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Study protocol to investigate biomolecular muscle profile as predictors of long-term urinary incontinence in women with gestational diabetes mellitus
Marilza V. C. Rudge1,
Fátima P. Souza2,
Joelcio F. Abbade1,
Raghavendra L. S. Hallur1,
João Paulo C. Marcondes1,
Fernanda Piculo1,3,
Gabriela Marini1,4,
Giovana Vesentini1,
Lehana Thabane5,6,
Steven S. Witkin7,8,
Iracema M. P. Calderon1,
Angélica M. P. Barbosa1,9,
The Diamater Study Group,
M. V. Rudge,
A. M. P. Barbosa,
I. M. P. Calderon,
F. P. Souza,
J. F. Abbade,
L. S. R. Hallur,
F. Piculo,
G. Marini,
G. Vesentini,
L. Thabane,
M. S. Palma,
C. F. O. Graeff,
R. K. Arni,
R. D. Herculano,
D. F. Salvadori,
S. Mateus,
M. Dal Pai Silva,
C. G. Magalhães,
R. A. Costa,
S. A. M. Lima,
S. L. Felisbino,
W. Barbosa,
A. Atallah,
M. J. B. Girão,
Z. Di Bella,
S. M. Uchoa,
S. Payão,
A. Hijas,
B. Berghman,
R. De Bie,
L. Sobrevia,
B. Junginger,
F. C. B. Alves,
P. S. Rossignoli,
C. B. Prudencio,
M. I. G. Orlandi,
M. I. Gonçalves,
S. K. Nunes,
B. B. Catinelli,
S. Quiroz,
B. V. Sarmento,
F. A. Pinheiro,
C. I. Sartorão,
R. R. Lucas,
D. R. A. Reyes,
S. B. C. V. Quiroz,
E. M. A. Enriquez,
R. G. Oliveira,
J. F. Floriano,
J. P. C. Marcondes,
S. Barneze,
T. D. Dangió,
T. Pascon,
P. Rossignoli,
J. V. Freitas,
L. Takano,
F. Reis,
T. D. Caldeirão,
J. N. Fernandes,
A. M. Carr,
M. V. C. Gaitero,
J. E. Corrente,
H. R. C. Nunes,
A. F. Candido,
S. M. B. Costa,
J. V. F. Melo,
F. V. D. S. Reis,
G. A. Garcia,
G. B. Rabadan,
H. C. M. Bassin,
K. S. Suyama,
L. N. Damasceno,
M. L. S. Takemoto,
M. D. Menezes,
D. G. Bussaneli,
V. K. C. Nogueira,
P. R. Lima,
I. O. Lourenço,
J. Marostica de Sá,
R. A. Megid,
I. P. Caruso,
L. T. Rasmussen,
G. M. Prata,
M. A. Arantes,
G. A. R. Ferraz,
L. P. Camargo,
M. R. Kron,
J. E. Corrente &
H. R. C. Nunes
Pelvic floor muscles (PFM) and rectus abdominis muscles (RAM) of pregnant diabetic rats exhibit atrophy, co-localization of fast and slow fibers and an increased collagen type I/III ratio. However, the role of similar PFM or RAM hyperglycemic-related myopathy in women with gestational diabetes mellitus (GDM) remains poorly investigated. This study aims to assess the frequency of pelvic floor muscle disorders and pregnancy-specific urinary incontinence (PS-UI) 12 months after the Cesarean (C) section in women with GDM. Specifically, differences in PFM/RAM hyperglycemic myopathy will be evaluated.
The Diamater is an ongoing cohort study of four groups of 59 pregnant women each from the Perinatal Diabetes Research Centre (PDRC), Botucatu Medical School (FMB)-UNESP (São Paulo State University), Brazil. Diagnosis of GDM and PS-UI will be made at 24–26 weeks, with a follow-up at 34–38 weeks of gestation. Inclusion in the study will occur at the time of C-section, and patients will be followed at 24–48 h, 6 weeks and 6 and 12 months postpartum. Study groups will be classified as (1) GDM plus PS-UI; (2) GDM without PS-UI; (3) Non-GDM plus PS-UI; and (4) Non-GDM without PS-UI. We will analyze relationships between GDM, PS-UI and hyperglycemic myopathy at 12 months after C-section. The mediator variables to be evaluated include digital palpation, vaginal squeeze pressure, 3D pelvic floor ultrasound, and 3D RAM ultrasound. RAM samples obtained during C-section will be analyzed for ex-vivo contractility, morphological, molecular and OMICS profiles to further characterize the hyperglycemic myopathy. Additional variables to be evaluated include maternal age, socioeconomic status, educational level, ethnicity, body mass index, weight gain during pregnancy, quality of glycemic control and insulin therapy.
To our knowledge, this will be the first study to provide data on the prevalence of PS-UI and RAM and PFM physical and biomolecular muscle profiles after C-section in mothers with GDM. The longitudinal design allows for the assessment of cause-effect relationships between GDM, PS-UI, and PFMs and RAMs myopathy. The findings may reveal previously undetermined consequences of GDM.
Gestational diabetes mellitus (GDM) and urinary incontinence (UI) are two clinical entities with substantial social and economic burden, associated with significant direct and indirect public health costs [1]. In addition, they often affect women at a young age. A new emphasis in the early diagnosis of GDM aims not only to prevent perinatal morbidity and mortality but also to identify potential long-term maternal complications [2]. In 2013, 382 million people had diabetes, and there is a strong likelihood that this will rise to 592 million by 2035. Brazil, a low-and-middle-income country, is one of the top 10 countries in terms of numbers of diabetic people, with projections of almost 19.2 million [3].
Beginning in 2008 [4] researchers reported that GDM resulted in postpartum genitourinary dysfunction that persisted for 2 years after delivery [5, 6]. Previous GDM was shown to be an independent risk factor for Pregnancy Specific- Urinary Incontinence (PS-UI), a risk factor for UI two-years after the Cesarean (C) section. The link between GDM and PS-UI with increased long-term UI highlighted the potential under-explored contribution of GDM to the mechanisms leading to long-term UI [5]. This was an unanticipated finding that was not included in the classical definition of long-term GDM-related outcomes [2]. Thus, to improve the quality of life in women with GDM, it is imperative to understand the connection between GDM and PS-UI. Delineation of the involved mechanism will lead to the development of protocols to reduce long-term UI complications.
The conceptual model delineated by Delancey et al. in the Lifespan Analysis of pelvic floor muscles (PFM) [7] identified GDM as an inciting factor for long-term UI [8]. GDM and long-term UI are two clinical entities with a substantial economic and health impact, ethical concerns related to the use of PFM biopsy material for investigation have limited clinical investigation in this area. Utilizing our expertise in diabetic pregnant rat models [9,10,11,12,13,14], we initiated a "bedside to bench" translational study to obtain a deeper understanding of the influence of GDM and pregnancy on urethral and rectal myopathology. The conceptual model is shown in Fig. 1.
Conceptual model of the role of integration between GDM, PS-UI and RAM-PFM myopathy as a new triad in determining the prevalence of long-term maternal UI
Relevance and uniqueness of our translational studies: from "bedside to bench"
Presently, human studies are based on clinical findings of a high incidence of UI 2 years after GDM. The role of GDM in the pathophysiological development of UI remains unclarified [15]. Investigations linking both entities with the synergistic co-activity of the PFM and RAM are insufficient [16]. Current clinical studies have provided evidence for PFM involvement in the etiology of PS-UI [17,18,19,20], including more recently, the contribution of extracellular matrix (ECM) components, such as collagen [21] and glycosaminoglycans (GAGs) [22] to female pelvic floor function.
Pregnancy itself alters the PFM, in preparation for parturition. Alperin et al. reported that adaptations during pregnancy occur in the myofibers of rat PFMs, which increase in length by the serial addition of sarcomeres [23]. Although the biochemical alterations in PFM extracellular matrix due to pregnancy include an increase in collagen V and a differential response in enzymatic vs. glycosylated collagen crosslinks, the relationships between PFM biochemical and mechanical parameters remain unclear [24].
In pregnant diabetic rats, our research group identified thinning, atrophy, disorganization, and disruption in the circular annulus associated with the co-localization of fast and slow fibers. This was accompanied by a steady decrease in the proportion of fast versus slow fibers (fast: slow, 1.5:1) associated with increased collagen deposition, severe fibrosis, lipid droplets, and numerous subsarcolemmal, and intermyofibrillar mitochondria [25]. These characteristics differentiated the urethral striated muscles of short-term severe diabetic pregnant rats and long-term mild diabetic pregnant rats from virgin, pregnant and diabetic control groups [20]. The diabetic models were obtained by streptozotocin injection, and according to the dose and duration of the hyperglycemic stimulus, they are classified as short-term severe diabetes or long-term mild diabetes [25, 26]. The increase in collagen and severe fibrosis may also affect the contractile properties of the urethra [26, 27]. The ECM molecular analyses of urethral components showed no difference in type I and type III collagen expression levels in short-term severe diabetic pregnant rats. However, the collagen type I /III ratio was higher in the hyperglycemic pregnant rats compared to the virgin group. The increased collagen type I/III ratio can favour a stiffer urethral tissue leading to an influence of hyperglycemia on the remodelling of urethral connective tissue in pregnant diabetic rats [28, 29].
In conclusion, these experimental results demonstrated that both long-term mild hyperglycemia and short-term severe hyperglycemia negatively impacted the muscle health in rats. RAM is subjected to similar structural changes related to pregnant diabetic myopathy [25, 26, 28] with intramuscular transformation and reorganization in fiber types [30,31,32].
Liu et al. showed that diabetes-induced time-dependent alterations of the external urethral sphincter and abnormal activity presumably contributes to the abnormal voiding function seen in diabetes [33]. Obesity, insulin resistance, and type 2 diabetes mellitus (T2DM) are associated with a significantly increased prevalence of vascular fibrosis and stiffness [34].
Significance of the proposed study: the bench-bedside proposal
Pregnant women with GDM are at increased risk of UI [35]. However, the direct association between women with GDM and PS-UI is undetermined. A few studies have reported women with GDM to have a high prevalence of UI due to higher body mass index, obesity, and macrosomia in their infants [36, 37]. Although the exact mechanism remains unclear, excess weight gain during pregnancy may exert pressure on the PFM, which increases pressure on the bladder and influences urethral mobility, leading to UI [38]. In addition, hyperglycemia in women with GDM may cause polyuria or detrusor instability. In a cross-sectional survey, Kim et al. [4] examined the prevalence of PS-UI among women who had GDM during pregnancy, surveying 228 women, and found that 49% of women had weekly or more frequent incontinence during pregnancy, and 50% of the women reported PS-UI within 5 years following delivery. A high prevalence of obesity may have contributed to the elevated rate of PS-UI during pregnancy and after delivery. Obesity was present in 42% of women during pregnancy and in 46% after delivery. Their conclusion was that PS-UI was common among women with GDM.
Barbosa et al. [5] and Chuang et al. [6] determined whether GDM was an independent risk factor for PS-UI postpartum. They found that women with GDM exhibited symptoms of PS-UI for up to 2 years postpartum in comparison to women without GDM. They concluded that GDM was an independent risk factor for UI postpartum with a significant impact on the quality of life. They also suggested that women with GDM should be provided with timely consultation and support once UI occurs.
Factors associated with PS-UI, before or at the time of GDM diagnosis, have also been associated with UI two-years post-C-section. Having GDM in a previous pregnancy was an independent risk factor for PS-UI [5]. PS-UI is a new clinical entity linked to GDM with a direct or indirect relationship to hyperglycemic myopathy. The possibility that it may represent the first clinical symptom of PS-UI requires more investigation. Experimental results on urethral muscles and RAM from pregnant diabetic rats have revealed a variety of abnormalities in muscles involved in urinary continence. The abnormalities in skeletal muscles and ECM in pregnant diabetic rats provide a rationale for multidisciplinary human in vivo research to investigate similar hyperglycaemic myopathy in GDM skeletal muscles during C-section. Brazil, a low-middle income country with a high prevalence of GDM and T2DM has established a Perinatal Diabetes Research Center (PDRC) at Botucatu University Hospital. The Center provides the initial GDM diagnosis and maintains strict glycemic control during pregnancy. The collection of muscle samples for in-depth analysis of the connection between GDM history and PS-UI with long-term UI has not previously been attempted.
Findings from GDM, PS-UI, and RAM/PFM muscle tissue lesions will be integrated to predict long-term risk for UI. Ethical approval was obtained to initiate RAM sample collection during C-section at PDRC, due to successful results on our combined clinical and experimental studies described above.
Potential mediators and moderators of GDM and UI
We seek to attempt to clarify the mechanisms that link two highly prevalent illnesses that affect women's health, are associated with high health costs, and are expected to increase in frequency.
Two procedures to evaluate underlying/influential factors are the mediator and moderator variables [39, 40]. The mediator model assumes that predictor variables are responsible for changes in mediator variables, and that mediator variables subsequently cause changes in outcome variables [41]. The moderator model analyzes qualitative or quantitative variables that affect the magnitude of the relation between an independent and a dependent variable [42].
Despite the established inter-relationship between DM and UI and pregnancy and UI, the inter-relationships between GDM and long-term UI have rarely been studied using a mediator or moderator model [39].
Furthermore, little information has been reported concerning a positive correlation between GDM and long-term UI [5, 35, 39, 42,43,44,45]. An outline of our proposed analysis is described in Fig. 2. It has components similar to prior investigations [40, 46].
Potential confounders –Mediators and Moderators of Diamater study
The longitudinal assessment of the role of GDM plus PS-UI on UI 12 months after C-section using mediator variables provides a foundation for optimizing future treatment for individual women and under what circumstances [47, 48].
GDM plus PS-UI and clinical-biomolecular muscle profile as a long-term predictor of UI
GDM during pregnancy and its association with PS-UI and a specific PFM or RAM biomolecular muscle profile constitute a new triad leading to long-term UI after C-section. We hypothesize that UI 12 months after C-section will be higher in women who developed GDM plus PS-UI compared to women without these factors. Our secondary hypotheses are: (1) GDM plus PS-UI is an independent risk factor for UI development 12 months after C-section and (2) Hyperglycemic-related myopathy parameters are potential mediators of the association between GDM plus PS-UI and symptomatic UI 12 months after C-section.
Therefore, we aim to quantify the clinical-biomolecular muscle profile of PFM and RAM hyperglycemic myopathy during pregnancy in GDM women with PS-UI as exposure, on UI 12 months after C-section and compare the profile to that obtained from women who did not have GDM or PS-UI. We include an analysis of the mediators and moderator variables that are related to PFMD and UI in this evaluation (Fig. 2).
The primary and secondary research questions to be addressed in this research are:
Primary question
➣ Is the incidence of UI 12 months after C-section different in women who developed GDM plus PS-UI compared to women without these conditions?
Secondary questions
➣ Does the presence of both GDM plus PS-UI modify the risk of UI 12 months after C-section independently of the moderator variables?
➣ Which mediator variables of hyperglycemic myopathy are abnormal in women who developed GDM and PS-UI compared to women without these conditions?
Aim of the study
➣ To analyze moderators and mediators involved in the relationship between GDM plus PS-UI and UI 12 months after C-section.
➣ To assess the association between GDM plus PS-UI and clinical assessment of PFM and RAM by (1) utilization of ultrasonographic, electromyographic and morphological assays, (2) molecular analysis of muscle fiber function, ECM-related genes and proteins, gene and protein expression, (3) OMICS and (4) ex-vivo assessment of RAM contractility. This will result in a comprehensive characterization of the clinical-biomolecular muscle profile of PFM and RAM hyperglycemic myopathy.
➣ To determine the correlation between maternal age, pre-pregnancy body mass index, nutritional parameters, glycemic level, quality of glycemic control, insulin therapy, and insulin dose with GDM plus PS-UI and UI 12 months after C-section.
➣ To examine the unidirectional relationship among the triad GDM, PS-UI, and hyperglycemic myopathy in UI 12 months after C-section compared with the normal population (Normoglycemic without PS-UI and without hyperglycemic myopathy).
Study area, design, and setting
The Diamater is an ongoing cohort prospective study of GDM pregnant women with PSUI following C-section, seen at the Perinatal Diabetes Research Center (PDRC), a tertiary center for Diabetes Care in Brazil, from April 2017 to March 2022. PDRC is located in three different cities of São Paulo State, including PDRC, FMB-UNESP, Botucatu, Clinic of Children's Hospital Maternal Risk Pregnancy, Faculdade de Medicina de Marília (FAMEMA)-UNESP, Marilia and Regional Hospital-UNESP of Assis.
Participants need to satisfy the following inclusion and exclusion criteria.
Eligible participants are volunteer pregnant women with a GDM diagnosis between 24 and 28 weeks of pregnancy who have follow-up prenatal care at PDRC and C-section delivery. Subjects will be primigravida or second gravida women who underwent a planned C-section in their previous pregnancy, between 18 to 40 years old; with a singleton pregnancy and seen between February 2017 and March 2022.
Pregnant women aged < 18 years and > 40 years old, pre-pregnancy UI, known type 1 or type 2 diabetes mellitus, preterm delivery (< 37 weeks of gestation), multiple pregnancies, chronic arterial hypertension, pre-eclampsia, eclampsia, known fetal anomaly, urogenital cancer, high-risk pregnancy, multiple sclerosis, asthma, chronic sinusitis, ulcerative colitis, biliary cirrhosis, inflammatory bowel disease and/or anorectal surgery/ personal history of connective tissue disease, vaginal delivery or any clinical condition that may have jeopardized health status or the ability to provide written informed consent.
Method of recruitment of participants
Participants will be recruited in two phases. The objective of the first phase (Phase 1) is to identify normoglycemic or hyperglycemic pregnant women with or without PS-UI. These women will be followed up until delivery. The second phase (Phase 2) of the study will begin at the time of delivery (C-section), and these women will be followed for up to one-year postpartum.
Pregnant women will be recruited at the time of antepartum testing for GDM at 24 to 28 weeks gestation. The study will be described, and the women will be asked to volunteer and sign the informed consent form. Socio-economic status information will be collected. Clinical data and blood samples will be collected, questionnaires about UI will be applied, and clinical PFM and RAM assessment will be performed. At 36 weeks of pregnancy, another informed consent will be requested to collect the RAM sample (during the C-section) for OMICS, genetic, protein, and morphological analyses (Additional file 1). The criteria for performing a C-section will be established by the hospital staff. The women will be included in phase 2 only if they have a cesarean delivery for obstetrical or clinical indication.
Women will be included in phase 2 cohort following C-section delivery. The cohort groups for the primary outcome will be established at this point. Prenatal care assistance, including GDM diagnosis and treatment, as well as the PS-UI diagnosis made at any time during pregnancy, will be used in the composition of the four study groups.
All recruited patients will be evaluated as follows: visit − 2- at 34 to 38 weeks gestational age (T2) and inclusion in the C-section delivery cohort (beginning of phase 2). After visit − 3-within 24 and 48 h postpartum (T3), visit − 4- 6 weeks postpartum (T4), and 6 and 12 months postpartum (T5 and T6, respectively). Four cohorts will be followed-up based on the results of GDM and PS-UI diagnosis: (i) GDM plus PS-UI; (ii) GDM without PS-UI; (iii) Non-GDM plus PS-UI and (iv) Non-GDM without PS-UI.
GDM diagnosis
The diagnostic protocol for GDM is a 75-g oral glucose tolerance test (OGTT) (Table 1) combined with the glycemic profile in use at PDRC-UNESP-Brazil since 1984 [46] for pregnant women without confirmed GDM or overt diabetes in their first trimester of pregnancy. All hyperglycemic pregnant women will be classified as GDM.
Table 1 GDM diagnosis by 75 g-OGTT and glycemic profile
Prenatal management of patients with GDM
All hyperglycemic pregnant women will undergo the same treatment, including adequate nutritional advice from nutritionists, encouragement to exercise regularly, and insulin associated with dietary advice if necessary [46].
Diagnosis of UI and definition of PS-UI
For the primary outcome of the study, UI will be considered if there is any involuntary leakage of urine according to the International Continence Society definition of UI [49]. PS-UI is defined as any urinary leakage newly onset during pregnancy ascertained by self-reporting [50]. Participants will be asked whether before pregnancy they had leaked or lost control of even a small amount of urine with activity such as coughing, lifting, or exercise or if they experienced an urge or pressure to urinate and could not go to the toilet fast enough (urge UI). Pregnant women with PS-UI and/or urge UI before pregnancy will be excluded from the study.
Pregnant women who reported PS-UI will be asked to complete the Brazilian version of the International Consultation on Incontinence Questionnaire-Urinary Incontinence-Short Form (ICIQ-SF) [51]. The participants will also be asked about the frequency and quantity of urinary leakage to assess the validated Incontinence Severity Index (ISI). The severity will be further graded depending on the frequency of leakage (grade I: once a week at most; grade II: two or more episodes per week, but not daily and grade III: one or more episodes of leakage per day) according to ISI questionnaire [52].
Assessment procedures and instrumentation
A comprehensive questionnaire was developed for collecting information on the socio-demographic, anthropometric, medical, and obstetrical history. A Case Report Forms (CRF) will be established for data collection of variables for the Diamater study from all subjects. In summary, the databank includes patients' identification, socio-economic status, demographic characteristics, obstetric history, delivery and birth outcomes, perinatal complications, neonatal morbidity, maternal postpartum follow-up and all variables related to biochemical and molecular analysis, functional and morphological assessments during pregnancy and at 6 weeks and 6–12 months after C-section (Table 2). Additional information will be collected to describe the study population. Several variables will be assessed as confounders or effect modifiers of the relationship between GDM and/or PSUI and intestinal microbiota colonization and UI 12 months after C-section. The participant flow chart is shown in Fig. 3.
Table 2 Data collection questionnaire, clinical assessment and laboratory analysis of study participants
Phases and Follow-up timelines of the proposed protocol
Moderator variables
The moderator variables to be included in the analysis are maternal age, socio-economic status, educational level, ethnicity, pre-pregnancy body mass index [53], weight gain during the pregnancy [54], maternal nutritional parameters, quality of glycemic control, glycemic level during pregnancy and insulin therapy and dose.
Mediator variables
Clinical assessment of PFM and RAM, the RAM sample collection and laboratory assays will be included in this analysis to characterize the hyperglycemic myopathy. All specific protocols for clinical assessment and laboratory analysis of pelvic floor muscles and rectus abdominis muscle as mediator variables are described in Additional file 1.
Predictor variables
GDM and PS-UI are considered as predictor variables.
PFM and UI 12 months after C-section are considered the outcome variables. The PFM and RAM analysis will be considered as mediator variables in this interrelationship. The common procedure for this is to apply statistical methods on production data to establish the interrelationship. The detailed procedure is described in Additional file 1.
Data measurement
Digital palpation and vaginal squeeze pressure
For the digital vaginal evaluation, the examiner will follow the Messelink et al. orientation [55]. A perineometer value higher than 33.6 mmHg will be considered as normal based on our previous nulliparous women study [5].
3D pelvic floor ultrasound (PFUS)
Levator function will be assessed using the modified Oxford grading of muscle strength scoring system [56]. Transperineal ultrasonographic assessment biometry of PFM and RAM data will be collected, including anteroposterior diameter, transversal diameter, Hiatal area, and levator ani muscle thickness, at rest, contraction and Valsalva maneuver. AGE Voluson "i" system with RAB 2–6 RS (2–6 MHz) curved array three-dimensional transducer (GE Healthcare, Zipf, Austria) with an 8–4 MHz curved-array volume transducer at an acquisition angle of 70° in the sagittal plane and 85° in the coronal plane (frame rate is approximate 3 Hz) will be used [57, 58].
3D RAM ultrasound protocol
First, the transducer will be placed above the umbilicus. It will then be moved laterally from the midline until the cross-section of the muscle will center on the image [59]. Ultrasound images will be acquired in the B-mode using a portable ultrasound unit, the GE Voluson "i" system with a RAB 2–6 RS (2–6 MHz) curved array three-dimensional transducer (GE Healthcare, Zipf, Austria) [59]. The thickness of the lateral abdominal muscles will be assessed at rest and during submaximal contraction of these muscles, bilaterally analyzing 36 images for each participant [60]. The anatomic and functional evaluation will be conducted in the lower right portion of RAM in a transversal direction along the muscle [56]. Before RAM image acquisition under PFM contraction, the patient will undergo a PFM function test according to the International Continence Society [55] to avoid bias during US evaluation, and to analyze its function subjectively.
Surface electromyograms (EMGs) will be recorded using an eight-channel electromyography (EMG) device (New MiotoolUro Wireless; Porto Alegre, Brazil), 16-bit A/D converter, a sampling frequency rate fixed at 2000 Hz, automatic gain, safety isolation for 3000 V and common moderate (CMRR) of 126 dB. The signal will be filtered using a 20–500 Hz dual-pass Butterworth second-order digital filter. The preparation of the skin, sensor placement, and location preparation will be acquired according to the recommendation of the Surface Electromyography for the Non-Invasive Assessment of Muscles (SENIAM). Modified Glazer protocol will be used to verify muscle activity during rest-activity and fast and hold contractions. These protocols will be used twice, one only asking to increase abdominal pressure without conscious contraction of the pelvic floor and the second time only performing pelvic floor contractions.
Laboratory data of maternal blood collection and analysis for biochemical analysis
Serum levels of relaxin, insulin, glucose, chemokine (C-C motif) ligand 7 (CCL7), calcium, calcitonin, parathyroid hormone (PTH), and vitamin D in maternal blood will be determined. The serum aliquots will be stored at − 80 °C for further batch processing according to the specific assay kit (relaxin: R & D Systems Catalog Number DRL200; Insulin: R&D Systems Catalog Number DINS00; and CCL7; R&D Systems Catalog Number DCC700). The total calcium levels (Catalog No. 448), calcitonin and PTH levels by the chemiluminescence method, vitamin D by high-performance liquid chromatography (HPLC) by following the procedures of processing and analysis of the manufacturer's manual.
RAM sample collection, storage, and laboratory assays
RAM sample collection
RAM samples will be collected according to a specific protocol. Morphological characterization, molecular analysis of muscle fiber function, ECM-related genes and proteins, gene and protein expression, OMICS, and ex-vivo assessment of RAM contractility will be performed according to specific protocols to characterize the hyperglycemic myopathy.
A biological sample of RAM from the region of a transverse Pfannenstiel incision will be obtained during C-section. RAMs are of mixed muscle fiber type [61, 62]. A 4 cm RAM tissue will be sampled in the lower portion. Dissections of skeletal muscle will be obtained within 10 min of delivery, dissected free from visible adipose and connective tissues, immediately divided into six fragments and stored according to different assays for further analysis.
Morphological assays
Part of the RAM will be harvested, powdered with talcum, frozen in liquid nitrogen and maintained at − 80 °C until processed by histochemical and immunohistochemical techniques for morphometric analysis and, to analyze the distribution, quantification, and characterization of key structural ECM components, such as type I and III collagens, the collagen type I/III ratio and GAGs. It will be examined via light microscopy and photographed. The morphometric analyses will be performed with Image-Pro Plus software (Version 7.0, Media Cybernetics, Silver Spring, MD) at Case Western Reserve University (OH). The proportions of RAM that fit each of the following types will be recorded: striated muscle, collagen, and blood vessel. Other samples (three samples/group) will be immersed in a fixative solution containing 0.1% ruthenium red, 3% glutaraldehyde, and 0.1 M cacodylate buffer for 12 h at 4 °C before transmission electron microscopy for ultrastructural analysis.
It is not possible to calculate the sample size for Phase 1 of the recruitment. All eligible pregnant women will be invited to be included in this phase. Considering that the incidence of UI was higher at 24-months in GDM-positive C-section post-partum women (44.8%) as compared with women without GDM (18.4%) [5], assuming a two-sided confidence level of 95% and power of 80%, it will be necessary to follow-up 49 C-section post-partum women in each purposed cohort to identify at least a 22% difference between them. Considering a 20% loss in follow-up, we will include 59 women in each cohort, which means that 236 women will be included in this research.
The mediator models assume that the predictor variable causes changes in the mediator variable, and the mediator variable then causes changes in the outcome variable. Mediation analysis will be conducted to evaluate whether the effect of GDM plus PS-UI on long-term UI is mediated through alteration in levels of all assessed parameters. The patient flow will be summarised using a diagram while social-demographic and obstetrics baseline characteristics will be reported as mean and standard deviation for continuous variables and count for categorical variables.
Multivariate logistic regression analyses will be conducted to identify the mediator variables and the outcome (UI 12-month C-section post-partum) that will be changed by the predictor variable (GDM plus PS-UI) as an independent variable after adjusting for confounders. Clinically important covariates will be investigated as potential confounders whenever appropriate for each outcome. There is likely to be missing data that will likely with the duration of the follow-up. The multiple imputations will be used to handle missing data [63]. Results will be expressed as odds ratio [OR], 95% confidence intervals and associated p-values. For all tests, the level of significance will be set at a p-value < 0.05. Assessment of the functional, morphological, biochemical, and molecular mediator variables are presented in Table 3.
Table 3 Statistical tools will be used for the study
Patient and public involvement
The development of the research questions and outcome measures was performed based on previously published clinical research and from our prior translational studies. Patients and the public will not be involved in the study design, recruitment, and the conduct of the study. The patients involved in this study are those admitted to the University Hospital-Botucatu Medical School-UNESP. After completion of the data analysis, we plan to introduce the results into our routine practice of long-term follow-up care. We are also planning to translate the results into short and easy-to-read summaries to disseminate it to the relevant patient community groups through local media.
Ethics and dissemination
The Institutional Review Board of Botucatu Medical School-UNESP (CAAE: 82225617.0.0000.5411) approved the Diamater study protocol. Written informed consent will be obtained from all subjects, and the procedures used in the study are in accordance with the guidelines of the Helsinki Declaration on human experimentation.
The patients will be exposed to only low risk during the study. The participants' information will be stored electronically or in a locked file in the project office. The documentation of research data and management of the study will follow the Guideline for Good Clinical Practice in collecting, storing, and processing data anonymously [50]. All samples will be managed and stored in a specific biorepository for the research and results disseminated in peer-reviewed journals.
The potential benefit to subjects
While there is no direct benefit to subjects, being asked about their health status in the first year postpartum by a member of the research team every 3 months may raise the mother's awareness of her health and that of her newborn. At PDRC, during the follow-up period, a nutritional assessment and exercise programs will be offered as well as long-term health education and promotion that is crucial to effectively control GDM and UI. This is particularly important for pregnant women in a low and middle –income country like Brazil.
The study team will also focus on expanding the number of new researchers through mentorship and supervision. A longitudinal study, such as the Diamater study protocol offers undergraduate, masters, Ph.D and postdoctoral students a special environment to gain experience with longitudinal data sets. Based on this premise, scholarships for these students are included in the financial support to Diamater study from our state and national research agencies. This prospective study is intended to create and reinforce national and international cooperation, as well as to attract international postdoctoral students and provide new biomarkers that will improve the ability to identify risk factors in GDM women more accurately.
The primary investigator has extensive training and experience in clinical research and relevant bioethics. The research staff will include a team of primary researchers that have extensive qualifications and expertise to effectively perform the study. All study staffs are trained and routinely re-educated about the ethical conduct of human subject research. There are no anticipated physical, social, legal, or economic risks associated with the study. There is minimal risk of breach of confidentiality. There are no vulnerable populations that are specifically targeted in this study. The findings of this study will be disseminated through peer-reviewed international and national journals, conferences, and seminars.
This study will provide new information to the limited longitudinal data currently available on factors contributing to long-term UI after GDM exposure. It will delineate multiple factors that may help to understand the performance of potential moderator and mediator variables necessary to establish a strategic plan to minimize the underlying mechanisms responsible for increased risk of long-term UI in GDM mothers. An enhanced understanding of the impact of modifiable risk factors can lead to protocols to reduce the rates of UI and associated health care costs, improve the quality of life of affected women and contribute to the global eradication of UI after GDM exposure. It will also enable clinicians to deal more effectively with individual women after their pregnancy and facilitate the transition of the Brazilian Health System from a curative to a preventive strategy [65].
In conclusion, Diamater is an ongoing study recruiting GDM pregnant women at a prenatal care outpatient clinic to investigate the relationship between GDM plus PS-UI with the occurrence of symptomatic UI plus PFMD 1 year after C-section and assess whether this relation can be explained by hyperglycaemic myopathy. It offers the unique opportunity to establish well-powered biomarker research in a new triad composed of GDM + PS-UI+ hyperglycemic myopathy as a predictor of long-term UI and PFMD. This approach allows for future innovative treatment proposals.
This is an ongoing study, and data sharing does not apply to this article. No data were generated or analyzed during the current study. Protocol related information can be obtained from the corresponding author (Marilza V.C. Rudge) upon request.
One-way analysis of variance
CCL7:
Chemokine C-C motif ligand 7
CRF:
Case Report Forms
C-section:
DIAMATER:
Diabetes and Maternity
ECM:
Extracellular Matrix
EMG:
EMGs:
Surface electromyograms
GAGs:
Glycosaminoglycans
HPLC:
High-Performance Liquid Chromatography
ICIQ-SF:
International Consultation on Incontinence Questionnaire-Urinary Incontinence-Short Form
IRB:
The Institutional Review Board
ISI:
Incontinence Severity Index
OGTT:
OPLS:
Orthogonal partial least squares
PCR:
Polymerase chain reaction
PDRC:
The Perinatal Diabetes Research Centre
PFM:
Pelvic Floor Muscles
PLS:
Partial least squares
PS-UI:
Pregnancy Specific Urinary Incontinence
PTH:
Rectus Abdominis Muscles
RNA:
Ribonucleic acid
SENIAM:
Surface Electromyography for the Non-Invasive Assessment of Muscles
T2DM:
UNESP:
Universidade Estadual Paulista Júlio de Mesquita Filho
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We would like to thank the Perinatal Diabetes Research Center (PDRC) -Botucatu Medical School-UNESP, Brazil. We gratefully acknowledge the substantial contribution of all women who participated/participating in the Diamater study.
The Diamater Study Group: Rudge MV, Barbosa AMP, Calderon IMP, Souza FP, Abbade JF, Hallur LSR, Piculo F, Marini G, Vesentini G, Thabane L, Palma MS, Graeff CFO, Arni RK, Herculano RD, Salvadori DF, Mateus S, Dal Pai Silva M, Magalhães CG, Costa RA, Lima SAM, FelisbinoSL, Barbosa W, Atallah A, Girão MJB, Di Bella Z, Uchoa SM, Payão S, Hijas A, Berghman B, De Bie R, Sobrevia L, Junginger B, Alves FCB, Rossignoli PS, Prudencio CB, Orlandi MIG, Gonçalves MI, Nunes SK, Catinelli BB, Quiroz S, Sarmento BV, Pinheiro FA, Sartorão CI, Lucas RR, Reyes DRA, Quiroz SBCV, Enriquez EMA, Oliveira RG, Floriano JF, Marcondes JPC, Barneze S, Dangió TD, Pascon T, Rossignoli P, Freitas JV, Takano L, Reis F, Caldeirão TD, Fernandes JN, Carr AM, Gaitero MVC, Corrente JE, Nunes HRC, Candido AF, Sarmento, Costa SMB, Dangió TD, Pascon T, Melo JVF, Takano L, Reis FVDS, Caldeirão TD, Carr AM, Garcia GA, Rabadan GB, Bassin HCM, Suyama KS, Damasceno LN, Takemoto MLS, Menezes MD, Bussaneli DG, Nogueira VKC, Lima PR, Lourenço IO, Marostica de Sá J, Megid RA, Caruso IP, Rasmussen LT, Prata GM, Piculo F, Vesentini G, Arantes MA, Ferraz GAR, Camargo LP, Kron MR, Corrente JE, Nunes HRC.
This study is funded by the São Paulo Research Foundation-FAPESP, São Paulo, Brazil in a 5 year (01-04-2017 to 31-03-2022) project grant (No: FAPESP 2016/01743–5), a government funding agency with the aim of providing grants, funds, and programs to support research, education, and innovation. The funding agency had no role in the design of this study and will not have any role during the collection, analysis, interpretation of data, in writing the manuscript or in decision to submit results. Postdoctoral fellowships and undergraduate scholarships for the Diamater project are supported by the São Paulo Research Foundation-FAPESP, São Paulo, Brazil, under the grant No: FAPESP 2016 ∕ 01743–5.
Department of Gynecology and Obstetrics, Botucatu Medical School (FMB), São Paulo State University (UNESP), CEP18618-687, Sao Paulo, Brazil
Marilza V. C. Rudge, Joelcio F. Abbade, Raghavendra L. S. Hallur, João Paulo C. Marcondes, Fernanda Piculo, Gabriela Marini, Giovana Vesentini, Iracema M. P. Calderon & Angélica M. P. Barbosa
Physics Department, Institute of Biosciences, Letters and Exact Sciences, Multiuser Center for Biomolecular Innovation, UNESP-São Paulo State University, Sao Paulo, Brazil
Fátima P. Souza
Physiotherapy Department, Faculdades Integradas de Bauru, FIB, Sao Paulo, Brazil
Fernanda Piculo
Universidade do Sagrado Coração (USC), Jardim Brasil, Bauru, Sao Paulo, Brazil
Gabriela Marini
Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
Lehana Thabane
Biostatistics Unit, Father Sean O'Sullivan Research Centre, St Joseph's Healthcare-Hamilton, Hamilton, ON, Canada
Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, USA
Steven S. Witkin
Institute of Tropical Medicine, University of Sao Paulo Medical School, Sao Paulo, Brazil
School of Philosophy and Sciences, Department of Physiotherapy and Occupational Therapy, UNESP-São Paulo State University, Marília, Sao Paulo, Brazil
Angélica M. P. Barbosa
Marilza V. C. Rudge
Joelcio F. Abbade
Raghavendra L. S. Hallur
João Paulo C. Marcondes
Giovana Vesentini
Iracema M. P. Calderon
M. V. Rudge
A. M. P. Barbosa
I. M. P. Calderon
F. P. Souza
J. F. Abbade
L. S. R. Hallur
F. Piculo
G. Marini
G. Vesentini
L. Thabane
M. S. Palma
C. F. O. Graeff
R. K. Arni
R. D. Herculano
D. F. Salvadori
S. Mateus
M. Dal Pai Silva
C. G. Magalhães
R. A. Costa
S. A. M. Lima
S. L. Felisbino
W. Barbosa
A. Atallah
M. J. B. Girão
Z. Di Bella
S. M. Uchoa
S. Payão
A. Hijas
B. Berghman
R. De Bie
L. Sobrevia
B. Junginger
F. C. B. Alves
P. S. Rossignoli
C. B. Prudencio
M. I. G. Orlandi
M. I. Gonçalves
S. K. Nunes
B. B. Catinelli
S. Quiroz
B. V. Sarmento
F. A. Pinheiro
C. I. Sartorão
R. R. Lucas
D. R. A. Reyes
S. B. C. V. Quiroz
E. M. A. Enriquez
R. G. Oliveira
J. F. Floriano
J. P. C. Marcondes
S. Barneze
T. D. Dangió
T. Pascon
P. Rossignoli
J. V. Freitas
L. Takano
F. Reis
T. D. Caldeirão
J. N. Fernandes
A. M. Carr
M. V. C. Gaitero
J. E. Corrente
A. F. Candido
S. M. B. Costa
J. V. F. Melo
F. V. D. S. Reis
G. A. Garcia
G. B. Rabadan
H. C. M. Bassin
K. S. Suyama
L. N. Damasceno
M. L. S. Takemoto
M. D. Menezes
D. G. Bussaneli
V. K. C. Nogueira
P. R. Lima
I. O. Lourenço
J. Marostica de Sá
R. A. Megid
I. P. Caruso
L. T. Rasmussen
G. M. Prata
M. A. Arantes
G. A. R. Ferraz
L. P. Camargo
M. R. Kron
The Diamater Study Group
MVCR and AMPB conceived the study concept, developed the funding proposal, applied for funding, and initiated the writing of the protocol paper. JFA and LT were responsible for the critical review of the final draft. SSW and RLSH were responsible for clarifying manuscript content and word usage for an English language audience. MVCR is the principal investigator (PI) and the grant holder of the CNPq -Brazil (PQ-1C). AMPB, IMPC and FPS are Co-PI of the Project, and IMPC is grant holder of CNPq-Brazil (PQ-1D). MVCR, AMPB, IMPC, and FPS initiated the study design. MVCR, AMPB, RLSH, and JP wrote the protocol for research ethics committee and conceptual model. AMPB, IMPC, JFA, RLSH, and JEC develop the statistical analysis plan and will contribute to the interpretation of data. MVRC, SFP, JFA, RLSH, JPM, FP, GM, GV, LT, IMPC, SSW, and AMPB drafted and revised the manuscript after feedback from all authors. All authors contributed to the refinement of the present manuscript and approved the final version of the manuscript.
Correspondence to Marilza V. C. Rudge.
Institutional Research Bureau (IRB) of Botucatu Medical School-UNESP approved the study, on 2nd December 2017 (R17.036/NL60484.100.17). Written informed consent will be obtained from all subjects, and the procedures used in the study are in accordance with the guidelines of the Helsinki Declaration on human experimentation.
Specific protocols for clinical assessment and laboratory analysis of PFM and RAM.
Rudge, M.V.C., Souza, F.P., Abbade, J.F. et al. Study protocol to investigate biomolecular muscle profile as predictors of long-term urinary incontinence in women with gestational diabetes mellitus. BMC Pregnancy Childbirth 20, 117 (2020). https://doi.org/10.1186/s12884-020-2749-x
Hyperglycemic myopathy


text:
A student checks his dictionary after classes let out at Wingate High School in Brooklyn, phased out in 2006. AP Photo/Bebeto Matthews
New York City Closed 29 High Schools. What Happened to the Students?
A new report shows Bloomberg's controversial closures have had some positive effects, contrary to popular opinion.
At the turn of the 21st century, New York City found itself at the center of a crisis in education. With the highest concentration of "drop-out factories" in the country, graduation rates from its public high schools hovered at around 51 percent. The system badly needed intervention, and then-Mayor Michael Bloomberg settled on a radical course of action: Close failing schools, start smaller new ones in their place, and open up enrollment across the district, so that students had more of a choice about where they attended.
For Kids, Bouncing Between Schools Has Long-Term Effects
Open-enrollment policies have good intentions, but a new study finds that students who change schools frequently have poorer math and behavior skills.
The school closures were by far the most controversial measure, sparking protests, petitions, and lawsuits. Critics felt that the city administration was placing blame on schools, rather than funding them sufficiently to meet the often high needs of students at "failing" institutions, or addressing other the structural differences in the resources available in the schools' neighborhoods. Some speculated that students would be damaged by being forced transfer, or, if they were allowed to stay at closing schools over a phase-out period, they'd suffer from dwindling staff and resources.
But for all of the speculation, few studies rigorously examined the effects of school closures on students, since they began in 2002. Now, a major report by the Research Alliance for New York City Schools at New York University shows that the closures themselves were not detrimental for students. In fact, for some students, they were positive.
In a study of 29 low-performing high schools stamped for closure between 2002 and 2008, the Research Alliance executive director and NYU education scholar James J. Kemple found three striking results:
In terms of academic performance and attendance, high-school students who were enrolled in schools at the time that those schools were designated to close neither suffered nor improved by staying put.
In fact, compared to students enrolled in the same high-schools before the closure decisions, these "phase-out" students actually had higher rates of graduation and attendance, and received higher scores on standardized Regents exams. However, Kemple writes, "these gains were similar to gains made in the other low-performing high schools at the same time—suggesting that the phaseout process, in and of itself, had little effect on these outcomes."
High-school students who chose to transfer out of schools designated for closure also saw neither positive nor negative effects.
Although high-school transfer rates obviously increased, the characteristics of students who transferred were the same as before the closure decisions in terms of their demographic, academic performance, and need for services.
Middle-schoolers who would have enrolled in a under-performing school had it not been designated for closure benefited.
In general, incoming ninth-graders who would have otherwise been headed for a "drop-out factory" high-school wound up attending higher-performing schools, in terms of attendance and achievement. And compared to students who went to high schools as low-performing as the ones that closed, "post-closure" students saw a 15-point increase in their graduation rates.
Still, it's crucial to note that this study measured only the effects of school closures, and only on high-school students. It did not measure effects on other grade levels, or on neighborhoods, parents, or teachers. It also didn't look at the effects of New York City's new, smaller schools (prior studies have shown these to have had positive effects for students). And it did not look at how the city's open-enrollment policy served its students throughout the closures. (Studies of a similar program in Chicago public schools, at least, have pointed to negative outcomes.)
And then, Kemple writes, there's this:
[W]hile our study shows that students who likely would have attended the closed schools fared better, they still did not fare well. On average, just 56 percent of these students graduated from high school within four years[.] This highlights deeply entrenched inequalities in the City's schools, where poor students of color lag far behind their more privileged peers on a wide range of measures.
School closures in New York City may have produced positive effects for some students, but policymakers should take caution not to interpret closures as a single-handed solution to school systems in distress.
@mslaurabliss
Laura Bliss is CityLab's West Coast bureau chief. She also writes MapLab, a biweekly newsletter about maps (subscribe here). Her work has appeared in The New York Times, The Atlantic, Sierra, GOOD, Los Angeles, and elsewhere, including in the book The Future of Transportation.
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The pioneering festival marketplace was among the most trendsetting urban attractions of the last 40 years. Now it's looking for a new place in a changed city.

redpajama_set_name: RedPajamaCommonCrawl


We've always heard this cliché: Have a maximum of 30 minutes of exercise at least five days a week.
Well, that's an everyday cliché, with a lesser truth to it. According to the prestigious American College of Sports medicine ( ACSM), it says " if you go harder, your exercise can be just 75 minutes in just a week to look more trimmed up", how wowing ain't it! In accordance with this refinement, the ASCM also expects you to add much effort for a maximum of three days in a week and give some more effort at least two days out of every week.
So your question may be, so instructor what's the right amount for me? It really depends on your choice, most fitness instructors call it the "determination". First of all, it isn't everyone who has the determination or the zeal to respond to the same exercise. We've got some who prefer the push-ups and others who prefer the cardio. You'll also have to put in consideration your workout goals, for example, a Yoga training is way different from an intense training schedule.
If you do want to lose some pound weight: Well dear readers, in this category you'll have to watch your diet and also make it consonant with moderate physical activity. Have a target of 300 minutes of minimal or intense exercise per week. And yes, there have been instances of people losing pound weight fewer than 300 minutes of exercise per week.
The crux of this discussion is, you literally need to burn more calories than you take in. And for a good number of people, there has to be more consideration in cutting calorie intake, than consuming a large number of supplemental calories.
I reckon you also add resistance training in addition to your cardio exercises. Strength training builds your muscle mass, which increases your basal metabolic rate, meaning even while you're at rest you'll still be burning calories. You'll also have to consider, changing your exercise technique from time to time, so that you can keep giving that challenge to your body.
Secondly, if you do want to have a slight trim to your body: Be vigorous in your intense training and also resistance training and make sure you do keep your cardio-exercises at 150 minutes in a week. Your muscle tone does not depend only on the muscles but also on the number of fats on top of the muscles. Some little bit of crunches might get you the six-pack abdominal muscles, but for most normal people of weight, the muscles may not be quite noticeable, unless if the body fat levels are quite small.
You'll have to start by supplementing resistance training two to three days per week. When you're ready to increase the intensity, set apart another day for strength training, having a focus on each muscle group twice in a week.
Thirdly, if you want to be ageless in physique: You'll have to be always active and stay active. Watch your diet and have an exercise of 150 minutes of minimal intensity, in addition to an increase in your resistance training twice per week. Make sure you also stretch after each practical exercise, which would make you more active and also prevent you from having injuries.
Having this goal helps to improve your lungs and your cardiovascular system, also preventing the development of insulin deficiency, giving you a more healthy weight and also helps you to avoid severe inflammation.
According to Ben Quist, a physical therapist and strength conditioning specialist, he also recommends you do some cross-training, which means doing a range of activities during your exercises (watch the video below). This helps to reduce the boredom and also helps to improve the body. Doing different physical activity at a certain time also helps to employ different muscle groups. You're also less probable to develop an injury. Since doing the same pattern of exercise daily can wear up your joints and ligaments.
In conclusion, do not think eating and exercise are separate topics or issues. Surprisingly, they're very connected. There are so many individuals who think having intense exercises, perhaps daily, is an avenue to eat whatever you like daily. To learn how to measure up your food intake and how you wish to have your body or overall health to be by your daily exercises.


Georgia families can have a fun, active day at the zoo courtesy of Zoo Atlanta and the Georgia Public Library Service. The Zoo Atlanta Family Pass program gives free admission for a family of four to adults with a valid library card.
The Family Pass program began in February 2011 and has provided Georgia children with opportunities to visit the zoo, participate in its programs and special events. It has also saved families thousands of dollars in admission fees.
Passes are available at any participating library branch in Georgia. To use the pass, families must first rent the Zoo Atlanta Family Pass program DVD from their library branch. When they return the DVD to the library, they will collect their receipt, which is required for zoo admission. The pass is valid for seven days after the return of the DVD to the library.
Families are limited to one pass per year, per household. For more information, visit Zoo Atlanta's website.


If you have disparate data sources, many analysts, multiple projects and file types, you'd normally be looking at a budget overload and project meltdown. Don't worry though, we've got you covered.
Our Excel subscriptions are sold in multi-seat packages, so you can get access to as many Semantria for Excel seats as you need. Just talk to us and we'll get a custom package going for you.
Sentiment analysis identifies the positive, negative or neutral tones embedded in your content to better understand your market position. By attaching sentiment scores to each theme, entity, and category, our sentiment analysis tools uncover how people feel about your brand, products, and services, and why they feel that way.
It's easy to perform text analysis in Excel as Semantria for Excel provides fast and accurate categorization of your input content. With just a quick glance, you'll know the subjects of discussion — whether that's general topics like "politics" or "banking", search queries searching for specific items, or your own machine-learning based classification.
Every feature in Semantria for Excel is customizable: categorization, context determination, entity extraction, and sentiment analysis all respond to user feedback and tweaking. We even include a "short-form content" mode, specifically optimized for social media and other small sentences (like Twitter content).
Semantria for Excel is uniquely applicable to all industries around the globe. We support 22 languages, including English, Italian, Japanese, and German. No matter your industry and your demographics, you'll benefit from applying Lexalytics text mining tools.
Automatically extract people, places, companies, brands, @mentions, #hashtags, job titles from your content to see who's hot and who's not. You can create custom entities as well, tailored to your specific market or interests. Each extracted entity comes with a sentiment score to provide deeper insight into the tone of discussion. Tuning is a snap – just tell us who you want us to track, we'll also automatically show you what we discover so that you can tell when a company or person has made a move, even when you didn't know to look for it.
Use the Excel visualization tools you're already familiar with to create rich charts and graphs: all of our results are displayed in simple visual terms, while retaining the deep insights Lexalytics is known for. If you're using a BI tool like Tableau™ or Qlik™ - then it's super easy to import the results of the text analysis in Excel into the tool you're using and look at it alongside all your structured data analysis. Want to know why that store isn't performing well? Now you can actually analyze the conversations alongside the numbers.
Pretty amazing. Once I had my data in Excel, I could run queries and had results back in seconds. What is particularly convenient for me is that the analytics are produced directly within Excel.


Photobrook Photography: I've only gone and entered my first half marathon!
I've only gone and entered my first half marathon!
Yes your reading that right I've decided that it's time to enter my first ever half marathon!
Just 5 months ago on a cold December morning my sister came down to Cornwall for a visit and insisted that I tried out a local Park Run event. Struggling around the course through breathless running and lots of walking I managed to just about get around the 5km course.
Fast forward just 5 months and the fact that it's only a few weeks to my 30th birthday I'm having a mini life crisis and I've decided that it's about time I challenged myself and decided to attempt something a lot harder. I've just agreed to sign up to the Cardiff half marathon. Alongside over 20,000 other people I will be attempting to get around a 13.1 mile course around the famous city of Cardiff, that's just over 21km, a lot LOT further than the 5km I'm used to struggling around.
As if that's not enough of a challenge to be taking on with all the additional training that will be required of me I am also raising money for a great charity and that's the WWF. For anyone that knows me or follows my blog will know just how much I adore panda bears and want to help a charity that works to protect their future and their environment.
I'm now asking kindly for people to sponsor me and they can on my just giving page here, every penny is gratefully received by the charity but also means so much to me in believing that I can actually do a half marathon.
Thank You to everyone that's supporting me on this event.


CHESMA, A.C. ("Comunidad Hebrea En San Miguel de Allende, Asociación Civil") is an inter-/non-denominational Jewish community in San Miguel de Allende, in the state of Guanajuato, Mexico. We have about 170 members, many ex-pat Jews from the US or Canada, and also a growing number of Mexicans, many of whom have formally converted/returned to Judaism.
CHESMA, AC is an umbrella organization whose mission is to provide for the religious/spiritual, social, intellectual, charitable, and cultural needs of the Jewish community of SMA and its friends. We meet at the recently purchased and renovated Jewish Cultural and Community Center of SMA, (the "JC3"), Calle de las Moras #45-47 (corner of Cinco de Mayo), in Col. Allende.
a new Reform Kabbalat Shabbat service, which meets the third Friday of each month.
Our motto, "One community, many paths", reflects our diversity—in language, culture, and levels of observance. We invite each member to express his or her sense of being Jewish, be it secularly, religiously, culturally, intellectually, or artistically--join with us!
CHESMA, AC is proud to be an associate member of the Comité Central de la Comunidad Judía de México, (we are officially recognized as being part of the Mexican Jewish yishuv).
Kehilla Shalom SMA is a member of the United Synagogue of Conservative Judaism, as well as a founding member of Masortí México. Rabbi Juan Mejia Restrepo, of Oklahoma City, OK, is the Honorary Rabbi of KSSMA.
*This entity is tax-exempt under US IRS law section 501(c)(3).
To visit our Photo Gallery, please click here.


Simple way to communicate with Modbus RTU devices using Modbus TCP instead. The Raspberry Pi is acting as both a Modbus TCP slave and Modbus RTU master. The Node RED flow simply maps the slave commands over to the RTU addresses.


text:
Home Muddy meets: Ed Byrne
Back to Arts & Culture
Muddy meets: Ed Byrne
On tour in Dorset & Somerset this Autumn, Muddy caught up with the comedian to chat jokes, famous friendships and not being a d**k
Photo Idil Sukan
The Irish comedian's a regular on Mock The Week, you may also have caught him on Celebrity Best Home Cook, co-presenting Dara & Ed's Big Adventure or BBC2's The Pilgrimage, but what we love him for most is his award-winning stand-up comedy.
Now the dad-of-two is touring the country with his show If I'm Honest… We caught up with Ed to chew the fat about family life, lockdowns and laughing at fashion faux pas.
So Ed, what's the show all about?
It's about the things you say to your kids which they say back to you. There's something about having your own words repeated back that makes you start thinking about the traits you want to pass on to your kids and reflecting on that – so really, the show's all about me!
Sometimes I ask my kids (Cosmo and Magnus) a question and they just don't listen, I can be asking three or four times and in the end I end up getting annoyed. I heard my son Cosmo repeating my words back to his mate, who also wasn't listening, but he sounded a d**k! I had to take him aside and say, "You can't say that, you sound like a d**k.' He said, "but you say it dad, so are you a d**k?" And I said "No, no I'm not"…
Are your kids repeating swear words too?
We're not at the stage where they're swearing because they're angry, they're not dropping something and swearing, but they do find swearing funny. Sometimes we allow a little bit of swearing in a controlled environment, but they do know that it's naughty to say shit *laughter*.
It must be great to be doing live shows again?
It is great, particularly as the show actually premiered in 2019! I played Sept to Dec and was due to carry on the tour throughout 2020 when Covid struck, suddenly there was nothing. Some theatres that were sold out are now struggling as marketing people were furloughed and box offices shut, it's been a tough time for live venues.
How was life during lockdown?
My wife and I divided and conquered. Normally we both do a bit of the cooking etc, but during lockdowns the garden became my domain and the kitchen hers. It was good to all be together as a family, but actually I found it a bit frustrating that we couldn't use that time to do all the things we wanted. I know it's a cliche, but 9 years old is the perfect age (they're old enough to be great company but young enough to still think you can fly), so it would have been great to go off and have some adventures like climb mountains or do some kayaking, rather than just be stuck at home, though I know we were luckier than many.
How did you get into comedy Ed?
People used to tell me I was funny at uni in Glasgow, but I assumed it would be really hard to actually do that for a living, I probably thought I'd could try and be a TV presenter or radio host or something. I was on the entertainment committee and Vice President of the union and had to entertain freshers, which went well, so other unis got in touch asking me to do their freshers' welcome too. I was studying horticulture, but decided to bite the bullet and do stand-up, using the contacts I'd made to set up a comedy club at a pub in Glasgow before moving down to London, where the streets were of course paved with gold.
What was your big break?
I didn't really have one! I started out in the 90s which was a great time to be doing stand-up, you could make a decent living without being famous – there were about 100 comedy clubs within the M25, so you could do three gigs a night. It took a few years to establish myself but I never really had that one moment that catapulted me to fame. My first TV appearance was on the Jonathan Ross Big Big Talent Show, but all that really did was help sell out my Edinburgh Fringe show.
You're good friends with comedian Dara Ó Briain, what's he like to hang out with?
We lose it over things that other people wouldn't necessarily find funny. The most we've probably ever laughed was at the Kilkenny Comedy Festival in the 90s. I was wearing what I thought were extremely fashionable baggy jeans, which comedian Barry Murphy was ridiculing. To demonstrate how on-trend I was I started singing Here Comes The Hot Stepper by Ini Kamoze until Dara pointed out that the song was in fact about eight years old….we lost it. Yes, there were people wondering why that was so funny.
Tell us a joke…
Some of the warm-up people's jokes always make me laugh, like: "I went to the Canary Islands, but there weren't any canaries. Going to the Virgin Islands next year, can't wait." *giggles*
Anything you'd like to add for Muddy readers?
This show is ideal to get back out there and support your local theatre, it's not esoteric or worthy, it's light-hearted and funny and no, I don't dwell on the pandemic – there are a couple of minutes on it, but other than that we'll just have a laugh (sounds good to us, Ed).
WHERE TO SEE ED BYRNE IN SOMERSET & DORSET
Catch Ed's show If I'm Honest… at the Marine Theatre in Lyme Regis on Thurs 7 Oct; Wellsprings in Taunton on Fri 15 Oct; The Redgrave in Bristol on Tues 26 Oct; and the Bridgwater Arts Centre , Sat 30 Oct and at the Bath Forum on Weds 8 Dec. For upcoming tour dates in 2022, click here.
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Winter walks with pubs


text:
/*
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package com.facebook.presto.orc;

import com.facebook.presto.orc.metadata.statistics.BooleanStatistics;
import com.facebook.presto.orc.metadata.statistics.ColumnStatistics;
import com.facebook.presto.orc.metadata.statistics.HiveBloomFilter;
import com.facebook.presto.orc.metadata.statistics.RangeStatistics;
import com.facebook.presto.spi.predicate.Domain;
import com.facebook.presto.spi.predicate.Range;
import com.facebook.presto.spi.predicate.TupleDomain;
import com.facebook.presto.spi.predicate.ValueSet;
import com.facebook.presto.spi.type.DecimalType;
import com.facebook.presto.spi.type.StandardTypes;
import com.facebook.presto.spi.type.Type;
import com.facebook.presto.spi.type.VarbinaryType;
import com.facebook.presto.spi.type.VarcharType;
import com.google.common.annotations.VisibleForTesting;
import com.google.common.collect.ImmutableList;
import io.airlift.slice.Slice;
import org.apache.hive.common.util.BloomFilter;

import java.util.Collection;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.function.Function;

import static com.facebook.presto.spi.type.BigintType.BIGINT;
import static com.facebook.presto.spi.type.BooleanType.BOOLEAN;
import static com.facebook.presto.spi.type.Chars.isCharType;
import static com.facebook.presto.spi.type.Chars.truncateToLengthAndTrimSpaces;
import static com.facebook.presto.spi.type.Decimals.encodeUnscaledValue;
import static com.facebook.presto.spi.type.Decimals.isLongDecimal;
import static com.facebook.presto.spi.type.Decimals.isShortDecimal;
import static com.facebook.presto.spi.type.Decimals.rescale;
import static com.facebook.presto.spi.type.DoubleType.DOUBLE;
import static com.facebook.presto.spi.type.IntegerType.INTEGER;
import static com.facebook.presto.spi.type.RealType.REAL;
import static com.facebook.presto.spi.type.SmallintType.SMALLINT;
import static com.facebook.presto.spi.type.TinyintType.TINYINT;
import static com.facebook.presto.spi.type.Varchars.isVarcharType;
import static com.google.common.base.MoreObjects.toStringHelper;
import static com.google.common.base.Preconditions.checkArgument;
import static java.lang.Float.floatToRawIntBits;
import static java.util.Objects.requireNonNull;

public class TupleDomainOrcPredicate<C>
        implements OrcPredicate
{
    private final TupleDomain<C> effectivePredicate;
    private final List<ColumnReference<C>> columnReferences;

    private final boolean orcBloomFiltersEnabled;

    public TupleDomainOrcPredicate(TupleDomain<C> effectivePredicate, List<ColumnReference<C>> columnReferences, boolean orcBloomFiltersEnabled, Optional<Integer> domainCompactionThreshold)
    {
        requireNonNull(effectivePredicate, "effectivePredicate is null");
        this.effectivePredicate = domainCompactionThreshold.map(effectivePredicate::compact).orElse(effectivePredicate);
        this.columnReferences = ImmutableList.copyOf(requireNonNull(columnReferences, "columnReferences is null"));
        this.orcBloomFiltersEnabled = orcBloomFiltersEnabled;
    }

    @Override
    public boolean matches(long numberOfRows, Map<Integer, ColumnStatistics> statisticsByColumnIndex)
    {
        Optional<Map<C, Domain>> optionalEffectivePredicateDomains = effectivePredicate.getDomains();
        if (!optionalEffectivePredicateDomains.isPresent()) {
            // effective predicate is none, so skip this section
            return false;
        }
        Map<C, Domain> effectivePredicateDomains = optionalEffectivePredicateDomains.get();

        for (ColumnReference<C> columnReference : columnReferences) {
            Domain predicateDomain = effectivePredicateDomains.get(columnReference.getColumn());
            if (predicateDomain == null) {
                // no predicate on this column, so we can't exclude this section
                continue;
            }
            ColumnStatistics columnStatistics = statisticsByColumnIndex.get(columnReference.getOrdinal());
            if (columnStatistics == null) {
                // no statistics for this column, so we can't exclude this section
                continue;
            }

            if (!columnOverlaps(columnReference, predicateDomain, numberOfRows, columnStatistics)) {
                return false;
            }
        }

        // this section was not excluded
        return true;
    }

    private boolean columnOverlaps(ColumnReference<C> columnReference, Domain predicateDomain, long numberOfRows, ColumnStatistics columnStatistics)
    {
        Domain stripeDomain = getDomain(columnReference.getType(), numberOfRows, columnStatistics);
        if (!stripeDomain.overlaps(predicateDomain)) {
            // there is no overlap between the predicate and this column
            return false;
        }

        // if bloom filters are not enabled, we can not restrict the range overlap
        if (!orcBloomFiltersEnabled) {
            return true;
        }

        // if there an overlap in null values, the bloom filter can not eliminate the overlap
        if (predicateDomain.isNullAllowed() && stripeDomain.isNullAllowed()) {
            return true;
        }

        // extract the discrete values from the predicate
        Optional<Collection<Object>> discreteValues = extractDiscreteValues(predicateDomain.getValues());
        if (!discreteValues.isPresent()) {
            // values are not discrete, so we can't exclude this section
            return true;
        }

        HiveBloomFilter bloomFilter = columnStatistics.getBloomFilter();
        if (bloomFilter == null) {
            // no bloom filter so we can't exclude this section
            return true;
        }

        // if none of the discrete predicate values are found in the bloom filter, there is no overlap and the section should be skipped
        if (discreteValues.get().stream().noneMatch(value -> checkInBloomFilter(bloomFilter, value, stripeDomain.getType()))) {
            return false;
        }
        return true;
    }

    @VisibleForTesting
    public static Optional<Collection<Object>> extractDiscreteValues(ValueSet valueSet)
    {
        return valueSet.getValuesProcessor().transform(
                ranges -> {
                    ImmutableList.Builder<Object> discreteValues = ImmutableList.builder();
                    for (Range range : ranges.getOrderedRanges()) {
                        if (!range.isSingleValue()) {
                            return Optional.empty();
                        }
                        discreteValues.add(range.getSingleValue());
                    }
                    return Optional.of(discreteValues.build());
                },
                discreteValues -> Optional.of(discreteValues.getValues()),
                allOrNone -> allOrNone.isAll() ? Optional.empty() : Optional.of(ImmutableList.of()));
    }

    // checks whether a value part of the effective predicate is likely to be part of this bloom filter
    @VisibleForTesting
    public static boolean checkInBloomFilter(BloomFilter bloomFilter, Object predicateValue, Type sqlType)
    {
        if (sqlType == TINYINT || sqlType == SMALLINT || sqlType == INTEGER || sqlType == BIGINT) {
            return bloomFilter.testLong(((Number) predicateValue).longValue());
        }

        if (sqlType == DOUBLE) {
            return bloomFilter.testDouble((Double) predicateValue);
        }

        if (sqlType instanceof VarcharType || sqlType instanceof VarbinaryType) {
            return bloomFilter.test(((Slice) predicateValue).getBytes());
        }

        // todo support DECIMAL, FLOAT, DATE, TIMESTAMP, and CHAR
        return true;
    }

    @VisibleForTesting
    public static Domain getDomain(Type type, long rowCount, ColumnStatistics columnStatistics)
    {
        if (rowCount == 0) {
            return Domain.none(type);
        }

        if (columnStatistics == null) {
            return Domain.all(type);
        }

        if (columnStatistics.hasNumberOfValues() && columnStatistics.getNumberOfValues() == 0) {
            return Domain.onlyNull(type);
        }

        boolean hasNullValue = columnStatistics.getNumberOfValues() != rowCount;

        if (type.getJavaType() == boolean.class && columnStatistics.getBooleanStatistics() != null) {
            BooleanStatistics booleanStatistics = columnStatistics.getBooleanStatistics();

            boolean hasTrueValues = (booleanStatistics.getTrueValueCount() != 0);
            boolean hasFalseValues = (columnStatistics.getNumberOfValues() != booleanStatistics.getTrueValueCount());
            if (hasTrueValues && hasFalseValues) {
                return Domain.all(BOOLEAN);
            }
            if (hasTrueValues) {
                return Domain.create(ValueSet.of(BOOLEAN, true), hasNullValue);
            }
            if (hasFalseValues) {
                return Domain.create(ValueSet.of(BOOLEAN, false), hasNullValue);
            }
        }
        else if (isShortDecimal(type) && columnStatistics.getDecimalStatistics() != null) {
            return createDomain(type, hasNullValue, columnStatistics.getDecimalStatistics(), value -> rescale(value, (DecimalType) type).unscaledValue().longValue());
        }
        else if (isLongDecimal(type) && columnStatistics.getDecimalStatistics() != null) {
            return createDomain(type, hasNullValue, columnStatistics.getDecimalStatistics(), value -> encodeUnscaledValue(rescale(value, (DecimalType) type).unscaledValue()));
        }
        else if (isCharType(type) && columnStatistics.getStringStatistics() != null) {
            return createDomain(type, hasNullValue, columnStatistics.getStringStatistics(), value -> truncateToLengthAndTrimSpaces(value, type));
        }
        else if (isVarcharType(type) && columnStatistics.getStringStatistics() != null) {
            return createDomain(type, hasNullValue, columnStatistics.getStringStatistics());
        }
        else if (type.getTypeSignature().getBase().equals(StandardTypes.DATE) && columnStatistics.getDateStatistics() != null) {
            return createDomain(type, hasNullValue, columnStatistics.getDateStatistics(), value -> (long) value);
        }
        else if (type.getJavaType() == long.class && columnStatistics.getIntegerStatistics() != null) {
            return createDomain(type, hasNullValue, columnStatistics.getIntegerStatistics());
        }
        else if (type.getJavaType() == double.class && columnStatistics.getDoubleStatistics() != null) {
            return createDomain(type, hasNullValue, columnStatistics.getDoubleStatistics());
        }
        else if (REAL.equals(type) && columnStatistics.getDoubleStatistics() != null) {
            return createDomain(type, hasNullValue, columnStatistics.getDoubleStatistics(), value -> (long) floatToRawIntBits(value.floatValue()));
        }
        return Domain.create(ValueSet.all(type), hasNullValue);
    }

    private static <T extends Comparable<T>> Domain createDomain(Type type, boolean hasNullValue, RangeStatistics<T> rangeStatistics)
    {
        return createDomain(type, hasNullValue, rangeStatistics, value -> value);
    }

    private static <F, T extends Comparable<T>> Domain createDomain(Type type, boolean hasNullValue, RangeStatistics<F> rangeStatistics, Function<F, T> function)
    {
        F min = rangeStatistics.getMin();
        F max = rangeStatistics.getMax();

        if (min != null && max != null) {
            return Domain.create(ValueSet.ofRanges(Range.range(type, function.apply(min), true, function.apply(max), true)), hasNullValue);
        }
        if (max != null) {
            return Domain.create(ValueSet.ofRanges(Range.lessThanOrEqual(type, function.apply(max))), hasNullValue);
        }
        if (min != null) {
            return Domain.create(ValueSet.ofRanges(Range.greaterThanOrEqual(type, function.apply(min))), hasNullValue);
        }
        return Domain.create(ValueSet.all(type), hasNullValue);
    }

    public static class ColumnReference<C>
    {
        private final C column;
        private final int ordinal;
        private final Type type;

        public ColumnReference(C column, int ordinal, Type type)
        {
            this.column = requireNonNull(column, "column is null");
            checkArgument(ordinal >= 0, "ordinal is negative");
            this.ordinal = ordinal;
            this.type = requireNonNull(type, "type is null");
        }

        public C getColumn()
        {
            return column;
        }

        public int getOrdinal()
        {
            return ordinal;
        }

        public Type getType()
        {
            return type;
        }

        @Override
        public String toString()
        {
            return toStringHelper(this)
                    .add("column", column)
                    .add("ordinal", ordinal)
                    .add("type", type)
                    .toString();
        }
    }
}

redpajama_set_name: RedPajamaGithub


This Brighton whole home remodel and addition was to create a master suite, as well as update the flow of the home, gut-remodel the kitchen, and update all bathrooms. The beautiful and eclectic result features surprises like reclaimed wood throughout married to traditional touches like white shaker style cabinets and schoolhouse pendants.
A beautiful master suite with separate walk-in closet was created as an addition on the second story of the home, with vaulted ceilings in the master bedroom that connect to a masterfully designed outdoor space that welcomes in the sunshine while screening out nearby neighbors in this densely packed area.
In addition to the master suite area, a second floor laundry room was created with adjacent full guest bathroom. This made the client's lives much easier, as prior to the remodel all laundry was handled in the basement of the home.
On the first floor there were many updates to the circulation of the space as a whole, as well as smaller touches like a new fireplace insert and mantle. The kitchen now captures the eye when you enter the building, drawing you back in to the major remodeling done in that space with the stunning feature island.


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Comprehensive Pain Specialists in Dayton is a company that specializes in Health And Allied Services, Nec. Our records show it was established in Tennessee.


Yann Tiersen is a French musician. With a classical background and punk influences, he started making music early. After the release of his third album, Yann invited several musician for a live show in Rennes, including Neil Hannon who was on the same label in France. Together they performed a version of 'Geronimo' and a cover of David Bowie's 'Life On Mars'. The show was recorded for broadcast as a Black Session on France Inter, and subsequently released as a live album.
For his next album L'Absente, Neil Hannon was invited again co-write and perform on the song 'Les Jours Tristes'. At the same time the song was also used for the soundtrack of the movie Amélie.
He then returned his favour to Hannon, by playing accordion on a couple of tracks during the recording of Absent Friends.
Neil Hannon and Yann Tiersen haven't worked together since. Yann has been since busy on several projects since, composing music for films, and making more rock-oriented records.


text:
using System;
using System.Collections.Generic;
using System.Text;

namespace Gallio.Common.Xml.Diffing
{
    /// <summary>
    /// A simple builder for the <see cref="DiffSet"/> object.
    /// </summary>
    public sealed class DiffSetBuilder
    {
        private readonly IList<Diff> items = new List<Diff>();

        /// <summary>
        /// Adds the specified diff item to the set.
        /// </summary>
        /// <param name="item">The diff item to be added.</param>
        /// <returns>A reference to the builder itself.</returns>
        /// <exception cref="ArgumentNullException">Thrown if <paramref name="item"/> is null.</exception>
        public DiffSetBuilder Add(Diff item)
        {
            if (item == null)
                throw new ArgumentNullException("item");

            items.Add(item);
            return this;
        }

        /// <summary>
        /// Adds the diff items contained into the specified set to the current set.
        /// </summary>
        /// <param name="items">The diff items to be added.</param>
        /// <returns>A reference to the builder itself.</returns>
        /// <exception cref="ArgumentNullException">Thrown if <paramref name="items"/> is null.</exception>
        public DiffSetBuilder Add(DiffSet items)
        {
            if (items == null)
                throw new ArgumentNullException("items");

            foreach (var item in items)
            {
                Add(item);
            }

            return this;
        }

        /// <summary>
        /// Returns a new <see cref="DiffSet"/> based on the current content of the builder.
        /// </summary>
        /// <returns>The resulting diff set object.</returns>
        public DiffSet ToDiffSet()
        {
            return new DiffSet(items);
        }
    }
}