dataesr/scientific-paragraphs-categorization huggingface dataset:
The most frequently reported adverse drug reactions (ADRs) were nausea (4. 7%), dizziness (3. 2%) and insomnia (2. 0%). ADR rates appeared higher in the elderly subpopulation (18. 6% reported ≥1 ADR vs. 12. 0% in the total population) but were not higher in the other predefined subgroups. MDRC study: The database follow-up analysis followed 2892 patients over 18 months for whom the duration of nalmefene treatment was between 2 and 3 months and <5% of patients used nalmefene for ≥1 year. Conclusions: Despite the inclusion of a wider patient population (e. g. elderly patients and those with relevant co-morbidities), the safety and tolerability profile of nalmefene given in routine practice was consistent with previous clinical studies. The differing rates of persistence beyond 1 year likely reflect the different methodologies and highlight the relevance of psychosocial support at follow-up visits.
Study medication was used as commercially available and was not supplied by the sponsor for this study. Investigators were asked to consecutively enrol all patients who consented and met the selection criteria, regardless of other considerations. Reasons for non-consent were also recorded. A total of eight visits were planned (i. e. baseline visit, 1-month visit, 3-month visit, then five visits every 3 months [± 1 month]), reflecting the medical aspects of the management of alcoholdependent patients in routine clinical practice typical of the public health sector. Descriptive data were collected via an electronic case report form which captured sociodemographic variables, comorbidities and current treatment. The frequency of nalmefene intake was recorded as was the occurrence of any dosing in excess of the licenced daily dose (i.
The multi-database retrospective cohort (MDRC) study This was a retrospective cohort study using longitudinal electronic medical records and administrative claims from automated databases. The study was registered at the EU PAS (EUPAS14083). Three countries were identified as having suitable and complementary databases for the analysis of drug persistence and potential overdosing: 1. German Statutory Health Insurance (SHI) claims database. 2. Swedish Prescribed Drug Register, Swedish Patient Register, Swedish Medical Birth Register and Swedish Cause of Death Register.
UK Clinical Practice Research Datalink General Practitioners Online Database. Separate analyses were performed at baseline and at the end of the 18-month follow-up. Outcomes included demographics, presence of comorbidities, duration of treatment and occasions where a patient was suspected to have taken more than one tablet in a day. Baseline analyses included all patients with an incident prescription/dispensing (first prescription/dispensing) who were prescribed nalmefene between the launch date in each country (Germany and Sweden: 1 September 2014, UK 1 May 2013) and a database-specific end-ofinclusion date (Germany: 30 June 2016; Sweden: 29 April 2017; UK: 28 February 2017). For Sweden, the analyses on comorbidities were restricted to patients who could be linked to the Swedish National Patient Register (SNPR).
0 months), and the proportion of patients using nalmefene for ≥1 year was also lower in these subgroups (35. 6% of elderly patients and 32. 0% of patients with history of seizure disorder vs. 49. 0% of patients in the TAP). Patients with a psychiatric comorbidity had a similar duration of treatment to the TAP population (this subgroup accounted for >50% of the TAP). Across the 18 months of follow-up, the most frequent reasons for treatment discontinuation were 'goal reached' and 'drug cost' (Table  3 ). There were nine occasions (8 patients) of a patient taking more than the recommended dose of one tablet per day; seven patients (8 occasions) took two tablets of nalmefene (36 mg) on the same a For Sweden, the number of patients who could be linked to the SNPR was N = 1848 in the Swedish database.
This denominator was used for the evaluation of comorbidities. NR: not reported. 2 ). The most frequently reported ADRs were nausea (4. 7%), dizziness (3. 2%), insomnia (2. 0%), vomiting (1. 7%) and headache (1. 5%) (Table  4 ). Twenty patients (1. 5%) reported 23 ADRs of special interest, including seven events of confusional state (including one serious event reported as 'disorientation', all resolved), six events of hallucination, five events of dissociation and five events of depression (all five were classified as serious ADR). There was no report of convulsions and no ADR of special interest led to treatment withdrawal or to death. Rates of ADR appeared higher in the elderly subpopulation (18. 6% of elderly patients reported ≥1 ADR during follow-up vs. 12. 0% in the TAP). Three participant pregnancies were reported during the study period (after 15 and 18 months of followup); no data (including ADRs of special interest) were reported in these women.
The multi-database retrospective cohort study The MDRC baseline analysis included 3393 patients treated with nalmefene in the UK (n = 247), Germany (n = 610) and Sweden (n = 2536). For Sweden, the number of patients who could be linked to the SNPR was N = 1848. Baseline characteristics per country are given in Table  1. The majority of patients were between 18 and 64 years old; with smaller proportion of elderly users in the UK and Germany compared to Sweden (8. 9% and 5. 6% vs. 19. 3%, respectively). More men than women were prescribed nalmefene and there were high rates of somatic and psychiatric comorbidities reported. Psychiatric comorbidities were more commonly reported for patients in the German SHI database than in the Swedish or UK databases (79. 0% vs. 20. 2% and 45. 3%, respectively).
Seizures or alcohol withdrawal state during the past 12 months were recorded in 200 patients in Germany (32. 8%), 89 in Sweden (4. 8%) and 3 (1. 2%) in the UK. Five women (in Germany and Sweden) became pregnant during treatment with nalmefene (with no further data reported). The proportion of patients who were prescribed nalmefene without a recorded diagnosis of alcohol dependence varied between 18. 0% in Germany (110 from 610 patients), 51. 3% in the UK (121 from 236 patients) and 68. 4% in Sweden (1482 from 2167 patients). Downloaded from https://academic. oup. com/alcalc/advance-article/doi/10. 1093/alcalc/agab045/6312435 by BIUS Jussieu user on 02 July 2021 The MDRC follow-up analysis included a total of 2892 patients (Germany: n = 494; Sweden: n = 2167; UK: n = 231); 116 patients from Germany were included in the baseline analyses, but not in the follow-up analyses due to an administrative change in the database.
Overall, the mean duration of nalmefene treatment during follow-up was between 2 and 3 months (Table  2 ). The proportion of patients who used nalmefene for ≥1 year was <5% in all three databases: 3. 0% (7 patients) in the UK, 4. 1% (20 patients) in Germany and 1. 6% (34 patients) in Sweden. Most (61. 9-84. 6%) nalmefene users had only one record of a nalmefene prescription during the observation period. Few patients took more than the recommended dose of one tablet per day, and there were fewer recorded instances of possible 'overdosing' (i. e. >1 tablet per day) in Germany and Sweden than in the UK (6. 1% and 0. 9% vs. 16. 5%, respectively).
This is in line with the time course of alcohol reduction with the as needed use of nalmefene which, in the pivotal studies, showed significant alcohol reduction as early as 1 month that was maintained through the 6-month treatment periods  (Gual et al. , 2013; Mann et al. , 2013). The higher retention rates in the START study versus MDRC likely reflects the differences in the methodologies employed. While a prospective study is preferable for collecting ADR data, the key advantage of using a retrospective database study design for persistence data is that it guarantees the absence of selection bias and a routine environment, including a routine level of psychosocial support. Just being included in a clinical study may have enhanced START study persistence outcomes, particularly as patients had to attend eight visits in 18 months to regularly discuss their alcohol intake.
ACKNOWLEDGEMENTS The authors would like to thank all patients who participated in this observational cohort study and would also like to acknowledge  Anita Chadha-Patel, PhD  ( ACP Clinical Communications Ltd , funded by H. Lundbeck A/S)  who assisted with preparation of the first draft, table preparation, referencing and final styling under full direction of the authors. The data analysis for Germany was performed in collaboration with the Institute for Applied Health Research Berlin.
IgAN Epidemiology The true prevalence of IgAN cannot be exactly determined. IgA deposits on the kidney are indeed frequent in asymptomatic patients and were reported in 16. 1% of a population of kidney donors in Japan  [1]. However, the overt disease can evolve to a rapidly progressive glomerulopathy (Figure  1 ). Since the diagnosis of IgAN requires a kidney biopsy, available data only refer to cases recorded after this procedure. The prevalence of IgAN varies widely across different geographic regions and ethnic groups  [2] : IgAN is most prevalent in East Asian people (with more than 40% of biopsy cases in Japan), followed by Caucasians and African individuals (respectively with about 25% and less than 5% of biopsy cases)  [3]. This disparity in population distribution can be attributed to the different health screening policies as well as several genetic and environmental factors.
Participation in the Survey Collaborators from 31/33 countries and 97/104 veterinary schools provided consent to participate in the study. Eight of the 97 schools were further excluded due to either absence of data collection (n = 3), participation below 10% (n = 4) or unknown number of eligible students (n = 1), leading to 30 countries and 89 schools finally enrolled in the study (Supplementary Materials Figure  S1 ). A total of 36 country coordinators (CCs) were in charge of survey distribution in the 30 countries (Croatia, France, Slovenia, Switzerland, and Turkey had two coordinators each, Italy had three, and UK and Romania shared one). We collected 5567 answers, of which 3423 were used for data analysis. Answers were excluded if the participation in a particular school was below 10% (four schools, n = 19 answers), if participation could not be estimated (due to lack of information on the total number eligible students) (one school, n = 12 answers), if the identity of the veterinary school was not indicated (n = 12 answers), or due to incompleteness (n = 2101 answers, including 667 students that were not enrolled in the final year of their veterinary education).
Data Analysis Data analysis and visualization were performed in R version 3. 6. 1  [18]. Data inspection was performed prior to statistical analyses using Pearson's correlation values, scatterplots for inspection of continuous data and boxplots for categorical data. Subsequently, Wilcoxon test, linear mixed models and linear regression were used to analyze our dataset. A summary of research questions and the corresponding statistical methods are shown in Table  S5. To reduce the size of models, we created a knowledge score for each student calculated as the percentage of correct answers to eight survey questions (Q14-18, Q21-23) (Q19-20 are not part of the knowledge score due to multiple possible correct answers). For country-level analyses, the knowledge score was calculated as the average percentage of students giving the correct answer to each question.
To avoid redundancy in model construction, the variable clinical rotations in the categorical format (Q4) was selected over the frequency format (Q26). In order to explore whether countries that are already implementing better education in AMS had also different patterns in prescription of antimicrobial agents, we analyzed possible associations between students' preparedness and antimicrobial sales at the country level using data on overall sales of veterinary antimicrobial agents from 2017 (expressed in mg/PCU) exported from the European Surveillance of Veterinary Antimicrobial Consumption (ESVAC) online database  [19]. Collinearity was examined in all models using the performance package in R  [20]. All average values across countries are reported as weighted arithmetic means to account for the different student population size in each country.
N19 antibody was blocked by overnight pre-incubation at 4 C with human SHH-N N19 peptide (4 mg/ml) (Santa Cruz). Chemiluminescence (Pierce ECLþ, Thermo Fisher Scientific) was acquired with a Chemidoc apparatus (Bio-Rad) and a densitometry analysis was performed using ImageLab software (Bio-Rad). 2. 6. Food intake, locomotor activity, body temperature, and indirect calorimetry Six YFP-Ptc þ/þ and YFP-Ptc À/À mice 13 weeks after tamoxifen treatment were monitored for 8 h for energy expenditure, oxygen consumption, carbon dioxide production, respiratory exchange rate (RER; VCO 2 /VO 2 ), food intake, and locomotor activity using metabolic cages (Labmaster; TSE Systems, Bad Homburg, Germany). Their activity was recorded using an infrared light beam-based locomotion monitoring system (beam breaks/h).
The mice were individually housed with free access to regular chow and acclimated to their chambers for 48 h before experimental measurements. The data analysis was carried out with Excel XP (Microsoft) using extracted raw values of VO 2 , VCO 2 (in ml/h), and energy expenditure (kJ/h). Each value was expressed either per total body weight or whole lean tissue mass extracted from an EchoMRI analysis as previously described  [25]. See the Supplementary Methods for further details. The rectal body temperature was measured in the morning with a thermometer probe (BIO-TK8851, rectal probe BIOBRET-3) lubricated with Vaseline (Cooper).
Nuclei were counterstained with DAPI. Images were acquired with a 20X objective (N. A. 0. 75) using a fluorescence microscope (Leica DM2000) or a 63X objective on a confocal microscope (Leica TCS SP8). For the latter, Z stacks 5. 9 mm thick containing 15 Z section images were analyzed using LAS-X software (Leica) and reconstructed in ImageJ 1. 52p (NIH) and Photoshop CS3 (Adobe). Small pieces of adipose tissues were fixed for 12e16 h at room temperature with 4% PFA at room temperature, embedded in paraffin, serially sectioned at 5 mm, stained with hematoxylin and eosin (HE), and evaluated using an Olympus AX60 conventional light microscope. Images of fat tissue areas were captured with a QIClick Color light camera (QI Imaging) using QCapture Pro software.
The number of Glast þ S100b þ cells per animal ranged between 34 and 67 in the ARC, 118 and 279 in the VMH, 133 and 332 in the dorsomedial hypothalamic nucleus (DMH), and 255 and 388 in the cerebral cortex. The number of S100b þ cells per animal ranged between 32 and 84 in the ARC, 141 and 216 in the VMH, 159 and 275 in the DMH, and 245 and 291 in the cerebral cortex. Counting the co-localized staining was done using the ROI and multipoint ImageJ tools. Quantitative data are expressed as the mean AE standard error of the mean (SEM). The two experimental groups were compared using the ManneWhitney test. A value of p < 0. 05 was considered statistically significant. Graphs were drawn using GraphPad Prism 5. 2 (GraphPad Software, Inc).
Acknowledgments Funding source received from  Pfizer  laboratory. The abstract of this paper was presented at the 29 th European Academy of Dermatology and Venerology and at the  Journées Derrmatologiques de Paris 2020  as a poster presentation with interim findings. The poster's abstract was published in "Poster Abstracts" in the  Annales de Dermatologie et de Vénéréologie ,  147 ,  Suppl Dec 2020.
The present study sought to retrospectively investigate the dietary habits of two adolescent, European populations from the cross-sectional Greek TEENAGE Study and French STANISLAS Family Study. We aimed to explore the relation between the populations' dietary patterns and blood pressure, glycemic and lipidemic profile. Dietary patterns were extracted via Principal Component Analysis (PCA), based on data collected from two 24 h dietary recalls for the TEENAGE study and a 3-day food consumption diary for the STANISLAS study. Multiple linear regressions and mixed models analyses, adjusting for confounding factors, were employed to investigate potential associations. A total of 766 Greek teenagers and 287 French teenagers, were included in analyses. Five dietary patterns were extracted for each population accounting for 49.
A second 24 h dietary and physical activity recall was conducted via telephone, 3 to 10 days after the in-person meeting. Overall, data for an original sample of 857 adolescent students from 1440 schools in the region of Attica, aged 13 to 15 years old, were cross-sectionally collected. Collection of anthropometric data during the in-person meeting consisted of height (measured to the nearest 0. 1 cm), weight (measured to the nearest 0. 1 kg), waist and hip circumference and skinfold measurements (measured to the nearest 0. 1 mm). Height was measured using a portable stadiometer, where participants were barefoot, looking ahead and with relaxed shoulders. Weight was measured via use of scales, where participants were barefoot and with light clothing. BMI was calculated as weight divided by height (kg/m 2 ).
Waist and hip circumference were measured using a soft tape, the former between the twelfth rib and the iliac crest and the latter at the widest point of the hips. Two skinfold measurements were collected for each of the triceps, subscapular and suprailiac skinfolds, using the Lange skinfold calipers. Assessment of dietary habits took place via the collection of the two non-consecutive 24 h dietary recalls, which were conducted on different days of the week. Analysis of the data collected took place via use of the Nutritionist Pro software, version 2. 2  [23]. The ratio of reported energy intake to BMR was calculated for each student, in order to assess potential under-reporting. BMR was calculated using the Schofield equations  [24, 25]  and cut-off points  [26]  were adapted to the ones reported for children and adolescents  [27].
All included families provided informed consent. The families enrolled participated in an in-person session with trained professionals, which included clinical examination, collection of blood samples and collection of anthropometric, dietary and lifestyle data. Collection of the food-related surveys was conducted by dietitians. Blood pressure, pulse rate, skinfold thickness and bone density were measured by nurses and pubertal development and family history of cardiovascular diseases was assessed by general practitioners. Data on alcohol and tobacco consumption, physical activity, education and socio-professional status were collected through questionnaires, under the supervision of trained nurses. Overall, data for an original sample of 1006 families were cross-sectionally collected. Weight, height, waist-to-hip ratio and impedancemetry measurements were conducted by technical operators.
BMI was, again, calculated as weight divided by height (kg/m 2 ). Assessment of dietary habits took place via collection of a 3 day food consumption diary, for two continuous days within the week and one day of the weekend. Analysis of the data took place via use of the GENI package, nutritional database program  [31]. For the purposes of the present study, we used the available anthropometric, biochemical and dietary data of 287 adolescents at the time of the baseline recruitment (as shown in Table  2 ). Dietary pattern extraction was based on the mean consumption of food groups, deriving from the 3 day food consumption diary. Low-density cholesterol (LDL-C) for this cohort was calculated based on the available data for total cholesterol (TC), highdensity lipoprotein cholesterol (HDL-C) and triglyceride (TG) levels, using the Friedeweld Equation, as follows  [32] : LDL -C = (TC) -(HDL -C) -(TG/5).
Statistical Analysis The entirety of the data handling and data analyses was carried out using the SPSS Software  [33]. Body Mass Index (BMI) was calculated as weight divided by height (kg/m 2 ). Assessment of the variables' distribution was conducted via use of the Shapiro-Wilk test, demonstrating the mean and standard deviation for all normally distributed variables and the median and interquartile range for all variables not following the normal distribution (Shapiro-Wilk p-value > 0. 05). We used the Student's t-test and Mann-Whitney test for all hypotheses testing for continuous variables. We performed Principal Component Analyses (PCA) in order to extract all dietary patterns for both populations  [34]. PCA constitutes an epidemiological tool, largely used in the assessment of dietary data and the subsequent extraction of dietary patterns  [35] , having been previously tested in large young populations  [36].
PCA was conducted on 15 food groups for the TEENAGE study population and 15 food groups for the STANISLAS Family study population, based on the available data for the cohorts. The Kaiser-Meyer-Olkin (KMO) test was calculated at 0. 545 and 0. 576 for the TEENAGE and the STANISLAS teenagers, respectively, indicating mediocre to sufficient data adequacy. The varimax orthogonal rotation was used for the extraction of the patterns and the Kaiser criterion was set at retaining 5 components with Eigen values bigger than 1. We further tested for potential associations between the extracted dietary patterns, blood pressure and biomarkers of glycemic and lipidemic control, as well as levels of CRP, via use of multiple linear regressions in the TEENAGE cohort and linear mixed models in the STANISLAS cohort.
Descriptive Characteristics The anthropometric and biochemical characteristics of the two populations are depicted in Tables  1  and 2. Concerning the TEENAGE cohort, a total of 766 teenagers (45. 56% boys, 54. 43% girls), with a median age of 13. 30 years, were included in the analyses. The STANISLAS cohort provided data for 287 teenagers (47. 73% boys, 525. 26% girls), with a median age of 13. 08 years. The daily energy intake for the two populations by sex, is depicted in Figure  1. As shown in Tables  1  and 2 , the Greek teenagers reported a median energy intake of 1741. 00 kcal/d (IQR = 760), significantly different between the two genders, with boys reporting a higher intake. The French teenagers reported a median energy intake of 2056. 03 kcal/d (IQR = 662. 24), without presenting significant differences between sexes.
Discussion The present study sought to investigate the dietary patterns of two adolescent, European populations, based on data from the Greek TEENAGE and the French STANISLAS Family studies, as well as their potential relations with blood pressure, biomarkers of glycemic and lipidemic control and levels of CRP. The study includes healthy teenagers from the two European populations, with a median BMI of 20. 88 kg/m 2 (IQR = 5. 88 kg/m 2 ) and 18. 44 kg/m 2 (IQR = 3. 61 kg/m 2 ). For the Greek teenagers, weight, waist-to-hip ratio (WHR), systolic blood pressure (SBP), levels for glucose, HOMA-IR, insulin, HDL-C and CRP significantly differed between boys and girls. Boys presented slightly higher values for weight, WHR, SP and glucose levels, while girls reported slightly higher levels of HOMA-IR, insulin and HDL-C.