when modeling low-pressure systems such as fermentations in bioreactors, making it sufficient to model only the liquid phase without the air headspace above the liquid – . Since plant cell suspension in this study is a low-pressure system, the degassing boundary allows the dispersed gas bubbles to escape while retaining the primary phase . The walls of the bioreactor vessel, shaft, impeller and the sparger wall were considered to be under no-slip condition for both air and the plant cell suspension. The inlet region of sparger was considered to be the input surface for air bubbles at an aeration rate of 0.2 vvm (volume of air per unit volume of culture medium per minute) and the impeller cell zone was set to an agitation rate of 85 rpm. This condition was adopted from cultivation conditions of V. odorata cell cultures to compare the hydrodynamics in all three impellers. Since the temperature of the system is maintained constant for plant cell growth, and being an incompressible flow, the pressure-based solver was used to solve the governing equations. Here, the pressure corrector equation, phase coupled-SIMPLE algorithm was used to correct the velocity to overcome the constraint of solving Eq. ( ) simultaneously with Eq. ( ). The gradient term was spatially discretized using least squares cell-based algorithm. The pressure equation was discretized to second order and the other governing equations were discretized to first order accuracy. The temporal discretization was performed with implicit integration with first order accuracy. Initially, a single phase (water only) simulation was carried out. The single-phase steady state results were used to initialize air-water simulation which was further used to initialize the air- V. odorata simulation to overcome convergence difficulties. The time step was taken to be 1.5 ms with maximum 20 iterations per time step. The governing equations of the model with appropriate boundary conditions were solved numerically using the commercially available code, ANSYS Fluent 2019R2 (ANSYS, Inc, United States) in a high-performance computing cluster environment. Convergence was defined to be attained when the residuals reached an order of 10 −5 for all equations and a constant volume averaged value of k L a, energy dissipation rate and liquid velocity magnitude were achieved through subsequent time steps.
Volumetric mass transfer coefficient of oxygen (k L a) is a parameter generally used to characterize the mass transfer of oxygen from the air to the liquid phase in stirred tank bioreactors. It is calculated as the product of the liquid mass transfer coefficient \documentclass[12pt]{minimal}
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\begin{document}$$\:{D}_{L}$$\end{document} is the molecular diffusivity of oxygen in liquid. For a non-Newtonian fluid, Eq. ( ) was modified by Kawase and Moo as given by 19 \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}=\frac{2}{\sqrt{\pi\:}}C\:\sqrt{{D}_{L}}{\left(\frac{\epsilon\:\rho\:}{K}\right)}^{\frac{1}{2(1+n)}}$$\end{document} Here C was taken as 0.15 . The interfacial area available for mass transfer between phases was calculated as given in Eq. ( ). Here, K and n refers to the consistency and flow behavior index respectively. This equation was incorporated in Fluent using a custom field function.
Plant cells are exposed to shear stress based on its relative size to the Kolmogorov length scale. The Kolmogorov length ( \documentclass[12pt]{minimal}
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\begin{document}$$\:{\tau\:}_{t}=\mu\:{\left(\frac{\epsilon\:}{\upsilon\:}\right)}^{0.5}$$\end{document} Unlike microbial and mammalian cells, plant cells tend to form aggregates and if the aggregate size is larger than \documentclass[12pt]{minimal}
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\begin{document}$$\:{\eta\:}_{k}$$\end{document} , potentially ranging from 0.1 to 2 mm in diameter , the cells are subjected to shear due to velocity differences across the diameter of the cell aggregate. This shear stress can be calculated as given in the following Eq. ( ) 21 \documentclass[12pt]{minimal}
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\begin{document}$$\:{d}_{cell}$$\end{document} refers to the diameter of the cell aggregate. These equations were incorporated in Fluent using a custom field function.
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\begin{document}$$\:{k}_{L}a$$\end{document} for setric impeller was experimentally determined using dynamic gassing in method . Briefly, the bioreactor (3.1 L) with setric impeller was autoclaved with 2.4 L working volume of water and connected to the DO sensor for polarization. After cooling, the bioreactor was aerated to constant oxygen concentration at 125 rpm and 2 vvm. One point calibration at 100% was performed after the saturation was sufficiently reached. The bioreactor was then stripped off oxygen completely by purging nitrogen gas. Once the dissolved oxygen concentration reached less than 2%, filtered compressed air was sparged in the reactor at the simulated operating conditions until steady state saturation was reached. The measurements of dissolved oxygen were recorded as a function of time using a polographic oxygen sensor (Applikon Biotechnology B.V, Netherlands). The probe response time of the O 2 sensor used in this study was 5 s which was significantly less than 1/ k L a (689 s). Therefore, the effect of the delay in the O 2 sensor on the measurement was neglected – . To calculate the rate of oxygen transfer from gas to liquid, the mass balance for the dissolved oxygen in the bioreactor was considered and is given by: 22 \documentclass[12pt]{minimal}
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V. odorata cell suspension V. odorata VOP-4 callus was previously established by Narayani et al. and was maintained by periodic subculturing. The cell suspension culture was developed as described by Babu and Srivastava . Briefly, the maintained callus (6 gDWL -1 ) was suspended in 50 mL woody plant medium (Himedia Laboratories) with 3% (w/v) sucrose and 3 mg L − 1 of 2,4-dichlorophenoxy acetic acid at an initial pH of 5.8. The cells were grown in an orbital shaker in conical flasks for 14 days at 23℃ with a photoperiod of 16/8 h light/dark cycle. Further, the cells were filtered using a Buchner funnel to obtain a synchronous fine cell suspension which was used as inoculum for cultivation of V. odorata in bioreactors . In order to bring the CFD model closer to reality, the rheological parameters of the cell suspension were characterised experimentally. V. odorata cell suspension was subjected to varying shear rates ( \documentclass[12pt]{minimal}
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\begin{document}$$\:\dot{\gamma\:}$$\end{document} ) from 0.0095 to 1000 s − 1 to determine the corresponding shear stress \documentclass[12pt]{minimal}
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\begin{document}$$\:\left(\tau\:\right)$$\end{document} using the rheometer AntonPaar MCR502 at 25℃. The flow behavior (n) and consistency index (K) were determined correlated by the Ostwald de Waele equation given by 23 \documentclass[12pt]{minimal}
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\begin{document}$$\:\tau\:=K{\dot{\gamma\:}}^{n}$$\end{document} The experiment was repeated at n = 5 and the data is presented as mean \documentclass[12pt]{minimal}
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\begin{document}$$\:\pm\:$$\end{document} standard error. The experimentally determined rheological parameters of V. odorata presented in Table was used to model the liquid properties in the CFD simulation. With a flow behavior index less than 1, V. odorata cell suspension was found to be pseudoplastic in nature. This characteristic is similar to other plant cell species which also exhibit pseudoplastic behaviour – . The non-Newtonian behavior of plant cells is generally attributed to cell elongation in suspension and the ability of plant cells to grow in high cell densities due to its comparatively lower oxygen demand . Further, in order to obtain the average cell aggregate size of V. odorata in suspension, 20 \documentclass[12pt]{minimal}
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\begin{document}$$\:\mu\:$$\end{document} L of the suspension was pipetted using cut tips onto a glass slide and was observed under an Olympus IX83 inverted fluorescence microscope. The images were then processed using the software ImageJ to determine the range and average cell aggregate size, tabulated in Table .
CFD model verification and validation The CFD model for the air-water system was first verified and validated as the steady state results of this simulation was used to initiate the air- V. odorata cell suspension system. It was ascertained that the residuals of all the governing equations decreased below an order of 10 −5 , and the monitored parameters, including the volume averaged velocity, energy dissipation rate and k L a achieved steady state (supplementary Fig. S2). Additionally, the mass conservation of the inlet and the outlet air flow rate was confirmed at the sparger inlet and degassing boundary. Since the multiple reference frame method has been used as the boundary condition for the CFD simulation, rather than actual movement of the impeller, the impeller tip speed from the CFD model was verified with theoretical tip speed for all three impellers. Theoretical tip speed of the impellers were calculated to be 0.2 ms −1 from the equation \documentclass[12pt]{minimal}
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\begin{document}$$\:{u}_{tip}=\:\pi\:\:.\:N\:{d}_{I}$$\end{document} , and the maximum liquid velocity from the CFD simulation at the impeller was found to be 0.212, 0.212, 0.195 ms − 1 for setric, marine and Rushton impeller, respectively which is considerably close to the theoretical value with an error of less than 6%. The CFD model was then verified with the literature reported ungassed power number for Rushton impeller as the correlation between impeller Reynolds number and the corresponding power number is well-established for the air-water system . The Reynolds number of 3000 calculated from Eq. ( ) corresponded to a power number of 4.5 and the power number estimated from the present CFD simulation was found to be 3.17. The error of 30% could be justified by the use of 4 baffles in the experimental study in contrast to 3 used in this study. Further, the CFD predicted \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}a\:$$\end{document} in the air-water simulation was validated with experimentally determined \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}a$$\end{document} at an agitation rate of 85 rpm and aeration rate of 0.2 vvm for setric impeller. A less than 4% error in k L a was found between the experimental and numerical data for the air-water system as shown in Table , confirming the validity of the model for further analysis. To validate the air-non-Newtonian system, the \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}a$$\end{document} determined from CFD simulation was validated using the literature reported experimental \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}a$$\end{document} at an agitation rate of 125 rpm and aeration rate of 0.2 vvm for setric impeller . It was observed that CFD predicted k L a had an error of less than 22% compared to the experimental data for the air-plant cell suspension system as shown in Table . The validated CFD model was then used for analyzing the impact of using different impellers on the fluid dynamics, oxygen mass transfer and shear in the bioreactor to rationally choose the suitable impeller for the cultivation of the model system V. odorata without performing hit and trial experiments. Effect of impeller design on liquid dynamics in stirred bioreactor With viscous plant cell suspension cultures, ineffective mixing can lead to development of dead zones which can hamper effective nutrient availability which is undesirable . Thus, for plant cells, the mixing efficiency of the impeller is assessed by the dead zone volume within the bioreactor in this study. The fluid flow patterns obtained by the effect of three different impellers in the stirred bioreactor in the air-plant cell suspension systems can be observed in the contour/velocity plots in Fig. . A dead zone in the bioreactor can be defined as the regions where the liquid velocity is less than 5% of the impeller tip speed . Based on this definition, the blue regions in Fig. , with velocity magnitudes below 0.011 ms −1 can be interpreted as the dead zones. In all three impeller configurations, it can be observed that the change in rheology from Newtonian (supplementary Fig. S3) to pseudoplastic (Fig. ) in the presence of plant cells has decreased the impeller mixing efficiency leading to increase in dead zones. The fluid in the setric impeller configuration is pushed axially downward and forms a recirculation loop towards the impeller region demonstrating that the impeller has predominantly downward pumping axial flow (supplementary Fig. S3). It is interesting to note that the fluid flow pattern shifts from fully axial (in air-water (supplementary Fig. S3)) to a combination of axial and radial (in air- V. odorata (Fig. (a)) which is in line with previous reports that axial impellers tend to show radial behavior when agitating highly viscous non-Newtonian fluids . The same can be observed by the radial increase in the impeller cavern in the axial marine impeller configuration ((Fig. (b)). However, the marine impeller pumps the fluid upward in contrast to the downward pumping setric impeller which is in line with experimental observations of Afedzi et al. . The simulations of Rushton impeller demonstrated the expected radial profile of the fluid movement (Fig. (c)) and the characteristic formation of trailing vortices behind the flat blade of the impeller (Fig. (f)) . It is critical to prevent plant cell aggregates from settling down with gravity as that could eventually lead to necrosis due to insufficient nutrients and oxygen during cultivation in bioreactors , . In this regard, it is critical to have good fluid movement in the regions below the impeller devoid of dead zones. In the presence of plant cells, it can be observed that setric impeller is able to facilitate good velocity magnitudes up to 0.02 ms −1 (10% of the tip speed) in the bottom plane, 20 mm from the base of the reactor (Fig. (d)). In contrast, at this agitation and aeration rate, both marine and Rushton impeller facilitate only 0.0056 ms −1 (less than 3% of the impeller tip speed) at the bottom plane (Fig. (e) and (f)) leading to negligible fluid movement. At the plane above the impeller (150 mm from the base of the bioreactor) the liquid is discharged after encountering the liquid surface, on to the walls and recirculates in two loops in each side of the vessel axially from top to bottom. This second recirculation loop that moves the fluid upward, primarily directed due to the sparged air is almost similar in all three impellers as the aeration rate is constant among the three cases. At the top plane, therefore all three impellers facilitate an average velocity magnitude of 0.03 ms −1 (15–17% of impeller tip speed) (Fig. (d), (e) and (f)) indicating the potential for good fluid movement for the plant cells. At the plane across the impeller, (65 mm from the base of the bioreactor) it is evident that the setric impeller exhibits a higher average velocity magnitude compared to the Rushton and marine impellers (Fig. (d), (e) and (f)), with fluid movement sweeping well across until the bioreactor walls. In contrast, both Rushton and marine exhibit localized mixing only in the vicinity of the impeller. This could lead to adherence of plant cells on the walls due to lack of movement, in addition to cell settling which is highly unfavorable . To further substantiate this observation across the entire volume of the reactor, in addition to analyzing at three planes, the liquid dead zone volume in the entire vessel was calculated. It was observed that Rushton impeller had the highest percentage of dead zone liquid volume (38.95%) compared to marine impeller (31.19%) and setric impeller (29.01%) as observed in Fig. (a). Further, the dead zone volume at different regions of the bioreactor was evaluated by dividing the bioreactor into four compartments as illustrated in Fig. (b). Figure (c) demonstrates that at the bottom setric impeller facilitated 56% lesser dead zone volume than Rushton and marine. Similarly, below the impeller, setric facilitated 74% and 71% lesser dead zone volume than Rushton and marine respectively. At the top of the reactor, all three impellers offered effective mixing with less than 15% dead zone volume similar to the plane wise analysis. These results indicated that the observations at the three planes are true for the behavior in the corresponding compartments as well. Though both Rushton and marine impellers are able to facilitate good mixing in air-water system throughout the bioreactor, the dead zones have increased substantially in presence of plant cells particularly below the impeller. It is crucial to prevent cell settling and wall growth when designing bioreactors suitable for plant cells, and hence this comparative analysis from the CFD study indicates that the setric impeller configuration facilitates effective mixing in the reactor bottom and sufficient mixing in the top regions, promoting efficient cell movement throughout the reactor and making it a suitable choice for cultivation of V. odorata cell suspension culture. Effect of impeller design on liquid velocity distribution in stirred bioreactor To further compare the hydrodynamic patterns among the three impellers during the agitation of V. odorata cell suspension, the distribution of liquid velocity components on a line at three different spatial locations in the reactor were studied, including one below the impeller (20 mm from base of the bioreactor) (Fig. (a)), second at the impeller center (65 mm from base of the bioreactor) (Fig. (b)) and third at the top of the impeller region (150 mm from base of the bioreactor) (Fig. (c)). The axial velocity, component of fluid parallel to the length of the bioreactor demonstrates how effectively the cells circulate through the bioreactor, crucial for adequate oxygen and nutrient availability. This is particularly important for plant cell aggregates due to their relatively higher settling velocity. In this regard, at the reactor bottom, setric impeller could facilitate a maximum axial velocity of 0.022 ms −1 and a radial velocity of 0.024 ms −1 which is close to four times higher axial and radial velocities than Rushton and marine impeller (Fig. (d) and (e)). It is important to note that the magnitudes of axial and radial velocities exhibited by the setric impeller is almost similar to its average bottom velocity magnitude (0.023 ms −1 ) and setric impeller offers axial liquid movement near the bioreactor walls and radial movement in the bottom center. This gives an insight that the fluid pushed axially downwards from the impeller radially moves towards the bioreactor wall before recirculating back to the impeller region. This fluid movement facilitated by setric impeller is clearly favorable for preventing plant cells from settling. The primary behavior of the impeller can be assessed by examining the axial and radial velocities at the impeller center , which can provide insight into the nature of fluid movement in different vessel geometries, scales, or when multiple impellers are utilized. Figure (f) show the axial velocity distributions for the three different impellers at the impeller region. The model indicated that the setric impeller offered a maximum of 1.8 times higher axial velocity magnitude (0.167 ms − 1 ) than Rushton and similar magnitudes to marine impeller in the upward direction. On the other hand, in the downward direction setric impeller exhibits a maximum axial velocity magnitude of 0.168 ms −1 (equivalent to the upwards axial velocity magnitude), which is 14 times higher than the maximum axial velocity magnitude of Rushton and 10 times higher than that of the marine impeller. It is evident that at the impeller region, setric impeller moves the fluid in both up and downward direction facilitating good mixing in contrast to Rushton and marine impellers which moves the fluid only towards the top. On the other hand, the radial velocity magnitude in Rushton impeller (0.074 ms −1 ) was up to 2 times and 4 times higher than marine and setric respectively which is as expected as it is well known that Rushton impeller exhibits radial behavior predominantly (Fig. (g)). But it is interesting to note that the magnitudes of radial velocity in Rushton impeller is 2.2 times lower than that of axial velocity (0.167 ms − 1 ) in setric impeller at the impeller region which indicates stronger fluid movement in the impeller region with setric configuration. The radial velocity in marine impeller exhibits similar fluid movement to setric impeller, with two times higher magnitudes than setric near the impeller. But towards the bioreactor walls, marine impeller demonstrates negligible radial velocity. This confirms that at the impeller region, the primary motion of the fluid can be considered axial for setric impeller. It is noteworthy that the marine impeller exhibits comparable axial velocity magnitudes to setric solely in the upward direction, whereas the setric impeller facilitates fluid movement axially in both upward and downward directions. It is reported that axial impellers are preferred over radial impellers for suspending plant cells in general and non-Newtonian fluids . The observations from this CFD study substantiate that radial impellers cannot recirculate fluid effectively at the bottom, and consequently, axial impellers are preferred. Furthermore, it can be indicated that downward-pumping axial impellers are more suitable, as it can be seen that upward-pumping marine impellers cannot recirculate fluid sufficiently towards the bottom as well. Analyzing the velocity component distributions at a line in the top region (Y = 150 mm), it was observed that the maximum axial velocities were 50 times higher in the upward direction for the Rushton and marine impeller than the setric impeller configuration (0.0033 ms − 1 ) which had negligible axial velocity ((Fig. (h)). This could be attributed to the liquid movement majorly directed towards the surface by the sparged air without radial movement in the Rushton and marine impeller configurations. This observation indicates that the higher velocity magnitudes in the top region, as depicted in Fig. (e) for marine and Fig. (f) for Rushton impeller, are primarily axial. Conversely, the setric impeller facilitated up to a maximum radial velocity of 0.179 ms − 1 at the top which was 16 times higher than Rushton and marine impellers (Fig. (i)). These results indicate that although the average velocity magnitudes are lower at the reactor top for the setric impeller, as observed in Fig. (d), the radial velocities are higher than Rushton and marine impellers, potentially providing effective recirculation for the plant cells as well as oxygen distribution. Notably, in all three locations examined, the axial component of the fluid movement is predominantly towards the top for Rushton and marine impellers, whereas the setric impeller facilitates a balance between the upward and downward movement, indicating effective mixing. These studies indicated that setric impeller is predominantly a downward pumping axial impeller which is found to be better than Rushton and marine impellers in facilitating cell lift. This is especially critical at relatively lower agitation rates which are typically employed for plant cell cultivations to maintain cell viability . Effect of impeller design on the volumetric oxygen mass transfer coefficient and shear stress in stirred bioreactor Though the model indicated that setric impeller facilitates better mixing at the reactor bottom making it a suitable choice for plant cell suspension cultures, it is important to additionally consider and compare oxygen mass transfer and shear environment in the bioreactor. The average k L a and shear stress in the bioreactor in presence of the three impellers was compared keeping the average liquid velocity magnitude in the reactor bottom constant as this parameter cannot be compromised. The average bottom velocity in setric impeller at 85 rpm was 0.02 m s −1 which was taken as the benchmark. The agitation rate at which bottom velocity magnitude in Rushton and marine impellers were similar (with less than 15% error) to setric at 85 rpm was identified by running the bioreactor simulations at increasing rpm from 100 to 350 rpm. It was observed that at 330 rpm, the average bottom velocity in Rushton impeller was 0.0214 m s −1 and at 300 rpm, the average bottom velocity in marine impeller was 0.0204 m s −1 as tabulated in Table . At this agitation rate and constant aeration of 0.2 vvm, the oxygen mass transfer and the shear stress among the three impellers were compared in the following sections. Effect of impeller design on the volumetric oxygen mass transfer coefficient at constant average velocity magnitude at reactor bottom Oxygen mass transfer is generally considered as one of the crucial limiting factors in aerated fermentations. But plant cells require relatively less oxygen than microbial cultures as they are slow growing and have low specific oxygen demand . The rate of oxygen mass transfer from gas bubbles to the liquid is dependent on concentration gradient of oxygen (difference between the maximum soluble oxygen concentration in the liquid and the actual oxygen concentration in the bulk liquid) and k L a . Among the two, k L a is the parameter which is controllable. It is dependent on impeller type, aeration and agitation rate and therefore it is important to compare the same between the three impellers. In this study, the model indicated that at the similar average velocity magnitude at the bottom, it was observed that Rushton impeller demonstrated 1.8 times better oxygen mass transfer than setric (1.37 h − 1 ) and marine impeller (1.32 h −1 ) as seen in Fig. (a). This can be justified by the known ability of radial Rushton impellers to disperse bubbles efficiently, leading to better interfacial area and better k L a . The marine impeller had a similar magnitude of k L a to setric impeller even at 300 rpm due to a similar interfacial area in spite of increase in the turbulence dissipation rate. The model hence indicates that in terms of oxygen mass transfer, Rushton impeller is the most suitable among the three impellers. However, there is generally a tradeoff between better oxygen mass transfer and low shear in bioreactor design. Since both parameters are functions of energy dissipation rates, when the impeller dissipates more energy, with high shear at the impeller, it leads to better bubble dispersion and better k L a. But since plant cells are shear sensitive and have much lower oxygen demand than microbial cells, it is more crucial to identify the impeller which offers lower shear environment than better oxygen mass transfer for maximum plant cell biomass productivity. Effect of impeller design on the shear environment in the bioreactor at constant average velocity magnitude at reactor bottom The two approaches generally adopted to determine shear environment in the bioreactor: shear due to velocity gradients ( τ t ) and shear due to aggregate size ( τ d ) have been employed in this study. The shear environment among the three impellers was evaluated at comparable average velocity magnitude at the bottom of the reactor, similar to the approach used for oxygen mass transfer assessment. Figure (b) illustrates the average magnitudes of τ t and τ d . It can be observed that τ t , in setric impeller (0.66 Pa) is 1.4 times lower than that of Rushton and marine impellers. On the other hand, τ d exhibited by setric impeller (0.22 Pa) is close to 1.9 times lower than Rushton and marine impeller. The Kolmogorov length scale is the determining factor in whether a cell/cell cluster experiences τ t or τ d in the flow field, with the estimated range varying between 0.046 and 9.6 mm in this system. The corresponding ranges for each impeller configuration has been tabulated in Table . In this study, it was estimated that the diameter of V. odorata cell aggregates ranges between 0.056 and 0.802 mm during inoculation (Table ) and therefore cell aggregates in this system can experience both τ t or τ d depending on their size. However, comparing the mean cell aggregate size of V. odorata (0.36 mm) with the mean Kolmogorov length scales (Table ) in this system, it can be observed that cell aggregates could most likely experience τ t in the flow field. Therefore, it can be indicated from the model that choosing an impeller with lower τ t is critical for V. odorata and therefore setric impeller can be a favorable choice over the other two impellers.
The CFD model for the air-water system was first verified and validated as the steady state results of this simulation was used to initiate the air- V. odorata cell suspension system. It was ascertained that the residuals of all the governing equations decreased below an order of 10 −5 , and the monitored parameters, including the volume averaged velocity, energy dissipation rate and k L a achieved steady state (supplementary Fig. S2). Additionally, the mass conservation of the inlet and the outlet air flow rate was confirmed at the sparger inlet and degassing boundary. Since the multiple reference frame method has been used as the boundary condition for the CFD simulation, rather than actual movement of the impeller, the impeller tip speed from the CFD model was verified with theoretical tip speed for all three impellers. Theoretical tip speed of the impellers were calculated to be 0.2 ms −1 from the equation \documentclass[12pt]{minimal}
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\begin{document}$$\:{u}_{tip}=\:\pi\:\:.\:N\:{d}_{I}$$\end{document} , and the maximum liquid velocity from the CFD simulation at the impeller was found to be 0.212, 0.212, 0.195 ms − 1 for setric, marine and Rushton impeller, respectively which is considerably close to the theoretical value with an error of less than 6%. The CFD model was then verified with the literature reported ungassed power number for Rushton impeller as the correlation between impeller Reynolds number and the corresponding power number is well-established for the air-water system . The Reynolds number of 3000 calculated from Eq. ( ) corresponded to a power number of 4.5 and the power number estimated from the present CFD simulation was found to be 3.17. The error of 30% could be justified by the use of 4 baffles in the experimental study in contrast to 3 used in this study. Further, the CFD predicted \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}a$$\end{document} at an agitation rate of 85 rpm and aeration rate of 0.2 vvm for setric impeller. A less than 4% error in k L a was found between the experimental and numerical data for the air-water system as shown in Table , confirming the validity of the model for further analysis. To validate the air-non-Newtonian system, the \documentclass[12pt]{minimal}
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\begin{document}$$\:{k}_{L}a$$\end{document} at an agitation rate of 125 rpm and aeration rate of 0.2 vvm for setric impeller . It was observed that CFD predicted k L a had an error of less than 22% compared to the experimental data for the air-plant cell suspension system as shown in Table . The validated CFD model was then used for analyzing the impact of using different impellers on the fluid dynamics, oxygen mass transfer and shear in the bioreactor to rationally choose the suitable impeller for the cultivation of the model system V. odorata without performing hit and trial experiments.
With viscous plant cell suspension cultures, ineffective mixing can lead to development of dead zones which can hamper effective nutrient availability which is undesirable . Thus, for plant cells, the mixing efficiency of the impeller is assessed by the dead zone volume within the bioreactor in this study. The fluid flow patterns obtained by the effect of three different impellers in the stirred bioreactor in the air-plant cell suspension systems can be observed in the contour/velocity plots in Fig. . A dead zone in the bioreactor can be defined as the regions where the liquid velocity is less than 5% of the impeller tip speed . Based on this definition, the blue regions in Fig. , with velocity magnitudes below 0.011 ms −1 can be interpreted as the dead zones. In all three impeller configurations, it can be observed that the change in rheology from Newtonian (supplementary Fig. S3) to pseudoplastic (Fig. ) in the presence of plant cells has decreased the impeller mixing efficiency leading to increase in dead zones. The fluid in the setric impeller configuration is pushed axially downward and forms a recirculation loop towards the impeller region demonstrating that the impeller has predominantly downward pumping axial flow (supplementary Fig. S3). It is interesting to note that the fluid flow pattern shifts from fully axial (in air-water (supplementary Fig. S3)) to a combination of axial and radial (in air- V. odorata (Fig. (a)) which is in line with previous reports that axial impellers tend to show radial behavior when agitating highly viscous non-Newtonian fluids . The same can be observed by the radial increase in the impeller cavern in the axial marine impeller configuration ((Fig. (b)). However, the marine impeller pumps the fluid upward in contrast to the downward pumping setric impeller which is in line with experimental observations of Afedzi et al. . The simulations of Rushton impeller demonstrated the expected radial profile of the fluid movement (Fig. (c)) and the characteristic formation of trailing vortices behind the flat blade of the impeller (Fig. (f)) . It is critical to prevent plant cell aggregates from settling down with gravity as that could eventually lead to necrosis due to insufficient nutrients and oxygen during cultivation in bioreactors , . In this regard, it is critical to have good fluid movement in the regions below the impeller devoid of dead zones. In the presence of plant cells, it can be observed that setric impeller is able to facilitate good velocity magnitudes up to 0.02 ms −1 (10% of the tip speed) in the bottom plane, 20 mm from the base of the reactor (Fig. (d)). In contrast, at this agitation and aeration rate, both marine and Rushton impeller facilitate only 0.0056 ms −1 (less than 3% of the impeller tip speed) at the bottom plane (Fig. (e) and (f)) leading to negligible fluid movement. At the plane above the impeller (150 mm from the base of the bioreactor) the liquid is discharged after encountering the liquid surface, on to the walls and recirculates in two loops in each side of the vessel axially from top to bottom. This second recirculation loop that moves the fluid upward, primarily directed due to the sparged air is almost similar in all three impellers as the aeration rate is constant among the three cases. At the top plane, therefore all three impellers facilitate an average velocity magnitude of 0.03 ms −1 (15–17% of impeller tip speed) (Fig. (d), (e) and (f)) indicating the potential for good fluid movement for the plant cells. At the plane across the impeller, (65 mm from the base of the bioreactor) it is evident that the setric impeller exhibits a higher average velocity magnitude compared to the Rushton and marine impellers (Fig. (d), (e) and (f)), with fluid movement sweeping well across until the bioreactor walls. In contrast, both Rushton and marine exhibit localized mixing only in the vicinity of the impeller. This could lead to adherence of plant cells on the walls due to lack of movement, in addition to cell settling which is highly unfavorable . To further substantiate this observation across the entire volume of the reactor, in addition to analyzing at three planes, the liquid dead zone volume in the entire vessel was calculated. It was observed that Rushton impeller had the highest percentage of dead zone liquid volume (38.95%) compared to marine impeller (31.19%) and setric impeller (29.01%) as observed in Fig. (a). Further, the dead zone volume at different regions of the bioreactor was evaluated by dividing the bioreactor into four compartments as illustrated in Fig. (b). Figure (c) demonstrates that at the bottom setric impeller facilitated 56% lesser dead zone volume than Rushton and marine. Similarly, below the impeller, setric facilitated 74% and 71% lesser dead zone volume than Rushton and marine respectively. At the top of the reactor, all three impellers offered effective mixing with less than 15% dead zone volume similar to the plane wise analysis. These results indicated that the observations at the three planes are true for the behavior in the corresponding compartments as well. Though both Rushton and marine impellers are able to facilitate good mixing in air-water system throughout the bioreactor, the dead zones have increased substantially in presence of plant cells particularly below the impeller. It is crucial to prevent cell settling and wall growth when designing bioreactors suitable for plant cells, and hence this comparative analysis from the CFD study indicates that the setric impeller configuration facilitates effective mixing in the reactor bottom and sufficient mixing in the top regions, promoting efficient cell movement throughout the reactor and making it a suitable choice for cultivation of V. odorata cell suspension culture.
To further compare the hydrodynamic patterns among the three impellers during the agitation of V. odorata cell suspension, the distribution of liquid velocity components on a line at three different spatial locations in the reactor were studied, including one below the impeller (20 mm from base of the bioreactor) (Fig. (a)), second at the impeller center (65 mm from base of the bioreactor) (Fig. (b)) and third at the top of the impeller region (150 mm from base of the bioreactor) (Fig. (c)). The axial velocity, component of fluid parallel to the length of the bioreactor demonstrates how effectively the cells circulate through the bioreactor, crucial for adequate oxygen and nutrient availability. This is particularly important for plant cell aggregates due to their relatively higher settling velocity. In this regard, at the reactor bottom, setric impeller could facilitate a maximum axial velocity of 0.022 ms −1 and a radial velocity of 0.024 ms −1 which is close to four times higher axial and radial velocities than Rushton and marine impeller (Fig. (d) and (e)). It is important to note that the magnitudes of axial and radial velocities exhibited by the setric impeller is almost similar to its average bottom velocity magnitude (0.023 ms −1 ) and setric impeller offers axial liquid movement near the bioreactor walls and radial movement in the bottom center. This gives an insight that the fluid pushed axially downwards from the impeller radially moves towards the bioreactor wall before recirculating back to the impeller region. This fluid movement facilitated by setric impeller is clearly favorable for preventing plant cells from settling. The primary behavior of the impeller can be assessed by examining the axial and radial velocities at the impeller center , which can provide insight into the nature of fluid movement in different vessel geometries, scales, or when multiple impellers are utilized. Figure (f) show the axial velocity distributions for the three different impellers at the impeller region. The model indicated that the setric impeller offered a maximum of 1.8 times higher axial velocity magnitude (0.167 ms − 1 ) than Rushton and similar magnitudes to marine impeller in the upward direction. On the other hand, in the downward direction setric impeller exhibits a maximum axial velocity magnitude of 0.168 ms −1 (equivalent to the upwards axial velocity magnitude), which is 14 times higher than the maximum axial velocity magnitude of Rushton and 10 times higher than that of the marine impeller. It is evident that at the impeller region, setric impeller moves the fluid in both up and downward direction facilitating good mixing in contrast to Rushton and marine impellers which moves the fluid only towards the top. On the other hand, the radial velocity magnitude in Rushton impeller (0.074 ms −1 ) was up to 2 times and 4 times higher than marine and setric respectively which is as expected as it is well known that Rushton impeller exhibits radial behavior predominantly (Fig. (g)). But it is interesting to note that the magnitudes of radial velocity in Rushton impeller is 2.2 times lower than that of axial velocity (0.167 ms − 1 ) in setric impeller at the impeller region which indicates stronger fluid movement in the impeller region with setric configuration. The radial velocity in marine impeller exhibits similar fluid movement to setric impeller, with two times higher magnitudes than setric near the impeller. But towards the bioreactor walls, marine impeller demonstrates negligible radial velocity. This confirms that at the impeller region, the primary motion of the fluid can be considered axial for setric impeller. It is noteworthy that the marine impeller exhibits comparable axial velocity magnitudes to setric solely in the upward direction, whereas the setric impeller facilitates fluid movement axially in both upward and downward directions. It is reported that axial impellers are preferred over radial impellers for suspending plant cells in general and non-Newtonian fluids . The observations from this CFD study substantiate that radial impellers cannot recirculate fluid effectively at the bottom, and consequently, axial impellers are preferred. Furthermore, it can be indicated that downward-pumping axial impellers are more suitable, as it can be seen that upward-pumping marine impellers cannot recirculate fluid sufficiently towards the bottom as well. Analyzing the velocity component distributions at a line in the top region (Y = 150 mm), it was observed that the maximum axial velocities were 50 times higher in the upward direction for the Rushton and marine impeller than the setric impeller configuration (0.0033 ms − 1 ) which had negligible axial velocity ((Fig. (h)). This could be attributed to the liquid movement majorly directed towards the surface by the sparged air without radial movement in the Rushton and marine impeller configurations. This observation indicates that the higher velocity magnitudes in the top region, as depicted in Fig. (e) for marine and Fig. (f) for Rushton impeller, are primarily axial. Conversely, the setric impeller facilitated up to a maximum radial velocity of 0.179 ms − 1 at the top which was 16 times higher than Rushton and marine impellers (Fig. (i)). These results indicate that although the average velocity magnitudes are lower at the reactor top for the setric impeller, as observed in Fig. (d), the radial velocities are higher than Rushton and marine impellers, potentially providing effective recirculation for the plant cells as well as oxygen distribution. Notably, in all three locations examined, the axial component of the fluid movement is predominantly towards the top for Rushton and marine impellers, whereas the setric impeller facilitates a balance between the upward and downward movement, indicating effective mixing. These studies indicated that setric impeller is predominantly a downward pumping axial impeller which is found to be better than Rushton and marine impellers in facilitating cell lift. This is especially critical at relatively lower agitation rates which are typically employed for plant cell cultivations to maintain cell viability .
Though the model indicated that setric impeller facilitates better mixing at the reactor bottom making it a suitable choice for plant cell suspension cultures, it is important to additionally consider and compare oxygen mass transfer and shear environment in the bioreactor. The average k L a and shear stress in the bioreactor in presence of the three impellers was compared keeping the average liquid velocity magnitude in the reactor bottom constant as this parameter cannot be compromised. The average bottom velocity in setric impeller at 85 rpm was 0.02 m s −1 which was taken as the benchmark. The agitation rate at which bottom velocity magnitude in Rushton and marine impellers were similar (with less than 15% error) to setric at 85 rpm was identified by running the bioreactor simulations at increasing rpm from 100 to 350 rpm. It was observed that at 330 rpm, the average bottom velocity in Rushton impeller was 0.0214 m s −1 and at 300 rpm, the average bottom velocity in marine impeller was 0.0204 m s −1 as tabulated in Table . At this agitation rate and constant aeration of 0.2 vvm, the oxygen mass transfer and the shear stress among the three impellers were compared in the following sections. Effect of impeller design on the volumetric oxygen mass transfer coefficient at constant average velocity magnitude at reactor bottom Oxygen mass transfer is generally considered as one of the crucial limiting factors in aerated fermentations. But plant cells require relatively less oxygen than microbial cultures as they are slow growing and have low specific oxygen demand . The rate of oxygen mass transfer from gas bubbles to the liquid is dependent on concentration gradient of oxygen (difference between the maximum soluble oxygen concentration in the liquid and the actual oxygen concentration in the bulk liquid) and k L a . Among the two, k L a is the parameter which is controllable. It is dependent on impeller type, aeration and agitation rate and therefore it is important to compare the same between the three impellers. In this study, the model indicated that at the similar average velocity magnitude at the bottom, it was observed that Rushton impeller demonstrated 1.8 times better oxygen mass transfer than setric (1.37 h − 1 ) and marine impeller (1.32 h −1 ) as seen in Fig. (a). This can be justified by the known ability of radial Rushton impellers to disperse bubbles efficiently, leading to better interfacial area and better k L a . The marine impeller had a similar magnitude of k L a to setric impeller even at 300 rpm due to a similar interfacial area in spite of increase in the turbulence dissipation rate. The model hence indicates that in terms of oxygen mass transfer, Rushton impeller is the most suitable among the three impellers. However, there is generally a tradeoff between better oxygen mass transfer and low shear in bioreactor design. Since both parameters are functions of energy dissipation rates, when the impeller dissipates more energy, with high shear at the impeller, it leads to better bubble dispersion and better k L a. But since plant cells are shear sensitive and have much lower oxygen demand than microbial cells, it is more crucial to identify the impeller which offers lower shear environment than better oxygen mass transfer for maximum plant cell biomass productivity. Effect of impeller design on the shear environment in the bioreactor at constant average velocity magnitude at reactor bottom The two approaches generally adopted to determine shear environment in the bioreactor: shear due to velocity gradients ( τ t ) and shear due to aggregate size ( τ d ) have been employed in this study. The shear environment among the three impellers was evaluated at comparable average velocity magnitude at the bottom of the reactor, similar to the approach used for oxygen mass transfer assessment. Figure (b) illustrates the average magnitudes of τ t and τ d . It can be observed that τ t , in setric impeller (0.66 Pa) is 1.4 times lower than that of Rushton and marine impellers. On the other hand, τ d exhibited by setric impeller (0.22 Pa) is close to 1.9 times lower than Rushton and marine impeller. The Kolmogorov length scale is the determining factor in whether a cell/cell cluster experiences τ t or τ d in the flow field, with the estimated range varying between 0.046 and 9.6 mm in this system. The corresponding ranges for each impeller configuration has been tabulated in Table . In this study, it was estimated that the diameter of V. odorata cell aggregates ranges between 0.056 and 0.802 mm during inoculation (Table ) and therefore cell aggregates in this system can experience both τ t or τ d depending on their size. However, comparing the mean cell aggregate size of V. odorata (0.36 mm) with the mean Kolmogorov length scales (Table ) in this system, it can be observed that cell aggregates could most likely experience τ t in the flow field. Therefore, it can be indicated from the model that choosing an impeller with lower τ t is critical for V. odorata and therefore setric impeller can be a favorable choice over the other two impellers.
Oxygen mass transfer is generally considered as one of the crucial limiting factors in aerated fermentations. But plant cells require relatively less oxygen than microbial cultures as they are slow growing and have low specific oxygen demand . The rate of oxygen mass transfer from gas bubbles to the liquid is dependent on concentration gradient of oxygen (difference between the maximum soluble oxygen concentration in the liquid and the actual oxygen concentration in the bulk liquid) and k L a . Among the two, k L a is the parameter which is controllable. It is dependent on impeller type, aeration and agitation rate and therefore it is important to compare the same between the three impellers. In this study, the model indicated that at the similar average velocity magnitude at the bottom, it was observed that Rushton impeller demonstrated 1.8 times better oxygen mass transfer than setric (1.37 h − 1 ) and marine impeller (1.32 h −1 ) as seen in Fig. (a). This can be justified by the known ability of radial Rushton impellers to disperse bubbles efficiently, leading to better interfacial area and better k L a . The marine impeller had a similar magnitude of k L a to setric impeller even at 300 rpm due to a similar interfacial area in spite of increase in the turbulence dissipation rate. The model hence indicates that in terms of oxygen mass transfer, Rushton impeller is the most suitable among the three impellers. However, there is generally a tradeoff between better oxygen mass transfer and low shear in bioreactor design. Since both parameters are functions of energy dissipation rates, when the impeller dissipates more energy, with high shear at the impeller, it leads to better bubble dispersion and better k L a. But since plant cells are shear sensitive and have much lower oxygen demand than microbial cells, it is more crucial to identify the impeller which offers lower shear environment than better oxygen mass transfer for maximum plant cell biomass productivity.
The two approaches generally adopted to determine shear environment in the bioreactor: shear due to velocity gradients ( τ t ) and shear due to aggregate size ( τ d ) have been employed in this study. The shear environment among the three impellers was evaluated at comparable average velocity magnitude at the bottom of the reactor, similar to the approach used for oxygen mass transfer assessment. Figure (b) illustrates the average magnitudes of τ t and τ d . It can be observed that τ t , in setric impeller (0.66 Pa) is 1.4 times lower than that of Rushton and marine impellers. On the other hand, τ d exhibited by setric impeller (0.22 Pa) is close to 1.9 times lower than Rushton and marine impeller. The Kolmogorov length scale is the determining factor in whether a cell/cell cluster experiences τ t or τ d in the flow field, with the estimated range varying between 0.046 and 9.6 mm in this system. The corresponding ranges for each impeller configuration has been tabulated in Table . In this study, it was estimated that the diameter of V. odorata cell aggregates ranges between 0.056 and 0.802 mm during inoculation (Table ) and therefore cell aggregates in this system can experience both τ t or τ d depending on their size. However, comparing the mean cell aggregate size of V. odorata (0.36 mm) with the mean Kolmogorov length scales (Table ) in this system, it can be observed that cell aggregates could most likely experience τ t in the flow field. Therefore, it can be indicated from the model that choosing an impeller with lower τ t is critical for V. odorata and therefore setric impeller can be a favorable choice over the other two impellers.
There is a need for rational design of bioreactors for plant cell bioreactors rather than adopting existing conventional designs through hit and trial approaches, saving time and resources. In this study, the hydrodynamics, mixing and mass transfer in stirred bioreactors using setric impeller has been characterized using CFD and compared with commonly used axial marine and radial Rushton impeller at relatively lower agitation and aeration rates generally used for plant cell cultivations with a fluid exhibiting plant cell characteristics for the first time. The CFD analysis indicated that setric impeller exhibited considerable downward pumping of fluid and facilitated higher velocity magnitudes below the impeller region than Rushton and marine impeller. These characteristics of setric impeller can prevent cell settling, which is commonly observed in plant cell cultivation as plant cells tend to grow as aggregates. Further, the model indicated that at similar velocity magnitudes at the reactor bottom, setric impeller exhibits lower average shear stress. Based on the fact that lower shear environment is preferred to enhanced oxygen mass transfer for plant cells, the CFD analysis was able to indicate that setric impeller facilitates low shear environment with good mixing, making it a better choice vis a vis the commonly used Rushton turbines and marine impellers for shear sensitive plant cell cultivations. This investigation was substantiated by the choice of setric impeller in a previous experimental study for mixing high density V. odorata cell cultivation in a stirred bioreactor where setric impeller was able to facilitate shake flask reproducible biomass productivity in the bioreactor at the same operating conditions . Further, the cell aggregate size and apparent viscosity can increase during the log phase during cultivation and the agitation rate may need to be varied to achieve the same mixing conditions. To achieve the same, this developed model can be further extended for rational optimization of the operating conditions during the cultivation period and to improve biomass productivity for scale up of plant cell cultivation from lab to pilot scale.
Below is the link to the electronic supplementary material. Supplementary Material 1
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Clinicopathological discrepancies in the diagnoses of childhood causes of death in the CHAMPS network: An analysis of antemortem diagnostic inaccuracies | 88079e49-8212-49ce-8fee-c4588f8503c2 | 11409330 | Forensic Medicine[mh] | A significant proportion (58%–77%) of deaths among young children in sub-Saharan Africa and South Asia are preventable with timely access to high-quality clinical care, which includes accurate diagnoses. Using data from 881 deaths among infants and children aged 1–59 months from the 10 most common causes determined through extensive postmortem examinations in 7 countries, we documented antemortem diagnostic errors in 39.5% of cases, with 82.3% of those diagnostic errors being considered major. To further reduce childhood mortality in resource-limited settings, there is an urgent need to improve antemortem diagnostic capability. Enhancing antemortem diagnostic capacity is a crucial step towards directing appropriate clinical care to children in regions with high childhood mortality rates in sub-Saharan Africa and South Asia. The comparison of common antemortem clinical diagnostic errors compared with postmortem determined causes of death identifies the disease processes in most need of improved diagnostic approaches. Despite more than a 50% reduction in childhood mortality rates since the 1990s, an estimated 5.2 million deaths occurred among children aged <5 years in 2019. Over 80% of deaths among children aged <5 years occur in sub-Saharan Africa and South Asia. Disparate rates in childhood mortality are attributable, in part, to high rates of childhood malnutrition, infections, poverty, and poor access to the health system, which are common in sub-Saharan Africa and South Asia. In addition to these factors that contribute to high rates of childhood mortality in these regions, prior studies suggest that as much as 58%–77% of childhood deaths in resource-limited settings could have potentially been averted with more timely access to high-quality clinical care. Limited access to laboratory and radiographic diagnostic tests, resulting in inaccurate diagnoses and subsequent inappropriate patient treatment contribute to high rates of childhood mortality in sub-Saharan Africa and South Asia. In a previous study, when antemortem and postmortem diagnoses aligned, clinician adherence to clinical care recommendations was higher. Thus, making correct diagnoses is key to improving clinical care in resource-limited settings with high rates of childhood mortality. A comparison of antemortem clinical diagnoses to postmortem-determined causes of death may help identify the most relevant diagnostic improvements to potentially reduce deaths among children aged <5 years. Previous studies suggest that rates of discrepancies in antemortem clinical diagnoses and postmortem diagnoses range from 20% of childhood deaths in the USA and Chile to 38% of maternal deaths in Mozambique and 40% of deceased adults in South America, using complete diagnostic autopsy as the reference standard. However, studies on the accuracy of antemortem diagnoses among young children are lacking in regions with high rates of childhood mortality in sub-Saharan Africa and South Asia. Our objective was to evaluate antemortem clinical diagnostic accuracy compared with causes of death determined by postmortem investigation among infants and children aged 1–59 months who died in seven sites in sub-Saharan Africa and South Asia participating in Child Health and Mortality Prevention Surveillance (CHAMPS). Moreover, we aimed to describe factors associated with major (ie, an accurate diagnosis could have impacted survival) antemortem diagnostic errors compared with postmortem causes of death. Such an understanding is a necessary step towards health systems’ strengthening and allocating the most crucial diagnostic resources to correctly diagnose children, improve clinical outcomes, and potentially reduce childhood mortality. Study design We conducted a descriptive study and analysed data from seven sites in sub-Saharan Africa and Bangladesh participating in the CHAMPS Network. CHAMPS is conducting prospective mortality surveillance in healthcare centres and communities in areas of high mortality among children aged <5 years (ie, >50 per 1000 live births). Patient and public involvement The development of the research question was informed by the large burden child mortality worldwide. Patients were not involved in the design, recruitment or conduct of the study. Results of this study will be made publicly available through publication where study participants may access them. Patients were not advisers in this study. Study setting The CHAMPS Network was established in 2015 and includes sites in Baliakandi and Faridpur, Bangladesh; Kersa, Haramaya and Harar, Ethiopia; Kisumu and Siaya, Kenya; Bamako, Mali; Manhiça and Quelimane, Mozambique; Makeni and Bo, Sierra Leone; and Soweto, South Africa. These regions were selected because they have high rates of mortality among children aged <5 years. CHAMPS employs postmortem pathological and microbiological evaluations to ascertain causes of child deaths, with the aim of preventing deaths by informing policies and programmes. Population and inclusion and exclusion criteria Our study population included all infants and children aged 1–59 months who died and were enrolled in CHAMPS from December 2016 to February 2022 and had documented antemortem clinical diagnoses. CHAMPS enrols stillbirths and deaths among neonates, infants and children that occur in health facilities or in the community. Here, we focused our analyses on deceased infants and children (1) with identifiable antemortem clinical diagnoses within their clinical records, (2) with consenting caregivers, (3) who underwent minimally invasive tissue sampling (MITS), and had adequate samples to determine causes of death and (4) whose results were reviewed by expert panels to determine postmortem pathology-based diagnoses. We excluded cases without clinical records and those who died before presentation to a health facility because antemortem clinical diagnoses could not be determined for these deaths. Study procedures Surveillance for stillbirths and child deaths occurring in healthcare facilities and the community is performed by CHAMPS staff at each site. CHAMPS enrols cases within 24 hours of death for the MITS procedure. Within this time frame, caregivers of deceased neonates, infants and children are informed about the CHAMPS data collection process and approached for potential enrolment in the study. CHAMPS procedures include the collection of demographic information, clinical record review, verbal autopsy, and extensive postmortem tissue sampling and testing. Briefly, MITS consists of collection of tissue samples from brain, lungs, liver, and heart using biopsy needles, in addition to samples of blood and cerebrospinal fluid using syringes. Moreover, nasopharyngeal and rectal swabs are collected. MITS serves as a proxy for complete diagnostic autopsy and has demonstrated high concordance, for all age groups, with complete diagnostic autopsy. All collected samples undergo histopathological and microbiological analyses including H&E staining, targeted histochemistry, and immunohistochemistry dictated by the morphological findings and molecular pathogen identification through extensive PCR testing for 126 different pathogens (TaqMan array; ThermoFisher Scientific, Waltham, Massachusetts, USA). Tissues and body fluids are sent for culture. Blood samples also undergo HIV PCR testing, malaria thick and thin smears, and TaqMan array PCR testing (including the screening of 126 pathogens) and microbial culture. Nasopharyngeal, oropharyngeal, and rectal swabs are sent for TaqMan array PCR testing. Samples are reviewed by anatomical pathologists who have received specific training for the CHAMPS study at each site, as well as by a central pathology lab at the US Centers for Disease Control and Prevention. To comprehensively capture clinicians’ diagnostic considerations and to determine antemortem clinical diagnoses, CHAMPS staff extracted all diagnoses recorded during the last clinical encounter before the infant’s or child’s death. These data were abstracted from all available admission forms, progress notes, laboratory results, and radiographic test results. All clinical, verbal autopsy, histopathological, and microbiological results were subsequently reviewed through a standardised process by CHAMPS Determination of Cause of Death (DeCoDe) panels, which are composed of experts across various fields, including paediatricians, pathologists, microbiologists, medical epidemiologists, local public health officials, and representatives of local ministries of health. They use antemortem clinical data, which includes clinicians’ documentation of clinical history, progress notes, laboratory and radiographic imaging results, postmortem MITS pathological results, microbiological results, and verbal autopsy data to determine the underlying cause of death, as well as the comorbid and immediate conditions contributing to death in all enrolled cases. The clinical diagnoses considered as antemortem diagnoses included all diagnoses documented from the time of the child’s clinical encounter to the time of the child’s death, which included diagnoses at admission (including known chronic diseases such as HIV), interim diagnoses and final diagnoses. To comprehensively capture all documented causes for each case of death, we analysed all levels of diagnoses along the causal chain of mortality. The causal chain of mortality refers to all causes of death documented for each case, including the underlying cause of death, immediate cause of death that directly preceded terminal events, and comorbid conditions contributing to death. Determined causes of death are coded in agreement with the International Classification of Diseases, 10th Revision and the WHO death certificate. Variables Each documented antemortem clinical diagnosis was compared with causes of death as determined by DeCoDe panels, which served as the reference standard. Overall, the 10 most common causes of death as determined by DeCoDe panels based on the aggregated CHAMPS data were (1) lower respiratory infections, (2) sepsis, (3) malnutrition, (4) malaria, (5) diarrhoeal diseases, (6) HIV, (7) congenital birth defects, (8) anaemia, (9) other respiratory disease (ie, non-infectious syndromes including aspiration pneumonia, interstitial lung disease and pulmonary haemorrhage), and (10) meningitis/encephalitis. Each documented antemortem clinical diagnosis was paired with each postmortem cause of death for every case. For cases with multiple postmortem causes of death, all postmortem causes of death were included (ie, immediate, underlying or comorbid). We classified each potential antemortem and postmortem diagnostic pairing that were discrepant as major (class I or class II) or minor (class III or class IV) diagnostic errors, following the criteria originally developed by Goldman and later modified by Battle. Two authors with clinical training in paediatrics (CB and CAR) independently reviewed each diagnostic pairing to classify them according to the established system. Any disagreements between these two reviewers were discussed until consensus was reached for each diagnostic pairing. Class I errors included errors in which ‘knowledge of the correct diagnosis before death would have impacted clinical management decisions that could have resulted in either cure or prolonged survival’ (eg, sepsis treated as malnutrition). Class II diagnostic errors were those in which the impact on survival was equivocal despite the misdiagnosis for primary diagnoses, such as cases in which there was ambiguity on whether the correct diagnosis would have changed outcomes (eg, lower respiratory tract infections treated as sepsis). Class III included missed diagnoses with symptoms that should have been treated because they were either related to the terminal disease but not directly responsible for death or could have eventually impacted prognosis (eg, congenital birth defects treated as anaemia). Class IV diagnostic discrepancies included undiagnosed diseases that carried either genetic or epidemiological importance and may have eventually impacted prognosis (eg, sickle cell disease treated as anaemia alone). Correctly diagnosed patients were categorised as class V. Deaths that were non-classifiable due to unclear antemortem clinical diagnoses or insufficient postmortem information were categorised as class VI. Statistical analyses Sensitivity, specificity and area under the curve (AUC) of each antemortem clinical diagnosis were calculated compared with each postmortem cause of death. We calculated the positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, proportion correctly diagnosed, and apparent and true prevalence for antemortem diagnoses for each cause of death. We used Cohen’s Kappa to determine agreement between antemortem diagnoses and postmortem-determined causes of death. For deaths with multiple antemortem clinical diagnoses or multiple postmortem causes of death, each antemortem diagnosis was compared with each postmortem cause of death and considered a match if the antemortem clinical diagnosis was in any location in the causal chain determined by the expert panel at each site. To identify the diseases in which antemortem clinical diagnoses had the most optimal sensitivity and specificity, we calculated the Youden’s index, which allows for the quantification of the overall diagnostic performance. We calculated the number needed to diagnose, which is the number of patients that need to be diagnosed antemortem to identify one correctly diagnosed patient. We calculated 95% CIs for all measures. We used mixed-effect univariable and multivariable logistic regression to identify factors associated with major diagnostic errors, including age, sex, time from hospital admission to death, the number of postmortem diagnoses, and site as candidate variables. The selection of these candidate variables for the inclusion in the model was predicated on their potential influence on diagnostic errors. Age, for instance, might influence disease presentation in children while the time from admission to death could impact disease progression and recognition of signs and symptoms. The number of postmortem diagnoses and site were included due to potential variations in healthcare infrastructure, diagnostic capabilities and disease prevalence across different regions. As diagnostic capacity and patient complexity may vary across CHAMPS sites, we introduced an interaction term between site and number of causes of death. We also conducted sensitivity analyses to determine the test characteristics of antemortem clinician diagnosis to postmortem determined causes of death by site, sex, age (ie, 1–11 months and 12–59 months) and duration of hospital admission (ie, <24 hours and ≥24 hours). All statistical analyses were performed by using R software, V.4.3.1 (R Foundation for Statistical Computing). We conducted a descriptive study and analysed data from seven sites in sub-Saharan Africa and Bangladesh participating in the CHAMPS Network. CHAMPS is conducting prospective mortality surveillance in healthcare centres and communities in areas of high mortality among children aged <5 years (ie, >50 per 1000 live births). The development of the research question was informed by the large burden child mortality worldwide. Patients were not involved in the design, recruitment or conduct of the study. Results of this study will be made publicly available through publication where study participants may access them. Patients were not advisers in this study. The CHAMPS Network was established in 2015 and includes sites in Baliakandi and Faridpur, Bangladesh; Kersa, Haramaya and Harar, Ethiopia; Kisumu and Siaya, Kenya; Bamako, Mali; Manhiça and Quelimane, Mozambique; Makeni and Bo, Sierra Leone; and Soweto, South Africa. These regions were selected because they have high rates of mortality among children aged <5 years. CHAMPS employs postmortem pathological and microbiological evaluations to ascertain causes of child deaths, with the aim of preventing deaths by informing policies and programmes. Our study population included all infants and children aged 1–59 months who died and were enrolled in CHAMPS from December 2016 to February 2022 and had documented antemortem clinical diagnoses. CHAMPS enrols stillbirths and deaths among neonates, infants and children that occur in health facilities or in the community. Here, we focused our analyses on deceased infants and children (1) with identifiable antemortem clinical diagnoses within their clinical records, (2) with consenting caregivers, (3) who underwent minimally invasive tissue sampling (MITS), and had adequate samples to determine causes of death and (4) whose results were reviewed by expert panels to determine postmortem pathology-based diagnoses. We excluded cases without clinical records and those who died before presentation to a health facility because antemortem clinical diagnoses could not be determined for these deaths. Surveillance for stillbirths and child deaths occurring in healthcare facilities and the community is performed by CHAMPS staff at each site. CHAMPS enrols cases within 24 hours of death for the MITS procedure. Within this time frame, caregivers of deceased neonates, infants and children are informed about the CHAMPS data collection process and approached for potential enrolment in the study. CHAMPS procedures include the collection of demographic information, clinical record review, verbal autopsy, and extensive postmortem tissue sampling and testing. Briefly, MITS consists of collection of tissue samples from brain, lungs, liver, and heart using biopsy needles, in addition to samples of blood and cerebrospinal fluid using syringes. Moreover, nasopharyngeal and rectal swabs are collected. MITS serves as a proxy for complete diagnostic autopsy and has demonstrated high concordance, for all age groups, with complete diagnostic autopsy. All collected samples undergo histopathological and microbiological analyses including H&E staining, targeted histochemistry, and immunohistochemistry dictated by the morphological findings and molecular pathogen identification through extensive PCR testing for 126 different pathogens (TaqMan array; ThermoFisher Scientific, Waltham, Massachusetts, USA). Tissues and body fluids are sent for culture. Blood samples also undergo HIV PCR testing, malaria thick and thin smears, and TaqMan array PCR testing (including the screening of 126 pathogens) and microbial culture. Nasopharyngeal, oropharyngeal, and rectal swabs are sent for TaqMan array PCR testing. Samples are reviewed by anatomical pathologists who have received specific training for the CHAMPS study at each site, as well as by a central pathology lab at the US Centers for Disease Control and Prevention. To comprehensively capture clinicians’ diagnostic considerations and to determine antemortem clinical diagnoses, CHAMPS staff extracted all diagnoses recorded during the last clinical encounter before the infant’s or child’s death. These data were abstracted from all available admission forms, progress notes, laboratory results, and radiographic test results. All clinical, verbal autopsy, histopathological, and microbiological results were subsequently reviewed through a standardised process by CHAMPS Determination of Cause of Death (DeCoDe) panels, which are composed of experts across various fields, including paediatricians, pathologists, microbiologists, medical epidemiologists, local public health officials, and representatives of local ministries of health. They use antemortem clinical data, which includes clinicians’ documentation of clinical history, progress notes, laboratory and radiographic imaging results, postmortem MITS pathological results, microbiological results, and verbal autopsy data to determine the underlying cause of death, as well as the comorbid and immediate conditions contributing to death in all enrolled cases. The clinical diagnoses considered as antemortem diagnoses included all diagnoses documented from the time of the child’s clinical encounter to the time of the child’s death, which included diagnoses at admission (including known chronic diseases such as HIV), interim diagnoses and final diagnoses. To comprehensively capture all documented causes for each case of death, we analysed all levels of diagnoses along the causal chain of mortality. The causal chain of mortality refers to all causes of death documented for each case, including the underlying cause of death, immediate cause of death that directly preceded terminal events, and comorbid conditions contributing to death. Determined causes of death are coded in agreement with the International Classification of Diseases, 10th Revision and the WHO death certificate. Each documented antemortem clinical diagnosis was compared with causes of death as determined by DeCoDe panels, which served as the reference standard. Overall, the 10 most common causes of death as determined by DeCoDe panels based on the aggregated CHAMPS data were (1) lower respiratory infections, (2) sepsis, (3) malnutrition, (4) malaria, (5) diarrhoeal diseases, (6) HIV, (7) congenital birth defects, (8) anaemia, (9) other respiratory disease (ie, non-infectious syndromes including aspiration pneumonia, interstitial lung disease and pulmonary haemorrhage), and (10) meningitis/encephalitis. Each documented antemortem clinical diagnosis was paired with each postmortem cause of death for every case. For cases with multiple postmortem causes of death, all postmortem causes of death were included (ie, immediate, underlying or comorbid). We classified each potential antemortem and postmortem diagnostic pairing that were discrepant as major (class I or class II) or minor (class III or class IV) diagnostic errors, following the criteria originally developed by Goldman and later modified by Battle. Two authors with clinical training in paediatrics (CB and CAR) independently reviewed each diagnostic pairing to classify them according to the established system. Any disagreements between these two reviewers were discussed until consensus was reached for each diagnostic pairing. Class I errors included errors in which ‘knowledge of the correct diagnosis before death would have impacted clinical management decisions that could have resulted in either cure or prolonged survival’ (eg, sepsis treated as malnutrition). Class II diagnostic errors were those in which the impact on survival was equivocal despite the misdiagnosis for primary diagnoses, such as cases in which there was ambiguity on whether the correct diagnosis would have changed outcomes (eg, lower respiratory tract infections treated as sepsis). Class III included missed diagnoses with symptoms that should have been treated because they were either related to the terminal disease but not directly responsible for death or could have eventually impacted prognosis (eg, congenital birth defects treated as anaemia). Class IV diagnostic discrepancies included undiagnosed diseases that carried either genetic or epidemiological importance and may have eventually impacted prognosis (eg, sickle cell disease treated as anaemia alone). Correctly diagnosed patients were categorised as class V. Deaths that were non-classifiable due to unclear antemortem clinical diagnoses or insufficient postmortem information were categorised as class VI. Sensitivity, specificity and area under the curve (AUC) of each antemortem clinical diagnosis were calculated compared with each postmortem cause of death. We calculated the positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, proportion correctly diagnosed, and apparent and true prevalence for antemortem diagnoses for each cause of death. We used Cohen’s Kappa to determine agreement between antemortem diagnoses and postmortem-determined causes of death. For deaths with multiple antemortem clinical diagnoses or multiple postmortem causes of death, each antemortem diagnosis was compared with each postmortem cause of death and considered a match if the antemortem clinical diagnosis was in any location in the causal chain determined by the expert panel at each site. To identify the diseases in which antemortem clinical diagnoses had the most optimal sensitivity and specificity, we calculated the Youden’s index, which allows for the quantification of the overall diagnostic performance. We calculated the number needed to diagnose, which is the number of patients that need to be diagnosed antemortem to identify one correctly diagnosed patient. We calculated 95% CIs for all measures. We used mixed-effect univariable and multivariable logistic regression to identify factors associated with major diagnostic errors, including age, sex, time from hospital admission to death, the number of postmortem diagnoses, and site as candidate variables. The selection of these candidate variables for the inclusion in the model was predicated on their potential influence on diagnostic errors. Age, for instance, might influence disease presentation in children while the time from admission to death could impact disease progression and recognition of signs and symptoms. The number of postmortem diagnoses and site were included due to potential variations in healthcare infrastructure, diagnostic capabilities and disease prevalence across different regions. As diagnostic capacity and patient complexity may vary across CHAMPS sites, we introduced an interaction term between site and number of causes of death. We also conducted sensitivity analyses to determine the test characteristics of antemortem clinician diagnosis to postmortem determined causes of death by site, sex, age (ie, 1–11 months and 12–59 months) and duration of hospital admission (ie, <24 hours and ≥24 hours). All statistical analyses were performed by using R software, V.4.3.1 (R Foundation for Statistical Computing). CHAMPS enrolled 1454 deaths in infants and children aged 1–59 months from December 2016 to February 2022. Of these, 498 did not have antemortem clinical records available and 75 died prior to presentation at a health facility, leaving 881 (60.5%) deaths that were included in the analyses . Included cases did not differ from excluded cases by age or sex but differed by site of enrolment . The median age at the time of death was 11 months (IQR 4–21 months) and 47.3% (n=417) were female. The majority (74.6%, n=657) died in hospital and the other 224 (25.4%) died at home following clinical encounters. Cases were distributed across the seven sites as follows: Kenya (25.9%, n=228), Sierra Leone (24.4%, n=215), South Africa (18.6%, n=164), Mali (15.3%, n=135), Mozambique (10.0%, n=88), Bangladesh (3.3%, n=29) and Ethiopia (2.5%, n=22) . Antemortem clinical diagnoses The most common antemortem diagnoses among the included cases were malaria (31.8%, n=280), diarrhoeal disease (30.7%, n=270), lower respiratory tract infections (30.5%, n=269) and malnutrition (22.6%, n=199) . Postmortem determined causes of death Overall, the most common causes of death anywhere in the causal chain of death were lower respiratory tract infections (31.1%, n=274), sepsis (29.3%, n=258), and malnutrition (19.0%, n=167; ). The most common underlying causes of death determined through postmortem examinations were malnutrition (13.5%, n=119), malaria (8.7%, n=77), and HIV (7.7%, n=68) . The most common immediate causes of death were sepsis (21.5%, n=189), lower respiratory tract infections (14.2%, n=125), and malaria (5.6%, n=49). Lower respiratory tract infections (12.5%, n=110), sepsis (6.6%, n=58), and anaemias (7.2%, n=63) were the most common comorbid causes of death. When there was only one cause of death determined postmortem, the most common conditions were malaria (n=43), lower respiratory infections (n=22), and diarrhoeal diseases (n=17). Test characteristics of antemortem clinical diagnoses A total of 635 diagnostic pairs between antemortem clinician diagnosis and postmortem causes of death were concordant. There were 64 diagnostic pairs between antemortem clinician diagnosis and postmortem causes of death that were unclassifiable. Malaria and diarrhoeal diseases were most often correctly diagnosed in the antemortem period . Anaemias, meningitis/encephalitis, and respiratory diseases other than lower respiratory tract infections (ie, aspiration pneumonia, interstitial lung disease and pulmonary haemorrhage) were most infrequently diagnosed among the top 10 causes of death. The sensitivity of antemortem clinical diagnosis ranged from 26.0% (95% CI 14.6% to 40.3%) for the category of other respiratory diseases to 82.2% (95% CI 72.7% to 89.5%) for diarrhoeal diseases . The specificity of antemortem clinical diagnosis ranged from 75.2% (95% CI 72.1% to 78.2%) for diarrhoeal diseases to 99.0% (95% CI 98.1% to 99.6%) for HIV . The AUC for antemortem clinical diagnoses compared with postmortem determined cause of death ranged from 0.56 for anaemias to 0.91 for HIV . The positive likelihood ratio of clinician antemortem diagnoses ranged from 2.12 (95% CI 1.56 to 2.88) for anaemias to 67.25 (95% CI 33.06 to 136.81) for HIV . Negative likelihood ratios of clinician antemortem diagnoses ranged from 0.25 (95% CI 0.18 to 0.36) for malaria to 0.77 (95% CI 0.65 to 0.91) for other respiratory diseases. The overall diagnostic accuracy of clinician antemortem diagnoses was highest for HIV (Youden’s index 0.65, 95% CI 0.52 to 0.77) and lowest for anaemias (Youden’s index 0.19, 95% CI 0.07 to 0.33). There were 464 cases in our analyses that had >1 postmortem-determined cause of death. Of these, the majority (83.6%, n=388) did not have all postmortem causes of death diagnosed prior to the child’s death. Major and minor diagnostic discrepancies A discrepancy between antemortem clinical diagnosis and postmortem determined causes of death was identified in 39.5% (n=348/881) cases. A total of 555 diagnostic errors were identified among 1254 diagnostic comparisons between antemortem clinical diagnoses and postmortem causes of death . Among the 555 diagnostic errors, 457 (82.3%) were classified as major and 98 (17.7%) as minor. Major antemortem diagnostic errors were most common among infants and children who died from meningitis/encephalitis (63.3%, n=31) and sepsis (54.2%, n=140), and least common among diagnostic pairs in cases of congenital birth defects (3.2%, n=2) and malaria (13.4%, n=19) . Minor diagnostic errors were most common among cases that died from anaemias (43.0%, n=40) and congenital birth defects (31.7%, n=20). In multivariable analyses, infants and children who had 2–3 postmortem causes of death (adjusted OR (aOR) 33.9, 95% CI 17.4 to 73.2) and >3 postmortem causes of death (aOR 90.5, 95% CI 42.7 to 210.3) were more likely to have a major antemortem diagnostic error than those who had only one postmortem cause of death . The interaction term between site and the number of causes of death did not reach statistical significance (p=0.428), which suggests that number of causes of death exerted an effect independent of site. Age, sex, duration of hospital admission and site were not associated with the presence of a major diagnostic error. Sensitivity analyses The sensitivity and specificity of clinician antemortem diagnoses compared with postmortem causes of death varied by site . However, test characteristics of antemortem diagnoses did not vary substantially by the sex or age of the deceased infant or child . The sensitivity of antemortem clinician diagnoses was generally higher among infants and children who were admitted for ≥24 hours than those admitted for <24 hours prior to death. For instance, the sensitivity for lower respiratory tract infection in infants aged 1–11 months was 49.7% (95% CI 41.6% to 57.8%), for sepsis it was 47.7% (95% CI 39.4% to 56.0%) and for malnutrition it was 46.9% (95% CI 35.7% to 58.3%) . Similar patterns were observed among those who had only one cause of death determined postmortem compared with those with more than one cause of death . The sensitivity and specificity of clinical antemortem diagnoses made at the final clinical encounter were generally lower for cases that died at home than among cases that died during hospital admission . The most common antemortem diagnoses among the included cases were malaria (31.8%, n=280), diarrhoeal disease (30.7%, n=270), lower respiratory tract infections (30.5%, n=269) and malnutrition (22.6%, n=199) . Overall, the most common causes of death anywhere in the causal chain of death were lower respiratory tract infections (31.1%, n=274), sepsis (29.3%, n=258), and malnutrition (19.0%, n=167; ). The most common underlying causes of death determined through postmortem examinations were malnutrition (13.5%, n=119), malaria (8.7%, n=77), and HIV (7.7%, n=68) . The most common immediate causes of death were sepsis (21.5%, n=189), lower respiratory tract infections (14.2%, n=125), and malaria (5.6%, n=49). Lower respiratory tract infections (12.5%, n=110), sepsis (6.6%, n=58), and anaemias (7.2%, n=63) were the most common comorbid causes of death. When there was only one cause of death determined postmortem, the most common conditions were malaria (n=43), lower respiratory infections (n=22), and diarrhoeal diseases (n=17). A total of 635 diagnostic pairs between antemortem clinician diagnosis and postmortem causes of death were concordant. There were 64 diagnostic pairs between antemortem clinician diagnosis and postmortem causes of death that were unclassifiable. Malaria and diarrhoeal diseases were most often correctly diagnosed in the antemortem period . Anaemias, meningitis/encephalitis, and respiratory diseases other than lower respiratory tract infections (ie, aspiration pneumonia, interstitial lung disease and pulmonary haemorrhage) were most infrequently diagnosed among the top 10 causes of death. The sensitivity of antemortem clinical diagnosis ranged from 26.0% (95% CI 14.6% to 40.3%) for the category of other respiratory diseases to 82.2% (95% CI 72.7% to 89.5%) for diarrhoeal diseases . The specificity of antemortem clinical diagnosis ranged from 75.2% (95% CI 72.1% to 78.2%) for diarrhoeal diseases to 99.0% (95% CI 98.1% to 99.6%) for HIV . The AUC for antemortem clinical diagnoses compared with postmortem determined cause of death ranged from 0.56 for anaemias to 0.91 for HIV . The positive likelihood ratio of clinician antemortem diagnoses ranged from 2.12 (95% CI 1.56 to 2.88) for anaemias to 67.25 (95% CI 33.06 to 136.81) for HIV . Negative likelihood ratios of clinician antemortem diagnoses ranged from 0.25 (95% CI 0.18 to 0.36) for malaria to 0.77 (95% CI 0.65 to 0.91) for other respiratory diseases. The overall diagnostic accuracy of clinician antemortem diagnoses was highest for HIV (Youden’s index 0.65, 95% CI 0.52 to 0.77) and lowest for anaemias (Youden’s index 0.19, 95% CI 0.07 to 0.33). There were 464 cases in our analyses that had >1 postmortem-determined cause of death. Of these, the majority (83.6%, n=388) did not have all postmortem causes of death diagnosed prior to the child’s death. A discrepancy between antemortem clinical diagnosis and postmortem determined causes of death was identified in 39.5% (n=348/881) cases. A total of 555 diagnostic errors were identified among 1254 diagnostic comparisons between antemortem clinical diagnoses and postmortem causes of death . Among the 555 diagnostic errors, 457 (82.3%) were classified as major and 98 (17.7%) as minor. Major antemortem diagnostic errors were most common among infants and children who died from meningitis/encephalitis (63.3%, n=31) and sepsis (54.2%, n=140), and least common among diagnostic pairs in cases of congenital birth defects (3.2%, n=2) and malaria (13.4%, n=19) . Minor diagnostic errors were most common among cases that died from anaemias (43.0%, n=40) and congenital birth defects (31.7%, n=20). In multivariable analyses, infants and children who had 2–3 postmortem causes of death (adjusted OR (aOR) 33.9, 95% CI 17.4 to 73.2) and >3 postmortem causes of death (aOR 90.5, 95% CI 42.7 to 210.3) were more likely to have a major antemortem diagnostic error than those who had only one postmortem cause of death . The interaction term between site and the number of causes of death did not reach statistical significance (p=0.428), which suggests that number of causes of death exerted an effect independent of site. Age, sex, duration of hospital admission and site were not associated with the presence of a major diagnostic error. The sensitivity and specificity of clinician antemortem diagnoses compared with postmortem causes of death varied by site . However, test characteristics of antemortem diagnoses did not vary substantially by the sex or age of the deceased infant or child . The sensitivity of antemortem clinician diagnoses was generally higher among infants and children who were admitted for ≥24 hours than those admitted for <24 hours prior to death. For instance, the sensitivity for lower respiratory tract infection in infants aged 1–11 months was 49.7% (95% CI 41.6% to 57.8%), for sepsis it was 47.7% (95% CI 39.4% to 56.0%) and for malnutrition it was 46.9% (95% CI 35.7% to 58.3%) . Similar patterns were observed among those who had only one cause of death determined postmortem compared with those with more than one cause of death . The sensitivity and specificity of clinical antemortem diagnoses made at the final clinical encounter were generally lower for cases that died at home than among cases that died during hospital admission . In our study of 881 deceased infants and children, we found that diagnostic errors were common when antemortem clinical diagnoses were compared with postmortem causes of death, which highlights the need for enhanced diagnostic approaches for young children. Many of the diagnostic discrepancies observed were major. Moreover, there were greater odds of antemortem clinical diagnostic errors among children who died from >1 cause. These findings underscore the limitations of clinical diagnosis and the critical need for improved diagnostic tools and techniques to reduce childhood mortality in resource-limited settings. Notably, many children died despite alignment between antemortem and postmortem diagnoses, underscoring that accurate diagnosis alone is insufficient to reduce childhood mortality but is a key step towards the provision of high-quality clinical care. Approximately 40% of all deaths among infants and children in our study had at least one diagnostic error. This rate is higher than prior studies among deceased children that have demonstrated clinicopathological discrepancy rates ranging from 19% among children in Chile to 30% among children in China. The higher rate of clinicopathological discrepancies observed in our study compared with prior studies among children is likely due to several reasons. First, laboratory capabilities in low- and middle-income countries are often more limited than that found in settings with more resources, which may hinder the determination of timely and accurate antemortem diagnoses. Prior studies also suggest commonly used clinical signs and symptoms for diagnosing lower respiratory tract infections can be non-specific and difficult to detect correctly in young children, making accurate diagnosis of these conditions challenging. Accurate diagnoses among young children may also be more challenging given non-specific symptoms for many conditions, which has prompted the development of risk assessment tools that make use of combined signs and symptoms to augment diagnostic and prognostic accuracy, though these tools are not yet widely used. Major diagnostic errors were more common among infants and children who had more than one cause of death. Children with more comorbid illnesses may have greater disease complexity that poses diagnostic challenges. Clinicians may prioritise diagnosing and treating one predominant condition while other comorbid illnesses are missed or not highlighted for treatment decisions. Additionally, overlapping signs and symptoms between concurrent diseases can complicate making accurate diagnoses. This finding may also represent underdocumentation of antemortem clinical diagnoses. However, we had no reason to believe that underdocumentation would be more common among children who died from >1 cause. Clinician antemortem diagnosis of malaria had the highest sensitivity in our study. Owing to the historically large burden of malaria-related mortality, much attention has been paid to developing simple and accurate diagnostic tools including malaria rapid diagnostic tests and malaria parasite smears. However, the accuracy of malaria rapid diagnostic tests is limited by the persistence of positive results for weeks after successful treatment and cure. This may lead to clinician overdiagnosis of malaria by clinicians based on positive rapid diagnostic tests, even with resolved infection, contributing to the low positive predictive value of 40.6% we observed. Moreover, in malaria-endemic areas, individuals can be infected but not necessarily have any clinical consequence of those infections, given the partial natural immunity progressively acquired to this disease. The availability of such rapid diagnostics, as well as a high pretest probability in malaria-endemic settings, may have contributed to high sensitivity of antemortem clinician diagnosis. As the sensitivity of clinician antemortem diagnoses was low for the other included diseases, our results suggest that additional rapid, simple, accurate and clinically relevant diagnostics and point-of-care testing in settings with limited laboratory capacity may be needed to enhance diagnostic accuracy for conditions such as lower respiratory tract infections and sepsis. The sensitivity of antemortem clinical diagnosis for common causes of death such as lower respiratory tract infections and sepsis was below 50%, rendering many of these diagnoses unrecognised while the child was alive. Moreover, the sensitivity of antemortem clinical diagnosis for other respiratory diseases (ie, aspiration pneumonia, interstitial lung disease, and pulmonary haemorrhage) was the lowest among the conditions considered. Potential factors contributing to this suboptimal diagnostic accuracy could include the lack of access to radiologic imaging, which may hinder the accurate identification of lung-related abnormalities. Additionally, the presence of non-specific signs and symptoms commonly associated with respiratory illnesses might further complicate precise diagnosis. Limitations The results of our study should be interpreted in the context of several limitations. First, clinical data collected in the CHAMPS network relies on documentation by treating clinicians and nurses, which at times may be incomplete and may not have included all antemortem clinical diagnoses. Some diagnoses considered by treating clinicians may not have been documented, leading to a potential overestimation or underestimation, of clinicopathological discrepancies. Respiratory diseases, such as pneumonia, are often the terminal event preceding death. Therefore, symptoms on admission may not always translate to the cause of death determined postmortem. There is also the potential difficulty in differentiating between transient or asymptomatic bacteraemia/positive culture and sepsis or SIRS, as the determination of sepsis was based on culture sampling via MITS and required careful consideration of clinical context and symptoms, which may not always be clearly documented or distinguishable in antemortem records. This discordance in symptoms at presentation through disease progression could contribute to the low sensitivity observed for other respiratory diseases in our analyses. We attempted to overcome these potential limitations by thorough review of all available clinical data by trained clinicians with familiarity with local contexts. We did not assess the relationship between the timing that the diagnosis was made and the postmortem-determined causes of death. As illnesses progress and patients can develop secondary illnesses, future studies assessing the concordance of antemortem and postmortem causes of death should include moderator analyses between the timing that antemortem diagnoses were made and postmortem causes of death. Furthermore, we did not assess whether diagnoses made by clinicians were for previously known chronic diseases (eg, chronic HIV disease) or new illnesses (eg, newly diagnosed HIV). Nevertheless, as our reference standard was robust postmortem determined causes of death that includes immediate, underlying and comorbid causes of death we do not expect this to have substantially affected our results. Some of the diagnoses considered discrepant, such as aspiration pneumonia, sepsis and interstitial lung disease, may reflect the natural progression of a primary illness rather than distinct, avertable causes of death, complicating the distinction between initial illness and subsequent conditions. Additionally, the diagnostic capabilities and skills of clinicians across sites vary and likely depend on the level of training of medical staff, which was not measured in this study. We did not separately analyse immediate, underlying and comorbid postmortem causes of death in relation to antemortem diagnoses. The classification system used to categorise major antemortem diagnostic errors does not necessarily indicate there was also an error in clinical management or treatment that could have prevented the child’s death. Some major errors may have still received appropriate supportive care, such as fluids, oxygen and antibiotics, which treat many conditions. Thus, while major diagnostic errors suggest potential opportunities to prevent mortality, it is difficult to quantify how many deaths were realistically avoidable. Some of the diagnoses considered discrepant, such as aspiration pneumonia, sepsis and interstitial lung disease, may reflect the natural progression of a primary illness rather than distinct, avertable causes of death, complicating the distinction between initial illness and subsequent conditions. We also did not capture the reasons clinicians made antemortem diagnoses or the use of equipment for diagnoses such as malnutrition through measurement of anthropometry, which warrants further investigation. Such an understanding may elucidate precise diagnostic challenges in need of targeted interventions to overcome. The relatively low specificity of antemortem diagnosis of diarrhoeal diseases could potentially be attributed to diarrhoea as a symptom accompanying other illnesses determined as the postmortem causes of death. Postmortem causes of death in CHAMPS are determined through a multifaceted approach that includes the integration of antemortem clinical diagnoses in addition to histopathological and microbiological MITS results. Lastly, our findings, although drawn from seven sites low-income and middle-income countries, may not represent the state of diagnostic accuracy in other settings in those countries or, more broadly, in sub-Saharan Africa and Bangladesh where postmortem examinations do not routinely occur. The results of our study should be interpreted in the context of several limitations. First, clinical data collected in the CHAMPS network relies on documentation by treating clinicians and nurses, which at times may be incomplete and may not have included all antemortem clinical diagnoses. Some diagnoses considered by treating clinicians may not have been documented, leading to a potential overestimation or underestimation, of clinicopathological discrepancies. Respiratory diseases, such as pneumonia, are often the terminal event preceding death. Therefore, symptoms on admission may not always translate to the cause of death determined postmortem. There is also the potential difficulty in differentiating between transient or asymptomatic bacteraemia/positive culture and sepsis or SIRS, as the determination of sepsis was based on culture sampling via MITS and required careful consideration of clinical context and symptoms, which may not always be clearly documented or distinguishable in antemortem records. This discordance in symptoms at presentation through disease progression could contribute to the low sensitivity observed for other respiratory diseases in our analyses. We attempted to overcome these potential limitations by thorough review of all available clinical data by trained clinicians with familiarity with local contexts. We did not assess the relationship between the timing that the diagnosis was made and the postmortem-determined causes of death. As illnesses progress and patients can develop secondary illnesses, future studies assessing the concordance of antemortem and postmortem causes of death should include moderator analyses between the timing that antemortem diagnoses were made and postmortem causes of death. Furthermore, we did not assess whether diagnoses made by clinicians were for previously known chronic diseases (eg, chronic HIV disease) or new illnesses (eg, newly diagnosed HIV). Nevertheless, as our reference standard was robust postmortem determined causes of death that includes immediate, underlying and comorbid causes of death we do not expect this to have substantially affected our results. Some of the diagnoses considered discrepant, such as aspiration pneumonia, sepsis and interstitial lung disease, may reflect the natural progression of a primary illness rather than distinct, avertable causes of death, complicating the distinction between initial illness and subsequent conditions. Additionally, the diagnostic capabilities and skills of clinicians across sites vary and likely depend on the level of training of medical staff, which was not measured in this study. We did not separately analyse immediate, underlying and comorbid postmortem causes of death in relation to antemortem diagnoses. The classification system used to categorise major antemortem diagnostic errors does not necessarily indicate there was also an error in clinical management or treatment that could have prevented the child’s death. Some major errors may have still received appropriate supportive care, such as fluids, oxygen and antibiotics, which treat many conditions. Thus, while major diagnostic errors suggest potential opportunities to prevent mortality, it is difficult to quantify how many deaths were realistically avoidable. Some of the diagnoses considered discrepant, such as aspiration pneumonia, sepsis and interstitial lung disease, may reflect the natural progression of a primary illness rather than distinct, avertable causes of death, complicating the distinction between initial illness and subsequent conditions. We also did not capture the reasons clinicians made antemortem diagnoses or the use of equipment for diagnoses such as malnutrition through measurement of anthropometry, which warrants further investigation. Such an understanding may elucidate precise diagnostic challenges in need of targeted interventions to overcome. The relatively low specificity of antemortem diagnosis of diarrhoeal diseases could potentially be attributed to diarrhoea as a symptom accompanying other illnesses determined as the postmortem causes of death. Postmortem causes of death in CHAMPS are determined through a multifaceted approach that includes the integration of antemortem clinical diagnoses in addition to histopathological and microbiological MITS results. Lastly, our findings, although drawn from seven sites low-income and middle-income countries, may not represent the state of diagnostic accuracy in other settings in those countries or, more broadly, in sub-Saharan Africa and Bangladesh where postmortem examinations do not routinely occur. Antemortem clinical diagnostic errors were common among infants and children who died in seven regions in sub-Saharan Africa and Bangladesh with high childhood mortality rates. Comparing antemortem clinical diagnoses to postmortem causes of death may inform disease processes in most need of enhanced antemortem diagnostic approaches. Most antemortem clinical diagnostic errors were major. To further reduce childhood mortality in resource-limited settings, there is an urgent need to improve antemortem diagnostic capability through advances in availability of diagnostic testing and clinical skills. 10.1136/bmjpo-2024-002654 online supplemental file 1 |
How large must a dose‐optimization trial be? | 0b5778d7-fa63-4d47-970f-bc73be31ff9d | 10681487 | Internal Medicine[mh] | The US Food and Drug Administration (FDA) Oncology Center of Excellence (OCE) has recently promulgated draft guidance recommending randomized, parallel dose–response trials for “dose optimization,” apparently without having undertaken formal modeling and simulation work to sharpen their thinking. , , Principles of pharmacometrics can be useful not only in the analysis of preclinical and early‐phase trial data, but also for abstract foundational concept development as needed for the rational development of such guidance.
A model of individual‐patient efficacy‐toxicity trade‐off is posited, with heterogeneity across individuals regarding both dose‐efficacy and dose‐toxicity relations. The model is solved to obtain a closed‐form expression for individually optimal dosing, and numerical methods are used to find the “optimal [single] dose” that maximizes expected utility in the population under one‐size‐fits‐all dosing. The ratio of benefit to harm terms in this expected utility is proposed as a measure of intrinsic drug tolerability. An expression for the utility lost to the one‐size‐fits‐all dosing constraint is also given. Finally, a criterion is proposed for reasonable precision of a dose‐randomization trial, then a formula for the minimum size of such a trial is derived and explored numerically as a function of drug tolerability and interindividual variability of pharmacokinetics and pharmacodynamics (PK/PD). All computation was done with Julia version 1.9. Utilities We take therapeutic efficacy, measured as the probability of achieving some good outcome, such as a remission, to constitute a utility measure. We posit a maximum effect (E max )‐type dose‐efficacy curve: (1) monotone increasing and concave, with P r ED 50 ≡ 0.5 P max and asymptote P r ∞ = P max . We will suppose that the disutility of toxicity T can be expressed objectively in units of P r , and that the dose‐toxicity relation T D is of the convex form: (2) T D = D D * 1 + η , η > 0 . Note that T D * ≡ 1 means the toxicity at dose D * is severe enough to nullify even the maximal utility P r = 1 of certain therapeutic benefit. Thus D * sets a strict upper bound on the tolerable dose range. While adopting the simplifying assumption that η is a fixed characteristic of the therapy itself, we will suppose D * varies from one patient to another to reflect heterogeneity jointly in individuals' PK/PD and in their subjective evaluation of toxicity. Individually optimal dosing As depicted in Figure , the net utility U D = P r D − T D is then strictly concave, and its unique maximum occurs at the (individually) optimal dose D ^ determined by: (3) P r ′ D ^ = T ′ D ^ . It is relatively straightforward to transform Equation to: η P max 1 + η 1 / η D * ln 2 η ED 50 1 + η η = D ln 2 η ED 50 exp D ln 2 η ED 50 , which we may see has the form z = we w , if we identify its left‐hand side with z and D ln 2 / η ED 50 with w . Because z > 0 , this has the unique real solution w = W 0 z , where W 0 denotes the principal branch of the Lambert W function. ,§4.13 Thus we obtain: (4) D ^ ED 50 D * = η ED 50 ln 2 W 0 η P max 1 + η 1 η D * ln 2 η ED 50 1 + η η . Expected utilities To develop population‐average results, we will suppose that the parameters P max and η are fixed, whereas ED 50 and D * are inverse‐gamma distributed: ED 50 ∼ Inv‐Gamma α , β D * ∼ Inv‐Gamma a , b , the Inv‐Gamma density being: f x α β = β α Γ α x − α − 1 exp − β / x . The closed form of Equation enables us efficiently to compute the integrand in: (5) E U D ^ = ∫ 0 ∞ ∫ 0 ∞ U D ^ x , y f x α β f y ; a , b d x d y , to integrate numerically for the expected (per capita) utility of individually optimal dosing. The integrals in the expected utility U ¯ D = P ¯ r D − T ¯ D of a one‐size‐fits‐all dose D , however, are readily obtained in closed form: (6) P ¯ r D P max = ∫ 0 ∞ 1 − exp − D ln 2 x β α Γ α x − α − 1 exp − β x d x = 1 − ∫ 0 ∞ β α Γ α x − α − 1 exp − β x − D ln 2 x d x = 1 − β β + D ln 2 α ∫ 0 ∞ f x ; α , β + D ln 2 d x = 1 − β β + D ln 2 α = 1 − 1 + ln 2 β D − α and (7) T ¯ D = ∫ 0 ∞ D x 1 + η b a Γ a x − a − 1 exp − b x d x = D 1 + η Γ a + 1 + η b 1 + η Γ a ∫ 0 ∞ f x ; a + 1 + η , b d x = Γ a + 1 + η Γ a D b 1 + η . A quantity of particular interest is the ratio: (8) τ D = P ¯ r D T ¯ D = P max 1 − 1 + ln 2 β D − α Γ a + 1 + η Γ a D b 1 + η , interpretable as a tolerability index for dose D : large values τ D ≫ 1 indicate that benefit P ¯ r D far outweighs harms from toxicity T ¯ D , whereas values of τ D approaching 1 indicate that harms nearly cancel out benefits; τ D < 1 indicates net harm at dose D . It is especially noteworthy that Equation may be written as: (9) T ¯ D = T ¯ 1 ⋅ D 1 + η = P ¯ r 1 τ 1 D 1 + η , showing that T ¯ D depends on parameters a and b only through τ 1 . This proves to be important below, where by normalizing our dose units so that median ED 50 ≡ 1 , we render τ 1 interpretable as the tolerability of median ED 50 . Optimal one‐size‐fits‐all dosing A regulatory agency constrained to “advocating a [single] dose for a population” , at [1:08:07] faces the problem of finding the population‐optimal dose: (10) D ˜ = arg max D U ¯ D . Being a straightforward population‐average over many optimization problems such as depicted in Figure , this problem possesses the same concavity, and enjoys the same guarantee of a unique positive solution, which we obtain by solving a first‐order condition analogous to Equation : This takes the form: C = x η 1 + x α + 1 , x = ln 2 β D ˜ , which we solve for D ˜ = βx / ln 2 by finding the unique real root of: (11) η ln x + 1 + α ln 1 + x − ln C = 0 . Section develops bounds for a numerical search. Whereas I have previously treated the cost of one‐size‐fits‐all dosing solely in terms of its impact on efficacy, , Equations , , , and allow for a more coherent and comprehensive treatment of net utility loss: (12) E U D ^ − U ¯ D ˜ . For further exploration of this, see Section . A lower bound on dose‐randomization trial size Although generally dose optimization may require adaptive exploration that ranges over many distinct doses, in order to obtain a strong lower bound on dose‐randomization trial size, we consider the power‐maximizing limit where n participants are randomized to one of two doses. Suppose we enroll a total of n participants into two arms each of size n / 2 , at doses D 1 < D 2 with respective efficacy probabilities p 1 < p 2 ; then the observed difference in proportions of successes in the two arms is an unbiased estimator of p 2 − p 1 with standard error: (13) σ p 2 − p 1 ^ = p 1 1 − p 1 n / 2 + p 2 1 − p 2 n / 2 . Adopting the rather weak standard that properly characterizing the difference p 2 − p 1 requires that Equation not exceed half the actual difference p 2 − p 1 , then we obtain the bound: (14) n ≥ 8 p 1 1 − p 1 + p 2 1 − p 2 p 2 − p 1 2 . To obtain a definite bound, we furthermore apply this criterion to a trial ideally designed to exhibit the canonical aspiration of Project Optimus: one in which the lower dose just so happens to be D ˜ , and the higher dose imposes twice the toxicity burden of the lower dose: (15) D 1 = D ˜ , E T D 2 = 2 ⋅ E T D 1 . Happily, the simple power‐law form of T D (see also Equation ) allows us to solve Equation for D 2 in terms of D 1 : D 2 = D 1 ⋅ 2 1 / 1 + η . Thus, we may obtain a definite lower bound on n by substituting: (16) p 1 = P ¯ r D ˜ , p 2 = P ¯ r D ˜ ⋅ 2 1 / 1 + η on the RHS of Equation : (17) n min = 8 p 1 1 − p 1 + p 2 1 − p 2 p 2 − p 1 2 p 1 = P ¯ r D ˜ , p 2 = P ¯ r D ˜ ⋅ 2 1 / 1 + η . This trial is depicted in Figure , the purely geometrical nature of which abstracts away the dose scale, thereby underscoring the genericity of our analysis. (The specific dimensions shown incidentally match the worked example in Section .) A systematic reduction of the parameter space The model posited here involves no fewer than 6 distinct parameters: P max , α , β , η , a , b . The β dimension may be eliminated by scaling dose units so that median ED 50 is 1. Furthermore, because parameters a and b enter into Equation only via D ˜ 's dependence on τ 1 , we can collapse the two dimensions a , b to the single dimension of τ 1 in an analysis of n min . (Importantly, our scaling of dose units renders τ 1 readily interpretable, as the tolerability of median ED 50 .) Of the four dimensions that remain after these reductions, we condition on a few discrete values of P max and η : (18) P max η ∈ 0.8,0.9,1 × 0.1 , 1 2 , 1 , then use two‐dimensional contour plots to describe the remaining dependence of n min .
We take therapeutic efficacy, measured as the probability of achieving some good outcome, such as a remission, to constitute a utility measure. We posit a maximum effect (E max )‐type dose‐efficacy curve: (1) monotone increasing and concave, with P r ED 50 ≡ 0.5 P max and asymptote P r ∞ = P max . We will suppose that the disutility of toxicity T can be expressed objectively in units of P r , and that the dose‐toxicity relation T D is of the convex form: (2) T D = D D * 1 + η , η > 0 . Note that T D * ≡ 1 means the toxicity at dose D * is severe enough to nullify even the maximal utility P r = 1 of certain therapeutic benefit. Thus D * sets a strict upper bound on the tolerable dose range. While adopting the simplifying assumption that η is a fixed characteristic of the therapy itself, we will suppose D * varies from one patient to another to reflect heterogeneity jointly in individuals' PK/PD and in their subjective evaluation of toxicity.
As depicted in Figure , the net utility U D = P r D − T D is then strictly concave, and its unique maximum occurs at the (individually) optimal dose D ^ determined by: (3) P r ′ D ^ = T ′ D ^ . It is relatively straightforward to transform Equation to: η P max 1 + η 1 / η D * ln 2 η ED 50 1 + η η = D ln 2 η ED 50 exp D ln 2 η ED 50 , which we may see has the form z = we w , if we identify its left‐hand side with z and D ln 2 / η ED 50 with w . Because z > 0 , this has the unique real solution w = W 0 z , where W 0 denotes the principal branch of the Lambert W function. ,§4.13 Thus we obtain: (4) D ^ ED 50 D * = η ED 50 ln 2 W 0 η P max 1 + η 1 η D * ln 2 η ED 50 1 + η η .
To develop population‐average results, we will suppose that the parameters P max and η are fixed, whereas ED 50 and D * are inverse‐gamma distributed: ED 50 ∼ Inv‐Gamma α , β D * ∼ Inv‐Gamma a , b , the Inv‐Gamma density being: f x α β = β α Γ α x − α − 1 exp − β / x . The closed form of Equation enables us efficiently to compute the integrand in: (5) E U D ^ = ∫ 0 ∞ ∫ 0 ∞ U D ^ x , y f x α β f y ; a , b d x d y , to integrate numerically for the expected (per capita) utility of individually optimal dosing. The integrals in the expected utility U ¯ D = P ¯ r D − T ¯ D of a one‐size‐fits‐all dose D , however, are readily obtained in closed form: (6) P ¯ r D P max = ∫ 0 ∞ 1 − exp − D ln 2 x β α Γ α x − α − 1 exp − β x d x = 1 − ∫ 0 ∞ β α Γ α x − α − 1 exp − β x − D ln 2 x d x = 1 − β β + D ln 2 α ∫ 0 ∞ f x ; α , β + D ln 2 d x = 1 − β β + D ln 2 α = 1 − 1 + ln 2 β D − α and (7) T ¯ D = ∫ 0 ∞ D x 1 + η b a Γ a x − a − 1 exp − b x d x = D 1 + η Γ a + 1 + η b 1 + η Γ a ∫ 0 ∞ f x ; a + 1 + η , b d x = Γ a + 1 + η Γ a D b 1 + η . A quantity of particular interest is the ratio: (8) τ D = P ¯ r D T ¯ D = P max 1 − 1 + ln 2 β D − α Γ a + 1 + η Γ a D b 1 + η , interpretable as a tolerability index for dose D : large values τ D ≫ 1 indicate that benefit P ¯ r D far outweighs harms from toxicity T ¯ D , whereas values of τ D approaching 1 indicate that harms nearly cancel out benefits; τ D < 1 indicates net harm at dose D . It is especially noteworthy that Equation may be written as: (9) T ¯ D = T ¯ 1 ⋅ D 1 + η = P ¯ r 1 τ 1 D 1 + η , showing that T ¯ D depends on parameters a and b only through τ 1 . This proves to be important below, where by normalizing our dose units so that median ED 50 ≡ 1 , we render τ 1 interpretable as the tolerability of median ED 50 .
A regulatory agency constrained to “advocating a [single] dose for a population” , at [1:08:07] faces the problem of finding the population‐optimal dose: (10) D ˜ = arg max D U ¯ D . Being a straightforward population‐average over many optimization problems such as depicted in Figure , this problem possesses the same concavity, and enjoys the same guarantee of a unique positive solution, which we obtain by solving a first‐order condition analogous to Equation : This takes the form: C = x η 1 + x α + 1 , x = ln 2 β D ˜ , which we solve for D ˜ = βx / ln 2 by finding the unique real root of: (11) η ln x + 1 + α ln 1 + x − ln C = 0 . Section develops bounds for a numerical search. Whereas I have previously treated the cost of one‐size‐fits‐all dosing solely in terms of its impact on efficacy, , Equations , , , and allow for a more coherent and comprehensive treatment of net utility loss: (12) E U D ^ − U ¯ D ˜ . For further exploration of this, see Section .
Although generally dose optimization may require adaptive exploration that ranges over many distinct doses, in order to obtain a strong lower bound on dose‐randomization trial size, we consider the power‐maximizing limit where n participants are randomized to one of two doses. Suppose we enroll a total of n participants into two arms each of size n / 2 , at doses D 1 < D 2 with respective efficacy probabilities p 1 < p 2 ; then the observed difference in proportions of successes in the two arms is an unbiased estimator of p 2 − p 1 with standard error: (13) σ p 2 − p 1 ^ = p 1 1 − p 1 n / 2 + p 2 1 − p 2 n / 2 . Adopting the rather weak standard that properly characterizing the difference p 2 − p 1 requires that Equation not exceed half the actual difference p 2 − p 1 , then we obtain the bound: (14) n ≥ 8 p 1 1 − p 1 + p 2 1 − p 2 p 2 − p 1 2 . To obtain a definite bound, we furthermore apply this criterion to a trial ideally designed to exhibit the canonical aspiration of Project Optimus: one in which the lower dose just so happens to be D ˜ , and the higher dose imposes twice the toxicity burden of the lower dose: (15) D 1 = D ˜ , E T D 2 = 2 ⋅ E T D 1 . Happily, the simple power‐law form of T D (see also Equation ) allows us to solve Equation for D 2 in terms of D 1 : D 2 = D 1 ⋅ 2 1 / 1 + η . Thus, we may obtain a definite lower bound on n by substituting: (16) p 1 = P ¯ r D ˜ , p 2 = P ¯ r D ˜ ⋅ 2 1 / 1 + η on the RHS of Equation : (17) n min = 8 p 1 1 − p 1 + p 2 1 − p 2 p 2 − p 1 2 p 1 = P ¯ r D ˜ , p 2 = P ¯ r D ˜ ⋅ 2 1 / 1 + η . This trial is depicted in Figure , the purely geometrical nature of which abstracts away the dose scale, thereby underscoring the genericity of our analysis. (The specific dimensions shown incidentally match the worked example in Section .)
The model posited here involves no fewer than 6 distinct parameters: P max , α , β , η , a , b . The β dimension may be eliminated by scaling dose units so that median ED 50 is 1. Furthermore, because parameters a and b enter into Equation only via D ˜ 's dependence on τ 1 , we can collapse the two dimensions a , b to the single dimension of τ 1 in an analysis of n min . (Importantly, our scaling of dose units renders τ 1 readily interpretable, as the tolerability of median ED 50 .) Of the four dimensions that remain after these reductions, we condition on a few discrete values of P max and η : (18) P max η ∈ 0.8,0.9,1 × 0.1 , 1 2 , 1 , then use two‐dimensional contour plots to describe the remaining dependence of n min .
Our key result is shown in Figure , where level curves of n min are plotted in the plane determined by plausible ranges for τ median ED 50 and IQR median ED 50 , for several discrete values of P max and η . Dose‐randomization trials meeting our reasonableness criterion (Equations and ) generally require enrollment of at least several hundred participants. Although some corner regions in Figure agree in magnitude with sizes of randomized dose‐optimization trials OCE cites as exemplary (e.g., N = 196 for DREAMM‐2), it is notable that even modest departures from P max = 1 inflate n min well above 200—especially for the intrinsically more tolerable drugs τ ≫ 2 specifically cited in the rationale of Project Optimus. Indeed, Figure offers some geometrical intuition for how decreasing P max may crowd p 1 and p 2 closer together, shrinking the denominator of Equation and driving n min higher.
To my knowledge, the design of oncology dose‐optimization trials has not previously been explored in a setting that explicitly acknowledges continuous variability between patients in respect to their PK/PD and to the utilities underlying their consideration of efficacy‐toxicity trade‐offs. I have previously analyzed the safety of dose‐finding trials as a function of PK/PD heterogeneity. , Heterogeneity over utilities has been considered previously in a categorical manner, linked to predefined prognostic subgroups. , Explicit acknowledgment of continuous variation in PK/PD tends to raise the specter of adaptive dose individualization, , , which the FDA's OCE shuns because: That is what an individual doctor has to do with an individual patient, and here again, that doesn't kind of fit in to the FDA because we're advocating a dose for a population. But … for an individual [dosing] decision, that is the practice of medicine that the FDA does not regulate. , at [1:07:53] One need not appeal to regulatory politics, however, to conceive circumstances in which dose‐randomization trials of the kind analyzed here might rationally be undertaken. If treatment occurs in a relatively brief episode, for example, so that neither benefits nor toxicities become evident until after administration of a full dose, then the modality offers no reasonable prospect for dose titration. (The hypothetical case of a single radiation treatment might be taken to exemplify this situation.) Such a setting also averts troublesome factors, such as treatment discontinuation, that would complicate the simple trial analysis presumed in Equation . It is clear, however, that the FDA OCE intends that dose‐randomization trials be undertaken quite broadly, with indeed much emphasis being placed on modern targeted agents that are intrinsically more tolerable than chemotherapy, and may be administered chronically. , , Nevertheless, because of the manner in which it concedes optimal foresight in trial design and conduct, the analysis offered here applies to any one‐size‐fits‐all “dose optimization” trial, whether its rationale be political or driven by essential characteristics of the therapy. Regarding the particular question addressed here, namely that of trial sample sizes, the new Draft Guidance states: The trial should be sized to allow for sufficient assessment of activity, safety, and tolerability for each dosage. The trial does not need to be powered to demonstrate statistical superiority of a dosage or statistical non‐inferiority among the dosages. This echoes similar language from an antecedent New England Journal of Medicine Perspective: Although conducting noninferiority comparisons is probably infeasible in many small, biomarker‐defined subgroups of patients with cancer, early efficacy, safety, and exposure‐response data collected from a randomized trial would support more informed dose selection. The “reasonableness” criterion advanced here (Equations and ) aims to supply a rigorous basis for objective analysis, against the invitation to impressionistic judgment offered by the vague language “sufficient assessment” and “more informed dose selection.” We note that this criterion addresses directly “the major issue” motivating Project Optimus: It is very hard to retrofit a dose of the drug and I can't emphasize [enough] how important it is to try — and that's why we're spending all this time — to try to get it right up front, because: here again, you don't know then if, when you reduce a dose, will it have the same efficacy, and that's the major issue here. , at [1:08:18] The purely geometrical character of Figure underscores the genericity of this criterion, and of the minimum trial sizes it implies. But apart from this overt focus on trial size, the basic tools developed here may prove more broadly useful. For example, the objective tolerability notion expressed by τ may support rational comparisons of drug candidates in early development. The utility‐based optimization framework of Equations , and may stimulate empirical research on the efficacy‐toxicity trade‐off considerations of real patients. Whether 0.1 < η < 1.0 covers a relevant range of patient perspectives, and indeed whether Equation suitably expresses a utility commensurable with Equation , are hardly obvious and warrant empirical scrutiny. My greatest hope for this analysis is that it demonstrates the possibility of formalizing pharmacologic notions underlying dose–response investigations, and provokes a critical response that generates further progress in that direction.
D.C.N. designed and performed the research, analyzed the data, and wrote the manuscript.
This research received no external funding.
The author declared no competing interests for this work.
Data S1 Click here for additional data file.
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Report from the 4th Cardiovascular Outcome Trial (CVOT) Summit of the Diabetes & Cardiovascular Disease (D&CVD) EASD Study Group | fc6dc1d0-742e-4e38-a384-9829da5eee5f | 6410488 | Physiology[mh] | Coronary heart disease, cerebrovascular disease and peripheral arterial disease of atherosclerotic origin, collectively termed atherosclerotic cardiovascular disease (ASCVD), are the major cause of mortality in patients with diabetes mellitus . Diabetes patients experience an up to 50% increased risk of cardiovascular (CV)-related death . A variety of studies has shown that an improvement in glycaemic control can positively impact long-term CV disease (CVD) risk in patients with type 2 diabetes mellitus (T2DM) . However, other trials like the UGDP and ACCORD trial , as well as studies on muraglitazar and rosiglitazone , raised concerns for elevated CV risk . This prompted the Food and Drug Administration (FDA) to release a “Guidance for Industry” in 2008, for the evaluation of CV safety of new antidiabetic therapies in T2DM in order to prevent an inacceptable increase of CV risk . In consequence, CV outcome trials (CVOTs) for glucose lowering therapies were introduced. In CVOTs, combined CV endpoints are evaluated as primary outcome, usually including CV mortality, non-fatal myocardial infarction (MI) and non-fatal stroke (3-point major adverse CV event, 3P-MACE). Some trials include the hospitalisation rate for unstable angina pectoris as additional primary outcome (4P-MACE). Secondary outcomes often include hospitalisation for heart failure (HF), death from CV causes, all-cause mortality and renal outcomes. Since 2008, every newly approved glucose lowering drug has undergone a CVOT to evaluate its CV safety (hazard ratio (HR) < 1.8) . So far, this has encompassed four main classes of substances: (1) dipeptidyl-peptidase-4 inhibitors (DPP-4i) (SAVOR-TIMI 53—saxagliptin; EXAMINE—alogliptin; TECOS—sitagliptin); (2) glucagon-like peptide-1 receptor agonists (GLP-1 RA) (ELIXA—lixisenatide; LEADER—liraglutide; SUSTAIN-6—semaglutide; EXSCEL—exenatide); and (3) sodium/glucose co-transporter-2 inhibitors (SGLT-2i) (EMPA-REG OUTCOME—empagliflozin; CANVAS—canagliflozin) as well as two insulins (ORIGIN—insulin glargine; DEVOTE—insulin degludec) [ – ], previously summarised by Schnell et al. . In 2018, the list of published CVOTs was further increased with CARMELINA (linagliptin, DPP-4i) , Harmony Outcomes (albiglutide, GLP-1 RA) and DECLARE-TIMI 58 (dapagliflozin, SLGT-2i) . In addition, a CV safety study for alirocumab (ODYSSEY OUTCOMES), a proprotein convertase subtilisin/kexin type-9 inhibitor (PCSK-9i), was published . As in previous years [ – ], we present and summarise the key aspects discussed at the 4th CVOT Summit in October 2018.
A summary of characteristics and results of CVOTs published in 2018 is listed in Tables and . DPP-4 inhibitors The CARMELINA trial investigated the effect of once-daily linagliptin on CV and kidney outcomes in patients with T2DM at high risk of CV and kidney events. With respect to kidney outcomes, CARMELINA was the first DPP-4i CVOT to investigate a composite kidney outcome in a statistically adequately powered manner . Inclusion criteria for the 6979 patients comprised high risk of vascular events (e.g. history of MI, stroke or coronary artery disease) or impaired renal function with or without CV comorbidities . In the primary endpoint (3P-MACE: CV mortality, non-fatal MI and non-fatal stroke), linagliptin showed CV safety (HR 1.02 (95% CI 0.89–1.17), p < 0.001 for non-inferiority) compared to placebo but did not demonstrate a CV benefit. No significant benefit was observed in the secondary kidney composite outcome (HR 1.04 (95% CI 0.89–1.22), p = 0.62) compared to placebo. Exploratory kidney and microvascular outcomes showed a significant reduction of albuminuria progression (HR 0.86 (95% CI 0.78–0.95), p = 0.003) and a significant reduction in the composite microvascular endpoint (HR 0.86 (0.78–0.95), p = 0.003) in the linagliptin group compared to placebo . GLP-1 receptor agonists In the Harmony Outcomes CVOT, CV effects of once-weekly albiglutide in patients with T2DM were evaluated . A total of 6493 participants with approximately 100% prior CVD was followed for a median of 1.6 years and assessed for 3P-MACE. With respect to the primary outcome (3P-MACE: CV mortality, non-fatal MI and non-fatal stroke), albiglutide showed superiority compared to placebo (HR 0.78 (95% CI 0.68–0.90), p = 0.0006; p < 0.0001 for non-inferiority). Statistically significant secondary outcomes included a reduced expanded composite outcome (death from CVD, non-fatal MI, non-fatal stroke or urgent revascularisation for unstable angina; HR 0.78 (95% CI 0.69–0.90), p = 0.0005) and a reduction of fatal or non-fatal MI (HR 0.75 (95% CI 0.61–0.90), p = 0.003). Incidences of acute pancreatitis, pancreatic cancer and medullary thyroid carcinoma did not differ between the albiglutide and placebo group . SGLT-2 inhibitors CV safety of dapagliflozin was investigated in the DECLARE-TIMI 58 trial . The trial encompassed 17,160 patients who were followed during a median of 4.2 years. A hitherto unique aspect of the DECLARE-TIMI 58 trial was its high proportion of patients in primary prevention, as 59.4% of the enrolled patients had no prior ASCVD. Dapagliflozin showed non-inferiority to placebo with respect to 3P-MACE (p < 0.0001 for non-inferiority), yet not superiority (p = 0.17 for superiority). As pre-defined co-primary superiority endpoint, a significant reduction of CVD death or hospitalisation for HF (HR 0.83 (95% CI 0.73–0.95), p = 0.005) was demonstrated. In addition, reduction of the renal composite endpoint (≥ 40% decrease in estimated glomerular filtration rate (eGFR) to < 60 mL/min/1.73 m 2 , new end-stage renal disease or death from renal or cardiovascular causes; HR 0.76 (95% CI 0.67–0.87)) and reduction of death from any cause (HR 0.93 (95% CI 0.82–1.04)) were observed. Adverse events included a significant increase of diabetic ketoacidosis (0.3% vs. 0.1%, p = 0.02), a significant increase in the rate of genital infections (0.9% vs. 0.1%, p < 0.001) but no increase in the risk of amputation with dapagliflozin compared to placebo . PCSK-9 inhibition The ODYSSEY OUTCOMES study was designed to assess CV outcomes of alirocumab in 18,924 patients with prior acute coronary syndrome and low-density lipoprotein (LDL) cholesterol levels of at least 70 mg/dL, non-high-density lipoprotein (HDL) cholesterol levels of at least 100 mg/dL or an apolipoprotein B level of at least 80 mg/dL and who were receiving statin therapy at high or maximum tolerated dose . 28.5% of the alirocumab study population had diabetes mellitus. Alirocumab significantly decreased CV outcomes (composite of death from coronary heart disease, non-fatal MI, fatal or non-fatal ischemic stroke, or unstable angina requiring hospitalisation; HR 0.85 (95% CI 0.78–0.93), p < 0.001) compared to placebo. Secondary endpoints included a significant reduction of any coronary heart disease event (death from coronary heart disease, non-fatal MI, unstable angina requiring hospitalisation, and an ischemia-driven coronary revascularisation procedure, HR 0.88 (95% CI 0.81–0.95), p = 0.001) and a significant reduction of 3P-MACE (HR 0.86 (95% CI 0.79–0.93), p < 0.001) . The previously published study FOURIER investigated the CV safety of evolocumab in a set of 27,564 patients with ASCVD and LDL-cholesterol levels of 70 mg/dL or higher, who already were receiving statin therapy . 5% of this study population were patients with diabetes. Evolocumab demonstrated a CV benefit compared to placebo, with a significant decrease in the primary endpoint (cardiovascular death, MI, stroke, hospitalization for unstable angina, or coronary revascularization; HR 0.85 (95% CI 0.79 – 0.92), p<0.001) and the key secondary endpoint (cardiovascular death, MI, or stroke; HR 0.80 (95% CI 0.73 – 0.88), p<0.001). Positive effects were particularly observed regarding the CV risk reduction in patients with T2DM . Angiotensin-receptor–neprilysin-inhibitors (ARNI) HF has been shown to strongly correlate with diabetes with a significantly increased initial presentation. Also, a dramatic increase of HF incidence was demonstrated corresponding to increasing age of diabetes patients, compared to individuals without diabetes . At this summit, an additional option for the therapy of HF, the angiotensin-receptor–neprilysin-inhibition (ARNI) therapy, was discussed. In the PARADIGM-HF trial, ARNI (valsartan/sacubitril) was compared to enalapril. A significant reduction in the primary composite endpoint (death from CV causes or first hospitalisation for worsening HF, death from CV causes, hospitalisation for HF and death from any cause) was observed . A post hoc analysis of the PARADIGM-HF trial revealed that valsartan/sacubitril might have beneficial effects on the glucose metabolism in patients with known diabetes (98% T2DM) or an HbA1c ≥ 6.5% . The recently presented PIONEER-HF trial revealed that valsartan/sacubitril, compared to enalapril, also has a significantly greater effect on the reduction of brain natriuretic peptide (NT-proBNP) among patients with HF with reduced ejection fraction, who were hospitalised for acute decompensated HF . Also, no differences in the rates of worsening renal function, symptomatic hypotension, and hyperkalemia were observed . Thus, it can be concluded that ARNI might present a valuable therapy option for patients with diabetes and HF.
The CARMELINA trial investigated the effect of once-daily linagliptin on CV and kidney outcomes in patients with T2DM at high risk of CV and kidney events. With respect to kidney outcomes, CARMELINA was the first DPP-4i CVOT to investigate a composite kidney outcome in a statistically adequately powered manner . Inclusion criteria for the 6979 patients comprised high risk of vascular events (e.g. history of MI, stroke or coronary artery disease) or impaired renal function with or without CV comorbidities . In the primary endpoint (3P-MACE: CV mortality, non-fatal MI and non-fatal stroke), linagliptin showed CV safety (HR 1.02 (95% CI 0.89–1.17), p < 0.001 for non-inferiority) compared to placebo but did not demonstrate a CV benefit. No significant benefit was observed in the secondary kidney composite outcome (HR 1.04 (95% CI 0.89–1.22), p = 0.62) compared to placebo. Exploratory kidney and microvascular outcomes showed a significant reduction of albuminuria progression (HR 0.86 (95% CI 0.78–0.95), p = 0.003) and a significant reduction in the composite microvascular endpoint (HR 0.86 (0.78–0.95), p = 0.003) in the linagliptin group compared to placebo .
In the Harmony Outcomes CVOT, CV effects of once-weekly albiglutide in patients with T2DM were evaluated . A total of 6493 participants with approximately 100% prior CVD was followed for a median of 1.6 years and assessed for 3P-MACE. With respect to the primary outcome (3P-MACE: CV mortality, non-fatal MI and non-fatal stroke), albiglutide showed superiority compared to placebo (HR 0.78 (95% CI 0.68–0.90), p = 0.0006; p < 0.0001 for non-inferiority). Statistically significant secondary outcomes included a reduced expanded composite outcome (death from CVD, non-fatal MI, non-fatal stroke or urgent revascularisation for unstable angina; HR 0.78 (95% CI 0.69–0.90), p = 0.0005) and a reduction of fatal or non-fatal MI (HR 0.75 (95% CI 0.61–0.90), p = 0.003). Incidences of acute pancreatitis, pancreatic cancer and medullary thyroid carcinoma did not differ between the albiglutide and placebo group .
CV safety of dapagliflozin was investigated in the DECLARE-TIMI 58 trial . The trial encompassed 17,160 patients who were followed during a median of 4.2 years. A hitherto unique aspect of the DECLARE-TIMI 58 trial was its high proportion of patients in primary prevention, as 59.4% of the enrolled patients had no prior ASCVD. Dapagliflozin showed non-inferiority to placebo with respect to 3P-MACE (p < 0.0001 for non-inferiority), yet not superiority (p = 0.17 for superiority). As pre-defined co-primary superiority endpoint, a significant reduction of CVD death or hospitalisation for HF (HR 0.83 (95% CI 0.73–0.95), p = 0.005) was demonstrated. In addition, reduction of the renal composite endpoint (≥ 40% decrease in estimated glomerular filtration rate (eGFR) to < 60 mL/min/1.73 m 2 , new end-stage renal disease or death from renal or cardiovascular causes; HR 0.76 (95% CI 0.67–0.87)) and reduction of death from any cause (HR 0.93 (95% CI 0.82–1.04)) were observed. Adverse events included a significant increase of diabetic ketoacidosis (0.3% vs. 0.1%, p = 0.02), a significant increase in the rate of genital infections (0.9% vs. 0.1%, p < 0.001) but no increase in the risk of amputation with dapagliflozin compared to placebo .
The ODYSSEY OUTCOMES study was designed to assess CV outcomes of alirocumab in 18,924 patients with prior acute coronary syndrome and low-density lipoprotein (LDL) cholesterol levels of at least 70 mg/dL, non-high-density lipoprotein (HDL) cholesterol levels of at least 100 mg/dL or an apolipoprotein B level of at least 80 mg/dL and who were receiving statin therapy at high or maximum tolerated dose . 28.5% of the alirocumab study population had diabetes mellitus. Alirocumab significantly decreased CV outcomes (composite of death from coronary heart disease, non-fatal MI, fatal or non-fatal ischemic stroke, or unstable angina requiring hospitalisation; HR 0.85 (95% CI 0.78–0.93), p < 0.001) compared to placebo. Secondary endpoints included a significant reduction of any coronary heart disease event (death from coronary heart disease, non-fatal MI, unstable angina requiring hospitalisation, and an ischemia-driven coronary revascularisation procedure, HR 0.88 (95% CI 0.81–0.95), p = 0.001) and a significant reduction of 3P-MACE (HR 0.86 (95% CI 0.79–0.93), p < 0.001) . The previously published study FOURIER investigated the CV safety of evolocumab in a set of 27,564 patients with ASCVD and LDL-cholesterol levels of 70 mg/dL or higher, who already were receiving statin therapy . 5% of this study population were patients with diabetes. Evolocumab demonstrated a CV benefit compared to placebo, with a significant decrease in the primary endpoint (cardiovascular death, MI, stroke, hospitalization for unstable angina, or coronary revascularization; HR 0.85 (95% CI 0.79 – 0.92), p<0.001) and the key secondary endpoint (cardiovascular death, MI, or stroke; HR 0.80 (95% CI 0.73 – 0.88), p<0.001). Positive effects were particularly observed regarding the CV risk reduction in patients with T2DM .
HF has been shown to strongly correlate with diabetes with a significantly increased initial presentation. Also, a dramatic increase of HF incidence was demonstrated corresponding to increasing age of diabetes patients, compared to individuals without diabetes . At this summit, an additional option for the therapy of HF, the angiotensin-receptor–neprilysin-inhibition (ARNI) therapy, was discussed. In the PARADIGM-HF trial, ARNI (valsartan/sacubitril) was compared to enalapril. A significant reduction in the primary composite endpoint (death from CV causes or first hospitalisation for worsening HF, death from CV causes, hospitalisation for HF and death from any cause) was observed . A post hoc analysis of the PARADIGM-HF trial revealed that valsartan/sacubitril might have beneficial effects on the glucose metabolism in patients with known diabetes (98% T2DM) or an HbA1c ≥ 6.5% . The recently presented PIONEER-HF trial revealed that valsartan/sacubitril, compared to enalapril, also has a significantly greater effect on the reduction of brain natriuretic peptide (NT-proBNP) among patients with HF with reduced ejection fraction, who were hospitalised for acute decompensated HF . Also, no differences in the rates of worsening renal function, symptomatic hypotension, and hyperkalemia were observed . Thus, it can be concluded that ARNI might present a valuable therapy option for patients with diabetes and HF.
On 4 October 2018, new treatment algorithms for T2DM were published based on knowledge gained from CVOTs . In contrast to previous suggestions, the new treatment algorithm recommends a highly patient centred, individualised approach of treatment instead of pushing towards standardised treatment goals. As before, guidelines recommend metformin and lifestyle changes as primary treatment option. Major changes were introduced for second- and third-line therapy: before choosing a second-line therapy, practitioners are encouraged to differentiate between present comorbidities and escalate the therapy accordingly and individually. In case of established CVD, if ASCVD predominates, GLP-1 RA with proven CV benefit or SGLT-2i with proven CV benefit (if eGFR adequate) are recommended. If HF or chronic kidney disease (CKD) predominate, SGLT-2i with evidence of reducing HF and/or CKD progression in CVOTs (if eGFR is adequate) are recommended . In cases without ASCVD, HF or CKD, various choices are offered, depending on the individual patient or setting: if there is a compelling need to minimise hypoglycaemia, if weight gain needs minimising or if costs are a major issue. For injectable therapies, step-wise therapy escalation is recommended, again considering GLP-1 RA options before insulin .
For the treatment of diabetes, CVOTs only evaluate effects of selected glucose lowering agents for T2DM, yet not combinatory approaches. Hence, the question of efficacy of these agents (i.e. SGLT-2 inhibitors) in adjunct therapy of T1DM was addressed. Last but not least, parallel to this year’s CVOT Summit, a FDA advisory board re-evaluated the benefit and perpetuation of CVOTs. Likewise, this was debated at the 4th CVOT Summit. Adjunct therapy in T1DM As in T2DM, T1DM is associated with a considerably increased risk of CV events which were shown to occur at a younger age than in non-diabetic individuals . Variations in glucose level and hyperglycaemia in children with T1DM have been associated with persistent cognitive dysfunction and both, hyper- and hypoglycaemia were linked to various adverse CV events , although the relationship of severe hypoglycaemia in T2DM seems to be bi-directional . However, as patients with T1DM are mainly treated with insulin, CV safety of new glucose lowering agents was only investigated in the context of T2DM. As of now, a variety of studies has started to investigate the use of glucose lowering medication typically used in T2DM, like metformin, pramlintide, GLP-1 RA, SGLT-2i and dual SGLT-1 and -2i as adjunctive therapy for T1DM, particularly in patients who have inadequate insulin control and/or are overweight . When looking at GLP-1 RA (liraglutide and exenatide) as adjunct therapy in T1DM, one is confronted with significant inter-study variability regarding reduction of HbA1c, postprandial plasma glucose and insulin doses (summarised in ). In the ADJUNCT ONE trial , evaluating the use of liraglutide as adjunctive therapy in T1DM, inconsistent results regarding HbA1c reduction and reduction of daily insulin dose were obtained across three liraglutide doses compared to placebo. Adverse events included increased rates of symptomatic hypoglycaemia and an increase in hyperglycaemia with ketosis . Various studies investigated the efficacy of SGLT-2i (empagliflozin , dapagliflozin , canagliflozin and the dual SGLT-1 and -2i sotagliflozin ) in the treatment of T1DM. All studies reported a significant decrease in HbA1c [ – ] and some also reductions in body weight [ , – ] and daily insulin dose . Adverse events included an increase in genital infections and diabetic ketoacidosis (DKA) . Strategies for the prevention of DKA need to be further established and defined. The strong educational need of health care professionals and diabetes teams was highlighted. It can be summarised that, although no direct comparison of T1DM and T2DM can be made, agents demonstrating CV safety in CVOTs may also exert beneficial effects when provided as adjunct therapy in T1DM. However, more and larger studies are needed to evaluate if CV safety or benefit demonstrated for those agents in T2DM, next to reductions in HbA1c, bodyweight and insulin dose, also hold true in T1DM. Diabetes comorbidities: “Is the future of the treatment of diabetes with CVD in the hands of general practitioners, diabetologists, cardiologists, nephrologists?” During the 4th CVOT Summit, the question of whose responsibility the treatment of diabetes with CVD should be in future arose—general practitioners (GPs), diabetologists, cardiologists or nephrologists. All disciplines are tightly interwoven in the field of diabetes, also reflected in the spectrum of available treatment options. Looking at patient numbers only, GPs and diabetologists might treat the majority of diabetes patients. However, CVOTs have provided further knowledge on CV and renal comorbidities, making integration of cardiologists and nephrologists in treatment of diabetes indispensable and/or promote further training of diabetologists in cardiovascular disease and of cardiologists in diabetes. Thus, CVOTs promoted the exchange of knowledge and tightened the close network between disciplines, also reflected in the new ADA/EASD consensus statement and future guidelines. CVOTs in diabetes: how should we continue? On the 10 year anniversary of the FDA “Guidance for Industry” in 2018, a FDA advisory board re-evaluated the benefit and perpetuation of CVOTs, parallel to the 4th CVOT Summit in October 2018. Among the issues addressed by the FDA advisory board were: (1) the impact of the recommendations in the 2008 “Guidance for Industry” on the assessment of CV risk for drugs indicated to improve glycaemic control in patients with T2DM; (2) the transferability of CV safety findings from members of a drug class to the entire class of drugs, and (3) whether an inacceptable increase in CV risk needs to be excluded for all new drugs to improve glycaemic control in patients with T2DM, regardless of the presence or absence of a signal for CV risk in the development program . The FDA panel voted for continuation, yet improvement of CVOTs . Questions of similar manner were discussed at the 4th CVOT Summit. On the one hand, positive aspects of CVOTs were reflected by, for example, the detection of unexpected benefits as observed in EMPA-REG OUTCOME , CANVAS , DECLARE-TIMI 58 , LEADER , SUSTAIN-6 and Harmony Outcomes . These benefits often are not restricted to CV endpoints; e.g. the CANVAS trial revealed a positive effect of canagliflozin on renal outcomes . These safety and benefit analyses led to the refinement of treatment algorithms as stated in the 2018 ADA/EASD Consensus Statement and the integration of new drugs as “preferred” or “safe” second- or third-line therapy into new guidelines . On the other hand, limitations of current CVOTs, such as the lack of generalisability (i.e. participants often are at high risk for a CV event or death, thus not representative for a larger population), relatively short time-lines for assessing potential harms or benefits and the placebo-controlled design of CVOTs were addressed. Room for improvement of cost-effectiveness and cost-sharing options as well as modification of end points and analyses were also discussed . In summary, concomitant with the FDA panel vote, it was concluded that continuation but modification of CVOTs is highly beneficial as they provide safety aspects relevant to all T2DM patients and create a broad body of evidence to base new guidelines and therapies on.
As in T2DM, T1DM is associated with a considerably increased risk of CV events which were shown to occur at a younger age than in non-diabetic individuals . Variations in glucose level and hyperglycaemia in children with T1DM have been associated with persistent cognitive dysfunction and both, hyper- and hypoglycaemia were linked to various adverse CV events , although the relationship of severe hypoglycaemia in T2DM seems to be bi-directional . However, as patients with T1DM are mainly treated with insulin, CV safety of new glucose lowering agents was only investigated in the context of T2DM. As of now, a variety of studies has started to investigate the use of glucose lowering medication typically used in T2DM, like metformin, pramlintide, GLP-1 RA, SGLT-2i and dual SGLT-1 and -2i as adjunctive therapy for T1DM, particularly in patients who have inadequate insulin control and/or are overweight . When looking at GLP-1 RA (liraglutide and exenatide) as adjunct therapy in T1DM, one is confronted with significant inter-study variability regarding reduction of HbA1c, postprandial plasma glucose and insulin doses (summarised in ). In the ADJUNCT ONE trial , evaluating the use of liraglutide as adjunctive therapy in T1DM, inconsistent results regarding HbA1c reduction and reduction of daily insulin dose were obtained across three liraglutide doses compared to placebo. Adverse events included increased rates of symptomatic hypoglycaemia and an increase in hyperglycaemia with ketosis . Various studies investigated the efficacy of SGLT-2i (empagliflozin , dapagliflozin , canagliflozin and the dual SGLT-1 and -2i sotagliflozin ) in the treatment of T1DM. All studies reported a significant decrease in HbA1c [ – ] and some also reductions in body weight [ , – ] and daily insulin dose . Adverse events included an increase in genital infections and diabetic ketoacidosis (DKA) . Strategies for the prevention of DKA need to be further established and defined. The strong educational need of health care professionals and diabetes teams was highlighted. It can be summarised that, although no direct comparison of T1DM and T2DM can be made, agents demonstrating CV safety in CVOTs may also exert beneficial effects when provided as adjunct therapy in T1DM. However, more and larger studies are needed to evaluate if CV safety or benefit demonstrated for those agents in T2DM, next to reductions in HbA1c, bodyweight and insulin dose, also hold true in T1DM.
During the 4th CVOT Summit, the question of whose responsibility the treatment of diabetes with CVD should be in future arose—general practitioners (GPs), diabetologists, cardiologists or nephrologists. All disciplines are tightly interwoven in the field of diabetes, also reflected in the spectrum of available treatment options. Looking at patient numbers only, GPs and diabetologists might treat the majority of diabetes patients. However, CVOTs have provided further knowledge on CV and renal comorbidities, making integration of cardiologists and nephrologists in treatment of diabetes indispensable and/or promote further training of diabetologists in cardiovascular disease and of cardiologists in diabetes. Thus, CVOTs promoted the exchange of knowledge and tightened the close network between disciplines, also reflected in the new ADA/EASD consensus statement and future guidelines.
On the 10 year anniversary of the FDA “Guidance for Industry” in 2018, a FDA advisory board re-evaluated the benefit and perpetuation of CVOTs, parallel to the 4th CVOT Summit in October 2018. Among the issues addressed by the FDA advisory board were: (1) the impact of the recommendations in the 2008 “Guidance for Industry” on the assessment of CV risk for drugs indicated to improve glycaemic control in patients with T2DM; (2) the transferability of CV safety findings from members of a drug class to the entire class of drugs, and (3) whether an inacceptable increase in CV risk needs to be excluded for all new drugs to improve glycaemic control in patients with T2DM, regardless of the presence or absence of a signal for CV risk in the development program . The FDA panel voted for continuation, yet improvement of CVOTs . Questions of similar manner were discussed at the 4th CVOT Summit. On the one hand, positive aspects of CVOTs were reflected by, for example, the detection of unexpected benefits as observed in EMPA-REG OUTCOME , CANVAS , DECLARE-TIMI 58 , LEADER , SUSTAIN-6 and Harmony Outcomes . These benefits often are not restricted to CV endpoints; e.g. the CANVAS trial revealed a positive effect of canagliflozin on renal outcomes . These safety and benefit analyses led to the refinement of treatment algorithms as stated in the 2018 ADA/EASD Consensus Statement and the integration of new drugs as “preferred” or “safe” second- or third-line therapy into new guidelines . On the other hand, limitations of current CVOTs, such as the lack of generalisability (i.e. participants often are at high risk for a CV event or death, thus not representative for a larger population), relatively short time-lines for assessing potential harms or benefits and the placebo-controlled design of CVOTs were addressed. Room for improvement of cost-effectiveness and cost-sharing options as well as modification of end points and analyses were also discussed . In summary, concomitant with the FDA panel vote, it was concluded that continuation but modification of CVOTs is highly beneficial as they provide safety aspects relevant to all T2DM patients and create a broad body of evidence to base new guidelines and therapies on.
The 4th CVOT Summit of the D&CVD EASD Study Group discussed key results of recently completed and published CVOTs in T2DM (CARMELINA, Harmony Outcomes, and DECLARE-TIMI 58) and CV safety studies of PCSK-9 inhibition (ODYSSEY OUTCOMES) in an interactive, multi-disciplinary format. The summit considered both potentials and limitations of current CVOT designs as well as the implementation of CVOTs in the newly published guidelines by the ADA/EASD consensus statement. Learnings for adjunct therapy of T1DM and continuation and modification of CVOT trials were discussed. The D&CVD EASD Study Group will continue its activity. In-depth discussions and presentations of upcoming CVOTs like REWIND, PIONEER-6, VERTIS CV Study or CREDENCE, will be resumed at the 5th CVOT Summit, which will be held from 24–25 October 2019 in Munich ( http://www.cvot.org ).
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Oral screening of dental calculus, gingivitis and dental caries through segmentation on intraoral photographic images using deep learning | b35cef34-d5de-4348-9c45-f22b7a96cbc3 | 11515110 | Dentistry[mh] | With urbanization and changes in living environments, the global prevalence of oral diseases is increasing, mainly driven by modifiable factors such as sugar consumption, tobacco and alcohol use, and personal hygiene practices. According to the 2022 Global State of Oral Health Report , nearly 3.5 billion people worldwide suffer from oral diseases, three-quarters of them in middle-income countries. Although most oral problems can be prevented and treated early, the shortage of oral doctors and the imbalance of medical resources aggravate the problem of patients’ difficulty in accessing medical services, and even lead to the deterioration of the disease, increase the cost of treatment, and even endanger life. The advent of oral endoscopy technology has opened up new possibilities for oral medicine. By providing high-resolution images of the interior of the mouth, this technology allows more precise observation of lesions and abnormalities, and is widely used in the diagnosis, treatment and evaluation of periodontal diseases . Compared with traditional oral examination equipment, although the price of oral endoscopy is higher, it can avoid problems such as limited visual field and inaccurate positioning, improve diagnostic accuracy and treatment effect, and reduce complications and recovery time. With the continuous advancement of technology and the intensification of market competition, the price of endoscopes may gradually decrease. Recent studies have shown that the application of deep learning technology in combination with oral endoscopy in the diagnosis of dental caries has provided implications for the development of new standardized techniques, making early detection of oral diseases more convenient, providing long-term benefits to patients, and alleviating medical shortages, especially in remote areas. With the continuous development of deep learning technology, its ability to automatically learn at a deep level and discriminating features from data has been applied to the field of medical image segmentation .Among fully supervised segmentation models, FCN based on end-to-end learning is a typical segmentation model . The modified U-Net algorithm based on FCN and its improved network structure methods such as 3D U-Net , Res-UNet , U-Net++ and UNet3+ are widely used because of their high precision in the segmentation task of tissues, organs, or lesions on medical images . In the oral area, U-Net has also been widely used, such as segmentation of the degree of dental caries lesions based on U-Net . However, U-Net also has some problems, which require a large number of data sets for training; otherwise, it is easy to generate overfitting and consume huge computing resources. Recently, structured state space models (SSMs) has attracted wide attention, because the Mamba model proposed by Albert Gu realizes the integration of RNN’s stepwise processing capability and CNN’s global information processing capability through the framework of SSMs, and introduces innovative selective mechanism and hardware sensing algorithm. Mamba has successfully solved the problem of computational efficiency when processing long sequence data, demonstrating excellent performance and efficiency when processing various sequence data, especially language, audio and genomics data. Improved Mamba-based models have also been applied in the medical field. U-Mamba proposed the hybrid model SSM-CNN for 3D abdominal organ segmentation on CT and MR images, instrument segmentation in endoscopic images, and cell segmentation in microscope images. SegMamba combines the U-shaped structure with Mamba and is specially used in 3D medical image segmentation. Swin-UMamba has shown tremendous superior performance on abdominal MRI, colonoscopy, and microscopy datasets. It can be said that Mamba has great potential in the medical field. Therefore, this study aims to develop a system that incorporates an oral endoscopic image segmentation method based on Mamba (Oral-Mamba) and an intelligent evaluation model of dental calculus degree. However, since the deep learning model requires the support of a large amount of training data and currently there is no data set that can be applied to the segmentation of oral endoscopy images, we produced more than 3000 oral endoscopy image data sets containing label samples. The system has high precision and fast speed, including visual analysis report of the lesion area, which can help the patient to see the condition intuitively and carry out treatment as early as possible.
Data and annotation All oral endoscopy image data collected in this study was collected by the network and screened by doctors in dental offices based on actual scenarios, with a total of 3365 oral endoscopy images collected.We verified the versatility of the deep learning method based on the similarity of oral endoscope images. Because it is an auxiliary screening, even if the population and sample, eligibility criteria, location, and dates are changed, our method still has generalization performance. The sample displayed at the top of Fig. is part of a collection of images containing gingivitis, dental caries, or dental calculus. It is important to note that the image data used in this study are all public or have been authorized by patients, and all are anonymous and do not contain patient information. We annotated our dataset using an interactive semi-automatic image segmentation annotation tool based on Segment Anything Model(SAM). Since our research is to judge gingivitis, dental caries and dental calculus, our labeling work is to outline the contour of the lesion area of these three types with points in the image, and the final mask will form a connected domain according to these points, as shown in (bottom of Fig. ) (The dental calculus marked in the pictures of this study refers to supragingival calculus).In addition, we will also add a degree label to the data with dental calculus, and the basis for degree judgment is: Degree 0: No soft scale and dental calculus; Degree 1: A little soft scale or dental calculus, but not more than l/3 of the tooth surface; Degree 2: There are dental calculus, more than 1/3 of the crown, there are a small number of subgingival calculus; Degree 3: The dental calculus does not exceed 2/3 of the crown; there is more subgingival calculus. The dental calculus degree label is used to train the intelligent evaluation model of dental calculus degree. The labeling work is carried out by doctors with rich clinical experience in the dental clinic together with us, and finally all the labeling is reviewed and approved by a review team composed of doctors. Prior to the annotation and review process, each clinician and reviewer was instructed and calibrated to segmentation tasks using standardized protocols. Deep learning method The system we studied is divided into two phases: Oral-Mamba and the intelligent evaluation model of dental calculus degree. Among them, Oral-Mamba is used to detect gingivitis, dental caries and dental calculus.And the intelligent evaluation model of dental calculus degree is used to judge the degree of dental calculus. Oral-Mamba Our study of Oral-Mamba (Fig. ) is improved based on the structure of the U-Net network, which passes through a Mamba block in the bottleneck (Fig. a). U-Net is used to obtain contextual and location information. U-Net itself is a very simple structure and is composed of two parts, the first half of the downsampling for feature extraction and the second half of the feature upsampling, called the encoder-decoder structure. The encoder gradually reduces the spatial dimension of the pooling layer, and the decoder gradually repairs the detail and spatial dimension of the object. There is usually a skip connection between the encoder and the decoder, so it helps the decoder better repair the details of the target. U-Net integrates the characteristics of higher and lower features, which helps us to identify and locate gingivitis, dental caries or dental calculus. The Mamba block in the Oral-Mamba network structure (Fig. a) is the core module of the Oral-Mamba network structure, which contains Selective State Space Models. First, let us introduce State Space Model(SSM). SSM is the most recent class of sequential models for deep learning. It is inspired by a special continuous system for describing hidden state representations and making next state predictions based on some input. 1 [12pt]{minimal}
$$ state \ equation: h^{ }(t)=A h(t)+B x(t) $$ s t a t e e q u a t i o n : h ′ ( t ) = A h ( t ) + B x ( t ) 2 [12pt]{minimal}
$$ output \ equation: y(t)=C h(t) $$ o u t p u t e q u a t i o n : y ( t ) = C h ( t ) Where [12pt]{minimal}
$$A R^{N N}$$ A ∈ R N × N , B , [12pt]{minimal}
$$C R^{N}$$ C ∈ R N , N is the number of variables in the state space. Matrix A describes how all the internal states are connected because they represent the underlying representation of the system. It is initialized on the basis of HiPPO theory. HiPPO’s model combines the concepts of Recurrent Memory and Optimal Polynomial Projections. This projection technique can significantly improve the performance of Recurrent Memory and solve the problem of remote dependence in processing long sequence data. By visualizing equations (1) and (2), we can obtain the architecture as shown in Fig. b. Since the oral endoscopy photos are discrete inputs, we also discretize the model using zero-order holding techniques: 3 [12pt]{minimal}
$$ & = ( A)=}( x_{t}) ) } \\ & = ( -{ {Linear}}( x_{t}) ) = 1- ( { {Linear}}( x_{t}) ) $$ A ¯ = exp ( Δ A ) = 1 1 + exp Linear x t = σ - Linear x t = 1 - σ Linear x t 4 [12pt]{minimal}
$$ & = ( A)^{-1}( ( A)-I) B \\ & = -( ( A)-I)=1-= ( { {Linear}}( x_{t}) ) $$ B ¯ = ( Δ A ) - 1 ( exp ( Δ A ) - I ) · Δ B = - ( exp ( Δ A ) - I ) = 1 - A ¯ = σ Linear x t After discretization, the calculation method is selected according to the task. In the training process, we use a convolution representation that can be parallelized, and in the inference process, we use an efficient circular representation, which can achieve efficient calculation of linear complexity: 5a [12pt]{minimal}
$$ h_t=h_{t-1}+x_t$$ h t = A ¯ h t - 1 + B ¯ x t 5b [12pt]{minimal}
$$ y_t=Ch_t $$ y t = C h t 6a [12pt]{minimal}
$$ }}=(C,C}}, ,C^k, )$$ K ¯ = ( C B ¯ , C AB ¯ , … , C A ¯ k B ¯ , … ) 6b [12pt]{minimal}
$$ y=x*}} $$ y = x ∗ K ¯ In order to make the model filter out irrelevant information and remember relevant information indefinitely, and have the characteristics of SSM, Mamba modifies the SSM by using Selective SSM, which selectively processes information and includes the entire history information, creating a very effective small state. At the same time, the hardware sensing algorithm is introduced to further improve the computing efficiency. In the Mamba block, the input data is first divided into two branches. In the first branch, the data goes through a linear layer for a basic transformation and is immediately passed to the SiLU activation function. SiLU is a smooth non-linear function that adaptively adjusts the activation level based on the input, which helps the model capture more complex feature relationships. At the same time, the data in the second branch also passes through a linear layer and then into a deeply separable convolution layer that is specifically designed to efficiently learn features at the spatial level. The output of the depth-separable convolution is further enhanced by the SiLU activation function and finally fed into a Selective state space models. The output of the two branches is then combined by a multiplication operation, which is designed to synthesize the information in the two branches while preserving each’s unique contribution. Finally, a linear layer is used to reconcile the output data of these features. Intelligent evaluation model of dental calculus degree From the perspective of clinical diagnosis, the degree of dental calculus is assessed based on the adhesion of the dental calculus to the surface of the tooth and the gingival margin. Therefore, we designed an intelligent evaluation algorithm for the degree of dental calculus based on the adhesion of dental calculus to the tooth surface and the gingival margin (Fig. ).Our intelligent evaluation model of dental calculus degree is designed based on the structure of the CNN network. The area of the lesion marked as dental calculus after Oral-Mamba will continue to judge the degree of dental calculus in the next stage using the intelligent evaluation algorithm of the degree of dental calculus. We used Segment Anything Model (SAM) , a pioneering basic model with rapid segmentation that has recently gained widespread attention, to automatically label the tooth surface and gingival margin of the original image of dental calculus.Then, the image with dental calculus mask and the image with tooth surface and gingival margin mask are fused as original data and entered into the intelligent evaluation model of dental calculus degree. After extracting features through convolution layer, activation function and pooling layer, the full connection layer can classify the degree of dental calculus, and finally a probability distribution diagram of 0,1, 2 and 3 degrees of dental calculus will be obtained. The degree of dental calculus with the highest probability is the final output result. We feed the image into the network. Firstly, medical image segmentation was performed by Oral-Mamba, and gingivitis, dental caries or dental calculus lesion areas were detected. The degree of dental calculus was then intelligibly diagnosed in the images with dental calculus lesions to determine the degree of dental calculus. Finally, visual results of gingivitis,dental caries and dental calculus lesion areas and the degree of dental calculus were output (Fig. ). Training strategy of deep learning model We randomly assigned the 3365 acquired oral endoscopy images into 3 subsets, with a 6: 2: 2 ratio. 60% of the data set is used for training, 20% for validation, and the remaining 20% for testing. So, the training set contains 2019 images, the verification set contains 673 images, and the test set contains 673 images. For training, K-fold cross-validation is applied and learned by sequentially replacing individual verification sets. For each training, the network was trained on 400 epochs, optimized using stochastic gradient descent with an initial learning rate of 1e-2. During training, we adopted the combination of Dice loss and cross entropy to segment and classify areas of gingivitis, dental caries, or dental calculus lesion, which can provide better performance in various tasks and scenarios . The loss function is defined as: 7 [12pt]{minimal}
$$ L & = ( - _{i=1}^{N} ( t_{i} p_{i}) . . +(1- )[ ( 1-t_{i}) ( 1-p_{i}) ] ) \\ & -(1- ) _{i=1}^{K}( ^{N} p_{i} t_{i}+S}{ _{i=1}^{N} p_{i}+ _{i=1}^{N} t_{i}+S}) $$ L = α - 1 N ∑ i = 1 N β t i ln p i + ( 1 - β ) 1 - t i ln 1 - p i - ( 1 - α ) ∑ i = 1 K 2 ∑ i = 1 N p i t i + S ∑ i = 1 N p i + ∑ i = 1 N t i + S The model was trained using NVIDIA RTX4060Ti GPU and 14th Gen Intel(R) Core(TM) i7-14700K CPU, and deep learning frameworks PyTorch 1.11, Cuda 11.4, and cuDNN 8.2. Statistical analysis In order to evaluate the overall performance of the Oral-Mamba network architecture we designed, we evaluated the results of the test set and the real results labeled by the physician in the model prediction. Meanwhile, we use U-Net, a popular medical image segmentation network, to compare its segmentation performance with that of Oral-Mamba. U-Net is one of the popular deep networks for medical image analysis. It consists of an encoder path with five levels for capturing context, and a symmetric decoder path for restoring image resolution to the input image resolution. U-Net has about 7.7 million trainable parameters. The metrics commonly used for evaluation include precision, accuracy, recall, and IoU, all of which are pixel-level comparisons that provide a comprehensive evaluation of the segmentation results. Intersection over Union (IoU): The IoU measures the degree of overlap between the predicted segmentation results and the real labels. It is defined by calculating the ratio of the intersection region between the predicted segmentation result and the real label to their union region. The closer the IoU is to 1, the higher the degree of overlap between the predicted result and the real label, and the better the segmentation effect. IoU is calculated as follows: 8 [12pt]{minimal}
$$ IoU= $$ I o U = TP T P + F P + F N Recall: The recall measures the proportion of true positive cases that are correctly predicted. In image segmentation, the recall represents the ratio of predicted positive example pixels to real positive example pixels, and a high recall means that the algorithm can capture more real positive examples to avoid omissions. Its calculation formula is as follows: 9 [12pt]{minimal}
$$ Recall= $$ R e c a l l = TP T P + F N Precision: Precision measures the proportion of all predicted positive examples that are actually positive. In image segmentation, precision represents the ratio between real example pixels and all pixels predicted as positive examples. The high-precision representation algorithm can accurately identify positive example pixels and reduce misrecognition. Its calculation formula is as follows: 10 [12pt]{minimal}
$$ Precision= $$ P r e c i s i o n = TP T P + F P Accuracy: Accuracy measures the ratio of all correctly classified pixels to the total number of pixels. In image segmentation, accuracy represents the ratio between the number of correctly classified pixels and the total number of pixels. Its calculation formula is as follows: 11 [12pt]{minimal}
$$ Accuracy= $$ A c c u r a c y = T P + T N T P + T N + F P + F N Among them, TP is the number of pixels of the true example (correctly classified as a positive example), FP is the number of pixels of the false positive example (incorrectly classified as a positive example), FN is the number of pixels of the false negative example (incorrectly classified as a negative example), and TN is the number of pixels of the true negative example (correctly classified as a negative example).
All oral endoscopy image data collected in this study was collected by the network and screened by doctors in dental offices based on actual scenarios, with a total of 3365 oral endoscopy images collected.We verified the versatility of the deep learning method based on the similarity of oral endoscope images. Because it is an auxiliary screening, even if the population and sample, eligibility criteria, location, and dates are changed, our method still has generalization performance. The sample displayed at the top of Fig. is part of a collection of images containing gingivitis, dental caries, or dental calculus. It is important to note that the image data used in this study are all public or have been authorized by patients, and all are anonymous and do not contain patient information. We annotated our dataset using an interactive semi-automatic image segmentation annotation tool based on Segment Anything Model(SAM). Since our research is to judge gingivitis, dental caries and dental calculus, our labeling work is to outline the contour of the lesion area of these three types with points in the image, and the final mask will form a connected domain according to these points, as shown in (bottom of Fig. ) (The dental calculus marked in the pictures of this study refers to supragingival calculus).In addition, we will also add a degree label to the data with dental calculus, and the basis for degree judgment is: Degree 0: No soft scale and dental calculus; Degree 1: A little soft scale or dental calculus, but not more than l/3 of the tooth surface; Degree 2: There are dental calculus, more than 1/3 of the crown, there are a small number of subgingival calculus; Degree 3: The dental calculus does not exceed 2/3 of the crown; there is more subgingival calculus. The dental calculus degree label is used to train the intelligent evaluation model of dental calculus degree. The labeling work is carried out by doctors with rich clinical experience in the dental clinic together with us, and finally all the labeling is reviewed and approved by a review team composed of doctors. Prior to the annotation and review process, each clinician and reviewer was instructed and calibrated to segmentation tasks using standardized protocols.
The system we studied is divided into two phases: Oral-Mamba and the intelligent evaluation model of dental calculus degree. Among them, Oral-Mamba is used to detect gingivitis, dental caries and dental calculus.And the intelligent evaluation model of dental calculus degree is used to judge the degree of dental calculus. Oral-Mamba Our study of Oral-Mamba (Fig. ) is improved based on the structure of the U-Net network, which passes through a Mamba block in the bottleneck (Fig. a). U-Net is used to obtain contextual and location information. U-Net itself is a very simple structure and is composed of two parts, the first half of the downsampling for feature extraction and the second half of the feature upsampling, called the encoder-decoder structure. The encoder gradually reduces the spatial dimension of the pooling layer, and the decoder gradually repairs the detail and spatial dimension of the object. There is usually a skip connection between the encoder and the decoder, so it helps the decoder better repair the details of the target. U-Net integrates the characteristics of higher and lower features, which helps us to identify and locate gingivitis, dental caries or dental calculus. The Mamba block in the Oral-Mamba network structure (Fig. a) is the core module of the Oral-Mamba network structure, which contains Selective State Space Models. First, let us introduce State Space Model(SSM). SSM is the most recent class of sequential models for deep learning. It is inspired by a special continuous system for describing hidden state representations and making next state predictions based on some input. 1 [12pt]{minimal}
$$ state \ equation: h^{ }(t)=A h(t)+B x(t) $$ s t a t e e q u a t i o n : h ′ ( t ) = A h ( t ) + B x ( t ) 2 [12pt]{minimal}
$$ output \ equation: y(t)=C h(t) $$ o u t p u t e q u a t i o n : y ( t ) = C h ( t ) Where [12pt]{minimal}
$$A R^{N N}$$ A ∈ R N × N , B , [12pt]{minimal}
$$C R^{N}$$ C ∈ R N , N is the number of variables in the state space. Matrix A describes how all the internal states are connected because they represent the underlying representation of the system. It is initialized on the basis of HiPPO theory. HiPPO’s model combines the concepts of Recurrent Memory and Optimal Polynomial Projections. This projection technique can significantly improve the performance of Recurrent Memory and solve the problem of remote dependence in processing long sequence data. By visualizing equations (1) and (2), we can obtain the architecture as shown in Fig. b. Since the oral endoscopy photos are discrete inputs, we also discretize the model using zero-order holding techniques: 3 [12pt]{minimal}
$$ & = ( A)=}( x_{t}) ) } \\ & = ( -{ {Linear}}( x_{t}) ) = 1- ( { {Linear}}( x_{t}) ) $$ A ¯ = exp ( Δ A ) = 1 1 + exp Linear x t = σ - Linear x t = 1 - σ Linear x t 4 [12pt]{minimal}
$$ & = ( A)^{-1}( ( A)-I) B \\ & = -( ( A)-I)=1-= ( { {Linear}}( x_{t}) ) $$ B ¯ = ( Δ A ) - 1 ( exp ( Δ A ) - I ) · Δ B = - ( exp ( Δ A ) - I ) = 1 - A ¯ = σ Linear x t After discretization, the calculation method is selected according to the task. In the training process, we use a convolution representation that can be parallelized, and in the inference process, we use an efficient circular representation, which can achieve efficient calculation of linear complexity: 5a [12pt]{minimal}
$$ h_t=h_{t-1}+x_t$$ h t = A ¯ h t - 1 + B ¯ x t 5b [12pt]{minimal}
$$ y_t=Ch_t $$ y t = C h t 6a [12pt]{minimal}
$$ }}=(C,C}}, ,C^k, )$$ K ¯ = ( C B ¯ , C AB ¯ , … , C A ¯ k B ¯ , … ) 6b [12pt]{minimal}
$$ y=x*}} $$ y = x ∗ K ¯ In order to make the model filter out irrelevant information and remember relevant information indefinitely, and have the characteristics of SSM, Mamba modifies the SSM by using Selective SSM, which selectively processes information and includes the entire history information, creating a very effective small state. At the same time, the hardware sensing algorithm is introduced to further improve the computing efficiency. In the Mamba block, the input data is first divided into two branches. In the first branch, the data goes through a linear layer for a basic transformation and is immediately passed to the SiLU activation function. SiLU is a smooth non-linear function that adaptively adjusts the activation level based on the input, which helps the model capture more complex feature relationships. At the same time, the data in the second branch also passes through a linear layer and then into a deeply separable convolution layer that is specifically designed to efficiently learn features at the spatial level. The output of the depth-separable convolution is further enhanced by the SiLU activation function and finally fed into a Selective state space models. The output of the two branches is then combined by a multiplication operation, which is designed to synthesize the information in the two branches while preserving each’s unique contribution. Finally, a linear layer is used to reconcile the output data of these features. Intelligent evaluation model of dental calculus degree From the perspective of clinical diagnosis, the degree of dental calculus is assessed based on the adhesion of the dental calculus to the surface of the tooth and the gingival margin. Therefore, we designed an intelligent evaluation algorithm for the degree of dental calculus based on the adhesion of dental calculus to the tooth surface and the gingival margin (Fig. ).Our intelligent evaluation model of dental calculus degree is designed based on the structure of the CNN network. The area of the lesion marked as dental calculus after Oral-Mamba will continue to judge the degree of dental calculus in the next stage using the intelligent evaluation algorithm of the degree of dental calculus. We used Segment Anything Model (SAM) , a pioneering basic model with rapid segmentation that has recently gained widespread attention, to automatically label the tooth surface and gingival margin of the original image of dental calculus.Then, the image with dental calculus mask and the image with tooth surface and gingival margin mask are fused as original data and entered into the intelligent evaluation model of dental calculus degree. After extracting features through convolution layer, activation function and pooling layer, the full connection layer can classify the degree of dental calculus, and finally a probability distribution diagram of 0,1, 2 and 3 degrees of dental calculus will be obtained. The degree of dental calculus with the highest probability is the final output result. We feed the image into the network. Firstly, medical image segmentation was performed by Oral-Mamba, and gingivitis, dental caries or dental calculus lesion areas were detected. The degree of dental calculus was then intelligibly diagnosed in the images with dental calculus lesions to determine the degree of dental calculus. Finally, visual results of gingivitis,dental caries and dental calculus lesion areas and the degree of dental calculus were output (Fig. ).
Our study of Oral-Mamba (Fig. ) is improved based on the structure of the U-Net network, which passes through a Mamba block in the bottleneck (Fig. a). U-Net is used to obtain contextual and location information. U-Net itself is a very simple structure and is composed of two parts, the first half of the downsampling for feature extraction and the second half of the feature upsampling, called the encoder-decoder structure. The encoder gradually reduces the spatial dimension of the pooling layer, and the decoder gradually repairs the detail and spatial dimension of the object. There is usually a skip connection between the encoder and the decoder, so it helps the decoder better repair the details of the target. U-Net integrates the characteristics of higher and lower features, which helps us to identify and locate gingivitis, dental caries or dental calculus. The Mamba block in the Oral-Mamba network structure (Fig. a) is the core module of the Oral-Mamba network structure, which contains Selective State Space Models. First, let us introduce State Space Model(SSM). SSM is the most recent class of sequential models for deep learning. It is inspired by a special continuous system for describing hidden state representations and making next state predictions based on some input. 1 [12pt]{minimal}
$$ state \ equation: h^{ }(t)=A h(t)+B x(t) $$ s t a t e e q u a t i o n : h ′ ( t ) = A h ( t ) + B x ( t ) 2 [12pt]{minimal}
$$ output \ equation: y(t)=C h(t) $$ o u t p u t e q u a t i o n : y ( t ) = C h ( t ) Where [12pt]{minimal}
$$A R^{N N}$$ A ∈ R N × N , B , [12pt]{minimal}
$$C R^{N}$$ C ∈ R N , N is the number of variables in the state space. Matrix A describes how all the internal states are connected because they represent the underlying representation of the system. It is initialized on the basis of HiPPO theory. HiPPO’s model combines the concepts of Recurrent Memory and Optimal Polynomial Projections. This projection technique can significantly improve the performance of Recurrent Memory and solve the problem of remote dependence in processing long sequence data. By visualizing equations (1) and (2), we can obtain the architecture as shown in Fig. b. Since the oral endoscopy photos are discrete inputs, we also discretize the model using zero-order holding techniques: 3 [12pt]{minimal}
$$ & = ( A)=}( x_{t}) ) } \\ & = ( -{ {Linear}}( x_{t}) ) = 1- ( { {Linear}}( x_{t}) ) $$ A ¯ = exp ( Δ A ) = 1 1 + exp Linear x t = σ - Linear x t = 1 - σ Linear x t 4 [12pt]{minimal}
$$ & = ( A)^{-1}( ( A)-I) B \\ & = -( ( A)-I)=1-= ( { {Linear}}( x_{t}) ) $$ B ¯ = ( Δ A ) - 1 ( exp ( Δ A ) - I ) · Δ B = - ( exp ( Δ A ) - I ) = 1 - A ¯ = σ Linear x t After discretization, the calculation method is selected according to the task. In the training process, we use a convolution representation that can be parallelized, and in the inference process, we use an efficient circular representation, which can achieve efficient calculation of linear complexity: 5a [12pt]{minimal}
$$ h_t=h_{t-1}+x_t$$ h t = A ¯ h t - 1 + B ¯ x t 5b [12pt]{minimal}
$$ y_t=Ch_t $$ y t = C h t 6a [12pt]{minimal}
$$ }}=(C,C}}, ,C^k, )$$ K ¯ = ( C B ¯ , C AB ¯ , … , C A ¯ k B ¯ , … ) 6b [12pt]{minimal}
$$ y=x*}} $$ y = x ∗ K ¯ In order to make the model filter out irrelevant information and remember relevant information indefinitely, and have the characteristics of SSM, Mamba modifies the SSM by using Selective SSM, which selectively processes information and includes the entire history information, creating a very effective small state. At the same time, the hardware sensing algorithm is introduced to further improve the computing efficiency. In the Mamba block, the input data is first divided into two branches. In the first branch, the data goes through a linear layer for a basic transformation and is immediately passed to the SiLU activation function. SiLU is a smooth non-linear function that adaptively adjusts the activation level based on the input, which helps the model capture more complex feature relationships. At the same time, the data in the second branch also passes through a linear layer and then into a deeply separable convolution layer that is specifically designed to efficiently learn features at the spatial level. The output of the depth-separable convolution is further enhanced by the SiLU activation function and finally fed into a Selective state space models. The output of the two branches is then combined by a multiplication operation, which is designed to synthesize the information in the two branches while preserving each’s unique contribution. Finally, a linear layer is used to reconcile the output data of these features.
From the perspective of clinical diagnosis, the degree of dental calculus is assessed based on the adhesion of the dental calculus to the surface of the tooth and the gingival margin. Therefore, we designed an intelligent evaluation algorithm for the degree of dental calculus based on the adhesion of dental calculus to the tooth surface and the gingival margin (Fig. ).Our intelligent evaluation model of dental calculus degree is designed based on the structure of the CNN network. The area of the lesion marked as dental calculus after Oral-Mamba will continue to judge the degree of dental calculus in the next stage using the intelligent evaluation algorithm of the degree of dental calculus. We used Segment Anything Model (SAM) , a pioneering basic model with rapid segmentation that has recently gained widespread attention, to automatically label the tooth surface and gingival margin of the original image of dental calculus.Then, the image with dental calculus mask and the image with tooth surface and gingival margin mask are fused as original data and entered into the intelligent evaluation model of dental calculus degree. After extracting features through convolution layer, activation function and pooling layer, the full connection layer can classify the degree of dental calculus, and finally a probability distribution diagram of 0,1, 2 and 3 degrees of dental calculus will be obtained. The degree of dental calculus with the highest probability is the final output result. We feed the image into the network. Firstly, medical image segmentation was performed by Oral-Mamba, and gingivitis, dental caries or dental calculus lesion areas were detected. The degree of dental calculus was then intelligibly diagnosed in the images with dental calculus lesions to determine the degree of dental calculus. Finally, visual results of gingivitis,dental caries and dental calculus lesion areas and the degree of dental calculus were output (Fig. ).
We randomly assigned the 3365 acquired oral endoscopy images into 3 subsets, with a 6: 2: 2 ratio. 60% of the data set is used for training, 20% for validation, and the remaining 20% for testing. So, the training set contains 2019 images, the verification set contains 673 images, and the test set contains 673 images. For training, K-fold cross-validation is applied and learned by sequentially replacing individual verification sets. For each training, the network was trained on 400 epochs, optimized using stochastic gradient descent with an initial learning rate of 1e-2. During training, we adopted the combination of Dice loss and cross entropy to segment and classify areas of gingivitis, dental caries, or dental calculus lesion, which can provide better performance in various tasks and scenarios . The loss function is defined as: 7 [12pt]{minimal}
$$ L & = ( - _{i=1}^{N} ( t_{i} p_{i}) . . +(1- )[ ( 1-t_{i}) ( 1-p_{i}) ] ) \\ & -(1- ) _{i=1}^{K}( ^{N} p_{i} t_{i}+S}{ _{i=1}^{N} p_{i}+ _{i=1}^{N} t_{i}+S}) $$ L = α - 1 N ∑ i = 1 N β t i ln p i + ( 1 - β ) 1 - t i ln 1 - p i - ( 1 - α ) ∑ i = 1 K 2 ∑ i = 1 N p i t i + S ∑ i = 1 N p i + ∑ i = 1 N t i + S The model was trained using NVIDIA RTX4060Ti GPU and 14th Gen Intel(R) Core(TM) i7-14700K CPU, and deep learning frameworks PyTorch 1.11, Cuda 11.4, and cuDNN 8.2.
In order to evaluate the overall performance of the Oral-Mamba network architecture we designed, we evaluated the results of the test set and the real results labeled by the physician in the model prediction. Meanwhile, we use U-Net, a popular medical image segmentation network, to compare its segmentation performance with that of Oral-Mamba. U-Net is one of the popular deep networks for medical image analysis. It consists of an encoder path with five levels for capturing context, and a symmetric decoder path for restoring image resolution to the input image resolution. U-Net has about 7.7 million trainable parameters. The metrics commonly used for evaluation include precision, accuracy, recall, and IoU, all of which are pixel-level comparisons that provide a comprehensive evaluation of the segmentation results. Intersection over Union (IoU): The IoU measures the degree of overlap between the predicted segmentation results and the real labels. It is defined by calculating the ratio of the intersection region between the predicted segmentation result and the real label to their union region. The closer the IoU is to 1, the higher the degree of overlap between the predicted result and the real label, and the better the segmentation effect. IoU is calculated as follows: 8 [12pt]{minimal}
$$ IoU= $$ I o U = TP T P + F P + F N Recall: The recall measures the proportion of true positive cases that are correctly predicted. In image segmentation, the recall represents the ratio of predicted positive example pixels to real positive example pixels, and a high recall means that the algorithm can capture more real positive examples to avoid omissions. Its calculation formula is as follows: 9 [12pt]{minimal}
$$ Recall= $$ R e c a l l = TP T P + F N Precision: Precision measures the proportion of all predicted positive examples that are actually positive. In image segmentation, precision represents the ratio between real example pixels and all pixels predicted as positive examples. The high-precision representation algorithm can accurately identify positive example pixels and reduce misrecognition. Its calculation formula is as follows: 10 [12pt]{minimal}
$$ Precision= $$ P r e c i s i o n = TP T P + F P Accuracy: Accuracy measures the ratio of all correctly classified pixels to the total number of pixels. In image segmentation, accuracy represents the ratio between the number of correctly classified pixels and the total number of pixels. Its calculation formula is as follows: 11 [12pt]{minimal}
$$ Accuracy= $$ A c c u r a c y = T P + T N T P + T N + F P + F N Among them, TP is the number of pixels of the true example (correctly classified as a positive example), FP is the number of pixels of the false positive example (incorrectly classified as a positive example), FN is the number of pixels of the false negative example (incorrectly classified as a negative example), and TN is the number of pixels of the true negative example (correctly classified as a negative example).
Segmentation performance of Oral-Mamba The segmentation performance of Oral-Mamba and U-Net is compared by drawing four tables. Tables , , , and respectively show the quantitative results of U-Net and Oral-Mamba network models on the segmentation performance of gingivitis, dental caries and dental calculus. From these results, we found that Oral-Mamba showed high performance in the segmentation of gingivitis, dental caries and dental calculus.Among them, Oral-Mamba showed the best improvement in the segmentation of dental caries, IoU increased from 0.59 to 0.71, recall increased from 0.75 to 0.83, precision increased from 0.74 to 0.84 and accuracy increased from 0.75 to 0.83. However,the IoU of U-Net is no higher than 0.64, the recall is no higher than 0.81, the precision is lower than 0.80, and the accuracy is no higher than 0.81.It can be seen that, regardless of the segmentation performance metrics for gingivitis, dental caries, or dental calculus, Oral-Mamba is superior to U-Net segmentation performance. The test results were qualitatively verified as shown in Fig. , where (second row of Fig. ) was the ground truth(GT) marked by the dentist, and (third row of Fig. ) was predicted by the model. It can be seen that Oral-Mamba can generate accurate segmentation masks for gingivitis, dental caries and dental calculus. Although the size of the predicted boundary may be slightly different in the case of TP than in the case of GT, the location of gingivitis, dental caries, and dental calculus can all be correctly detected and contains a large proportion of their areas correctly. Accuracy of the intelligent evaluation model of dental calculus degree The intelligent evaluation model of dental calculus degree is achieved based on the evaluation of the dental calculus attached to the dental surface and the gingival margin, resulting in a relatively accurate classification of the dental calculus into 0, 1, 2, and 3 degrees. The accuracy reaches a medium to high level, with an accuracy exceeding 85%. Figure presents the probability diagram of our intelligent evaluation model of dental calculus degree in some images.
The segmentation performance of Oral-Mamba and U-Net is compared by drawing four tables. Tables , , , and respectively show the quantitative results of U-Net and Oral-Mamba network models on the segmentation performance of gingivitis, dental caries and dental calculus. From these results, we found that Oral-Mamba showed high performance in the segmentation of gingivitis, dental caries and dental calculus.Among them, Oral-Mamba showed the best improvement in the segmentation of dental caries, IoU increased from 0.59 to 0.71, recall increased from 0.75 to 0.83, precision increased from 0.74 to 0.84 and accuracy increased from 0.75 to 0.83. However,the IoU of U-Net is no higher than 0.64, the recall is no higher than 0.81, the precision is lower than 0.80, and the accuracy is no higher than 0.81.It can be seen that, regardless of the segmentation performance metrics for gingivitis, dental caries, or dental calculus, Oral-Mamba is superior to U-Net segmentation performance. The test results were qualitatively verified as shown in Fig. , where (second row of Fig. ) was the ground truth(GT) marked by the dentist, and (third row of Fig. ) was predicted by the model. It can be seen that Oral-Mamba can generate accurate segmentation masks for gingivitis, dental caries and dental calculus. Although the size of the predicted boundary may be slightly different in the case of TP than in the case of GT, the location of gingivitis, dental caries, and dental calculus can all be correctly detected and contains a large proportion of their areas correctly.
The intelligent evaluation model of dental calculus degree is achieved based on the evaluation of the dental calculus attached to the dental surface and the gingival margin, resulting in a relatively accurate classification of the dental calculus into 0, 1, 2, and 3 degrees. The accuracy reaches a medium to high level, with an accuracy exceeding 85%. Figure presents the probability diagram of our intelligent evaluation model of dental calculus degree in some images.
Easy to operate with digital storage and the ability to capture high-quality images, oral endoscope is introduced into oral diseases detection, lowering the threshold and helping to prevent the deterioration of oral diseases.Therefore, it has been widely used in stomatology, as a visual inspection tool for dental caries detection , applied in periodontal treatment, and can also help diagnose suspected subgingival diseases such as dental caries and root cleft.The development of artificial intelligence has prompted people to combine deep learning technology with medical equipment to alleviate the shortage of medical resources. At the same time, artificial intelligence is used as a tool for the preliminary judgment of patient conditions, which can provide patients with low-cost, convenient, and professional advice, reducing the economic burden and mental pressure of patients. The rapid advancement of smart diagnosis and treatment will inevitably bring win-win results to doctors and patients. At present, deep learning-represented artificial intelligence technology has been widely used in the field of stomatology, has achieved significant results, and is a reliable and standardized assistant to help doctors in the diagnosis and treatment of oral diseases. In addition, it can provide other benefits, such as speed, efficiency, and cost reduction. In particular, the U-Net framework has achieved excellent results in various medical imaging tasks, such as segmentation of the degree of dental caries based on U-Net. Li et al. use deep learning methods to identify teeth such as incisors, canines, premolars, and molars.However, in the process of using deep learning to diagnose oral and dental problems, many obstacles have been found: since most of the diagnoses are made with panoramic X-rays, the examination is expensive;U-Net requires a large number of data sets for training and consumes huge computational resources, but there is a lack of high-quality labeled oral image data sets. The current shortcomings of these models forced us to build high-quality datasets and develop a novel medical image segmentation architecture. Therefore, we propose a competitive system, one that incorporates Oral-Mamba and an intelligent evaluation model of dental calculus degree, to solve the problem of capturing powerful telematics and maintaining linear computational complexity.Specifically, the algorithm has local capture capabilities and efficient remote modeling capabilities, making it more efficient in terms of GPU memory and inference time for high-resolution images. We used Oral-Mamba for medical image segmentation of intraoral photographic images to detect gingivitis, dental caries and dental calculus. We proposed an intelligent evaluation model of dental calculus degree to judge the degree of dental calculus based on the adhesion of dental calculus to the tooth surface and gingival margin, combined the domain small model with the SAM large model, combined with clinical experience to judge the degree of calculus. In addition, we produced high-quality data sets for the model training. The system can quickly and efficiently give the analysis report of the visual lesion area of the patient’s dental calculus, gingivitis, and dental caries, which can help the patient see the diseases intuitively and carry out treatment as early as possible. The segmentation IoU score of Oral-Mamba ranges from 0.64 to 0.71, the precision is near 0.80, and recall and accuracy are higher than 0.80, which is better than the segmentation effect using U-Net.Among them, the segmentation accuracy of dental caries was the highest, and the segmentation accuracy of dental calculus was the lowest. In terms of training speed, Oral-Mamba runs 25% faster than U-Net. Based on the adhesion of dental calculus to the tooth surface and gingival margin, the intelligent evaluation model of dental calculus degree is excellent, reaching up to 85%. Although our system has achieved some success in terms of speed and accuracy, there are still some limitations. The first is the limitation of the oral endoscope itself, which can only be used to inspect the surface of the tooth. The lesions inside the tooth including the pulp, dentin, pulp cavity, and other structures cannot be directly observed by the oral endoscope, and more comprehensive information needs to be obtained by X-ray, CT scan, and other imaging techniques.In addition, the effect of the oral endoscope is easily affected by light, and the quality and direction of light will affect the imaging quality and clarity of the oral endoscope, affecting our model’s judgment of gingivitis, and so on. In addition, teeth with serious tea stains and smoke stains will also affect the judgment of dental calculus. In any case, this study is the first system to merge Mamba and U-Net for the segmentation of gingivitis, dental caries, and dental calculus regions, solving the problem of capturing powerful telematics and maintaining linear computational complexity. It also performs the classification of the degree of dental calculus. The diagnosis may vary depending on the experience and skill of the clinician, but the system will not, it will be a visual aid diagnostic system that includes the diagnostic opinions of professional doctors.Applying this system in dental practice can alleviate the shortage of medical resources, allow patients to undergo early oral screening more conveniently and cheaply, and enable patients to understand their condition more intuitively and earlier, thus benefiting patients.
The purpose of this study is to solve the problem that the shortage of dentists and the uneven distribution of medical resources aggravate the difficulty of seeing a doctor and the problem of early prevention of oral diseases. To this end, we propose a system and make an oral endoscopic data set for the training model to achieve accurate segmentation of gingivitis and dental caries with segmentation accuracy ranging from 81% to 83%. The degree of dental calculus was also classified with 85% accuracy. This provides a useful idea for combining deep learning with oral endoscopy technology for the early prevention and treatment of oral diseases.
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Current trends in antimicrobial use and the role of antimicrobial stewardship in palliative oncology: a narrative review | 2fd15d22-7cad-4f4e-ab90-d8a85486ce82 | 11736969 | Internal Medicine[mh] | Palliative care (PC) is defined as a holistic approach that aims to enhance the quality of life (QOL) for patients and their families facing life-threatening or terminal illnesses by preventing and relieving suffering through early identification, comprehensive assessment, and management of pain as well as physical, psychosocial, and spiritual issues . Oncology patients under PC are susceptible to infections due to several factors such as malnutrition, vulnerable immune systems, presence of catheters, and immunosuppression from chemotherapy . Distinguishing between bacterial infections and disease-related symptoms can be challenging, often leading to overuse of antimicrobials without clear indications . Antimicrobial stewardship (ASP) aims to ensure that patients are receiving the right antimicrobial therapy, in the right indication, dose and duration. Applying ASP in oncology patients under PC is under looked but has great potential in achieving the goals of care; however, many challenges exist. Understanding antimicrobial use, including its frequency, impact on patients’ survival and oncologists’ perceptions, is crucial for improving antimicrobial practices. This review aims to explore the current approach to antimicrobial use in palliative oncology settings, identify the associated challenges, and draw conclusions for best practices of ASP in oncology patients under PC. This review was conducted by searching the Pubmed database for articles published between January 2000 and June 2024. The search strategy includes the following keyword (“palliative care” OR “end-of-life care” OR “comfort care”) AND (“antimicrobial” OR “antibiotic” OR “Antimicrobial stewardship”) AND (“oncology” OR “neoplasm” OR “malignancy” OR “cancer”). Articles were selected if they provided data on antimicrobial use in palliative setting, challenges and strategies for ASP. Antimicrobial use in palliative oncology Oncology patients receiving PC face an increased risk of infection due to factors such as a compromised immune system, the presence of invasive catheters, malnutrition, and recent chemotherapy . In fact, sepsis is an inevitable event in individuals nearing the end of life (EOL) . Additionally, distinguishing between symptoms caused by cancer and those indicating a new infection can be difficult. For that reason, overuse of antimicrobials is not uncommon in patients with advanced cancer. Overprescription of antibiotics is a significant concern, contributing to the rise of multidrug-resistant organisms and other adverse effects, which can prolong hospital stays and reduce patient satisfaction. Table summarizes the characteristics of cohort studies on antimicrobial usage in cancer patients under PC. In two-thirds of the studies, antimicrobials were used in more than 50% of the patients and this frequency reached 97.5% in some studies . Even after shifting the patient to EOL and patients being taken in charge by PC doctors, a high percentage of patients were kept on antimicrobials. A study published in 2012 showed that 86.9% of hospitalized cancer patients were under antimicrobials during their last weeks of life with only 48.4% of them found to have a documented infection . Furthermore, in the last few days of life, where comfort is the main goal of care, around 55% of those patients were still receiving antimicrobials . This trend is not only limited to cancer patients but was also reported in other populations. Data from nursing homes caring for demented patients reported around 66.4% of residents receiving antimicrobials during the last weeks of their lifetime . However, this use is not without additional cost. Prescribing antibiotics is associated with emergence of multidrug resistance (MDR) in bacterial infections, drug-drug interactions (DDI), anaphylaxis and drug adverse effects . MDR is considered one of the major threats to global public health due to limited treatment options and risk of transmission to other vulnerable patients ( https://www.who.int/publications/i/item/9789241509763 ). In addition, antimicrobial use can lead to Clostridiodes difficile colitis, leading to an increased morbidity, hospital stay and cost ( https://www.who.int/publications/i/item/9789241509763 ). Isolation precautions for patients colonized with MDR pathogens negatively impact both the patient and their caregivers, causing discomfort due to restricted visits and limited interaction. These measures also increase the workload for nursing staff . This is crucial for this cohort of patients, as they require psychological support and continuous interaction with their loved ones and hospital staff. In addition to that, these vulnerable cancer patients are on polypharmacy regimens including but not limited to opioids, which may have DDI with different antibiotic classes, which can ultimately affect the antibiotic’s pharmacokinetics . Other adverse effects include injection site inflammation, phlebitis, local skin infections, and secondary bacteremia . In fact, such risk is considered against the goals of palliation and symptom relief. Despite the previously mentioned risks, intravenous antibiotics were still used in up to 82% of patients as reported in some data . In addition, increased use of antibiotics puts the patients at higher risk for fungal infections necessitating expensive and at times toxic antifungal agents . Challenges leading to overuse of antibiotics Optimizing antimicrobial use in palliative oncology is challenging. This is due to many reasons including patient-physician relationship, family preference, unrealistic hope, assumption that antibiotics are safe drugs with no harm, and misleading symptoms and laboratory results. These challenges with the assumption of beneficial impact of prescribing antibiotics can lead to antimicrobial misuse. Patients and their families are all at times reluctant not to prescribe antibiotics in the febrile patients despite the expectations for overall poor outcome. Regarding physician perceptions, Crispim et al. demonstrated in their online survey about antibiotic prescription at EOL that most physicians opted to initiate antibiotics in all hypothetical scenarios of patients with infections . Physicians who had graduated since more than 13 years and those without formal education on PC were more likely to prescribe antibiotics. While initiating antibiotics is challenging, withholding it carries a complex ethical challenge. Even for non-responders' patients, most doctors still chose to broaden or maintain antibiotic regimens 72-h after initiation rather than de-escalating . Gaw et al. highlighted that half of the physicians chose to continue antibiotics for nearly all types of infections, even for patients under comfort care where death was imminent . Many factors drive or even force physicians to continue antibiotics despite no response in EOL cancer patients, with family preference being a significant one. Larnard et al. demonstrated in a qualitative study that patient/family preference and the goal of providing palliation were the two major factors influencing physicians' decisions . Similarly, Servid et al. concluded that 19.4% of antibiotic prescriptions were driven by the family's preference rather than by clinical signs of infection . Apart from physicians' and family perspectives, obtaining a definite diagnosis in patients with advanced cancer is challenging because many symptoms can be attributed to disease progression. For instance, studies have shown that 7% to 19% of oncology patients with advanced cancer who presented with fever of unknown origin had paraneoplastic fever, and these patients usually respond well to non-steroidal anti-inflammatory drugs . Additionally, in one study, leukemoid reaction was attributed to infection in only 15% of cases, compared to 10% resulting from a paraneoplastic reaction . In both cases of paraneoplastic fever and leukemoid reaction, patients with advanced cancer will remain clinically stable but have a poor prognosis unless effective antineoplastic treatment is administered. Recognizing non-infectious causes of a patient's clinical presentation is crucial, as it can help optimize antibiotic use, especially when initial sepsis work-up is negative and the patient is clinically stable. Antibiotic use and goals of care The primary goal of palliative care (PC) is to preserve quality of life (QOL) and alleviate symptoms during a patient’s final days. While antibiotics are often used with the intention of prolonging survival, evidence shows that treating reversible infections does not significantly impact survival with limited effectiveness in palliating symptoms. Several cohort studies examined the impact of antibiotics on survival in patients with advanced cancer. White et al., in their prospective cohort study, demonstrated that antibiotics use in suspected infections did not impact survival . In the same line, Reibolt et al., and Mal et al., have shown no survival benefit of antibiotic use in EOL care of oncology patients . In contrast, Chen et al. et al. reported a positive impact of antibiotics on survival in advanced cancer patients (14.6 days vs. 8.7 days; p -value: 0.03) . However, the extension of life in patients suffering from terminal illness is not a marker of a better outcome as it merely implies prolonging suffering in many cases. The impact of antibiotics on controlling symptoms in terminal patients is also controversial. For instance, Vitetta et al. reported a 40% rate of symptom reduction with the use of antibiotics in patients with imminent death . Similar results have been reported by Stiel et al., where 56% of the surveyed patients reported good or very good clinical effect after receiving antibiotics . Despite the positive impact reported in some studies, the effect differs depending on the site of infection . White et al. demonstrated that antibiotic use effectively resolved symptoms in most patients with urinary tract infections (UTIs) . However, it was less effective in alleviating symptoms from infections at other sites, including respiratory infections, bacteremia, and skin and soft tissue infections . Similarly, Fombuena et al. found that 64% of patients treated for possible infections experienced symptom resolution, with UTIs being the most responsive to antibiotic treatment . Out of the 633 treated patients in an outpatient hospice care, symptomatic relief was reported in 79% of patients with UTI,43% with respiratory infections, 41% in skin and soft tissue infections and none with bacteremia . In fact, the failure of palliating respiratory symptoms in patients with pneumonia was linked to high palliative prognostic index, indicating poorer prognosis . Even in non-cancer terminally ill patients, the impact of antibiotics on symptomatic relief varied by the site of infection. Rosenberg et al., in a systematic review, showed that patients with UTI experienced the greatest improvement in symptoms following antibiotic therapy, with improvement rates ranging from 67 to 92% . Therefore, it's essential to weigh the risks of treating potentially reversible infections against the limited evidence of benefit, ensuring that the diagnosis of infection is supported by clinical, laboratory, or microbiological evidence. Approach of antibiotic use in palliative care ASP aims to ensure that patients receive the appropriate antibiotic with the correct dose, indication and duration. While there are no definitive guidelines for management of infections in advanced cancer patients, the IDSA considered prescribing antibiotics in EOL care as an aggressive intervention . In view of the previously mentioned challenges, several interventions can be applied to optimize the use of antimicrobials. A summary of potential ASP interventions is summarized in Table . Infectious diseases (ID) specialist’s role is crucial for optimizing antimicrobials in palliative oncology setting. This should be done through different approaches including being actively involved in goals of care discussion for patients with recurrent infections. The integration of ID physicians in such discussions aims to set-up a plan for antimicrobial use based on realistic expectations rather than false hopes . By being involved in goals of care discussion, the ID physician should emphasize to the patients and their families the inevitable consequences of the disease leading to possible infections, pros and cons of antimicrobials, and limited benefit of antimicrobials in later stages . Following the illustration of the realistic expectations, outlining the goals of care to either complete comfort, palliating symptoms or full treatment is needed. Even in the patients who decide to treat possible infections, a time-limited approach should be tried through setting-up objective markers for response to antibiotics followed by re-evaluation after 48-h and clear actions if antibiotics are ineffective . Further discussions about care goals should occur when the patient's clinical situation deteriorates, acknowledging the emotional distress the patient is experiencing . Besides, early referral to a specialized palliative team may help in effectively reducing antimicrobial use, as demonstrated by Jeong-Han Kim et al., in their retrospective cohort analysis . Other ASP interventions that can be done to optimize antimicrobial use include institutional guidelines and educational interventions . Oncology patients receiving PC face an increased risk of infection due to factors such as a compromised immune system, the presence of invasive catheters, malnutrition, and recent chemotherapy . In fact, sepsis is an inevitable event in individuals nearing the end of life (EOL) . Additionally, distinguishing between symptoms caused by cancer and those indicating a new infection can be difficult. For that reason, overuse of antimicrobials is not uncommon in patients with advanced cancer. Overprescription of antibiotics is a significant concern, contributing to the rise of multidrug-resistant organisms and other adverse effects, which can prolong hospital stays and reduce patient satisfaction. Table summarizes the characteristics of cohort studies on antimicrobial usage in cancer patients under PC. In two-thirds of the studies, antimicrobials were used in more than 50% of the patients and this frequency reached 97.5% in some studies . Even after shifting the patient to EOL and patients being taken in charge by PC doctors, a high percentage of patients were kept on antimicrobials. A study published in 2012 showed that 86.9% of hospitalized cancer patients were under antimicrobials during their last weeks of life with only 48.4% of them found to have a documented infection . Furthermore, in the last few days of life, where comfort is the main goal of care, around 55% of those patients were still receiving antimicrobials . This trend is not only limited to cancer patients but was also reported in other populations. Data from nursing homes caring for demented patients reported around 66.4% of residents receiving antimicrobials during the last weeks of their lifetime . However, this use is not without additional cost. Prescribing antibiotics is associated with emergence of multidrug resistance (MDR) in bacterial infections, drug-drug interactions (DDI), anaphylaxis and drug adverse effects . MDR is considered one of the major threats to global public health due to limited treatment options and risk of transmission to other vulnerable patients ( https://www.who.int/publications/i/item/9789241509763 ). In addition, antimicrobial use can lead to Clostridiodes difficile colitis, leading to an increased morbidity, hospital stay and cost ( https://www.who.int/publications/i/item/9789241509763 ). Isolation precautions for patients colonized with MDR pathogens negatively impact both the patient and their caregivers, causing discomfort due to restricted visits and limited interaction. These measures also increase the workload for nursing staff . This is crucial for this cohort of patients, as they require psychological support and continuous interaction with their loved ones and hospital staff. In addition to that, these vulnerable cancer patients are on polypharmacy regimens including but not limited to opioids, which may have DDI with different antibiotic classes, which can ultimately affect the antibiotic’s pharmacokinetics . Other adverse effects include injection site inflammation, phlebitis, local skin infections, and secondary bacteremia . In fact, such risk is considered against the goals of palliation and symptom relief. Despite the previously mentioned risks, intravenous antibiotics were still used in up to 82% of patients as reported in some data . In addition, increased use of antibiotics puts the patients at higher risk for fungal infections necessitating expensive and at times toxic antifungal agents . Optimizing antimicrobial use in palliative oncology is challenging. This is due to many reasons including patient-physician relationship, family preference, unrealistic hope, assumption that antibiotics are safe drugs with no harm, and misleading symptoms and laboratory results. These challenges with the assumption of beneficial impact of prescribing antibiotics can lead to antimicrobial misuse. Patients and their families are all at times reluctant not to prescribe antibiotics in the febrile patients despite the expectations for overall poor outcome. Regarding physician perceptions, Crispim et al. demonstrated in their online survey about antibiotic prescription at EOL that most physicians opted to initiate antibiotics in all hypothetical scenarios of patients with infections . Physicians who had graduated since more than 13 years and those without formal education on PC were more likely to prescribe antibiotics. While initiating antibiotics is challenging, withholding it carries a complex ethical challenge. Even for non-responders' patients, most doctors still chose to broaden or maintain antibiotic regimens 72-h after initiation rather than de-escalating . Gaw et al. highlighted that half of the physicians chose to continue antibiotics for nearly all types of infections, even for patients under comfort care where death was imminent . Many factors drive or even force physicians to continue antibiotics despite no response in EOL cancer patients, with family preference being a significant one. Larnard et al. demonstrated in a qualitative study that patient/family preference and the goal of providing palliation were the two major factors influencing physicians' decisions . Similarly, Servid et al. concluded that 19.4% of antibiotic prescriptions were driven by the family's preference rather than by clinical signs of infection . Apart from physicians' and family perspectives, obtaining a definite diagnosis in patients with advanced cancer is challenging because many symptoms can be attributed to disease progression. For instance, studies have shown that 7% to 19% of oncology patients with advanced cancer who presented with fever of unknown origin had paraneoplastic fever, and these patients usually respond well to non-steroidal anti-inflammatory drugs . Additionally, in one study, leukemoid reaction was attributed to infection in only 15% of cases, compared to 10% resulting from a paraneoplastic reaction . In both cases of paraneoplastic fever and leukemoid reaction, patients with advanced cancer will remain clinically stable but have a poor prognosis unless effective antineoplastic treatment is administered. Recognizing non-infectious causes of a patient's clinical presentation is crucial, as it can help optimize antibiotic use, especially when initial sepsis work-up is negative and the patient is clinically stable. The primary goal of palliative care (PC) is to preserve quality of life (QOL) and alleviate symptoms during a patient’s final days. While antibiotics are often used with the intention of prolonging survival, evidence shows that treating reversible infections does not significantly impact survival with limited effectiveness in palliating symptoms. Several cohort studies examined the impact of antibiotics on survival in patients with advanced cancer. White et al., in their prospective cohort study, demonstrated that antibiotics use in suspected infections did not impact survival . In the same line, Reibolt et al., and Mal et al., have shown no survival benefit of antibiotic use in EOL care of oncology patients . In contrast, Chen et al. et al. reported a positive impact of antibiotics on survival in advanced cancer patients (14.6 days vs. 8.7 days; p -value: 0.03) . However, the extension of life in patients suffering from terminal illness is not a marker of a better outcome as it merely implies prolonging suffering in many cases. The impact of antibiotics on controlling symptoms in terminal patients is also controversial. For instance, Vitetta et al. reported a 40% rate of symptom reduction with the use of antibiotics in patients with imminent death . Similar results have been reported by Stiel et al., where 56% of the surveyed patients reported good or very good clinical effect after receiving antibiotics . Despite the positive impact reported in some studies, the effect differs depending on the site of infection . White et al. demonstrated that antibiotic use effectively resolved symptoms in most patients with urinary tract infections (UTIs) . However, it was less effective in alleviating symptoms from infections at other sites, including respiratory infections, bacteremia, and skin and soft tissue infections . Similarly, Fombuena et al. found that 64% of patients treated for possible infections experienced symptom resolution, with UTIs being the most responsive to antibiotic treatment . Out of the 633 treated patients in an outpatient hospice care, symptomatic relief was reported in 79% of patients with UTI,43% with respiratory infections, 41% in skin and soft tissue infections and none with bacteremia . In fact, the failure of palliating respiratory symptoms in patients with pneumonia was linked to high palliative prognostic index, indicating poorer prognosis . Even in non-cancer terminally ill patients, the impact of antibiotics on symptomatic relief varied by the site of infection. Rosenberg et al., in a systematic review, showed that patients with UTI experienced the greatest improvement in symptoms following antibiotic therapy, with improvement rates ranging from 67 to 92% . Therefore, it's essential to weigh the risks of treating potentially reversible infections against the limited evidence of benefit, ensuring that the diagnosis of infection is supported by clinical, laboratory, or microbiological evidence. ASP aims to ensure that patients receive the appropriate antibiotic with the correct dose, indication and duration. While there are no definitive guidelines for management of infections in advanced cancer patients, the IDSA considered prescribing antibiotics in EOL care as an aggressive intervention . In view of the previously mentioned challenges, several interventions can be applied to optimize the use of antimicrobials. A summary of potential ASP interventions is summarized in Table . Infectious diseases (ID) specialist’s role is crucial for optimizing antimicrobials in palliative oncology setting. This should be done through different approaches including being actively involved in goals of care discussion for patients with recurrent infections. The integration of ID physicians in such discussions aims to set-up a plan for antimicrobial use based on realistic expectations rather than false hopes . By being involved in goals of care discussion, the ID physician should emphasize to the patients and their families the inevitable consequences of the disease leading to possible infections, pros and cons of antimicrobials, and limited benefit of antimicrobials in later stages . Following the illustration of the realistic expectations, outlining the goals of care to either complete comfort, palliating symptoms or full treatment is needed. Even in the patients who decide to treat possible infections, a time-limited approach should be tried through setting-up objective markers for response to antibiotics followed by re-evaluation after 48-h and clear actions if antibiotics are ineffective . Further discussions about care goals should occur when the patient's clinical situation deteriorates, acknowledging the emotional distress the patient is experiencing . Besides, early referral to a specialized palliative team may help in effectively reducing antimicrobial use, as demonstrated by Jeong-Han Kim et al., in their retrospective cohort analysis . Other ASP interventions that can be done to optimize antimicrobial use include institutional guidelines and educational interventions . The use of antimicrobials in EOL care remains a challenge with no clear recommendations that can guide both the caregivers and the decision makers. Cultural factors, particularly from the family's perspective, and the views of physicians also play crucial roles. Optimizing antimicrobial use through setting up realistic expectations, outlining clear goals of care and balancing between treating possible infections and potential harms is needed. Further studies are necessary to develop guidelines and to evaluate their impact on the rational use of antibiotics in EOL patients. |
Characterization of psychrotrophic and thermoduric bacteria in raw milk using a multi-omics approach | e9fc4888-e354-4e30-b6a8-27f3cd1f6552 | 11540130 | Biochemistry[mh] | Psychrotrophic and thermoduric bacteria in raw milk are considered to be the main factors to affect milk quality. In this study, microbial contamination in raw milk samples from Heilongjiang Province and Inner Mongolia (China) were investigated. Pseudomonas , Lactococcus and Acinetobacter were dominant psychrotrophic bacteria. Enterococcus , Enterobacter , Lactococcus and Bacillus were the most frequently isolated mesophilic thermoduric bacteria. Deinococcus geothermalis and Staphylococcus pasteuri were thermophilic. Two groups of typical samples were selected to explore the relationship between microbial structure and proteins. A large number of peptidases were annotated by metagenomics, such as PepA aminopeptidase, aminopeptidase P3, HtpX peptidase and AlgW peptidase, but interestingly, they were not detected by metaproteomics. Most expressed proteins in fresh raw milk were related to bacterial growth, reproduction and adaptation to cold environments rather than proteases or lipases. This paper offers valuable insights to better understand the potential impact of the microbiota influencing milk quality from three aspects of culture, metagenomics and metaproteomics, providing a comprehensive view for further study of enzymes produced by psychrotrophic and thermoduric bacteria in raw milk.
All metagenomic raw sequences have been deposited to the National Center for Biotechnology Information (NCBI) sequence read archive ( https://www.ncbi.nlm.nih.gov/sra ) under accession numbers SRR30211375 to SRR30211380. The metaproteomic data have been deposited to the ProteomeXchange Consortium ( https://proteomecentral.proteomexchange.org ) via the iProX partner repository with the dataset identifier PXD054735.
Raw milk offers an ideal environment for micro-organisms to thrive, given its abundant nutrients, nearly neutral pH and high water activity. Consequently, milk contamination by micro-organisms remains an ongoing concern. Throughout milking, storage, transportation and processing, raw milk can get contaminated with various micro-organisms. Even when stored at controlled temperatures, the presence of spoilage bacteria remains persistent as a concern causing milk contamination . Psychrotrophic and thermoduric bacteria are common spoilage bacteria. Psychrotrophic bacteria are ubiquitous organisms capable of growing at below 7 °C, in spite of their high optimum growth . Thermoduric bacteria are a group of micro-organisms that are resistant to heat treatment in traditional processes . Microbial diversity in raw milk has been extensively studied in recent years. Research has identified various psychrotrophic and thermoduric bacteria, such as Pseudomonas , Flavobacterium , Chryseobacterium , Acinetobacter and Bacillus , as the main culprits behind milk spoilage . These bacteria can contaminate milk from sources such as water, soil, udder and teat surfaces and farm storage tanks, pumps, pipes and processing equipment. Conventional heat treatment effectively eliminates psychrotrophic bacteria, but it may not inactivate the heat-stable proteases they produce. As a result, residual proteases persist and continue to degrade the milk quality during storage. The residual proteases induce a bitter flavour and gelation . Lipases produced by some psychrotrophic bacteria are thermostable, and the residual lipases hydrolyze fat and the released fatty acids can cause off-flavours in milk . Therefore, the analysis of spoilage microbial diversity in unpasteurized milk holds significance. The microbial communities present in raw milk exhibit a richness and complexity that exceeds the ability to comprehensively characterize based on traditional culture techniques. High-throughput sequencing based on the highly variable region of 16S rRNA is popularly used in the field of dairy microbiology . Although high-throughput sequencing can quickly and accurately identify the species and abundance of micro-organisms, it can only annotate micro-organisms at the genus level and cannot meet the needs of more in-depth analysis. Metagenomic sequencing technology has emerged as a powerful tool for in-depth analysis of microbial communities at the genetic and functional levels. Random fragmentation, reassembly and annotation of the microbial genome allow for the investigation of microbial evolution, examination of gene functionalities and species-level or strain-level annotations. There is a dynamic interaction between bacteria and the milk system, where the bacterial community correlates with specific proteins/peptides and fatty acid profiles . Our research also integrated metaproteomics (proteomics performed in bulk population of cells) to conduct a more comprehensive investigation of the microbial dynamics and various gene expressions in bacteria present in raw milk, which could shed light on the underlying reasons for raw milk deterioration. Metaproteomics gathers data concerning the proteins present and the biochemical pathways employed by the microbiota in the given sampling circumstances , offering unique insights not achievable through metagenomics. Proteomics based on data-independent acquisition (DIA) in four dimensions (4D) is a highly promising technological approach, with the potential to achieve enhanced coverage of protein samples . Metaproteomics based on 4D-DIA technology plays a vital role in comprehensively analysing microbial proteins within the research environment. This technique is essential for gaining insights into the functional characteristics and behaviour of spoilage micro-organisms found in raw milk. The main objective of this research was to analyse the composition of bacterial communities and microbial proteins in raw milk samples obtained from Heilongjiang and Inner Mongolia Province in China. This was achieved by utilizing advanced techniques such as Illumina-based metagenomic sequencing and 4D-DIA metaproteomics. The aim of this investigation was to evaluate the protease-producing and lipase-producing abilities of micro-organisms in fresh milk and gain a better understanding of the potential quality deterioration of micro-organisms in raw milk. The findings will provide insights valuable for developing new strategies to improve dairy product preservation and ensure the production of premium-quality dairy items.
Raw milk sampling Twenty-four raw milk samples from milk tanks were collected from two different commercial dairy farms located in the Heilongjiang (HLJ) and Inner Mongolia Province (NMG) of China from August 2022 to April 2023. The milk samples were divided into eight groups of samples, and three parallel samples of each group were from the same tanks (commingled milk harvested from the same herd). The detailed sampling time is listed in . Three parallel samples (one group sample) were collected for every sampling time. Under conditions of strict sterility, the collected samples were obtained and promptly transported to the laboratory at a temperature of 4 °C for immediate analysis. Bacteria enumeration and isolation To determine the total bacterial count (TBC), a volume of 25 ml from each raw milk sample was utilized in the testing process. The samples were serially diluted tenfold to 10 5 with 0.1% sterile protein saline (w/v), 100 µl for each dilution, and plated on plate counting agar (PCA, Qingdao Hope Bio-Technology Co., Ltd., China). The plates were incubated at 37 °C for 48 h. The milk samples for psychrotrophic bacterial counts (PBCs) were diluted tenfold to 10 5 , and each dilution was cultured on milk powder count agar (MPC, Qingdao Hope Bio-Technology) at 7 °C for 10 days according to a previous method . The thermoduric bacteria were enumerated after subjecting the milk sample (5 ml) to a pasteurization simulation condition (62.8±0.5 °C for 30 min) followed by immediate refrigeration at 10 °C for 10 min. Then, the samples were serially diluted tenfold to 10 3 , and each dilution (100 µl) was spread on PCA in triplicates. The mesophilic and thermophilic thermoduric bacteria were cultured at 35±1 °C and 55±1 °C for 48 h, respectively . All the plates were incubated in aerobic constant temperature incubators. The standard bacterial count of each sample was shown as log c.f.u. ml −1 after incubation. The traditional culture-based method, as a gold standard, is widely used to isolate bacteria . Randomly, 50–60 colonies with different morphologies were selected from the counting plate (30–300 colonies) to ensure that one or more isolates represent different colony morphologies. The culture conditions were as follows: 25 °C for psychrotrophic bacteria, 37 °C for mesophilic thermoduric bacteria and 55 °C for thermophilic thermoduric bacteria. In total, except for non-culturable colonies, 356 isolates were collected for 16S rRNA gene sequencing. 16S rRNA gene amplification Psychrotrophic, mesophilic and thermophilic thermoduric bacteria were cultured in Luria Bertani broth (LB, Qingdao Hopebio Technology, China) at 25 °C, 35±1 °C and 55±1 °C for 24 h, respectively. The extraction of genomic DNA was carried out following the one-step water bath method . DNA concentration was not less than 20 ng µl −1 , and A260/A280 was between 1.8 and 2.0. The genomic DNA was employed as a template for performing PCR targeting the 16S rRNA gene, employing the universal primers 27F (5′- AGAGTTTGATCCTGGCTCAG -3′) and 1492R (5′- TACGGCTACCTTGTTACGACTT -3′). PCR amplification and agarose gel electrophoresis (AGE) verification were executed following the protocols established by Yang et al. . The amplified products were sent to BeiJing RuiBiotech Co., Ltd. (Beijing, China) for Sanger sequencing (3730xl DNA analyzer). Strains were identified by blasting sequencing results from the NCBIBLAST website ( http://www.ncbi.nlm.nih.gov/bLAST/ ). Metagenomics Two groups of milk samples from HLJ (A) and NMG (B) (three parallel samples each), collected in September 2022, were chosen for further omics analysis ( ). The replicate samples came from three samples in the same groups. The Mag-Bind Soil DNA Kit (OMEGA Bio-tek, GA) was utilized to extract the genomic DNA from the milk samples. The quantity and quality of extracted DNAs were measured using a Qubit 4 Fluorometer, with WiFi: Q33238 (QubitAssay Tubes: Q32856 and Qubit 1X dsDNA HS Assay Kit: Q33231) (Invitrogen, USA) and AGE, respectively. The extracted microbial DNA was processed to construct metagenome shotgun sequencing libraries with insert sizes of 400 bp by using Illumina TruSeq Nano DNA LT Library Preparation Kit. Each library was sequenced by Illumina NovaSeq platform (Illumina, USA) with PE150 strategy at Personal Biotechnology Co., Ltd. (Shanghai, China). A sequencing approach employing paired-end reads, with a target read length and insert size of 150 bp, was employed. Cutadapt (v1.2.1) was utilized to screen the paired-end raw data, obtaining high-quality CleanData for subsequent metagenomic analysis. The microbial composition spectrum was determined at both genus and species levels, identifying species that displayed significant differences between groups A and B based on the criteria of ⌈Log2(Fold change value)⌈ >1 and P< 0.05 by metagenomeSeq method . Alpha and beta diversities of the two groups of milk samples were computed by QIIME2 (v1.9.1) and R v.4.2.0 software ( http://www.R-project.org ) according to the species composition spectrum. In order to analyse and identify the dissimilarities between the two groups of milk samples, linear discriminant analysis effect size (LEfSe) was employed. The use of principal coordinate analysis (PcoA) plots allowed for the visualization of the beta diversity observed within the samples. Statistical methods were then used to select the core function and dominant species. To provide functional annotations to the sequencing data, databases namely the Kyoto Encyclopedia of Genes and Genomes (KEGG) (v2020_10_20) , the Evolutionary Genealogy of Genes: Non-supervised Orthologous Group (EggNOG) (v5.0), KEGG Orthology (KO) (v2020_10_20), Carbohydrate-Active enZymes Database (CAZy) (v2021_09_24) , Swissprot (v2021.9.24) and MEROPS (v2021.9.24) were utilized. Furthermore, the functionality of genes and proteins within the raw milk samples was analysed using the above database. All bioinformatic and statistical analyses were conducted using R software version 4.2.0 ( http://www.R-project.org ). The raw sequencing data for each sample were sorted, and the sequencing volume along with the proportion of high-quality bases was calculated to assess the overall quality of the sequencing. Subsequently, the raw data were screened and filtered using fastp (version 0.20.0), which involved removing 3' end-joint sequences and sequences shorter than 50 bp and those containing ambiguous bases. Minimap2 software (version 2.24-r1122, https://github.com/lh3/minimap2 ) was used to compare the above effective sequences and host sequences and then discarded host matching sequences in order to remove as many contaminating host sequences as possible, resulting in a CleanData set (i.e. a set of target sequences). Kraken2 (version 2.0.8-beta) was employed on the CleanData, utilizing microbial genome data from the National Center for Biotechnology (NCBI)’s RefSeq genome database as a reference to construct a database, with the confidence level set to 0.5 for annotation analysis. Non-target sequences were filtered out and subsequently spliced. Splicing was performed using MEGAHIT (v1.2.9) to retain contigs with a length of at least 300 bp. Finally, all contig sequences were merged. Using MMseqs2 software (v 13–45111), redundancy within the contig sequence set was eliminated based on a similarity threshold of 95% and a coverage of 90%, resulting in a non-redundant contig set. MetaGeneMark software (v3.26) ( http://exon.gatech.edu/GeneMark/ ) was then employed to predict prokaryotic microbiology and macro genome sequences, identifying ORFs and predicting coding regions to obtain the corresponding gene and protein sequences. The taxonomy module of MMseqs2 (v 13–45111) was utilized to compare the non-redundant protein sequences against the NCBI nr database (version 2021.10.11, corresponding to the download date), with the sensitivity parameter set to 5.7 and the lca-mode set to 4, allowing for the selection of species information with the highest alignment score as the representative species information for the protein gene sequences. 4D-DIA metaproteomic analysis To prepare the raw milk samples for analysis, they were mixed with SDT (SDS and DTT) lysis buffer containing 4% SDS, 100 mM Tris-HCl at a pH of 7.6, and then boiled for 15 min. The protein component of each sample was collected through centrifugation at 14 000 g for 40 min. The collected protein was quantified using the BCA Protein Assay Kit from Bio-Rad (USA). Next, 20 µg of protein from each sample was mixed with the appropriate 5× loading buffer and boiled for 5 min. The proteins were then separated using a 4–20% SDS-PAGE gel with a constant voltage of 180 V for 45 min. To visualize the protein bands, Coomassie Blue R-250 staining was used. For further analysis and quality control purposes, an equal aliquot from each sample was combined into one sample. This pooled sample would be used for data-dependent acquisition (DDA) library generation. Each sample was treated with DTT, a detergent known as detergent dithiothreitol, at a final concentration of 10 mM. The mixture was then blended at 600 r.p.m. for 1.5 h at a temperature of 37 ℃. Subsequently, to block reduced cysteine residues, iodoacetic acid (IAA) was added to the mixture at a final concentration of 20 mM. The samples were left to incubate in darkness for 30 min, following which they were cooled to room temperature. Next, the samples were purified and concentrated by transferring them to 10 kDa filters. To achieve this, the filters were washed three times with 100 µl of UA buffer (consisting of 8 M urea, 0.1 M Tris-HCl and 50 mM dithiothreitol) and twice with 100 µl of 25 mM NH 4 HCO 3 buffer. Subsequently, trypsin was introduced into the samples in a 1 : 50 trypsin to protein (wt/wt) ratio. The samples were incubated at 37 ℃ for 15–18 h (overnight), resulting in the collection of peptides as a filtrate. The desalting of each sample’s peptides was performed using C18 Cartridges (Empore SPE Cartridges C18), with a bed I.D. of 7 mm and a volume of 3 ml, sourced from Sigma. These peptides were then concentrated via vacuum centrifugation and reconstituted in 40 µl of 0.1% (v/v) formic acid. The estimation of the peptide content was accomplished by utilizing UV light spectral density at 280 nm. To conduct DIA experiments, indexed retention time (iRT) calibration peptides were added to the samples. The TIMSTOF (Trapped Ion Mobility Spectrometry Time of Flight) mass spectrometer (Bruker) was used to analyse all samples of fractions. It was connected to an Evosep One system liquid chromatography system (Denmark) to ensure accurate results. A dynamic exclusion of 24.0 s was implemented to avoid repetitive measurements. The ion source voltage was set at 1500 V, while the temperature was maintained at 180 ℃. A dry gas flow rate of 3 l min −1 was used. Ion mobility scanning was performed within the range from 0.75 to 1.35 Vs cm −2 , followed by eight cycles of PASEF (Parallel Accumulation–Serial Fragmentation) MS/MS scanning. The peptides from each sample were subsequently analysed using the TIMSTOF mass spectrometer (Bruker) in combination with the Evosep One system liquid chromatography (Denmark) operating in the DIA mode. The mass spectrometer recorded ion mobility MS spectra covering a mass range from m/z 100 to 1700. For accurate measurements, we carefully selected up to four windows, each corresponding to a 100 ms TIMS scan, based on the m/z-ion mobility plane. During PASEF MS/MS scanning, the collision energy was gradually increased from 20 eV at 1 /K0=0.85 Vs cm −2 to 59 eV at 1 /K0=1.30 Vs cm −2 , following a linear ramp. The DIA data were also analysed using the Spectronaut 14.4.200727.47784 software by searching the previously constructed spectral library. The main software parameters included dynamic iRT for retention time prediction, enabled correction for interference on the MS2 level and enabled cross-run normalization. The results were filtered based on a Q value cut-off of 0.01, equivalent to an FDR (False Discovery Rate) of less than 1%. Integrated multi-omics analysis To assess the relationship between proteomics data and microbial abundance, R software package ‘vegan’ was used to calculate the Bray–Curtis distance matrix for ‘proteomic data’ and ‘flora abundance’, respectively. Compare_distance_matrices.py (v 1.8.0) in QIIME software was used to conduct Mantel test statistical tests, and the samples were replaced (999 times) to evaluate the statistical significance (i.e. P -value) of the similarity between proteomics data and microbiome composition data. We employed the Mothur (version 1.41) for calculating the Spearman ranking correlation coefficient. The correlation coefficient matrix revealed the degree of association between the two variables (rho correlation coefficient ranges from −1 to 1). When −1＜rho＜0, the two variables exhibit a negative correlation; on the other hand, when 0＜rho＜1, a positive correlation is observed. A rho value of 0 corresponds to no correlation between the variables. R package corrplot (version 0.92) was used for generating heat map . Spearman’s correlation coefficient between proteomic data and microbial abundance was calculated. An association network was constructed for the related information of |rho|>0.8 and P value<0.01 and imported into Cytoscape software for visualization.
Twenty-four raw milk samples from milk tanks were collected from two different commercial dairy farms located in the Heilongjiang (HLJ) and Inner Mongolia Province (NMG) of China from August 2022 to April 2023. The milk samples were divided into eight groups of samples, and three parallel samples of each group were from the same tanks (commingled milk harvested from the same herd). The detailed sampling time is listed in . Three parallel samples (one group sample) were collected for every sampling time. Under conditions of strict sterility, the collected samples were obtained and promptly transported to the laboratory at a temperature of 4 °C for immediate analysis.
To determine the total bacterial count (TBC), a volume of 25 ml from each raw milk sample was utilized in the testing process. The samples were serially diluted tenfold to 10 5 with 0.1% sterile protein saline (w/v), 100 µl for each dilution, and plated on plate counting agar (PCA, Qingdao Hope Bio-Technology Co., Ltd., China). The plates were incubated at 37 °C for 48 h. The milk samples for psychrotrophic bacterial counts (PBCs) were diluted tenfold to 10 5 , and each dilution was cultured on milk powder count agar (MPC, Qingdao Hope Bio-Technology) at 7 °C for 10 days according to a previous method . The thermoduric bacteria were enumerated after subjecting the milk sample (5 ml) to a pasteurization simulation condition (62.8±0.5 °C for 30 min) followed by immediate refrigeration at 10 °C for 10 min. Then, the samples were serially diluted tenfold to 10 3 , and each dilution (100 µl) was spread on PCA in triplicates. The mesophilic and thermophilic thermoduric bacteria were cultured at 35±1 °C and 55±1 °C for 48 h, respectively . All the plates were incubated in aerobic constant temperature incubators. The standard bacterial count of each sample was shown as log c.f.u. ml −1 after incubation. The traditional culture-based method, as a gold standard, is widely used to isolate bacteria . Randomly, 50–60 colonies with different morphologies were selected from the counting plate (30–300 colonies) to ensure that one or more isolates represent different colony morphologies. The culture conditions were as follows: 25 °C for psychrotrophic bacteria, 37 °C for mesophilic thermoduric bacteria and 55 °C for thermophilic thermoduric bacteria. In total, except for non-culturable colonies, 356 isolates were collected for 16S rRNA gene sequencing.
Psychrotrophic, mesophilic and thermophilic thermoduric bacteria were cultured in Luria Bertani broth (LB, Qingdao Hopebio Technology, China) at 25 °C, 35±1 °C and 55±1 °C for 24 h, respectively. The extraction of genomic DNA was carried out following the one-step water bath method . DNA concentration was not less than 20 ng µl −1 , and A260/A280 was between 1.8 and 2.0. The genomic DNA was employed as a template for performing PCR targeting the 16S rRNA gene, employing the universal primers 27F (5′- AGAGTTTGATCCTGGCTCAG -3′) and 1492R (5′- TACGGCTACCTTGTTACGACTT -3′). PCR amplification and agarose gel electrophoresis (AGE) verification were executed following the protocols established by Yang et al. . The amplified products were sent to BeiJing RuiBiotech Co., Ltd. (Beijing, China) for Sanger sequencing (3730xl DNA analyzer). Strains were identified by blasting sequencing results from the NCBIBLAST website ( http://www.ncbi.nlm.nih.gov/bLAST/ ).
Two groups of milk samples from HLJ (A) and NMG (B) (three parallel samples each), collected in September 2022, were chosen for further omics analysis ( ). The replicate samples came from three samples in the same groups. The Mag-Bind Soil DNA Kit (OMEGA Bio-tek, GA) was utilized to extract the genomic DNA from the milk samples. The quantity and quality of extracted DNAs were measured using a Qubit 4 Fluorometer, with WiFi: Q33238 (QubitAssay Tubes: Q32856 and Qubit 1X dsDNA HS Assay Kit: Q33231) (Invitrogen, USA) and AGE, respectively. The extracted microbial DNA was processed to construct metagenome shotgun sequencing libraries with insert sizes of 400 bp by using Illumina TruSeq Nano DNA LT Library Preparation Kit. Each library was sequenced by Illumina NovaSeq platform (Illumina, USA) with PE150 strategy at Personal Biotechnology Co., Ltd. (Shanghai, China). A sequencing approach employing paired-end reads, with a target read length and insert size of 150 bp, was employed. Cutadapt (v1.2.1) was utilized to screen the paired-end raw data, obtaining high-quality CleanData for subsequent metagenomic analysis. The microbial composition spectrum was determined at both genus and species levels, identifying species that displayed significant differences between groups A and B based on the criteria of ⌈Log2(Fold change value)⌈ >1 and P< 0.05 by metagenomeSeq method . Alpha and beta diversities of the two groups of milk samples were computed by QIIME2 (v1.9.1) and R v.4.2.0 software ( http://www.R-project.org ) according to the species composition spectrum. In order to analyse and identify the dissimilarities between the two groups of milk samples, linear discriminant analysis effect size (LEfSe) was employed. The use of principal coordinate analysis (PcoA) plots allowed for the visualization of the beta diversity observed within the samples. Statistical methods were then used to select the core function and dominant species. To provide functional annotations to the sequencing data, databases namely the Kyoto Encyclopedia of Genes and Genomes (KEGG) (v2020_10_20) , the Evolutionary Genealogy of Genes: Non-supervised Orthologous Group (EggNOG) (v5.0), KEGG Orthology (KO) (v2020_10_20), Carbohydrate-Active enZymes Database (CAZy) (v2021_09_24) , Swissprot (v2021.9.24) and MEROPS (v2021.9.24) were utilized. Furthermore, the functionality of genes and proteins within the raw milk samples was analysed using the above database. All bioinformatic and statistical analyses were conducted using R software version 4.2.0 ( http://www.R-project.org ). The raw sequencing data for each sample were sorted, and the sequencing volume along with the proportion of high-quality bases was calculated to assess the overall quality of the sequencing. Subsequently, the raw data were screened and filtered using fastp (version 0.20.0), which involved removing 3' end-joint sequences and sequences shorter than 50 bp and those containing ambiguous bases. Minimap2 software (version 2.24-r1122, https://github.com/lh3/minimap2 ) was used to compare the above effective sequences and host sequences and then discarded host matching sequences in order to remove as many contaminating host sequences as possible, resulting in a CleanData set (i.e. a set of target sequences). Kraken2 (version 2.0.8-beta) was employed on the CleanData, utilizing microbial genome data from the National Center for Biotechnology (NCBI)’s RefSeq genome database as a reference to construct a database, with the confidence level set to 0.5 for annotation analysis. Non-target sequences were filtered out and subsequently spliced. Splicing was performed using MEGAHIT (v1.2.9) to retain contigs with a length of at least 300 bp. Finally, all contig sequences were merged. Using MMseqs2 software (v 13–45111), redundancy within the contig sequence set was eliminated based on a similarity threshold of 95% and a coverage of 90%, resulting in a non-redundant contig set. MetaGeneMark software (v3.26) ( http://exon.gatech.edu/GeneMark/ ) was then employed to predict prokaryotic microbiology and macro genome sequences, identifying ORFs and predicting coding regions to obtain the corresponding gene and protein sequences. The taxonomy module of MMseqs2 (v 13–45111) was utilized to compare the non-redundant protein sequences against the NCBI nr database (version 2021.10.11, corresponding to the download date), with the sensitivity parameter set to 5.7 and the lca-mode set to 4, allowing for the selection of species information with the highest alignment score as the representative species information for the protein gene sequences.
To prepare the raw milk samples for analysis, they were mixed with SDT (SDS and DTT) lysis buffer containing 4% SDS, 100 mM Tris-HCl at a pH of 7.6, and then boiled for 15 min. The protein component of each sample was collected through centrifugation at 14 000 g for 40 min. The collected protein was quantified using the BCA Protein Assay Kit from Bio-Rad (USA). Next, 20 µg of protein from each sample was mixed with the appropriate 5× loading buffer and boiled for 5 min. The proteins were then separated using a 4–20% SDS-PAGE gel with a constant voltage of 180 V for 45 min. To visualize the protein bands, Coomassie Blue R-250 staining was used. For further analysis and quality control purposes, an equal aliquot from each sample was combined into one sample. This pooled sample would be used for data-dependent acquisition (DDA) library generation. Each sample was treated with DTT, a detergent known as detergent dithiothreitol, at a final concentration of 10 mM. The mixture was then blended at 600 r.p.m. for 1.5 h at a temperature of 37 ℃. Subsequently, to block reduced cysteine residues, iodoacetic acid (IAA) was added to the mixture at a final concentration of 20 mM. The samples were left to incubate in darkness for 30 min, following which they were cooled to room temperature. Next, the samples were purified and concentrated by transferring them to 10 kDa filters. To achieve this, the filters were washed three times with 100 µl of UA buffer (consisting of 8 M urea, 0.1 M Tris-HCl and 50 mM dithiothreitol) and twice with 100 µl of 25 mM NH 4 HCO 3 buffer. Subsequently, trypsin was introduced into the samples in a 1 : 50 trypsin to protein (wt/wt) ratio. The samples were incubated at 37 ℃ for 15–18 h (overnight), resulting in the collection of peptides as a filtrate. The desalting of each sample’s peptides was performed using C18 Cartridges (Empore SPE Cartridges C18), with a bed I.D. of 7 mm and a volume of 3 ml, sourced from Sigma. These peptides were then concentrated via vacuum centrifugation and reconstituted in 40 µl of 0.1% (v/v) formic acid. The estimation of the peptide content was accomplished by utilizing UV light spectral density at 280 nm. To conduct DIA experiments, indexed retention time (iRT) calibration peptides were added to the samples. The TIMSTOF (Trapped Ion Mobility Spectrometry Time of Flight) mass spectrometer (Bruker) was used to analyse all samples of fractions. It was connected to an Evosep One system liquid chromatography system (Denmark) to ensure accurate results. A dynamic exclusion of 24.0 s was implemented to avoid repetitive measurements. The ion source voltage was set at 1500 V, while the temperature was maintained at 180 ℃. A dry gas flow rate of 3 l min −1 was used. Ion mobility scanning was performed within the range from 0.75 to 1.35 Vs cm −2 , followed by eight cycles of PASEF (Parallel Accumulation–Serial Fragmentation) MS/MS scanning. The peptides from each sample were subsequently analysed using the TIMSTOF mass spectrometer (Bruker) in combination with the Evosep One system liquid chromatography (Denmark) operating in the DIA mode. The mass spectrometer recorded ion mobility MS spectra covering a mass range from m/z 100 to 1700. For accurate measurements, we carefully selected up to four windows, each corresponding to a 100 ms TIMS scan, based on the m/z-ion mobility plane. During PASEF MS/MS scanning, the collision energy was gradually increased from 20 eV at 1 /K0=0.85 Vs cm −2 to 59 eV at 1 /K0=1.30 Vs cm −2 , following a linear ramp. The DIA data were also analysed using the Spectronaut 14.4.200727.47784 software by searching the previously constructed spectral library. The main software parameters included dynamic iRT for retention time prediction, enabled correction for interference on the MS2 level and enabled cross-run normalization. The results were filtered based on a Q value cut-off of 0.01, equivalent to an FDR (False Discovery Rate) of less than 1%.
To assess the relationship between proteomics data and microbial abundance, R software package ‘vegan’ was used to calculate the Bray–Curtis distance matrix for ‘proteomic data’ and ‘flora abundance’, respectively. Compare_distance_matrices.py (v 1.8.0) in QIIME software was used to conduct Mantel test statistical tests, and the samples were replaced (999 times) to evaluate the statistical significance (i.e. P -value) of the similarity between proteomics data and microbiome composition data. We employed the Mothur (version 1.41) for calculating the Spearman ranking correlation coefficient. The correlation coefficient matrix revealed the degree of association between the two variables (rho correlation coefficient ranges from −1 to 1). When −1＜rho＜0, the two variables exhibit a negative correlation; on the other hand, when 0＜rho＜1, a positive correlation is observed. A rho value of 0 corresponds to no correlation between the variables. R package corrplot (version 0.92) was used for generating heat map . Spearman’s correlation coefficient between proteomic data and microbial abundance was calculated. An association network was constructed for the related information of |rho|>0.8 and P value<0.01 and imported into Cytoscape software for visualization.
Bacterial enumeration As shown in , the TBC varied between 3.15 and 5.76 log c.f.u. ml −1 , with an average of 4.63 log c.f.u. ml −1 (4.34 log c.f.u. ml −1 for HLJ and 4.92 log c.f.u. ml −1 for NMG). The PBC ranged from 3.22 to 5.99 log c.f.u. ml −1 , with a mean value of 4.82 log c.f.u. ml −1 (4.77 log c.f.u. ml −1 for HLJ and 4.87 log c.f.u. ml −1 for NMG). It should be noted that these findings align with the study conducted by Yang et al. . The concentration of mesophilic thermoduric bacteria ranged from 2.38 to 4.9 log c.f.u. ml −1 with a mean value of 3.68 log c.f.u. ml −1 (2.87 log c.f.u. ml −1 for HLJ and 4.49 log c.f.u. ml −1 for NMG) and the concentration of thermophilic thermoduric bacteria ranged from 1 to 2.38 log c.f.u. ml −1 with a mean value of 1.81 log c.f.u. ml −1 for HLJ. Overall, TBC and PBC were higher in September 2022 compared to other months, and the concentration of thermophilic thermoduric bacteria was significantly higher in NMG than in HLJ. The HLJ group exhibited distinct thermophilic thermoduric bacteria that were not found in NMG. Psychrotrophic bacteria and thermoduric bacteria play a vital role in assessing the quality of raw milk and the final dairy products. According to a study conducted by Yuan et al. , it has been observed that the presence of psychrotrophic and thermoduric bacteria in dairy products can lead to degradation in quality and shelf-life. These bacteria have the ability to produce enzymes, specifically proteolytic and lipolytic enzymes, which are capable of withstanding high temperatures during heat treatments. It is crucial to consider various factors such as the sanitation conditions of the milking environment, the overall health of the animals, the packaging methods and the handling practices to prevent the contamination of dairy products with these bacteria . Furthermore, previous investigations have proven that the seasonal variations and the geographical positioning exert noteworthy influences on the community organization of psychrotrophic and thermoduric bacteria present in raw milk. Investigating the presence of psychrotrophic and thermoduric bacteria in raw milk is of great significance as it helps in understanding the sources of contamination and enables effective source control measures. According to Matta et al. , the threshold for milk spoilage to commence is ~10 6 c.f.u. ml −1 in terms of PBC levels and the milk samples in September 2022 were close to the value ( ). Identification of psychrotrophic and thermoduric bacteria using culture-based method The 16S rRNA PCR was conducted to determine the isolates at species or subspecies level . Using the culture-based method, a total of 356 colonies were obtained from eight raw milk samples. These colonies consisted of 212 psychrotrophic bacteria and 144 thermoduric bacteria, displaying variations in their morphologies. To identify these isolates, sequencing of the 16S rRNA gene was performed. The psychrotrophic bacteria isolates exhibited a wide range of diversity, belonging to 26 different genera and 50 species. Similarly, the mesophilic thermoduric bacteria isolates were classified into 20 genera and 32 species. In contrast, the thermophilic thermoduric bacteria isolates were limited to only two genera and two species ( ). This extensive characterization of the bacterial communities in our samples emphasizes their varied composition and abundance of psychrotrophic and thermoduric bacteria. The dominant genera of psychrotrophic bacteria were Pseudomonas , Lactococcus , Acinetobacter and Enterobacter . Within the Pseudomonas species, P. fluorescens is renowned for its significant contribution to milk and dairy product spoilage . Notably, most of Pseudomonas species were from samples of the dairy farm at NMG. Lactococcus and Acinetobacter were frequently isolated psychrotrophic genera, consistent with the findings from Bellassi et al. ’s study . The dominant genera of mesophilic thermoduric bacteria were Enterococcus , Enterobacter , Lactococcus and Bacillus. This result aligns with a previous study . Bacillus has been widely reported as thermoduric bacteria, which can survive in high-temperature processing in the form of spores and can also produce hydrolase, resulting in spoilage of milk . The thermophilic thermoduric bacteria have only been isolated from the dairy farm at HLJ. Deinococcus geothermalis and Staphylococcus pasteuri as thermophilic thermoduric bacteria have been isolated for the first time in this investigation. D. geothermalis was initially isolated from hot spring and runoff and its thermoduric proteins, such as amylosucrase and novel thermostable single-stranded DNA-binding protein, have been effectively expressed for diverse applications in molecule biology . Staphylococcus species are prominent pathogens within the mammary glands, frequently resulting in subclinical mastitis and sporadic clinical mastitis or enduring infection in dairy cows during lactation , which may come from cow’s teat, skin and unclean milking facilities and environment . Our result suggests that Enterococcus faecalis , Enterobacter cloacae , Enterobacter kobei , Enterobacter asburiae , Moraxella osloensis , Lactococcus lactis , Lactococcus raffinolactis and Leuconostoc pseudomesenteroides, exhibiting psychrotrophic and thermoduric traits, should attract more attention. Composition of psychrotrophic and thermoduric bacterial microbiota The results of sequencing depth and quality are summarized in Additional File S1. A total of 420 million reads and 63.48 billion bases were generated from the samples, yielding an average of 70.07 million reads and 10.58 billion bases per sample. The base identification accuracy exceeded 97%, reaching over 99%. The CleanData set contained an average of 491143 sequences. Furthermore, the assembly and splicing processes resulted in an average of 2627 scaffold sequences, with an N50 value of 708. These results indicated a successful splicing effect and suggested that the obtained metagenomic sequences are relatively complete. Based on the results of microbial enumeration, it was evident that the contamination in September 2022 was more severe compared to other months ( ). Consequently, the metagenomic investigation concentrated on the two groups of samples obtained from HLJ and NMG, designated as A and B, specifically from September 2022. Fig. S1 (available in the online version of this article) depicts the rarefaction curves, indicating that the sequencing depth adequately anticipated the diversity found in the samples. The classification class tree of micro-organisms in raw milk generated by GraPhlAn is shown in . Proteobacteria was the main group of psychrotrophic bacteria in raw milk, followed by Firmicutes and Bacteroidetes. The bacterial genus included Chryseobacterium , Staphylococcus and Moraxella with Staphylococcus aureus , Chryseobacterium bovis and M. osloensis main species. The dominant species in each sample were found at each classification level, as shown in . The abundance of the bacteria C. bovis varied between the two dairy farms, whereas the abundance of M. osloensis and S. aureus was similar. M. osloensis was identified during the screening of psychrotrophic and thermoduric bacteria, underscoring its environmental adaptability. L. lactis was detected as both psychrotrophic and mesophilic thermoduric bacteria. Other psychrotrophic bacteria identified, included Acinetobacter johnsonii and L. pseudomesenteroides . Variance of bacterial diversity between locations Through LEfSe analysis, 103 taxa were observed, exhibiting significant distinctions between groups A and B ( ). Specifically, 37 taxa showed a substantial prevalence within group A, while 66 taxa displayed a considerable prevalence within group B. The top 50 taxa with significant differences in relative abundance between the samples were presented by cluster analysis and heat map ( ). The analysis revealed that the sample replicates were clustered together, indicating good research consistency. The community profiles were significantly distinct between two dairy farms. Methyloversatilis , Acinetobacter and Pseudomonas were the dominant genus in group B. Leucothrix , Empedobacter , Lactobacillus , Leuconostoc , Bifidobacterium , Chryseobacterium and Lactococcus were the dominant genus in group A. The PCoA plot (Fig. S2) supported the observed differences. The study conducted by Du et al. aimed to explore the species diversity of psychrotrophic bacteria found in raw milk collected from various provinces in China, including Heilongjiang, Anhui, Jiangsu, Inner Mongolia, Gansu, Chongqing, Henan and Hunan. They found that the microbial compositions of Heilongjiang and Inner Mongolia were similar to other cities, with Pseudomonas , Stenotrophomonas and Enterococcus being highly isolated, which aligns with our study findings. Liang et al. found that Pseudomonas was the most abundant bacteria genus, followed by Lactococcus and Acinetobacter by using single-molecule real-time sequencing technology for raw milk from five provinces in China. Another research on mesophilic bacterial diversity in raw milk from southern Germany showed that Staphylococcus , Streptococcus or Janibacter , Chryseobacterium and Acinetobacter were the main bacterial genera by pure culture and high-throughput sequencing. Metaproteomic investigation of the microbial communities To assess the potential impacts of psychrotrophic and thermophilic bacteria on raw milk, we classified proteins using the KO database and completed functional characterization of the milk microbiota ( ). Overall, Chryseobacterium , Moraxella and Epilithonimonas could be key bacteria in raw milk. These bacteria were characterized as psychrotrophic bacteria, with Chryseobacterium and Moraxella also being classified as thermoduric bacteria. Various pathways, including glycolysis/gluconeogenesis, citrate cycle (TCA cycle), ascorbate and aldarate metabolism, ribosome, RNA transport, RNA degradation, RNA polymerase, pentose phosphate pathway, DNA replication and mineral absorption, were identified facilitating microbial growth and metabolism in raw milk. The activation of pathways, such as two-component system, quorum sensing, lipopolysaccharide biosynthesis and peptidoglycan biosynthesis pathways, was observed, indicating their role in supporting the stress resistance of microbial community and enabling them to adapt to the changing environment . The protein analysis detected various proteins associated with the bacterial secretion system, proteasome, protein export, biosynthesis of unsaturated fatty acids and protein digestion and absorption, suggesting the presence of potential proteases and lipases in the microbial community. The analysis of the microbiota revealed the presence of 36 proteins and 58 peptides in both sample groups through metaproteomics. A notable dissimilarity was observed in the bacterial protein profiles between the two groups of samples, as indicated by the principal component analysis (PCA) (Fig. S3a). There were three unique proteins distinguished from the two groups (Fig. S3b). The functions of 36 proteins were determined, as shown in Additional File S1. The functional characterization of the milk microbiota was classified by utilizing diverse protein ontology databases, which encompassedKO, eggnoggNOG, Swissprot, Cazyme and MEROPS. The functional classification overview is available in Additional File S1. A large number of peptidases were annotated, such as PepA aminopeptidase, aminopeptidase P3, HtpX peptidase and AlgW peptidase, which mainly came from Chryseobacterium , Epilithonimonas , Pseudomonas , Psychrobacter , Acinetobacter, Lactococcus, Escherichia and Bacillus . These results have been approved by many studies. PepA aminopeptidase has been reported in Escherichia coli , L. lactis and Tetragenococcus halophilus . Aminopeptidase P was identified from L. lactis previously . E. coli ’s HtpX peptidase is recognized as a cytoplasmic membrane zinc metalloproteinase belonging to the M48 family, whose function revolves around maintaining the quality control of membrane proteins . Although none of the above peptidase was detected by metaproteomics, the potential of specific bacteria in raw milk to produce hydrolytic peptidase has been confirmed. We speculated that the phenomenon was attributed to non-expression or little expression of the relevant proteolytic and lipolytic genes in fresh raw milk. Multi-omics analysis of microbial communities and identified proteins In order to work out the expression and function of psychrotrophic and thermoduric bacteria protein in fresh raw milk, the data from metagenomics and metaproteome were further integrated. The identified proteins were discovered to be linked with various psychrotrophic bacteria (including C. bovis , Acinetobacter guillouiae , Pseudomonas spp. and Leuconostoc mesenteroides ), thermoduric bacteria (including Lactobacillus paracasei , Kocuria varians and Streptococcus macedonicus ), and psychrotrophic/thermoduric bacteria (such as M. osloensis , L. lactis , L. pseudomesenteroides , L. raffinolactis , Chryseobacterium spp. and Acinetobacter spp.). shows the association between differentially abundant bacteria and expressed protein. The relative expression abundances of protein 10424, 15130, 20078, 755, 11520 and 11465 were high, whereas proteins 4115 and 2406 were low ( ). According to , the majority of microflora was correlated with small ribosomal subunit protein uS15 (protein 12030), malate dehydrogenase (protein 4801) and nucleoside-diphosphate kinase (NDPKs; protein 16465). Protein 4115 showed great species abundance, indicating a high level of protein expression. The CAZyme classified it as Glycoside Hydrolase Family 36 (GH36), which serves as U Intracellular trafficking, secretion and vesicular transport. GH36 exhibits α -galactosidase and α - N -acetylgalactosaminidase activity, firstly reported in an NMR study on the α -galactosidase GalA from Thermotoga maritima . It involves the formation of a covalent glycosyl-enzyme intermediate . We speculated that L. pseudomesenteroides may produce extracellular enzymes and result in lactose hydrolysis . Protein 16465 was identified as NDPKs derived from Acinetobacter sp. ( ) and Additional File S1. Additionally, Protein 16465 was associated tightly with Pseudomonas peli , indicating Pseudomonas spp. may play a role in promoting the protein expression of Acinetobacter spp. NDPKs found in the study are evolutionarily conserved enzymes that catalyse phosphoryl transformation between nucleosides . In bacteria, NDPKs appear as dimers or tetramers , showing important status in DNA and RNA biosynthesis. In addition, it actively participates in the synthesis of polysaccharides and proteins, while also playing a crucial role in energy metabolism. Protein 12030 was identified as AA4 by CAZyme annotation. The VAO (Vanillyl alcohol oxidase) enzymes, found in the AA4 family, perform the important role of facilitating the transformation of phenolic compounds that possess side chains located at the para-position of the aromatic ring. The EggNOG and Nr databases have assigned J as the annotation for Protein 12030, which is associated with translation, ribosomal structure and biogenesis. Similarly, CAZyme has annotated Protein 4801 as GH3. The Glycoside Hydrolase Family 3 category includes a variety of enzymes, such as exo-acting β - d -glucosidases, α - l -arabinofuranosidases, β - d -xylopyranosidases, N -acetyl- β - d -glucosaminidases (glycoside hydrolases) and N -acetyl- β - d -glucosaminide phosphorylases. One specific N -acetyl- β - d -glucosaminidase belonging to the GH3 family, known as NagZ, has been reported to play a role in bacterial cell wall recycling . In Gram-negative bacteria, NagZ removes GlcNAc from 1,6-anhydroMurNAc-peptides , whereas in Gram-positive bacteria, it removes GlcNAc from GlcNAc-MurNAc-peptides . According to Mark et al. , the NagZ product, which is known as 1,6-anhydroMurNAc-peptide, plays a crucial role in promoting the overproduction of AmpC β-lactamase in various Gram-negative micro-organisms. This particular compound has garnered attention as a potential target for therapeutic interventions . Protein 4801, annotated as C Energy production and conversion by eggnog and as malate dehydrogenase by KO and Nr, participates in diverse bioprocesses. These include the citrate cycle, metabolism of cysteine and methionine, pyruvate metabolism, glyoxylate and dicarboxylate metabolism, methane metabolism in different environments and the carbon metabolism pathway. Based on the aforementioned protein functions, a significant portion of the identified proteins was closely associated with bacterial growth and adaptation to the environment.
As shown in , the TBC varied between 3.15 and 5.76 log c.f.u. ml −1 , with an average of 4.63 log c.f.u. ml −1 (4.34 log c.f.u. ml −1 for HLJ and 4.92 log c.f.u. ml −1 for NMG). The PBC ranged from 3.22 to 5.99 log c.f.u. ml −1 , with a mean value of 4.82 log c.f.u. ml −1 (4.77 log c.f.u. ml −1 for HLJ and 4.87 log c.f.u. ml −1 for NMG). It should be noted that these findings align with the study conducted by Yang et al. . The concentration of mesophilic thermoduric bacteria ranged from 2.38 to 4.9 log c.f.u. ml −1 with a mean value of 3.68 log c.f.u. ml −1 (2.87 log c.f.u. ml −1 for HLJ and 4.49 log c.f.u. ml −1 for NMG) and the concentration of thermophilic thermoduric bacteria ranged from 1 to 2.38 log c.f.u. ml −1 with a mean value of 1.81 log c.f.u. ml −1 for HLJ. Overall, TBC and PBC were higher in September 2022 compared to other months, and the concentration of thermophilic thermoduric bacteria was significantly higher in NMG than in HLJ. The HLJ group exhibited distinct thermophilic thermoduric bacteria that were not found in NMG. Psychrotrophic bacteria and thermoduric bacteria play a vital role in assessing the quality of raw milk and the final dairy products. According to a study conducted by Yuan et al. , it has been observed that the presence of psychrotrophic and thermoduric bacteria in dairy products can lead to degradation in quality and shelf-life. These bacteria have the ability to produce enzymes, specifically proteolytic and lipolytic enzymes, which are capable of withstanding high temperatures during heat treatments. It is crucial to consider various factors such as the sanitation conditions of the milking environment, the overall health of the animals, the packaging methods and the handling practices to prevent the contamination of dairy products with these bacteria . Furthermore, previous investigations have proven that the seasonal variations and the geographical positioning exert noteworthy influences on the community organization of psychrotrophic and thermoduric bacteria present in raw milk. Investigating the presence of psychrotrophic and thermoduric bacteria in raw milk is of great significance as it helps in understanding the sources of contamination and enables effective source control measures. According to Matta et al. , the threshold for milk spoilage to commence is ~10 6 c.f.u. ml −1 in terms of PBC levels and the milk samples in September 2022 were close to the value ( ).
The 16S rRNA PCR was conducted to determine the isolates at species or subspecies level . Using the culture-based method, a total of 356 colonies were obtained from eight raw milk samples. These colonies consisted of 212 psychrotrophic bacteria and 144 thermoduric bacteria, displaying variations in their morphologies. To identify these isolates, sequencing of the 16S rRNA gene was performed. The psychrotrophic bacteria isolates exhibited a wide range of diversity, belonging to 26 different genera and 50 species. Similarly, the mesophilic thermoduric bacteria isolates were classified into 20 genera and 32 species. In contrast, the thermophilic thermoduric bacteria isolates were limited to only two genera and two species ( ). This extensive characterization of the bacterial communities in our samples emphasizes their varied composition and abundance of psychrotrophic and thermoduric bacteria. The dominant genera of psychrotrophic bacteria were Pseudomonas , Lactococcus , Acinetobacter and Enterobacter . Within the Pseudomonas species, P. fluorescens is renowned for its significant contribution to milk and dairy product spoilage . Notably, most of Pseudomonas species were from samples of the dairy farm at NMG. Lactococcus and Acinetobacter were frequently isolated psychrotrophic genera, consistent with the findings from Bellassi et al. ’s study . The dominant genera of mesophilic thermoduric bacteria were Enterococcus , Enterobacter , Lactococcus and Bacillus. This result aligns with a previous study . Bacillus has been widely reported as thermoduric bacteria, which can survive in high-temperature processing in the form of spores and can also produce hydrolase, resulting in spoilage of milk . The thermophilic thermoduric bacteria have only been isolated from the dairy farm at HLJ. Deinococcus geothermalis and Staphylococcus pasteuri as thermophilic thermoduric bacteria have been isolated for the first time in this investigation. D. geothermalis was initially isolated from hot spring and runoff and its thermoduric proteins, such as amylosucrase and novel thermostable single-stranded DNA-binding protein, have been effectively expressed for diverse applications in molecule biology . Staphylococcus species are prominent pathogens within the mammary glands, frequently resulting in subclinical mastitis and sporadic clinical mastitis or enduring infection in dairy cows during lactation , which may come from cow’s teat, skin and unclean milking facilities and environment . Our result suggests that Enterococcus faecalis , Enterobacter cloacae , Enterobacter kobei , Enterobacter asburiae , Moraxella osloensis , Lactococcus lactis , Lactococcus raffinolactis and Leuconostoc pseudomesenteroides, exhibiting psychrotrophic and thermoduric traits, should attract more attention.
The results of sequencing depth and quality are summarized in Additional File S1. A total of 420 million reads and 63.48 billion bases were generated from the samples, yielding an average of 70.07 million reads and 10.58 billion bases per sample. The base identification accuracy exceeded 97%, reaching over 99%. The CleanData set contained an average of 491143 sequences. Furthermore, the assembly and splicing processes resulted in an average of 2627 scaffold sequences, with an N50 value of 708. These results indicated a successful splicing effect and suggested that the obtained metagenomic sequences are relatively complete. Based on the results of microbial enumeration, it was evident that the contamination in September 2022 was more severe compared to other months ( ). Consequently, the metagenomic investigation concentrated on the two groups of samples obtained from HLJ and NMG, designated as A and B, specifically from September 2022. Fig. S1 (available in the online version of this article) depicts the rarefaction curves, indicating that the sequencing depth adequately anticipated the diversity found in the samples. The classification class tree of micro-organisms in raw milk generated by GraPhlAn is shown in . Proteobacteria was the main group of psychrotrophic bacteria in raw milk, followed by Firmicutes and Bacteroidetes. The bacterial genus included Chryseobacterium , Staphylococcus and Moraxella with Staphylococcus aureus , Chryseobacterium bovis and M. osloensis main species. The dominant species in each sample were found at each classification level, as shown in . The abundance of the bacteria C. bovis varied between the two dairy farms, whereas the abundance of M. osloensis and S. aureus was similar. M. osloensis was identified during the screening of psychrotrophic and thermoduric bacteria, underscoring its environmental adaptability. L. lactis was detected as both psychrotrophic and mesophilic thermoduric bacteria. Other psychrotrophic bacteria identified, included Acinetobacter johnsonii and L. pseudomesenteroides .
Through LEfSe analysis, 103 taxa were observed, exhibiting significant distinctions between groups A and B ( ). Specifically, 37 taxa showed a substantial prevalence within group A, while 66 taxa displayed a considerable prevalence within group B. The top 50 taxa with significant differences in relative abundance between the samples were presented by cluster analysis and heat map ( ). The analysis revealed that the sample replicates were clustered together, indicating good research consistency. The community profiles were significantly distinct between two dairy farms. Methyloversatilis , Acinetobacter and Pseudomonas were the dominant genus in group B. Leucothrix , Empedobacter , Lactobacillus , Leuconostoc , Bifidobacterium , Chryseobacterium and Lactococcus were the dominant genus in group A. The PCoA plot (Fig. S2) supported the observed differences. The study conducted by Du et al. aimed to explore the species diversity of psychrotrophic bacteria found in raw milk collected from various provinces in China, including Heilongjiang, Anhui, Jiangsu, Inner Mongolia, Gansu, Chongqing, Henan and Hunan. They found that the microbial compositions of Heilongjiang and Inner Mongolia were similar to other cities, with Pseudomonas , Stenotrophomonas and Enterococcus being highly isolated, which aligns with our study findings. Liang et al. found that Pseudomonas was the most abundant bacteria genus, followed by Lactococcus and Acinetobacter by using single-molecule real-time sequencing technology for raw milk from five provinces in China. Another research on mesophilic bacterial diversity in raw milk from southern Germany showed that Staphylococcus , Streptococcus or Janibacter , Chryseobacterium and Acinetobacter were the main bacterial genera by pure culture and high-throughput sequencing.
To assess the potential impacts of psychrotrophic and thermophilic bacteria on raw milk, we classified proteins using the KO database and completed functional characterization of the milk microbiota ( ). Overall, Chryseobacterium , Moraxella and Epilithonimonas could be key bacteria in raw milk. These bacteria were characterized as psychrotrophic bacteria, with Chryseobacterium and Moraxella also being classified as thermoduric bacteria. Various pathways, including glycolysis/gluconeogenesis, citrate cycle (TCA cycle), ascorbate and aldarate metabolism, ribosome, RNA transport, RNA degradation, RNA polymerase, pentose phosphate pathway, DNA replication and mineral absorption, were identified facilitating microbial growth and metabolism in raw milk. The activation of pathways, such as two-component system, quorum sensing, lipopolysaccharide biosynthesis and peptidoglycan biosynthesis pathways, was observed, indicating their role in supporting the stress resistance of microbial community and enabling them to adapt to the changing environment . The protein analysis detected various proteins associated with the bacterial secretion system, proteasome, protein export, biosynthesis of unsaturated fatty acids and protein digestion and absorption, suggesting the presence of potential proteases and lipases in the microbial community. The analysis of the microbiota revealed the presence of 36 proteins and 58 peptides in both sample groups through metaproteomics. A notable dissimilarity was observed in the bacterial protein profiles between the two groups of samples, as indicated by the principal component analysis (PCA) (Fig. S3a). There were three unique proteins distinguished from the two groups (Fig. S3b). The functions of 36 proteins were determined, as shown in Additional File S1. The functional characterization of the milk microbiota was classified by utilizing diverse protein ontology databases, which encompassedKO, eggnoggNOG, Swissprot, Cazyme and MEROPS. The functional classification overview is available in Additional File S1. A large number of peptidases were annotated, such as PepA aminopeptidase, aminopeptidase P3, HtpX peptidase and AlgW peptidase, which mainly came from Chryseobacterium , Epilithonimonas , Pseudomonas , Psychrobacter , Acinetobacter, Lactococcus, Escherichia and Bacillus . These results have been approved by many studies. PepA aminopeptidase has been reported in Escherichia coli , L. lactis and Tetragenococcus halophilus . Aminopeptidase P was identified from L. lactis previously . E. coli ’s HtpX peptidase is recognized as a cytoplasmic membrane zinc metalloproteinase belonging to the M48 family, whose function revolves around maintaining the quality control of membrane proteins . Although none of the above peptidase was detected by metaproteomics, the potential of specific bacteria in raw milk to produce hydrolytic peptidase has been confirmed. We speculated that the phenomenon was attributed to non-expression or little expression of the relevant proteolytic and lipolytic genes in fresh raw milk.
In order to work out the expression and function of psychrotrophic and thermoduric bacteria protein in fresh raw milk, the data from metagenomics and metaproteome were further integrated. The identified proteins were discovered to be linked with various psychrotrophic bacteria (including C. bovis , Acinetobacter guillouiae , Pseudomonas spp. and Leuconostoc mesenteroides ), thermoduric bacteria (including Lactobacillus paracasei , Kocuria varians and Streptococcus macedonicus ), and psychrotrophic/thermoduric bacteria (such as M. osloensis , L. lactis , L. pseudomesenteroides , L. raffinolactis , Chryseobacterium spp. and Acinetobacter spp.). shows the association between differentially abundant bacteria and expressed protein. The relative expression abundances of protein 10424, 15130, 20078, 755, 11520 and 11465 were high, whereas proteins 4115 and 2406 were low ( ). According to , the majority of microflora was correlated with small ribosomal subunit protein uS15 (protein 12030), malate dehydrogenase (protein 4801) and nucleoside-diphosphate kinase (NDPKs; protein 16465). Protein 4115 showed great species abundance, indicating a high level of protein expression. The CAZyme classified it as Glycoside Hydrolase Family 36 (GH36), which serves as U Intracellular trafficking, secretion and vesicular transport. GH36 exhibits α -galactosidase and α - N -acetylgalactosaminidase activity, firstly reported in an NMR study on the α -galactosidase GalA from Thermotoga maritima . It involves the formation of a covalent glycosyl-enzyme intermediate . We speculated that L. pseudomesenteroides may produce extracellular enzymes and result in lactose hydrolysis . Protein 16465 was identified as NDPKs derived from Acinetobacter sp. ( ) and Additional File S1. Additionally, Protein 16465 was associated tightly with Pseudomonas peli , indicating Pseudomonas spp. may play a role in promoting the protein expression of Acinetobacter spp. NDPKs found in the study are evolutionarily conserved enzymes that catalyse phosphoryl transformation between nucleosides . In bacteria, NDPKs appear as dimers or tetramers , showing important status in DNA and RNA biosynthesis. In addition, it actively participates in the synthesis of polysaccharides and proteins, while also playing a crucial role in energy metabolism. Protein 12030 was identified as AA4 by CAZyme annotation. The VAO (Vanillyl alcohol oxidase) enzymes, found in the AA4 family, perform the important role of facilitating the transformation of phenolic compounds that possess side chains located at the para-position of the aromatic ring. The EggNOG and Nr databases have assigned J as the annotation for Protein 12030, which is associated with translation, ribosomal structure and biogenesis. Similarly, CAZyme has annotated Protein 4801 as GH3. The Glycoside Hydrolase Family 3 category includes a variety of enzymes, such as exo-acting β - d -glucosidases, α - l -arabinofuranosidases, β - d -xylopyranosidases, N -acetyl- β - d -glucosaminidases (glycoside hydrolases) and N -acetyl- β - d -glucosaminide phosphorylases. One specific N -acetyl- β - d -glucosaminidase belonging to the GH3 family, known as NagZ, has been reported to play a role in bacterial cell wall recycling . In Gram-negative bacteria, NagZ removes GlcNAc from 1,6-anhydroMurNAc-peptides , whereas in Gram-positive bacteria, it removes GlcNAc from GlcNAc-MurNAc-peptides . According to Mark et al. , the NagZ product, which is known as 1,6-anhydroMurNAc-peptide, plays a crucial role in promoting the overproduction of AmpC β-lactamase in various Gram-negative micro-organisms. This particular compound has garnered attention as a potential target for therapeutic interventions . Protein 4801, annotated as C Energy production and conversion by eggnog and as malate dehydrogenase by KO and Nr, participates in diverse bioprocesses. These include the citrate cycle, metabolism of cysteine and methionine, pyruvate metabolism, glyoxylate and dicarboxylate metabolism, methane metabolism in different environments and the carbon metabolism pathway. Based on the aforementioned protein functions, a significant portion of the identified proteins was closely associated with bacterial growth and adaptation to the environment.
In this study, significant variations were observed in the microbial composition of raw milk samples across different sampling months and locations, indicating a notable diversity of psychrotrophic and thermoduric bacteria in the raw milk samples that were tested. The microbial compositions of psychotrophic and thermoduric bacteria were significantly distinct between the two dairy farms, specifically in the month of September 2022. The majority of proteins detected in the proteomic profiling were indicative of bacterial growth at an early stage, in strong association with bacterial growth, reproduction and adaptation to cold environments. However, the functional genes related to microbial hydrolases, proteases and lipases remained undetectable. A hypothesis proposes that the concentration of spoilage enzymes is anticipated to rise when the growth concentration surpasses a specific threshold. The comprehensive analysis through metagenomic and proteomics in our study offers valuable insights to better understand the potential impact of the microbial content influencing milk quality. Further investigation will be conducted to explore the potential impact of heat-resistant enzymes generated by psychrotrophic and thermoduric bacteria on the quality of milk.
10.1099/mgen.0.001311 Uncited Supplementary Material 1. 10.1099/mgen.0.001311 Uncited Supplementary Material 2.
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Resident factors associated with American board of internal medicine certification exam failure | 6208d704-8c0f-4d90-a74f-c672849f1c18 | 9718560 | Internal Medicine[mh] | Passing a certification exam – commonly referred to as a board exam or simply ‘the Boards’ – is an important milestone for the residency program graduate. Residency program staff also have an abiding interest in their graduates’ board exam performance. For example, beyond wanting graduates to succeed, residency programs must achieve specific aggregate certifying exam pass rates to meet the Common Program Requirements of the Accreditation Council for Graduate Medical Education (ACGME) . For internal medicine residency programs, for example, a 3-year rolling average first-attempt board exam pass rate of 80% or greater is required to meet accreditation standards. Identifying factors associated with exam performance can help programs ensure both graduate success and ongoing program accreditation. There is a gap between which factors educators expect to be linked to board exam performance and which associations have empirical evidence to support such a linkage. For example, in a 2013 survey, residency program directors proposed links between internal medicine board exam performance and various factors such as ACGME work hour requirements, performance on other standardized tests, teaching conference attendance, and competing personal obligations . Published data to test such hypotheses are scant but reliably show that higher scores on the USA Medical Licensing Examination (USMLE) and the Internal Medicine In-Training Examination (IM-ITE) are associated with a higher likelihood of passing the ABIM-CE. No association has been found between board exam performance and work hour requirements or competing personal obligations like parenting or recent life stressors. Investigators have found similar relationships in the fields of surgery and radiology, where written board exam performance is associated with performance on the USMLE or respective in-training exam , with no association between surgical board exam performance and work hour requirements . Teaching conference attendance may be associated with IM-ITE performance but is not independently associated with ABIM-CE performance . Within internal medicine, research regarding associations between passing the ABIM-CE and participation in specific clinical experiences is inconclusive , whereas participation in a mandatory research year in general surgery residency was associated with passing American Board of Surgery General Surgery Certifying Exam . Incorporating the timing of rotations with overnight call, however, investigators at the Cleveland Clinic developed a nomogram to determine an internal medicine resident’s probability of passing the ABIM-CE using IM-ITE scores and number of months with overnight call in the final 6 months of residency . Other investigators have examined links between ABIM-CE performance and characteristics including age , gender , time elapsed between medical school graduation and residency , fellowship interest , and scholarly productivity . No durable associations have been found between these individual factors and board exam performance. Single-center studies on this topic have examined associations over a short time span, and multicenter studies have tested for associations in only 1 year. Instruments used by faculty members to assess resident performance (e.g., ABIM Monthly Evaluation Form and ABIM Resident Evaluation Form are no longer used) have changed over time, and certain factors such as the content, frequency and length of required educational conferences vary by institution. The current study aimed to use data from a longitudinal sample to identify factors durably associated with first-attempt ABIM-CE performance among internal medicine residents from a medium-sized residency program in the USA.
We performed a retrospective study of all residents who graduated from the Internal Medicine Residency Program at Mayo Clinic in Arizona from 1998 through 2017. The program has full ACGME accreditation, and its size gradually increased from an initial 6 residents per class to its current 12 residents per class. The program is affiliated with a tertiary care hospital in a large metropolitan area in the Southwest USA. Residents in the program during the study period were provided access to ABIM-CE preparation resources, including the Medical Knowledge Self-Assessment Program, MedStudy Internal Medicine Board Review, and the opportunity to participate in a funded, off-site ABIM-CE preparatory course. Residents with IM-ITE performance below a prespecified score were enrolled in an individualized education plan with access to another question bank and check-ins from an associate program director. The study protocol was approved by the Institutional Review Board of the Mayo Clinic in Arizona (application 13–000080). The Board conducted a risk-benefit analysis, determined the study constituted minimal risk research, and waived the requirement to obtain informed consent. Residency program coordinators, the principal investigator, and a nonmedical volunteer abstracted demographic and scholastic data from archived files of all program graduates into a digital spreadsheet. Information was deidentified by these abstractors through substitution of a number for the graduate’s name, the key for which was kept by the principal investigator. Information collected and subsequently coded as binary variables included gender, marital status, primary language, medical degree type (e.g., MD, DO, MBBS, or MB, BCh), off-cycle residency graduation, Alpha Omega Alpha (AOA) Honor Medical Society membership, childrearing or childbearing in residency, graduation from a medical school outside the USA, graduate or professional degrees earned before starting residency, completing a rotation at the program’s institution before starting residency, board review course completion, a gap of at least 1 year between completion of medical school and starting residency, area of program director concern during residency, and publication of an article or abstract during residency. Information collected on work hour requirements was coded as a categorical variable, with specific requirements noted in . Data collected on the following factors were coded as continuous variables: USMLE scores, IM-ITE percentile ranks, distance of home address from program address, time separating medical school and residency graduation, and age on starting residency. Distance of a resident’s home address from the program’s street address was determined using the shortest driving route between the 2 locations according to Google Maps. We used univariate analysis to test associations between various resident factors and first-attempt ABIM-CE results classified as pass or fail. Binary and categorical variables are presented as counts and percentages. Continuous variables are presented as median (range or interquartile range). Associations were tested by using Fisher’s exact test for categorical variables and Wilcoxon rank sum test for continuous variables, and correlations were estimated with the Pearson correlation coefficient. P < 0.05 was the threshold for statistical significance. R Statistical Software version 3.6.2 was used to conduct the analysis.
Among 167 residents, 1 did not graduate and was excluded from analysis. Data from 166 graduates were included for analysis. One resident restarted the residency program after a leave of absence, and data from work before the leave of absence were excluded. The overall first-attempt board exam failure rate of graduates was 8.4% (n = 14). Resident demographic characteristics are summarized in . Compared with graduates who failed the board exam on the first attempt, graduates who passed on the first attempt started residency at a significantly younger median [interquartile range] age (no pass: 29 [28–31.8] years vs pass: 27 [26–29] years; P = 0.01) . There were no significant between-group differences among the other examined demographic factors . Graduates who passed the board exam on the first attempt had higher performance on standardized tests taken before and during residency, including median percentile ranks on the IM-ITE in each of the first (63 vs 36), second (71 vs 32), and third (69 vs 24.5) years of residency ( P < 0.001 for all) . Similarly, those who passed the ABIM-CE on the first attempt had higher median USMLE scores for Step 1 (222 vs 206; P = 0.02), Step 2 Clinical Knowledge (230 vs 210; P = 0.01), and Step 3 (221 vs 200; P < 0.001). There were no between-group differences in other scholastic performance factors evaluated . We next analyzed the correlation between age and IM-ITE and USMLE scores. Pearson correlation coefficients ranged from −0.07 to −0.22 . The correlation was significant between age and postgraduate year 2 IM-ITE score ( r = −0.19; P = 0.02), postgraduate year 3 IM-ITE score ( r = −0.22; P = 0.005), and USMLE Step 3 score ( r = −0.18; P = 0.03).
In our study population, residents who passed the ABIM-CE on the first attempt had higher performance on the USMLE and IM-ITE than did peers who failed the ABIM-CE. This is in line with findings of other investigators . Unlike in other investigations, however, we found that residents who passed the ABIM-CE on the first attempt also were younger at the start of residency than those who failed. Potential explanations for the correlation in our population between increasing age and decreasing USMLE Step 3 and IM-ITE scores are not readily apparent. We hypothesized that among residents in our study population, those entering residency at younger ages may have different average test scores than those entering at older ages. Further analysis identified a small negative correlation between age and some of the IM-ITE and USMLE scores. This suggests that those who were younger on entering residency had slightly higher exam scores during residency than did those who started residency at older ages. Residents who were older may be more likely to have more family commitments – marriage, childbearing, childrearing, or aging family members with caregiver needs – and competing time demands outside of work. However, those who were married, who bore children or who raised children were not significantly older on average than residents who were single and did not bear or raise children (28.7 years vs. 28.3 years, P = 0.47). Furthermore, there was no significant difference in the proportion of residents with such additional family commitments who passed the first-attempt ABIM-CE and those who failed (59.9% vs. 57.1%, P = 1.00). Future research with larger sample sizes and wider-ranging demographic data collection could help determine why an association might exist between certifying examination performance and age at residency entry. Burnout is associated with adverse physician and perhaps even patient outcomes , but data linking certification status to burnout are scarce. An association between burnout and ABIM-CE result makes intuitive sense. That adequate social support would decrease likelihood of developing burnout also makes intuitive sense, though data are conflicting. While Ripp and co-investigators reported no association between certain social supports and incident resident burnout, Ironside and colleagues reported residents perceive social relationships to be protective against burnout. Further, Salles and others reported an inverse association between social belonging and thoughts of leaving surgical residency. We did not design our study to test for an association between burnout and ABIM-CE performance. Following data collection, we hypothesized that residents who graduated from in-state medical schools might have more numerous local social ties and more robust social support networks, contributing to a higher likelihood of passing the ABIM-CE through lower rates of loneliness-associated conditions such as burnout. However, a lower proportion of our residents who passed the ABIM-CE graduated from an in-state medical school, though this difference was not statistically significant (17.8% vs. 28.6%, P = 0.30). Future studies with dedicated measurement of burnout would be valuable to determine whether an association exists between burnout and certifying exam performance. Additional factors that may potentially associate with board passage include AOA membership and post-residency fellowship pursuit. Of residents who passed the ABIM-CE in our cohort, a higher proportion were AOA members (19.1% vs. 0.0%), and a lower proportion pursued subspecialty practice after residency graduation (57.9% vs. 78.6%), though these differences were not statistically significant. Horn and colleagues in radiology and Shellito and others in general surgery found associations between resident AOA membership and passing results on their respective board exams. Grossman et al. evaluated those enrolled in fellowship programs when taking the ABIM-CE for the first time in 1991 were significantly more likely to pass the exam than were those not in fellowship. There are methodologic differences that do not allow direct comparison of our fellowship-trained graduates and those in the study by Grossman et al, namely that in our study some of our graduates took the ABIM-CE before entering fellowship. Our study’s strength was in inclusion of novel factors not examined in the existing internal medicine literature. These included AOA membership, completion of an audition rotation at our hospital while in medical school, and an estimate of commute distance. It also included results from data collected over a longer period than in other studies, a characteristic that might mitigate potentially confounding effects of broader changes in residency training and the ABIM-CE over time. Finding differences that do – or do not – endure over time may make those findings more reliable or externally valid. We acknowledge study limitations, including the size of the study. With the given ABIM-CE pass rate, the study was not powered to reach statistical significance for between-group differences of small magnitudes. The study is exploratory in nature, and to reduce type II error, no corrections were made for multiple. All findings require validation. Another limitation is that the study population includes residents at only 1 center. Residents in our residency program may not be representative of those in another, or of those in other specialties. Importantly, we did not collect data that reflected the program’s active efforts to increase the ABIM-CE pass rate. These efforts included implementing interventions such as medical knowledge enhancement opportunities for residents whose IM-ITE scores were concerning for failing the boards, and programs to systematically ensure all residents’ review of relevant topics. For instance, in 2019, the residency program created and offered protected time for third-year residents to attend a program-created weekly review of medicine topics and practice tests for those in the last six months of residency, with a 100% first-attempt ABIM-CE pass rate in the three years since. In addition, other than including the updated ACGME work hour rules, our study does not account for institutional factors that may influence resident performance. As examples, investigators have found possible associations between resident-specific ABIM-CE results and timing of certain clinical experiences , number of specific clinical experiences , and performance in a specific ambulatory curriculum . Additionally, residency program–level ABIM-CE pass rates may be associated with a program’s institutional classification (e.g., university program, university-affiliated community program), size, and location ; length of a program director’s tenure in that role ; program-level resident demographics ; faculty-to-resident ratio ; amount of external graduate medical education funding ; ACGME survey results ; and ACGME Residency Review Committee certification length . Knowledge of such factors could facilitate the creation of program-level interventions to offset the effects of individual factors associated with lower likelihood of passing the ABIM-CE. Lastly, as illustrated by the change in USMLE Step 1 score reporting, some of these variables may not be useful in the future. Critical appraisal of current assessment methods and markers of achievement may identify systemic issues, even if explanations for such issues can only be theorized. As an example, in the Summary Report and Preliminary Recommendations from the March 2019 Invitational Conference on USMLE Scoring (InCUS), Barone and others noted racial differences in USMLE performance that persisted despite examination content monitoring. Wijesekera and colleagues also found gender and racial disparities in which residency program applicants inducted into one or both of two honor societies. Decision-making in medical education should incorporate the highest quality empirical evidence as well as ethical principles. If a given measure of performance or achievement proves ineffective or conflicts with ethical principles, it should be removed from use.
The USMLE Step 1 score reporting has changed from a numeric score to pass or fail. Over time, evaluation instruments provided by the ACGME and specialty boards and used by residency program faculty members to assess resident performance have also changed. Accordingly, within internal medicine, association of faculty member assessment of resident performance and ABIM-CE result has been variable across time, with some investigators finding an association and others finding none . These points introduce uncertainty into attempts at the timely identification of residents at risk of failing their respective certifying examinations. Novel methods of assessment are needed to better predict performance on standardized measures of competence or achievement. The results of this study and others like it may help educators identify and deliver targeted interventions for residents at risk of failing the ABIM-CE, primarily those with low performance on standardized examinations before and during residency and those who started residency at an older age.
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Rigour and reproducibility in perinatal and paediatric epidemiologic research using big data | 899c25a2-0839-4c27-89c8-73ad3f6b5b5b | 10175126 | Pediatrics[mh] | RIGOUR AND BIG DATA Scientific rigour requires careful application of the scientific method in the design, conduct, analysis, interpretation, and reporting of a study to ensure results are robust and minimally biased. Randomised controlled trials are thought to provide the highest-quality evidence but are difficult to conduct in perinatal research due to narrow eligibility criteria and heightened ethical concerns in pregnancy and infancy. In the absence of randomised trials, rigorous evidence can be obtained from observational studies if selection bias and confounders, both measured and unmeasured, are sufficiently accounted for. Observational studies using big data may be particularly subject to selection bias since data are typically generated for clinical or commercial purposes rather than for research. Marginalised communities may be under-represented in EHRs and claim datasets because they receive less frequent care due to structural barriers. Wearables, commercial genetic tests, and social media may be more commonly used in populations with higher income and education levels. The systematic exclusion of certain populations in epidemiologic research cannot be fixed by relying on big data, and biased sampling frames may be harder to detect in pre-existing data sources. Studies constructing cohorts from population registries, EHRs, or claims data are vulnerable to left truncation bias when excluding early pregnancy losses or delayed pregnancy detection, as is common in perinatal studies. If factors that inform if an individual is represented in data also affect the perinatal relationship being studied, the resulting estimates will undoubtedly be biased. Selection biases cannot be easily ameliorated with big data, which only underscores the importance of both classical and novel approaches to detecting and minimising bias. G-methods (e.g., inverse probability weighting and doubly robust estimation) and quasi-experimental designs (e.g., instrumental variables and Mendelian randomization) can reduce bias and mimic RCTs with big data observational epidemiology. However, the rigour of evidence produced with these designs may be highly sensitive to investigators’ assumptions. For example, in a study using Mendelian randomization, Diemer et al demonstrated how risk differences for prenatal alcohol exposure and attention deficit hyperactivity disorder are sensitive to choices in instrument selection and homogeneity assumptions. Employing causal inference methods with big data does not necessarily eliminate bias, and investigators must carefully assess causal assumptions and be transparent about potential violations. Big data may be susceptible to measurement error if they are not primarily collected for research purposes. Insurance claims and EHRs have become popular data sources for epidemiologic research, but the codes and fields they contain are not used consistently in clinical practice and may portend low sensitivity and specificity. A recent study comparing automated EHR data extraction versus manual chart abstraction for obstetrics research found that automatically extracted measurements had high reliability overall but lower accuracy for variables related to care processes (e.g., labor induction) or requiring provider interpretation (e.g., postpartum haemorrhage). Even sophisticated computational tools can be subject to classical forms of information bias. Validation studies and quantitative bias analyses are useful tools to assess the extent of, and potentially correct for, measurement error and misclassification bias in big data studies. Machine learning (ML) can be used to construct new variables from high-dimensional data and free-text fields, such as the use of clustering algorithms by Petersen et al, to learn placental features from tissue samples. However, opaque training processes can mask how information is extracted and make it difficult to assess biases in model outputs. Algorithmic bias, in which predictive performance differs across subgroups, can introduce differential misclassification if model accuracy is driven by factors that are informative to the research question at hand. Algorithmic fairness and mitigation methods are essential to minimising these biases in future big data perinatal and paediatric studies. While big data may include numerous variables that could be controlled for as potential confounders, care must be taken to avoid over-adjustment bias. For example, gestational age is commonly adjusted for as a confounder when it may in fact mediate a causal question. Similarly, whether it is appropriate to treat pregnancy history as a time-dependent confounder depends on the specific research question. Directed acyclic graphs are an essential tool for distinguishing confounders from mediators and minimising over-adjustment and collider biases. , REPRODUCIBILITY AND BIG DATA Across scientific disciplines, the “reproducibility crisis” has exposed major vulnerabilities in the practice of science that are likely to increase as big data is used more frequently. New guidelines for rigour, reproducibility, and transparency from the National Institutes of Health and other funding bodies are an important first step. Yet, assessing rigour and reproducibility during funding decisions is not enough; researchers must embrace rigour and reproducibility best practices in every stage of their research . Researchers – no matter how well-intentioned or conscientious – are prone to confirmation bias. For example, during data curation and analysis, analysts make countless seemingly innocuous judgments that could cumulatively tilt them towards observing the expected effect. In addition, selective reporting of results from multiple statistical models (i.e., “p-hacking”) can produce apparent effects that otherwise are nonexistent. Conducting data processing and analyses with a masked version of the exposure or treatment variable can reduce confirmation bias because initial estimates viewed while checking code do not reflect study findings. Documenting and registering statistical pre-analysis plans holds researchers accountable to the methods they planned before seeing data. Big data studies involve code in every step, from constructing a study population to producing statistical estimates. Adopting reproducible computational workflows can reduce the chance of errors and streamline replication efforts. Best practices for maintaining these workflows include the use of open-source statistical software, modular analysis code, bash scripts, version control, and decision logs. Statistical software, such as R and Python, can be used to manage large multi-step analyses and compare intermediate data objects during replication. Breaking an analysis into modular, self-contained scripts allows researchers to assess the results of each step and efficiently identify points of replication failure. Bash scripts can be used to easily rerun scripts in the appropriate order to replicate study findings. Version control tools, such as Github, keep a history of scripts and allow researchers to annotate changes in scripts over time. They can be used to pinpoint specific edits that cause changes in results and make coding processes transparent. Researchers can use decision logs to clearly note necessary deviations from the pre-analysis plan, which increases transparency in reporting. Ideally, a study’s computational workflow can be easily replicated from data extraction through table/figure generation, even by investigators not part of the original study team. Having multiple analysts internally replicate data processing and analysis scripts before publication can catch and resolve unintentional errors in code or identify decisions in data processing that are highly impactful in the results. Publishing data and code alongside a study manuscript allows for greater transparency and makes results findable, accessible, interoperable, and reusable (FAIR). They facilitate replication of study results by other investigators and ultimately may lead to more rapid scientific advances. However, many big data sources contain sensitive information that cannot be made publicly available. Synthetic data can be generated to allow for the publication of de-identified data that retain the statistical properties of the original, sensitive dataset. For example, Braddon et al generated synthetic data from sensitive EHRs using parametric and non-parametric methods and showed that the synthetic data could closely replicate estimates from the original data used. When generating synthetic data, context-dependent rules should be enforced to avoid unrealistic relationships between variables. With careful implementation, these developments in data sharing and security can help make perinatal epidemiologic research more transparent and reproducible. CONCLUSIONS Articles in this special “Big Data” issue of Paediatric and Perinatal Epidemiology showcase the promise of big data for perinatal and paediatric epidemiology. Yet, with big data comes big responsibility. Using novel causal inference or machine learning methods with big data does not guarantee that a study is unbiased, and foundational epidemiologic methods to maximise study rigour remain just as essential as ever. As studies using big data become increasingly computationally intensive, best practices in reproducibility must become standard tools in the epidemiology toolbox. |
Status and influential factors of health literacy in patients with ischemic stroke: A cross-sectional study | 5805bd1c-e9a7-40fb-bc7a-3a55e6e4db96 | 11285942 | Health Literacy[mh] | The 2019 Global Burden of Disease showed that stroke is the second leading cause of death and the third leading cause of disability in the world . The global cost of stroke is estimated over US$ 891 billion (1.12% of the global gross domestic product) . The “China Stroke Surveillance Report 2021” showed that a total of 3,418,432 stroke cases were admitted in China during 2020, over 80% (81.9%) were ischemic stroke (IS), and the medical cost of hospitalization for stroke in 2020 was CNY 58.0 billion, of which the patient pays approximately CNY 19.8 billion . During the past three decades, in absolute terms, the global stroke incidence increased by 70%, its prevalence increased by 85%, and its mortality increased by 43%, with a greater increase in stroke burden in low-income and middle-income countries (LMICs) than in high-income countries . Stroke is characterized by high morbidity, disability, mortality and recurrence and is the leading cause of death and disability among Chinese adults . In a cross-sectional study of 676,394 participants aged 40 years and older, the estimated prevalence, incidence, and mortality rate of stroke in China in 2020 were 2.6%, 505.2 per 100 000 person-years, and 343.4 per 100 000 person-years . Ischemic stroke patients in the United States account for 87% of all stroke patients . In Sweden, approximately 22,000 people with a mean age of 75 years have a stroke each year, of whom 20% have a recurrent stroke . the China Stroke Prevention Project Committee (CSPPC) investigated 12-month stroke fatality and recurrence rates after the first-ever stroke through a prospective nationwide hospital-based cohort study and the data showed that the 12-month fatality rate for ischemic stroke survivors was 6.0%, and the recurrence rate was 6.4% . For people with ischemic stroke, the ability to understand and use health information is important to prevent recurrent strokes and to regain function . Health literacy (HL) refers to the ability of individuals to obtain, understand and process basic health information and services and make correct health-related decisions . At present, the level of health knowledge popularization among the masses is generally low. A European study found that 47% of the general population had limited (insufficient or problematic) health literacy . Most citizens of the Czech Republic (58.5%) have sufficient health literacy . A study on the level of health literacy of high-risk stroke groups in Jilin Province showed that only 18.03% of high-risk stroke groups had basic health literacy, and the overall level of health literacy was low . A recent study on cardiovascular and cerebrovascular disease outpatient patients in the United Arab Emirates reported that 39.3% of respondents possessed inadequate HL . In Taiwan, stroke history was reported in 4.3% of participants, and 25.3% reported low health literacy . Previous studies have shown that the treatment compliance of stroke patients is related to their health literacy level , and low health literacy may increase the risk of recurrence . The Healthy China Action Plan (2019–2030) revealed that the burden caused by chronic diseases such as cardiovascular and cerebrovascular diseases accounted for more than 70% of the total disease burden, and the health literacy level of residents was only 14.18% in 2017. Improving health literacy should be taken as the basic way to improve the health of all people to improve their health level. Among people with cardiovascular and cerebrovascular diseases, significant associations were found between higher health literacy and higher levels of physical activity, healthier diet, and better self-reported health outcomes . A study in patients with heart failure showed that low education level and household income level predicted poor health literacy . Limited health literacy prevents individuals and families from developing the knowledge, skills, and confidence necessary to engage or participate in their care . Although there have been studies on the status quo of health literacy in patients with stroke, there are few studies on the status quo and influencing factors of health literacy in patients with ischemic stroke. This study aimed to investigate the status quo and influencing factors of health literacy in patients with ischemic stroke.
2.1. Participants This study was a cross-sectional survey. Patients with ischemic stroke who were hospitalized in the Department of Neurology, West China Hospital, Sichuan University in China from January 2022 to May 2023 were selected as subjects using a convenience sampling method. The inclusion criteria were as follows: ① Diagnosed as having an ischemic stroke by a neurologist through CT and MRI; ②The patient was ≥18 years old; ③There was no cognitive impairment, no communication impairment; ④Vital signs are stable, and the patient could cooperate; and ⑤The patient volunteered to participate in this study and signed the consent form. The exclusion criteria were as follows: ① serious mental disorders; ② obvious dysfunction of the heart, liver and lung; ③ other serious complications; and ④ inability to cooperate with the questionnaire survey or inability to complete the questionnaire. This study was approved by the Ethics Committee of West China Hospital, Sichuan University in China number2019(728). 2.2. Instruments 2.2.1. General characteristics questionnaire We designed this questionnaire to assess the general characteristics of the patients. It mainly includes the patient’s age, gender, education level, occupation, family per capita monthly income, medical payment method, whether the patient has chronic diseases such as hypertension, whether the patient takes aspirin or clopidogrel and other antiplatelet agglutination drugs, and whether the patient takes lipid-lowering drugs. 2.2.2. National Institutes of Health Stroke Scale (NIHSS) The National Institutes of Health Stroke Scale (NIHSS) is a 15-item impairment scale used to measure stroke severity . The total score ranges from 0 to 42, and the higher the score is, the more serious the nervous system function injury . The NIHSS has moderate-to-high reliability when carried out by medical and nonmedical staff (intrarater κ = 0.66 to 0.77; interrater κ = 0.69). Very high reliability has also been demonstrated when clinicians rate from videos of patients (intrarater ICC = 0.93; interrater ICC = 0.95) . According to the Stroke Scale score of the National Institutes of Health, NIHSS > 14 was classified as severe stroke patients, and NIHSS≤14 was classified as mild to moderate stroke patients . 2.2.3. Health literacy scale The Health Literacy Scale for Chronic Patients (HLSCP) is a scale used to evaluate the health literacy level of patients with chronic diseases, and it was revised from the Health Literacy Management Scale . The scale has a total of 24 items, including the ability to obtain health information, the ability to communicate and interact, the willingness to improve health, and economic support. The Likert 5-level scoring method was adopted for each item, with a total score of 120. The higher the score, the better the health literacy. Cronbach’s α coefficient of the scale was 0.894, and the retest reliability was 0.683. When the score or total score of each dimension exceeds 80%, the patient’s health literacy level is considered to be good; that is, when the total score of health literacy is ≥96, the patient’s health literacy level is good. 2.3. Data Collection The patients completed the general demographic data questionnaire and health literacy survey of chronic disease patients by themselves. The researchers explained the purpose and significance of the study to the patients and their families and conducted a one-to-one questionnaire survey after obtaining the informed consent of the patients. For the patients who could not complete the questionnaire due to vision decline or illiteracy, the researchers assisted them. The questionnaire was completed according to the patient’s answers to ensure the completeness of the questionnaire. The National Institutes of Health Stroke Inventory was obtained by reviewing patient records. A total of 447 questionnaires were sent out in this study. After excluding invalid questionnaires, 423 valid questionnaires were collected , with an effective recovery rate of 94.6%. The average filling time was 10–20 minutes. 2.4. Statistical analysis Descriptive statistics and frequencies were carried out to describe the sociodemographic and health literacy scores. The scores of the HLSCP were tested for normality and are shown as the mean and standard deviation. The correlation between the NIHSS scores and the level of health literacy was calculated using the Spearman correlation coefficient. Before developing the multiple linear regression model, we checked the linear relationship between the independent variables and the dependent variables, the distribution of residuals, the variance of the residuals, the independence between the residuals, and the collinearity between independent variables. Meanwhile, multicollinearity, outliers and leverage points were also tested. Then, the forward stepwise regression method was used to select the regression variables, and the multiple linear regression model was developed after screening the meaningful indicators. Only variables with P <0.05 in the correlation analysis were included. SPSS 26.0 software was used for statistical analysis. Statistical tests were two-tailed, and statistical significance was set at 0.05.
This study was a cross-sectional survey. Patients with ischemic stroke who were hospitalized in the Department of Neurology, West China Hospital, Sichuan University in China from January 2022 to May 2023 were selected as subjects using a convenience sampling method. The inclusion criteria were as follows: ① Diagnosed as having an ischemic stroke by a neurologist through CT and MRI; ②The patient was ≥18 years old; ③There was no cognitive impairment, no communication impairment; ④Vital signs are stable, and the patient could cooperate; and ⑤The patient volunteered to participate in this study and signed the consent form. The exclusion criteria were as follows: ① serious mental disorders; ② obvious dysfunction of the heart, liver and lung; ③ other serious complications; and ④ inability to cooperate with the questionnaire survey or inability to complete the questionnaire. This study was approved by the Ethics Committee of West China Hospital, Sichuan University in China number2019(728).
2.2.1. General characteristics questionnaire We designed this questionnaire to assess the general characteristics of the patients. It mainly includes the patient’s age, gender, education level, occupation, family per capita monthly income, medical payment method, whether the patient has chronic diseases such as hypertension, whether the patient takes aspirin or clopidogrel and other antiplatelet agglutination drugs, and whether the patient takes lipid-lowering drugs. 2.2.2. National Institutes of Health Stroke Scale (NIHSS) The National Institutes of Health Stroke Scale (NIHSS) is a 15-item impairment scale used to measure stroke severity . The total score ranges from 0 to 42, and the higher the score is, the more serious the nervous system function injury . The NIHSS has moderate-to-high reliability when carried out by medical and nonmedical staff (intrarater κ = 0.66 to 0.77; interrater κ = 0.69). Very high reliability has also been demonstrated when clinicians rate from videos of patients (intrarater ICC = 0.93; interrater ICC = 0.95) . According to the Stroke Scale score of the National Institutes of Health, NIHSS > 14 was classified as severe stroke patients, and NIHSS≤14 was classified as mild to moderate stroke patients . 2.2.3. Health literacy scale The Health Literacy Scale for Chronic Patients (HLSCP) is a scale used to evaluate the health literacy level of patients with chronic diseases, and it was revised from the Health Literacy Management Scale . The scale has a total of 24 items, including the ability to obtain health information, the ability to communicate and interact, the willingness to improve health, and economic support. The Likert 5-level scoring method was adopted for each item, with a total score of 120. The higher the score, the better the health literacy. Cronbach’s α coefficient of the scale was 0.894, and the retest reliability was 0.683. When the score or total score of each dimension exceeds 80%, the patient’s health literacy level is considered to be good; that is, when the total score of health literacy is ≥96, the patient’s health literacy level is good.
We designed this questionnaire to assess the general characteristics of the patients. It mainly includes the patient’s age, gender, education level, occupation, family per capita monthly income, medical payment method, whether the patient has chronic diseases such as hypertension, whether the patient takes aspirin or clopidogrel and other antiplatelet agglutination drugs, and whether the patient takes lipid-lowering drugs.
The National Institutes of Health Stroke Scale (NIHSS) is a 15-item impairment scale used to measure stroke severity . The total score ranges from 0 to 42, and the higher the score is, the more serious the nervous system function injury . The NIHSS has moderate-to-high reliability when carried out by medical and nonmedical staff (intrarater κ = 0.66 to 0.77; interrater κ = 0.69). Very high reliability has also been demonstrated when clinicians rate from videos of patients (intrarater ICC = 0.93; interrater ICC = 0.95) . According to the Stroke Scale score of the National Institutes of Health, NIHSS > 14 was classified as severe stroke patients, and NIHSS≤14 was classified as mild to moderate stroke patients .
The Health Literacy Scale for Chronic Patients (HLSCP) is a scale used to evaluate the health literacy level of patients with chronic diseases, and it was revised from the Health Literacy Management Scale . The scale has a total of 24 items, including the ability to obtain health information, the ability to communicate and interact, the willingness to improve health, and economic support. The Likert 5-level scoring method was adopted for each item, with a total score of 120. The higher the score, the better the health literacy. Cronbach’s α coefficient of the scale was 0.894, and the retest reliability was 0.683. When the score or total score of each dimension exceeds 80%, the patient’s health literacy level is considered to be good; that is, when the total score of health literacy is ≥96, the patient’s health literacy level is good.
The patients completed the general demographic data questionnaire and health literacy survey of chronic disease patients by themselves. The researchers explained the purpose and significance of the study to the patients and their families and conducted a one-to-one questionnaire survey after obtaining the informed consent of the patients. For the patients who could not complete the questionnaire due to vision decline or illiteracy, the researchers assisted them. The questionnaire was completed according to the patient’s answers to ensure the completeness of the questionnaire. The National Institutes of Health Stroke Inventory was obtained by reviewing patient records. A total of 447 questionnaires were sent out in this study. After excluding invalid questionnaires, 423 valid questionnaires were collected , with an effective recovery rate of 94.6%. The average filling time was 10–20 minutes.
Descriptive statistics and frequencies were carried out to describe the sociodemographic and health literacy scores. The scores of the HLSCP were tested for normality and are shown as the mean and standard deviation. The correlation between the NIHSS scores and the level of health literacy was calculated using the Spearman correlation coefficient. Before developing the multiple linear regression model, we checked the linear relationship between the independent variables and the dependent variables, the distribution of residuals, the variance of the residuals, the independence between the residuals, and the collinearity between independent variables. Meanwhile, multicollinearity, outliers and leverage points were also tested. Then, the forward stepwise regression method was used to select the regression variables, and the multiple linear regression model was developed after screening the meaningful indicators. Only variables with P <0.05 in the correlation analysis were included. SPSS 26.0 software was used for statistical analysis. Statistical tests were two-tailed, and statistical significance was set at 0.05.
A total of 423 patients participated in the survey, of which 298 (70.4%) were male. There were 260 patients (61.5%) aged 60 years and above. The number of patients with a high school education or below was 312 (73.8%), and the number of patients with a bachelor’s degree or above was 47 (11.1%). The number of retired patients was 185 (43.7%). The number of spouses who were caregivers for patients was 216 (51.1%). There were 150 patients (35.5%) whose per capita family income was 5,000 yuan or above. Patients with other chronic diseases accounted for 80.1%. Most of the patients (74%) had urban employee medical insurance or urban resident medical insurance. The vast majority of patients (74.2%) lived with their partner . The results of the univariate analysis of influencing factors of health literacy in patients with ischemic stroke are shown in . Through the comparison of different demographic characteristics of patients, the univariate analysis showed that the health literacy levels of patients with ischemic stroke were different with different ages, educational levels, occupational statuses, caregivers, per capita monthly family income, types of medical insurance and living situations, and the differences were statistically significant ( P <0.05). The health literacy scores of patients with ischemic stroke are shown in . The total health literacy score was 99.13 ± 10.15. The average score of the 423 patients with ischemic stroke included in the study was 31.31±7.03 in the dimension of information acquisition ability and 41.09±8.30 in the dimension of communication and interaction ability. The average score of the improvement intention dimension was 17.87±3.27 points, and the average score of economic support intention was 8.86±1.35 points. The health literacy level of the patients with ischemic stroke in this study was 68.79%. The multifactor analysis of influencing factors of health literacy in patients with ischemic stroke is shown in . Health literacy in patients with ischemic stroke was generally divided into dependent variables, and significant correlation variables in the univariate analysis were taken as independent variables. Age, education, occupational status, caregiver, monthly income per capita in the family, type of health insurance, living situations and NIHSS scores were included as independent variables. Through multiple stepwise linear regression analysis, the results showed that age, education level, per capita monthly family income, living situations and NIHSS scores were the factors influencing the health literacy level of patients with ischemic stroke ( P <0.05).
This study investigated the health literacy level of patients with ischemic stroke during hospitalization and discussed the influencing factors of health literacy. The results showed that 68.79% of patients with ischemic stroke had a good level of health literacy. Results of a Swedish study investigated health literacy levels in stroke patients 12 months after discharge showed that 62% of participants had adequate health literacy . This was consistent with our findings, possibly because stroke patients received health care services both during hospitalization and after discharge, and received stroke-related health education, thereby learned more stroke-related health knowledge. The results of our study showed that participants’ willingness to improve their health scored the highest, indicating that participants were eager to recover their health after stroke and were willing to accept health education with a more positive attitude, so as to have a good level of health literacy. However in another study, only 18.03% of people at high risk for stroke had basic health literacy, indicating an overall low level . It was different from the results of our study, on the one hand, it may be because the participants’ basic knowledge level was low, the understanding of stroke was little, and the participants were mainly 45–69 years old, but also the life and career of the high risk group, so their health problems were often ignored . On the other hand, it may be because health knowledge about stroke prevention and treatment involved multiple specialties and was not widespread enough in daily life. Previous research has shown that health literacy can be spread and improved through interactions with social networks and healthcare professionals . Therefore, we can carry out health education for different groups through more diversified popular science methods to improve their health literacy level. The multiple stepwise linear regression analysis showed that degree of education, age, per capita monthly income, living situations and NIHSS scores were the main factors affecting ischemic stroke patients. In this study, the higher the education level of patients with ischemic stroke was, the higher the level of health literacy, which is basically consistent with the results of previous studies . Education was the basis of health literacy, and previous studies had identified the link between education levels and health literacy; well-educated elderly patients had better learning and understanding abilities . It may be that patients with higher education levels have a higher acceptance of health education and can take the initiative to obtain health information in the process of health promotion, thus having a higher level of health literacy. Lower education was associated with lower health literacy . Results from a multicenter study that explored the relationship between patient health literacy and disease perception and health-related quality mentioned that participants in eight out of 12 countries reported that the most common difficulty affecting health literacy was "reading and understanding all the information on pharmaceutical labels" . Patients with lower education levels have limited access to information due to limitations in reading and comprehension abilities, making it difficult to ensure the effectiveness of health education. This also suggests that we should focus on strengthening health education for people with lower educational levels in a more understandable way to improve the overall health literacy level of patients. Age was one of the factors affecting the health literacy level of patients with ischemic stroke. Older age was associated with lower levels of health literacy, which was consistent with previous research . Compared with patients aged between 18 and 44 years old, the health literacy level of elderly patients over 60 years old was lower . The possible reason is that with age, body function gradually decreases. The elderly’s ability to accept, understand, remember and learn new things was reduced, leading to a low level of health literacy . The majority of stroke patients are middle-aged and elderly, and their ability to understand and receive health information is lower than that of young people. Therefore, when conducting health education for patients with ischemic stroke, the frequency of health education should be appropriately increased according to the age and specific conditions of patients, so as to help patients master stroke-related health knowledge and improve their health literacy. In this study, patients with a per capita monthly family income of 3000 yuan and above had better health literacy. The level of health literacy of patients with ischemic stroke was also affected by the level of per capita monthly family income. This result is consistent with the research results of Lin and Xiao and Schaeffer et al. . Patients with higher income had higher health literacy scores, and patients were more willing to improve their health status after meeting their daily basic needs. They tend to invest more in their own health management, which may account for their higher level of health literacy . Patients with less income have little time and not much extra money to take care of their health to guarantee material life, which results in patients having less access to health information . The World Health Organization stresses that improving health literacy is a public health goal . Therefore, in order to ensure the effect of health education, personalized health education plans should be formulated according to the different ways of receiving health information for different income groups. Through diversified health education methods to improve their health literacy level. In this study, living situation was also one of the factors affecting the health literacy level of patients with ischemic stroke. Living with a spouse was associated with higher levels of health literacy than living with other people. Research by Shi, Y. et al showed that marital status and family structure played an important role in maintaining and promoting health literacy. Zhao, C. S. et al .found that there was a positive correlation between family function and health literacy level. After stroke, the self-care ability of patients decreased more or less, and the dependence on family and spouse increased. Therefore, when medical personnel carry out health education, the education object should include not only the patient himself but also the spouse of the patient. By improving the health literacy of family members and improving family function, the goal of improving the health literacy level of patients can be achieved . The NIHSS can comprehensively assess the dysfunction of patients after stroke. The higher the NIHSS scores, the more serious the neurological impairment. Patients with high NIHSS scores usually have physical dysfunction . Few previous studies have explored the relationship between NIHSS scores and health literacy in stroke patients. In this study, the higher the NIHSS scores of patients, the lower the level of health literacy. A previous study showed that health education can reduce the degree of neurological impairment in patients . Results of a study examining the relationship between health literacy and reduced depressive symptoms, improved perceived recovery, improved perceived engagement, and the ability to walk one year after stroke showed that health literacy was associated with post-stroke outcomes . So we can implement personalized health education for patients with different degrees of neurological impairment to improve their health literacy, so as to achieve the purpose of improving the prognosis.
There are some limitations to the study. A stratified random sampling method was not adopted in this study to select survey objects, and all the subjects were from one hospital, so the representativeness of survey objects may be affected to some extent. In future studies, the sample size and distribution range should be expanded as much as possible. In addition, this study only investigated the health literacy level of patients during hospitalization. But health literacy is dynamically changing, so future studies should continue to follow up the health literacy level of patients after discharge to further explore the relationship between health literacy and stroke prognosis.
An important finding of this study is that there is a negative correlation between NIHSS scores and health literacy levels. This study showed that the health literacy level of patients with ischemic stroke was good. Age, education level, per capita monthly family income, living conditions and NIHSS scores were all influencing factors. It is also necessary to propose targeted health education according to the influencing factors to improve the health literacy of patients and improve their health outcomes.
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Molecular diagnosis of hereditary spherocytosis by multi-gene target sequencing in Korea: matching with osmotic fragility test and presence of spherocyte | f8b7c713-ade5-4170-936f-92690308220e | 6533652 | Pathology[mh] | Hereditary spherocytosis (HS) is the most common cause of hereditary hemolytic anemia (HHA) characterized by the presence of spherocytes in peripheral blood smear (PBS) . HS occurs in 1 in 2000 Caucasians, with less common frequency in Asians . The crude incidence of HS in Korea was reported as 1 in every 5000 births . Approximately 75% cases of HS are inherited as autosomal dominant (AD) mutations, whereas the remaining cases involve autosomal recessive (AR) or de-novo mutations . HS is caused by a deficiency in or dysfunction of membrane proteins, including spectrin, ankyrin 1, band 3, and protein 4.2, associated with the RBC cytoskeleton . Defective membrane proteins disrupt the vertical linkage between the RBC membrane cytoskeleton and the phospholipid bilayer, causing RBCs to lose its biconcave characteristics and become spherical in shape . This abnormal RBC morphology leads to osmotically fragile cells that are selectively trapped and destroyed in the spleen . A major clinical manifestation of HS is hemolytic anemia, which exhibits a wide range of clinical manifestations from asymptomatic to life-threatening anemia requiring regular RBC transfusions . Other clinical symptoms include splenomegaly, jaundice, and gallstones, depending on disease severity . We have been operating the Korean Hereditary Hemolytic Anemia Working Party (KHHAWP) of the Korean Society of Hematology for 7 years since 2010, which name has been changed to RBC Disorder Working Party since November 2016. From 2007 to 2011, 195 patients (121 males and 74 females) diagnosed with HHA from 25 institutions were registered . The KHHAWP presented standard operating procedure (SOP) for the diagnosis of HHA (Fig. ) , which is similar to ICSH (International Council for Standardization in Haematology) guideline except for excluding acid glycerol lysis time test as a screening test. Instead of gel electrophoresis analysis of erythrocyte membranes, the KHHAWP adopted mass spectrometry method as a confirmatory test, which is performed in one central laboratory in Korea. The diagnosis of HS is based upon a combination of positive family history, clinical features and presence of spherocytes in PBS, which are detectable in 97% of patients . When the diagnosis of HS is equivocal, additional laboratory tests are recommended such as osmotic fragility test (OFT), autohemolysis test, flow cytometry [OFT and eosin-5-maleimide (EMA) binding test] for screening test, and protein analysis using gel electrophoresis or mass spectrometry can be additionally tested . However, none of the current diagnostic test can detect all patients with HS. Considering the limitations of existing diagnostic tests, development of a simple and direct method to measure RBC membrane protein abnormalities to confirm HS is required. Analysis of RBC membrane protein-encoding genes is expected that it can be used complementarily with the conventional confirmatory tests . Multi-gene target sequencing for RBC membrane protein-encoding genes is feasible and reliable diagnostic method to detect mutations in patients affected by various disorders of the RBC membrane. Particularly, gene testing is important in young children with congenital anemia, transfusion-dependent patients, and in families with variable clinical expression or complex inheritance patterns . In the present study, we investigated the genetic variation of RBC membrane protein-encoding genes using multi-gene target sequencing, comparing with clinical features. A total of 43 genes was included; 17 RBC membrane protein-encoding genes and 20 RBC enzyme-encoding genes, in context with six additional candidate genes for the purpose of differential diagnoses [thalassemia, congenital dyserythropoietic anemia (CDA), paroxysmal nocturnal hemoglobinuria (PNH), and Gilbert syndrome].
Patients A total of 59 patients with HS including 31 males and 28 females with a median age of 7 years (range: 1–81 years), were registered between July 2013 and July 2014 from the pediatrics and internal medicine departments of 25 institutions in Korea. HS was diagnosed according to the SOP recommended by the KHHAWP of the Korean Society of Hematology (Fig. ) . Along with clinical data including age, sex, symptoms and family history, we collected the results of laboratory tests including CBC with RBC index, reticulocyte count, total and direct bilirubin concentration, lactate dehydrogenase (LDH), iron, total iron-binding capacity (TIBC), ferritin, PBS, and OFT by reviewing medical records (Table ). Blood samples were collected from each patient after obtaining their written consent. Targeted sequencing To gain insight into the genetic variations, we performed targeted sequencing for 43 gene panel (Additional file : Table S1). gDNA shearing to generate the standard library and the hybridization step targeting only exonic regions were performed by Celemics Inc. (Seoul, Korea). The final quality was assessed using the Agilent 2200 TapeStation System (Santa Clara, CA, USA). We sequenced a total target length of 259-kb regions using the paired-end 150-bp rapid-run sequencing mode on an Illumina HiSeq 2500 platform. The mean sequencing depth for the targeted regions (259-kb) was 231-fold ( n = 59). Because a matched control sample was not included in this study, we applied a stringent variant selection pipeline to prioritize the high-confidence set of somatic mutations. Variant calling The filtration process was performed as follows. Variants within non-exonic regions were removed. Variants that do not have enough depth were also filtered out to remove false positives. Common variants on 1000 genome projects with more than 5% of allele frequency were filtered out. CADD score shows predictive pathogenicity of variants. It considers diverse annotations from allelic diversity to functionality, in order to estimate pathogenic variants. In this study, CADD scores below 10 were cut-off for filtration. After these filters, in-house variants were also removed to make filtered variant lists. Validation of variant call was performed by target gene sequencing of involved genes. Simulation of the effect of mutated genes on protein structure To predict how gene mutation affect protein structure, we visualized three-dimensional (3-D) spatial protein structure following acquisition of their structural information ( http://www.proteinmodelportal.org ) (Additional file : Table S2). We used PyMOL ( http://www.pymol.org ) to visualize 3-D representations of the protein, modified protein structures based on genetic mutation profiles from next-generation sequencing (NGS) results. Statistical analyses Stata/SE (v.14; StataCorp, College Station, TX, USA) was used for data analyses. Statistical differences in terms of continuous clinical characteristic variables were estimated by two sample t test. The significance of differences in categorical variables between groups was determined by the Pearson χ2 test or Fisher’s exact test. The level of significance was set at P < 0.05.
A total of 59 patients with HS including 31 males and 28 females with a median age of 7 years (range: 1–81 years), were registered between July 2013 and July 2014 from the pediatrics and internal medicine departments of 25 institutions in Korea. HS was diagnosed according to the SOP recommended by the KHHAWP of the Korean Society of Hematology (Fig. ) . Along with clinical data including age, sex, symptoms and family history, we collected the results of laboratory tests including CBC with RBC index, reticulocyte count, total and direct bilirubin concentration, lactate dehydrogenase (LDH), iron, total iron-binding capacity (TIBC), ferritin, PBS, and OFT by reviewing medical records (Table ). Blood samples were collected from each patient after obtaining their written consent.
To gain insight into the genetic variations, we performed targeted sequencing for 43 gene panel (Additional file : Table S1). gDNA shearing to generate the standard library and the hybridization step targeting only exonic regions were performed by Celemics Inc. (Seoul, Korea). The final quality was assessed using the Agilent 2200 TapeStation System (Santa Clara, CA, USA). We sequenced a total target length of 259-kb regions using the paired-end 150-bp rapid-run sequencing mode on an Illumina HiSeq 2500 platform. The mean sequencing depth for the targeted regions (259-kb) was 231-fold ( n = 59). Because a matched control sample was not included in this study, we applied a stringent variant selection pipeline to prioritize the high-confidence set of somatic mutations.
The filtration process was performed as follows. Variants within non-exonic regions were removed. Variants that do not have enough depth were also filtered out to remove false positives. Common variants on 1000 genome projects with more than 5% of allele frequency were filtered out. CADD score shows predictive pathogenicity of variants. It considers diverse annotations from allelic diversity to functionality, in order to estimate pathogenic variants. In this study, CADD scores below 10 were cut-off for filtration. After these filters, in-house variants were also removed to make filtered variant lists. Validation of variant call was performed by target gene sequencing of involved genes.
To predict how gene mutation affect protein structure, we visualized three-dimensional (3-D) spatial protein structure following acquisition of their structural information ( http://www.proteinmodelportal.org ) (Additional file : Table S2). We used PyMOL ( http://www.pymol.org ) to visualize 3-D representations of the protein, modified protein structures based on genetic mutation profiles from next-generation sequencing (NGS) results.
Stata/SE (v.14; StataCorp, College Station, TX, USA) was used for data analyses. Statistical differences in terms of continuous clinical characteristic variables were estimated by two sample t test. The significance of differences in categorical variables between groups was determined by the Pearson χ2 test or Fisher’s exact test. The level of significance was set at P < 0.05.
Clinical characteristics Among 59 patients with HS, 20 (33.9%) had a family history of HS, whereas symptoms of splenomegaly, neonatal jaundice, and hepatomegaly were exhibited in 38 of 59 (64.4%), 28 of 54 (51.9%), and 10 of 59 (16.7%) patients, respectively. Mean values for laboratory tests were as follows: hemoglobin concentration 8.4 g/dL (3.6–13.6 g/dL); corpuscular volume 80.9 fL (62.3–107.0 fL); corpuscular hemoglobin concentration 35.3 g/dL (30.8–38.2 g/dL); reticulocyte count indicating hemolysis 7.5% (0.5–24.8%); total bilirubin/direct bilirubin 4.1/0.7 mg/dL (0.8–19.1/0.2–1.3 mg/dL); LDH 508 IU/L (187–1557 IU/L); parameters representing iron profile, including iron 101 μg/dL (26–245 μg/dL), TIBC 266 μg/dL (108–486 μg/dL); and ferritin concentration, 342 ng/mL (32–4671 ng/mL). PBS was rated for spherocytes on a four-point scale from 0, 1+ or slight (2–5%), 2+ or moderate (6–15%), and 3+ or marked (> 16%) and the number of smears returning 0, 1+ or slight, 2+ or moderate and 3+ or marked were 5 (8.5%), 18 (30.5%), 20 (33.9%), and 16 (27.1%) patients, respectively. According to HS-severity criteria , severe, moderate, and mild cases were 26 (44.1%), 27 (45.8%), and 6 (10.2%) patients, respectively (Table ). Variants profile of RBC membrane protein-encoding genes Among 17 RBC membrane protein-encoding genes examined, significant disease-related mutations were observed in six: SPTB (spectrin, beta), ANK1 (ankyrin 1), SLC4A1 (solute carrier family 4, member 1), SPTA1 (spectrin, alpha 1), EPB41 (erythrocyte membrane protein band 4.1), and EPB42 (erythrocyte membrane protein band 4.2) (Fig. ). A total of 54 significant mutations were observed, of which eight were previously reported as pathogenic in patients with HS and 46 variants were novel mutations (Additional file : Table S3). The highest number of mutations were found in SPTB ( n = 28), and followed by ANK1 ( n = 19), SLC4A1 ( n = 3), SPTA1 ( n = 2), EPB41 ( n = 1), and EPB42 ( n = 1). According to the American College of Medical Genetics and Genomics guidelines , 12 were pathogenic mutations (including eight previously reported variants), 29 were likely pathogenic mutations, and 13 were classified as having uncertain significance. All the variants have been confirmed by Sanger sequencing using 35 primer sets (Additional file : Table S4). Variant characteristics in patients with HS Among 59 patients with HS, 50 (84.7%) had at least one mutation in a RBC membrane protein-encoding gene (Fig. ). Twenty eight patients carried mutations in the SPTB gene, and 20 patients had mutations in the ANK1 gene. Forty patients (67.8%) carried a single mutation, and 10 patients (16.9%) carried two mutations. Among 40 patients with a single mutation, the most frequently mutated genes were SPTB and ANK1 , which were mutated in 21 and 17 patients, respectively. The SCL4A1 mutation was found in two patients. Among the 10 patients harboring two mutations, one carried two mutations in a single gene ( ANK1 ), and three patients carried mutations in both SPTB and SPTA1 . Combinations of mutations in SPTB and ANK1 , SPTB and EPB41, and SPTB and EPB42 were detected in one patient each. In addition, combination with RBC enzyme-encoding gene mutations were found in three patients [ SLC4A1 and GAPDH (glyceraldehyde-3-phosphate dehydrogenase), ANK1 and GSR (glutathione reductase), SPTB and ALDOB (aldolase B)] (Additional file : Table S5). Nine patients carried no mutation on the RBC membrane protein- or enzyme-encoding genes. Coexisting mutations of UGT1A1 (UDP glycosyltransferase 1 family, polypeptide A1) gene were detected in 24 of 59 HS patients (40.7%), with UGT1A1 mutations combined with other gene mutations in 20 patients and without other gene mutation in four patients (Table , Additional file : Table S6). Total bilirubin level or presence of neonatal jaundice did not differ significantly from those without UGT1A1 mutations. Genotype and phenotype correlations in patients with HS Comparisons of laboratory findings and clinical characteristics showed no significant differences in hematologic parameters, hemolysis markers, iron status parameters, sex, family history of HS, number of splenectomized patients, and disease severity according to the gene mutation type and number of mutation or presence of UGT1A1 mutation (Table , Additional file : Table S6). Among 59 patients with HS, nine patients (15.3%) without mutation associated with RBC membrane protein-encoding genes showed similar baseline characteristics in most aspects as compared with those with mutations (Table ). Median age of patients without mutation was 8 years, and the proportion of family history, clinical symptoms, grading of peripheral spherocytes, and OFT results did not differ significantly from those with mutation. Intercorrelations between gene mutations and laboratory findings: OFT, the presence of spherocytes in PBS, and gene mutations The results of genetic test were matched with routine diagnostic tests for HS including OFT and the presence of spherocytes in PBS (Table , Fig. ). Among 59 patients with clinical HS, results of NaCl induced OFT (room temperature and/or 24 h incubated) was available in 47 patients and 41 of them (87.2%) showed positive results (Additional file : Figure S2). Thirty three of 47 patients (70.2%) showed positivity in both OFT and gene test, while one patients (2.1%) showed negative results in both OFT and gene test. In six out of 47 patients (12.7%) with negative OFT, five carried mutations in RBC membrane protein-encoding genes. Among 38 patients harboring HS-related gene mutations, 33 showed positive OFT (86.8%). Spherocytes in PBS were present in 54 of 59 patients (91.5%). Among five patients without spherocytes in PBS, four carried mutations in RBC membrane protein-encoding genes (Additional file : Table S7). One of 59 patients who had anemia and family history of HS showed negative results on all three tests.
Among 59 patients with HS, 20 (33.9%) had a family history of HS, whereas symptoms of splenomegaly, neonatal jaundice, and hepatomegaly were exhibited in 38 of 59 (64.4%), 28 of 54 (51.9%), and 10 of 59 (16.7%) patients, respectively. Mean values for laboratory tests were as follows: hemoglobin concentration 8.4 g/dL (3.6–13.6 g/dL); corpuscular volume 80.9 fL (62.3–107.0 fL); corpuscular hemoglobin concentration 35.3 g/dL (30.8–38.2 g/dL); reticulocyte count indicating hemolysis 7.5% (0.5–24.8%); total bilirubin/direct bilirubin 4.1/0.7 mg/dL (0.8–19.1/0.2–1.3 mg/dL); LDH 508 IU/L (187–1557 IU/L); parameters representing iron profile, including iron 101 μg/dL (26–245 μg/dL), TIBC 266 μg/dL (108–486 μg/dL); and ferritin concentration, 342 ng/mL (32–4671 ng/mL). PBS was rated for spherocytes on a four-point scale from 0, 1+ or slight (2–5%), 2+ or moderate (6–15%), and 3+ or marked (> 16%) and the number of smears returning 0, 1+ or slight, 2+ or moderate and 3+ or marked were 5 (8.5%), 18 (30.5%), 20 (33.9%), and 16 (27.1%) patients, respectively. According to HS-severity criteria , severe, moderate, and mild cases were 26 (44.1%), 27 (45.8%), and 6 (10.2%) patients, respectively (Table ).
Among 17 RBC membrane protein-encoding genes examined, significant disease-related mutations were observed in six: SPTB (spectrin, beta), ANK1 (ankyrin 1), SLC4A1 (solute carrier family 4, member 1), SPTA1 (spectrin, alpha 1), EPB41 (erythrocyte membrane protein band 4.1), and EPB42 (erythrocyte membrane protein band 4.2) (Fig. ). A total of 54 significant mutations were observed, of which eight were previously reported as pathogenic in patients with HS and 46 variants were novel mutations (Additional file : Table S3). The highest number of mutations were found in SPTB ( n = 28), and followed by ANK1 ( n = 19), SLC4A1 ( n = 3), SPTA1 ( n = 2), EPB41 ( n = 1), and EPB42 ( n = 1). According to the American College of Medical Genetics and Genomics guidelines , 12 were pathogenic mutations (including eight previously reported variants), 29 were likely pathogenic mutations, and 13 were classified as having uncertain significance. All the variants have been confirmed by Sanger sequencing using 35 primer sets (Additional file : Table S4).
Among 59 patients with HS, 50 (84.7%) had at least one mutation in a RBC membrane protein-encoding gene (Fig. ). Twenty eight patients carried mutations in the SPTB gene, and 20 patients had mutations in the ANK1 gene. Forty patients (67.8%) carried a single mutation, and 10 patients (16.9%) carried two mutations. Among 40 patients with a single mutation, the most frequently mutated genes were SPTB and ANK1 , which were mutated in 21 and 17 patients, respectively. The SCL4A1 mutation was found in two patients. Among the 10 patients harboring two mutations, one carried two mutations in a single gene ( ANK1 ), and three patients carried mutations in both SPTB and SPTA1 . Combinations of mutations in SPTB and ANK1 , SPTB and EPB41, and SPTB and EPB42 were detected in one patient each. In addition, combination with RBC enzyme-encoding gene mutations were found in three patients [ SLC4A1 and GAPDH (glyceraldehyde-3-phosphate dehydrogenase), ANK1 and GSR (glutathione reductase), SPTB and ALDOB (aldolase B)] (Additional file : Table S5). Nine patients carried no mutation on the RBC membrane protein- or enzyme-encoding genes. Coexisting mutations of UGT1A1 (UDP glycosyltransferase 1 family, polypeptide A1) gene were detected in 24 of 59 HS patients (40.7%), with UGT1A1 mutations combined with other gene mutations in 20 patients and without other gene mutation in four patients (Table , Additional file : Table S6). Total bilirubin level or presence of neonatal jaundice did not differ significantly from those without UGT1A1 mutations.
Comparisons of laboratory findings and clinical characteristics showed no significant differences in hematologic parameters, hemolysis markers, iron status parameters, sex, family history of HS, number of splenectomized patients, and disease severity according to the gene mutation type and number of mutation or presence of UGT1A1 mutation (Table , Additional file : Table S6). Among 59 patients with HS, nine patients (15.3%) without mutation associated with RBC membrane protein-encoding genes showed similar baseline characteristics in most aspects as compared with those with mutations (Table ). Median age of patients without mutation was 8 years, and the proportion of family history, clinical symptoms, grading of peripheral spherocytes, and OFT results did not differ significantly from those with mutation.
The results of genetic test were matched with routine diagnostic tests for HS including OFT and the presence of spherocytes in PBS (Table , Fig. ). Among 59 patients with clinical HS, results of NaCl induced OFT (room temperature and/or 24 h incubated) was available in 47 patients and 41 of them (87.2%) showed positive results (Additional file : Figure S2). Thirty three of 47 patients (70.2%) showed positivity in both OFT and gene test, while one patients (2.1%) showed negative results in both OFT and gene test. In six out of 47 patients (12.7%) with negative OFT, five carried mutations in RBC membrane protein-encoding genes. Among 38 patients harboring HS-related gene mutations, 33 showed positive OFT (86.8%). Spherocytes in PBS were present in 54 of 59 patients (91.5%). Among five patients without spherocytes in PBS, four carried mutations in RBC membrane protein-encoding genes (Additional file : Table S7). One of 59 patients who had anemia and family history of HS showed negative results on all three tests.
Using multi-gene target sequencing, 50 of 59 patients (84.7%) of clinically diagnosed HS proved to be molecular HS and three patients harbored coexisting gene mutations of RBC enzymes ( ALDOB, GAPDH, and GSR ) in this study. Mutations of six kinds of RBC membrane protein-encoding genes (total 54 variants) were detected in order of SPTB , ANK1 , SLC4A1 , SPTA1 , EPB41 , and EPB42 . To find whether there is an ethnic difference in HS related variants, we reviewed the literatures on the reports of HS related mutations in comparison with the results of the present study, although the methods are different among reported mutations of HS. Table shows summary of comparison among previous reports by NGS . With regards to the frequency of mutated gene, the SPTA1 mutation was the most common followed by the SPTB mutation in the reports from the United States . Meanwhile, a study in Netherland revealed that the ANK1 mutation was the most common mutation followed by the SPTA1 mutation . In the present study, SPTB mutations was the most common mutation, followed by ANK1 mutations. Particularly noteworthy, SPTA1 mutations was rarely detected, compared to that of the United States. Briefly, mutation frequency by NGS study in Korean was different from those of Caucasian. Korean patients with HS showed higher frequency of ANK1 mutation. Consistent with our study, another study in Korea reported that 25 patients with HS carried one heterozygous mutation of ANK1 ( n = 13) or SPTB ( n = 12) but none carried mutations in SPTA1 , SLC4A1 , or EPB42 by Sanger sequencing . Previous molecular testing demonstrated that mutations in the ANK1, SPTB, SLC4A1, SPTA1 , and EPB42 genes account for 60, 10, 15, 10, and 5% cases of HS, respectively, in the United States and Europe . Ethnic differences in RBC membrane protein defects were also reported in previous studies according to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analyses (Table ) . A Korean study in 2000 reported that protein 4.2 defects were detected at a higher frequency than those of band 3 in the United States and Europe. That study also reported that most defects were found in ankyrin 1 according to SDS-PAGE analysis, whereas most mutations were detected in the SPTB followed by ANK1 , according to our NGS results. Additionally, protein defects were not observed was nine out of 27 patients (33.3%) . Meanwhile, single defects in band 3 and spectrin constitute the primary variants reported in Italy , and a combined defect in spectrin/ankyrin is frequently detected in patients in the United States and Spain . Regarding to the incidence of HS, an incidence of Japan is highest among Asian countries, and the defect in the 4.2 protein in Japan is more frequent as compared to the United States and Europe . Those different profiles of HS among countries might be due to complexity associated with SDS-PAGE methods and lack of objectiveness in the interpretation of the results. The interpretation of SDS-PAGE is based on the comparison with normal healthy control. For that reason, the standardization is not possible and the comparison of SDS-PAGE results cannot give a meaningful conclusion. By contrast, nucleotide sequence analysis gives us straightforward results, and the interpretation of results is objective. Inherited pattern of HS differs depending on the gene. In most HS patients, inheritance is AD and each of HS patients has a unique mutation . However, SPTA1 or EPB42 mutation is inherited with AR pattern. Rarely, double dominant HS due to defects in SLC4A1 or SPTB are reported , which results in fetal death or severe transfusion-dependent hemolytic anemia presenting in the neonatal period. SPTB and SPTA1 mutations can be AD or de novo, whereas ANK1 mutation can be AD, AR, or de novo. SLC4A1 mutation is AD and EPB42 is AR. Inherited pattern is not clearly revealed in EPB41 . Of note, all the significant variants in RBC membrane protein-encoding genes are heterozygous. Hence, mutations of genes inherited in AR pattern such as EPB41 and EPB42 gene possibly cannot be a direct cause of HS, requiring additional mutation to cause hemolytic phenotype. In the present study, two patients harboring EPB41 and EPB42 mutations also carried another mutation in the SPTB gene ( EPB41 and SPTB , EPB42 and SPTB in each patient). Interestingly, concurrent mutations of genes encoding RBC enzymes ( ALDOB, GAPDH , and GSR ) were detected along with heterozygous mutations of RBC membrane protein-encoding genes in three patients. Further analysis of enzyme activities in these patients is necessary for validation. Of the 59 patients with HS examined in this study, 24 (40.7%) had significant UGT1A1 variants. It was reported that a polymorphism of UGT1A1 gene promoter homozygous insertion of TA pairs (genotype UGT1A1 *28/*28) might results in a decrease in bilirubin glucuronidation activity, leading to hyperbilirubinemia and late complication of patients with HS, such as development gallstones . In contrast, there are debates on the late impact of genotype of UGT1A1 . However, a polymorphism of UGT1A1 gene promoter was not included in this study. Based on the results of the present study showing high frequency of UGT1A1 variant with low enzymatic activity, we infer that genotyping of UGT1A1 polymorphism might help to predict the development of gallstones in HS. The laboratory diagnosis of HS routinely relies on the presence of spherocytes in PBS, OFT, and more recently EMA binding test . Yet, there is no single test that can confirm HS. We have matched the results of genetic test with those of routine diagnostic tests (Table ). Among 50 patients harboring mutations of encoding RBC membrane protein, 86.8% showed positive OFT, while 70.2% of clinical HS showed positive OFT. On the contrary, eight patients (17.0%) with positive OFT result revealed no mutation of membrane genes, and five (10.6%) with negative OFT proved to harbor membrane gene mutation. Regarding to spherocytes, four of 50 patients (8%) harboring membrane gene mutation did not show spherocytes in PBS. We retrospectively reviewed PBS to determine the presence of spherocytes in those four patients who did not show spherocytes in PBS but with RBC membrane protein-encoding gene mutations. However, we could not detect additional spherocytes. Conclusively, OFT and spherocytes in PBS can be used in conjunction with genetic test for the -diagnosis of HS, giving higher sensitivity and specificity. With regards to the genotype-phenotype relationship, we could not find any correlation between the genetic test results and clinical characteristics including disease severity, mean hemoglobin concentrations, splenomegaly, gallstones, aplastic crisis and bilirubin levels according to mutations of four genes ( SPTB, ANK1, SPTA1, and SLC4A1 ), except EPB41 and EPB42 , which were found in only one patient each, However, one study reported that anemia was most severe in HS patients with mutations on the ANK1 spectrin-binding domain and splenectomy was more frequently performed in patients with ANK1 mutations than in those with SPTB mutations . In addition, the other reported that hemoglobin concentration was slightly lower in patients with spectrin deficiency than with band 3 deficiency . Other NGS study on RBC membrane diseases reported similar results (86.3%, 44 of 51 patients) . This finding suggested a close correlation between clinical diagnosis and gene mutations. In the present study, molecular test could detect additional HS which could be missed without molecular test (Fig. ). Furthermore, molecular test would be an effective method for neonates or transfused individuals, since the result of OFT and spherocytes in PBS can be unreliable, especially when the patients are transfused . Collectively, our results suggest that mutation analyses will complement with other conventional tests for accurate diagnosis of HS. We consider the molecular test needs to be integrated to the diagnostic criteria of HS. The limitation of this study is that we did not perform the analysis on RBC membrane protein as a validation. Instead, we simulated 3-D spatial structure of protein encoding mutated genes, predicting the effects of gene mutations in silico. Although exact changes in protein structure cannot be predicted based on 3-D spatial structure, large-scale modification of the protein due to frame shift or nonsense mutations can be visualized and subsequent functional changes can be expected from structure analysis. Further family study or functional studies using knockout mice needs to be conducted to validate the significance of variants. Another limitation is that we could not match the results of EMA binding test with genetic results, since our study was done retrospectively. Nine patients who did not harbor gene mutation of RBC membrane protein (Additional file : Table S8), satisfied the diagnostic criteria of HS suggested in the guideline . Though they satisfied those criteria, there are two possibilities that they have other forms of hemolytic anemia or other membrane gene mutations that is not included in our multi-gene panel (e.g. channel defects such as KCNN4 as found in hereditary stomatocytosis) . When we target the most frequent mutations only, composition of gene panel with genes over 10% frequency ( SPTB and ANK1 ) will cover 94% (47 of 50 patients) of the diagnosis of HS. This could provide a cheaper and more convenient method than current strategies for diagnosis of HS. Regarding to the diagnostic guidelines suggested by international working parties, we suggest that genetic test should be conducted at least in patients without clues of laboratory tests in spite of clinically suspected HS.
This constitutes the first large-scaled genetic study of Korean patients with HS. We detected 54 significant HS-related mutations, including 46 novel mutations in RBC membrane protein-encoding genes. We demonstrated that multi-gene target sequencing is sensitive and feasible that can be used as a powerful tool for diagnosing HS. Considering the discrepancies between clinical and molecular diagnoses, use of molecular genetics analysis provides an effective method for improving the accuracy of HS diagnosis.
Additional file 1: Figure S1. Significant variants diagrams for UGT1A1 gene. Figure S2. Results of NaCl induced OFT. Table S1. Multi-gene panel for targeted sequencing. Table S2. List of protein simulation templates. Table S3. List of significant variants detected in RBC membrane protein-encoding genes. Table S4. Primer sets for all significant variants in RBC membrane protein-encoding genes. Table S5. List of significant variants detected in RBC enzyme-encoding genes among patients with HS. Table S6. List of UGT1A1 gene variants in patients with HS in Korea. Table S7. Clinical characteristics of patients with HS without peripheral blood spherocytes. Table S8. Patients without RBC membrane-encoding gene mutation. (DOCX 114 kb)
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Identification and growth-promoting effect of | 88775a0d-4bf6-4e17-841d-54ea635e9e11 | 11623802 | Microbiology[mh] | Walnut ( Juglans regia L.) is a significant economic tree species within the walnut genus Pidaceae and ranks as one of the world’s four major dried fruits, boasting rich nutritional and medicinal value . Xinjiang stands as the second-largest province for walnut cultivation in China, with a planting area that reached 4.14x10 5 hm 2 and an annual output of 1.15x10 6 t in 2020 . However, in recent years, the extensive walnut planting in Xinjiang has been plagued by walnut rot disease, significantly impeding the healthy growth of the walnut industry in the region . Presently, disease management relies heavily on chemical control methods, but these chemical fungicides pose various issues, including environmental pollution, risks to human and livestock safety, and pesticide residues . Therefore, the development of efficient biological and fungal strains to replace chemical agents in controlling walnut rot disease can not only effectively manage disease occurrence and progression but also mitigate the problems associated with chemical control. Paecilomyces lilacinus widely distributed throughout the world, it has the advantages of high efficacy, wide host, easy to cultivate and so on, especially in the control of plant pathogen nematodes . Related studies have confirmed that P . lilacinum has antagonistic activity against a variety of plant pathogenic fungi, bacteria and even viruses . In the study of the control mechanism of plant fungal diseases, chitinase, β-1,3 glucanase and other related cell wall degrading enzymes have been proved as defense enzymes with disease resistance. The mechanism of action is to degrade the pathogenic fungal cell wall, thus killing the pathogen . Currently, there is a lack of research on the antagonistic and growth-promoting impacts of P . lilacinus on walnut rot disease. This study aims to investigate the inhibitory properties of secondary metabolites produced by P . lilacinus against C . chrysosperma , focusing on disease prevention and growth enhancement. Additionally, the research will explore the stability of indoor antagonistic fermentation filtrate and the potential of using P . lilacinus for controlling various fungal diseases in crops. Materials used in the experiment In May 2023, the test soil was collected the walnut orchard in Wensu County, Aksu Region. The walnut variety in the orchard was "Wen 185", the age of the trees was 30 years, and the spacing between the rows was 5 m×7 m. The walnut trees with uniform growth were selected for sampling, and 0~5 cm of topsoil was removed from the main trunks of the walnut trees at a distance of 1 m. The soil samples were taken from the soil auger at a distance of 5–20 cm, and then the soil samples were put into a sterile bag, and stored in a refrigerator at 4°C for use. The following pathogenic fungi were provided by the Key Laboratory of Integrated Pest Management in Southern Xinjiang Corps: Cytospora chrysosperma 、 Cytospora nivea 、 Valsa mali 、 Valsa ambiens 、 Cytospora chrysosperma 、 Cytospora leucostoma 、 Alternaria alternata 、 Verticillium dahliae 、 Fusarium oxysporum . The test walnut seed variety is "Wen 185", the weight of a single fruit is not less than 12g, and the kernel is full, free of mildew and insect pests. Isolation of soil microorganisms A soil sample weighing 10.0 g was placed into a conical flask along with 90 mL of sterile water and glass beads. The mixture was shaken on a shaker for 30 minutes to create a suspension of the soil sample. This suspension 10ml suspension was taken and serially diluted to 10 −2 , 10 −3 and 10 -4 .Subsequently, 100 μL of each diluted solution was absorbed onto PDA medium for strain isolation. The plate was incubated at 26°C for 3–7 days. The strain was then subcultured to purify it, labeled and stored at 4c°Cfor later use. Screening of the antagonistic fungi Using the plate confrontation culture method,a cross was made at an equal distance (approximately 2.5cm) from the pathogen on the PDA plate inoculated with C . chrysosperma . The control consisted only of the pathogen, with each fungus treated in three replicates. The cultures were maintained at a constant temperature of 26°C for 3days. Once the control mycelium was close to filling the plate, colony morphology was observed, and colony diameter was measured to calculate the inhibition rate of colony growth. The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter ofthe control group]×100%. Identification of the antagonistic fungal Morphological characteristics The preserved strains were incubated for 3 days on PDA medium at 28°C. During this period, colony characteristics such as growth rate, mycelium texture, separation, thin density, presence of exudate, and absence of pigment were observed and recorded. Morphological observation of mycelium and conidia was conducted by inserting a sterilized cover slide obliquely into the PDA medium plate, mycelium morphology under a microscope. Visual fields with typical features were photographed and recorded for identification of the antagonistic genus following the fungi Identification Manual . Molecular biology identification A small number of hyphae was carefully selected from the activated plate using a sterilized inoculation needle and transferred into 100 ml of liquid PDA medium. The sample was then placed in a 28°C, 180 r/min shaker for 3–5 days (Speed-regulating mini centrifuge SMD BioEngineering (Shanghai) Co., Ltd). Subsequently, it was filtered on a superclean bench, rinsed three times with sterile water, drained using sterile filter paper, and finally placed in a 45°C-drying box for 4 hours(Electric heating constant temperature blast drying box DHG-9240AS Ningbo Jiangnan Instrument Factory). The dried hyphae were then transferred into a sterilized mortar and pestle and ground with liquid nitrogen added in small increments. Genomic DNA extraction of the test strain was performed using the Ezup column fungal genomic DNA extraction kit (Shanghai Biological Engineering Co., Ltd.), followed by storage in a 4°C refrigerator after electrophoresis in 1% agarose gel. The extracted strain DNA was used as a template with the fungal universal primers ITS 1 (5’- TCCGTAGGTGAACCTGCG -3’) / ITS 4 (5’- TCCTCCGCTTATTGATATGC -3’) . The amplification reaction was carried out in a 50 μl system consisting of 2 μl DNA template, 2 μl each of upper and lower primers, 25 μl Taq PCR Master Mix, and 19 μl ddH2O. PCR amplification conditions included predenaturation at 95°C for 5 min, denaturation at 95°C for 35s, annealing at 55°C for 35s, extension at 72°C for 2 min by 35 cycles, and extension at 72°C for 10 min. The amplified products were analyzed by 1% agarose gel electrophoresis and viewed using an integrated gel imager. The PCR amplification productes were sent to Shanghai Biological Engineering Co., LTD. A phylogenetic tree based on ITS genes was constructed using MEGA 11 software to determine the taxonomic status of the antagonistic strains. Inhibition of the antagonistic strains against eight pathogenic fungi In this study, the walnut tree rot pathogen C . nivea , the apple tree rot pathogen V . mal i, the fragrant pear tree rot pathogen V . ambiens , the elegans tree rot pathogen C . chrysosperma , the almond tree rot pathogen C . leucostoma , and the walnut tree brown spot pathogen A . alternata , V . dahliae , and F . oxysporum were selected as target fungus. Antagonistic strains were positioned 2.5 cm away from the pathogenic fungus in a symmetrical manner, with PDA culture medium inoculated with pathogen cake alone serving as the control. Each treatment was replicated three times. The plates were then incubated at a constant temperature of 26°C. Following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter of the control group]×100%. Effects of different concentrations of antimicrobial fermentation filtrate on C . chrysosperma hyphae The fermentation filtrate of 3%, 6%, 9%, 12%, 15% concentration is mixed with the ratio of PDA (1:1).The mixture was then poured into a petri dish, with the walnut rot pathogen inoculated in the center of the plate. A PDA plate without fermentation filtrate was used as the blank control. The cultures were maintained at a constant temperature of 26°C, with each treatment being replicated three times. Once the control fungus had filled the Petri dish, the colony diameter was measured using the cross method to calculate the inhibition rate of the fermentation filtrate on mycelium. Following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter of the control group]×100%. Determination of the thermal stability of filtrate Five centrifuge tubes containing 10 ml of fermentation filtrate were placed in water baths at temperatures of 55°C, 65°C, 75°C, 85°C, and 95°C for 30 minutes. A positive control was prepared by mixing fermentation filtrate without temperature treatment with PDA culture medium in a 1:3 ratio. Another control was set up using only PDA culture medium without the addition of fermentation filtrate. The mixture was poured onto plates and allowed to solidify. Pathogenic fungi were placed in the center of the plates. Each treatment was replicated three times and incubated in the dark at 26°C until the pathogenic fungus hyphae in the control group had grown over the plate. Subsequently, the diameter of the pathogenic fungus colonies was measured, following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter ofthe control group]×100%. The effect of biocontrol fermentation liquid on walnut rot spot Branches were collected from healthy and uniform 1–2 year old walnut trees, cut into 10–15 cm segments, washed with tap water, disinfected with a 0.6% sodium hypochlorite solution for 15–20 minutes, rinsed with sterile water 3–4 times until no odor of sodium hypochlorite was detected, and left to naturally dry at room temperature. The branches were then sealed on both ends with melted paraffin using an alcohol lamp to retain moisture, and left to dry. Independent branch spot control test Punch holes in the branches with a sterilized 5 mm diameter hole punch, then inoculate each hole with a 5 mm diameter C . chrysosperma fungus cake (mycelial side facing down). Apply one inoculation point per branch. After cultivate at a constant temperature of 26°C for two days, remove the pathogenic fungi using an inoculation needle. Dip a brush into 3% amount of antagonistic fungi fermentation liquid and apply it to the branches three times (allowing to air dry between each application). After moisturizing and cultivating at 26°C for 15 days, observe and measure the lesion areas. Use C . chrysosperma as a control, repeat the experiment three times, and calculate the control effect. Disease spot area (cm 2 ) = 1 / 4 π long diameter and short diameter. Prevention effect = (control spot area-treated spot area) / control spot area ×100. Effect of strain fermentation filtrate on the growth of walnut seeds Pretreatment of shelled walnut seeds The shelled walnut seeds were gently split with a walnut clip, and the walnut kernel contacted the antagonistic fungi fermentation filtrate. At five concentrations of 50 mg/ml, 150 mg/ml, 250 mg/ml, 350 mg/ml and 450 mg/ml, the culture medium without the fermentation filtrate served as the control (CK), with each treatment consisting of 25 walnut seeds repeated 5 times. Seed soaking and sprouting treatment The prepared walnut seeds were surface disinfected with 75% ethanol for 30s, rinsed in sterile water for three times, and dried naturally. Seed treatment of the test group the shelled walnut was gently split using a walnut clip to avoid the walnut kernel from unable to touch the antagonistic fungi fermentation filtrate. Walnut seeds were individually soaked in five concentrations of fermentation filtrates for 24 h. After soaking, the seeds were rinsed with sterile water and placed in a 28°C incubator to stimulate germination. The germination rate was counted before sowing on the hole plate.After germination, seeds were sown in a hole plate (32 holes, 6 cm 4.5 cm), 2–3 seeds per hole, covered with l cm thick matrix (vermiculite: perlite: peat: soil volume ratio was 1:1:1:1), germination rate and rotten seed rate were counted after germination and true leaves.Control seed treatment liquid medium without antagonistic fungi was used as control for 24 h. Germinatio rate /% = (number of white seeds after germination / number of tested seeds)×100; Germination rate /% = (total number of germinated grains / numbers of tested seeds) ×100; Rotten seed rate /% = [(number of pests + decay number) / number of tested seeds] ×100. Effect of strain fermentation filtrate on the growth of walnut seedlings A potted experiment on growth promotion of walnut seedlings was conducted at the Key Laboratory of Southern Xinjiang Integrated Pest Management Corps of Tarim University. The experimental materials consisted of dried fruits with full kernels, no mold or insects, and a single fruit weight of 12 g or more, which were selected and naturally dried. The control group received sterile water treatment, with each treatment being repeated 5 times, using 25 seeds per treatment and 5 seeds per replication. Prior to soaking, the walnut shells were opened to allow contact between the fermentation filtrate and the walnut kernels. After soaking the seeds for 1 day, they were washed with clean water, placed in a moist germination box, and subjected to germination treatment in a 30°C constant-temperature incubator. Seed germination was monitored daily, with any rotten or moldy seeds promptly removed. Once the seeds germinated, they were planted in flowerpots (20 cm × 20 cm), with 1 seed per hole, and covered with a 1 cm thick substrate (vermiculite: perlite: peat: soil volume ratio of 1:1:1:1) in three replicate groups. Indoor potted seedlings treatment involved sowing walnut seeds treated with germination on flowerpots, followed by watering with antagonistic fungi fermentation filtrate (test group received 150 mg/ml fermentation filtrate, while control group received sterile water) at 50 ml per point every 5 days. After 20 days of seed growth, the indoor potted seedlings were transplanted into outdoor field pots. In July 2023, potted walnut seedlings will be transplanted into a 40 cm diameter pot at Tarim University’s water-saving irrigation field. The seedlings will be watered three times with 500 ml of fermentation filtrate every 10 days. After 90 days of growth post-transplanting, in September 2023, five seedlings will be randomly selected for measuring dry weight, height, root length, root number, and other biological indicators. It is important to ensure the integrity of the plants when pulling out the walnut seedlings and to wash the roots slowly with sterile water to maintain their integrity. Data analysis Multiple comparisons of test data were implemented by Duncan’s new multiple range testusing sPss version 16.0 software. In May 2023, the test soil was collected the walnut orchard in Wensu County, Aksu Region. The walnut variety in the orchard was "Wen 185", the age of the trees was 30 years, and the spacing between the rows was 5 m×7 m. The walnut trees with uniform growth were selected for sampling, and 0~5 cm of topsoil was removed from the main trunks of the walnut trees at a distance of 1 m. The soil samples were taken from the soil auger at a distance of 5–20 cm, and then the soil samples were put into a sterile bag, and stored in a refrigerator at 4°C for use. The following pathogenic fungi were provided by the Key Laboratory of Integrated Pest Management in Southern Xinjiang Corps: Cytospora chrysosperma 、 Cytospora nivea 、 Valsa mali 、 Valsa ambiens 、 Cytospora chrysosperma 、 Cytospora leucostoma 、 Alternaria alternata 、 Verticillium dahliae 、 Fusarium oxysporum . The test walnut seed variety is "Wen 185", the weight of a single fruit is not less than 12g, and the kernel is full, free of mildew and insect pests. A soil sample weighing 10.0 g was placed into a conical flask along with 90 mL of sterile water and glass beads. The mixture was shaken on a shaker for 30 minutes to create a suspension of the soil sample. This suspension 10ml suspension was taken and serially diluted to 10 −2 , 10 −3 and 10 -4 .Subsequently, 100 μL of each diluted solution was absorbed onto PDA medium for strain isolation. The plate was incubated at 26°C for 3–7 days. The strain was then subcultured to purify it, labeled and stored at 4c°Cfor later use. Using the plate confrontation culture method,a cross was made at an equal distance (approximately 2.5cm) from the pathogen on the PDA plate inoculated with C . chrysosperma . The control consisted only of the pathogen, with each fungus treated in three replicates. The cultures were maintained at a constant temperature of 26°C for 3days. Once the control mycelium was close to filling the plate, colony morphology was observed, and colony diameter was measured to calculate the inhibition rate of colony growth. The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter ofthe control group]×100%. Morphological characteristics The preserved strains were incubated for 3 days on PDA medium at 28°C. During this period, colony characteristics such as growth rate, mycelium texture, separation, thin density, presence of exudate, and absence of pigment were observed and recorded. Morphological observation of mycelium and conidia was conducted by inserting a sterilized cover slide obliquely into the PDA medium plate, mycelium morphology under a microscope. Visual fields with typical features were photographed and recorded for identification of the antagonistic genus following the fungi Identification Manual . Molecular biology identification A small number of hyphae was carefully selected from the activated plate using a sterilized inoculation needle and transferred into 100 ml of liquid PDA medium. The sample was then placed in a 28°C, 180 r/min shaker for 3–5 days (Speed-regulating mini centrifuge SMD BioEngineering (Shanghai) Co., Ltd). Subsequently, it was filtered on a superclean bench, rinsed three times with sterile water, drained using sterile filter paper, and finally placed in a 45°C-drying box for 4 hours(Electric heating constant temperature blast drying box DHG-9240AS Ningbo Jiangnan Instrument Factory). The dried hyphae were then transferred into a sterilized mortar and pestle and ground with liquid nitrogen added in small increments. Genomic DNA extraction of the test strain was performed using the Ezup column fungal genomic DNA extraction kit (Shanghai Biological Engineering Co., Ltd.), followed by storage in a 4°C refrigerator after electrophoresis in 1% agarose gel. The extracted strain DNA was used as a template with the fungal universal primers ITS 1 (5’- TCCGTAGGTGAACCTGCG -3’) / ITS 4 (5’- TCCTCCGCTTATTGATATGC -3’) . The amplification reaction was carried out in a 50 μl system consisting of 2 μl DNA template, 2 μl each of upper and lower primers, 25 μl Taq PCR Master Mix, and 19 μl ddH2O. PCR amplification conditions included predenaturation at 95°C for 5 min, denaturation at 95°C for 35s, annealing at 55°C for 35s, extension at 72°C for 2 min by 35 cycles, and extension at 72°C for 10 min. The amplified products were analyzed by 1% agarose gel electrophoresis and viewed using an integrated gel imager. The PCR amplification productes were sent to Shanghai Biological Engineering Co., LTD. A phylogenetic tree based on ITS genes was constructed using MEGA 11 software to determine the taxonomic status of the antagonistic strains. Inhibition of the antagonistic strains against eight pathogenic fungi In this study, the walnut tree rot pathogen C . nivea , the apple tree rot pathogen V . mal i, the fragrant pear tree rot pathogen V . ambiens , the elegans tree rot pathogen C . chrysosperma , the almond tree rot pathogen C . leucostoma , and the walnut tree brown spot pathogen A . alternata , V . dahliae , and F . oxysporum were selected as target fungus. Antagonistic strains were positioned 2.5 cm away from the pathogenic fungus in a symmetrical manner, with PDA culture medium inoculated with pathogen cake alone serving as the control. Each treatment was replicated three times. The plates were then incubated at a constant temperature of 26°C. Following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter of the control group]×100%. Effects of different concentrations of antimicrobial fermentation filtrate on C . chrysosperma hyphae The fermentation filtrate of 3%, 6%, 9%, 12%, 15% concentration is mixed with the ratio of PDA (1:1).The mixture was then poured into a petri dish, with the walnut rot pathogen inoculated in the center of the plate. A PDA plate without fermentation filtrate was used as the blank control. The cultures were maintained at a constant temperature of 26°C, with each treatment being replicated three times. Once the control fungus had filled the Petri dish, the colony diameter was measured using the cross method to calculate the inhibition rate of the fermentation filtrate on mycelium. Following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter of the control group]×100%. Determination of the thermal stability of filtrate Five centrifuge tubes containing 10 ml of fermentation filtrate were placed in water baths at temperatures of 55°C, 65°C, 75°C, 85°C, and 95°C for 30 minutes. A positive control was prepared by mixing fermentation filtrate without temperature treatment with PDA culture medium in a 1:3 ratio. Another control was set up using only PDA culture medium without the addition of fermentation filtrate. The mixture was poured onto plates and allowed to solidify. Pathogenic fungi were placed in the center of the plates. Each treatment was replicated three times and incubated in the dark at 26°C until the pathogenic fungus hyphae in the control group had grown over the plate. Subsequently, the diameter of the pathogenic fungus colonies was measured, following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter ofthe control group]×100%. The effect of biocontrol fermentation liquid on walnut rot spot Branches were collected from healthy and uniform 1–2 year old walnut trees, cut into 10–15 cm segments, washed with tap water, disinfected with a 0.6% sodium hypochlorite solution for 15–20 minutes, rinsed with sterile water 3–4 times until no odor of sodium hypochlorite was detected, and left to naturally dry at room temperature. The branches were then sealed on both ends with melted paraffin using an alcohol lamp to retain moisture, and left to dry. Independent branch spot control test Punch holes in the branches with a sterilized 5 mm diameter hole punch, then inoculate each hole with a 5 mm diameter C . chrysosperma fungus cake (mycelial side facing down). Apply one inoculation point per branch. After cultivate at a constant temperature of 26°C for two days, remove the pathogenic fungi using an inoculation needle. Dip a brush into 3% amount of antagonistic fungi fermentation liquid and apply it to the branches three times (allowing to air dry between each application). After moisturizing and cultivating at 26°C for 15 days, observe and measure the lesion areas. Use C . chrysosperma as a control, repeat the experiment three times, and calculate the control effect. Disease spot area (cm 2 ) = 1 / 4 π long diameter and short diameter. Prevention effect = (control spot area-treated spot area) / control spot area ×100. The preserved strains were incubated for 3 days on PDA medium at 28°C. During this period, colony characteristics such as growth rate, mycelium texture, separation, thin density, presence of exudate, and absence of pigment were observed and recorded. Morphological observation of mycelium and conidia was conducted by inserting a sterilized cover slide obliquely into the PDA medium plate, mycelium morphology under a microscope. Visual fields with typical features were photographed and recorded for identification of the antagonistic genus following the fungi Identification Manual . A small number of hyphae was carefully selected from the activated plate using a sterilized inoculation needle and transferred into 100 ml of liquid PDA medium. The sample was then placed in a 28°C, 180 r/min shaker for 3–5 days (Speed-regulating mini centrifuge SMD BioEngineering (Shanghai) Co., Ltd). Subsequently, it was filtered on a superclean bench, rinsed three times with sterile water, drained using sterile filter paper, and finally placed in a 45°C-drying box for 4 hours(Electric heating constant temperature blast drying box DHG-9240AS Ningbo Jiangnan Instrument Factory). The dried hyphae were then transferred into a sterilized mortar and pestle and ground with liquid nitrogen added in small increments. Genomic DNA extraction of the test strain was performed using the Ezup column fungal genomic DNA extraction kit (Shanghai Biological Engineering Co., Ltd.), followed by storage in a 4°C refrigerator after electrophoresis in 1% agarose gel. The extracted strain DNA was used as a template with the fungal universal primers ITS 1 (5’- TCCGTAGGTGAACCTGCG -3’) / ITS 4 (5’- TCCTCCGCTTATTGATATGC -3’) . The amplification reaction was carried out in a 50 μl system consisting of 2 μl DNA template, 2 μl each of upper and lower primers, 25 μl Taq PCR Master Mix, and 19 μl ddH2O. PCR amplification conditions included predenaturation at 95°C for 5 min, denaturation at 95°C for 35s, annealing at 55°C for 35s, extension at 72°C for 2 min by 35 cycles, and extension at 72°C for 10 min. The amplified products were analyzed by 1% agarose gel electrophoresis and viewed using an integrated gel imager. The PCR amplification productes were sent to Shanghai Biological Engineering Co., LTD. A phylogenetic tree based on ITS genes was constructed using MEGA 11 software to determine the taxonomic status of the antagonistic strains. In this study, the walnut tree rot pathogen C . nivea , the apple tree rot pathogen V . mal i, the fragrant pear tree rot pathogen V . ambiens , the elegans tree rot pathogen C . chrysosperma , the almond tree rot pathogen C . leucostoma , and the walnut tree brown spot pathogen A . alternata , V . dahliae , and F . oxysporum were selected as target fungus. Antagonistic strains were positioned 2.5 cm away from the pathogenic fungus in a symmetrical manner, with PDA culture medium inoculated with pathogen cake alone serving as the control. Each treatment was replicated three times. The plates were then incubated at a constant temperature of 26°C. Following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter of the control group]×100%. C . chrysosperma hyphae The fermentation filtrate of 3%, 6%, 9%, 12%, 15% concentration is mixed with the ratio of PDA (1:1).The mixture was then poured into a petri dish, with the walnut rot pathogen inoculated in the center of the plate. A PDA plate without fermentation filtrate was used as the blank control. The cultures were maintained at a constant temperature of 26°C, with each treatment being replicated three times. Once the control fungus had filled the Petri dish, the colony diameter was measured using the cross method to calculate the inhibition rate of the fermentation filtrate on mycelium. Following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter of the control group]×100%. Five centrifuge tubes containing 10 ml of fermentation filtrate were placed in water baths at temperatures of 55°C, 65°C, 75°C, 85°C, and 95°C for 30 minutes. A positive control was prepared by mixing fermentation filtrate without temperature treatment with PDA culture medium in a 1:3 ratio. Another control was set up using only PDA culture medium without the addition of fermentation filtrate. The mixture was poured onto plates and allowed to solidify. Pathogenic fungi were placed in the center of the plates. Each treatment was replicated three times and incubated in the dark at 26°C until the pathogenic fungus hyphae in the control group had grown over the plate. Subsequently, the diameter of the pathogenic fungus colonies was measured, following growth of colonies in the control group, The inhibition rate was calculated using the formula: Inhibition rate = [(colony diameter ofthe control group—colony diameter ofthe test group)/ colony diameter ofthe control group]×100%. Branches were collected from healthy and uniform 1–2 year old walnut trees, cut into 10–15 cm segments, washed with tap water, disinfected with a 0.6% sodium hypochlorite solution for 15–20 minutes, rinsed with sterile water 3–4 times until no odor of sodium hypochlorite was detected, and left to naturally dry at room temperature. The branches were then sealed on both ends with melted paraffin using an alcohol lamp to retain moisture, and left to dry. Punch holes in the branches with a sterilized 5 mm diameter hole punch, then inoculate each hole with a 5 mm diameter C . chrysosperma fungus cake (mycelial side facing down). Apply one inoculation point per branch. After cultivate at a constant temperature of 26°C for two days, remove the pathogenic fungi using an inoculation needle. Dip a brush into 3% amount of antagonistic fungi fermentation liquid and apply it to the branches three times (allowing to air dry between each application). After moisturizing and cultivating at 26°C for 15 days, observe and measure the lesion areas. Use C . chrysosperma as a control, repeat the experiment three times, and calculate the control effect. Disease spot area (cm 2 ) = 1 / 4 π long diameter and short diameter. Prevention effect = (control spot area-treated spot area) / control spot area ×100. Pretreatment of shelled walnut seeds The shelled walnut seeds were gently split with a walnut clip, and the walnut kernel contacted the antagonistic fungi fermentation filtrate. At five concentrations of 50 mg/ml, 150 mg/ml, 250 mg/ml, 350 mg/ml and 450 mg/ml, the culture medium without the fermentation filtrate served as the control (CK), with each treatment consisting of 25 walnut seeds repeated 5 times. Seed soaking and sprouting treatment The prepared walnut seeds were surface disinfected with 75% ethanol for 30s, rinsed in sterile water for three times, and dried naturally. Seed treatment of the test group the shelled walnut was gently split using a walnut clip to avoid the walnut kernel from unable to touch the antagonistic fungi fermentation filtrate. Walnut seeds were individually soaked in five concentrations of fermentation filtrates for 24 h. After soaking, the seeds were rinsed with sterile water and placed in a 28°C incubator to stimulate germination. The germination rate was counted before sowing on the hole plate.After germination, seeds were sown in a hole plate (32 holes, 6 cm 4.5 cm), 2–3 seeds per hole, covered with l cm thick matrix (vermiculite: perlite: peat: soil volume ratio was 1:1:1:1), germination rate and rotten seed rate were counted after germination and true leaves.Control seed treatment liquid medium without antagonistic fungi was used as control for 24 h. Germinatio rate /% = (number of white seeds after germination / number of tested seeds)×100; Germination rate /% = (total number of germinated grains / numbers of tested seeds) ×100; Rotten seed rate /% = [(number of pests + decay number) / number of tested seeds] ×100. Effect of strain fermentation filtrate on the growth of walnut seedlings A potted experiment on growth promotion of walnut seedlings was conducted at the Key Laboratory of Southern Xinjiang Integrated Pest Management Corps of Tarim University. The experimental materials consisted of dried fruits with full kernels, no mold or insects, and a single fruit weight of 12 g or more, which were selected and naturally dried. The control group received sterile water treatment, with each treatment being repeated 5 times, using 25 seeds per treatment and 5 seeds per replication. Prior to soaking, the walnut shells were opened to allow contact between the fermentation filtrate and the walnut kernels. After soaking the seeds for 1 day, they were washed with clean water, placed in a moist germination box, and subjected to germination treatment in a 30°C constant-temperature incubator. Seed germination was monitored daily, with any rotten or moldy seeds promptly removed. Once the seeds germinated, they were planted in flowerpots (20 cm × 20 cm), with 1 seed per hole, and covered with a 1 cm thick substrate (vermiculite: perlite: peat: soil volume ratio of 1:1:1:1) in three replicate groups. Indoor potted seedlings treatment involved sowing walnut seeds treated with germination on flowerpots, followed by watering with antagonistic fungi fermentation filtrate (test group received 150 mg/ml fermentation filtrate, while control group received sterile water) at 50 ml per point every 5 days. After 20 days of seed growth, the indoor potted seedlings were transplanted into outdoor field pots. In July 2023, potted walnut seedlings will be transplanted into a 40 cm diameter pot at Tarim University’s water-saving irrigation field. The seedlings will be watered three times with 500 ml of fermentation filtrate every 10 days. After 90 days of growth post-transplanting, in September 2023, five seedlings will be randomly selected for measuring dry weight, height, root length, root number, and other biological indicators. It is important to ensure the integrity of the plants when pulling out the walnut seedlings and to wash the roots slowly with sterile water to maintain their integrity. Data analysis Multiple comparisons of test data were implemented by Duncan’s new multiple range testusing sPss version 16.0 software. The shelled walnut seeds were gently split with a walnut clip, and the walnut kernel contacted the antagonistic fungi fermentation filtrate. At five concentrations of 50 mg/ml, 150 mg/ml, 250 mg/ml, 350 mg/ml and 450 mg/ml, the culture medium without the fermentation filtrate served as the control (CK), with each treatment consisting of 25 walnut seeds repeated 5 times. The prepared walnut seeds were surface disinfected with 75% ethanol for 30s, rinsed in sterile water for three times, and dried naturally. Seed treatment of the test group the shelled walnut was gently split using a walnut clip to avoid the walnut kernel from unable to touch the antagonistic fungi fermentation filtrate. Walnut seeds were individually soaked in five concentrations of fermentation filtrates for 24 h. After soaking, the seeds were rinsed with sterile water and placed in a 28°C incubator to stimulate germination. The germination rate was counted before sowing on the hole plate.After germination, seeds were sown in a hole plate (32 holes, 6 cm 4.5 cm), 2–3 seeds per hole, covered with l cm thick matrix (vermiculite: perlite: peat: soil volume ratio was 1:1:1:1), germination rate and rotten seed rate were counted after germination and true leaves.Control seed treatment liquid medium without antagonistic fungi was used as control for 24 h. Germinatio rate /% = (number of white seeds after germination / number of tested seeds)×100; Germination rate /% = (total number of germinated grains / numbers of tested seeds) ×100; Rotten seed rate /% = [(number of pests + decay number) / number of tested seeds] ×100. A potted experiment on growth promotion of walnut seedlings was conducted at the Key Laboratory of Southern Xinjiang Integrated Pest Management Corps of Tarim University. The experimental materials consisted of dried fruits with full kernels, no mold or insects, and a single fruit weight of 12 g or more, which were selected and naturally dried. The control group received sterile water treatment, with each treatment being repeated 5 times, using 25 seeds per treatment and 5 seeds per replication. Prior to soaking, the walnut shells were opened to allow contact between the fermentation filtrate and the walnut kernels. After soaking the seeds for 1 day, they were washed with clean water, placed in a moist germination box, and subjected to germination treatment in a 30°C constant-temperature incubator. Seed germination was monitored daily, with any rotten or moldy seeds promptly removed. Once the seeds germinated, they were planted in flowerpots (20 cm × 20 cm), with 1 seed per hole, and covered with a 1 cm thick substrate (vermiculite: perlite: peat: soil volume ratio of 1:1:1:1) in three replicate groups. Indoor potted seedlings treatment involved sowing walnut seeds treated with germination on flowerpots, followed by watering with antagonistic fungi fermentation filtrate (test group received 150 mg/ml fermentation filtrate, while control group received sterile water) at 50 ml per point every 5 days. After 20 days of seed growth, the indoor potted seedlings were transplanted into outdoor field pots. In July 2023, potted walnut seedlings will be transplanted into a 40 cm diameter pot at Tarim University’s water-saving irrigation field. The seedlings will be watered three times with 500 ml of fermentation filtrate every 10 days. After 90 days of growth post-transplanting, in September 2023, five seedlings will be randomly selected for measuring dry weight, height, root length, root number, and other biological indicators. It is important to ensure the integrity of the plants when pulling out the walnut seedlings and to wash the roots slowly with sterile water to maintain their integrity. Multiple comparisons of test data were implemented by Duncan’s new multiple range testusing sPss version 16.0 software. Isolation and screening of biocontrol strains A total of 293 fungi were isolated using the dilution coating plate method, with 34 strains exhibiting antagonistic effects on C . chrysosperma . Among these, 7 strains demonstrated an antimicrobial rate exceeding 70% . The strains with over 70% inhibition were subjected to further screening . Among them, strain 5–38 displayed the most potent inhibitory effect on C . chrysosperma ( Ab), achieving an inhibition rate of 78.71%. Observation of the hyphae inhibition revealed localized expansion and rupture of the pathogenic fungi by strain 5–38, along with a deepening of mycelium color and inhibited hyphal growth . Consequently, strain 5–38 was chosen for subsequent studies in this research. Identification of fungus Morphological identification On PDA medium, strains 5–38 initially displayed white colony color, with mycelium spread evenly in a radial direction, round colony, loose cotton texture and wheel pattern. These strains exhibited slow growth at a rate of 0.36cm/day. As strain 5–38 produced spores, the front of the colony transitioned from white to pink. The colony darkened with an increase in spores, while the back remained light yellow . The conidia were nearly round and transparent, with thick conidial stems in a bottle shape, rounded ends, or short branches. The conidia formed monospore chains, while the mycelium appeared transparent and slender . Based on morphological characteristics and the Manual of Fungi Identification, it was initially classified as Paecilomyces . Molecular biological identification Strains 5–38 were sequenced using ITS and the sequences were submitted to GenBank with the accession number PP065674. Analysis of the amplified sequences in the NCBI database revealed that that strains 5–38 exhibit up to 99% similarity to Paecilomyces lilacinus . A phylogenetic tree of the ITS genes was constructed using the MEGA11 software. illustrates that strains 5–38 form a cluster within the same branch as P . lilacinus , indicating a recent affinity to P . lilacinus . Through a combination of morphological observations and molecular biology analysis, strains 5–38 were identified as P . lilacinus . Determination of antibacterial spectrum The inhibitory effect of antagonistic strain 5–38 on 8 tested pathogenic fungi was determined by cross plate confrontation method. As illustrated in , strain 5–38 effectively inhibited the growth of all 8 pathogens towards the periphery . The calculation of inhibition rates revealed that strain 5–38 inhibited 70% of the 8 pathogens , exhibiting the highest efficacy against C . leucostoma , V . mali , and V . dahliae at 85.00%, 81.00%, and 81.00%, respectively. Additionally, V . ambiens , C . chrysosperma , and A . alternata were inhibited by more than 75%, specifically at 77%, 76%, and 79%, respectively. C . nivea and F . oxysporum showed inhibition rates of 73% and 72%, respectively. Effects of fermentation filtrate of different concentrations of biocontrol fungi on mycelia growth of C . chrysosperma To investigate the inhibitory effect of C . chrysosperma mycelial growth, different proportions (3%, 6%, 9%, 12%, 15%) of fermentation filtrate were mixed with PDA medium. C . chrysosperma cakes were inoculated with strain 5–38 and incubated at a constant temperature of 26°C for 3 days. The inhibition of C . chrysosperma mycelium growth was evaluated using the mycelium growth rate method . Results indicated that strain 5–38 exhibited a significant inhibitory effect on C . chrysosperma , with the inhibition effect increasing as the fermentation filtrate concentration rose. Specifically, at a 3% concentration, strain 5–38 inhibited C . chrysosperma growth by 65.83%, while at a 15% concentration, it displayed the highest inhibition rate of 92.28% . Determination of thermal stability of biocontrol fungi The results presented in demonstrate that the fermentation filtrate of strain 5–38, when exposed to a temperature of 75°C, exhibited the highest inhibition rate of C . chrysosperma growth at 84.63%. Furthermore, it was observed that as the treatment temperature exceeded 75°C, the inhibition rate started to decrease; however, it remained higher than that of the positive control . These findings suggest that the fermentation filtrate of the 5–38 antagonistic fungi displayed increased antibacterial activity following temperature gradient treatment, highlighting the importance of maintaining an appropriate temperature to enhance the metabolites’ ability to inhibit pathogenic fungi. Control of diseased spots in vitro branches of fermentation broth According to , the biocontrol fungal fermentation was compared with the control group. The lesion area was 0.62 cm 2 , and biocontrol showed 88.44% effectiveness against C . chrysosperma . C . chrysosperma . Effect of different concentration of fermentation filtrate on the growth of walnut seeds The results presented in indicate that the germination rate of walnut seeds significantly increases when treated with antagonistic fungal fermentation filtrate, particularly at concentrations of around 150 mg/ml and 250 mg/ml. The seed germination effect was observed to be highest at 250 mg/ml followed by 150 mg/ml, 50 mg/ml, 350 mg/ml, and 450 mg/ml, which was significantly higher than the control (P <0.05), The highest germination rates were recorded at 83.70% and 76.68% for concentrations of 250 mg/ml and 150 mg/ml, respectively . As illustrated in , the germination rate of walnut seeds with the shell was influenced by the concentration of antagonistic fungi. The filtrate of P . lilacinus at concentrations between 50–150 mg/ml resulted in a gradual increase in the germination rate of walnut seeds, peaking at 150 mg/ml of fermentation. which gradually weakened when the concentration of fermentation filtrate exceeded 250 mg/ml. Therefore, It is evident that the concentration of the filtrate between 150 and 250 mg/ml significantly promoted walnut seed germination. The study demonstrated that as the concentration of fermentation filtrate increased, the rate of poor seed planting for walnut seeds initially decreased before slightly increasing. Specifically, P . lilacinus 5–38 exhibited the lowest poor rate at 150 mg/ml, with a rate of 14.68%. Beyond a concentration of 150 mg/ml, the poor planting rate showed an upward trend, albeit still significantly lower than that of the control group (P < 0.05) after each concentration. Different concentrations of fermentation filtrate on the growth of walnut seedlings The antagonistic fungi fermentation filtrate exhibited optimal germination rates at concentrations of 150 mg/ml and 250 mg/ml. However, the incidence of non-viable seeds was markedly elevated at 250 mg/ml compared to 150 mg/ml. Consequently, the 150 mg/ml concentration was selected for subsequent promotion assays on walnut seedlings. Analysis of the data revealed that walnut seedlings treated with P . lilacinus 5–38 demonstrated a mean growth index of 12.63 cm, a primary root length of 26.67 cm, 16.37 lateral roots, a foliar area of 39.89 cm 2 , and a dry mass of 4.56 g . In contrast, control specimens exhibited a height of 9.70 cm, primary root length of 19.92 cm, 9 lateral roots, foliar area of 38.34 cm 2 , and dry mass of 2.30 g. The P . lilacinus 5-38-treated seedlings displayed significant enhancements in all measured parameters compared to the control group, with increases of 30.12%, 33.89%, 81.89%, 6.83%, and 98.26% in height, primary root length, lateral root quantity, foliar area, and dry mass, respectively. A total of 293 fungi were isolated using the dilution coating plate method, with 34 strains exhibiting antagonistic effects on C . chrysosperma . Among these, 7 strains demonstrated an antimicrobial rate exceeding 70% . The strains with over 70% inhibition were subjected to further screening . Among them, strain 5–38 displayed the most potent inhibitory effect on C . chrysosperma ( Ab), achieving an inhibition rate of 78.71%. Observation of the hyphae inhibition revealed localized expansion and rupture of the pathogenic fungi by strain 5–38, along with a deepening of mycelium color and inhibited hyphal growth . Consequently, strain 5–38 was chosen for subsequent studies in this research. Morphological identification On PDA medium, strains 5–38 initially displayed white colony color, with mycelium spread evenly in a radial direction, round colony, loose cotton texture and wheel pattern. These strains exhibited slow growth at a rate of 0.36cm/day. As strain 5–38 produced spores, the front of the colony transitioned from white to pink. The colony darkened with an increase in spores, while the back remained light yellow . The conidia were nearly round and transparent, with thick conidial stems in a bottle shape, rounded ends, or short branches. The conidia formed monospore chains, while the mycelium appeared transparent and slender . Based on morphological characteristics and the Manual of Fungi Identification, it was initially classified as Paecilomyces . Molecular biological identification Strains 5–38 were sequenced using ITS and the sequences were submitted to GenBank with the accession number PP065674. Analysis of the amplified sequences in the NCBI database revealed that that strains 5–38 exhibit up to 99% similarity to Paecilomyces lilacinus . A phylogenetic tree of the ITS genes was constructed using the MEGA11 software. illustrates that strains 5–38 form a cluster within the same branch as P . lilacinus , indicating a recent affinity to P . lilacinus . Through a combination of morphological observations and molecular biology analysis, strains 5–38 were identified as P . lilacinus . Determination of antibacterial spectrum The inhibitory effect of antagonistic strain 5–38 on 8 tested pathogenic fungi was determined by cross plate confrontation method. As illustrated in , strain 5–38 effectively inhibited the growth of all 8 pathogens towards the periphery . The calculation of inhibition rates revealed that strain 5–38 inhibited 70% of the 8 pathogens , exhibiting the highest efficacy against C . leucostoma , V . mali , and V . dahliae at 85.00%, 81.00%, and 81.00%, respectively. Additionally, V . ambiens , C . chrysosperma , and A . alternata were inhibited by more than 75%, specifically at 77%, 76%, and 79%, respectively. C . nivea and F . oxysporum showed inhibition rates of 73% and 72%, respectively. On PDA medium, strains 5–38 initially displayed white colony color, with mycelium spread evenly in a radial direction, round colony, loose cotton texture and wheel pattern. These strains exhibited slow growth at a rate of 0.36cm/day. As strain 5–38 produced spores, the front of the colony transitioned from white to pink. The colony darkened with an increase in spores, while the back remained light yellow . The conidia were nearly round and transparent, with thick conidial stems in a bottle shape, rounded ends, or short branches. The conidia formed monospore chains, while the mycelium appeared transparent and slender . Based on morphological characteristics and the Manual of Fungi Identification, it was initially classified as Paecilomyces . Strains 5–38 were sequenced using ITS and the sequences were submitted to GenBank with the accession number PP065674. Analysis of the amplified sequences in the NCBI database revealed that that strains 5–38 exhibit up to 99% similarity to Paecilomyces lilacinus . A phylogenetic tree of the ITS genes was constructed using the MEGA11 software. illustrates that strains 5–38 form a cluster within the same branch as P . lilacinus , indicating a recent affinity to P . lilacinus . Through a combination of morphological observations and molecular biology analysis, strains 5–38 were identified as P . lilacinus . The inhibitory effect of antagonistic strain 5–38 on 8 tested pathogenic fungi was determined by cross plate confrontation method. As illustrated in , strain 5–38 effectively inhibited the growth of all 8 pathogens towards the periphery . The calculation of inhibition rates revealed that strain 5–38 inhibited 70% of the 8 pathogens , exhibiting the highest efficacy against C . leucostoma , V . mali , and V . dahliae at 85.00%, 81.00%, and 81.00%, respectively. Additionally, V . ambiens , C . chrysosperma , and A . alternata were inhibited by more than 75%, specifically at 77%, 76%, and 79%, respectively. C . nivea and F . oxysporum showed inhibition rates of 73% and 72%, respectively. C . chrysosperma To investigate the inhibitory effect of C . chrysosperma mycelial growth, different proportions (3%, 6%, 9%, 12%, 15%) of fermentation filtrate were mixed with PDA medium. C . chrysosperma cakes were inoculated with strain 5–38 and incubated at a constant temperature of 26°C for 3 days. The inhibition of C . chrysosperma mycelium growth was evaluated using the mycelium growth rate method . Results indicated that strain 5–38 exhibited a significant inhibitory effect on C . chrysosperma , with the inhibition effect increasing as the fermentation filtrate concentration rose. Specifically, at a 3% concentration, strain 5–38 inhibited C . chrysosperma growth by 65.83%, while at a 15% concentration, it displayed the highest inhibition rate of 92.28% . Determination of thermal stability of biocontrol fungi The results presented in demonstrate that the fermentation filtrate of strain 5–38, when exposed to a temperature of 75°C, exhibited the highest inhibition rate of C . chrysosperma growth at 84.63%. Furthermore, it was observed that as the treatment temperature exceeded 75°C, the inhibition rate started to decrease; however, it remained higher than that of the positive control . These findings suggest that the fermentation filtrate of the 5–38 antagonistic fungi displayed increased antibacterial activity following temperature gradient treatment, highlighting the importance of maintaining an appropriate temperature to enhance the metabolites’ ability to inhibit pathogenic fungi. Control of diseased spots in vitro branches of fermentation broth According to , the biocontrol fungal fermentation was compared with the control group. The lesion area was 0.62 cm 2 , and biocontrol showed 88.44% effectiveness against C . chrysosperma . C . chrysosperma . Effect of different concentration of fermentation filtrate on the growth of walnut seeds The results presented in indicate that the germination rate of walnut seeds significantly increases when treated with antagonistic fungal fermentation filtrate, particularly at concentrations of around 150 mg/ml and 250 mg/ml. The seed germination effect was observed to be highest at 250 mg/ml followed by 150 mg/ml, 50 mg/ml, 350 mg/ml, and 450 mg/ml, which was significantly higher than the control (P <0.05), The highest germination rates were recorded at 83.70% and 76.68% for concentrations of 250 mg/ml and 150 mg/ml, respectively . As illustrated in , the germination rate of walnut seeds with the shell was influenced by the concentration of antagonistic fungi. The filtrate of P . lilacinus at concentrations between 50–150 mg/ml resulted in a gradual increase in the germination rate of walnut seeds, peaking at 150 mg/ml of fermentation. which gradually weakened when the concentration of fermentation filtrate exceeded 250 mg/ml. Therefore, It is evident that the concentration of the filtrate between 150 and 250 mg/ml significantly promoted walnut seed germination. The study demonstrated that as the concentration of fermentation filtrate increased, the rate of poor seed planting for walnut seeds initially decreased before slightly increasing. Specifically, P . lilacinus 5–38 exhibited the lowest poor rate at 150 mg/ml, with a rate of 14.68%. Beyond a concentration of 150 mg/ml, the poor planting rate showed an upward trend, albeit still significantly lower than that of the control group (P < 0.05) after each concentration. Different concentrations of fermentation filtrate on the growth of walnut seedlings The antagonistic fungi fermentation filtrate exhibited optimal germination rates at concentrations of 150 mg/ml and 250 mg/ml. However, the incidence of non-viable seeds was markedly elevated at 250 mg/ml compared to 150 mg/ml. Consequently, the 150 mg/ml concentration was selected for subsequent promotion assays on walnut seedlings. Analysis of the data revealed that walnut seedlings treated with P . lilacinus 5–38 demonstrated a mean growth index of 12.63 cm, a primary root length of 26.67 cm, 16.37 lateral roots, a foliar area of 39.89 cm 2 , and a dry mass of 4.56 g . In contrast, control specimens exhibited a height of 9.70 cm, primary root length of 19.92 cm, 9 lateral roots, foliar area of 38.34 cm 2 , and dry mass of 2.30 g. The P . lilacinus 5-38-treated seedlings displayed significant enhancements in all measured parameters compared to the control group, with increases of 30.12%, 33.89%, 81.89%, 6.83%, and 98.26% in height, primary root length, lateral root quantity, foliar area, and dry mass, respectively. The results presented in demonstrate that the fermentation filtrate of strain 5–38, when exposed to a temperature of 75°C, exhibited the highest inhibition rate of C . chrysosperma growth at 84.63%. Furthermore, it was observed that as the treatment temperature exceeded 75°C, the inhibition rate started to decrease; however, it remained higher than that of the positive control . These findings suggest that the fermentation filtrate of the 5–38 antagonistic fungi displayed increased antibacterial activity following temperature gradient treatment, highlighting the importance of maintaining an appropriate temperature to enhance the metabolites’ ability to inhibit pathogenic fungi. According to , the biocontrol fungal fermentation was compared with the control group. The lesion area was 0.62 cm 2 , and biocontrol showed 88.44% effectiveness against C . chrysosperma . C . chrysosperma . The results presented in indicate that the germination rate of walnut seeds significantly increases when treated with antagonistic fungal fermentation filtrate, particularly at concentrations of around 150 mg/ml and 250 mg/ml. The seed germination effect was observed to be highest at 250 mg/ml followed by 150 mg/ml, 50 mg/ml, 350 mg/ml, and 450 mg/ml, which was significantly higher than the control (P <0.05), The highest germination rates were recorded at 83.70% and 76.68% for concentrations of 250 mg/ml and 150 mg/ml, respectively . As illustrated in , the germination rate of walnut seeds with the shell was influenced by the concentration of antagonistic fungi. The filtrate of P . lilacinus at concentrations between 50–150 mg/ml resulted in a gradual increase in the germination rate of walnut seeds, peaking at 150 mg/ml of fermentation. which gradually weakened when the concentration of fermentation filtrate exceeded 250 mg/ml. Therefore, It is evident that the concentration of the filtrate between 150 and 250 mg/ml significantly promoted walnut seed germination. The study demonstrated that as the concentration of fermentation filtrate increased, the rate of poor seed planting for walnut seeds initially decreased before slightly increasing. Specifically, P . lilacinus 5–38 exhibited the lowest poor rate at 150 mg/ml, with a rate of 14.68%. Beyond a concentration of 150 mg/ml, the poor planting rate showed an upward trend, albeit still significantly lower than that of the control group (P < 0.05) after each concentration. The antagonistic fungi fermentation filtrate exhibited optimal germination rates at concentrations of 150 mg/ml and 250 mg/ml. However, the incidence of non-viable seeds was markedly elevated at 250 mg/ml compared to 150 mg/ml. Consequently, the 150 mg/ml concentration was selected for subsequent promotion assays on walnut seedlings. Analysis of the data revealed that walnut seedlings treated with P . lilacinus 5–38 demonstrated a mean growth index of 12.63 cm, a primary root length of 26.67 cm, 16.37 lateral roots, a foliar area of 39.89 cm 2 , and a dry mass of 4.56 g . In contrast, control specimens exhibited a height of 9.70 cm, primary root length of 19.92 cm, 9 lateral roots, foliar area of 38.34 cm 2 , and dry mass of 2.30 g. The P . lilacinus 5-38-treated seedlings displayed significant enhancements in all measured parameters compared to the control group, with increases of 30.12%, 33.89%, 81.89%, 6.83%, and 98.26% in height, primary root length, lateral root quantity, foliar area, and dry mass, respectively. The study elucidated a pronounced antagonistic effect of the fungus on walnut rot pathogens and various pathogenic fungi, culminating in localized expansion, rupture, and inhibition of hyphal and spore development. Dai et al. demonstrated that antagonistic fungi substantially ameliorated rot disease. The isolated and screened Fungi 153 not only impeded apple rot hyphal growth but also suppressed spore germination. Moreover, the fungal fermentation broth exhibited inhibitory effects on the propagation of branch disease lesions. Shi et al. observed that the P . lilacinus NH-PL-03 strain induced local expansion of F . oxysporum hyphae, increased cytoplasmic density, and cell wall degradation. While these findings align with the current study, the confrontation culture results suggested that P . lilacinus did not exhibit a significant growth advantage or clear reparasitism effect on pathogen hyphae. Upon examining the inhibitory effect on C . chrysosperma , We ascertained that the efficacy of strain 5–38 filtrate intensified with increasing concentration. Thermal stability tests revealed robust inhibition at temperatures below 75°C, with diminished activity observed above this threshold. This observation suggests that metabolites produced by P . lilacinus 5–38 may experience reduced antibacterial activity or inactivation at elevated temperatures, although the strains still exhibited laudable thermal stability. These findings suggest that the fermentation filtrate of the 5–38 antagonistic fungi displayed increased antibacterial activity following temperature gradient treatment, highlighting the importance of maintaining an appropriate temperature to enhance the metabolites’ ability to inhibit pathogenic fungi.Wang et al. elucidated that the antimicrobial effect of P . lilacinus strain 36–1 primarily stemmed from anti-biomass compounds produced during fermentation, with prolonged high-temperature treatments attenuating their potency. Li et al. corroborated that inhibitory substances obtained from P . lilacinus fermentation exhibited poor tolerance to high temperatures. This study further corroborated that anti-biomass compounds are largely secreted into the fermentation filtrate during late-stage fermentation, and fungal-inhibitory substances can be isolated via centrifugation, albeit with limited high-temperature tolerance. The fermentation filtrate also demonstrated a promotive effect on walnut seeds and seedlings, with optimal germination rates and lowest germination time observed at a concentration of 150 mg/mL. Noteworthy enhancements were noted in seedling height, primary root length, lateral root number, leaf area, and dry weight. Abdeldaym et al. found that P. lilacinus secondary metabolites could regulate plant growth through the production of growth hormones. Liu et al. reported that the fermentation broth, resembling IAA, promoted the growth of wheat coleoptiles and cucumber cotyledons. Xia et al. observed growth promotion at low concentrations and inhibition of cabbage seed germination at high concentrations. These experimental outcomes align with our findings, suggesting the potential for further application of this antagonistic fungus. |
Experiences & challenges in making Model Rural Health Research Unit (MRHRU) pandemic ready – Establishing COVID-19 molecular diagnostic facility at MRHRU, Dahanu, Maharashtra | 086f8319-973e-49ec-a70c-94bc1562cefa | 10466487 | Pathology[mh] | The study was funded by the intramural grant from the Department of Health Research and ICMR-NIRRCH, Mumbai. None. |
Integration of pharmacochemistry, pharmacodynamics and metabolomics to reveal active ingredients and mechanism of Nan Bao detox capsule alleviating methamphetamine addiction | 3292dde9-2303-4ea5-9f32-66bc08cac7ed | 11551880 | Biochemistry[mh] | INTRODUCTION Methamphetamine (MA) serves as a potent synthetic stimulant of both the peripheral and central nervous systems, facilitating the release of dopamine, serotonin and norepinephrine from intracellular stores into the synaptic cleft, thereby inducing feelings of excitement and euphoria. Chronic exposure to MA elevates the risk of neurological diseases such as Parkinson's disease, Alzheimer's disease and major depressive disorder MA represents a highly addictive psychoactive substance with considerable potential for misuse. As reported in the 2023 China Drug Situation Report, METH is the most prevalent illicit drug in China, accounting for 50.8% of drug abuse incidents among 896 000 users. The 2024 World Drug Report indicates amphetamines rank as the third most commonly abused substance globally. The widespread misuse of METH poses a substantial challenge to the international healthcare sector. Despite treatment with antipsychotics such as risperidone, opioid substitution therapies like methadone and antibiotic interventions with ceftriaxone, a significant proportion of METH users experience relapse post‐treatment. To date, the United States Food and Drug Administration has not approved any definitive therapeutic regimen for the management of METH withdrawal syndrome. Consequently, innovative strategies to combat METH addiction are in high demand. Traditional Chinese Medicine (TCM) has been effectively utilized in China for over a century to cure opioid‐induced withdrawal syndrome due to its high safety and non‐addictive. The monograph ‘Jiu Mi Liang Fang’ in TCM focuses on drug addiction rehabilitation, compiling treatment methods for opium poisoning, including avoidance of acid pills, opium prescriptions and smoking cessation prescriptions. Chinese herbal extracts such as levo‐tetrahydropalmatine ( l ‐THP) derived from Corydalis, pseudoginsenoside‐F11 and ginsenoside Re from ginseng, as well as rhynchophylline from Uncaria tomentosa , have been documented for their protective effects against MA dependence. , , , Clinically and experimentally, polyherbal formulations like Guiyuan Tablets, Fukang Tablets, Jitai Tablets, Jinniu Capsules and Shuhelian Xieyu capsules have been developed as new drugs as therapeutic options for MA dependence. However, the pharmacodynamic substance basis and mechanisms of action for these herbal remedies in treating MA addiction remain uncharacterized. Leveraging its robust separation capabilities, rapid analysis speeds and exceptional sensitivity, ultra‐performance liquid chromatography (UPLC) in tandem with high‐resolution mass spectrometry (MS) serves as a powerful tool for the prediction and elucidation of unknown compound structures. For instance, Liu et al utilized UHPLC‐Q‐Orbitrap HRMS to annotate 138 constituents within walnut leaves, pinpointing 38 as potentially bioactive compounds. Similarly, Guan et al employed UHPLC‐Q‐Orbitrap HRMS to characterize 114 chemical components in Polygonum capitatum , identifying 68 organically absorbed exogenous substances—including 16 prototype compounds and 52 metabolites—within the plasma of hyperuricemic rats. This technique is especially adept at profiling bioactive constituents and compounds in biological matrices like blood and is particularly suitable for pharmaceutical and biomedical research. Metabolomics occupies a leading position in biomedical innovation, offering the potential to uncover novel biomarkers and elucidate both physiological and pathological processes. Sheng et al harnessed gas chromatography–mass spectrometry to identify four metabolites in serum as potential biomarkers from MA exposure. An untargeted metabolomics approach combining serum and liver analyses revealed 10 potential metabolic biomarkers in mice with ethanol‐induced gastric ulcers that had been administered polysaccharides from Evodiae fructus . These biomarkers are enriched to five significant metabolic pathways. Such research advancements illustrate how metabolomics is not only instrumental in biomarker discovery but also increasingly pivotal in deciphering underlying biological mechanisms. Nan Bao detox capsule (NBDC) has historically been utilized in the treatment of opioid dependency for many years. Prior animal studies conducted by our team demonstrated that NBDC effectively mitigates dependencies on morphine and MA, exhibiting safety profiles verified through acute and long‐term toxicity assessments. Preliminary clinical investigations by our group indicated reduced scores for symptoms of withdrawal, anxiety and TCM syndromes in the treatment group, highlighting the therapeutic potential of NBDC for MA abstinence syndrome, particularly in cases with Qi and Yin deficiencies, toxin accumulation and stasis. Consequently, NBDC has been expanded to include a new indication for alleviating MA addiction. It has obtained authorization for preparation usage in medical facilities in Hunan, China, under the registration number (xiang‐z20090939), and is currently being manufactured at scale, ensuring consistent quality. Quality control (QC) of the formulation is maintained through the use of a chromatographic fingerprint, as depicted in Figures and and Table . Clinically, NBDC has been implemented across 13 local drug rehabilitation centres, including those in Changsha, Shaoyang and Hengyang. Despite its therapeutic applications, the active constituents and the pharmacodynamic mechanism of NBDC remain unclear. Utilizing an animal model of MA addiction, this study endeavours to identify NBDC components that enter the bloodstream via UPLC‐MS, investigate the pharmacodynamic influence of NBDC on the dopaminergic and serotonergic systems and explore the mechanism of action underlying the therapeutic effects of NBDC against MA addiction through metabolomics. This research will provide a scientifically grounded framework for guiding clinical applications of NBDC.
MATERIALS AND METHODS 2.1 Materials and reagents MA was obtained from Shaoyang Addiction Treatment Centre (Shaoyang, China). NBDCs were supplied by Hunan Dekang Pharmaceutical Co. (Changsha, China, batch number: 200801). Risperidone, a positive drug, was purchased from Xi'an Janssen Pharmaceutical Co., Ltd. (Xi'an China, batch number: 190302047, specification: 1 mg per tablet). Anti‐dopamine receptor D1 and anti‐5HT1A receptor antibodies were purchased from Abcam Plc (Cambridge, U.K.). The kits of DA ELISA, 5‐HT ELISA, BCA protein assay and SDS‐PAGE gel and goat anti‐rabbit IgG (H + L) (peroxidase/HRP conjugated) were purchased from Elabscience Biotechnology Co. (Wuhan, China). The kits of QuickBlock™ western solution, haematoxylin–eosin (HE) staining and DAB Horseradish Peroxidase Color Development were purchased from Beyotime Biotech Inc (Shanghai, China). Universal two‐step detection kit was purchased from ZSGB Biotechnology Co. (Beijing, China). GAPDH Polyclonal antibody was purchased from Proteintech Group, Inc. (Wuhan, China). NBDC is a typical Chinese medicine formulation of herbs, animals and minerals detailed in Table . The plant name has been checked with http://www.theplantlist.org . Each herb was tested in accordance with the Chinese Pharmacopoeia (2020 edition) and conformed to the regulations. 2.2 Animal experiments Sprague–Dawley rats (6 weeks of age, weighing 180–200 g, with specific pathogen‐free [SPF] status, and an equal sex ratio of males and females) were obtained from Tianqin Biotechnology Co. Ltd. (Changsha, China), Licence No. SCXK [Xiang] 2019–0014. These animals were housed in an SPF‐grade facility at the Chinese Medicine Research Institute of Hunan Academy of Chinese Medicine, Laboratory Licence No. SYXK [Xiang] 2020‐0008. The experimental protocol involving these animals was ethically reviewed and approved in accordance with internationally recognized guidelines for the care and use of laboratory animals, with the Ethics Approval Number 2021‐0098. According to body weight, 60 rats were randomly divided into six groups: blank group, model group, low‐dose group, medium‐dose group, high‐dose group and positive group, each group consisted of 10 animals. Blood samples from the rats were collected and separated serum and plasma. The samples were preserved at −80°C. The serum was used for biochemical analysis, and the plasma was detected by UPLC‐MS. The hippocampus tissues of the rats were harvested and stored at −80°C for western blot and fixed in 4% paraformaldehyde for pathological examination. In analysing components absorbed into the blood study, the rats ( n = 6) were intragastrically administrated by NBDC (6.48 g/kg) for 14 days. They were called the drug‐containing group (medicated plasma group). Blood samples from the rats were collected, and the plasma was separated to detect by UPLC‐MS. In the metabolomics study, six plasma samples of the blank group, model group and high dose group (drug group) were randomly selected for metabolomics study by UPLC‐MS. 2.3 The analysis of NBDC components in blood and metabolomics study 2.3.1 Sample preparation In this study, 1‐g NBDC samples and 100‐μL plasma samples were thoroughly blended with 400 μL of cold methanol and acetonitrile (v/v, 1:1) by the vortex. Then, the mixtures were handled with sonication for 1 h in 4°C water, reacted at −20°C for 1 h and centrifuged at 16,000 g at 4°C for 20 min. The supernatants were gathered and dried under a vacuum. The samples were redissolved by adding 200‐μL acetonitrile‐aqueous solution (1:1, v/v) and centrifuged for 20 min at 4°C with a speed of 16,000 g . The supernatant was used for UPLC‐MS analysis. 2.3.2 Conditions of UPLC‐MS The untargeted metabolomics and component analysis of the samples was performed on the UPLC‐ESI‐Triple‐TOF 5600‐MS system (UHPLC, Shimadzu Nexera X2 LC‐30 AD, Shimadzu, Japan) coupled with Q‐Exactive Plus (Thermo Scientific, San Jose, USA). The samples were placed in a 4°C autosampler throughout the analysis and were separated using ACQUIY UPLC HSS T3 column (2.1 mm × 100 mm × 1.7 μm, Waters). The flow rate was 0.3 mL/min, the injection volume was 5 μL and the column temperature was 40°C. The mobile phase contained: A: 0.1% formic acid solution in water and B: 100% acetonitrile (ACN). The mobile phase gradient elution is shown in Table . Both electrospray ionization (ESI) positive mode and negative mode were applied for MS data acquisition ). The ESI source conditions were set as follows: spray voltage: 3.8 kv (+), 3.2 kv (−); capillary temperature: 320 (±); sheath gas: 30 (±); aux gas: 5 (±); probe heater temperature: 350 (±); S‐Lens RF level: 50. In MS only acquisition, the instrument was set to acquire over the m/z range 80–1200 Da. The full MS scans were acquired at a resolution of 70 000 at m/z 200 and 17 500 at m/z 200 for MS/MS scans. The maximum injection time was set to 100 ms for MS and 50 ms for MS/MS. The isolation window for MS2 was set to 2 m/z, and the normalized collision energy (stepped) was set as 27, 29 and 32 for fragmentation. QC samples were prepared by mixing different and equal amounts of blank extracted plasma samples to represent the samples under analysis. 2.3.3 Data preprocessing and filtering The raw MS data was pre‐handled by MS‐DIAL for peak alignment, peak area extraction and retention time (RT) correction. The metabolites were screened by accuracy mass (mass tolerance < 0.01 Da) and MS/MS data (mass tolerance < 0.02 Da) and compared with HMDB, PubChem, TCMSP, other public databases and the self‐built metabolite standard library. In the extracted ion features, only the variables having more than 50% of the non‐zero measurement values in at least one group were kept. 2.3.4 Multivariate statistical analysis R (version 4.0.3) and R packages were used for all multivariate data analysis and model building. The principal component analysis (PCA), partial least‐square discriminant analysis (PLS‐DA) and orthogonal partial least‐square discriminant analysis (OPLS‐DA) were used to establish the model and analyse the data. The value of variable importance prediction (VIP) in the model of OPLS‐DA and the p ‐value from the two‐tailed Student's test for two groups analysis or one‐way analysis of variance (ANOVA) for multiple groups analysis were used to determine the discriminating metabolites. The score of VIP indicated the contribution of an element to the discrimination between two groups of samples. The p ‐value suggested whether the difference between groups is significant. 2.3.5 Components absorbed into blood screening The NBDC drug components were identified reference online databases such as PubChem, TCMSP and literatures of single medicinal ingredient analysis. The blood‐absorbed prototype components were screened by VIP value and p ‐value and compared with the NBDC drug compositions to confirm the source of Chinese herbs. 2.3.6 Differential metabolites screening VIP value and p ‐value were used to screen the discriminating metabolites. Components with VIP values greater than 1.0 and p ‐values of less than 0.05 were considered statistically significant metabolites. The identified differential metabolites were subjected to cluster analysis. 2.3.7 KEGG enrichment analysis In order to recognize the involved biological signal pathways, the differential metabolite data were executed KEGG pathway analysis using the KEGG database ( http://www.kegg.jp ). Enriched KEGG pathways were regarded as statistically significant by a p ‐value of less than 0.05. 2.4 The relieve effect of NBDC on MA addiction 2.4.1 Rat modelling and drug administration In our previous pilot experiments, we established three dosage groups of 5, 10 and 20 mg/kg to explore the optimal dosing regimen and cycle for inducing addiction to MA. The results indicated that after MA administration at 20 mg/kg for 14 days, the most significant damage was observed in the hippocampal region. Therefore, for the modelling method, except for the blank group, all other groups received intraperitoneal injections of 20 mg/kg MA for continuous modelling over 14 days. The low, medium and high doses of NBDC were set at 1.62, 3.24 and 6.38 g/kg, respectively, equivalent to half, one and two times the equivalent rat dose calculated based on the maximum clinical dose for humans. The drugs were dissolved to the required concentrations in purified water before administration via gavage. For the positive (risperidone) group, the dosage was set at 1.08 mg/kg, equivalent to twice the equivalent rat dose, and administered via gavage for 14 consecutive days. 2.4.2 Ethology evaluation Conditioned place preference The conditioned place preference (CPP) experimental box was homemade, and the experiment was divided into pre‐conditioning phase, conditioning phase, testing phase and extinction phase. The pre‐conditioning phase was from the first day to the third day. The middle partition of the CPP box was opened. The rats were put into the box to run freely and acclimatized once daily for 20 min each for 3 days. The residence time of the rats in the white box and the black box was recorded. It implied the natural preference tendency of the rats and helped select the non‐naturally preferred side box as the companion drug box. The conditioning phase was from the fourth day to the 17th day. The model and treatment groups were injected intraperitoneally with MA, and the blank group was injected with equal saline. The animals were put into the companion box with closed access; then, the experimental rats were conditioned to train for 30 min each time; after 8 h, equal amounts of saline were injected; then, the rats were put into the non‐companion box to train for 30 min, and the training continued for 14 days. The elimination stage was from the 18th to the 31st day. Only saline or Nan Bao detoxification clear capsule was given, and the rats were not trained. The test phase was on the 32nd day. The animals were put into the CPP training box and observed the conditioned positional preference response. CPP score is based on activity time in the companion drug box. The specific modelling and administration methods are shown in Figure . Stereotyped behaviour A stereotyped behaviour test was conducted using the following scale: if rats were stationary, little or normal movement, scoring zero; if rats were active, occasional to frequent movement, scoring one; if rats were active with episodes of repetitive forward head searching, scoring two; if rats were continuous forward head searching, scoring three; if rats were frequent repetitive rearing, side‐to‐side weaving or turning, scoring four; and if rats were episodes of rapid jerking side‐to‐side, circular or dorsoventral head movements, scoring five. Stereotyped behaviours were scored by a valuator unaware of the specific experimental conditions. After each MA injection, rats were placed at the centre of the empty cage for a 10‐min adaptive period. Then, the stereotyped behaviours of each rat were scored every 10 min over the next 60 min by an observer blind to the treatments. The final score was from the average score. Spontaneous locomotor activity After 20 min of administration, the rats were placed in the YLS‐1B multifunctional rat spontaneous activity recorder (Shandong Academy of Medical Sciences Equipment Station Products). And then, the instrument began to record the number of autonomous activities in rats within 10 min. 2.4.3 Neurotransmitter and receptor changes DA and 5‐HT concentration changes Blood was collected from rats, and the supernatant was centrifuged. The determination of DA or 5‐HT concentration referred to the ELISA kit. The optical density (OD) value was measured at 450 nm using an enzyme calibrator. DRD1 and 5‐HT1A receptor expression changes The expressions of DAD1 and HIT1A receptors in the hippocampus were detected by immunohistochemical staining (IHC) and western blot (WB) experiments. Immunoreactivity was quantified using the software of Image J to measure the mean OD positive cells. Densitometric analysis was performed using gel image scanner equipment (ChemiDoc XRS, Biorad, USA). 2.4.4 Hippocampus histopathology observation The Hippocampus was isolated, fixed in 4% paraformaldehyde, embedded in paraffin and then cut into thin sections (about 5 μm). The paraffin sections were stained with HE staining. The morphological changes of cells in the hippocampus tissues were observed and recorded using a colourized pathology image analyser. 2.4.5 Statistical analyses SPSS 21.0 statistical software was used to analyse the data. Data on continuous variables conformed to a normal distribution with homogeneous variance and were expressed as the mean ± standard deviation. The two‐tailed Student's test for two groups analysis or one‐way ANOVA for multiple groups analysis was used to compare differences between groups. p < 0.05, p < 0.01 and p < 0.001 were considered significant, statistically significant and highly significant, respectively. 2.5 Relevance analysis The Spearman correlation between serum metabolites and pharmacodynamic indicators was performed by the corr.test function from the pacman R package. We completed the correlation in those pharmacodynamic indicators and metabolites ( p < 0.05, VIP > 1), which were found to be statistically significant between groups.
Materials and reagents MA was obtained from Shaoyang Addiction Treatment Centre (Shaoyang, China). NBDCs were supplied by Hunan Dekang Pharmaceutical Co. (Changsha, China, batch number: 200801). Risperidone, a positive drug, was purchased from Xi'an Janssen Pharmaceutical Co., Ltd. (Xi'an China, batch number: 190302047, specification: 1 mg per tablet). Anti‐dopamine receptor D1 and anti‐5HT1A receptor antibodies were purchased from Abcam Plc (Cambridge, U.K.). The kits of DA ELISA, 5‐HT ELISA, BCA protein assay and SDS‐PAGE gel and goat anti‐rabbit IgG (H + L) (peroxidase/HRP conjugated) were purchased from Elabscience Biotechnology Co. (Wuhan, China). The kits of QuickBlock™ western solution, haematoxylin–eosin (HE) staining and DAB Horseradish Peroxidase Color Development were purchased from Beyotime Biotech Inc (Shanghai, China). Universal two‐step detection kit was purchased from ZSGB Biotechnology Co. (Beijing, China). GAPDH Polyclonal antibody was purchased from Proteintech Group, Inc. (Wuhan, China). NBDC is a typical Chinese medicine formulation of herbs, animals and minerals detailed in Table . The plant name has been checked with http://www.theplantlist.org . Each herb was tested in accordance with the Chinese Pharmacopoeia (2020 edition) and conformed to the regulations.
Animal experiments Sprague–Dawley rats (6 weeks of age, weighing 180–200 g, with specific pathogen‐free [SPF] status, and an equal sex ratio of males and females) were obtained from Tianqin Biotechnology Co. Ltd. (Changsha, China), Licence No. SCXK [Xiang] 2019–0014. These animals were housed in an SPF‐grade facility at the Chinese Medicine Research Institute of Hunan Academy of Chinese Medicine, Laboratory Licence No. SYXK [Xiang] 2020‐0008. The experimental protocol involving these animals was ethically reviewed and approved in accordance with internationally recognized guidelines for the care and use of laboratory animals, with the Ethics Approval Number 2021‐0098. According to body weight, 60 rats were randomly divided into six groups: blank group, model group, low‐dose group, medium‐dose group, high‐dose group and positive group, each group consisted of 10 animals. Blood samples from the rats were collected and separated serum and plasma. The samples were preserved at −80°C. The serum was used for biochemical analysis, and the plasma was detected by UPLC‐MS. The hippocampus tissues of the rats were harvested and stored at −80°C for western blot and fixed in 4% paraformaldehyde for pathological examination. In analysing components absorbed into the blood study, the rats ( n = 6) were intragastrically administrated by NBDC (6.48 g/kg) for 14 days. They were called the drug‐containing group (medicated plasma group). Blood samples from the rats were collected, and the plasma was separated to detect by UPLC‐MS. In the metabolomics study, six plasma samples of the blank group, model group and high dose group (drug group) were randomly selected for metabolomics study by UPLC‐MS.
The analysis of NBDC components in blood and metabolomics study 2.3.1 Sample preparation In this study, 1‐g NBDC samples and 100‐μL plasma samples were thoroughly blended with 400 μL of cold methanol and acetonitrile (v/v, 1:1) by the vortex. Then, the mixtures were handled with sonication for 1 h in 4°C water, reacted at −20°C for 1 h and centrifuged at 16,000 g at 4°C for 20 min. The supernatants were gathered and dried under a vacuum. The samples were redissolved by adding 200‐μL acetonitrile‐aqueous solution (1:1, v/v) and centrifuged for 20 min at 4°C with a speed of 16,000 g . The supernatant was used for UPLC‐MS analysis. 2.3.2 Conditions of UPLC‐MS The untargeted metabolomics and component analysis of the samples was performed on the UPLC‐ESI‐Triple‐TOF 5600‐MS system (UHPLC, Shimadzu Nexera X2 LC‐30 AD, Shimadzu, Japan) coupled with Q‐Exactive Plus (Thermo Scientific, San Jose, USA). The samples were placed in a 4°C autosampler throughout the analysis and were separated using ACQUIY UPLC HSS T3 column (2.1 mm × 100 mm × 1.7 μm, Waters). The flow rate was 0.3 mL/min, the injection volume was 5 μL and the column temperature was 40°C. The mobile phase contained: A: 0.1% formic acid solution in water and B: 100% acetonitrile (ACN). The mobile phase gradient elution is shown in Table . Both electrospray ionization (ESI) positive mode and negative mode were applied for MS data acquisition ). The ESI source conditions were set as follows: spray voltage: 3.8 kv (+), 3.2 kv (−); capillary temperature: 320 (±); sheath gas: 30 (±); aux gas: 5 (±); probe heater temperature: 350 (±); S‐Lens RF level: 50. In MS only acquisition, the instrument was set to acquire over the m/z range 80–1200 Da. The full MS scans were acquired at a resolution of 70 000 at m/z 200 and 17 500 at m/z 200 for MS/MS scans. The maximum injection time was set to 100 ms for MS and 50 ms for MS/MS. The isolation window for MS2 was set to 2 m/z, and the normalized collision energy (stepped) was set as 27, 29 and 32 for fragmentation. QC samples were prepared by mixing different and equal amounts of blank extracted plasma samples to represent the samples under analysis. 2.3.3 Data preprocessing and filtering The raw MS data was pre‐handled by MS‐DIAL for peak alignment, peak area extraction and retention time (RT) correction. The metabolites were screened by accuracy mass (mass tolerance < 0.01 Da) and MS/MS data (mass tolerance < 0.02 Da) and compared with HMDB, PubChem, TCMSP, other public databases and the self‐built metabolite standard library. In the extracted ion features, only the variables having more than 50% of the non‐zero measurement values in at least one group were kept. 2.3.4 Multivariate statistical analysis R (version 4.0.3) and R packages were used for all multivariate data analysis and model building. The principal component analysis (PCA), partial least‐square discriminant analysis (PLS‐DA) and orthogonal partial least‐square discriminant analysis (OPLS‐DA) were used to establish the model and analyse the data. The value of variable importance prediction (VIP) in the model of OPLS‐DA and the p ‐value from the two‐tailed Student's test for two groups analysis or one‐way analysis of variance (ANOVA) for multiple groups analysis were used to determine the discriminating metabolites. The score of VIP indicated the contribution of an element to the discrimination between two groups of samples. The p ‐value suggested whether the difference between groups is significant. 2.3.5 Components absorbed into blood screening The NBDC drug components were identified reference online databases such as PubChem, TCMSP and literatures of single medicinal ingredient analysis. The blood‐absorbed prototype components were screened by VIP value and p ‐value and compared with the NBDC drug compositions to confirm the source of Chinese herbs. 2.3.6 Differential metabolites screening VIP value and p ‐value were used to screen the discriminating metabolites. Components with VIP values greater than 1.0 and p ‐values of less than 0.05 were considered statistically significant metabolites. The identified differential metabolites were subjected to cluster analysis. 2.3.7 KEGG enrichment analysis In order to recognize the involved biological signal pathways, the differential metabolite data were executed KEGG pathway analysis using the KEGG database ( http://www.kegg.jp ). Enriched KEGG pathways were regarded as statistically significant by a p ‐value of less than 0.05.
Sample preparation In this study, 1‐g NBDC samples and 100‐μL plasma samples were thoroughly blended with 400 μL of cold methanol and acetonitrile (v/v, 1:1) by the vortex. Then, the mixtures were handled with sonication for 1 h in 4°C water, reacted at −20°C for 1 h and centrifuged at 16,000 g at 4°C for 20 min. The supernatants were gathered and dried under a vacuum. The samples were redissolved by adding 200‐μL acetonitrile‐aqueous solution (1:1, v/v) and centrifuged for 20 min at 4°C with a speed of 16,000 g . The supernatant was used for UPLC‐MS analysis.
Conditions of UPLC‐MS The untargeted metabolomics and component analysis of the samples was performed on the UPLC‐ESI‐Triple‐TOF 5600‐MS system (UHPLC, Shimadzu Nexera X2 LC‐30 AD, Shimadzu, Japan) coupled with Q‐Exactive Plus (Thermo Scientific, San Jose, USA). The samples were placed in a 4°C autosampler throughout the analysis and were separated using ACQUIY UPLC HSS T3 column (2.1 mm × 100 mm × 1.7 μm, Waters). The flow rate was 0.3 mL/min, the injection volume was 5 μL and the column temperature was 40°C. The mobile phase contained: A: 0.1% formic acid solution in water and B: 100% acetonitrile (ACN). The mobile phase gradient elution is shown in Table . Both electrospray ionization (ESI) positive mode and negative mode were applied for MS data acquisition ). The ESI source conditions were set as follows: spray voltage: 3.8 kv (+), 3.2 kv (−); capillary temperature: 320 (±); sheath gas: 30 (±); aux gas: 5 (±); probe heater temperature: 350 (±); S‐Lens RF level: 50. In MS only acquisition, the instrument was set to acquire over the m/z range 80–1200 Da. The full MS scans were acquired at a resolution of 70 000 at m/z 200 and 17 500 at m/z 200 for MS/MS scans. The maximum injection time was set to 100 ms for MS and 50 ms for MS/MS. The isolation window for MS2 was set to 2 m/z, and the normalized collision energy (stepped) was set as 27, 29 and 32 for fragmentation. QC samples were prepared by mixing different and equal amounts of blank extracted plasma samples to represent the samples under analysis.
Data preprocessing and filtering The raw MS data was pre‐handled by MS‐DIAL for peak alignment, peak area extraction and retention time (RT) correction. The metabolites were screened by accuracy mass (mass tolerance < 0.01 Da) and MS/MS data (mass tolerance < 0.02 Da) and compared with HMDB, PubChem, TCMSP, other public databases and the self‐built metabolite standard library. In the extracted ion features, only the variables having more than 50% of the non‐zero measurement values in at least one group were kept.
Multivariate statistical analysis R (version 4.0.3) and R packages were used for all multivariate data analysis and model building. The principal component analysis (PCA), partial least‐square discriminant analysis (PLS‐DA) and orthogonal partial least‐square discriminant analysis (OPLS‐DA) were used to establish the model and analyse the data. The value of variable importance prediction (VIP) in the model of OPLS‐DA and the p ‐value from the two‐tailed Student's test for two groups analysis or one‐way analysis of variance (ANOVA) for multiple groups analysis were used to determine the discriminating metabolites. The score of VIP indicated the contribution of an element to the discrimination between two groups of samples. The p ‐value suggested whether the difference between groups is significant.
Components absorbed into blood screening The NBDC drug components were identified reference online databases such as PubChem, TCMSP and literatures of single medicinal ingredient analysis. The blood‐absorbed prototype components were screened by VIP value and p ‐value and compared with the NBDC drug compositions to confirm the source of Chinese herbs.
Differential metabolites screening VIP value and p ‐value were used to screen the discriminating metabolites. Components with VIP values greater than 1.0 and p ‐values of less than 0.05 were considered statistically significant metabolites. The identified differential metabolites were subjected to cluster analysis.
KEGG enrichment analysis In order to recognize the involved biological signal pathways, the differential metabolite data were executed KEGG pathway analysis using the KEGG database ( http://www.kegg.jp ). Enriched KEGG pathways were regarded as statistically significant by a p ‐value of less than 0.05.
The relieve effect of NBDC on MA addiction 2.4.1 Rat modelling and drug administration In our previous pilot experiments, we established three dosage groups of 5, 10 and 20 mg/kg to explore the optimal dosing regimen and cycle for inducing addiction to MA. The results indicated that after MA administration at 20 mg/kg for 14 days, the most significant damage was observed in the hippocampal region. Therefore, for the modelling method, except for the blank group, all other groups received intraperitoneal injections of 20 mg/kg MA for continuous modelling over 14 days. The low, medium and high doses of NBDC were set at 1.62, 3.24 and 6.38 g/kg, respectively, equivalent to half, one and two times the equivalent rat dose calculated based on the maximum clinical dose for humans. The drugs were dissolved to the required concentrations in purified water before administration via gavage. For the positive (risperidone) group, the dosage was set at 1.08 mg/kg, equivalent to twice the equivalent rat dose, and administered via gavage for 14 consecutive days. 2.4.2 Ethology evaluation Conditioned place preference The conditioned place preference (CPP) experimental box was homemade, and the experiment was divided into pre‐conditioning phase, conditioning phase, testing phase and extinction phase. The pre‐conditioning phase was from the first day to the third day. The middle partition of the CPP box was opened. The rats were put into the box to run freely and acclimatized once daily for 20 min each for 3 days. The residence time of the rats in the white box and the black box was recorded. It implied the natural preference tendency of the rats and helped select the non‐naturally preferred side box as the companion drug box. The conditioning phase was from the fourth day to the 17th day. The model and treatment groups were injected intraperitoneally with MA, and the blank group was injected with equal saline. The animals were put into the companion box with closed access; then, the experimental rats were conditioned to train for 30 min each time; after 8 h, equal amounts of saline were injected; then, the rats were put into the non‐companion box to train for 30 min, and the training continued for 14 days. The elimination stage was from the 18th to the 31st day. Only saline or Nan Bao detoxification clear capsule was given, and the rats were not trained. The test phase was on the 32nd day. The animals were put into the CPP training box and observed the conditioned positional preference response. CPP score is based on activity time in the companion drug box. The specific modelling and administration methods are shown in Figure . Stereotyped behaviour A stereotyped behaviour test was conducted using the following scale: if rats were stationary, little or normal movement, scoring zero; if rats were active, occasional to frequent movement, scoring one; if rats were active with episodes of repetitive forward head searching, scoring two; if rats were continuous forward head searching, scoring three; if rats were frequent repetitive rearing, side‐to‐side weaving or turning, scoring four; and if rats were episodes of rapid jerking side‐to‐side, circular or dorsoventral head movements, scoring five. Stereotyped behaviours were scored by a valuator unaware of the specific experimental conditions. After each MA injection, rats were placed at the centre of the empty cage for a 10‐min adaptive period. Then, the stereotyped behaviours of each rat were scored every 10 min over the next 60 min by an observer blind to the treatments. The final score was from the average score. Spontaneous locomotor activity After 20 min of administration, the rats were placed in the YLS‐1B multifunctional rat spontaneous activity recorder (Shandong Academy of Medical Sciences Equipment Station Products). And then, the instrument began to record the number of autonomous activities in rats within 10 min. 2.4.3 Neurotransmitter and receptor changes DA and 5‐HT concentration changes Blood was collected from rats, and the supernatant was centrifuged. The determination of DA or 5‐HT concentration referred to the ELISA kit. The optical density (OD) value was measured at 450 nm using an enzyme calibrator. DRD1 and 5‐HT1A receptor expression changes The expressions of DAD1 and HIT1A receptors in the hippocampus were detected by immunohistochemical staining (IHC) and western blot (WB) experiments. Immunoreactivity was quantified using the software of Image J to measure the mean OD positive cells. Densitometric analysis was performed using gel image scanner equipment (ChemiDoc XRS, Biorad, USA). 2.4.4 Hippocampus histopathology observation The Hippocampus was isolated, fixed in 4% paraformaldehyde, embedded in paraffin and then cut into thin sections (about 5 μm). The paraffin sections were stained with HE staining. The morphological changes of cells in the hippocampus tissues were observed and recorded using a colourized pathology image analyser. 2.4.5 Statistical analyses SPSS 21.0 statistical software was used to analyse the data. Data on continuous variables conformed to a normal distribution with homogeneous variance and were expressed as the mean ± standard deviation. The two‐tailed Student's test for two groups analysis or one‐way ANOVA for multiple groups analysis was used to compare differences between groups. p < 0.05, p < 0.01 and p < 0.001 were considered significant, statistically significant and highly significant, respectively.
Rat modelling and drug administration In our previous pilot experiments, we established three dosage groups of 5, 10 and 20 mg/kg to explore the optimal dosing regimen and cycle for inducing addiction to MA. The results indicated that after MA administration at 20 mg/kg for 14 days, the most significant damage was observed in the hippocampal region. Therefore, for the modelling method, except for the blank group, all other groups received intraperitoneal injections of 20 mg/kg MA for continuous modelling over 14 days. The low, medium and high doses of NBDC were set at 1.62, 3.24 and 6.38 g/kg, respectively, equivalent to half, one and two times the equivalent rat dose calculated based on the maximum clinical dose for humans. The drugs were dissolved to the required concentrations in purified water before administration via gavage. For the positive (risperidone) group, the dosage was set at 1.08 mg/kg, equivalent to twice the equivalent rat dose, and administered via gavage for 14 consecutive days.
Ethology evaluation Conditioned place preference The conditioned place preference (CPP) experimental box was homemade, and the experiment was divided into pre‐conditioning phase, conditioning phase, testing phase and extinction phase. The pre‐conditioning phase was from the first day to the third day. The middle partition of the CPP box was opened. The rats were put into the box to run freely and acclimatized once daily for 20 min each for 3 days. The residence time of the rats in the white box and the black box was recorded. It implied the natural preference tendency of the rats and helped select the non‐naturally preferred side box as the companion drug box. The conditioning phase was from the fourth day to the 17th day. The model and treatment groups were injected intraperitoneally with MA, and the blank group was injected with equal saline. The animals were put into the companion box with closed access; then, the experimental rats were conditioned to train for 30 min each time; after 8 h, equal amounts of saline were injected; then, the rats were put into the non‐companion box to train for 30 min, and the training continued for 14 days. The elimination stage was from the 18th to the 31st day. Only saline or Nan Bao detoxification clear capsule was given, and the rats were not trained. The test phase was on the 32nd day. The animals were put into the CPP training box and observed the conditioned positional preference response. CPP score is based on activity time in the companion drug box. The specific modelling and administration methods are shown in Figure . Stereotyped behaviour A stereotyped behaviour test was conducted using the following scale: if rats were stationary, little or normal movement, scoring zero; if rats were active, occasional to frequent movement, scoring one; if rats were active with episodes of repetitive forward head searching, scoring two; if rats were continuous forward head searching, scoring three; if rats were frequent repetitive rearing, side‐to‐side weaving or turning, scoring four; and if rats were episodes of rapid jerking side‐to‐side, circular or dorsoventral head movements, scoring five. Stereotyped behaviours were scored by a valuator unaware of the specific experimental conditions. After each MA injection, rats were placed at the centre of the empty cage for a 10‐min adaptive period. Then, the stereotyped behaviours of each rat were scored every 10 min over the next 60 min by an observer blind to the treatments. The final score was from the average score. Spontaneous locomotor activity After 20 min of administration, the rats were placed in the YLS‐1B multifunctional rat spontaneous activity recorder (Shandong Academy of Medical Sciences Equipment Station Products). And then, the instrument began to record the number of autonomous activities in rats within 10 min.
The conditioned place preference (CPP) experimental box was homemade, and the experiment was divided into pre‐conditioning phase, conditioning phase, testing phase and extinction phase. The pre‐conditioning phase was from the first day to the third day. The middle partition of the CPP box was opened. The rats were put into the box to run freely and acclimatized once daily for 20 min each for 3 days. The residence time of the rats in the white box and the black box was recorded. It implied the natural preference tendency of the rats and helped select the non‐naturally preferred side box as the companion drug box. The conditioning phase was from the fourth day to the 17th day. The model and treatment groups were injected intraperitoneally with MA, and the blank group was injected with equal saline. The animals were put into the companion box with closed access; then, the experimental rats were conditioned to train for 30 min each time; after 8 h, equal amounts of saline were injected; then, the rats were put into the non‐companion box to train for 30 min, and the training continued for 14 days. The elimination stage was from the 18th to the 31st day. Only saline or Nan Bao detoxification clear capsule was given, and the rats were not trained. The test phase was on the 32nd day. The animals were put into the CPP training box and observed the conditioned positional preference response. CPP score is based on activity time in the companion drug box. The specific modelling and administration methods are shown in Figure .
A stereotyped behaviour test was conducted using the following scale: if rats were stationary, little or normal movement, scoring zero; if rats were active, occasional to frequent movement, scoring one; if rats were active with episodes of repetitive forward head searching, scoring two; if rats were continuous forward head searching, scoring three; if rats were frequent repetitive rearing, side‐to‐side weaving or turning, scoring four; and if rats were episodes of rapid jerking side‐to‐side, circular or dorsoventral head movements, scoring five. Stereotyped behaviours were scored by a valuator unaware of the specific experimental conditions. After each MA injection, rats were placed at the centre of the empty cage for a 10‐min adaptive period. Then, the stereotyped behaviours of each rat were scored every 10 min over the next 60 min by an observer blind to the treatments. The final score was from the average score.
After 20 min of administration, the rats were placed in the YLS‐1B multifunctional rat spontaneous activity recorder (Shandong Academy of Medical Sciences Equipment Station Products). And then, the instrument began to record the number of autonomous activities in rats within 10 min.
Neurotransmitter and receptor changes DA and 5‐HT concentration changes Blood was collected from rats, and the supernatant was centrifuged. The determination of DA or 5‐HT concentration referred to the ELISA kit. The optical density (OD) value was measured at 450 nm using an enzyme calibrator. DRD1 and 5‐HT1A receptor expression changes The expressions of DAD1 and HIT1A receptors in the hippocampus were detected by immunohistochemical staining (IHC) and western blot (WB) experiments. Immunoreactivity was quantified using the software of Image J to measure the mean OD positive cells. Densitometric analysis was performed using gel image scanner equipment (ChemiDoc XRS, Biorad, USA).
Blood was collected from rats, and the supernatant was centrifuged. The determination of DA or 5‐HT concentration referred to the ELISA kit. The optical density (OD) value was measured at 450 nm using an enzyme calibrator.
The expressions of DAD1 and HIT1A receptors in the hippocampus were detected by immunohistochemical staining (IHC) and western blot (WB) experiments. Immunoreactivity was quantified using the software of Image J to measure the mean OD positive cells. Densitometric analysis was performed using gel image scanner equipment (ChemiDoc XRS, Biorad, USA).
Hippocampus histopathology observation The Hippocampus was isolated, fixed in 4% paraformaldehyde, embedded in paraffin and then cut into thin sections (about 5 μm). The paraffin sections were stained with HE staining. The morphological changes of cells in the hippocampus tissues were observed and recorded using a colourized pathology image analyser.
Statistical analyses SPSS 21.0 statistical software was used to analyse the data. Data on continuous variables conformed to a normal distribution with homogeneous variance and were expressed as the mean ± standard deviation. The two‐tailed Student's test for two groups analysis or one‐way ANOVA for multiple groups analysis was used to compare differences between groups. p < 0.05, p < 0.01 and p < 0.001 were considered significant, statistically significant and highly significant, respectively.
Relevance analysis The Spearman correlation between serum metabolites and pharmacodynamic indicators was performed by the corr.test function from the pacman R package. We completed the correlation in those pharmacodynamic indicators and metabolites ( p < 0.05, VIP > 1), which were found to be statistically significant between groups.
RESULTS 3.1 Analysis of NBDC chemical components in vivo and in vitro using UPLC‐Q‐Orbitrap‐MS 3.1.1 PCA The TIC of the plasma samples in the blank, model and drug (high‐dose) group in positive and negative ion mode are shown in Figure . The mass spectrometry detection data of NB capsules, blank plasma group, drug‐containing plasma group and QC sample group were imported into SIMCA software and analysed by PCA, which showed that the QC samples clustered well together, indicating good instrument stability and reliable data results (Figure ). 3.1.2 PLS‐DA PLS‐DA was applied to investigate the changes in plasma metabolites in the blank group and drug‐containing group. The PLS‐DA score plots were generated based on the metabolites detected in positive and negative ion modes (Figure ). The blank group and the drug‐containing group were separated on both sides, proving significant differences in the chemical composition of the two groups of samples. The value of R2Y was 1.0, and Q2 was 0.891 in positive ion mode. In negative ion mode, the value of R2Y was 1.0 and Q2 was 0.849. The permutation tests for PLS‐DA models are shown in Figure . The above data prove that the model is stable and reliable with good prediction ability. 3.1.3 Orthogonal projections to latent structures analysis (OPLS‐DA) OPLS‐DA was applied to investigate the changes in plasma metabolites in the blank group and drug‐containing group. The OPLS‐DA score plots were generated based on the metabolites detected in positive and negative ion modes (Figure ). The blank and drug‐containing groups were distinguished, implying that the between‐group differences were more significant than the within‐group differences and that the model could be used to screen for differential chemical compounds between the two groups. The value of R2Y was 1.0, and Q2 was 0.851 in positive ion mode. In negative ion mode, the value of R2Y was 1.0, and Q2 was 0.808. The permutation tests for OPLS‐DA models are shown in Figure . The above data prove that the model is stable and reliable with good prediction ability. 3.1.4 Identification and analysis of absorbed components of NBDC A total of 258 components in NB capsules were identified or tentatively characterized, 154 in positive ion mode and 104 in negative ion mode. The difference compounds between the blank group and the drug‐containing group were screened with criteria that the value of FC was more than 2, the VIP value was more than 1 and the p ‐value was less than 0.05. Compared with NBDC compounds, 87 components of prototype compounds in plasma were identified, 57 in positive and 30 in negative ion modes. The constituents absorbed into blood were mainly derived from the Zhichuanwu, Zhicaowu, Yanhusuo, Gouteng, Renshen and Gancao and mostly belonged to alkaloids, flavonoids and saponosides shown in Figure . The compound‐specific information is shown in Table . 3.2 Effect of NBDC on MA‐addicted rats 3.2.1 Effect on body weight Compared to the blank group, the model group of rats demonstrated a significant reduction in body weight ( p < 0.05). In contrast, both the medium and high dose groups, as well as the positive drug group, exhibited increased body weights relative to the model group ( p < 0.05). These results suggest that NBDC can increase the body weight of MA‐induced rats. The results are shown in Table . 3.2.2 Effect on ethology The result of ethology is shown in Table and Figure . An elevation in the CPP score was evident in the model group relative to the blank group ( p < 0.01), indicating the development of a position‐specific conditioned preference by the rats toward the drug‐paired chamber. This confirms the successful establishment of the MA‐induced rat model. Similarly, the number of spontaneous activities and the score of stereotyped behaviour increased in the model group compared with the blank group ( p < 0.01). Subsequent treatment with NBDC or risperidone led to a significant reduction in three behavioural parameters, with trends toward normalization to levels observed in the blank group ( p < 0.05). Conversely, the low‐dose group showed no significant change in CPP scores compared to the model group ( p > 0.05). Furthermore, the CPP score was found to be lower in the positive control group compared to the high‐dose group. Collectively, these outcomes suggest that high‐dose NBDC effectively mitigates MA‐induced CPP in rats, demonstrating a superior efficacy profile to risperidone. 3.2.3 Effect on the concentration of DA and 5‐HT in serum DA and 5‐HT are common biomarkers in addiction to MA. Figure shows the alterations in serum concentrations of DA and 5‐HT in rats before and after modelling and drug administration. Compared to the blank group, the model group exhibited a significant increase in both DA and 5‐HT levels ( p < 0.05). When compared with the model group, the DA levels were higher in the medium‐dose, high‐dose and positive groups ( p < 0.05), whereas the high‐dose group showed an increase in 5‐HT levels ( p < 0.05), and the positive control group demonstrated a decrease in 5‐HT levels ( p < 0.05). 3.2.4 Effect on the expression of DRD1 and 5‐HT1AR in the hippocampus To delineate the impact of NBDC on the dopaminergic and serotonergic systems within the hippocampus, western blot (WB) assays and immunohistochemistry (IHC) staining techniques were employed to quantify the protein levels of dopamine receptor D1 (DRD1) and serotonin receptor 1A (5‐HT1AR), respectively. The findings from both methodologies are concordant, as depicted in Figure . MA exposure led to a significant downregulation of DRD1 levels relative to the blank group ( p < 0.01). Post‐treatment with NBDC or risperidone, there was a notable restoration of DRD1 protein expression compared to the model group ( p < 0.05). Conversely, MA engendered an upregulation of 5‐HT1AR protein expression compared with the blank group ( p < 0.05), an effect which also appeared in the NBDC treatment group compared with the model group ( p < 0.05). No discernible variation in 5‐HT1AR receptor expression was observed between the positive group and the model group ( p > 0.05). 3.2.5 Effect on cells morphological changes in the hippocampus The morphological alterations induced by MA within hippocampal cells upon exposure were examined using phase‐contrast microscopy to assess the therapeutic effects of NBDC. Microscopic observation revealed that rats administered with MA exhibited distinct histopathological disruptions, characterized by the disarray of pyramidal cells, intensified nuclear staining and a decline in the quantity of intact neurons, among other cellular anomalies. The hippocampal cell morphology in animals treated with NBDC progressively regained normalcy, as illustrated in Figure . This suggests that NBDC possesses potential neurorestorative properties capable of mitigating the deleterious effects of MA on hippocampal architecture. 3.3 Mechanism of NBDC relieving MA addiction based on metabolomics 3.3.1 Total ion chromatogram of metabolomics of plasma The TIC of the plasma samples in the blank, model and drug (high‐dose) groups in positive and negative ion modes are shown in Figure . After data preprocessing, comparing the RT and matching with HMDB databases, 614 and 525 compounds were identified from plasma samples in the positive and negative ion modes, respectively. 3.3.2 Analysis of differential metabolites and metabolic pathways in MA addiction Multivariate statistical analysis The metabolites in the plasma samples of the model and blank groups were analysed by using PCA, and the model and blank groups were clearly distinguished in the positive ion model (Figure ), indicating that the chemical composition of the samples in the two groups was significantly different. However, there was no significant difference between the two groups in negative ion mode (Figure ). In the PLS‐DA supervised model, the parameters of R2Y and Q2 were 1.0 and 0.706, respectively, in the positive ion mode and 1.0 and 0.436, respectively, in the negative ion mode. The parameters were R2Y = 1.0, Q2 = 0.586, and R2Y = 1.0, Q2 = 0.255, respectively, in positive and negative ion modes in the OPLS‐DA supervised model. The above data indicates that the model is steady and trusty with excellent predictive ability in the positive ion model (Figure ). The data of this experiment were statistically analysed using the data under the positive ion model. Differential metabolite screening Differential metabolites were screened by the VIP value of the OPLS‐DA model and the p ‐value of the t ‐test. Based on VIP > 1.0 and p < 0.05, 75 differential metabolites were screened between the model and the blank groups in the positive ion mode. A total of 19 metabolites were upregulated (FC > 1), and 56 metabolites were downregulated (FC < 1). The top 50 differential metabolites with VIP values were selected for hierarchical cluster analysis, with up‐regulation in red and down‐regulation in green (Figure ). Potential biomarker prediction The screened differential metabolites were subjected to functional analysis in HMDB and KEGG database. Finally, eight differential endogenous metabolites in the serum of MA‐induced rats were confirmed as potential biomarkers of MA addiction and are shown in Table . Compared with the blank group, the levels of anserine, histidine, pregnenolone and 3‐methylhistidine were increased. The levels of L‐dopa, 1,5‐anhydro‐D‐sorbitol, melibiose and norharman were decreased in the model group. KEGG pathway analysis To further explore the overall metabolic alterations during MA addiction, the data of screened differential metabolites were dealt with the MetaboAnalyst platform for enrichment analysis and pathway analysis, matching with multiple metabolic pathways. The potential MA addiction pathways by the KEGG pathway analysis in the plasma are shown in Figure . The results showed that the main enrichment pathways for differential metabolites included cocaine addiction, amphetamine addiction and alcoholism. Among them, histidine and tyrosine metabolism had the smallest p ‐value, the highest significance and the most enriched metabolites. 3.3.3 Analysis of differential metabolites and metabolic pathways in NBDC relieving effect on MA addiction Multivariate statistical analysis The metabolites in the model and drug groups' plasma samples were analysed by using PCA, PLS‐DA and OPLS‐DA. In the PCA unsupervised model, the model and drug groups were clearly distinguished in the positive ion model (Figure ) and the negative ion model (Figure ), indicating that the composition of metabolites in the rat with MA addiction has been varied. The PLS‐DA supervised model was steady and trusty, which can be confirmed by the parameters (R2Y = 1.0, Q2 = 0.903) based on the permutation test in the positive ion mode (Figure ). The OPLS‐DA supervised model was also steady and trusty, which can be confirmed by the parameters (R2Y = 1.0, Q2 = 0.916) based on the permutation test in the positive ion mode (Figure ). The above data proved that the model is steady and trusty with excellent predictive ability in the positive ion model. Differential metabolite screening Differential metabolites were screened by the VIP value of the OPLS‐DA model and the p ‐value of the t ‐test. Based on VIP > 1.0 and p < 0.05, 231 differential metabolites were screened in the positive ion mode between the drug and the model groups. A total of 156 metabolites were upregulated (FC > 1), and 75 metabolites were downregulated (FC < 1). The top 50 differential metabolites with the VIP value were selected for hierarchical cluster analysis, with up‐regulation in red and down‐regulation in green (Figure ). Potential biomarker prediction The screened differential metabolites were subjected to functional analysis in HMDB and KEGG database. Finally, 26 differential endogenous metabolites in the serum of MA‐induced rats were confirmed as potential biomarkers of MA addiction and shown in Table . Compared with the model group, the levels of 4‐(beta‐acetylaminoethyl) imidazole, norharman, cytidine 5′‐diphosphocholine, 4‐aminobenzoic acid, L‐tyrosine, L‐dopa, D‐alanyl‐D‐alanine, dopamine, all‐trans‐retinoic acid, L‐theanine, 4‐aminophenol, trimethylamine N‐oxide, pregnenolone, 3‐methylcrotonylglycine, 5′‐methylthioadenosine, 4‐guanidinobutyric acid, histidine, D‐tryptophan and diethanolamine were increased, and the levels of palmitoylcarnitine, isoleucine, nicotinamide, homoarginine, lactose, bilirubin and tauroursodeoxycholic acid were decreased in the drug group. KEGG pathway analysis The potential NBDC relieving MA addiction pathways by the KEGG pathway analysis in the plasma are shown in Figure . The results showed that the main enrichment pathways for differential metabolites included cocaine addiction, amphetamine addiction, alcoholism, Parkinson's disease, tyrosine metabolism, prolactin signalling pathway and dopaminergic synapse. Among them, cocaine addiction and amphetamine addiction had the smallest p ‐value and the highest significance, and tyrosine metabolism had the most enriched metabolites. 3.4 Relevance analysis In order to gain a deeper understanding of the correlation between pharmacodynamic changes and metabolic changes, Pearson correlation analysis was conducted, revealing a significant association. The comprehensive correlation matrix presented in Figure revealed a suite of robust correlations. The concentrations of DA and 5‐HT exhibited positive relationships with D‐alanyl‐D‐alanine, pregnenolone, histidine, 4‐(beta‐acetylaminoethyl) imidazole, cytidine 5′‐diphosphocholine, 4‐aminobenzoic acid, dopamine and 5′‐methylthioadenosine and inverse correlations with homoarginine, lactose and tauroursodeoxycholic acid, and so does 5‐HT1AR. The ethology indicators of CPP and spontaneous activity were negatively correlated with trimethylamine N‐oxide and 4‐guanidinobutyric acid. These findings underscore the intricate network of biochemical interactions implicated in pharmacological responses and metabolic processes.
Analysis of NBDC chemical components in vivo and in vitro using UPLC‐Q‐Orbitrap‐MS 3.1.1 PCA The TIC of the plasma samples in the blank, model and drug (high‐dose) group in positive and negative ion mode are shown in Figure . The mass spectrometry detection data of NB capsules, blank plasma group, drug‐containing plasma group and QC sample group were imported into SIMCA software and analysed by PCA, which showed that the QC samples clustered well together, indicating good instrument stability and reliable data results (Figure ). 3.1.2 PLS‐DA PLS‐DA was applied to investigate the changes in plasma metabolites in the blank group and drug‐containing group. The PLS‐DA score plots were generated based on the metabolites detected in positive and negative ion modes (Figure ). The blank group and the drug‐containing group were separated on both sides, proving significant differences in the chemical composition of the two groups of samples. The value of R2Y was 1.0, and Q2 was 0.891 in positive ion mode. In negative ion mode, the value of R2Y was 1.0 and Q2 was 0.849. The permutation tests for PLS‐DA models are shown in Figure . The above data prove that the model is stable and reliable with good prediction ability. 3.1.3 Orthogonal projections to latent structures analysis (OPLS‐DA) OPLS‐DA was applied to investigate the changes in plasma metabolites in the blank group and drug‐containing group. The OPLS‐DA score plots were generated based on the metabolites detected in positive and negative ion modes (Figure ). The blank and drug‐containing groups were distinguished, implying that the between‐group differences were more significant than the within‐group differences and that the model could be used to screen for differential chemical compounds between the two groups. The value of R2Y was 1.0, and Q2 was 0.851 in positive ion mode. In negative ion mode, the value of R2Y was 1.0, and Q2 was 0.808. The permutation tests for OPLS‐DA models are shown in Figure . The above data prove that the model is stable and reliable with good prediction ability. 3.1.4 Identification and analysis of absorbed components of NBDC A total of 258 components in NB capsules were identified or tentatively characterized, 154 in positive ion mode and 104 in negative ion mode. The difference compounds between the blank group and the drug‐containing group were screened with criteria that the value of FC was more than 2, the VIP value was more than 1 and the p ‐value was less than 0.05. Compared with NBDC compounds, 87 components of prototype compounds in plasma were identified, 57 in positive and 30 in negative ion modes. The constituents absorbed into blood were mainly derived from the Zhichuanwu, Zhicaowu, Yanhusuo, Gouteng, Renshen and Gancao and mostly belonged to alkaloids, flavonoids and saponosides shown in Figure . The compound‐specific information is shown in Table .
PCA The TIC of the plasma samples in the blank, model and drug (high‐dose) group in positive and negative ion mode are shown in Figure . The mass spectrometry detection data of NB capsules, blank plasma group, drug‐containing plasma group and QC sample group were imported into SIMCA software and analysed by PCA, which showed that the QC samples clustered well together, indicating good instrument stability and reliable data results (Figure ).
PLS‐DA PLS‐DA was applied to investigate the changes in plasma metabolites in the blank group and drug‐containing group. The PLS‐DA score plots were generated based on the metabolites detected in positive and negative ion modes (Figure ). The blank group and the drug‐containing group were separated on both sides, proving significant differences in the chemical composition of the two groups of samples. The value of R2Y was 1.0, and Q2 was 0.891 in positive ion mode. In negative ion mode, the value of R2Y was 1.0 and Q2 was 0.849. The permutation tests for PLS‐DA models are shown in Figure . The above data prove that the model is stable and reliable with good prediction ability.
Orthogonal projections to latent structures analysis (OPLS‐DA) OPLS‐DA was applied to investigate the changes in plasma metabolites in the blank group and drug‐containing group. The OPLS‐DA score plots were generated based on the metabolites detected in positive and negative ion modes (Figure ). The blank and drug‐containing groups were distinguished, implying that the between‐group differences were more significant than the within‐group differences and that the model could be used to screen for differential chemical compounds between the two groups. The value of R2Y was 1.0, and Q2 was 0.851 in positive ion mode. In negative ion mode, the value of R2Y was 1.0, and Q2 was 0.808. The permutation tests for OPLS‐DA models are shown in Figure . The above data prove that the model is stable and reliable with good prediction ability.
Identification and analysis of absorbed components of NBDC A total of 258 components in NB capsules were identified or tentatively characterized, 154 in positive ion mode and 104 in negative ion mode. The difference compounds between the blank group and the drug‐containing group were screened with criteria that the value of FC was more than 2, the VIP value was more than 1 and the p ‐value was less than 0.05. Compared with NBDC compounds, 87 components of prototype compounds in plasma were identified, 57 in positive and 30 in negative ion modes. The constituents absorbed into blood were mainly derived from the Zhichuanwu, Zhicaowu, Yanhusuo, Gouteng, Renshen and Gancao and mostly belonged to alkaloids, flavonoids and saponosides shown in Figure . The compound‐specific information is shown in Table .
Effect of NBDC on MA‐addicted rats 3.2.1 Effect on body weight Compared to the blank group, the model group of rats demonstrated a significant reduction in body weight ( p < 0.05). In contrast, both the medium and high dose groups, as well as the positive drug group, exhibited increased body weights relative to the model group ( p < 0.05). These results suggest that NBDC can increase the body weight of MA‐induced rats. The results are shown in Table . 3.2.2 Effect on ethology The result of ethology is shown in Table and Figure . An elevation in the CPP score was evident in the model group relative to the blank group ( p < 0.01), indicating the development of a position‐specific conditioned preference by the rats toward the drug‐paired chamber. This confirms the successful establishment of the MA‐induced rat model. Similarly, the number of spontaneous activities and the score of stereotyped behaviour increased in the model group compared with the blank group ( p < 0.01). Subsequent treatment with NBDC or risperidone led to a significant reduction in three behavioural parameters, with trends toward normalization to levels observed in the blank group ( p < 0.05). Conversely, the low‐dose group showed no significant change in CPP scores compared to the model group ( p > 0.05). Furthermore, the CPP score was found to be lower in the positive control group compared to the high‐dose group. Collectively, these outcomes suggest that high‐dose NBDC effectively mitigates MA‐induced CPP in rats, demonstrating a superior efficacy profile to risperidone. 3.2.3 Effect on the concentration of DA and 5‐HT in serum DA and 5‐HT are common biomarkers in addiction to MA. Figure shows the alterations in serum concentrations of DA and 5‐HT in rats before and after modelling and drug administration. Compared to the blank group, the model group exhibited a significant increase in both DA and 5‐HT levels ( p < 0.05). When compared with the model group, the DA levels were higher in the medium‐dose, high‐dose and positive groups ( p < 0.05), whereas the high‐dose group showed an increase in 5‐HT levels ( p < 0.05), and the positive control group demonstrated a decrease in 5‐HT levels ( p < 0.05). 3.2.4 Effect on the expression of DRD1 and 5‐HT1AR in the hippocampus To delineate the impact of NBDC on the dopaminergic and serotonergic systems within the hippocampus, western blot (WB) assays and immunohistochemistry (IHC) staining techniques were employed to quantify the protein levels of dopamine receptor D1 (DRD1) and serotonin receptor 1A (5‐HT1AR), respectively. The findings from both methodologies are concordant, as depicted in Figure . MA exposure led to a significant downregulation of DRD1 levels relative to the blank group ( p < 0.01). Post‐treatment with NBDC or risperidone, there was a notable restoration of DRD1 protein expression compared to the model group ( p < 0.05). Conversely, MA engendered an upregulation of 5‐HT1AR protein expression compared with the blank group ( p < 0.05), an effect which also appeared in the NBDC treatment group compared with the model group ( p < 0.05). No discernible variation in 5‐HT1AR receptor expression was observed between the positive group and the model group ( p > 0.05). 3.2.5 Effect on cells morphological changes in the hippocampus The morphological alterations induced by MA within hippocampal cells upon exposure were examined using phase‐contrast microscopy to assess the therapeutic effects of NBDC. Microscopic observation revealed that rats administered with MA exhibited distinct histopathological disruptions, characterized by the disarray of pyramidal cells, intensified nuclear staining and a decline in the quantity of intact neurons, among other cellular anomalies. The hippocampal cell morphology in animals treated with NBDC progressively regained normalcy, as illustrated in Figure . This suggests that NBDC possesses potential neurorestorative properties capable of mitigating the deleterious effects of MA on hippocampal architecture.
Effect on body weight Compared to the blank group, the model group of rats demonstrated a significant reduction in body weight ( p < 0.05). In contrast, both the medium and high dose groups, as well as the positive drug group, exhibited increased body weights relative to the model group ( p < 0.05). These results suggest that NBDC can increase the body weight of MA‐induced rats. The results are shown in Table .
Effect on ethology The result of ethology is shown in Table and Figure . An elevation in the CPP score was evident in the model group relative to the blank group ( p < 0.01), indicating the development of a position‐specific conditioned preference by the rats toward the drug‐paired chamber. This confirms the successful establishment of the MA‐induced rat model. Similarly, the number of spontaneous activities and the score of stereotyped behaviour increased in the model group compared with the blank group ( p < 0.01). Subsequent treatment with NBDC or risperidone led to a significant reduction in three behavioural parameters, with trends toward normalization to levels observed in the blank group ( p < 0.05). Conversely, the low‐dose group showed no significant change in CPP scores compared to the model group ( p > 0.05). Furthermore, the CPP score was found to be lower in the positive control group compared to the high‐dose group. Collectively, these outcomes suggest that high‐dose NBDC effectively mitigates MA‐induced CPP in rats, demonstrating a superior efficacy profile to risperidone.
Effect on the concentration of DA and 5‐HT in serum DA and 5‐HT are common biomarkers in addiction to MA. Figure shows the alterations in serum concentrations of DA and 5‐HT in rats before and after modelling and drug administration. Compared to the blank group, the model group exhibited a significant increase in both DA and 5‐HT levels ( p < 0.05). When compared with the model group, the DA levels were higher in the medium‐dose, high‐dose and positive groups ( p < 0.05), whereas the high‐dose group showed an increase in 5‐HT levels ( p < 0.05), and the positive control group demonstrated a decrease in 5‐HT levels ( p < 0.05).
Effect on the expression of DRD1 and 5‐HT1AR in the hippocampus To delineate the impact of NBDC on the dopaminergic and serotonergic systems within the hippocampus, western blot (WB) assays and immunohistochemistry (IHC) staining techniques were employed to quantify the protein levels of dopamine receptor D1 (DRD1) and serotonin receptor 1A (5‐HT1AR), respectively. The findings from both methodologies are concordant, as depicted in Figure . MA exposure led to a significant downregulation of DRD1 levels relative to the blank group ( p < 0.01). Post‐treatment with NBDC or risperidone, there was a notable restoration of DRD1 protein expression compared to the model group ( p < 0.05). Conversely, MA engendered an upregulation of 5‐HT1AR protein expression compared with the blank group ( p < 0.05), an effect which also appeared in the NBDC treatment group compared with the model group ( p < 0.05). No discernible variation in 5‐HT1AR receptor expression was observed between the positive group and the model group ( p > 0.05).
Effect on cells morphological changes in the hippocampus The morphological alterations induced by MA within hippocampal cells upon exposure were examined using phase‐contrast microscopy to assess the therapeutic effects of NBDC. Microscopic observation revealed that rats administered with MA exhibited distinct histopathological disruptions, characterized by the disarray of pyramidal cells, intensified nuclear staining and a decline in the quantity of intact neurons, among other cellular anomalies. The hippocampal cell morphology in animals treated with NBDC progressively regained normalcy, as illustrated in Figure . This suggests that NBDC possesses potential neurorestorative properties capable of mitigating the deleterious effects of MA on hippocampal architecture.
Mechanism of NBDC relieving MA addiction based on metabolomics 3.3.1 Total ion chromatogram of metabolomics of plasma The TIC of the plasma samples in the blank, model and drug (high‐dose) groups in positive and negative ion modes are shown in Figure . After data preprocessing, comparing the RT and matching with HMDB databases, 614 and 525 compounds were identified from plasma samples in the positive and negative ion modes, respectively. 3.3.2 Analysis of differential metabolites and metabolic pathways in MA addiction Multivariate statistical analysis The metabolites in the plasma samples of the model and blank groups were analysed by using PCA, and the model and blank groups were clearly distinguished in the positive ion model (Figure ), indicating that the chemical composition of the samples in the two groups was significantly different. However, there was no significant difference between the two groups in negative ion mode (Figure ). In the PLS‐DA supervised model, the parameters of R2Y and Q2 were 1.0 and 0.706, respectively, in the positive ion mode and 1.0 and 0.436, respectively, in the negative ion mode. The parameters were R2Y = 1.0, Q2 = 0.586, and R2Y = 1.0, Q2 = 0.255, respectively, in positive and negative ion modes in the OPLS‐DA supervised model. The above data indicates that the model is steady and trusty with excellent predictive ability in the positive ion model (Figure ). The data of this experiment were statistically analysed using the data under the positive ion model. Differential metabolite screening Differential metabolites were screened by the VIP value of the OPLS‐DA model and the p ‐value of the t ‐test. Based on VIP > 1.0 and p < 0.05, 75 differential metabolites were screened between the model and the blank groups in the positive ion mode. A total of 19 metabolites were upregulated (FC > 1), and 56 metabolites were downregulated (FC < 1). The top 50 differential metabolites with VIP values were selected for hierarchical cluster analysis, with up‐regulation in red and down‐regulation in green (Figure ). Potential biomarker prediction The screened differential metabolites were subjected to functional analysis in HMDB and KEGG database. Finally, eight differential endogenous metabolites in the serum of MA‐induced rats were confirmed as potential biomarkers of MA addiction and are shown in Table . Compared with the blank group, the levels of anserine, histidine, pregnenolone and 3‐methylhistidine were increased. The levels of L‐dopa, 1,5‐anhydro‐D‐sorbitol, melibiose and norharman were decreased in the model group. KEGG pathway analysis To further explore the overall metabolic alterations during MA addiction, the data of screened differential metabolites were dealt with the MetaboAnalyst platform for enrichment analysis and pathway analysis, matching with multiple metabolic pathways. The potential MA addiction pathways by the KEGG pathway analysis in the plasma are shown in Figure . The results showed that the main enrichment pathways for differential metabolites included cocaine addiction, amphetamine addiction and alcoholism. Among them, histidine and tyrosine metabolism had the smallest p ‐value, the highest significance and the most enriched metabolites. 3.3.3 Analysis of differential metabolites and metabolic pathways in NBDC relieving effect on MA addiction Multivariate statistical analysis The metabolites in the model and drug groups' plasma samples were analysed by using PCA, PLS‐DA and OPLS‐DA. In the PCA unsupervised model, the model and drug groups were clearly distinguished in the positive ion model (Figure ) and the negative ion model (Figure ), indicating that the composition of metabolites in the rat with MA addiction has been varied. The PLS‐DA supervised model was steady and trusty, which can be confirmed by the parameters (R2Y = 1.0, Q2 = 0.903) based on the permutation test in the positive ion mode (Figure ). The OPLS‐DA supervised model was also steady and trusty, which can be confirmed by the parameters (R2Y = 1.0, Q2 = 0.916) based on the permutation test in the positive ion mode (Figure ). The above data proved that the model is steady and trusty with excellent predictive ability in the positive ion model. Differential metabolite screening Differential metabolites were screened by the VIP value of the OPLS‐DA model and the p ‐value of the t ‐test. Based on VIP > 1.0 and p < 0.05, 231 differential metabolites were screened in the positive ion mode between the drug and the model groups. A total of 156 metabolites were upregulated (FC > 1), and 75 metabolites were downregulated (FC < 1). The top 50 differential metabolites with the VIP value were selected for hierarchical cluster analysis, with up‐regulation in red and down‐regulation in green (Figure ). Potential biomarker prediction The screened differential metabolites were subjected to functional analysis in HMDB and KEGG database. Finally, 26 differential endogenous metabolites in the serum of MA‐induced rats were confirmed as potential biomarkers of MA addiction and shown in Table . Compared with the model group, the levels of 4‐(beta‐acetylaminoethyl) imidazole, norharman, cytidine 5′‐diphosphocholine, 4‐aminobenzoic acid, L‐tyrosine, L‐dopa, D‐alanyl‐D‐alanine, dopamine, all‐trans‐retinoic acid, L‐theanine, 4‐aminophenol, trimethylamine N‐oxide, pregnenolone, 3‐methylcrotonylglycine, 5′‐methylthioadenosine, 4‐guanidinobutyric acid, histidine, D‐tryptophan and diethanolamine were increased, and the levels of palmitoylcarnitine, isoleucine, nicotinamide, homoarginine, lactose, bilirubin and tauroursodeoxycholic acid were decreased in the drug group. KEGG pathway analysis The potential NBDC relieving MA addiction pathways by the KEGG pathway analysis in the plasma are shown in Figure . The results showed that the main enrichment pathways for differential metabolites included cocaine addiction, amphetamine addiction, alcoholism, Parkinson's disease, tyrosine metabolism, prolactin signalling pathway and dopaminergic synapse. Among them, cocaine addiction and amphetamine addiction had the smallest p ‐value and the highest significance, and tyrosine metabolism had the most enriched metabolites.
Total ion chromatogram of metabolomics of plasma The TIC of the plasma samples in the blank, model and drug (high‐dose) groups in positive and negative ion modes are shown in Figure . After data preprocessing, comparing the RT and matching with HMDB databases, 614 and 525 compounds were identified from plasma samples in the positive and negative ion modes, respectively.
Analysis of differential metabolites and metabolic pathways in MA addiction Multivariate statistical analysis The metabolites in the plasma samples of the model and blank groups were analysed by using PCA, and the model and blank groups were clearly distinguished in the positive ion model (Figure ), indicating that the chemical composition of the samples in the two groups was significantly different. However, there was no significant difference between the two groups in negative ion mode (Figure ). In the PLS‐DA supervised model, the parameters of R2Y and Q2 were 1.0 and 0.706, respectively, in the positive ion mode and 1.0 and 0.436, respectively, in the negative ion mode. The parameters were R2Y = 1.0, Q2 = 0.586, and R2Y = 1.0, Q2 = 0.255, respectively, in positive and negative ion modes in the OPLS‐DA supervised model. The above data indicates that the model is steady and trusty with excellent predictive ability in the positive ion model (Figure ). The data of this experiment were statistically analysed using the data under the positive ion model. Differential metabolite screening Differential metabolites were screened by the VIP value of the OPLS‐DA model and the p ‐value of the t ‐test. Based on VIP > 1.0 and p < 0.05, 75 differential metabolites were screened between the model and the blank groups in the positive ion mode. A total of 19 metabolites were upregulated (FC > 1), and 56 metabolites were downregulated (FC < 1). The top 50 differential metabolites with VIP values were selected for hierarchical cluster analysis, with up‐regulation in red and down‐regulation in green (Figure ). Potential biomarker prediction The screened differential metabolites were subjected to functional analysis in HMDB and KEGG database. Finally, eight differential endogenous metabolites in the serum of MA‐induced rats were confirmed as potential biomarkers of MA addiction and are shown in Table . Compared with the blank group, the levels of anserine, histidine, pregnenolone and 3‐methylhistidine were increased. The levels of L‐dopa, 1,5‐anhydro‐D‐sorbitol, melibiose and norharman were decreased in the model group. KEGG pathway analysis To further explore the overall metabolic alterations during MA addiction, the data of screened differential metabolites were dealt with the MetaboAnalyst platform for enrichment analysis and pathway analysis, matching with multiple metabolic pathways. The potential MA addiction pathways by the KEGG pathway analysis in the plasma are shown in Figure . The results showed that the main enrichment pathways for differential metabolites included cocaine addiction, amphetamine addiction and alcoholism. Among them, histidine and tyrosine metabolism had the smallest p ‐value, the highest significance and the most enriched metabolites.
The metabolites in the plasma samples of the model and blank groups were analysed by using PCA, and the model and blank groups were clearly distinguished in the positive ion model (Figure ), indicating that the chemical composition of the samples in the two groups was significantly different. However, there was no significant difference between the two groups in negative ion mode (Figure ). In the PLS‐DA supervised model, the parameters of R2Y and Q2 were 1.0 and 0.706, respectively, in the positive ion mode and 1.0 and 0.436, respectively, in the negative ion mode. The parameters were R2Y = 1.0, Q2 = 0.586, and R2Y = 1.0, Q2 = 0.255, respectively, in positive and negative ion modes in the OPLS‐DA supervised model. The above data indicates that the model is steady and trusty with excellent predictive ability in the positive ion model (Figure ). The data of this experiment were statistically analysed using the data under the positive ion model.
Differential metabolites were screened by the VIP value of the OPLS‐DA model and the p ‐value of the t ‐test. Based on VIP > 1.0 and p < 0.05, 75 differential metabolites were screened between the model and the blank groups in the positive ion mode. A total of 19 metabolites were upregulated (FC > 1), and 56 metabolites were downregulated (FC < 1). The top 50 differential metabolites with VIP values were selected for hierarchical cluster analysis, with up‐regulation in red and down‐regulation in green (Figure ).
The screened differential metabolites were subjected to functional analysis in HMDB and KEGG database. Finally, eight differential endogenous metabolites in the serum of MA‐induced rats were confirmed as potential biomarkers of MA addiction and are shown in Table . Compared with the blank group, the levels of anserine, histidine, pregnenolone and 3‐methylhistidine were increased. The levels of L‐dopa, 1,5‐anhydro‐D‐sorbitol, melibiose and norharman were decreased in the model group.
To further explore the overall metabolic alterations during MA addiction, the data of screened differential metabolites were dealt with the MetaboAnalyst platform for enrichment analysis and pathway analysis, matching with multiple metabolic pathways. The potential MA addiction pathways by the KEGG pathway analysis in the plasma are shown in Figure . The results showed that the main enrichment pathways for differential metabolites included cocaine addiction, amphetamine addiction and alcoholism. Among them, histidine and tyrosine metabolism had the smallest p ‐value, the highest significance and the most enriched metabolites.
Analysis of differential metabolites and metabolic pathways in NBDC relieving effect on MA addiction Multivariate statistical analysis The metabolites in the model and drug groups' plasma samples were analysed by using PCA, PLS‐DA and OPLS‐DA. In the PCA unsupervised model, the model and drug groups were clearly distinguished in the positive ion model (Figure ) and the negative ion model (Figure ), indicating that the composition of metabolites in the rat with MA addiction has been varied. The PLS‐DA supervised model was steady and trusty, which can be confirmed by the parameters (R2Y = 1.0, Q2 = 0.903) based on the permutation test in the positive ion mode (Figure ). The OPLS‐DA supervised model was also steady and trusty, which can be confirmed by the parameters (R2Y = 1.0, Q2 = 0.916) based on the permutation test in the positive ion mode (Figure ). The above data proved that the model is steady and trusty with excellent predictive ability in the positive ion model. Differential metabolite screening Differential metabolites were screened by the VIP value of the OPLS‐DA model and the p ‐value of the t ‐test. Based on VIP > 1.0 and p < 0.05, 231 differential metabolites were screened in the positive ion mode between the drug and the model groups. A total of 156 metabolites were upregulated (FC > 1), and 75 metabolites were downregulated (FC < 1). The top 50 differential metabolites with the VIP value were selected for hierarchical cluster analysis, with up‐regulation in red and down‐regulation in green (Figure ). Potential biomarker prediction The screened differential metabolites were subjected to functional analysis in HMDB and KEGG database. Finally, 26 differential endogenous metabolites in the serum of MA‐induced rats were confirmed as potential biomarkers of MA addiction and shown in Table . Compared with the model group, the levels of 4‐(beta‐acetylaminoethyl) imidazole, norharman, cytidine 5′‐diphosphocholine, 4‐aminobenzoic acid, L‐tyrosine, L‐dopa, D‐alanyl‐D‐alanine, dopamine, all‐trans‐retinoic acid, L‐theanine, 4‐aminophenol, trimethylamine N‐oxide, pregnenolone, 3‐methylcrotonylglycine, 5′‐methylthioadenosine, 4‐guanidinobutyric acid, histidine, D‐tryptophan and diethanolamine were increased, and the levels of palmitoylcarnitine, isoleucine, nicotinamide, homoarginine, lactose, bilirubin and tauroursodeoxycholic acid were decreased in the drug group. KEGG pathway analysis The potential NBDC relieving MA addiction pathways by the KEGG pathway analysis in the plasma are shown in Figure . The results showed that the main enrichment pathways for differential metabolites included cocaine addiction, amphetamine addiction, alcoholism, Parkinson's disease, tyrosine metabolism, prolactin signalling pathway and dopaminergic synapse. Among them, cocaine addiction and amphetamine addiction had the smallest p ‐value and the highest significance, and tyrosine metabolism had the most enriched metabolites.
The metabolites in the model and drug groups' plasma samples were analysed by using PCA, PLS‐DA and OPLS‐DA. In the PCA unsupervised model, the model and drug groups were clearly distinguished in the positive ion model (Figure ) and the negative ion model (Figure ), indicating that the composition of metabolites in the rat with MA addiction has been varied. The PLS‐DA supervised model was steady and trusty, which can be confirmed by the parameters (R2Y = 1.0, Q2 = 0.903) based on the permutation test in the positive ion mode (Figure ). The OPLS‐DA supervised model was also steady and trusty, which can be confirmed by the parameters (R2Y = 1.0, Q2 = 0.916) based on the permutation test in the positive ion mode (Figure ). The above data proved that the model is steady and trusty with excellent predictive ability in the positive ion model.
Differential metabolites were screened by the VIP value of the OPLS‐DA model and the p ‐value of the t ‐test. Based on VIP > 1.0 and p < 0.05, 231 differential metabolites were screened in the positive ion mode between the drug and the model groups. A total of 156 metabolites were upregulated (FC > 1), and 75 metabolites were downregulated (FC < 1). The top 50 differential metabolites with the VIP value were selected for hierarchical cluster analysis, with up‐regulation in red and down‐regulation in green (Figure ).
The screened differential metabolites were subjected to functional analysis in HMDB and KEGG database. Finally, 26 differential endogenous metabolites in the serum of MA‐induced rats were confirmed as potential biomarkers of MA addiction and shown in Table . Compared with the model group, the levels of 4‐(beta‐acetylaminoethyl) imidazole, norharman, cytidine 5′‐diphosphocholine, 4‐aminobenzoic acid, L‐tyrosine, L‐dopa, D‐alanyl‐D‐alanine, dopamine, all‐trans‐retinoic acid, L‐theanine, 4‐aminophenol, trimethylamine N‐oxide, pregnenolone, 3‐methylcrotonylglycine, 5′‐methylthioadenosine, 4‐guanidinobutyric acid, histidine, D‐tryptophan and diethanolamine were increased, and the levels of palmitoylcarnitine, isoleucine, nicotinamide, homoarginine, lactose, bilirubin and tauroursodeoxycholic acid were decreased in the drug group.
The potential NBDC relieving MA addiction pathways by the KEGG pathway analysis in the plasma are shown in Figure . The results showed that the main enrichment pathways for differential metabolites included cocaine addiction, amphetamine addiction, alcoholism, Parkinson's disease, tyrosine metabolism, prolactin signalling pathway and dopaminergic synapse. Among them, cocaine addiction and amphetamine addiction had the smallest p ‐value and the highest significance, and tyrosine metabolism had the most enriched metabolites.
Relevance analysis In order to gain a deeper understanding of the correlation between pharmacodynamic changes and metabolic changes, Pearson correlation analysis was conducted, revealing a significant association. The comprehensive correlation matrix presented in Figure revealed a suite of robust correlations. The concentrations of DA and 5‐HT exhibited positive relationships with D‐alanyl‐D‐alanine, pregnenolone, histidine, 4‐(beta‐acetylaminoethyl) imidazole, cytidine 5′‐diphosphocholine, 4‐aminobenzoic acid, dopamine and 5′‐methylthioadenosine and inverse correlations with homoarginine, lactose and tauroursodeoxycholic acid, and so does 5‐HT1AR. The ethology indicators of CPP and spontaneous activity were negatively correlated with trimethylamine N‐oxide and 4‐guanidinobutyric acid. These findings underscore the intricate network of biochemical interactions implicated in pharmacological responses and metabolic processes.
DISCUSSION The composition of Chinese medicine compounds is intricate, and the component absorbed into blood serves as the material basis for Chinese medicine to exert its medicinal effects and is also the key guarantee for the quality of Chinese medicine. , In this investigation, 87 prototype compounds in NBDC were detected in the plasma. The present author's preliminary literature review has revealed that components such as l‐tetrahydropalmatine, ginsenosides, rhynchophylline and astragaloside have shown promising effects in mitigating MA addiction. , These components have also been identified in NBDC, and they can serve as Q biomarkers for the QC of NBDC compound formulations. The CPP experiment, spontaneous locomotor activity experiment and stereotyped behaviour are currently the classical experimental models for evaluating psychiatric dependence on drugs. , MA promotes the release of monoamine neurotransmitters, increases extracellular monoamine neurotransmitter concentrations and produces excitatory effects. Therefore, monoamine neurotransmitters DA and 5‐HT are both classical biomarkers of MA addiction, and DA receptors and 5‐HT receptors are important targets for the treatment of MA addiction. This study found that NBDC could reduce the behaviour and psychiatric abnormalities induced by MA in rats in a dose‐related manner and NBDC also could increase DA and 5‐HT levels and correlative receptor expression. MA promotes the release of monoamine neurotransmitters, including DA and 5‐HT, from nerve terminals, thereby facilitating addiction via the reward system. MA withdrawal causes significant emotional distress as DA and 5‐HT are undergoing reductions. Increasing DA and 5‐HT levels can ease withdrawal symptoms. NBDC maintains the normal physiological state of the body by increasing DA and 5‐HT levels to improve the withdrawal syndrome such as depression and cognitive impairment caused by the decrease of neurotransmitter levels after acute withdrawal and to reduce the drug‐seeking cravings of users. The metabolomics profiling elucidated showed that seven prominent KEGG signalling pathways were intricately associated with the mechanisms of MA addiction and NBDC therapeutic interventions. These pathways encompassed cocaine addiction, amphetamine addiction, alcohol addiction, Parkinson's disease, tyrosine metabolism, prolactin signalling and dopaminergic synapses. Specifically, within the amphetamine addiction metabolic pathway, three key endogenous metabolites—L‐tyrosine, L‐dopa and dopamine—were quantitatively identified. Moreover, an in‐depth analysis of metabolite signatures revealed that five distinct endogenous substances were implicated in the histidine metabolic signalling pathway. This included histidine, anserine, histamine, 4‐(β‐acetylaminoethyl)imidazole (also recognized as N‐acetylhistamine) and N‐methyl‐L‐histidine (also known as 3‐methylhistidine). Histamine H1 and H2 receptors stimulate dopamine D1 and D2 receptors, thereby facilitating the release of dopamine. Conversely, the histamine H3 receptor exerts an inhibitory effect on dopamine synthesis. It is speculated that NBDC may enhance the histamine level in vivo by enhancing the ‘histidine → histamine → N‐acetylhistamine’ metabolic pathway, thereby promoting dopamine release and playing a role in intervening MA addiction. Neuroprotective effect of histamine H3 receptor blockade on MA‐induced cognitive impairment in mice. Metoprine increasing the content of histamine attenuates MA‐induced hyperlocomotion via activation of histaminergic neurotransmission in mice. L‐dopa, dopamine, histidine and histamine may serve as potential biomarkers of MA addiction, and histamine may serve as a potential action target for the treatment of MA addiction.
CONCLUSION In summary, NBDC ameliorates MA‐induced behavioural abnormalities and alleviates MA withdrawal syndrome by acting on DRD1 and 5‐HT1AR receptors and increasing neurotransmitter DA and 5‐HT levels. Alkaloid components (e.g. benzoylmesaconine, uncarine, tetrahydroberberine, corydaline and L‐tetrahydropalmatine) and saponin components (e.g. isoliquiritin, liquiritin, ginsenoside Rb3, ginsenoside Rb1 and licoricesaponin J2) were possibly the potential bioactive components of NBDC for relieving with MA addiction. Amphetamine addiction, tyrosine metabolism and dopaminergic synapse were possibly the critical metabolic pathways involved in alleviating MA addiction by NBDC. L‐dopa, dopamine, histidine and histamine may serve as potential biomarkers of MA addiction, and histamine may serve as a potential target in the treatment of MA addiction.
The authors declare that there are no conflicts of interest.
This research was conducted in accordance with the Wiley Best Practice Guidelines on Research Integrity and Publishing Ethics.
The experimental protocol involving these animals was ethically reviewed and approved in accordance with internationally recognized guidelines for the care and use of laboratory animals, with the Ethics Approval Number 2021‐0098.
Bin Zhang is responsible for designing experimental protocols, executing experimental plans, processing data results and writing papers. Chen Yang and Zheng Yuxiao Zheng are responsible for executing the experiments. Xinliang Li is responsible for guiding the experiments. Xingguo Wang is responsible for providing the drug. Yuehui Li is responsible for formulating overarching research goals and aims.
Data S1. Supporting Information.
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Trends in Psychiatrist-Led Care for Medicare Part B Enrollees | d66c4a67-fc89-459c-8212-225d0509951f | 11803478 | Psychiatry[mh] | As the primary insurer of older US adults as well as an important insurer for many individuals with disabilities (including many aged <65 years with disability due to mental illness), Medicare reached 62.6 million enrollees in 2021. , , More than half (35.6 million) of these individuals were enrolled in traditional Medicare (in which the government pays practitioners directly on a fee-for-service model); the remainder were enrolled in Medicare Advantage (in which care is contracted by the Medicare program to private managed care organizations). Many of these older adults and individuals with disabilities have mental health and substance use disorders. Adverse outcomes from behavioral health crises are rising among older adults, with deaths due to overdose quadrupling in the past 2 decades. These adverse outcomes may be related to gaps in access to timely care; for instance, less than half (45%) of adults aged 50 years or older who needed treatment for opioid use disorder in the past year received any treatment. , Indeed, national survey data suggest that less than 60% of office-based psychiatrists accept insurance of any kind, let alone government-sponsored insurance such as Medicare. , This is a critical issue for Medicare, given the nontrivial price elasticity of demand for mental health services. Understanding the size of the workforce serving older adults and individuals with disabilities is critical to guide policy that may influence the behavioral health care workforce pipeline. For decades after its creation in 1965, Medicare was not a major payer in US mental health care. Notably, traditional Medicare Part B (which covers outpatient care and many physician services during inpatient care) required enrollees to pay 50% of care costs vs only 20% for other covered services, and it also capped the annual benefit for outpatient mental health care at $250 (50% of $500). This benefit cap was raised to $1100 in 1987, and then removed entirely in 1989. Importantly, the Medicare Improvement for Patients and Providers Act of 2008 began aligning enrollees’ copay for Medicare Part B mental health coverage with that for other types of care, reaching parity (ie, 20% paid by the enrollee and 80% paid by Medicare) in 2014. Some evidence indicates this increased enrollees’ access to mental health services, but whether it has changed psychiatrists’ participation in Part B is unknown. In recent years, Medicare’s Welcome to Medicare initial examination has included screenings for depression and alcohol use disorder, which presumably might lead to more referrals to specialist care. Medicare Part B helps to pay for this visit, and nearly all other psychiatric services, for traditional Medicare enrollees seeking access to mental health care. Although the number of professionally active psychiatrists has increased in recent years since reimbursement parity was met and the number of medical school graduates matching into psychiatry has increased for 13 consecutive years, the number and proportion of psychiatrists who choose to serve traditional Medicare enrollees has received little study. Accordingly, this repeated cross-sectional study aimed to evaluate how the number of psychiatrists providing professional services to adults on traditional Medicare Part B has changed over time, both relative to all active psychiatrists and relative to the number of adults covered by traditional Medicare Part B. Assessing psychiatrist numbers relative to the number of traditional Medicare enrollees is important because as Medicare Advantage has grown in popularity, enrollment in traditional Medicare has declined even as the program overall has expanded. To accomplish our study aims, we characterized and compared recent trends in the number of Medicare Part B enrollees and number of Medicare Part B–serving psychiatrists in the US from 2014 to 2022. We analyzed changes in the number of Medicare-serving psychiatrists and traditional Medicare enrollees nationwide, by state, and by geographic region over this period to understand variations in the growth rates of active psychiatrists, traditional Medicare enrollees, and the number of psychiatrists per Medicare enrollee. We bypassed response bias in practitioner survey data by directly examining claims filed by psychiatrists to traditional Medicare over this time period, combining 3 national datasets in an approach readily applicable by health services researchers in other specialties. This approach allowed us to assess whether the recent growth of psychiatrists entering residency , has translated into growth in traditional Medicare Part B–accepting psychiatrists.
Institutional Approval and Participant Consent This cross-sectional study was based on publicly available information in accordance with 45 CFR §46 and thus did not require institutional review board approval. Informed consent was not required because no patient-level data were collected. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. Data Sources and Study Population To determine the number of psychiatrists accepting Medicare by state and year, we used the Centers for Medicare & Medicaid Services (CMS) Medicare Physician & Other Practitioners dataset files (for January 1, 2014, through December 31, 2022). This dataset includes all clinicians submitting more than 10 claims in a year for Medicare Part B with data on the location of the physician rendering services to Medicare. Medicare Part B is of particular interest because it encompasses fees from services rendered by psychiatrists across the mental health care continuum, from outpatient care to partial hospitalization programs to inpatient hospitalizations. From this dataset, we selected physicians as indicated by specialty and medical degree (MD, DO, MBBS, etc), selecting for psychiatrists using the taxonomy codes in eTable 1 in . We excluded physician assistants, nurse practitioners, and other advanced practice clinicians from this analysis, as well as practitioners who provided services exclusively outside the 50 US states and District of Columbia. We also excluded enrollees from outside of these areas of interest from our analysis. To compare the numbers of psychiatrists submitting claims to traditional Medicare Part B and the number of traditional Medicare Part B enrollees in each state, we used the Medicare Monthly Enrollment database to obtain the number of traditional Medicare Part B person-years insured nationally and by state (including the District of Columbia) for the years 2014 to 2022; this person-year methodology allowed us to account for changes in a Medicare enrollee’s insurance status over time (eg, an enrollee who switched to Medicare Advantage on June 30 during a given year would count as 0.5 insured traditional Medicare Part B person-years rather than a full traditional Medicare Part B enrollee). For the purposes of this study, an insured person-year was counted as an enrollee. Supplementary eligibility data were gathered from the CMS Program Statistics–Original Medicare Enrollment dataset. Total Active Psychiatrists To determine a denominator for the proportion of professionally active psychiatrists accepting traditional Medicare, we queried data on professionally active psychiatrists from state-level data available on the Kaiser Family Foundation website for the years 2014 to 2022, which synthesizes active professional email and state licensing data. Data on professionally active psychiatrists for years prior to 2022 were no longer available on the Kaiser Family Foundation website at the time of our analysis; to retrieve these data, we used the Internet Archive Wayback Machine to access time- and date-stamped web crawls of these deleted pages. Study Outcomes First, we collated state-level data by regions identified by the US Census Bureau. For each year, we calculated the number of psychiatrists per 100 000 traditional Medicare Part B enrollees by state, region, and nationally. We further calculated the compound annual growth rate (CAGR) for psychiatrists per 100 000 Medicare enrollees for each state, region, and nationally between 2014 and 2022, alongside values for percentages of practitioner growth and Medicare population growth. We repeated these calculations by state. Finally, we calculated the proportion of active psychiatrists submitting claims to traditional Medicare Part B nationally, regionally, and by state. Statistical Analysis Descriptive statistical analyses were performed on national, regional, and state levels to determine the number of psychiatrists billing traditional Medicare Part B. We reported these statistics on an absolute, per–professionally active psychiatrist, and per-enrollee basis. The significance of the trend in the number of active psychiatrists billing Medicare Part B over time was assessed using univariable linear regression. We performed additional difference-in-differences analysis to assess for any effect of statewide Medicare Advantage coverage rates at the end of our study period on the change in the proportion of statewide professionally active psychiatrists billing Medicare. All tests were 2-tailed with significance set at P < .05. Stata, version 17.0 (StataCorp LLC) and Python, version 3.1 (Python Software Foundation) were used for all analyses and figure creation.
This cross-sectional study was based on publicly available information in accordance with 45 CFR §46 and thus did not require institutional review board approval. Informed consent was not required because no patient-level data were collected. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline.
To determine the number of psychiatrists accepting Medicare by state and year, we used the Centers for Medicare & Medicaid Services (CMS) Medicare Physician & Other Practitioners dataset files (for January 1, 2014, through December 31, 2022). This dataset includes all clinicians submitting more than 10 claims in a year for Medicare Part B with data on the location of the physician rendering services to Medicare. Medicare Part B is of particular interest because it encompasses fees from services rendered by psychiatrists across the mental health care continuum, from outpatient care to partial hospitalization programs to inpatient hospitalizations. From this dataset, we selected physicians as indicated by specialty and medical degree (MD, DO, MBBS, etc), selecting for psychiatrists using the taxonomy codes in eTable 1 in . We excluded physician assistants, nurse practitioners, and other advanced practice clinicians from this analysis, as well as practitioners who provided services exclusively outside the 50 US states and District of Columbia. We also excluded enrollees from outside of these areas of interest from our analysis. To compare the numbers of psychiatrists submitting claims to traditional Medicare Part B and the number of traditional Medicare Part B enrollees in each state, we used the Medicare Monthly Enrollment database to obtain the number of traditional Medicare Part B person-years insured nationally and by state (including the District of Columbia) for the years 2014 to 2022; this person-year methodology allowed us to account for changes in a Medicare enrollee’s insurance status over time (eg, an enrollee who switched to Medicare Advantage on June 30 during a given year would count as 0.5 insured traditional Medicare Part B person-years rather than a full traditional Medicare Part B enrollee). For the purposes of this study, an insured person-year was counted as an enrollee. Supplementary eligibility data were gathered from the CMS Program Statistics–Original Medicare Enrollment dataset.
To determine a denominator for the proportion of professionally active psychiatrists accepting traditional Medicare, we queried data on professionally active psychiatrists from state-level data available on the Kaiser Family Foundation website for the years 2014 to 2022, which synthesizes active professional email and state licensing data. Data on professionally active psychiatrists for years prior to 2022 were no longer available on the Kaiser Family Foundation website at the time of our analysis; to retrieve these data, we used the Internet Archive Wayback Machine to access time- and date-stamped web crawls of these deleted pages.
First, we collated state-level data by regions identified by the US Census Bureau. For each year, we calculated the number of psychiatrists per 100 000 traditional Medicare Part B enrollees by state, region, and nationally. We further calculated the compound annual growth rate (CAGR) for psychiatrists per 100 000 Medicare enrollees for each state, region, and nationally between 2014 and 2022, alongside values for percentages of practitioner growth and Medicare population growth. We repeated these calculations by state. Finally, we calculated the proportion of active psychiatrists submitting claims to traditional Medicare Part B nationally, regionally, and by state.
Descriptive statistical analyses were performed on national, regional, and state levels to determine the number of psychiatrists billing traditional Medicare Part B. We reported these statistics on an absolute, per–professionally active psychiatrist, and per-enrollee basis. The significance of the trend in the number of active psychiatrists billing Medicare Part B over time was assessed using univariable linear regression. We performed additional difference-in-differences analysis to assess for any effect of statewide Medicare Advantage coverage rates at the end of our study period on the change in the proportion of statewide professionally active psychiatrists billing Medicare. All tests were 2-tailed with significance set at P < .05. Stata, version 17.0 (StataCorp LLC) and Python, version 3.1 (Python Software Foundation) were used for all analyses and figure creation.
Baseline and End Point Study Sample Our patient study sample consisted of all traditional Medicare Part B enrollees in all 50 states and the District of Columbia, comprising 33 042 936 person-years in 2014 (5 800 903 [17.6%] eligible due to disability alone and 27 242 030 [82.4%] eligible due to age) and 29 544 994 person-years in 2022 ( ). Our physician study sample included all professionally active psychiatrists, comprising 50 416 in 2014 and 56 492 in 2022. Absolute and Per-Professional Changes in Medicare Part B–Serving Psychiatrists and Medicare Enrollment From 2014 to 2022, traditional Medicare Part B enrollment declined by 10.6% (from 33 042 936 enrollee-years in 2014 to 29 544 994 enrollee-years in 2022, a net loss of 3 497 942 enrollee-years). Changes in Medicare Part B enrollment varied by geographic region over the study period ( ): Enrollment decreased 15.2% in the Midwest (from 7 609 269 enrollee-years in 2014 to 6 455 740 enrollee-years in 2022, a loss of 1 153 529 enrollee-years), 12.0% in the Northeast (from 6 084 288 to 5 352 345 enrollee-years, a loss of 731 943 enrollee-years), and 13.3% in the South (from 13 167 225 to 11 416 127 enrollee-years, a loss of 1 751 908 enrollee-years), whereas it increased by 2.2% in the West (from 6 182 154 to 6 320 782 enrollee-years, a gain of 138 628 enrollee-years). Although the absolute number of active psychiatrists increased by 12.1% nationwide from 2014 to 2022 (from 50 416 to 56 492, a net gain of 6076 psychiatrists) and increased in 48 of the 50 states and 1 federal district assessed, the nationwide number of professionally active psychiatrists submitting professional services claims to Medicare Part B declined by 16.8% (from 22 409 to 18 637 psychiatrists, a net loss of 3772 psychiatrists) nationwide over this period. This occurred alongside a decrease in the proportion of active psychiatrists submitting professional services claims to traditional Medicare Part B (from 22 409 of 50 416 active psychiatrists [44.4%] in 2014 to 18 637 of 56 492 active psychiatrists [33.0%] in 2022; β = −1.4%, P < .001) ( ) and declined in all states and the District of Columbia. This decline in the proportion of active psychiatrists submitting claims to traditional Medicare Part B was significant even before the COVID-19 pandemic (from 22 409 of 50 416 [44.4%] in 2014 to 21 798 of 54 935 [39.7%] in 2019; β = −0.9%, P = .005). The absolute number of psychiatrists submitting professional services claims to Medicare Part B during this period decreased by 18.8% in the Midwest, 19.1% in the Northeast, 15.7% in the South, and 12.7% in the West. Per-Enrollee Changes in Medicare Part B–Serving Psychiatrists The overall number of traditional Medicare Part B–serving psychiatrists per 100 000 Medicare enrollees decreased from 67.8 in 2014 to 63.1 in 2022 (eTable 2 in ). In the Midwest, there were 63.9 psychiatrists per 100 000 Medicare Part B enrollees in 2014, falling to 61.2 per 100 000 enrollees in 2022. In the Northeast, there were 108.8 psychiatrists per 100 000 Medicare Part B enrollees in 2014, which decreased to 100.0 enrollees in 2022. In the South, there were 52.4 psychiatrists per 100 000 enrollees in 2014, which decreased to 50.9 per 100 000 enrollees in 2022. Finally, in the West, there were 65.3 psychiatrists per 100 000 enrollees in 2014, falling to 55.7 per 100 000 enrollees in 2022. Throughout this period, the Northeast was the only region consistently above the national average in Medicare Part B–serving psychiatrists per capita. Variation in State-Level Participation Rates In 2022, the highest numbers of traditional Medicare Part B–serving psychiatrists per 100 000 Medicare enrollees were in Rhode Island at 174.7, the District of Columbia at 163.7, and Connecticut at 126.9 ( A and eTable 3 in ). The lowest numbers of Medicare Part B–serving psychiatrists per 100 000 enrollees during that year were in Wyoming at 13.8, Mississippi at 22.1, and Montana at 27.4; Wyoming had less than one-tenth the per-enrollee Medicare-serving psychiatrists than the District of Columbia and Rhode Island. Between 2014 and 2022, the state with the greatest decrease in per-enrollee psychiatrists was also Wyoming, with a reduction of 67.8% (from 42.9 to 13.8 active psychiatrists per 100 000 enrollees; CAGR, −13.2%) ( B). The state with the largest increase in per-enrollee psychiatrists from 2014 to 2022 was Alabama, with an increase of 31.7% (from 36.5 to 48.1 active psychiatrists per 100 000 enrollees; CAGR, 3.5%). From 2014 to 2022, the number of traditional Medicare Part B–serving psychiatrists per enrollee decreased for 36 of the 50 states and 1 federal district assessed. In every state and federal district assessed, the percentage of active psychiatrists billing Medicare Part B for professional services decreased from 2014 to 2022 ( C). The 10 states with the highest proportion of Medicare Advantage enrollees among those enrolled in Medicare in 2021, the year with most recent available total Medicare enrollment data (Minnesota, Michigan, Rhode Island, Florida, Alabama, Hawaii, Wisconsin, Oregon, Ohio, and Connecticut) had declines in their proportion of traditional Medicare Part B–serving psychiatrists (mean [SD] decrease, 27.2% [5.5%]), similar to the 9 states and 1 federal district with the lowest proportion of Medicare Advantage enrollees (Alaska, Wyoming, Maryland, Vermont, North Dakota, Montana, Delaware, Nebraska, District of Columbia, and Kansas; mean [SD] decrease, 34.7% [14.0%]; P = .55 for interaction term of group and time).
Our patient study sample consisted of all traditional Medicare Part B enrollees in all 50 states and the District of Columbia, comprising 33 042 936 person-years in 2014 (5 800 903 [17.6%] eligible due to disability alone and 27 242 030 [82.4%] eligible due to age) and 29 544 994 person-years in 2022 ( ). Our physician study sample included all professionally active psychiatrists, comprising 50 416 in 2014 and 56 492 in 2022.
From 2014 to 2022, traditional Medicare Part B enrollment declined by 10.6% (from 33 042 936 enrollee-years in 2014 to 29 544 994 enrollee-years in 2022, a net loss of 3 497 942 enrollee-years). Changes in Medicare Part B enrollment varied by geographic region over the study period ( ): Enrollment decreased 15.2% in the Midwest (from 7 609 269 enrollee-years in 2014 to 6 455 740 enrollee-years in 2022, a loss of 1 153 529 enrollee-years), 12.0% in the Northeast (from 6 084 288 to 5 352 345 enrollee-years, a loss of 731 943 enrollee-years), and 13.3% in the South (from 13 167 225 to 11 416 127 enrollee-years, a loss of 1 751 908 enrollee-years), whereas it increased by 2.2% in the West (from 6 182 154 to 6 320 782 enrollee-years, a gain of 138 628 enrollee-years). Although the absolute number of active psychiatrists increased by 12.1% nationwide from 2014 to 2022 (from 50 416 to 56 492, a net gain of 6076 psychiatrists) and increased in 48 of the 50 states and 1 federal district assessed, the nationwide number of professionally active psychiatrists submitting professional services claims to Medicare Part B declined by 16.8% (from 22 409 to 18 637 psychiatrists, a net loss of 3772 psychiatrists) nationwide over this period. This occurred alongside a decrease in the proportion of active psychiatrists submitting professional services claims to traditional Medicare Part B (from 22 409 of 50 416 active psychiatrists [44.4%] in 2014 to 18 637 of 56 492 active psychiatrists [33.0%] in 2022; β = −1.4%, P < .001) ( ) and declined in all states and the District of Columbia. This decline in the proportion of active psychiatrists submitting claims to traditional Medicare Part B was significant even before the COVID-19 pandemic (from 22 409 of 50 416 [44.4%] in 2014 to 21 798 of 54 935 [39.7%] in 2019; β = −0.9%, P = .005). The absolute number of psychiatrists submitting professional services claims to Medicare Part B during this period decreased by 18.8% in the Midwest, 19.1% in the Northeast, 15.7% in the South, and 12.7% in the West.
The overall number of traditional Medicare Part B–serving psychiatrists per 100 000 Medicare enrollees decreased from 67.8 in 2014 to 63.1 in 2022 (eTable 2 in ). In the Midwest, there were 63.9 psychiatrists per 100 000 Medicare Part B enrollees in 2014, falling to 61.2 per 100 000 enrollees in 2022. In the Northeast, there were 108.8 psychiatrists per 100 000 Medicare Part B enrollees in 2014, which decreased to 100.0 enrollees in 2022. In the South, there were 52.4 psychiatrists per 100 000 enrollees in 2014, which decreased to 50.9 per 100 000 enrollees in 2022. Finally, in the West, there were 65.3 psychiatrists per 100 000 enrollees in 2014, falling to 55.7 per 100 000 enrollees in 2022. Throughout this period, the Northeast was the only region consistently above the national average in Medicare Part B–serving psychiatrists per capita.
In 2022, the highest numbers of traditional Medicare Part B–serving psychiatrists per 100 000 Medicare enrollees were in Rhode Island at 174.7, the District of Columbia at 163.7, and Connecticut at 126.9 ( A and eTable 3 in ). The lowest numbers of Medicare Part B–serving psychiatrists per 100 000 enrollees during that year were in Wyoming at 13.8, Mississippi at 22.1, and Montana at 27.4; Wyoming had less than one-tenth the per-enrollee Medicare-serving psychiatrists than the District of Columbia and Rhode Island. Between 2014 and 2022, the state with the greatest decrease in per-enrollee psychiatrists was also Wyoming, with a reduction of 67.8% (from 42.9 to 13.8 active psychiatrists per 100 000 enrollees; CAGR, −13.2%) ( B). The state with the largest increase in per-enrollee psychiatrists from 2014 to 2022 was Alabama, with an increase of 31.7% (from 36.5 to 48.1 active psychiatrists per 100 000 enrollees; CAGR, 3.5%). From 2014 to 2022, the number of traditional Medicare Part B–serving psychiatrists per enrollee decreased for 36 of the 50 states and 1 federal district assessed. In every state and federal district assessed, the percentage of active psychiatrists billing Medicare Part B for professional services decreased from 2014 to 2022 ( C). The 10 states with the highest proportion of Medicare Advantage enrollees among those enrolled in Medicare in 2021, the year with most recent available total Medicare enrollment data (Minnesota, Michigan, Rhode Island, Florida, Alabama, Hawaii, Wisconsin, Oregon, Ohio, and Connecticut) had declines in their proportion of traditional Medicare Part B–serving psychiatrists (mean [SD] decrease, 27.2% [5.5%]), similar to the 9 states and 1 federal district with the lowest proportion of Medicare Advantage enrollees (Alaska, Wyoming, Maryland, Vermont, North Dakota, Montana, Delaware, Nebraska, District of Columbia, and Kansas; mean [SD] decrease, 34.7% [14.0%]; P = .55 for interaction term of group and time).
In this study, we observed a 16.8% decrease in the number of psychiatrists (loss of 3772) billing traditional Medicare for professional services from 2014 to 2022, a period in which the number of professionally active psychiatrists in the US increased by 12.1% (gain of 6076). In this study, there was a per-enrollee decline in Medicare Part B–accepting psychiatrists across every region across the US, despite a more than decade-long increase in the number of medical students entering training to become psychiatrists each year. These findings of decreasing numbers of psychiatrists serving Medicare Part B enrollees despite increasing numbers of these active professionals have, to our knowledge, not been documented for any other medical specialty. Our results suggest a need for further serious study of (1) potentially long-term diminishing access to psychiatric care for a growing and vulnerable patient population and (2) increased strain placed on the remaining practitioners that accept traditional Medicare. It appears that efforts to increase the psychiatric workforce have not translated to an increase in accessible care for some of the most vulnerable in the US, even as behavioral health crises in this population continue to rise ; although the number of professionally active psychiatrists increased by 6076 over the study period, the number submitting more than 10 claims to Medicare Part B for professional services shrank by 3772 psychiatrists during this time. Although one might assume that an increasing psychiatric workforce begets increased access to psychiatric care, our findings suggest that this may not the case for those relying on traditional Medicare to cover costs rather than cash pay or through enrollment in a privately managed Medicare Advantage plan. It may be that the US is entering a period of “paucity in the land of plenty,” where an increased number of psychiatrists does not translate to equitable availability of psychiatrist-led care. More work is needed to determine whether this longitudinal decline in the proportion of psychiatrists billing traditional Medicare has translated into a difference in the proportion of total Medicare enrollees receiving timely and warranted mental health care. This would require data on Medicare Advantage plans, which serve a similar population but are harder to evaluate because much of their data are proprietary rather than public. Psychiatrists demonstrate limited acceptance for insurance in general and even less so for government-sponsored options. In fact, psychiatrists accept Medicare as well as other public and private insurance options at substantially lower rates than physicians of other specialties. , This barrier to care presents a challenge for a field of medicine in which (1) accessing care is particularly difficult and (2) those with the most severe illness are more likely to be treated by those accepting insurance, requiring longer and more frequent episodes of care. , , , We concur with the opinions of previous researchers that low acceptance of insurance among psychiatrists could be attributable to low reimbursements compared with other specialties, a protracted national shortage of psychiatrists enabling insurance-free practice due to nearly unlimited demand, and the regulatory and logistical hurdles of billing Medicare for solo practitioners. , , , Fewer psychiatrists participate in Medicare Part B each year, as observed in this study. The reasons for this decreased participation in Medicare Part B are likely multifactorial. Further work is warranted to study the causes of these trends, which appear not to be universal across other fields of medicine and appear unrelated to the traditional or Medicare Advantage coverage mix in a given state, to inform future policy ensuring not only an adequate but also an equitable supply of psychiatrists in terms of geography and the payer status of patients served. Our findings identify states that should command particular concern, states with the steepest declines in Medicare Part B–serving psychiatrists per enrollee, with decreases that suggest potentially drastic losses in access to psychiatric care. These cases may warrant closer investigation as to the current availability of psychiatric care and root causes of such declines, as well as corrective state-level policy action such as recruitment and retention incentives, creation of state-level behavioral health workforce development plans, or tuition reimbursement for those training to become behavioral health care specialists. Many of the states with the lowest (and highest) concentrations of psychiatrists per capita have comparatively low numbers of traditional Medicare Part B beneficiaries; thus, relatively modest increases in the numbers of practicing psychiatrists accepting traditional Part B in these states could have substantial effects on per-enrollee psychiatrist availability. Because mental health parity is now present in traditional Medicare Part B but is not mandated for Medicare Advantage plans (Part C), it would be optimistic to assume that shortages in psychiatric care under the former have been compensated for by expansions in coverage in the latter. A route to expanding mental health access across Medicare currently under discussion among legislators in Washington, DC, is to extend parity protections to Part C, which could help older adults and individuals with disabilities to have access to psychiatric care regardless of which Medicare arrangement they prefer. Limitations This study’s findings should be considered within the context of several limitations. Our study is limited to traditional fee-for-service Medicare data, because these data are freely and publicly available to researchers (although access to these data may soon change), and our results should not be conflated to represent the number of psychiatrists accepting Medicare more broadly (especially Medicare Advantage). Our denominator data are from the Kaiser Family Foundation and limited in scope, which does not allow for further interrogation of active physician characteristics such as age or sex. We did not account for nurse practitioners or physician assistants who may have played a greater role in serving Medicare patients as the number of psychiatrists decreased, as suggested by a 2022 study, although stratification of available psychiatric practitioner type by insurance status is an equity issue in itself and one that may prove increasingly important in the future. Finally, we do not address the rise of telepsychiatry, which may distort pandemic-year data. Nevertheless, this study is the first, to our knowledge, to characterize the decline in psychiatrists providing professional services to fee-for-service Medicare Part B patients on the national, regional, and state levels, while placing these findings in the context of a workforce that has been long increasing.
This study’s findings should be considered within the context of several limitations. Our study is limited to traditional fee-for-service Medicare data, because these data are freely and publicly available to researchers (although access to these data may soon change), and our results should not be conflated to represent the number of psychiatrists accepting Medicare more broadly (especially Medicare Advantage). Our denominator data are from the Kaiser Family Foundation and limited in scope, which does not allow for further interrogation of active physician characteristics such as age or sex. We did not account for nurse practitioners or physician assistants who may have played a greater role in serving Medicare patients as the number of psychiatrists decreased, as suggested by a 2022 study, although stratification of available psychiatric practitioner type by insurance status is an equity issue in itself and one that may prove increasingly important in the future. Finally, we do not address the rise of telepsychiatry, which may distort pandemic-year data. Nevertheless, this study is the first, to our knowledge, to characterize the decline in psychiatrists providing professional services to fee-for-service Medicare Part B patients on the national, regional, and state levels, while placing these findings in the context of a workforce that has been long increasing.
In this repeated cross-sectional study of all traditional Medicare Part B enrollees from 2014 to 2022, we found significant declines in psychiatrists per enrollee, nationally and across all geographic regions. The nationwide proportion of psychiatrists billing Medicare Part B declined during a time when the total number of active psychiatrists increased. We further identified sizable regional and state-level variation in access to care, with the most underserved state having less than one-tenth the per-capita psychiatrists serving Medicare Part B of the most served state. Taken together, the results of this study suggest a potential decline in access to psychiatrist-led care among many individuals with mental and physical disabilities and older adults nationwide. The causes of these findings and their implications on mental health care access and equity merit further research.
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The Use of Platelet-Rich Fibrin (PRF) in the Management of Dry Socket: A Systematic Review | 05385bce-d080-45f3-b35a-6b86110d57c9 | 11432458 | Dentistry[mh] | A surgical complication that frequently arises following the extraction of a tooth is known as alveolar osteitis (AO) or dry socket (DS) . This condition is a painful but not potentially life-threatening complication seen in approximately 0.5–5% of all patients subjected to tooth extractions, most frequently the third molar . This prevalent postoperative issue results in severe and debilitating pain within and around the site of the tooth extraction . The intensity of the pain generally escalates between the first and third day following the extraction procedure, typically triggered by a blood clot within the socket that has either partially or completely disintegrated . Although the precise etiology of DS remains unclear, the most commonly identified causes include fibrinolysis induced by bacterial invasion and the subsequent collapse of the blood coagulum . Various factors can contribute to the development of DS, such as traumatic tooth extraction, the age and sex of the patient, smoking habits, the use of contraceptives, the concentration of the anesthetic used, intraligamentary anesthesia, and the specific location of the tooth being extracted . Various treatment strategies have been employed to manage and resolve this condition . Conventional treatment involves the application of medicated dressings, such as those containing eugenol or iodine-based solutions, which offer analgesic and antimicrobial effects while providing a protective barrier to the exposed bone. In addition to dressings, socket irrigation with saline or antiseptic solutions is commonly used to cleanse the site and reduce the risk of infection. Analgesics, including nonsteroidal anti-inflammatory drugs and opioids, are often prescribed to manage pain. More recent approaches include the use of topical gels or pastes containing anesthetics or corticosteroids to provide additional pain relief and reduce inflammation. However, these methods often provide temporary relief without addressing the underlying tissue regeneration process. Emerging treatments involve regenerative techniques, such as the application of platelet-rich plasma (PRP), platelet-rich fibrin (PRF), or other biomaterials, which aim to enhance the healing process and promote tissue regeneration . PRP and PRF are both autologous blood-derived products used to enhance tissue healing and regeneration. They differ in their preparation methods, composition, and clinical applications . PRP is obtained by centrifuging a sample of the patient’s blood to concentrate the platelets and associated growth factors (GF) in the plasma. PRP can be used in DS management by applying it to the extraction site to aid in the healing process. The GFs in PRP stimulate tissue repair and potentially reduce inflammation and pain. However, due to its liquid nature, PRP may not provide long-lasting mechanical support to the extraction site. PRF constitutes the second generation of platelet concentrates. It belongs to a new generation of hemo-concentrates obtained by the sole centrifugation, which do not require additives such as heparin or thrombin, allowing a slow release of GF. Furthermore, PRF has the following bioactive properties: stimulation, through the GF contained within it, of the proliferation, differentiation, chemotaxis, and adhesion of stem cells, promoting angiogenesis and immune processes; an increased expression of alkaline phosphatase in stem cells, leading to faster mineralization of the newly formed tissue; the induction of mineralization of the defect thanks to the GF it contains transforming growth factor-beta(TGF-β1) and platelet-derived growth factor PDGF); and the creation of an epithelial barrier by the PRF membrane . PRP offers a high concentration of GFs and is useful for the short-term stimulation of tissue repair. Its application in the treatment of DS is beneficial but might be less effective in providing long-term support due to its liquid nature. PRF provides a robust fibrin matrix that supports prolonged healing and regeneration. Its solid consistency and natural formation make it particularly effective in enhancing the healing process in DS cases . In recent years, PRF has gained attention as a potential therapeutic option for enhancing tissue repair and regeneration in various oral and maxillofacial applications . Initially, medical professionals in France began advocating for the use of PRF to expedite the healing process, alleviate postoperative discomfort, and prevent the occurrence of DS after tooth extraction . PRF is an autologous biomaterial derived from the patient’s blood, which, through a simple centrifugation process, yields a fibrin matrix rich in platelets, GFs, and cytokines . These biological components are critical in promoting angiogenesis, reducing inflammation, and accelerating tissue healing . PRF has emerged as a promising therapeutic modality in dentistry due to its rich concentration of GFs and cytokines which are essential for wound healing and tissue regeneration . The application of PRF in the treatment of DS offers a biologically driven approach aimed at improving outcomes beyond mere symptomatic relief . By providing a concentrated source of healing factors directly to the extraction site, PRF may facilitate faster tissue regeneration, reduce the intensity and duration of pain, and decrease the incidence of secondary complications . Numerous studies and reports from various authors have recently highlighted the highly successful outcomes associated with the use of PRF in preventing DS, particularly following the extraction of lower third molars . Its application in DS treatment aims to accelerate healing, reduce pain, and minimize complications associated with delayed healing . Despite the evidence supporting the efficacy of fibrin adhesives in multiple medical fields over the past three decades , their usage has been mired in controversy due to the complexities involved . These include the potential for cross infections and the time-consuming and labor-intensive methods required for their production . This systematic review aims to critically evaluate the efficacy of PRF in the management of DS. By synthesizing current evidence from clinical studies, the paper seeks to assess its impact on pain reduction, healing time, and overall patient outcomes compared to conventional treatments . Understanding the role of PRF in enhancing tissue repair mechanisms within the alveolar socket is crucial for optimizing post-operative care and improving patient satisfaction following tooth extraction .
2.1. Protocol and Registration This systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the protocol was registered at PROSPERO under the ID: CRD 578018 . 2.2. Search Processing To find studies that evaluate the use of PRF in the management of DS, a search was conducted on PubMed, Scopus, and Web of Science for papers published between 1 January 2013 and 1 May 2024. Boolean keywords have been used in the search strategy: (“Treatment”) AND (“Dry Socket”) AND (“Platelet Rich Fibrin” OR “PRF”). These keywords were selected as they closely aligned with the objective of our study, which aimed to assess the management of DS with PRF. The primary focus was to explore the most effective approaches for minimizing complication and enhancing an easy healing for the patient . 2.3. Elegibility Criteria and Study Selection The two stages of the selection process involved assessing the abstract and title as well as the material in its entirety. The following inclusion criteria were considered: (1) open-access studies that investigated treatment of the DS; (2) studies in vivo; (3) observational and randomized clinical studies, randomized clinical trials, retrospective studies, case–control studies, and prospective studies; (4) studies published in the English language; and (5) full-text. Papers that did not meet the specified requirements were not accepted. Excluded publications included research techniques, conference presentations, in vitro or animal experiments, meta-analyses, and publications without original data. Titles and abstracts found during the initial search were evaluated for relevancy. Complete papers from pertinent research were acquired for further analysis. Using the previously indicated criteria, two different reviewers (P.A. and L.R.) assessed the retrieved studies for inclusion. 2.4. PICOS Requirement The PICOS (Population, Intervention, Comparison, Outcome, Study Design) criteria were used to conduct the review: Population: adults, both male and female; Intervention: treatment of DS with PRF; Comparison: treatment of DS with PRF with different techniques; Outcome: better healing; Study Design: randomized clinical trials, retrospective studies, case–control studies, prospective studies, and observational and randomize clinical studies. 2.5. Data Processing Based on selection criteria, two reviewers (P.A. and L.R.) independently accessed the databases to gather the studies and assign them a quality rating. Disagreements among the three writers were resolved through consultation with a senior reviewer (F.I.). Publications that did not align with the themes under examination could be excluded during the screening procedure. The publications′ whole texts were read after it was determined that they satisfied the predetermined inclusion criteria. The selected articles were downloaded as a 6.0.15 version to be used with Zotero, Center for History and Media, George Mason University 4400 University Drive, MSN 1E7 Fairfax, Virginia 22030. 2.6. Quality Assessment The quality of the included papers was assessed using the ROBINS, a tool developed to assess risk of bias in the results of non-randomized studies that compare health effects of two or more interventions. Seven points were evaluated and each was assigned a degree of bias. A third reviewer (F.I.) was consulted in the event of a disagreement until an agreement was reached. The types of biases in the domains evaluated by the ROBINS were the following: Bias due to confounding; Bias arising from measurement of exposure; Bias in the selection of participants into the study; Bias due to post-exposure intervention; Bias due to missing data; Bias arising from measurement of the outcome; Bias in the selection of the reported results.
This systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the protocol was registered at PROSPERO under the ID: CRD 578018 .
To find studies that evaluate the use of PRF in the management of DS, a search was conducted on PubMed, Scopus, and Web of Science for papers published between 1 January 2013 and 1 May 2024. Boolean keywords have been used in the search strategy: (“Treatment”) AND (“Dry Socket”) AND (“Platelet Rich Fibrin” OR “PRF”). These keywords were selected as they closely aligned with the objective of our study, which aimed to assess the management of DS with PRF. The primary focus was to explore the most effective approaches for minimizing complication and enhancing an easy healing for the patient .
The two stages of the selection process involved assessing the abstract and title as well as the material in its entirety. The following inclusion criteria were considered: (1) open-access studies that investigated treatment of the DS; (2) studies in vivo; (3) observational and randomized clinical studies, randomized clinical trials, retrospective studies, case–control studies, and prospective studies; (4) studies published in the English language; and (5) full-text. Papers that did not meet the specified requirements were not accepted. Excluded publications included research techniques, conference presentations, in vitro or animal experiments, meta-analyses, and publications without original data. Titles and abstracts found during the initial search were evaluated for relevancy. Complete papers from pertinent research were acquired for further analysis. Using the previously indicated criteria, two different reviewers (P.A. and L.R.) assessed the retrieved studies for inclusion.
The PICOS (Population, Intervention, Comparison, Outcome, Study Design) criteria were used to conduct the review: Population: adults, both male and female; Intervention: treatment of DS with PRF; Comparison: treatment of DS with PRF with different techniques; Outcome: better healing; Study Design: randomized clinical trials, retrospective studies, case–control studies, prospective studies, and observational and randomize clinical studies.
Based on selection criteria, two reviewers (P.A. and L.R.) independently accessed the databases to gather the studies and assign them a quality rating. Disagreements among the three writers were resolved through consultation with a senior reviewer (F.I.). Publications that did not align with the themes under examination could be excluded during the screening procedure. The publications′ whole texts were read after it was determined that they satisfied the predetermined inclusion criteria. The selected articles were downloaded as a 6.0.15 version to be used with Zotero, Center for History and Media, George Mason University 4400 University Drive, MSN 1E7 Fairfax, Virginia 22030.
The quality of the included papers was assessed using the ROBINS, a tool developed to assess risk of bias in the results of non-randomized studies that compare health effects of two or more interventions. Seven points were evaluated and each was assigned a degree of bias. A third reviewer (F.I.) was consulted in the event of a disagreement until an agreement was reached. The types of biases in the domains evaluated by the ROBINS were the following: Bias due to confounding; Bias arising from measurement of exposure; Bias in the selection of participants into the study; Bias due to post-exposure intervention; Bias due to missing data; Bias arising from measurement of the outcome; Bias in the selection of the reported results.
3.1. Selection and Characteristics of the Study A total of 738 publications were found using the electronic database search (Scopus n = 345, PubMed n = 219, Web of Science n = 174) using the Boolean keywords (“Treatment”) AND (“Dry Socket”) AND (“Platelet Rich Fibrin” OR “PRF”) as the search string; no articles were found using the manual search. After removing duplicates (n = 81), the titles and abstracts of 657 papers were assessed to filter them. A total of 97 records that did not match the inclusion criteria were identified (319 off-topic, 157 reviews, 84 vitro experiments), leaving us with 560 papers. Following the removal of 33 records that could not be retrieved, another 50 reports were removed for not meeting the inclusion criteria (45off-topic, 6 reviews). A further 13 articles were reviewed in the quality analysis. The selection process and the summary of selected records are shown in . The study characteristics are summarized in . 3.2. Quality Assessment and Risk of Bias The risk of bias in the included studies is reported in . Most of the studies exhibit some issues regarding bias due to confounding data. Measuring the exposure generally has a low risk of bias. Many studies also display a low risk of bias in the selection of participants. The bias due to missing data presents mostly some concerns. The bias arising from the measurement of the outcome is primarily low. The bias in the selection of the reported results mainly raises some concerns. The final results indicate that out of fourteen analyzed articles, three studies have a low risk of bias, ten studies have some issues, and one study has a high risk of bias.
A total of 738 publications were found using the electronic database search (Scopus n = 345, PubMed n = 219, Web of Science n = 174) using the Boolean keywords (“Treatment”) AND (“Dry Socket”) AND (“Platelet Rich Fibrin” OR “PRF”) as the search string; no articles were found using the manual search. After removing duplicates (n = 81), the titles and abstracts of 657 papers were assessed to filter them. A total of 97 records that did not match the inclusion criteria were identified (319 off-topic, 157 reviews, 84 vitro experiments), leaving us with 560 papers. Following the removal of 33 records that could not be retrieved, another 50 reports were removed for not meeting the inclusion criteria (45off-topic, 6 reviews). A further 13 articles were reviewed in the quality analysis. The selection process and the summary of selected records are shown in . The study characteristics are summarized in .
The risk of bias in the included studies is reported in . Most of the studies exhibit some issues regarding bias due to confounding data. Measuring the exposure generally has a low risk of bias. Many studies also display a low risk of bias in the selection of participants. The bias due to missing data presents mostly some concerns. The bias arising from the measurement of the outcome is primarily low. The bias in the selection of the reported results mainly raises some concerns. The final results indicate that out of fourteen analyzed articles, three studies have a low risk of bias, ten studies have some issues, and one study has a high risk of bias.
The utilization of PRF in managing AO has demonstrated significant promise across multiple studies. DS, a common and painful complication following tooth extraction, particularly mandibular molars, poses substantial challenges in dental practice due to the severe pain and delayed healing associated with it . Traditional treatments have yielded variable results, prompting the exploration of alternative therapies like PRF, which is rich in GF essential for tissue repair and regeneration. The potential fields for PRF application are multiple . The studies consistently highlight PRF′s effectiveness in pain reduction and wound healing . For instance, one study involving 100 patients found a significant decrease in pain and inflammation by the third and seventh days post-PRF application, with complete granulation tissue coverage by the second week . Similarly, another trial with 10 patients reported substantial pain relief within the first day, and most patients required minimal analgesics, with satisfactory healing being observed by the seventh day . These findings align with those of Chakravarthi, who noted early and significant pain reduction and minimal analgesic use over a week . Comparative studies further underscore PRF′s superior performance. A split-mouth trial comparing PRF with aspirin cones revealed that PRF provided significantly better pain relief at 24 and 48 h post-treatment . Additionally, PRF influenced bacterial concentrations, suggesting a potential antimicrobial effect, though further research is required to elucidate this mechanism fully . This indicates that PRF not only accelerates healing but may also play a role in modulating the oral microbiome, which is crucial in preventing infections that can exacerbate AO . The underlying mechanisms of PRF′s efficacy are attributed to its high concentration of GF such as PDGF, TGF-β, and vascular endothelial growth factor (VEGF) . These factors facilitate angiogenesis, enhance tissue regeneration, and reduce inflammation, creating a conducive environment for rapid and effective healing . The fibrin matrix provided by PRF also supports cellular migration and proliferation, further aiding in the repair process . The practical implications of these findings are significant. PRF, derived from the patient’s own blood, is biocompatible and easy to prepare, making it a cost-effective and patient-friendly option . Its application can potentially reduce the reliance on analgesics and antibiotics, mitigating the risks associated with their long-term use . Moreover, the rapid pain relief and accelerated healing it leads to can enhance patient satisfaction and reduce the burden on dental care providers . The article by Iqbal et al. investigates the use of PRF in reducing the incidence of DS, a painful complication after wisdom tooth extraction . This study reveals that PRF, rich in GFs and cytokines, significantly lowers the occurrence of DS, reduces postoperative pain, and accelerates healing by promoting cell migration and proliferation . Similarly, the article by Keshini et al. compares PRF with Alvogyl, a traditional medicated dressing . The findings indicate that while both treatments are effective, PRF offers superior pain relief and faster healing due to its regenerative properties, suggesting it as a preferable option for managing DS . The results of the study by Asif et al. corroborate the previous studies by showing a significantly lower frequency of AO in patients treated with PRF . These patients also reported less postoperative pain and quicker recoveries, highlighting PRF′s efficacy in maintaining the protective blood clot necessary for proper healing . The study by Reeshma et al. adds to this body of evidence by comparing PRF with zinc oxide eugenol (ZOE) . The study found that PRF not only provided quicker pain relief but also facilitated a more rapid and effective healing process, positioning PRF as a superior treatment for alleviating the symptoms of DS . Building on these insights, the article by Eshghpour et al. further validates PRF′s benefits through a rigorous methodology . This study′s findings reinforce PRF′s ability to significantly reduce the frequency of DS, decrease postoperative pain, and expedite healing . A more innovative approach is discussed in the study of Balint et al. which introduces a comprehensive treatment combining surgical debridement, pharmacological therapy, and the use of a fibrin sealant as a biomatrix for PRF . The results demonstrate significantly improved outcomes, including faster pain relief and accelerated healing, showcasing the synergistic benefits of this multifaceted approach . The versatility of PRF is further highlighted in the article by Rastogi et al. which confirms PRF′s effectiveness in providing immediate pain relief, reducing inflammation, and promoting faster wound healing . This study emphasizes PRF′s potential as a versatile and potent treatment option in dental surgery . Finally, the article of Asutay et al. focuses on the broader benefits of PRF in reducing postoperative complications such as pain, swelling, and delayed healing. The study found that PRF significantly enhances patient comfort and speeds up recovery, making it a valuable addition to routine postoperative care in oral surgery . However, while the current evidence is promising, there is a need for larger, randomized, and multicenter studies with long-term follow-ups to confirm PRF′s efficacy and establish it as a standard treatment for DS . Future research could also explore the use of leukocyte-platelet-rich fibrin (L-PRF) and other variations to potentially improve outcomes further .
The studies included varied widely in their designs, ranging from randomized controlled trials to observational and crossover studies. This heterogeneity complicates the comparison and synthesis of outcomes. Furthermore, the studies assessed diverse endpoints, such as bacterial colony counts, enamel remineralization, and implant osseointegration, which are not directly comparable . Many studies featured small sample sizes. Additionally, several studies did not provide detailed demographic information, which limits the generalizability of the findings across different populations. Some studies did not provide explicit details about the methodologies used, such as the average age and gender of participants . This lack of information hinders the ability to fully evaluate the study′s context and potential biases. The properties of nanoparticles, including size, concentration, and type, varied significantly among the studies. For instance, the studies investigated nanoparticles such as silver, titanium dioxide, calcium phosphate, and nanocomposites, each with distinct characteristics and mechanisms of action . This variability may influence the outcomes and limit our ability to draw consistent conclusions about the efficacy of nanotechnology in dental applications . Moreover, there is a notable variability in the methodologies used across the studies, particularly in the preparation and application of PRF. Differences in centrifugation protocols, PRF formulations (such as variations between PRF and leukocyte-PRF), and outcome assessment criteria introduce heterogeneity that complicates direct comparisons and meta-analyses. Given these limitations, future research should focus on conducting larger, multicenter randomized controlled trials with standardized protocols for PRF preparation and application. Investigating variations such as L-PRF could also provide further insights into optimizing treatment outcomes.
This review analysis highlights PRF as a viable treatment for DS. In conclusion, the application of PRF has shown promising results, yet several critical areas warrant further investigation to optimize its use. The trials examined consistently show that PRF significantly lowers pain, speeds up wound healing, and may reduce the occurrence of DS healing (through its rich content of GF and cytokines), providing a considerable advantage over standard therapy. PRF′s effects are mostly due to its high concentration of GF which promote tissue regeneration, reduce inflammation, and speed up recovery. Furthermore, PRF′s biocompatibility and ease of preparation make it a cost-effective and patient-friendly alternative, potentially lowering the need for analgesics and antibiotics. Long-term studies are needed to evaluate the sustained efficacy of PRF in preventing DS recurrence, as well as to compare its effectiveness with other treatment modalities such as PRP and collagen-based products. Despite these hopeful findings, standardized protocols for PRF preparation and application are necessary to ensure consistency and reproducibility across studies. Additionally, research should address how patient-specific factors, including systemic health conditions and lifestyle factors like smoking, impact PRF’s effectiveness. As the field progresses, these research directions will be crucial for refining PRF applications and enhancing patient care in the management of DS. Combining PRF with adjunctive therapies, such as laser treatment or advanced antimicrobial agents, may offer synergistic benefits and improve clinical outcomes. Economic evaluations and cost-effectiveness analyses are essential to assess the overall value of PRF compared to traditional methods. As the field progresses, these future research directions will be crucial for refining PRF applications and enhancing patient care in the management of DS.
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Optimized workflow for digitalized FISH analysis in pathology | 68e93533-b64e-40aa-a723-8a3290eaeb15 | 8114497 | Pathology[mh] | Interphase fluorescence in situ hybridization (FISH) has gained importance as diagnostic and predictive examination in pathology . Together with its cost effectiveness, it allows for a rapid target-oriented analysis providing results within a day. In most instances, FISH slides are analyzed by an epi-fluorescent microscope, with or without a motorized scanning platform. Signal counting is done either manually at the microscope or at a computer screen or automatically by software-supported algorithms. Bright field whole-slide imaging (WSI) for Hematoxylin and Eosin (H&E) stained slides and immunohistochemistry is already used in many routine diagnostic laboratories. However, scanning FISH slides is not widely used yet. Our aim was to introduce the WSI for FISH slides into routine diagnostics. A further goal was to accelerate and standardize the FISH analysis process by introducing a rapid hybridization protocol and an automated cell-signal counting program. Herein, we report our experiences in establishing an optimal workflow for our digitalized FISH technique. Furthermore, we discuss the pros and cons of different scanning profiles and the value of an automated cell counting software. Pre-analytical workflow First, a representative tumor area was encircled on the H&E-slide by a pathologist. Second, the corresponding area was marked with a diamond pen on the back of the slide to be hybridized. This narrowed down the tissue surface to be scanned since the diamond scratches remain visible on the scan-preview. FISH technique A standard protocol was established for FISH on formalin fixed, paraffin embedded (FFPE) specimens. A tissue-micro-array (TMA) with ten cores (at 3mm 2 diameter) for the probe set up and 42 diagnostic samples including core needle and excisional biopsies were analyzed. Adapted to the tissue type, the pretreatment time varied from 30 to 40 min. The specific probes (Zytovision, Germany or Vysis, Abbott Molecular, USA) were hybridized at 37 °C for 4 h in the presence of the IntelliFISH Hybridization buffer (Vysis, Abbott Molecular, USA). As nuclear stain and mounting medium the DAPI (4′,6 diamidino-2-phenylindole) VECTASHIELD® HardSet™ (Vector laboratories, CA, USA) with a minimum hardening time of 30 min was used. Slide imaging and analyzing The optical system of the Pannoramic 250 Flash II Scanner (3DHISTECH, Sysmex, Switzerland) contains two Zeiss (Jena, Germany) Plan-Apochromat dry objectives (20x and 40x with a numerical aperture of 0.80 and 0.95 respectively) allowing also bright field scanning. In a motorized software-controlled wheel, three fluorescence filters are incorporated: FITC (green light, 459 nm), TRITC (red light, 544 nm) and DAPI (autofluorescence, 360 nm). The “SPECTRA light (Lumencor, USA) engine 6” switches the filters fast without fading. Images are acquired by the 16-bit scientific CMOS pco.edge 4.2 camera. We scanned all slides with the 40x objective with a resolution of 0.25 um/pixel. To circumvent inherent tissue-quality fluctuations, two main scanning profiles (low (LP) and high (HP)) were generated. The profiles differ in their exposure time (ET) (LP: 150 ms vs HP: 2000 ms) for the FITC and TRITC channels and their digital gain (LP: 3–4 vs HP: 0–2). For both profiles, the Z-stack function was activated using five to seven layers with a layer distance of 0.4 μm. The scanning time (min), the file size (MB) and the fields of view (FOV) of the two profiles were compared (Table B). The area-scanning technology of the current scanner is FOV based. The FOV corresponds to the square image of the camera sensor. The larger the area to be scanned, the greater the number of the FOV required. When using different profiles with the identical area to be scanned, the number of FOV remains the same. Manual counting Digitalized images were visualized in the CaseViewer (3DHISTEC, Sysmex, Switzerland), a digital microscope application software. As a control step, the pre-selected areas of the corresponding H&E- and FISH-slides were viewed in parallel. Thereafter, FISH signals of a hundred of nuclei were counted manually at the computer screen. Cut-off levels were assessed as described earlier . A signal was counted as abnormal, when the green and the red signal were two diameters of one signal apart. Software counting FISHQuant (3DHISTECH, Sysmex, Switzerland), is an IVD approved module allowing to automatically quantify structural and numerical FISH signal abnormalities in solid tumors and neoplasias of the hematopoietic system. Since automated classification is error prone due to tissue inherent artefacts like overlapping of nuclei, manual editing is mandatory before signing out final reports. First, a representative tumor area was encircled on the H&E-slide by a pathologist. Second, the corresponding area was marked with a diamond pen on the back of the slide to be hybridized. This narrowed down the tissue surface to be scanned since the diamond scratches remain visible on the scan-preview. A standard protocol was established for FISH on formalin fixed, paraffin embedded (FFPE) specimens. A tissue-micro-array (TMA) with ten cores (at 3mm 2 diameter) for the probe set up and 42 diagnostic samples including core needle and excisional biopsies were analyzed. Adapted to the tissue type, the pretreatment time varied from 30 to 40 min. The specific probes (Zytovision, Germany or Vysis, Abbott Molecular, USA) were hybridized at 37 °C for 4 h in the presence of the IntelliFISH Hybridization buffer (Vysis, Abbott Molecular, USA). As nuclear stain and mounting medium the DAPI (4′,6 diamidino-2-phenylindole) VECTASHIELD® HardSet™ (Vector laboratories, CA, USA) with a minimum hardening time of 30 min was used. The optical system of the Pannoramic 250 Flash II Scanner (3DHISTECH, Sysmex, Switzerland) contains two Zeiss (Jena, Germany) Plan-Apochromat dry objectives (20x and 40x with a numerical aperture of 0.80 and 0.95 respectively) allowing also bright field scanning. In a motorized software-controlled wheel, three fluorescence filters are incorporated: FITC (green light, 459 nm), TRITC (red light, 544 nm) and DAPI (autofluorescence, 360 nm). The “SPECTRA light (Lumencor, USA) engine 6” switches the filters fast without fading. Images are acquired by the 16-bit scientific CMOS pco.edge 4.2 camera. We scanned all slides with the 40x objective with a resolution of 0.25 um/pixel. To circumvent inherent tissue-quality fluctuations, two main scanning profiles (low (LP) and high (HP)) were generated. The profiles differ in their exposure time (ET) (LP: 150 ms vs HP: 2000 ms) for the FITC and TRITC channels and their digital gain (LP: 3–4 vs HP: 0–2). For both profiles, the Z-stack function was activated using five to seven layers with a layer distance of 0.4 μm. The scanning time (min), the file size (MB) and the fields of view (FOV) of the two profiles were compared (Table B). The area-scanning technology of the current scanner is FOV based. The FOV corresponds to the square image of the camera sensor. The larger the area to be scanned, the greater the number of the FOV required. When using different profiles with the identical area to be scanned, the number of FOV remains the same. Digitalized images were visualized in the CaseViewer (3DHISTEC, Sysmex, Switzerland), a digital microscope application software. As a control step, the pre-selected areas of the corresponding H&E- and FISH-slides were viewed in parallel. Thereafter, FISH signals of a hundred of nuclei were counted manually at the computer screen. Cut-off levels were assessed as described earlier . A signal was counted as abnormal, when the green and the red signal were two diameters of one signal apart. FISHQuant (3DHISTECH, Sysmex, Switzerland), is an IVD approved module allowing to automatically quantify structural and numerical FISH signal abnormalities in solid tumors and neoplasias of the hematopoietic system. Since automated classification is error prone due to tissue inherent artefacts like overlapping of nuclei, manual editing is mandatory before signing out final reports. FISH technique Introducing the IntelliFISH Hybridization buffer substantially shortened the hybridization process from 18 to 4 h and resulted in good signal to noise ratios with strong and distinct signals (Figs. and ). The DAPI hardening mounting media VECTASHIELD® HardSet™ proved to be the fastest option of the several types of media tested. Slide imaging and analyzing The handling of the scanner software turned out to be intuitive and rather easy. Both established profiles (LP and HP) provided signals of good quality, however, the HP translated a better signal to noise ratio (Fig. ). The scanning time of a TMA core (3mm 2 ) varied between 5 to 7 min with a LP and 15 to 20 min with a HP. The scanning time for FISH depended on the FOV reflecting the size of the selected area and the exposure time (ET) per fluorescence channel. In 16/42 samples we applied an LP (150 ms ET) and in 26/42 samples a HP (2000 ms ET) (Table B). With this approach, the scanning time was more than ten times longer for the HP (mean 170 min) than for the LP (mean 15 min). Moreover, the file size was 2.5 times larger for the HP than for the LP (Table B) while the mean file size per FOV remained comparable for all approaches (low: 0.32; high: 0.34) as expected. In four cases (one with LP and three with HP) the FOV was > 10′000 resulting in high data volumes (min 2390 MB, max 7620 MB, mean 4453 MB) leading to the longest scanning time with the LP (72 min) and HP (949 min). Whereas the LP showed strong enough signals to be successfully analyzed in most instances, HP improved picture quality in cases with weak signals or high background (Figs. b and ). Manual vs automated counting In three out of the 42 diagnostic samples and the TMA, the FISHQuant software automatically classified the signals and the nuclei correctly. Compared to manual counting FISHQuant provided similar results within seconds (e.g. 7% vs 6% for ETVS1). However, in the remaining samples, especially those containing lymphatic tissue, the nuclei were too densely packed to be correctly identified by the automatic algorithm, leading to a high number of erroneously classified signals. Introducing the IntelliFISH Hybridization buffer substantially shortened the hybridization process from 18 to 4 h and resulted in good signal to noise ratios with strong and distinct signals (Figs. and ). The DAPI hardening mounting media VECTASHIELD® HardSet™ proved to be the fastest option of the several types of media tested. The handling of the scanner software turned out to be intuitive and rather easy. Both established profiles (LP and HP) provided signals of good quality, however, the HP translated a better signal to noise ratio (Fig. ). The scanning time of a TMA core (3mm 2 ) varied between 5 to 7 min with a LP and 15 to 20 min with a HP. The scanning time for FISH depended on the FOV reflecting the size of the selected area and the exposure time (ET) per fluorescence channel. In 16/42 samples we applied an LP (150 ms ET) and in 26/42 samples a HP (2000 ms ET) (Table B). With this approach, the scanning time was more than ten times longer for the HP (mean 170 min) than for the LP (mean 15 min). Moreover, the file size was 2.5 times larger for the HP than for the LP (Table B) while the mean file size per FOV remained comparable for all approaches (low: 0.32; high: 0.34) as expected. In four cases (one with LP and three with HP) the FOV was > 10′000 resulting in high data volumes (min 2390 MB, max 7620 MB, mean 4453 MB) leading to the longest scanning time with the LP (72 min) and HP (949 min). Whereas the LP showed strong enough signals to be successfully analyzed in most instances, HP improved picture quality in cases with weak signals or high background (Figs. b and ). In three out of the 42 diagnostic samples and the TMA, the FISHQuant software automatically classified the signals and the nuclei correctly. Compared to manual counting FISHQuant provided similar results within seconds (e.g. 7% vs 6% for ETVS1). However, in the remaining samples, especially those containing lymphatic tissue, the nuclei were too densely packed to be correctly identified by the automatic algorithm, leading to a high number of erroneously classified signals. FISH has become an important theranostic auxiliary method in surgical pathology over the years . To meet the current needs of shortening turn-around-times while maintaining high quality and cost-effectiveness, we accelerated the hybridization process by introducing the IntelliFISH hybridization buffer. Thereby, we shortened the duration of the experimental process by more than 12 h while preserving an excellent signal quality. The overall time from the entry of the order to the hybridized slide was cut to approximatively 6 h with around 30 min hands on time. The Pannoramic 250 Flash II Scanner equipped with a fluorescent module has proven to be a reliable and efficient tool for routine diagnostics of break-apart and enumeration probes. Our observations are in line with a previous report regarding the same system and a second one dealing with a different scanning system . One main difference and advantage compared to conventional fluorescence microscopes is the lack of fading of the fluorescent probes during the scanning process. Additional major advantages of digitalizing FISH slides are the preview and the alignment of the hybridized slides with their corresponding H&E or immunohistochemical stain on the CaseViewer, allowing a more precise as well as fast, identification and analysis of the diseased area (Fig. ) . Other benefits for the examiner compared to the use of a traditional fluorescence microscope were the larger fields of view and wider zoom-ranges. Both could be easily and continuously adjusted on the CaseViewer without losing the area of interest. This simplified analysis and the optimized FISH protocols might be reasons for the lower cut-off values for our probes as compared to those described in the literature (Table A) . However, the methods used for the assessment of the thresholds were not indicated in all reports . Based on our experience, the establishment of two different scanning profiles is sufficient to enable a routine diagnostic FISH laboratory to easily scan and analyze tissue samples of different origin. A mean scanning time of 15 min for the majority of samples applying the LP seems reasonable. Hence, the HP can be reserved for more demanding probes. In our hands, the automated FISHQuant software is promising and provides graphically represented results of break-apart probes within seconds. However, the ability to discriminate nuclei and to correctly assign the signals to them is limited by the algorithm, necessitating an elaborate manual editing compared to the manual counting by means of the CaseViewer. Therefore, the FISHQuant software is not yet ideal for certain tissues, especially not for lymphomatous tissue, since the algorithm is only able to correctly classify a minority of nuclei. A further refinement into a self-learning system would be desirable. In conclusion, in our view the advantages of scanning FISH slides far outweigh the conventional analysis by fluorescence microscopes. Particularly storage, sharing and remote diagnostics open up new opportunities. The development of tissue adapted self-scoring software would be desirable. |
Functional Outcomes After ‘SHURUI’ Single‐Port Robot‐Assisted Pyeloplasty for Uretero Pelvic Junction Obstruction: Single‐Centre Experience | 673c3e0e-9f7c-47e4-bb07-5a1950f5e5e6 | 11884222 | Robotic Surgical Procedures[mh] | Introduction Ureteropelvic junction obstruction (UPJO) is a condition in which urine flow from the renal pelvis to the ureter is impaired due to anatomical or functional abnormalities, leading to renal dilatation, cortical atrophy, and damage. UPJO can be congenital or secondary, with congenital cases being more common in newborns (1 in 1000–2000) and less frequent in adults (1 in 1500) . It is often associated with ureteral stenosis, muscular hypoplasia, fibrous tissue proliferation, and other factors such as high ureteral insertion or ectopic vessels may also contribute . Treatment aims to relieve obstruction, reduce hydronephrosis, and preserve renal function . Since Gettman et al. first reported robot‐assisted laparoscopic pyeloplasty (RALP) in 2002, this surgery has been widely performed both domestically and internationally . Compared with traditional laparoscopic surgery, robotic surgery offers greater flexibility, with the robotic arm providing more operating dimensions and the imaging system delivering a magnified 3D view. This results in a significant advantage in anastomosis. Robotic surgery maintains the success rate of traditional methods while significantly reducing complications and shortening the patient's recovery period . With the continuous development of modern medical technology, the goal of medical treatment has expanded beyond just effective treatment to include cosmetic outcomes. This has led to the development of single‐incision single‐port laparoscopic technology. However, this technique faces challenges such as the loss of the triangular relationship between instruments and the loss of depth perception, which limit its potential. The advent of single‐port robots has addressed these issues to some extent. In recent years, domestic robotic surgical platforms have developed rapidly. SHURUI Company has launched a single‐port snake‐arm robotic surgical platform to achieve minimally invasive and efficient surgery while significantly reducing surgical costs. This domestically produced robotic surgery platform has been used in clinical practice. The purpose of this study was to evaluate the clinical outcomes and feasibility of single‐port robot‐assisted pyeloplasty using the ‘SHURUI’ single‐port serpentine‐arm robotic surgery system.
Materials and Methods 2.1 Study Design and Patient Selection Between November 2023 and May 2024, 20 patients diagnosed with ureteropelvic junction obstruction (UPJO) underwent single‐port robotic‐assisted laparoscopic pyeloplasty using the ‘SHURUI’ system at a dedicated high‐volume robotic surgery centre (Xi'an People's Hospital). Inclusion criteria required a confirmed UPJO diagnosis via imaging and no prior ipsilateral kidney surgery. Patients with incomplete or missing records were excluded from the study. This study was approved by the Ethic Committee of Xi'an People's Hospital (Approval No. 20220019). The data collected included preoperative demographic information (age, body mass index (BMI), surgical history), specifics about UPJO (side affected, clinical symptoms, pre‐ and postoperative imaging results), perioperative details (procedure duration, blood loss, presence of crossing vessels or stones), and postoperative metrics (operation time, estimated blood loss (EBL), pain scores, length of hospital stay (LOS), time to urinary catheter and double J stent removal, and any complications). The success of the surgery was defined based on the absence of pain, the presence of normal renal function, and absence of renal obstruction, as determined by imaging studies conducted 3 months postoperatively. 2.2 Surgical Technique The SHURUI system is an ‘assistive’ platform consisting of a surgeon console, a single‐port serpentine arm, and reusable endoscopic instruments (Figure ). All patients underwent transperitoneal dismembered pyeloplasty by a surgeon who had performed more than 100 robotic surgeries. All operations were completed using a domestically produced ‘SHURUI’ serpentine‐arm single‐port robot. After general anaesthesia, the patient was placed in a supine position, the waist of the affected side was elevated 50–60° towards the healthy side, all stress‐bearing parts were properly protected and fixed, a periumbilical incision was made on the affected side with an arc of 270°, the pedicled skin flap was facing the surgical field, the skin and subcutaneous tissue were incised layer by layer, the peritoneum was opened, the abdominal cavity was entered, and a disposable single‐port multi‐channel puncture device was inserted to establish pneumoperitoneum with a pressure of 13 mmHg and a flow rate of 4 L/min. Connect the ‘SHURUI’ single‐port robotic system (Figure ). For a left‐sided condition, the left lateral peritoneum is released or the renal pelvis and ureter are access via the left colon mesentery. For the right side, release the right lateral peritoneum to reveal the renal pelvis and ureter. Open the posterior peritoneum, free and expose the renal pelvis and upper ureter on the affected side to identify the obstruction site (Figure ). Excise the narrowed ureteropelvic junction and make a longitudinal incision of about 2.0 cm on the lateral wall of the ureter (Figure ). Identify the lowest point of the renal pelvis and suture it to the lowest point of the ureter incision (Figure ). Continuously suture the posterior wall of the anastomosis and insert a ureteral stent through the anastomosis in an antegrade manner (Figure ). Ensure the stent reaches the bladder, then continuously suture the anterior wall of the anastomosis and trim excess renal pelvis tissue to form a new anastomosis (Figure ). After completing the anastomosis, furosemide was administered intravenously (0.3 mg/kg) and checked for leakage or folding at the anastomosis site. Flush the surgical area with warm saline, remove any fluid in the abdominal cavity, and ensure no active bleeding in the surgical field. Intermittently suture the mesenteric defect, disconnect the robot from the patient, remove the robotic platform, and close the incision in layers. For UPJO with kidney stones, stone extraction was performed using a flexible ureteroscope during the procedure. All patients had the urinary catheter removed before discharge. 2.3 Statistical Analysis Statistical analysis was conducted using SPSS 22.0 software. Demographic and perioperative data were analysed using descriptive statistics. Counts of frequencies were expressed as percentages, and continuous data were presented as medians and interquartile ranges (IQRs).
Study Design and Patient Selection Between November 2023 and May 2024, 20 patients diagnosed with ureteropelvic junction obstruction (UPJO) underwent single‐port robotic‐assisted laparoscopic pyeloplasty using the ‘SHURUI’ system at a dedicated high‐volume robotic surgery centre (Xi'an People's Hospital). Inclusion criteria required a confirmed UPJO diagnosis via imaging and no prior ipsilateral kidney surgery. Patients with incomplete or missing records were excluded from the study. This study was approved by the Ethic Committee of Xi'an People's Hospital (Approval No. 20220019). The data collected included preoperative demographic information (age, body mass index (BMI), surgical history), specifics about UPJO (side affected, clinical symptoms, pre‐ and postoperative imaging results), perioperative details (procedure duration, blood loss, presence of crossing vessels or stones), and postoperative metrics (operation time, estimated blood loss (EBL), pain scores, length of hospital stay (LOS), time to urinary catheter and double J stent removal, and any complications). The success of the surgery was defined based on the absence of pain, the presence of normal renal function, and absence of renal obstruction, as determined by imaging studies conducted 3 months postoperatively.
Surgical Technique The SHURUI system is an ‘assistive’ platform consisting of a surgeon console, a single‐port serpentine arm, and reusable endoscopic instruments (Figure ). All patients underwent transperitoneal dismembered pyeloplasty by a surgeon who had performed more than 100 robotic surgeries. All operations were completed using a domestically produced ‘SHURUI’ serpentine‐arm single‐port robot. After general anaesthesia, the patient was placed in a supine position, the waist of the affected side was elevated 50–60° towards the healthy side, all stress‐bearing parts were properly protected and fixed, a periumbilical incision was made on the affected side with an arc of 270°, the pedicled skin flap was facing the surgical field, the skin and subcutaneous tissue were incised layer by layer, the peritoneum was opened, the abdominal cavity was entered, and a disposable single‐port multi‐channel puncture device was inserted to establish pneumoperitoneum with a pressure of 13 mmHg and a flow rate of 4 L/min. Connect the ‘SHURUI’ single‐port robotic system (Figure ). For a left‐sided condition, the left lateral peritoneum is released or the renal pelvis and ureter are access via the left colon mesentery. For the right side, release the right lateral peritoneum to reveal the renal pelvis and ureter. Open the posterior peritoneum, free and expose the renal pelvis and upper ureter on the affected side to identify the obstruction site (Figure ). Excise the narrowed ureteropelvic junction and make a longitudinal incision of about 2.0 cm on the lateral wall of the ureter (Figure ). Identify the lowest point of the renal pelvis and suture it to the lowest point of the ureter incision (Figure ). Continuously suture the posterior wall of the anastomosis and insert a ureteral stent through the anastomosis in an antegrade manner (Figure ). Ensure the stent reaches the bladder, then continuously suture the anterior wall of the anastomosis and trim excess renal pelvis tissue to form a new anastomosis (Figure ). After completing the anastomosis, furosemide was administered intravenously (0.3 mg/kg) and checked for leakage or folding at the anastomosis site. Flush the surgical area with warm saline, remove any fluid in the abdominal cavity, and ensure no active bleeding in the surgical field. Intermittently suture the mesenteric defect, disconnect the robot from the patient, remove the robotic platform, and close the incision in layers. For UPJO with kidney stones, stone extraction was performed using a flexible ureteroscope during the procedure. All patients had the urinary catheter removed before discharge.
Statistical Analysis Statistical analysis was conducted using SPSS 22.0 software. Demographic and perioperative data were analysed using descriptive statistics. Counts of frequencies were expressed as percentages, and continuous data were presented as medians and interquartile ranges (IQRs).
Results A total of 20 patients with UPJO were included, which included 18 adults and 2 children, 16 males and 4 females, with a male‐to‐female ratio of 4:1. There were 15 cases on the left side and 5 cases on the right side. Patients' ages ranged from 13 to 39 years, with an average age of 26.2 years (IQR, 7.4; 21–35). The median follow‐up time was 4 months. Other demographic and disease characteristics are shown in Table . Through preoperative examinations (including ultrasound, retrograde pyelography, and/or CT scans) and intraoperative findings, the etiological distribution of 20 UPJO patients was as follows: congenital causes account for 55%, idiopathic causes for 35%, and crossing vessels for 10%. One patient had concurrent kidney stones, which were surgically addressed during the procedure. The majority of cases were on the left side (15/20, accounting for 75%). All surgeries were successfully completed without any intraoperative complications or conversions. The operative time ranged from 115 to 225 min. The estimated blood loss ranged from 15 to 80 mL. All patients had a Foley catheter placed during surgery, which was removed before discharge. Additional surgical details are provided in Table . During postoperative recovery, 1 patient (5%) developed a urinary infection and was treated with antibiotics; 1 patient (5%) experienced delayed wound healing; and 2 patients (10%) developed bladder irritation symptoms, which improved after the double J stent was removed. No serious complications were observed. The double J stents were removed between 6 and 8 weeks after surgery. At the last follow‐up, all patients were asymptomatic, with no obstruction on imaging and no requirement for additional procedures or stents (Table ). The median follow‐up time was 4 months.
Discussion The arrival of single‐port robotic surgery systems not only meets the need for minimally invasive procedures, aesthetic results, and speedy recovery but also tackles the technical obstacles associated with traditional single‐port laparoscopic surgery. The feasibility and safety of this system are supported by current literature findings . Among these systems, the American company Intuitive Surgical has developed a dedicated da Vinci SP system that integrates three operating instruments and an observation mirror into a single robotic arm. Each instrument and the observation mirror can be independently articulated by the robotic wrist, eliminating the need for instrument crossing. This innovation, merging robotics with LESS (Laparoendoscopic Single‐Site Surgery), has significantly advanced single‐port surgery in urology. However, the Da Vinci SP system is currently undergoing clinical trials in China and has not yet been widely adopted in clinical practice, which has directly impacted the progression of single‐port robotic surgery in China . The clinical adoption of the domestically produced ‘SHURUI’ single‐port serpentine‐arm robotic surgery system has effectively addressed this challenge. The serpentine arm in the ‘SHURUI’ robotic system is highly flexible and capable of bending within the body. Its dual‐continuum structure enhances the arm's strength, ensuring successful completion of single‐port surgery. Wang et al. initially reported using the ‘SHURUI’ single‐port robot to perform four cases of zero ischaemia partial nephrectomy, thereby preliminarily confirming the safety and efficacy of the ‘SHURUI’ single‐port robotic surgery system . Based on data from a multicenter clinical trial, Zhu et al. reported the safety and effectiveness of the ‘SHURUI’ single‐port robot in performing retroperitoneal partial nephrectomy and adrenalectomy . In this study, the domestically produced ‘SHURUI’ single‐port robot was utilised to perform 20 cases of pyeloplasty. The preliminary results indicate that the procedure was safe and effective, demonstrating satisfactory outcomes in terms of operation time, robot operation time, blood loss, and postoperative improvement of obstruction. In this study, the transabdominal approach was employed for all patients. The optimal operating distance for the surgical single‐port robotic arm ranged from 10 to 15 cm. It is imperative to meticulously deliberate on the optimal location for the incision and to employ continuous muscle relaxation techniques during surgery. The decision was taken to employ an umbilical arc incision, a method that confers benefits such as diminished pain, reduced port‐related complications, faster recovery and improved cosmetic outcomes. In this study, the average operative time for pyeloplasty was 147(IQR, 125–175) minutes, and the overall complication rate was 20% (4/20). Over a median follow‐up period of 4 months, the surgical success rate was 100% (20/20). Marien et al. reported a single‐centre experience involving 149 patients who underwent pyeloplasty using the da Vinci surgical system. They reported an average operation time of 185.2 min, with perioperative complications occurring in 16 patients (10.7%). The radiological and symptomatic success rates were 99.0% and 95.0%, respectively . Consequently, in pyeloplasty, the domestically produced ‘SHURUI’ single‐port robotic system demonstrates comparable surgical feasibility and effectiveness to the Da Vinci surgical system. It must be acknowledged that this study has several limitations. Firstly, due to its early stages, the study involved a small number of cases, lacked long‐term follow‐up, and did not include a control group, only comparisons with similar reports in foreign literature. Secondly, although all cases in this study were performed by experienced robotic surgeons, the expertise and skill level of the surgeons can significantly impact surgical outcomes. Finally, single‐port robotic surgery is characterised by high technical demands, requiring specialised training and experience.
Conclusion The SHURUI single‐port robotic surgery system has been demonstrated to exhibit postoperative benefits analogous to those observed with other robotic technologies, including rapid recovery, minimal surface trauma, and minimal postoperative pain. The ‘SHURUI’ single‐port snake‐arm robotic surgery system has been demonstrated to be safe and effective for the performance of pyeloplasty, with outcomes that have been found to be satisfactory.
All the authors contributed to the study. Data collection and analysis were performed by Xuelian Li, Bin Wu, Bo Li, RuiPing Su, Song Xue, and YongPan An. The first draft of the manuscript was written by RuiXiao Li, and all the authors commented on previous versions of the manuscript. GuoJun Wu and JianXin Ni critically revised the manuscript. All authors have read and approved the final manuscript.
This study was approved by the Ethic Committee of Xi'an People's Hospital (Approval No. 20220019).
The authors declare no conflicts of interest.
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Differential diversity and structure of autotrophs in agricultural soils of Qinghai Province | 84bcafcd-84f5-44f5-97e4-1e30b0e7875d | 11792524 | Microbiology[mh] | The concentration of carbon dioxide in the atmosphere is continuously increasing, posing a threat to global warming. Atmospheric CO 2 is primarily removed by biological CO 2 fixation by terrestrial plants or microbes . Biological systems for CO 2 conversion provide a potential path forward owing to their high application selectivity and adaptability. Moreover, many bacteria can use CO 2 as their sole source of carbon and convert it into value-added products . Autotrophic bacteria that utilize inorganic compounds as electron donors for growth fix CO 2 photosynthetically or chemo-autotrophically even in extreme ecosystems, and affect soil organic carbon sequestration. Among the seven pathways developed by autotrophic bacteria for carbon dioxide fixation, the Calvin-Benson-Bassham (CBB) cycle is the most widely distributed pathway . Ribulose-1,5-bisphosphate carboxylase oxygenase (RubisCO) is the rate-limiting enzyme of the CBB pathway and exists in forms I, II, III, and IV, each with different structures, catalytic properties, and substrate specificities. Among the four forms, form I RubisCO is the most abundant in autotrophic bacteria . The cbbL gene, which encodes a large subunit of RubisCO form I, has been widely used as a functional marker for studying autotrophic CO 2 -fixing bacteria in diverse ecosystems . Agricultural soils have drawn increasing attention as important components of terrestrial ecosystems for carbon fixation during carbon capture and storage with long-term effects on ecosystems. Soil microbial fixation of atmospheric CO 2 notably contributes to the organic C pool in agricultural soils under various management conditions . Previous studies that have focused on cbbL -containing bacteria have demonstrated that soil properties, agronomic management measures, and environmental factors can influence the community composition, abundance, and activity, although the extent to which each factor plays a role has varied among these studies . For example, the predominance of cbbL sequences is associated with Rhizobium leguminosarum , Bradyrhizobium sp., Sinorhizobium meliloti , Ochrobactrum anthropi , and a variety of uncultured cbbL -harboring bacteria from the rhizosphere of Arachis hypogaea . Additionally, cbbL -containing bacterial communities and diversity indices vary with site and plant type in agroecosystem soils . In Qinghai Province, agricultural soils cover an area of approximately 58.97 million ha. Wheat, barley, and oilseed rape are the main crops grown in semiarid regions. Previously, differences in the diversity of the 16S rRNA and ITS1 genes were observed in the rhizosphere soils of oats in different alpine regions . The role of soil microbial autotrophy in the sequestration of carbon dioxide through the CBB pathway in both upland and paddy soils in South China has been highlighted in several studies . However, little is known about the abundance, composition, and activity of autotrophic CO 2 fixation microorganisms in the semiarid alpine region of northwestern China. In the present study, four areas of soil were directly collected from a field in Qinghai Province, China, where wheat, oilseed rape, and barley were planted as major crops once each year. Field sampling was conducted during the flowering and fruiting stages. Autotrophic CO 2 -assimilating bacterial diversity and communities were assessed by cbbL gene amplicon sequencing. This study aimed to determine the effects of different regions and crop types on the abundance, composition, and activity of CO 2 -fixing bacteria in agricultural soil. Field sampling Field sampling in Qinghai Province (36°02′18.36″–37°04′10.24″N, 98°03′40.64″–102°06′08.23″E) was conducted as previously described by Zhou et al. . Briefly, on July 2022, 9, 4, 12, and 15 soil samples were collected from Dulan (DL), Datong (DT), Gonghe (GH), and Huzhu (HZ) counties , respectively. The mean annual precipitation in DL county is 179.1 mm, with a mean annual temperature ranging from 16°C to 27°C. DT county experiences an average annual precipitation of 450–800 mm, with a low temperature of 10°C and a high temperature of 24°C. The GH region has an average high temperature of 23°C, a low temperature of 10°C, and receives between 250 and 420 mm of precipitation. In the HZ region, the mean annual temperature ranges from 16°C to 27°C, with precipitation levels varying from 350 to 650 mm. The cropping system was wheat ( Triticum aestivum , Ta), oilseed rape ( Brassica napus , Bn), and barley ( Hordeum vulgare , Hv), respectively. Considering that environmental factors affect the crop planting area, sites in the same village were chosen to minimize the effects of these factors. Barley was planted narrowly in DT County. Each sample was collected from 5 to 20 cm surface soil using a drill (10 cm in diameter) by mixing five soil cores. The samples for each plot were divided into three parts and stored at 4°C, –20°C, and –80°C for the measurement of soil biogeochemical properties, soil enzymes, and soil DNA extraction. Microbial DNA extraction and Illumina high-throughput sequencing Microbial DNA was extracted from the soil samples using a HiPure soil DNA kit (Azenta) according to the manufacturer’s protocol. The DNA concentration was monitored using the Qubit dsDNA HS Assay Kit. A sequencing library was constructed using a MetaVX library preparation kit (Azenta, Inc., South Plainfield, NJ, USA). The cbbL gene was amplified with primers 595f (5′- GACTTCACCAAAGACGACGA -3′) and 1387r (5′- TCGAACTTGATTTCTTTCCA -3′) . PCR was conducted using the following program: 3 min of denaturation at 94°C, 24 cycles of 5 s at 95°C, 90 s of annealing at 57°C, and 10 s of elongation at 72°C, and a final extension at 72°C for 5 min. Another 25 µL of PCR mixture was prepared with 2.5 µL of TransStart buffer, 2 µL of dNTPs, 1 µL of each primer, 0.5 µL of TransStart Taq DNA polymerase, and 20 ng of template DNA. Indexed adapters were added to each amplicon using a limited-cycle PCR. Subsequently, magnetic beads were used to purify the library. Illumina sequencing and data processing The concentration of PCR product was determined using a microplate reader (Tecan, Infinite 200 Pro), and the amplicon size was checked using agarose gel (1.5%) electrophoresis. Next-generation sequencing was analyzed on an Illumina MiSeq platform (Illumina, San Diego, USA) at Azenta, Inc. (South Plainfield, NJ, USA). Automated cluster generation and 250/300 base paired-end sequencing with dual reads were performed following the manufacturer’s protocol. The raw sequences were extracted, trimmed, and quality screened using Quantitative Insights into Microbial Ecology (QIIME, version 1.9.1). Briefly, quality filtering of the joined sequences was performed, and low-quality sequences (quality score <20, length <200 bp) were discarded. After quality filtering, the sequence data set was used for taxonomic grouping, and unique sequences were aligned to the SILVA 138 database with a 70% confidence threshold. The remaining sequences were binned into operational taxonomic units (OTUs) with a 97% nucleotide sequence similarity cutoff using Vsearch (version 1.9.6). The Bayes algorithm classifier provided by the Ribosomal Database Program (RDP, version 2.2) was used to analyze the representative sequences of OTUs. Based on the OTU analysis results, the Good’s coverage and Alpha-diversity (Shannon, Simpson, Chao1, and Ace) of the autotrophic bacterial communities were calculated using QIIME. In addition, the relative abundances of dominant taxa including the phylum, class, order, family, and genus, were estimated by the proportion of number of reads allocated to a particular taxon to the total obtained sequences. The Venn diagram and the relative abundance of dominant taxa were determined using R software (version 3.3.1). Nonmetric multidimensional scaling (NMDS) was performed using the vegan R package with normalized data. Analysis of similarity (ANOSIM) tests were also conducted to assess the roles of region and crop type in structuring CO 2 -assimilating bacterial communities. The R package was used to cluster samples based on the Bray-Curtis similarity index by using principal coordinates analysis (PCoA). Linear discriminant analysis effect size (LEfSe, version 1.0) was applied to identify the biomarker taxa that explained the differences between different groups using linear discriminant analyses (LDAs = 2). Soil physical and chemical analysis Total protein was extracted from the soil according to the instructions of the RubisCO assay kit (Jiangsu Meimian Industrial Company, Jiangsu, China). Briefly, 1 g of soil was suspended in 9 mL of 0.01 mol/L phosphate-buffered saline (pH 7.2). The mixture was manually homogenized in a mortar and pestle. The extract was centrifuged at 4°C for 15 min at 5,000 rpm. RubisCO activity was monitored at 450 nm by using a BioStach Ready (BioTek Instruments, Inc., Winooski, USA). Reactions in the absence of soil extraction and enzyme-labeled reagents were used as negative controls. Other physical and chemical properties, including pH, soil water content, organic matter, ammonium nitrogen, nitrate nitrogen, total phosphate, effective phosphate, total sulfur, and effective sulfur, were reported in a previous study . Statistical analysis The data are expressed as the mean ± standard deviation. A univariate analysis of variance (ANOVA) was performed to determine between-subject effects in accordance with the general linear model. Correlation analysis was performed between the measured indicators and environmental factors using Pearson test (SPSS 16). Field sampling in Qinghai Province (36°02′18.36″–37°04′10.24″N, 98°03′40.64″–102°06′08.23″E) was conducted as previously described by Zhou et al. . Briefly, on July 2022, 9, 4, 12, and 15 soil samples were collected from Dulan (DL), Datong (DT), Gonghe (GH), and Huzhu (HZ) counties , respectively. The mean annual precipitation in DL county is 179.1 mm, with a mean annual temperature ranging from 16°C to 27°C. DT county experiences an average annual precipitation of 450–800 mm, with a low temperature of 10°C and a high temperature of 24°C. The GH region has an average high temperature of 23°C, a low temperature of 10°C, and receives between 250 and 420 mm of precipitation. In the HZ region, the mean annual temperature ranges from 16°C to 27°C, with precipitation levels varying from 350 to 650 mm. The cropping system was wheat ( Triticum aestivum , Ta), oilseed rape ( Brassica napus , Bn), and barley ( Hordeum vulgare , Hv), respectively. Considering that environmental factors affect the crop planting area, sites in the same village were chosen to minimize the effects of these factors. Barley was planted narrowly in DT County. Each sample was collected from 5 to 20 cm surface soil using a drill (10 cm in diameter) by mixing five soil cores. The samples for each plot were divided into three parts and stored at 4°C, –20°C, and –80°C for the measurement of soil biogeochemical properties, soil enzymes, and soil DNA extraction. Microbial DNA was extracted from the soil samples using a HiPure soil DNA kit (Azenta) according to the manufacturer’s protocol. The DNA concentration was monitored using the Qubit dsDNA HS Assay Kit. A sequencing library was constructed using a MetaVX library preparation kit (Azenta, Inc., South Plainfield, NJ, USA). The cbbL gene was amplified with primers 595f (5′- GACTTCACCAAAGACGACGA -3′) and 1387r (5′- TCGAACTTGATTTCTTTCCA -3′) . PCR was conducted using the following program: 3 min of denaturation at 94°C, 24 cycles of 5 s at 95°C, 90 s of annealing at 57°C, and 10 s of elongation at 72°C, and a final extension at 72°C for 5 min. Another 25 µL of PCR mixture was prepared with 2.5 µL of TransStart buffer, 2 µL of dNTPs, 1 µL of each primer, 0.5 µL of TransStart Taq DNA polymerase, and 20 ng of template DNA. Indexed adapters were added to each amplicon using a limited-cycle PCR. Subsequently, magnetic beads were used to purify the library. The concentration of PCR product was determined using a microplate reader (Tecan, Infinite 200 Pro), and the amplicon size was checked using agarose gel (1.5%) electrophoresis. Next-generation sequencing was analyzed on an Illumina MiSeq platform (Illumina, San Diego, USA) at Azenta, Inc. (South Plainfield, NJ, USA). Automated cluster generation and 250/300 base paired-end sequencing with dual reads were performed following the manufacturer’s protocol. The raw sequences were extracted, trimmed, and quality screened using Quantitative Insights into Microbial Ecology (QIIME, version 1.9.1). Briefly, quality filtering of the joined sequences was performed, and low-quality sequences (quality score <20, length <200 bp) were discarded. After quality filtering, the sequence data set was used for taxonomic grouping, and unique sequences were aligned to the SILVA 138 database with a 70% confidence threshold. The remaining sequences were binned into operational taxonomic units (OTUs) with a 97% nucleotide sequence similarity cutoff using Vsearch (version 1.9.6). The Bayes algorithm classifier provided by the Ribosomal Database Program (RDP, version 2.2) was used to analyze the representative sequences of OTUs. Based on the OTU analysis results, the Good’s coverage and Alpha-diversity (Shannon, Simpson, Chao1, and Ace) of the autotrophic bacterial communities were calculated using QIIME. In addition, the relative abundances of dominant taxa including the phylum, class, order, family, and genus, were estimated by the proportion of number of reads allocated to a particular taxon to the total obtained sequences. The Venn diagram and the relative abundance of dominant taxa were determined using R software (version 3.3.1). Nonmetric multidimensional scaling (NMDS) was performed using the vegan R package with normalized data. Analysis of similarity (ANOSIM) tests were also conducted to assess the roles of region and crop type in structuring CO 2 -assimilating bacterial communities. The R package was used to cluster samples based on the Bray-Curtis similarity index by using principal coordinates analysis (PCoA). Linear discriminant analysis effect size (LEfSe, version 1.0) was applied to identify the biomarker taxa that explained the differences between different groups using linear discriminant analyses (LDAs = 2). Total protein was extracted from the soil according to the instructions of the RubisCO assay kit (Jiangsu Meimian Industrial Company, Jiangsu, China). Briefly, 1 g of soil was suspended in 9 mL of 0.01 mol/L phosphate-buffered saline (pH 7.2). The mixture was manually homogenized in a mortar and pestle. The extract was centrifuged at 4°C for 15 min at 5,000 rpm. RubisCO activity was monitored at 450 nm by using a BioStach Ready (BioTek Instruments, Inc., Winooski, USA). Reactions in the absence of soil extraction and enzyme-labeled reagents were used as negative controls. Other physical and chemical properties, including pH, soil water content, organic matter, ammonium nitrogen, nitrate nitrogen, total phosphate, effective phosphate, total sulfur, and effective sulfur, were reported in a previous study . The data are expressed as the mean ± standard deviation. A univariate analysis of variance (ANOVA) was performed to determine between-subject effects in accordance with the general linear model. Correlation analysis was performed between the measured indicators and environmental factors using Pearson test (SPSS 16). α-diversity of the autotrophic microbial community The Chao1 and Ace indices, which are the two key estimators for calculating the community richness, ranged from 616.63 ± 286.44 to 2,442.06 ± 289.16 and from 602.98 ± 279.67 to 2,523.04 ± 264.80, respectively . The Simpson and Shannon diversity indices ranged from 0.551 ± 0.040 to 0.962 ± 0.007 and from 2.54 ± 0.37 to 6.63 ± 0.29, respectively. High values of the Chao1 and Ace indices were observed for DLBn1, whereas low values were obtained for GHHv2. In contrast, high Simpson and Shannon diversity indexes were observed for HZHv5, whereas low values were observed for DTHv1. The Chao1 and Shannon diversity indices indicated that the diversity of the cbbL gene differed significantly among the 40 soil samples ( P < 0.001). Regions with highly significant ( P < 0.001, ) effects were detected for the Ace, Chao1, Shannon, Simpson, and Goods coverage indices of the cbbL gene. Crop type had the most significant ( P < 0.01) effect on the cbbL gene according to Simpson and Shannon indices. In addition, Simpson and Shannon diversity indices exhibited interactions between region and crop type ( P < 0.05, ). Among the four regions, the Chao1 and Shannon diversity indices in the DL and HZ samples were significantly greater than those in the GH and DT soils ( P < 0.05, ). According to the analysis of the effect of crop type on community composition using one-way ANOVA, no significant differences were observed in the Chao1 or Shannon indices across the three crop groups . The Chao1 and Shannon indices significantly varied in the each region across different crops, as well as in the planted crop across various regions . Except for the DT location, there were no significant differences in α-diversity indexes between barley and wheat soils at the same site. However, in certain sampling location, the Chao1 and Shannon diversity indices varied significantly between oilseed rape and other crop soils. β-diversity of autotrophic microbial community PCoA based on the Bray-Curtis dissimilarity revealed that the cbbL -containing bacterial community extracted from the soil samples differed . The PCoA indicated that the bacterial communities from the GH, DT, and DL regions were more similar than those from the HZ region . However, the results for oilseed rape, wheat, and barley soils mostly overlapped . The distinct distributions of the cbbL -containing bacterial communities were compared among the 40 soil samples using NMDS analysis . The HZ, DL, GH, and DT regions were largely separated ( , ANOSIM, R = 0.75, P = 0.001), revealing a clear distinction in the cbbL -containing bacterial communities by region. Within all three crop groups, the NMDS plot ordination estimated the distribution of cbbL -containing bacterial communities between and within clusters ( , R = –0.008, P = 0.667). However, NMDS ordination plotting revealed a highly significant separation in each region across different crops, as well as in the planted crop across different regions . Autotrophic microbial OTUs Forty samples collected from these four regions were successfully amplified and sequenced. cbbL clone sequences were grouped into OTUs based on a cutoff of 97% sequence similarity. The number of OTUs ranged from 31,068 to 84,984 per soil sample. The average number of OTUs was 55,178.058, and the highest number was observed for DLTa1. A total of 17,290 OTUs were identified, 5 of which (OTU1, OTU2, OTU5, OTU36, and OTU26) were among the 40 soil groups . A total of 537, 410, 386, 361, and 315 OTUs were unique to DLHv3, HZTa4, DLBn1, DLHv1, and HZHv5, respectively. In total, 9,339, 9,245, 5,595, and 2,407 OTUs were obtained from the HZ, DL, GH, and DT soils, respectively . Among the different regions, a large overlap of bacterial OTUs was observed in the GH and HZ soils, whereas the DL, GH, HZ, and DT soils shared 572 OTUs. Furthermore, only 5,359 OTUs were present in the DL soils, 4,299 OTUs were present in the HZ soils, 1,066 OTUs were present in the GH soils, and 363 OTUs were present in the DT soils. Moreover, 11,749, 11,686, and 11,469 OTUs were obtained from the oilseed rape, barley, and wheat soils, respectively . Among the different crops, the three crops shared 6,648 common OTUs, only 2,033 OTUs were detected in oilseed rape soils, 2,035 OTUs were found in wheat soils, and 2,256 OTUs were observed in barley soils. Autotrophic microbial community composition shows a distinct heatmap of the 30 selected dominant OTUs across all the samples. The coverage percentage of the top 30 OTUs varied among the samples. The coverage rates of OTU36, OTU14, OTU12, and OTU6 in the soil samples were 97.5%, 95%, 92.5%, and 90%, respectively. OTU7 and OTU10 had low coverage (25% and 17.5%, respectively). OTU1 was primarily distributed in the HZTa1 and HZHv1 soils. OTU2 was dominant in the DLTa1, DLBn1, and DLHv1 soils. The highest number of OTU3 or OTU7 was observed in the DTHv1 or DTTa1 soils. OTU5 was primarily distributed in the HZTa3 soil, whereas OTU13 was primarily present in the DLBn4 soil. In addition, OTU341 dominated the GHTa2 and GHBn2 soils. The number of taxa at the phylum, class, order, family, and genus levels was calculated. In total, 18 phyla were identified . Proteobacteria and Actinobacteria were detected across all the samples and composed the top two phyla, with relative abundances ranging from 50.87% to 95.44% and from 46.08% to 74.68%, respectively. Differences were observed in the phylum composition within the regional groups . Among the top two phyla, Proteobacteria and Actinobacteria accounted for 71.02% and 32.50%, respectively, of the bacteria in the DL group; 79.11% and 16.17%, respectively, in the HZ group; 60.52% and 29.91%, respectively, in the GH group; and 77.75% and 21.22%, respectively, in the DT group, In addition, the abundance of Proteobacteria in the three crop types was similar , but the abundance of Actinobacteria decreased in the order wheat (33.35%) > oilseed rape (20.85%) > barley (20.06%). A total of 32 classes were identified in this study. A diverse community was observed in each soil sample at the class level . Betaproteobacteria, Gammaproteobacteria, Actinobacteria, Alphaproteobacteria, and Acidithiobacillus were ubiquitous in the soils investigated. The soil indicator classes included mainly Betaproteobacteria, Gammaproteobacteria, Actinobacteria, and Alphaproteobacteria, with relative abundances of 31.85%–84.60%, 31.61%–79.76%, 33.16%–74.68%, and 63.61%, respectively. Notably, variations at the class level were observed in the DL, GH, HZ, and DT regions . The soil in the DL region was dominated by Betaproteobacteria (42.85%), Gammaproteobacteria (18.91%), and Actinobacteria (24.36%), whereas the GH soil was dominated by Betaproteobacteria (26.21%), Gammaproteobacteria (18.42%), Actinobacteria (29.41%), and unclassified classes (14.14%). In the HZ soils, Betaproteobacteria (37.06%), Gammaproteobacteria (32.00%), and Actinobacteria (15.27%) were the three major classes, and in the DT soils, Betaproteobacteria (69.47%) and Actinobacteria (20.96%) were the predominant classes. The three crop types had similar class compositions . Betaproteobacteria dominated 34.81%–42.08% of the bacteria in both samples, followed by Gammaproteobacteria (19.31%–27.97%) and Actinobacteria (19.72%–25.22%). A total of 47 bacterial orders were found, 11 of which were common to the tested soil samples . Nitrosomonadales (31.17%–84.07%), Pseudonocardiale (33.16%–74.68%), Burkholderiales (29.37%–80.04%), and Acidiferrobacterales (25.74%–41.31%) were highly abundant in some soils. Similarly, the GHHv1 soil was dominated by Rhizobiales (57.90%), and the DLBn4 soil was dominated by Thiotrichales (56.44%). A large fraction of these keystone orders were unclassified bacteria related to Gammaproteobacteria in the HZBn2 (30.82%) and GHHv2 (44.97%) soils, while the most abundant were unclassified bacteria associated with Betaproteobacteria in the HZTa4 (27.91%) and HZTa2 (49.39%) soils. In terms of the four regions, diverse order compositions were observed . The three orders Nitrosomonadales, Pseudonocardiales, and Burkholderiales were dominant, with relative abundances of 16.13%, 24.36%, and 25.56%, respectively, in the DL soils. Additionally, Nitrosomonadales (22.06%), Pseudonocardiales (29.41%), and Rhizobiales (12.38%) were dominant in the GH soils, and Nitrosomonadales (21.43%), Pseudonocardiales (15.27%), and Acidiferrobacterales (19.37%) were highly abundant in the HZ soils. The DT soil was dominated mainly by Nitrosomonadales (68.59%) and Pseudonocardiales (20.96%). In contrast, the orders Nitrosomonadales, Pseudonocardiales, Burkholderiales, and Acidiferrobacterales were dominant in all three crop soils . The relative abundance of Pseudonocardiales was highest in wheat soils and lowest in barley soils (25.22% and 19.72%, respectively), whereas the abundance of Nitrosomonadales was highest in wheat soils and lowest in oilseed rape soils (23.80% and 22.08%, respectively). These changes indicated that the effect of region on the order community was more evident than on the crop groups. A total of 78 families were identified, and 11 common families were recorded among the 40 soils . Members of Pseudonocardiaceae (27.75%–74.68%), Thiobacillaceae (36.72%–83.56%), Acidiferrobacteraceae (25.74%–41.31%), Comamonadaceae (25.71%–70.22%), Bradyrhizobiaceae (51.78%–57.90%), Nitrosomonadaceae (44.61%–51.05%), Thiotrichaceae (56.37%), and unclassified family (34.37%–59.57%) were dominant in the 10, 10, 5, 4, 2, 2, 1, and 6 soil samples, respectively. Large differences were apparent in the taxonomic distribution of CO 2 -fixing bacteria in the four regions at the family level . The four predominant families in the DL soil were Pseudonocardiaceae (24.36%), Comamonadaceae (21.80%), Nitrosomonadaceae (13.55%), and unclassified bacteria (11.87%). The four families Pseudonocardiaceae (29.41%), Thiobacillaceae (19.99%), unclassified family (19.52%), and Bradyrhizobiaceae (12.35%) were dominant in the GH soils. The major families in the HZ soils were unclassified bacteria (19.87%), Acidiferrobacteraceae (19.37%), Thiobacillaceae (18.03%), and Pseudonocardiaceae (15.27%). Thiobacillaceae (65.82%) and Pseudonocardiaceae (20.96%) were predominant in the DT soils. In addition, the five dominant families, Pseudonocardiaceae, Thiobacillaceae, unclassified bacteria, Acidiferrobacteraceae, and Comamonadaceae accounted for abundances of 19.72%–25.22%, 15.39%–18.42%, 14.33%–17.14%, 9.79%–12.18%, and 9.15%–10.27%, respectively, of the bacteria in all three crop soils . Thus, region had a stronger effect on these families than crop type. In total, 134 genera were identified in this study. The 10 common genera widely distributed in all 40 samples were Pseudonocardia , Sulfuritortus , Sulfuricaulis , Nitrosomonas , Thiohalobacter , Nitrobacter , Thiobacillus , Elioraea , Thioalkalivibrio , and Thiomonas . The genera Pseudonocardia , Sulfuritortus , Sulfuricaulis , Nitrosomonas , Hydrogenophaga , and unclassified genera were predominant, with the relative abundances of 17.76%–74.67%, 36.63%–83.55%, 25.74%–41.30%, 44.03%–51.56%, 24.56%–49.77%, and 27.39%–59.96%, respectively, in 11, 10, 6, 3, 3, and 5 soil samples, respectively. Additionally, the genus Beggiatoa was characteristic of DLBn4 (56.37%) soil, whereas Thiohalobacter was characteristic of HZBn2 (26.66%) soil. The genus composition in the four regions showed greater variation than in the three crop soils . In the DL soils, Pseudonocardia (22.36%), an unclassified genus (16.61%), Hydrogenophaga (16.72%), and Nitrosomonas (13.11%) were the major genera. The dominant genera in the GH soils were Pseudonocardia (29.40%), Sulfuritortus (18.97%), unclassified bacteria (18.46%), and Nitrobacter (12.34%). The predominant genera were Sulfuricaulis (19.36%), Sulfuritortus (17.84%), unclassified bacteria (16.47%), and Pseudonocardia (15.27%) in the HZ soils and Sulfuritortus (65.79%) and Pseudonocardia (20.96%) in the DT soils. The four genera Pseudonocardia , Sulfuritortus , unclassified bacteria, and Sulfuricaulis were dominant across all three crop soils, with relative abundances of 19.72%–25.22%, 14.66%–17.65%, 14.10%–17.62%, and 9.76%–12.16%, respectively. Differences in the marked taxa of soil CO 2 -assimilating bacteria Autotrophic microbial community features in the soils that were significantly different between groups were identified using LEfSe analysis. A total of 31, 27, 10, and 8 significant biomarkers were identified in the four regions collected from the HZ, DL, DT, and GH, respectively . The HZ group was enriched with bacterial lineages at different taxonomic levels, and included the phyla Proteobacteria, Firmicutes, and Streptophyta; classes Gammaproteobacteria, Bacilli, Acidithiobacillia and Rubrobacteria; orders Chromatiales, Acidiferrobacterales, Lactobacillales, Acidithiobacillales, and Gaiellales; families Acidiferrobacteraceae, Streptococcaceae, Sterolibacteriaceae, Piscirickettsiaceae, Chromatiaceae, Gaiellaceae, Acidithiobacillaceae, and Methylophilaceae; and genera Sulfuricaulis , Streptococcus , Sulfurisoma , Thiomicrorhabdus , Actibacterium , Gaiella , Acidihalobacter , Acidithiobacillus , Methylobacillus , and Maritimibacter . Bacterial lineages such as class Alphaproteobacteria; order Rhizobiales; families Bradyrhizobiaceae, Gallionellaceae, and Ectothiorhodospiraceae; and genera Nitrobacter , Sulfuriferula , and Marichromatium were enriched in the GH group. Bacterial lineages including class Betaproteobacteriaceae; orders Nitrosomonadales, Enterobacterales, and Rhodospirillales; families Thiobacillaceae and Enterobacteriaceae; and genera Sulfuritortus , Klebsiella , Ectothiorhodosinus , and Thiothrix were enriched in the DT group. The DL soil was enriched with bacterial lineages such as class Hydrogenophilalia; orders Thiotrichales, Hydrogenophilales, Pseudomonadales, Rhodobacterales, and Ferrovales; families Comamonadaceae, Nitrosomonadaceae, Pseudomonadaceae, Rhodobacteraceae, Ferrovaceae, and Burkholderiaceae; and genera Hydrogenophaga , Nitrosomonas , Beggiatoa , Limnohabitans, Pseudomonas , Candidatus Nitrotoga , Thiobacillus , Thioalkalivibrio , Bradyrhizobium , Nitrosospira , Serpentinomonas , Ferrovum , and Polynucleobacter . The variation of enriched autotrophs in each region was identified at the class, order, family, and genus levels . The relative abundances of bacterial lineages exhibited the most differences in the planted crop across different regions . However, no significant biomarkers were detected in any of the three crop groups. Region and crop type affected the abundance of autotrophic bacteria and RubisCO activity Significant ( P < 0.05, P < 0.001, ) regional effects were detected for soil RubisCO activity and some autotrophic bacterial genera, such as Sulfuritortus , Sulfuricaulis , Hydrogenophaga , Nitrobacter , Nitrosomonas , Thiohalobacter , and Beggiatoa . In addition, some interactions were observed between region and crop type for Sulfuritortus , Nitrobacter , Thiohalobacter , and Beggiatoa ( P < 0.05). The RubisCO activities of all the soils ranged from 0.81 ± 0.08 to 1.44 ± 0.15 U/g soil and were 1.94 times greater in the DLBn1 soil than in the DLBn3 soil . RubisCO activity in the HZ region was significantly greater than in the other three soil samples ( P < 0.001) , with no significant difference among the three crop types . Relationships among selected autotrophic bacterial genera, indicators of cbbL gene, and soil properties The correlations among the selected autotrophic bacterial genera, autotrophic bacterial properties, and selected soil factors were investigated using Pearson correlation analysis . The relative abundance of Sulfuritortus was negatively correlated with the autotrophic bacterial Chao1 and Ace ( P < 0.05), and Simpson, Shannon, and altitude ( P < 0.01), but positively correlated with organic matter, total phosphate, and total sulfur levels ( P < 0.05). Hydrogenophaga was positively associated with the Ace, Shannon, altitude, and ammonium nitrogen content ( P < 0.05, P < 0.01), but negatively correlated with total phosphate ( P < 0.05). In addition, Limnohabitans was the most positively correlated with Shannon and ammonium nitrogen, but Pseudonocardia was the most negatively correlated with RubisCO activity ( P < 0.01) and ammonium nitrogen ( P < 0.05). The abundances of both Sulfuricaulis and Thiohalobacter were positively correlated with total phosphate, whereas the abundance of Beggiatoa was negatively correlated with total phosphate ( P < 0.05). The unclassified genera exhibited a positive correlation with Shannon, Simpson, altitude, and ammonium nitrogen, but a negative relationship with the soil water content, organic matter content, and effective phosphate ( P < 0.05). No significant relationships were detected between the selected soil properties and the α-diversity indices of the cbbL gene . The Chao1 and Ace indices, which are the two key estimators for calculating the community richness, ranged from 616.63 ± 286.44 to 2,442.06 ± 289.16 and from 602.98 ± 279.67 to 2,523.04 ± 264.80, respectively . The Simpson and Shannon diversity indices ranged from 0.551 ± 0.040 to 0.962 ± 0.007 and from 2.54 ± 0.37 to 6.63 ± 0.29, respectively. High values of the Chao1 and Ace indices were observed for DLBn1, whereas low values were obtained for GHHv2. In contrast, high Simpson and Shannon diversity indexes were observed for HZHv5, whereas low values were observed for DTHv1. The Chao1 and Shannon diversity indices indicated that the diversity of the cbbL gene differed significantly among the 40 soil samples ( P < 0.001). Regions with highly significant ( P < 0.001, ) effects were detected for the Ace, Chao1, Shannon, Simpson, and Goods coverage indices of the cbbL gene. Crop type had the most significant ( P < 0.01) effect on the cbbL gene according to Simpson and Shannon indices. In addition, Simpson and Shannon diversity indices exhibited interactions between region and crop type ( P < 0.05, ). Among the four regions, the Chao1 and Shannon diversity indices in the DL and HZ samples were significantly greater than those in the GH and DT soils ( P < 0.05, ). According to the analysis of the effect of crop type on community composition using one-way ANOVA, no significant differences were observed in the Chao1 or Shannon indices across the three crop groups . The Chao1 and Shannon indices significantly varied in the each region across different crops, as well as in the planted crop across various regions . Except for the DT location, there were no significant differences in α-diversity indexes between barley and wheat soils at the same site. However, in certain sampling location, the Chao1 and Shannon diversity indices varied significantly between oilseed rape and other crop soils. PCoA based on the Bray-Curtis dissimilarity revealed that the cbbL -containing bacterial community extracted from the soil samples differed . The PCoA indicated that the bacterial communities from the GH, DT, and DL regions were more similar than those from the HZ region . However, the results for oilseed rape, wheat, and barley soils mostly overlapped . The distinct distributions of the cbbL -containing bacterial communities were compared among the 40 soil samples using NMDS analysis . The HZ, DL, GH, and DT regions were largely separated ( , ANOSIM, R = 0.75, P = 0.001), revealing a clear distinction in the cbbL -containing bacterial communities by region. Within all three crop groups, the NMDS plot ordination estimated the distribution of cbbL -containing bacterial communities between and within clusters ( , R = –0.008, P = 0.667). However, NMDS ordination plotting revealed a highly significant separation in each region across different crops, as well as in the planted crop across different regions . Forty samples collected from these four regions were successfully amplified and sequenced. cbbL clone sequences were grouped into OTUs based on a cutoff of 97% sequence similarity. The number of OTUs ranged from 31,068 to 84,984 per soil sample. The average number of OTUs was 55,178.058, and the highest number was observed for DLTa1. A total of 17,290 OTUs were identified, 5 of which (OTU1, OTU2, OTU5, OTU36, and OTU26) were among the 40 soil groups . A total of 537, 410, 386, 361, and 315 OTUs were unique to DLHv3, HZTa4, DLBn1, DLHv1, and HZHv5, respectively. In total, 9,339, 9,245, 5,595, and 2,407 OTUs were obtained from the HZ, DL, GH, and DT soils, respectively . Among the different regions, a large overlap of bacterial OTUs was observed in the GH and HZ soils, whereas the DL, GH, HZ, and DT soils shared 572 OTUs. Furthermore, only 5,359 OTUs were present in the DL soils, 4,299 OTUs were present in the HZ soils, 1,066 OTUs were present in the GH soils, and 363 OTUs were present in the DT soils. Moreover, 11,749, 11,686, and 11,469 OTUs were obtained from the oilseed rape, barley, and wheat soils, respectively . Among the different crops, the three crops shared 6,648 common OTUs, only 2,033 OTUs were detected in oilseed rape soils, 2,035 OTUs were found in wheat soils, and 2,256 OTUs were observed in barley soils. shows a distinct heatmap of the 30 selected dominant OTUs across all the samples. The coverage percentage of the top 30 OTUs varied among the samples. The coverage rates of OTU36, OTU14, OTU12, and OTU6 in the soil samples were 97.5%, 95%, 92.5%, and 90%, respectively. OTU7 and OTU10 had low coverage (25% and 17.5%, respectively). OTU1 was primarily distributed in the HZTa1 and HZHv1 soils. OTU2 was dominant in the DLTa1, DLBn1, and DLHv1 soils. The highest number of OTU3 or OTU7 was observed in the DTHv1 or DTTa1 soils. OTU5 was primarily distributed in the HZTa3 soil, whereas OTU13 was primarily present in the DLBn4 soil. In addition, OTU341 dominated the GHTa2 and GHBn2 soils. The number of taxa at the phylum, class, order, family, and genus levels was calculated. In total, 18 phyla were identified . Proteobacteria and Actinobacteria were detected across all the samples and composed the top two phyla, with relative abundances ranging from 50.87% to 95.44% and from 46.08% to 74.68%, respectively. Differences were observed in the phylum composition within the regional groups . Among the top two phyla, Proteobacteria and Actinobacteria accounted for 71.02% and 32.50%, respectively, of the bacteria in the DL group; 79.11% and 16.17%, respectively, in the HZ group; 60.52% and 29.91%, respectively, in the GH group; and 77.75% and 21.22%, respectively, in the DT group, In addition, the abundance of Proteobacteria in the three crop types was similar , but the abundance of Actinobacteria decreased in the order wheat (33.35%) > oilseed rape (20.85%) > barley (20.06%). A total of 32 classes were identified in this study. A diverse community was observed in each soil sample at the class level . Betaproteobacteria, Gammaproteobacteria, Actinobacteria, Alphaproteobacteria, and Acidithiobacillus were ubiquitous in the soils investigated. The soil indicator classes included mainly Betaproteobacteria, Gammaproteobacteria, Actinobacteria, and Alphaproteobacteria, with relative abundances of 31.85%–84.60%, 31.61%–79.76%, 33.16%–74.68%, and 63.61%, respectively. Notably, variations at the class level were observed in the DL, GH, HZ, and DT regions . The soil in the DL region was dominated by Betaproteobacteria (42.85%), Gammaproteobacteria (18.91%), and Actinobacteria (24.36%), whereas the GH soil was dominated by Betaproteobacteria (26.21%), Gammaproteobacteria (18.42%), Actinobacteria (29.41%), and unclassified classes (14.14%). In the HZ soils, Betaproteobacteria (37.06%), Gammaproteobacteria (32.00%), and Actinobacteria (15.27%) were the three major classes, and in the DT soils, Betaproteobacteria (69.47%) and Actinobacteria (20.96%) were the predominant classes. The three crop types had similar class compositions . Betaproteobacteria dominated 34.81%–42.08% of the bacteria in both samples, followed by Gammaproteobacteria (19.31%–27.97%) and Actinobacteria (19.72%–25.22%). A total of 47 bacterial orders were found, 11 of which were common to the tested soil samples . Nitrosomonadales (31.17%–84.07%), Pseudonocardiale (33.16%–74.68%), Burkholderiales (29.37%–80.04%), and Acidiferrobacterales (25.74%–41.31%) were highly abundant in some soils. Similarly, the GHHv1 soil was dominated by Rhizobiales (57.90%), and the DLBn4 soil was dominated by Thiotrichales (56.44%). A large fraction of these keystone orders were unclassified bacteria related to Gammaproteobacteria in the HZBn2 (30.82%) and GHHv2 (44.97%) soils, while the most abundant were unclassified bacteria associated with Betaproteobacteria in the HZTa4 (27.91%) and HZTa2 (49.39%) soils. In terms of the four regions, diverse order compositions were observed . The three orders Nitrosomonadales, Pseudonocardiales, and Burkholderiales were dominant, with relative abundances of 16.13%, 24.36%, and 25.56%, respectively, in the DL soils. Additionally, Nitrosomonadales (22.06%), Pseudonocardiales (29.41%), and Rhizobiales (12.38%) were dominant in the GH soils, and Nitrosomonadales (21.43%), Pseudonocardiales (15.27%), and Acidiferrobacterales (19.37%) were highly abundant in the HZ soils. The DT soil was dominated mainly by Nitrosomonadales (68.59%) and Pseudonocardiales (20.96%). In contrast, the orders Nitrosomonadales, Pseudonocardiales, Burkholderiales, and Acidiferrobacterales were dominant in all three crop soils . The relative abundance of Pseudonocardiales was highest in wheat soils and lowest in barley soils (25.22% and 19.72%, respectively), whereas the abundance of Nitrosomonadales was highest in wheat soils and lowest in oilseed rape soils (23.80% and 22.08%, respectively). These changes indicated that the effect of region on the order community was more evident than on the crop groups. A total of 78 families were identified, and 11 common families were recorded among the 40 soils . Members of Pseudonocardiaceae (27.75%–74.68%), Thiobacillaceae (36.72%–83.56%), Acidiferrobacteraceae (25.74%–41.31%), Comamonadaceae (25.71%–70.22%), Bradyrhizobiaceae (51.78%–57.90%), Nitrosomonadaceae (44.61%–51.05%), Thiotrichaceae (56.37%), and unclassified family (34.37%–59.57%) were dominant in the 10, 10, 5, 4, 2, 2, 1, and 6 soil samples, respectively. Large differences were apparent in the taxonomic distribution of CO 2 -fixing bacteria in the four regions at the family level . The four predominant families in the DL soil were Pseudonocardiaceae (24.36%), Comamonadaceae (21.80%), Nitrosomonadaceae (13.55%), and unclassified bacteria (11.87%). The four families Pseudonocardiaceae (29.41%), Thiobacillaceae (19.99%), unclassified family (19.52%), and Bradyrhizobiaceae (12.35%) were dominant in the GH soils. The major families in the HZ soils were unclassified bacteria (19.87%), Acidiferrobacteraceae (19.37%), Thiobacillaceae (18.03%), and Pseudonocardiaceae (15.27%). Thiobacillaceae (65.82%) and Pseudonocardiaceae (20.96%) were predominant in the DT soils. In addition, the five dominant families, Pseudonocardiaceae, Thiobacillaceae, unclassified bacteria, Acidiferrobacteraceae, and Comamonadaceae accounted for abundances of 19.72%–25.22%, 15.39%–18.42%, 14.33%–17.14%, 9.79%–12.18%, and 9.15%–10.27%, respectively, of the bacteria in all three crop soils . Thus, region had a stronger effect on these families than crop type. In total, 134 genera were identified in this study. The 10 common genera widely distributed in all 40 samples were Pseudonocardia , Sulfuritortus , Sulfuricaulis , Nitrosomonas , Thiohalobacter , Nitrobacter , Thiobacillus , Elioraea , Thioalkalivibrio , and Thiomonas . The genera Pseudonocardia , Sulfuritortus , Sulfuricaulis , Nitrosomonas , Hydrogenophaga , and unclassified genera were predominant, with the relative abundances of 17.76%–74.67%, 36.63%–83.55%, 25.74%–41.30%, 44.03%–51.56%, 24.56%–49.77%, and 27.39%–59.96%, respectively, in 11, 10, 6, 3, 3, and 5 soil samples, respectively. Additionally, the genus Beggiatoa was characteristic of DLBn4 (56.37%) soil, whereas Thiohalobacter was characteristic of HZBn2 (26.66%) soil. The genus composition in the four regions showed greater variation than in the three crop soils . In the DL soils, Pseudonocardia (22.36%), an unclassified genus (16.61%), Hydrogenophaga (16.72%), and Nitrosomonas (13.11%) were the major genera. The dominant genera in the GH soils were Pseudonocardia (29.40%), Sulfuritortus (18.97%), unclassified bacteria (18.46%), and Nitrobacter (12.34%). The predominant genera were Sulfuricaulis (19.36%), Sulfuritortus (17.84%), unclassified bacteria (16.47%), and Pseudonocardia (15.27%) in the HZ soils and Sulfuritortus (65.79%) and Pseudonocardia (20.96%) in the DT soils. The four genera Pseudonocardia , Sulfuritortus , unclassified bacteria, and Sulfuricaulis were dominant across all three crop soils, with relative abundances of 19.72%–25.22%, 14.66%–17.65%, 14.10%–17.62%, and 9.76%–12.16%, respectively. 2 -assimilating bacteria Autotrophic microbial community features in the soils that were significantly different between groups were identified using LEfSe analysis. A total of 31, 27, 10, and 8 significant biomarkers were identified in the four regions collected from the HZ, DL, DT, and GH, respectively . The HZ group was enriched with bacterial lineages at different taxonomic levels, and included the phyla Proteobacteria, Firmicutes, and Streptophyta; classes Gammaproteobacteria, Bacilli, Acidithiobacillia and Rubrobacteria; orders Chromatiales, Acidiferrobacterales, Lactobacillales, Acidithiobacillales, and Gaiellales; families Acidiferrobacteraceae, Streptococcaceae, Sterolibacteriaceae, Piscirickettsiaceae, Chromatiaceae, Gaiellaceae, Acidithiobacillaceae, and Methylophilaceae; and genera Sulfuricaulis , Streptococcus , Sulfurisoma , Thiomicrorhabdus , Actibacterium , Gaiella , Acidihalobacter , Acidithiobacillus , Methylobacillus , and Maritimibacter . Bacterial lineages such as class Alphaproteobacteria; order Rhizobiales; families Bradyrhizobiaceae, Gallionellaceae, and Ectothiorhodospiraceae; and genera Nitrobacter , Sulfuriferula , and Marichromatium were enriched in the GH group. Bacterial lineages including class Betaproteobacteriaceae; orders Nitrosomonadales, Enterobacterales, and Rhodospirillales; families Thiobacillaceae and Enterobacteriaceae; and genera Sulfuritortus , Klebsiella , Ectothiorhodosinus , and Thiothrix were enriched in the DT group. The DL soil was enriched with bacterial lineages such as class Hydrogenophilalia; orders Thiotrichales, Hydrogenophilales, Pseudomonadales, Rhodobacterales, and Ferrovales; families Comamonadaceae, Nitrosomonadaceae, Pseudomonadaceae, Rhodobacteraceae, Ferrovaceae, and Burkholderiaceae; and genera Hydrogenophaga , Nitrosomonas , Beggiatoa , Limnohabitans, Pseudomonas , Candidatus Nitrotoga , Thiobacillus , Thioalkalivibrio , Bradyrhizobium , Nitrosospira , Serpentinomonas , Ferrovum , and Polynucleobacter . The variation of enriched autotrophs in each region was identified at the class, order, family, and genus levels . The relative abundances of bacterial lineages exhibited the most differences in the planted crop across different regions . However, no significant biomarkers were detected in any of the three crop groups. Significant ( P < 0.05, P < 0.001, ) regional effects were detected for soil RubisCO activity and some autotrophic bacterial genera, such as Sulfuritortus , Sulfuricaulis , Hydrogenophaga , Nitrobacter , Nitrosomonas , Thiohalobacter , and Beggiatoa . In addition, some interactions were observed between region and crop type for Sulfuritortus , Nitrobacter , Thiohalobacter , and Beggiatoa ( P < 0.05). The RubisCO activities of all the soils ranged from 0.81 ± 0.08 to 1.44 ± 0.15 U/g soil and were 1.94 times greater in the DLBn1 soil than in the DLBn3 soil . RubisCO activity in the HZ region was significantly greater than in the other three soil samples ( P < 0.001) , with no significant difference among the three crop types . cbbL gene, and soil properties The correlations among the selected autotrophic bacterial genera, autotrophic bacterial properties, and selected soil factors were investigated using Pearson correlation analysis . The relative abundance of Sulfuritortus was negatively correlated with the autotrophic bacterial Chao1 and Ace ( P < 0.05), and Simpson, Shannon, and altitude ( P < 0.01), but positively correlated with organic matter, total phosphate, and total sulfur levels ( P < 0.05). Hydrogenophaga was positively associated with the Ace, Shannon, altitude, and ammonium nitrogen content ( P < 0.05, P < 0.01), but negatively correlated with total phosphate ( P < 0.05). In addition, Limnohabitans was the most positively correlated with Shannon and ammonium nitrogen, but Pseudonocardia was the most negatively correlated with RubisCO activity ( P < 0.01) and ammonium nitrogen ( P < 0.05). The abundances of both Sulfuricaulis and Thiohalobacter were positively correlated with total phosphate, whereas the abundance of Beggiatoa was negatively correlated with total phosphate ( P < 0.05). The unclassified genera exhibited a positive correlation with Shannon, Simpson, altitude, and ammonium nitrogen, but a negative relationship with the soil water content, organic matter content, and effective phosphate ( P < 0.05). No significant relationships were detected between the selected soil properties and the α-diversity indices of the cbbL gene . The cbbL gene is a key gene that is usually used as an index for evaluating autotrophic potential. The present study showed variations in the diversity, structure, and activity of soil autotrophic CO 2 -fixing bacteria among four agricultural regions and three crop types. The effect of region on these changes was more evident than on the other crop groups. Differential diversity of soil autotrophic CO 2 -fixing bacteria between regions and crop types The Chao1 and Shannon diversity indices of the three crop groups from all four regions did not significantly differ, indicating comparable bacterial diversity in the wheat, barley, and oilseed rape soils. Besides, the α-diversity indices were similar between barley and wheat soils from the same site. These results disagree with the findings of Yuan et al. , who reported that in the Pantang Agroecosystem, the species richness, Shannon-Wiener index, and evenness of cbbL -containing bacteria in rice-rice management soil were greater than those in rice-wheat and wheat-corn rotation soils. These inconsistent results may be related to geography. Whereas, in certain sampling locations, the Chao1 and Shannon diversity indices varied significantly between oilseed rape and other crop soils. The Shannon-Wiener index and Pielou index of cbbL -containing bacteria varied significantly among the four rice soils from four different regions . The Chao1 and Shannon diversity indices for wheat, oilseed rape, and barley soils from the four regions differed significantly. Additionally, the NMDS ordination showed dissimilar plots of the four regions that denoted variations in the bacterial community, and similar plots of the three crop soils from the four regions. A greater autotrophic microbial α-diversity was observed in the DL and HZ samples than in the GH and DT soils, suggesting distinct diversity in the four regions. Generally, the autotrophic bacterial diversity varies with soil conditions, such as pH, total organic carbon, and nitrogen content . For instance, the Chao1 and Shannon indices of autotrophic bacteria at the study sites were negatively correlated with soil organic carbon and total nitrogen . In contrast, there was no significant relationship between the soil physiochemical parameters and the diversity of the cbbL -containing bacteria in the present study. This was also observed for different land use types . These results suggest that some soil properties do not affect the biodiversity of the cbbL -containing bacteria. Differential structure of soil autotrophic CO 2 -fixing bacteria between regions and crop types Carbon fixation was genetically monitored using the cbbL gene marker, which encodes the key photosynthesis related enzyme RubisCO. The distribution and quantification of cbbL gene-containing bacteria in terrestrial ecosystems have largely focused on agricultural bulk soil . The results showed the number of shared and unique OTUs among the 40 soil samples, four regional groups, and three crop types. The four paddy soils from the four different regions had common dominant terminal restriction fragments (58 and 125 bp). In addition, some soils have common or unique dominant microbial populations . The predominant microbial populations in the four paddy soils from the four different regions varied, and most of these OTUs were distantly related to known sequences . Furthermore, our obtained sequences were mostly assigned to Proteobacteria and Actinobacteria, which commonly exist in farmland soils . Long et al. and Liu et al. identified Proteobacteria and Actinobacteria as the dominant phyla in paddy soils from five sites and four sites in South China, respectively. In addition, our present study indicated a high diversity of autotrophic bacterial taxa in the four soil regions, which is consistent with previous findings . The cbbL gene sequences at the genus level were assigned mainly to Bradyrhizobium , Azospirillum , Rhodopseudomonas , Variovorax , Methylibium , and Pseudonocardia . The high abundances of the autotrophic bacterial dominant genera Xanthobacter , Bradyrhizobium , Aminobacter , and Nitrosospira were detected in maize soil . The relative percentages of the dominant autotrophic bacterial phyla, classes, and genera differed among the paddy soils from five sites in South China, in which the values for Rhodoferax varied from 0.006 to 0.15 . In the present study, the 10 most common genera among the samples were Pseudonocardia , Sulfuritortus , Sulfuricaulis , Nitrosomonas , Thiohalobacter , Nitrobacter , Thiobacillus , Elioraea , Thioalkalivibrio , and Thiomonas . The dominant genera Pseudonocardia , Sulfuritortus , Sulfuricaulis , and Nitrosomonas varied greatly among the four soil regions, and are involved in the geochemical cycling of sulfur and nitrogen. Similarly, at the species level, the bacterial phylotypes exhibited diverse distribution patterns. The cbbL gene sequence obtained from groundnut rhizospheric soil contained the most Ochrobactrum and Rhizobium strains and included functional groups such as R. leguminosarum , Bradyrhizobium japonicum , S. meliloti , O. anthropi , Acidithiomicrobium sp., and Rubrivivax gelatinosus , which significantly contribute to the C or N cycles, and sulfur, CO-, and H 2 oxidation . Tolli and King observed distinct soil lithotrophic soil communities associated with land use and crop type (cotton and peanut) in agroecosystems. Yuan et al. reported that Mycobacterium sp., Rhodopseudomonas palustris , B. japonicum , Ralstonia eutropha , and Alcaligenes eutrophus were detected in all soil samples and composed the majority of the cbbL -containing bacterial community under different land uses, whereas Thiobacillus denitrificans , Nitrobacter winogradskyi , and N. vulgaris composed only a small part of the total microbial community. In addition, the cbbL -containing bacterial community composition in double rice soil differed from that in wheat-corn and rice-wheat rotation soils from the Pantang Agroecosystem . Similarly, Wu et al. reported that R. palustris , B. japonicum , R. gelatinosus , and R. eutropha were distributed in rice and corn soils from different geographical regions in China, and that these species could fix CO 2 . However, Acidiphilium multivorum and Synechococcus sp. were detected only in corn soil, and the T. alkaliphila strain ALgr 6 sp. was found only in rice soils. Pseudonocardia sp., S. calidifontis , S. limicola , Nitrobacter sp., T. thiocyanaticus , N. marina , Elioraea sp., N. hamburgensis , and Thiobacillus sp. were detected in the soils investigated. N. marina , Elioraea sp. YIM 72297, N. hamburgensis , and Thiobacillus sp. 63–78 composed only a small portion of the total microbial community. In particular, the cbbL -containing bacterial community compositions of the four regions were diverse, but the cbbL -containing populations of the three crop soils were similar. Furthermore, differential indicator groups were present in the four soil regions but not in the three crop-type soils. The dominant microbial groups in this study were quite different from those in paddy soil in South China and rice and corn soils in distinct geographical regions . These findings indicate that the distribution of the microbial community varies among different geographic locations. Various bacterial populations containing cbbL were selected in response to these variables. The obtained cbbL clone sequences were not closely affiliated with known cultured autotrophic bacteria and showed close proximity to uncultured bacteria retrieved from differently managed agricultural systems, agroecosystems, arid and semiarid soils . At present, the ecological roles of novel soil lithotrophs remain largely unknown . These taxa are affiliated with new CO 2 -fixing bacteria, that have not yet been explored. The abundance and diversity of soil autotrophic bacteria are key factors for carbon sequestration . Shifts in autotrophic microorganisms with diverse metabolic strategies and activities may cause changes in CO 2 fixation functions. The current study demonstrated that changes in autotrophic bacterial community composition can accurately account for the variation in the soil C fixation rate compared to that in abundance and α-diversity. In the present study, organic matter, total phosphate, total sulfur, and ammonium nitrogen were found to have positive or negative relationships with the abundances of Sulfuritortus , Sulfuricaulis , Thiohalobacter , Limnohabitans , Pseudonocardia , Beggiatoa , or Hydrogenophaga . Similarly, Yuan et al. also reported that total nitrogen and soil organic carbon were significantly correlated with the composition of the cbbL -containing bacteria in four different land use soils. Moreover, the CO 2 -fixing bacterial community was significantly affected by seven selected soil factors, such as total organic carbon, total sulfur, and ammonium nitrogen . Differences in RubisCO activities between regions and crop types RubisCO activities are greater in paddy soils than in upland soils, and RubisCO activities differ significantly among paddy soils in different geographical regions . Wu et al. reported that the RubisCO activities differed among rice-rice, rice-rapeseed, and rapeseed-corn rotated soils, with the highest activities occurring in rice-rice cropping systems. In the present study, RubisCO activity likely differed across different regions, but these values were similar among the three crop types from the four countries. This inconsistency can be attributed to differences in the geographical and cbbL -containing bacterial community compositions. Future research using stable isotope tracking is warranted to verify the causal links among the soil bacterial community, RubisCO activity, and CO 2 emissions. Conclusions Similar cbbL -bearing bacterial communities were observed among the three crop soils based on Chao1 and Shannon diversity indices, ANOSIM, LEfSe analysis, and the relative abundances of dominant taxa. However, significant differences in the cbbL -carrying bacterial community were observed between the four site pairs, indicating the roles of both latitude and longitude in structuring agroecosystem CO 2 -assimilating bacterial communities. The effect of region on RubisCO activity was more evident than on RubisCO activity in crop groups. The composition of the autotrophic bacterial community was significantly related to several soil properties. 2 -fixing bacteria between regions and crop types The Chao1 and Shannon diversity indices of the three crop groups from all four regions did not significantly differ, indicating comparable bacterial diversity in the wheat, barley, and oilseed rape soils. Besides, the α-diversity indices were similar between barley and wheat soils from the same site. These results disagree with the findings of Yuan et al. , who reported that in the Pantang Agroecosystem, the species richness, Shannon-Wiener index, and evenness of cbbL -containing bacteria in rice-rice management soil were greater than those in rice-wheat and wheat-corn rotation soils. These inconsistent results may be related to geography. Whereas, in certain sampling locations, the Chao1 and Shannon diversity indices varied significantly between oilseed rape and other crop soils. The Shannon-Wiener index and Pielou index of cbbL -containing bacteria varied significantly among the four rice soils from four different regions . The Chao1 and Shannon diversity indices for wheat, oilseed rape, and barley soils from the four regions differed significantly. Additionally, the NMDS ordination showed dissimilar plots of the four regions that denoted variations in the bacterial community, and similar plots of the three crop soils from the four regions. A greater autotrophic microbial α-diversity was observed in the DL and HZ samples than in the GH and DT soils, suggesting distinct diversity in the four regions. Generally, the autotrophic bacterial diversity varies with soil conditions, such as pH, total organic carbon, and nitrogen content . For instance, the Chao1 and Shannon indices of autotrophic bacteria at the study sites were negatively correlated with soil organic carbon and total nitrogen . In contrast, there was no significant relationship between the soil physiochemical parameters and the diversity of the cbbL -containing bacteria in the present study. This was also observed for different land use types . These results suggest that some soil properties do not affect the biodiversity of the cbbL -containing bacteria. 2 -fixing bacteria between regions and crop types Carbon fixation was genetically monitored using the cbbL gene marker, which encodes the key photosynthesis related enzyme RubisCO. The distribution and quantification of cbbL gene-containing bacteria in terrestrial ecosystems have largely focused on agricultural bulk soil . The results showed the number of shared and unique OTUs among the 40 soil samples, four regional groups, and three crop types. The four paddy soils from the four different regions had common dominant terminal restriction fragments (58 and 125 bp). In addition, some soils have common or unique dominant microbial populations . The predominant microbial populations in the four paddy soils from the four different regions varied, and most of these OTUs were distantly related to known sequences . Furthermore, our obtained sequences were mostly assigned to Proteobacteria and Actinobacteria, which commonly exist in farmland soils . Long et al. and Liu et al. identified Proteobacteria and Actinobacteria as the dominant phyla in paddy soils from five sites and four sites in South China, respectively. In addition, our present study indicated a high diversity of autotrophic bacterial taxa in the four soil regions, which is consistent with previous findings . The cbbL gene sequences at the genus level were assigned mainly to Bradyrhizobium , Azospirillum , Rhodopseudomonas , Variovorax , Methylibium , and Pseudonocardia . The high abundances of the autotrophic bacterial dominant genera Xanthobacter , Bradyrhizobium , Aminobacter , and Nitrosospira were detected in maize soil . The relative percentages of the dominant autotrophic bacterial phyla, classes, and genera differed among the paddy soils from five sites in South China, in which the values for Rhodoferax varied from 0.006 to 0.15 . In the present study, the 10 most common genera among the samples were Pseudonocardia , Sulfuritortus , Sulfuricaulis , Nitrosomonas , Thiohalobacter , Nitrobacter , Thiobacillus , Elioraea , Thioalkalivibrio , and Thiomonas . The dominant genera Pseudonocardia , Sulfuritortus , Sulfuricaulis , and Nitrosomonas varied greatly among the four soil regions, and are involved in the geochemical cycling of sulfur and nitrogen. Similarly, at the species level, the bacterial phylotypes exhibited diverse distribution patterns. The cbbL gene sequence obtained from groundnut rhizospheric soil contained the most Ochrobactrum and Rhizobium strains and included functional groups such as R. leguminosarum , Bradyrhizobium japonicum , S. meliloti , O. anthropi , Acidithiomicrobium sp., and Rubrivivax gelatinosus , which significantly contribute to the C or N cycles, and sulfur, CO-, and H 2 oxidation . Tolli and King observed distinct soil lithotrophic soil communities associated with land use and crop type (cotton and peanut) in agroecosystems. Yuan et al. reported that Mycobacterium sp., Rhodopseudomonas palustris , B. japonicum , Ralstonia eutropha , and Alcaligenes eutrophus were detected in all soil samples and composed the majority of the cbbL -containing bacterial community under different land uses, whereas Thiobacillus denitrificans , Nitrobacter winogradskyi , and N. vulgaris composed only a small part of the total microbial community. In addition, the cbbL -containing bacterial community composition in double rice soil differed from that in wheat-corn and rice-wheat rotation soils from the Pantang Agroecosystem . Similarly, Wu et al. reported that R. palustris , B. japonicum , R. gelatinosus , and R. eutropha were distributed in rice and corn soils from different geographical regions in China, and that these species could fix CO 2 . However, Acidiphilium multivorum and Synechococcus sp. were detected only in corn soil, and the T. alkaliphila strain ALgr 6 sp. was found only in rice soils. Pseudonocardia sp., S. calidifontis , S. limicola , Nitrobacter sp., T. thiocyanaticus , N. marina , Elioraea sp., N. hamburgensis , and Thiobacillus sp. were detected in the soils investigated. N. marina , Elioraea sp. YIM 72297, N. hamburgensis , and Thiobacillus sp. 63–78 composed only a small portion of the total microbial community. In particular, the cbbL -containing bacterial community compositions of the four regions were diverse, but the cbbL -containing populations of the three crop soils were similar. Furthermore, differential indicator groups were present in the four soil regions but not in the three crop-type soils. The dominant microbial groups in this study were quite different from those in paddy soil in South China and rice and corn soils in distinct geographical regions . These findings indicate that the distribution of the microbial community varies among different geographic locations. Various bacterial populations containing cbbL were selected in response to these variables. The obtained cbbL clone sequences were not closely affiliated with known cultured autotrophic bacteria and showed close proximity to uncultured bacteria retrieved from differently managed agricultural systems, agroecosystems, arid and semiarid soils . At present, the ecological roles of novel soil lithotrophs remain largely unknown . These taxa are affiliated with new CO 2 -fixing bacteria, that have not yet been explored. The abundance and diversity of soil autotrophic bacteria are key factors for carbon sequestration . Shifts in autotrophic microorganisms with diverse metabolic strategies and activities may cause changes in CO 2 fixation functions. The current study demonstrated that changes in autotrophic bacterial community composition can accurately account for the variation in the soil C fixation rate compared to that in abundance and α-diversity. In the present study, organic matter, total phosphate, total sulfur, and ammonium nitrogen were found to have positive or negative relationships with the abundances of Sulfuritortus , Sulfuricaulis , Thiohalobacter , Limnohabitans , Pseudonocardia , Beggiatoa , or Hydrogenophaga . Similarly, Yuan et al. also reported that total nitrogen and soil organic carbon were significantly correlated with the composition of the cbbL -containing bacteria in four different land use soils. Moreover, the CO 2 -fixing bacterial community was significantly affected by seven selected soil factors, such as total organic carbon, total sulfur, and ammonium nitrogen . RubisCO activities are greater in paddy soils than in upland soils, and RubisCO activities differ significantly among paddy soils in different geographical regions . Wu et al. reported that the RubisCO activities differed among rice-rice, rice-rapeseed, and rapeseed-corn rotated soils, with the highest activities occurring in rice-rice cropping systems. In the present study, RubisCO activity likely differed across different regions, but these values were similar among the three crop types from the four countries. This inconsistency can be attributed to differences in the geographical and cbbL -containing bacterial community compositions. Future research using stable isotope tracking is warranted to verify the causal links among the soil bacterial community, RubisCO activity, and CO 2 emissions. Similar cbbL -bearing bacterial communities were observed among the three crop soils based on Chao1 and Shannon diversity indices, ANOSIM, LEfSe analysis, and the relative abundances of dominant taxa. However, significant differences in the cbbL -carrying bacterial community were observed between the four site pairs, indicating the roles of both latitude and longitude in structuring agroecosystem CO 2 -assimilating bacterial communities. The effect of region on RubisCO activity was more evident than on RubisCO activity in crop groups. The composition of the autotrophic bacterial community was significantly related to several soil properties. |
Experiencing Complications After Metabolic and Bariatric Surgeries is a Risk Factor for Postoperative Emergency Department Admissions: a Retrospective Cohort Study | 4e171e94-924e-49c4-b4f5-841697d46ca8 | 11906519 | Surgery[mh] | Obesity is associated with many medical problems, including Obstructive Sleep Apnea (OSA) and type II diabetes, cardiovascular diseases, and cancer . The indication threshold for MBS was reduced from BMI ≥ 40 kg/m 2 to BMI ≥ 35 kg/m 2 and in the presence of obesity-related medical problems, from BMI ≥ 35 kg/m 2 to BMI ≥ 30 kg/m 2 . It is expected that the number of postoperative emergency room visits will increase in parallel with the development of laparoscopic techniques and the increasing prevalence of obesity in the society. Complications and hospital readmission rates are important quality measures for surgical clinics . The Clavien-Dindo Classification (CDC) has been preferred in clinics in recent years for the evaluation and reporting of postoperative complications in general surgery . The data on the use of CDC for MBS are limited. MBS can be considered a relatively safe surgery with low major complication rates . A previous study reported the 30-day complication rate following laparoscopic sleeve gastrectomy (LSG) as 15.3% . A different study that compared the 30-day morbidity and mortality of sleeve gastrectomy (SG), Roux-en-Y Gastric Bypass (RYGB), and one anastomosis gastric bypass (OAGB) reported that the difference in surgery type did not cause any significant differences in complication rates . Anastomotic leakage, bleeding, anastomotic stenosis, stomach erosion, and small intestine obstruction are surgery-related complications that might be detected following MBSs . A previous multicenter study reported the 30-day readmission rate as 4.4% . Identification of patients who are at high risk for complications by surgical teams and informing patients and their relatives about this can prevent unnecessary emergency room visits. Emergency service professionals’ familiarity with the post-bariatric process might contribute to the targeted use of examination and imaging methods and can provide an increase in patient satisfaction and savings in the use of hospital resources. The present study aimed to determine the rates, characteristics, and antecedents of emergency department admissions within 2 years following MBSs performed in our hospital.
The present study was designed in a retrospective, observational, and single-center design. The study was evaluated at the meeting of Karamanoğlu Mehmetbey University Faculty of Medicine Ethics Committee on 20 June 2023. Ethical approval was received (Decision No: 06–2023/21) and was registered to ANZCTR on 01 July 2024 (ACTRN12624000810516). Necessary permissions were obtained to conduct the study in our hospital. The study was conducted in line with the Declaration of Helsinki. Individuals who underwent surgery were informed that their data could be used for scientific purposes during the preoperative period. Surgical Techniques Primary surgeries were SG, gastric plication (GP), RYGB, OAGB, and revision bariatric surgeries (RBSs); bariatric conversions (BCs), RYGB, and OAGB were determined according to the patient’s clinical characteristics and the surgeon’s decision. All procedures were performed laparoscopically by one single surgeon under general anesthesia. If there are no complications after MBS in our clinic, those who have undergone SG and GP operations are monitored in the hospital for 2 days, and those who have undergone RYGB, OAGB, and RBS operations are monitored in the hospital for 4 days. The nutritionist is a member of our multidisciplinary team and makes preoperative and postoperative evaluations; plans the patient’s nutrition in line with the surgery, starting from the beginning of oral intake in the postoperative period; and follows implementation. Inclusion Criteria Individuals who were between the ages of 18 and 65 who had MBS and were classified according to CDC at their first postoperative follow-ups were included in the study. Exclusion Criteria Patients whose data could not be accessed in the electronic database, patients diagnosed with psychiatric diseases that were not in remission, and those with a follow-up period of less than 3 month were excluded from the study. Data Sources The data on the individuals who underwent MBS between June 2021 and June 2023 were evaluated from the hospital’s electronic database and from follow-up forms kept with patient consent for the follow-up of obese individuals who routinely undergo MBS in our hospital. The database provided data on patient-level demographics, diagnoses, surgical procedures, and hospital emergency department admission dates. The evaluation of complications for the first month was made by providing electronic database support with the Clavien-Dindo Classification System (CDC) as a treatment-based system used to rate complications in seven classes (I, II, IIIa, IIIb, IVa, IVb, and V) . In the present study, CDC > III was considered a major complication. CDC is recorded online on the system in the first postoperative month for individuals with obesity and who undergo bariatric surgery. Records for the study were scanned retrospectively through the system. Study Variables Age, gender, height, weight, and body mass index (BMI) values recorded in the preoperative anesthesia examination of individuals with obesity, for whom a surgery decision was made following the evaluation of a multidisciplinary team including general surgery, anesthesia, endocrinology, nutritionist, and psychiatry specialists, and hemoglobin (Hb) values measured with an automatic hematology analyzer and medical problems diagnosed at least 1 year before bariatric surgery were determined. Diabetes mellitus, hypertension, OSA diagnoses, preoperative Hb values, and CDC classifications were accepted as study variables. The presence of OSA was established by questioning whether the participants had been diagnosed before, based on the patient’s declaration. Smoking 10 or more cigarettes a day for more than 1 year was considered “smoking.” To be evaluated in statistical analysis, all morbidities of individuals undergoing bariatric surgery were categorized as Yes/No. The emergency service visits of the patients following discharge were scanned in the database. The data on the first emergency department visits were recorded. Applications associated with upper respiratory tract infections, urinary tract infections, and pregnancy were not considered emergency applications associated with surgery. Complaints that caused postoperative emergency room visits were recorded as expressed by the patients. Primary diagnoses of outpatients who did not require hospitalization were obtained from the emergency department epicrisis reports. Secondary diagnoses of patients requiring hospitalization were obtained from the surgical service epicrisis reports during the period they were followed in the general surgery ward. The surgical requirements of the patients were queried through the system. Statistical Evaluation Mean and standard deviation for numerical variables and frequency and percentage values for categorical variables were given as descriptive statistics. The chi-square and Fisher’s exact tests were used in the analysis of the categorical variables. The Mann–Whitney U and Kruskal–Wallis tests were used in the analysis of the numerical variables. Multivariate Cox regression analyses were used to find the variables that were associated with emergency admissions. The data analysis was performed with the R 4.3.2 program. p < 0.05 was considered significant.
Primary surgeries were SG, gastric plication (GP), RYGB, OAGB, and revision bariatric surgeries (RBSs); bariatric conversions (BCs), RYGB, and OAGB were determined according to the patient’s clinical characteristics and the surgeon’s decision. All procedures were performed laparoscopically by one single surgeon under general anesthesia. If there are no complications after MBS in our clinic, those who have undergone SG and GP operations are monitored in the hospital for 2 days, and those who have undergone RYGB, OAGB, and RBS operations are monitored in the hospital for 4 days. The nutritionist is a member of our multidisciplinary team and makes preoperative and postoperative evaluations; plans the patient’s nutrition in line with the surgery, starting from the beginning of oral intake in the postoperative period; and follows implementation.
Individuals who were between the ages of 18 and 65 who had MBS and were classified according to CDC at their first postoperative follow-ups were included in the study.
Patients whose data could not be accessed in the electronic database, patients diagnosed with psychiatric diseases that were not in remission, and those with a follow-up period of less than 3 month were excluded from the study.
The data on the individuals who underwent MBS between June 2021 and June 2023 were evaluated from the hospital’s electronic database and from follow-up forms kept with patient consent for the follow-up of obese individuals who routinely undergo MBS in our hospital. The database provided data on patient-level demographics, diagnoses, surgical procedures, and hospital emergency department admission dates. The evaluation of complications for the first month was made by providing electronic database support with the Clavien-Dindo Classification System (CDC) as a treatment-based system used to rate complications in seven classes (I, II, IIIa, IIIb, IVa, IVb, and V) . In the present study, CDC > III was considered a major complication. CDC is recorded online on the system in the first postoperative month for individuals with obesity and who undergo bariatric surgery. Records for the study were scanned retrospectively through the system.
Age, gender, height, weight, and body mass index (BMI) values recorded in the preoperative anesthesia examination of individuals with obesity, for whom a surgery decision was made following the evaluation of a multidisciplinary team including general surgery, anesthesia, endocrinology, nutritionist, and psychiatry specialists, and hemoglobin (Hb) values measured with an automatic hematology analyzer and medical problems diagnosed at least 1 year before bariatric surgery were determined. Diabetes mellitus, hypertension, OSA diagnoses, preoperative Hb values, and CDC classifications were accepted as study variables. The presence of OSA was established by questioning whether the participants had been diagnosed before, based on the patient’s declaration. Smoking 10 or more cigarettes a day for more than 1 year was considered “smoking.” To be evaluated in statistical analysis, all morbidities of individuals undergoing bariatric surgery were categorized as Yes/No. The emergency service visits of the patients following discharge were scanned in the database. The data on the first emergency department visits were recorded. Applications associated with upper respiratory tract infections, urinary tract infections, and pregnancy were not considered emergency applications associated with surgery. Complaints that caused postoperative emergency room visits were recorded as expressed by the patients. Primary diagnoses of outpatients who did not require hospitalization were obtained from the emergency department epicrisis reports. Secondary diagnoses of patients requiring hospitalization were obtained from the surgical service epicrisis reports during the period they were followed in the general surgery ward. The surgical requirements of the patients were queried through the system.
Mean and standard deviation for numerical variables and frequency and percentage values for categorical variables were given as descriptive statistics. The chi-square and Fisher’s exact tests were used in the analysis of the categorical variables. The Mann–Whitney U and Kruskal–Wallis tests were used in the analysis of the numerical variables. Multivariate Cox regression analyses were used to find the variables that were associated with emergency admissions. The data analysis was performed with the R 4.3.2 program. p < 0.05 was considered significant.
A total of 153 patients suffering from MBS were evaluated in the present study (109 (71%) women). The average age was 39.85 ± 10.58, the average follow-up period of the sample was 609.63 ± 222.89, 140 patients (92%) had a follow-up period of 9 months to 2 years, 13 patients (8%) had a follow-up period of 3 months to 9 months, and 31% of the patients applied to the emergency department at least once during the follow-up period. The demographic and clinical characteristics of the patients who underwent MBS are given in Table . In the present study, the number of patients who underwent primary surgery was 130 (84.9%), and the number of patients who underwent revision bariatric surgeries (RBSs) was 23 (15.1%) (Table ). The number of patients who visited to the emergency department after primary surgery was 36 (28.5%). The number of patients who visited to the emergency department after RBS was 10 (43.5%). The CDC classification data of the patients and the times of admission to the emergency department in the first postoperative month after MBS in our clinic are given in Table . According to the CDC determined at the end of the first postoperative month, 78% of the patients who had MBS did not encounter any complications; 4.6% of individuals had MBS required surgical, endoscopic, and radiological interventions, which we consider as major complications. The rate of emergency department visits in individuals with MBS was 31% and 7.8% made their first emergency visits within the first month after surgery. The complaints of those who applied to the emergency department following MBS are given in Table . The most common presentation was for abdominal pain. Nausea-vomiting and fatigue were the other most common complaints. Hospitalization diagnoses, hospitalization, and surgical requirements of the patients who were admitted to the emergency department and readmitted to the hospital following MBSs are given in Table . The most common hospitalization diagnosis was alkaline reflux gastritis (33%) in our study sample. Gastroesophageal reflux (GER) with 15% and dehydration with 13% were recorded as the other most common hospitalization diagnoses. Following discharge, 15% of the patients required re-hospitalization and applied to the emergency department, and 9.8% required surgical procedures following emergency admission. The comparison of the demographic data and emergency admissions requiring hospital readmission is given in Table , and the comparison of emergency admissions requiring surgery is given in Table . A statistically significant relationship was detected between the presence of HT, low BMI, and the presence of complications at all times and the need for rehospitalization and surgery (Tables and ). The duration of emergency admission was compared with the demographic and clinical characteristics separately for the first postoperative month, postoperative 1 to 3 months, postoperative 3–9 months, postoperative 9 months, and 2-year periods (Table ). A statistically significant relationship was detected between age, the presence of HT and DM, the presence of smoking status, and complications. Since the CDC classification is evaluated at the end of the 30th postoperative day in obese individuals, multivariate Cox regression analyses (Table ) were performed by excluding the first 30-day admissions for the variables and are given in Table . A statistically significant relationship was detected between experiencing complications and seeking emergency admission according to age, presence of HT, and DM.
It was found that 31% of the individuals who underwent MBS were admitted to the emergency department, with an average follow-up period of 609.63 ± 222.89 days. The fact that only 9.8% of these applications were within the first postoperative month shows that emergency department applications following MBSs might occur throughout the following period. We argue that experiencing postoperative complications is the most important determinant of emergency department admissions. Patients who experience early complications after MBS can be treated in the hospital before their discharge, but they might present to the emergency department with acute abdominal pain that occurs months or years after surgery . The mean follow-up period was 609.63 ± 222.89 days in the present study. Among the 153 patients who were included in the present study, 140 were followed up between 9 months and 2 years. When demographic and clinical data and emergency department application times were compared (Table ), it was found that 119 patients presented to the emergency department at or after the ninth postoperative month. We also evaluated the effects of the complication status assessed at the end of the first postoperative month with the Clavien-Dindo Classification (CDC) on emergency department applications after the first postoperative month. Minor complications were defined only for the first month in the present study. We found that 16 patients who presented to the emergency department after the first month postoperatively without complications (CDC 0) or with minor complications (CDC I, CDC II) were readmitted to the hospital after presentation, and eight underwent surgery. Late or long-term complications (after the postoperative first month) resulting from MBS were not fully understood because of the variety of surgical procedures . In a multicenter study, the emergency department presentation rate for MBS after the sixth month was reported to be 41.2% . For example, anastomotic stenosis is seen in approximately 12% of patients after bypass and typically develops 1 month or more after surgery. It is most frequently detected 50 days after gastric bypass . Similar evaluations can be made for marginal ulcers and small bowel obstruction (SBO). Marginal ulcer complications can occur in the early or late period . In a previous study, the average presentation time for SBO after gastric bypass (GB) was reported to be 313 days . Patients with uncomplicated or minor complications might present to the emergency department with clinical conditions that require urgent surgery in the long term. One of the aims of the present study was to investigate the relationship between late emergency department visits after the first month postoperatively and patient demographic and clinical data. To this end, the relationship between the variables of diabetes mellitus (DM), hypertension (HT), preoperative Hb value, obstructive sleep apnea (OSA), smoking status, and complications in the first month postoperatively and emergency visits was evaluated. Smoking patients constituted a large proportion of our sample size (35%). Yüce et al. found that smokers were associated with more frequent rehospitalization, mortality, serious morbidity, wound complications, and respiratory complications in their study that evaluated bariatric surgeries . Previous studies have evaluated that smoking status is associated with the development of marginal ulcers requiring surgical revision after MBS . We believe that it is important to evaluate the relationship between smoking status, which is a modifiable risk factor, and MBS results. The relationship between the presence of HT, DM, and OSA, which are considered obesity-related medical problems; preoperative Hb value and smoking status; and emergency department visits in individuals with obesity was evaluated. Interestingly, no statistically significant relationships were detected between OSA and emergency admissions following emergency admissions. We think that the length of our follow-up period and the regression that might be detected in OSA cases following MBS are effective in our results. Postoperative bleeding is a relatively common complication and might cause mortality and morbidity . Although its contribution to the complications could not be determined, no statistically significant relationship was detected between postoperative emergency admissions and preoperative Hb values in the study. A statistically significant relationship was detected between age, presence of HT, presence of DM, smoking status, and experiencing complications in the evaluation of emergency department visits over time; however, in the statistical evaluations, it was found that experiencing postoperative complications was the strongest determinant. In the present study, it was also found that readmission was considered necessary following emergency department admissions in 15% of cases following MBS, and surgical intervention was required in 9.8%. The three most common complaints in these applications were abdominal pain, nausea-vomiting, and fatigue. The most common hospitalization diagnoses following emergency department admissions were alkaline reflux gastritis, GER, and dehydration. Tuğcan et al. reported a 22% rate of emergency department visits in the patient population that were followed for 6 months following bariatric surgery . The most common complaint in emergency department admissions was abdominal pain, and the most common diagnosis in patients deemed suitable for hospitalization was perforation . We think that the long follow-up period in the present study and the large number of patients whose first admission to the emergency department was following the ninth postoperative month were the reasons for the difference in hospitalization diagnoses. In their study that reported their 1-year follow-up data following bariatric surgery, Pinzon et al. found the frequency of admission to the emergency department between 10.7% (postoperative days 0–30) and 5.7% (postoperative days 181–270) . We think that long-term complications of bariatric surgery, e.g., cholecystitis and marginal ulcer among the diagnoses of rehospitalization after emergency admissions, were also reflected in our results because of the large number of follow-ups up to 2 years. We argue that information on how to manage abdominal pain following MBSs must be given to patients who will undergo MBS in the preoperative period and to emergency department and surgical team staff as part of their in-service training. A total of 78% of our patients completed their first postoperative month without any complications; 4.6% faced major complications that required surgical, endoscopic and radiological interventions. In the present study, the early-period (postoperative first month) major complication rate after MBS was defined as patients who were graded CDC III and higher. The early-period major complication rate (as seen in Table ) was 4.6% at the end of the first month postoperatively. Davey et al. examined five RCTs in their meta-analysis and determined a major complication rate of 3.4% . Our leakage rate was found to be 1.9% after MBS at all times and 6.5% among patients who required hospitalization after emergency room visits. De Simone et al. reported leakage rates of 4.2% in their study. Abdegavad et al. published their 3-year follow-up results in RBS and examined 81 RBSs reporting eight major complications (10.4%), five of which were leaks . The emergency visit rate after RBS was found to be 43.5% in the present study. We think that the high complication and leakage rates in the present study were associated with the presence of revision bariatric surgeries (RBSs) performed at a rate of 15.1% in our sample (Table ). Our high complication survival rates might have occurred because of the presence of RBSs in our sample. RBS is technically more complex than primary MBS and is associated with increased hospital stay and higher complication rates [ – ]. We hope that studies in which different types of surgeries will be performed separately will be published in the future after the appropriate sample size is reached. In the present study, nearly half of the patients who applied to the emergency department required hospitalization, which was higher than previous studies reporting results on this subject. In their study, Telem et al. reported that 34.9% of the patients and Pinzon et al. reported that approximately one-fourth of the patients were readmitted following emergency department admissions following admission to the emergency departments . Our higher readmission rates might be associated with the presence of RBS in our samples and the wider use of hospitalization indications, considering the transportation difficulties of patients who lived outside the city. When the hospital readmission and surgical requirements that were evaluated in our study were compared with demographic data and clinical characteristics, the presence of HT was detected, and lower BMI values and higher CDC values were significant for hospital readmission and surgical necessity. In our study, the researchers found the need for readmission and surgery to be associated with lower BMI. The reason for this might be RBSs in our sample size. Bariatric conversions are the most common RBS procedure . The incidence of RBS is estimated to be between 5 and 26% . The most common causes of RBS are stomach acid reflux, bile reflux, fistula, leak, unexplained abdominal pain, protein-calorie malnutrition (PCM), and stricture . We think that PMC-associated low BMI values affected the need for re-hospitalization and surgery following emergency admission in our study. One of our limitations is that our study was conducted in a single center and by a single surgeon. The fact that the studies were conducted retrospectively in one single center and with a long follow-up period carries the possibility of missing data. There is a possibility of emergency service applications to different centers. We consider this as the limitation of the present study. We tried to minimize this by screening our patient inquiries during repeated outpatient clinic checks associated with our long follow-up period. Our sample size was heterogeneous for surgical procedures, and this heterogeneity might have different reasons for admission in the postoperative period; however, only the main presenting complaints and diagnoses could be recorded nonspecifically. We think that prospective studies that can eliminate these limitations will be added to the literature in the future.
In the present study, it was shown that emergency department visits following MBS continued significantly after 1 month postoperatively and that advanced age, hypertension, DM, smoking, and experiencing postoperative complications were effective in emergency department visits. The researchers presented the data showing that the most important determinant among all these factors is experiencing postoperative complications.
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Biological Control of | f7f72392-f532-4ffb-8449-37dd16540c72 | 11124295 | Microbiology[mh] | Escherichia coli O157:H7, a leading foodborne pathogen, is commonly shed in the feces of cattle and other food-producing animals. Numerous studies have reported the prolonged survival of E. coli O157:H7 in raw manure, thereby heightening the risk of its transmission into the food chain and posing a public health threat . Indeed, outbreaks of E. coli O157:H7 infections have frequently been linked to the consumption of fresh produce or other food products directly or indirectly contaminated by water or manure containing this foodborne pathogen . Due to the presence of human pathogens in raw animal wastes, the proper composting of these wastes and handling of the finished products are critical for ensuring the safety of fresh produce production when the animal manure-based compost is used as a fertilizer and biological soil amendment. Importantly, the Food and Drug Administration’s (FDA) Food Safety Modernization Act (FSMA) Produce Safety Rule has placed limitations on the use of raw manure and has also established microbial standards for composted manure used on crops produced for direct human consumption . Composting is an aerobic process during which organic waste is biologically degraded by microorganisms to humus-like material. Both bacteria and fungi are present and active in a typical composting process . Most of the foodborne pathogens inherently present in the raw manure are inactivated during the thermophilic phase due to high temperature . Furthermore, compost contains a wealth of microbial species; however, these organisms face fierce competition within their environment. Compost microorganisms can interact synergistically or compete for the available nutrients . In this complex ecosystem, it is likely that some microorganisms have acquired protective features, such as the secretion of biocidal compounds. Bacterial competition in the environment can be classified as exploitative competition, where bacteria utilize limited nutrients or compete for colonizing sites, thereby depriving fellow microorganisms of the same genotypes, and interference competition, where cell damage occurs via the release of bioactive compounds by other microorganisms . As a result, certain populations of compost microflora may possess antimicrobial activities against harmful human pathogens. Biocontrol of foodborne pathogens in agricultural settings, such as animal production, fresh produce fields, and food processing environments, has been reported . This approach seems feasible since these microorganisms originated from agricultural environments and would be adapted to their native environment. Another advantage is that, ultimately, the usage of biocontrol agents against foodborne pathogens leads to less reliance on harmful chemicals and sanitizers by the food industry. The objective of this study was to isolate microorganisms from compost samples that produce metabolites bacteriostatic or bactericidal to E. coli O157:H7 and then determine their ability to inhibit the growth of the pathogen in dairy compost under laboratory and greenhouse conditions.
2.1. Bacterial Strains and Culture Conditions Due to strain variation in growth parameters and persistence, a cocktail of three to five E. coli O157:H7 strains was used for this study. Five E. coli O157:H7 strains (spinach outbreak strain F06M-0923-21 and Taco John’s outbreak strain F07M-020-1, both obtained from California Department of Health , avirulent strain B6914 stx 1 − and 2 − obtained from Dr. Pina Fratamico, USDA-ARS-ERRC , and avirulent strains MD46 and MD47 obtained from Dr. Mike Doyle at the University of Georgia) were used in this study . To differentiate from the competitive exclusion (CE) strains or the compost microflora, all tested E. coli O157:H7 strains were induced to be rifampicin-resistant via the gradient plate method , and no antagonistic effect was observed among these strains. Prior to each experiment, the strains from the freezer stocks were streaked on Tryptic Soy Agar supplemented with 100 µg mL −1 rifampicin (Fisher Scientific, Fair Lawn, NJ, USA) (TSA-R) plates and incubated at 35 °C for 24 h. Single colonies were inoculated into Tryptic Soy Broth (TSB) without glucose, grown to an early stationary phase, and used in further experiments. 2.2. Competitive Exclusion Microorganism Isolation and Culture Conditions The CE strains were isolated from 31 samples of finished composts, including poultry litter-, dairy manure- and plant wastes-based as described previously . Briefly, 9 mL of universal pre-enrichment broth (UPB) was added to each compost sample (ca. 1 g), and the mixtures were serially diluted (1:10) in phosphate-buffered saline (PBS). A volume of 0.1 mL of each dilution was plated in duplicate on tryptone, yeast extract, proteose peptone 3 agar plates (TYP) containing proteose peptone 3 (5 g L −1 ), tryptone (5 g L −1 ), yeast extract (5 g L −1 ), sodium chloride (8 g L −1 ), and agar (17 g L −1 ) and incubated at room temperature. The colonies were randomly selected from plates and streaked several times for isolation. Two methods, including a spot-on-lawn assay and liquid co-culture experiments, were used to screen isolates for antimicrobial activity against E. coli O157:H7 strains. In addition to selection at room temperature, some isolates were tested for antimicrobial activity at 42 °C. For the spot-on-lawn assay, 0.1 mL of approximately 10 7 CFU ml −1 cells of the 3-strain cocktail of E. coli O157:H7 (F06M-0923-21, F07M-020-1, and B6914) were plated in duplicate onto the surface of TYP plate. Putative CE isolates were grown individually on TYP plates at 25 °C for 48 h; then, a single colony was replica-plated on a sterile TYP plate and a TYP plate containing E. coli O157:H7 strains as the indicator microorganism. The plates were incubated at 25 °C for 48 h and then observed for zones of inhibition. The CE isolates were selected for a liquid co-culture experiment based on their antimicrobial activity against E. coli O157:H7 expressed as a clear inhibition zone. For the liquid co-culture experiments, E. coli O157:H7 strain B6914 was grown to stationary phase at room temperature on a rotary shaker in TYP broth. The putative CE isolates were grown in similar conditions. To test the inhibitory capacity in TYP broth, CE isolates were inoculated in equal concentration (ca. 10 2 CFU/mL) with the target E. coli O157:H7. Concurrently, individual CE strains and E. coli O157:H7 strain were inoculated in TYP broth separately and monitored for growth. Samples were collected at selected intervals and plated on TSA-R to enumerate only E. coli O157:H7 or TSA for CE isolates. 2.3. Species Identification by Amplifying the 16S rRNA Gene The DNA of potential CE isolates from the compost samples was extracted using the UltraClean TM Microbial DNA Isolation Kit (Mo-Bio Laboratories, Inc., Carlsbad, CA, USA) as described in the manufacturer’s instructions. Isolates were identified by PCR amplification of 16S rRNA genes using universal primers and sequenced by Eurofins Genomics (Louisville, KY, USA) as described previously . The forward primer ENV1 (5′-AGA GTT TGA TII TGG CTC AG-3′) targets positions 8–27 of E. coli 16S rRNA, whereas the reverse primer ENV2 (5′-CGG ITA CCT TGT TAC GAC TT-30′) corresponds to positions 1511–1492 . PCR reagents were used as a negative control, while the E. coli O157:H7 DNA was used as a positive control. The bacterial species was identified using BLAST (NSBI) and The Ribosomal Database Program . 2.4. Compost Inoculation, Sampling and Bacterial Enumeration Finished dairy waste—based compost (Black Kow ® , Black Gold Compost Co., Oxford, FL, USA) was used to determine the efficacy of CE strains against E. coli O157:H7 under both laboratory and greenhouse conditions. Prior to experiments, large particles present in compost samples were removed by sieving (sieve pore size, 0.3 × 0.3 cm). Compost was placed in sterile containers under refrigeration conditions and used for further experiments. 2.4.1. E. coli O157:H7 Growth under Laboratory Conditions The selected CE strains ( n = 3) were grown in TSB without glucose to the early stationary phase and then centrifuged and washed twice with 0.8% saline solution. To determine the effectiveness of CE on E. coli O157 inhibition in the compost, about 4 logs of the 3-strain cocktail of CE cultures were inoculated into the above compost containing ca. 6 logs of indigenous microorganisms using the spraying method . The CE-inoculated compost was then adjusted with sterile tap water to different moisture contents (20, 30, and 40%) and then acclimated at room temperature for 24 h. The overnight cultures of three rifampicin-resistant E. coli O157:H7 strains (F06M-0923-21, F07M-020-1, and B6914) grown in TSB-R broth were washed with saline and then inoculated to the CE-inoculated compost at an initial concentration of ca. 2 log CFU/g, and the inoculated samples were then stored at temperatures of 22 or 30 °C. At selected intervals, compost samples were enumerated for E. coli O157:H7 on TSA-R plates. 2.4.2. E. coli O157:H7 Growth under Greenhouse Conditions Two experimental approaches were conducted in the greenhouse. Both CE strains and E. coli O157:H7 strains were prepared as described above. The first approach was to simulate pathogen contamination of the finished compost. Briefly, the finished compost with adjusted moisture levels of 20, 30, and 40% were first inoculated (at a ratio of 1:10 v/wt) with the 10-strain cocktail of CE cultures to reach ca. 10 8 –10 9 CFU g −1 . After 24 h, the compost was inoculated with a cocktail of three avirulent E. coli O157:H7 strains (B6914, MD46, and MD47) at ca. 10 5 –10 6 CFU g −1 . Samples consisted of (i) compost inoculated only with E. coli O157:H7 cocktail, (ii) compost inoculated only with CE cocktail, (iii) compost inoculated with both E. coli O157:H7 and CE cocktail, and (iv) uninoculated compost. The second approach was to simulate the survival of the pathogen during thermophilic composting. To prepare for heat-adapted cells in compost, above-avirulent E. coli O157:H7 cocktail strains were inoculated (1:10 v/wt) to the finished compost with 40% MC, subjected to heat at 48 °C for 30 min and then inoculated further at a ratio of 1:10 wt/wt in compost samples with 40, 30, and 20% MC. After 24 h incubation at room temperature, the E. coli O157:H7 inoculated compost samples were inoculated (1:10 v/wt) with the 10-strain cocktail of CE cultures to reach ca.10 8 –10 9 CFU g −1 . Four treatments of compost samples were prepared the same as described in the first approach. For both approaches, two independent experiments were performed in triplicate. Experiments were performed as follows: Summer trials (August–September), Fall trials (October–December), and Winter trials (February–March) inside a greenhouse. Sterile cups containing compost samples were arranged in large plastic containers, and a digital hydrothermometer (EU 620-0915; VWR International, Radnor, PA, USA) for temperature and relative humidity was placed inside. Containers had recipients with saturated KCl solution and were closed every evening and opened in the morning. The moisture levels of the samples were adjusted every evening based on weight loss. Adjustment in the morning was not necessary since there was little moisture loss due to the overnight storage in high relative humidity. Therefore, samples were subjected to lower temperatures and high relative humidity overnight and high temperatures and decreased humidity during the day. Treatments were sampled on day 2 then every 4 days and analyzed for moisture content (the moisture levels of the samples were adjusted every day in the greenhouse for all samples) and bacterial enumeration. Briefly, 5 g of inoculated compost was mixed and homogenized with 45 mL of PBS in a sterile stomacher bag. The samples were then serially diluted and plated on TSA-R for the enumeration of E. coli O157:H7 or TSA for the enumeration of CE or the compost microflora. Data obtained from bacterial enumeration were expressed as log CFU per gram dry weight (CFU g/dw), and the detection limit of the plating method was approximately 100 CFU g/dw . 2.5. Statistical Analysis The analysis of pathogen survival data was performed using JMP 11.2.1 (SAS Institute Inc., Atlanta, GA, USA). Analysis of variance (ANOVA), followed by the least significant differences (LSD) test, was carried out to determine whether significant differences ( p < 0.05) existed among different treatments.
Due to strain variation in growth parameters and persistence, a cocktail of three to five E. coli O157:H7 strains was used for this study. Five E. coli O157:H7 strains (spinach outbreak strain F06M-0923-21 and Taco John’s outbreak strain F07M-020-1, both obtained from California Department of Health , avirulent strain B6914 stx 1 − and 2 − obtained from Dr. Pina Fratamico, USDA-ARS-ERRC , and avirulent strains MD46 and MD47 obtained from Dr. Mike Doyle at the University of Georgia) were used in this study . To differentiate from the competitive exclusion (CE) strains or the compost microflora, all tested E. coli O157:H7 strains were induced to be rifampicin-resistant via the gradient plate method , and no antagonistic effect was observed among these strains. Prior to each experiment, the strains from the freezer stocks were streaked on Tryptic Soy Agar supplemented with 100 µg mL −1 rifampicin (Fisher Scientific, Fair Lawn, NJ, USA) (TSA-R) plates and incubated at 35 °C for 24 h. Single colonies were inoculated into Tryptic Soy Broth (TSB) without glucose, grown to an early stationary phase, and used in further experiments.
The CE strains were isolated from 31 samples of finished composts, including poultry litter-, dairy manure- and plant wastes-based as described previously . Briefly, 9 mL of universal pre-enrichment broth (UPB) was added to each compost sample (ca. 1 g), and the mixtures were serially diluted (1:10) in phosphate-buffered saline (PBS). A volume of 0.1 mL of each dilution was plated in duplicate on tryptone, yeast extract, proteose peptone 3 agar plates (TYP) containing proteose peptone 3 (5 g L −1 ), tryptone (5 g L −1 ), yeast extract (5 g L −1 ), sodium chloride (8 g L −1 ), and agar (17 g L −1 ) and incubated at room temperature. The colonies were randomly selected from plates and streaked several times for isolation. Two methods, including a spot-on-lawn assay and liquid co-culture experiments, were used to screen isolates for antimicrobial activity against E. coli O157:H7 strains. In addition to selection at room temperature, some isolates were tested for antimicrobial activity at 42 °C. For the spot-on-lawn assay, 0.1 mL of approximately 10 7 CFU ml −1 cells of the 3-strain cocktail of E. coli O157:H7 (F06M-0923-21, F07M-020-1, and B6914) were plated in duplicate onto the surface of TYP plate. Putative CE isolates were grown individually on TYP plates at 25 °C for 48 h; then, a single colony was replica-plated on a sterile TYP plate and a TYP plate containing E. coli O157:H7 strains as the indicator microorganism. The plates were incubated at 25 °C for 48 h and then observed for zones of inhibition. The CE isolates were selected for a liquid co-culture experiment based on their antimicrobial activity against E. coli O157:H7 expressed as a clear inhibition zone. For the liquid co-culture experiments, E. coli O157:H7 strain B6914 was grown to stationary phase at room temperature on a rotary shaker in TYP broth. The putative CE isolates were grown in similar conditions. To test the inhibitory capacity in TYP broth, CE isolates were inoculated in equal concentration (ca. 10 2 CFU/mL) with the target E. coli O157:H7. Concurrently, individual CE strains and E. coli O157:H7 strain were inoculated in TYP broth separately and monitored for growth. Samples were collected at selected intervals and plated on TSA-R to enumerate only E. coli O157:H7 or TSA for CE isolates.
The DNA of potential CE isolates from the compost samples was extracted using the UltraClean TM Microbial DNA Isolation Kit (Mo-Bio Laboratories, Inc., Carlsbad, CA, USA) as described in the manufacturer’s instructions. Isolates were identified by PCR amplification of 16S rRNA genes using universal primers and sequenced by Eurofins Genomics (Louisville, KY, USA) as described previously . The forward primer ENV1 (5′-AGA GTT TGA TII TGG CTC AG-3′) targets positions 8–27 of E. coli 16S rRNA, whereas the reverse primer ENV2 (5′-CGG ITA CCT TGT TAC GAC TT-30′) corresponds to positions 1511–1492 . PCR reagents were used as a negative control, while the E. coli O157:H7 DNA was used as a positive control. The bacterial species was identified using BLAST (NSBI) and The Ribosomal Database Program .
Finished dairy waste—based compost (Black Kow ® , Black Gold Compost Co., Oxford, FL, USA) was used to determine the efficacy of CE strains against E. coli O157:H7 under both laboratory and greenhouse conditions. Prior to experiments, large particles present in compost samples were removed by sieving (sieve pore size, 0.3 × 0.3 cm). Compost was placed in sterile containers under refrigeration conditions and used for further experiments. 2.4.1. E. coli O157:H7 Growth under Laboratory Conditions The selected CE strains ( n = 3) were grown in TSB without glucose to the early stationary phase and then centrifuged and washed twice with 0.8% saline solution. To determine the effectiveness of CE on E. coli O157 inhibition in the compost, about 4 logs of the 3-strain cocktail of CE cultures were inoculated into the above compost containing ca. 6 logs of indigenous microorganisms using the spraying method . The CE-inoculated compost was then adjusted with sterile tap water to different moisture contents (20, 30, and 40%) and then acclimated at room temperature for 24 h. The overnight cultures of three rifampicin-resistant E. coli O157:H7 strains (F06M-0923-21, F07M-020-1, and B6914) grown in TSB-R broth were washed with saline and then inoculated to the CE-inoculated compost at an initial concentration of ca. 2 log CFU/g, and the inoculated samples were then stored at temperatures of 22 or 30 °C. At selected intervals, compost samples were enumerated for E. coli O157:H7 on TSA-R plates. 2.4.2. E. coli O157:H7 Growth under Greenhouse Conditions Two experimental approaches were conducted in the greenhouse. Both CE strains and E. coli O157:H7 strains were prepared as described above. The first approach was to simulate pathogen contamination of the finished compost. Briefly, the finished compost with adjusted moisture levels of 20, 30, and 40% were first inoculated (at a ratio of 1:10 v/wt) with the 10-strain cocktail of CE cultures to reach ca. 10 8 –10 9 CFU g −1 . After 24 h, the compost was inoculated with a cocktail of three avirulent E. coli O157:H7 strains (B6914, MD46, and MD47) at ca. 10 5 –10 6 CFU g −1 . Samples consisted of (i) compost inoculated only with E. coli O157:H7 cocktail, (ii) compost inoculated only with CE cocktail, (iii) compost inoculated with both E. coli O157:H7 and CE cocktail, and (iv) uninoculated compost. The second approach was to simulate the survival of the pathogen during thermophilic composting. To prepare for heat-adapted cells in compost, above-avirulent E. coli O157:H7 cocktail strains were inoculated (1:10 v/wt) to the finished compost with 40% MC, subjected to heat at 48 °C for 30 min and then inoculated further at a ratio of 1:10 wt/wt in compost samples with 40, 30, and 20% MC. After 24 h incubation at room temperature, the E. coli O157:H7 inoculated compost samples were inoculated (1:10 v/wt) with the 10-strain cocktail of CE cultures to reach ca.10 8 –10 9 CFU g −1 . Four treatments of compost samples were prepared the same as described in the first approach. For both approaches, two independent experiments were performed in triplicate. Experiments were performed as follows: Summer trials (August–September), Fall trials (October–December), and Winter trials (February–March) inside a greenhouse. Sterile cups containing compost samples were arranged in large plastic containers, and a digital hydrothermometer (EU 620-0915; VWR International, Radnor, PA, USA) for temperature and relative humidity was placed inside. Containers had recipients with saturated KCl solution and were closed every evening and opened in the morning. The moisture levels of the samples were adjusted every evening based on weight loss. Adjustment in the morning was not necessary since there was little moisture loss due to the overnight storage in high relative humidity. Therefore, samples were subjected to lower temperatures and high relative humidity overnight and high temperatures and decreased humidity during the day. Treatments were sampled on day 2 then every 4 days and analyzed for moisture content (the moisture levels of the samples were adjusted every day in the greenhouse for all samples) and bacterial enumeration. Briefly, 5 g of inoculated compost was mixed and homogenized with 45 mL of PBS in a sterile stomacher bag. The samples were then serially diluted and plated on TSA-R for the enumeration of E. coli O157:H7 or TSA for the enumeration of CE or the compost microflora. Data obtained from bacterial enumeration were expressed as log CFU per gram dry weight (CFU g/dw), and the detection limit of the plating method was approximately 100 CFU g/dw .
E. coli O157:H7 Growth under Laboratory Conditions The selected CE strains ( n = 3) were grown in TSB without glucose to the early stationary phase and then centrifuged and washed twice with 0.8% saline solution. To determine the effectiveness of CE on E. coli O157 inhibition in the compost, about 4 logs of the 3-strain cocktail of CE cultures were inoculated into the above compost containing ca. 6 logs of indigenous microorganisms using the spraying method . The CE-inoculated compost was then adjusted with sterile tap water to different moisture contents (20, 30, and 40%) and then acclimated at room temperature for 24 h. The overnight cultures of three rifampicin-resistant E. coli O157:H7 strains (F06M-0923-21, F07M-020-1, and B6914) grown in TSB-R broth were washed with saline and then inoculated to the CE-inoculated compost at an initial concentration of ca. 2 log CFU/g, and the inoculated samples were then stored at temperatures of 22 or 30 °C. At selected intervals, compost samples were enumerated for E. coli O157:H7 on TSA-R plates.
E. coli O157:H7 Growth under Greenhouse Conditions Two experimental approaches were conducted in the greenhouse. Both CE strains and E. coli O157:H7 strains were prepared as described above. The first approach was to simulate pathogen contamination of the finished compost. Briefly, the finished compost with adjusted moisture levels of 20, 30, and 40% were first inoculated (at a ratio of 1:10 v/wt) with the 10-strain cocktail of CE cultures to reach ca. 10 8 –10 9 CFU g −1 . After 24 h, the compost was inoculated with a cocktail of three avirulent E. coli O157:H7 strains (B6914, MD46, and MD47) at ca. 10 5 –10 6 CFU g −1 . Samples consisted of (i) compost inoculated only with E. coli O157:H7 cocktail, (ii) compost inoculated only with CE cocktail, (iii) compost inoculated with both E. coli O157:H7 and CE cocktail, and (iv) uninoculated compost. The second approach was to simulate the survival of the pathogen during thermophilic composting. To prepare for heat-adapted cells in compost, above-avirulent E. coli O157:H7 cocktail strains were inoculated (1:10 v/wt) to the finished compost with 40% MC, subjected to heat at 48 °C for 30 min and then inoculated further at a ratio of 1:10 wt/wt in compost samples with 40, 30, and 20% MC. After 24 h incubation at room temperature, the E. coli O157:H7 inoculated compost samples were inoculated (1:10 v/wt) with the 10-strain cocktail of CE cultures to reach ca.10 8 –10 9 CFU g −1 . Four treatments of compost samples were prepared the same as described in the first approach. For both approaches, two independent experiments were performed in triplicate. Experiments were performed as follows: Summer trials (August–September), Fall trials (October–December), and Winter trials (February–March) inside a greenhouse. Sterile cups containing compost samples were arranged in large plastic containers, and a digital hydrothermometer (EU 620-0915; VWR International, Radnor, PA, USA) for temperature and relative humidity was placed inside. Containers had recipients with saturated KCl solution and were closed every evening and opened in the morning. The moisture levels of the samples were adjusted every evening based on weight loss. Adjustment in the morning was not necessary since there was little moisture loss due to the overnight storage in high relative humidity. Therefore, samples were subjected to lower temperatures and high relative humidity overnight and high temperatures and decreased humidity during the day. Treatments were sampled on day 2 then every 4 days and analyzed for moisture content (the moisture levels of the samples were adjusted every day in the greenhouse for all samples) and bacterial enumeration. Briefly, 5 g of inoculated compost was mixed and homogenized with 45 mL of PBS in a sterile stomacher bag. The samples were then serially diluted and plated on TSA-R for the enumeration of E. coli O157:H7 or TSA for the enumeration of CE or the compost microflora. Data obtained from bacterial enumeration were expressed as log CFU per gram dry weight (CFU g/dw), and the detection limit of the plating method was approximately 100 CFU g/dw .
The analysis of pathogen survival data was performed using JMP 11.2.1 (SAS Institute Inc., Atlanta, GA, USA). Analysis of variance (ANOVA), followed by the least significant differences (LSD) test, was carried out to determine whether significant differences ( p < 0.05) existed among different treatments.
3.1. Isolation and Identification of CE Bacteria against E. coli O157:H7 Potential CE microorganisms were isolated from various samples, including dairy manure-based and chicken litter-based finished compost, plant-based compost, and commercial organic fertilizers ( n = 31). The 786 phenotypically different colonies were purified and tested for inhibition activity against E. coli O157:H7 using the spot-on-lawn method followed by broth co-culture method. A total of 22 isolates were considered as potential CE microorganisms. In the presence of individual CE strains, E. coli O157:H7 population reduction ranged from 1.1 to 3.9 logs in TYP broth and 0.9 to 3.7 logs in compost, with Kluyvera strain as the most effective . These CE isolates were identified as Brevibacillus parabrevis , Bacillus amyloliquefaciens , Pseudomonas thermotolerans , Comamonas testosterone , Enterobacter , Citrobacter , Raoultella , Kluyvera , unclassified Comanondaceae , and unclassified Enterobacteriaceae by 16S rRNA method. Three CE isolates ( B. parabrevis , B. amyloliquefaciens, and P. thermotolerans ) were selected for laboratory trials, and ten CE isolates were used for the greenhouse study. 3.2. Effectiveness of CE Treatment on the Growth Reduction in E. coli O157:H7 in Compost under Laboratory Conditions Under laboratory conditions, E. coli O157:H7 grew in the compost with or without CE application under three moisture levels (20, 30, and 40%) and two temperatures (22 and 30 °C) ( and ). As compared with the controls, the CE treatment was effective by reducing the growth of E. coli O157 within 3 days of incubation at 22 and 30 °C by 1.1~2.1, 2.2 ~2.6, and 2.6~3.4 logs in compost with moisture levels of 20, 30, and 40%, respectively. For the compost with 20% moisture, there was more reduction in E. coli O157:H7 at 30 °C than at 22 °C; however, at higher moisture contents (30 and 40%), CE reduced slightly more E. coli O157:H7 population at a lower temperature (22 °C). 3.3. Effectiveness of CE Treatment on the Growth Reduction in E. coli O157:H7 in Compost under Greenhouse Conditions To test the effects of seasonal changes on bacterial inactivation, experiments were performed in the fall, winter, and summer seasons. The average values of temperature in the greenhouse were 24.4, 21.2, and 28.4 °C for fall, winter, and summer trials, respectively, while the average values of relative humidity in the greenhouse were 42.9, 28.0, and 55.4%, respectively. Two different scenarios for pathogen inoculation were tested: a possible recontamination event of the finished compost and the presence of heat-adapted cells that survived the thermophilic phase of composting. For the controls, the season or the compost moisture levels did not influence overall the pathogen survival in the compost samples . In the presence of CE microorganisms, E. coli O157:H7 inoculated in composts with high moisture levels (30 and 40%) declined faster than in the compost with low moisture levels (20% MC) regardless of the inoculation method. Overall, the E. coli O157:H7 population was reduced more for non-adapted cells (0.06 to 2.14 log CFU/g) than the heat-adapted cells (0.02 to 1.54 log CFU/g) by CE treatment for all trials. These results demonstrated the impact of bacterial physiological state and moisture levels on pathogen survival in the compost environment. Seasons influenced the rate of pathogen inactivation. Although E. coli O157:H7 declined in CE-treated samples in all cases as compared with the controls, significant inactivation of non-adapted E. coli O157:H7 by CE microorganisms occurred after only 2 days of storage in the greenhouse in compost samples with higher moisture content (40 and 30%) during the fall and winter trials . In the compost with 20% MC, a significant reduction in E. coli O157:H7 by CE microorganisms took 16 days of storage for the same conditions. On the other hand, the heat-adapted cells showed resistance to inhibitory action by CE since significant differences between treatments and controls were present after 12 days for compost with 40 and 30% MC and 16 days of storage for compost with 20% MC in the fall trial. A similar outcome resulted from the winter trial: heat-adapted cells with CE treatments showed differences compared to controls in compost with 40% moisture content at day 8, 30% moisture content at day 12, and 20% moisture content at day 16 of greenhouse storage. As for the summer trial, there was no significant difference between the treatment and the controls in the first 4 days of greenhouse incubation for both heat-adapted and non-heat-adapted cells. E. coli O157:H7 population in most of the treatments dropped to significant levels after 8 days of storage in the greenhouse. The temperature in the greenhouse varied greatly between the three tested seasons (in the summer trial, occasional temperatures over 50 °C were recorded in the sample, whereas in the fall and winter, the temperature did not exceed 38 °C). Also, some of the CE strains did not grow at elevated temperatures (42 °C) and therefore may be less active when exposed to elevated temperatures.
Potential CE microorganisms were isolated from various samples, including dairy manure-based and chicken litter-based finished compost, plant-based compost, and commercial organic fertilizers ( n = 31). The 786 phenotypically different colonies were purified and tested for inhibition activity against E. coli O157:H7 using the spot-on-lawn method followed by broth co-culture method. A total of 22 isolates were considered as potential CE microorganisms. In the presence of individual CE strains, E. coli O157:H7 population reduction ranged from 1.1 to 3.9 logs in TYP broth and 0.9 to 3.7 logs in compost, with Kluyvera strain as the most effective . These CE isolates were identified as Brevibacillus parabrevis , Bacillus amyloliquefaciens , Pseudomonas thermotolerans , Comamonas testosterone , Enterobacter , Citrobacter , Raoultella , Kluyvera , unclassified Comanondaceae , and unclassified Enterobacteriaceae by 16S rRNA method. Three CE isolates ( B. parabrevis , B. amyloliquefaciens, and P. thermotolerans ) were selected for laboratory trials, and ten CE isolates were used for the greenhouse study.
Under laboratory conditions, E. coli O157:H7 grew in the compost with or without CE application under three moisture levels (20, 30, and 40%) and two temperatures (22 and 30 °C) ( and ). As compared with the controls, the CE treatment was effective by reducing the growth of E. coli O157 within 3 days of incubation at 22 and 30 °C by 1.1~2.1, 2.2 ~2.6, and 2.6~3.4 logs in compost with moisture levels of 20, 30, and 40%, respectively. For the compost with 20% moisture, there was more reduction in E. coli O157:H7 at 30 °C than at 22 °C; however, at higher moisture contents (30 and 40%), CE reduced slightly more E. coli O157:H7 population at a lower temperature (22 °C).
To test the effects of seasonal changes on bacterial inactivation, experiments were performed in the fall, winter, and summer seasons. The average values of temperature in the greenhouse were 24.4, 21.2, and 28.4 °C for fall, winter, and summer trials, respectively, while the average values of relative humidity in the greenhouse were 42.9, 28.0, and 55.4%, respectively. Two different scenarios for pathogen inoculation were tested: a possible recontamination event of the finished compost and the presence of heat-adapted cells that survived the thermophilic phase of composting. For the controls, the season or the compost moisture levels did not influence overall the pathogen survival in the compost samples . In the presence of CE microorganisms, E. coli O157:H7 inoculated in composts with high moisture levels (30 and 40%) declined faster than in the compost with low moisture levels (20% MC) regardless of the inoculation method. Overall, the E. coli O157:H7 population was reduced more for non-adapted cells (0.06 to 2.14 log CFU/g) than the heat-adapted cells (0.02 to 1.54 log CFU/g) by CE treatment for all trials. These results demonstrated the impact of bacterial physiological state and moisture levels on pathogen survival in the compost environment. Seasons influenced the rate of pathogen inactivation. Although E. coli O157:H7 declined in CE-treated samples in all cases as compared with the controls, significant inactivation of non-adapted E. coli O157:H7 by CE microorganisms occurred after only 2 days of storage in the greenhouse in compost samples with higher moisture content (40 and 30%) during the fall and winter trials . In the compost with 20% MC, a significant reduction in E. coli O157:H7 by CE microorganisms took 16 days of storage for the same conditions. On the other hand, the heat-adapted cells showed resistance to inhibitory action by CE since significant differences between treatments and controls were present after 12 days for compost with 40 and 30% MC and 16 days of storage for compost with 20% MC in the fall trial. A similar outcome resulted from the winter trial: heat-adapted cells with CE treatments showed differences compared to controls in compost with 40% moisture content at day 8, 30% moisture content at day 12, and 20% moisture content at day 16 of greenhouse storage. As for the summer trial, there was no significant difference between the treatment and the controls in the first 4 days of greenhouse incubation for both heat-adapted and non-heat-adapted cells. E. coli O157:H7 population in most of the treatments dropped to significant levels after 8 days of storage in the greenhouse. The temperature in the greenhouse varied greatly between the three tested seasons (in the summer trial, occasional temperatures over 50 °C were recorded in the sample, whereas in the fall and winter, the temperature did not exceed 38 °C). Also, some of the CE strains did not grow at elevated temperatures (42 °C) and therefore may be less active when exposed to elevated temperatures.
Composting is an environmentally friendly process for converting livestock and agricultural wastes into organic fertilizer and soil amendment. During composting, the high temperatures achieved in the thermophilic phase are critical for pathogen inactivation. However, despite high temperatures, extended survival of pathogens in compost has been reported . This study evaluated the effectiveness of selected competitive exclusion microorganisms (CE) isolated from composts for inactivating E. coli O157:H7 in dairy compost with different moisture levels under both laboratory and greenhouse conditions. According to the literature, lactic acid bacteria, Enterococcus , Pseudomonas , Paenibacillus , Streptomyces , Bacillus , and some commercially produced bacterial cultures have been widely used as CE microorganisms in controlling foodborne pathogens . Some of the CE species identified in this study were previously reported as possessing inhibitory activities against both human and plant pathogens. For example, Pseudomonas aeruginosa ISO1 and ISO2 isolated from the compost inhibited plant pathogens Pythium aphanidermatum and Fusarium solani . Wang and Jiang reported the inhibition of 10 fresh-produce outbreak strains of Listeria monocytogenes up to 2.2 logs by 17 CE strains isolated from compost, including Bacillus spp., Brevibacillus spp., Kocuria spp., Paenibacillus spp., and Planococcus spp. Additionally, Kluyvera , a soil bacterium, exhibited a significant reduction in E. coli O157:H7 in both liquid broth and compost . A previous study reported that Kluyvera ascorbate SUD165 could protect canola, Indian mustard, and tomato seedlings against the inhibitory effects of high concentrations of heavy metals such as nickel, lead, and zinc by providing the plants with sufficient ions . Iron is an essential micronutrient for most pathogenic bacteria, including E. coli O157:H7, in bacterial growth and metabolism, playing a vital role in various cellular processes . The robust iron sequestration capability of Kluyvera may account for the reduction in E. coli O157:H7 observed in this study. However, experimental confirmation is necessary to validate this hypothesis. Compost is rich in the nutrients, and studies have shown the growth of foodborne pathogens in compost under favorable conditions . Data from showed CE reduced slightly more E. coli O157:H7 population at lower temperatures (22 °C) in compost with higher moisture contents (30 and 40%). Being a mesophile, E. coli O157:H7 is expected to grow faster in higher moisture compost at 30 °C than at 22 °C. In contrast, the CE strains isolated from the finished compost grow better at room temperature. Due to the high growth rate of CE microorganisms in compost with high MC, it’s unsurprising that more E. coli O157:H7 was inactivated at room temperature than at 30 °C. Even though animal manure-based compost is highly recommended for use as the organic fertilizer or biological soil amendment in agricultural production, inadequately treated or handled compost has been implicated in a few produce-related outbreaks . It is well-documented that foodborne pathogens, such as Salmonella spp., can regrow in composted biosolids and stored biosolids . However, only a few studies have examined the growth potential of pathogens in animal manure-based compost. Kim and Jiang reported that E. coli O157:H7, Salmonella spp., and Listeria monocytogenes were able to grow ca. 2–4 logs in 3 days in compost in a greenhouse setting under different seasons when the population of indigenous microorganisms was low (<3 logs CFU/g) and moisture content at least 30–40%. To evaluate the impact on pathogen growth in compost, our CE treatment trials investigated several factors, such as temperature, compost moisture, and physiological stages of E. coli O157:H7, which were considered key factors influencing the fate of enteric bacterial pathogens in the environment . In this study, the maximal reduction in E. coli O157:H7 was 2 logs under greenhouse conditions, which is similar to our previous study on inhibiting L. monocytogenes in compost using CE microorganisms . Up to 2.2 log inhibition of L. monocytogenes in both compost extract and compost samples by compost-adapted CE microorganisms was reported, and the inhibition was affected by compost types, nutrient levels, and incubation temperatures. These results suggest the effectiveness of applying CE microorganisms to control foodborne pathogens in the finished compost. Due to the temperature gradients formed across the composting heaps or piles, some populations of bacterial pathogens may be heat-shocked and survive the composting process by adapting to sublethal temperatures. Singh et al. reported that heat-shocked E. coli O157:H7, Salmonella spp., and L. monocytogenes extended survival at lethal temperatures (50–60 °C) following heat shock at 47.5 °C for 1 h. Besides developing heat resistance, heat-shock response can also induce cross-resistance to other stressors, including competition from other microorganisms . In this study, it appears that the heat-shocked E. coli O157:H7 became more resistant to CE treatment than not heat-shocked pathogen in compost. A possible explanation is that the changes induced by newly expressed heat-shock genes could influence interactions of heat-shocked E. coli O157:H7 with other microorganisms . These interactions may affect adhesion, biofilm formation, nutrient utilization, or susceptibility to antimicrobial compounds produced by competing microorganisms. Further study is needed to understand this cross-resistance mechanism. As stated by Mead , factors unique to the field conditions affecting the efficacy of CE treatment should be evaluated. In this study, the reduction in E. coli O157:H7 in compost with similar moisture levels and temperatures by CE treatment was noticeably less under greenhouse conditions compared to laboratory conditions. Unlike the controlled environment for laboratory-based studies, pathogen persistence in the greenhouse environment is exposed to various stresses, such as fluctuations in temperature and relative humidity, UV exposure, unsteady airflow, and others. Based on our research findings, a cocktail of CE microorganisms should be applied a few days prior to the use of the finished compost, preferably in the colder seasons. The advantage of treating the finished compost with the compost-isolated CE microorganisms is that (i) these CE microorganisms are adapted to the compost environment, thus ensuring their survival; (ii) this biological control method ensures microbiological safety to the compost; and (iii) avoid major changes in compost physicochemical and microbiological properties.
Our results demonstrated that up to 99% population of E. coli O157:H7 cells, resulting from cross-contamination, can be effectively reduced within 2 days during colder seasons (winter and fall) by CE microorganisms (such as Brevibacillus , Bacillus , Pseudomonas , Kluyvera and so on) in the finished dairy compost with at least 30% moisture. For those heat-adapted E. coli O157:H7 cells surviving the thermophilic composting process, the inhibitory effects from CE became significant only after 8~12 days, suggesting the cross-resistance of the heat-adapted E. coli O157:H7 population. Both higher moisture content in the compost and cold seasons enhanced the activity of CE microorganisms against E. coli O157:H7. These results indicate that some indigenous compost microflora can be an efficient tool to control foodborne pathogens in finished compost and reduce the potential for soil and crop contamination. However, factors such as the physiological state of the bacteria, the environmental conditions, and compost moisture levels should be considered. Furthermore, those CE strains should be further characterized to ensure the safety of applying these biological control agents. Based on the results of this study, to prevent pathogen growth in finished compost due to cross-contamination, a cocktail of strains of competitive exclusion microorganisms can be applied a few days prior to the use of the finished compost, preferably in the colder seasons.
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