dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments: We thank  D. Wu  ( NIDCD/NIH, USA ) for supplying Prickle2 antibody,  V. Bennett  ( Duke Cancer Institute, USA ) for supplying the AnkG270-GFP and AnkG190-GFP constructs,  C. Hoogenraad  ( Utrecht University, The Netherlands ) for the AnkG480-GFP cDNA, and  M. Deans  ( University of Utah, USA ) for GFP-Prickle2 cDNA construct. We thank  C. Medina ,  A. Barranger ,  I. Seynat ,  S. Dos Santos Carvalho ,  J. Stanic , and  C. Lefranc  for technical assistance. We thank the personnel of the  Animal Facility of the Neurocentre Magendie  for the rat care. We thank the  Bordeaux Neurocampus core  facilities used in this study and supported by the  LabEx BRAIN  (grant  ANR-10-LABX-43 ), including the  Biochemistry facility BioProt , and the assistance of  Y. Rufin  for GST production and purification is acknowledged.
Methods The nationwide data provided by the French National Hospital Discharge database (PMSI-Programme de Médicalisation des Systèmes d'Information) were transmitted by the national agency for the management of hospitalization data. This process was approved by the National Committee for Data Protection. Transmission of these data to a third party is forbidden. Despite the fact that PMSI data are confidential, they are available for researchers who meet specific criteria, from the Agency for Information on Hospital Care (ATIH-Agence Technique de l'Information sur l'Hospitalisation).
Study Design We retrospectively analyzed the data for all patients living in France and admitted to public and private hospitals in France for acute myocarditis or endocarditis between January and September 2020. This period included the first peak of the COVID-19 pandemic and the national complete lockdown from 17 March (week 12) to 11 May (week 19) 2020. Hospitalization numbers were compared month by month with the numbers from the same period in 2017 to 2019. Clinical characteristics and in-hospital deaths were compared between stays with and without COVID-19 during the lockdown. This retrospective study had no impact on patient care and all data were anonymous. This study was authorized by the French Data Protection Authority on 3 July 2020 (registration number: DR-2020-250 on 07/03/2020).
Statistical Analysis Qualitative variables are presented as frequencies (percentages). Quantitative variables are presented as medians and interquartile ranges (IQR). The different variables analyzed in the cohort of hospitalized patients were compared using the Chi 2 test or the Fisher's exact test (for qualitative variables) and the median test (for quantitative variables), between patients with and without COVID-19 during the lockdown. The change in the number of stays for each disease in 2020 compared with the mean of 2017 to 2019 by month was plotted as smoothed curves using degree 2 spline functions. The threshold for statistical significance was set at <0. 05. All analyses were performed using SAS (SAS Institute Inc. , Version 9. 4, Cary, NC, USA).
Limitations: This nationwide study is a descriptive, retrospective, observational study. Possible misclassification may have occurred. However, while under-detection of cases is of course possible, this risk should be greatly reduced by the long post-lockdown period studied. This prolonged period allowed for almost complete capture of the discharge abstracts, which are an obligation for all public and private hospitals. Moreover, we have no data on the causes of endocarditis or the number of surgical cases. Access times to hospital and procedures were not ascertained in discharge abstracts. Strengths: All French hospital data from public and private hospitals and primary, secondary, and tertiary cardiac units were collected, and we were, thus, able to be nationally representative. The post-lockdown period was evaluated, and the possible risk of a seasonal effect was limited by using data from 2017 to 2019.
Data Availability Statement: The PMSI database was transmitted by the national agency for the management of hospitalization data. The use of these data by our department was approved by the National Committee for data protection. We are not allowed to transmit these data. PMSI data are available for researchers who meet the criteria for access to these French confidential data (this access is submitted to the approval of the National Committee for data protection) from the national agency for the management of hospitalization (ATIH-Agence technique de l'information sur l'hospitalisation). Address: Agence technique de l'information sur l'hospitalisation, 117 boulevard Marius Vivier Merle, 69329 Lyon CEDEX 03.
Method A prospective naturalistic study of a clinical sample of adolescents under psychiatric treatment in the Maule Region, Chile. Adolescents will be evaluated using a thorough protocol that includes suicide-related clinical variables. The study seeks to establish patterns of change in the trajectories of ideation and suicide attempts among adolescents. Ethics and dissemination Ethical approval was granted by the Scientific Ethics Committee of the Universidad Católica del Maule in Chile. This protocol was registered in ClinicalTrials. gov. The results of this study will be disseminated to health centres through executive reports and feedback sessions. In addition, the most relevant findings will be presented in scientific articles, conferences and seminars open to the community. Trial registration number NCT04635163.
The treating clinical team will provide information about the study to their patients; and if they agree to participate, the researchers will contact them, always protecting patient anonymity. Participants will receive written and verbal information about the essential aspects of the research, its objective, benefits and clinical implications. Informed consent, signed by the participant if older than 18 years of age and by the mother, father, or responsible tutor if under 18, will be requested subsequently. Selected patients will be assessed at three time points during the study: at baseline, at 6 months and 6 months after the second measurement. It is estimated that the implementation time of the protocol will range from 60 to 80 min. To complement the information collected with the study protocol, clinical records will be used to extract data on family history, mental illnesses, hospitalisations, treatments and previous suicide attempts.
Statistical analysis and results Initially, different exploratory analyses will be carried out with the goal of obtaining a first approximation to the data and spot possible coding errors. Then, we will conduct analyses to examine the reliability and validity for each of the instruments in our protocol. Modelling techniques will also be implemented with the objective of analysing the information gathered from an explicative and predictive perspective, exploring the extent to which the models being tested fit the data. Finally, using latent class analyses for longitudinal data, we will seek to identify change trajectories in relation to the variables studied, based on the following hypotheses: 1. High levels of suicidal ideation at baseline will be associated with a higher likelihood of suicide attempts during follow-up.
Data analysis We calculated gain scores between the Pre and Posttests to assess the differences between them. Then, we obtained descriptive statistics of all the quantitative scores using R program version 3. 6. 2. We performed ANOVAs to evaluate changes over time for the gain scores, Water Balance Model use scores, and the Mid-Semester Evaluation. In the cases in which we found statistically significant differences, we applied Tukey HSD Tests to identify the differences between years using R. Given the number of pairwise comparisons, we used the Bonferroni correction to establish the threshold for   2 ), (3) (  1 ), (  2 ), (3) (3), (  1 ), (2) (3), (  1 ), (2) significance at p =. 008 for post-hoc tests within each ANOVA. To identify factors that would predict the gains or losses in students' post-test scores, we performed an Analysis of Covariance (ANCOVA) where we included the categorical factors of gender, academic level and Major (STEM or Non-STEM), and all two-way interactions, and the covariate is the students' pre-test scores.
To analyze the qualitative data from the MSE, we evaluated, coded, and categorized each response to perform a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis about students' perceptions of the course. The SWOT analysis complemented the quantitative analysis from the MSE. First, we organized students' comments by year, academic level, and Major using Word. Each comment received a number based on the order in which it was reviewed. We developed a code sheet using Excel with "strengths", "weaknesses", "opportunities", and "threats" as main categories. We added columns representing the year, academic level, and Major to help keep track each response. As we read each response, we identified emergent sub-categories using representative words and assigned each comments' number to a corresponding category and sub-category.
When a comment represented two or more categories or subcategories, it was added to the corresponding sections. As we read each comment, we also highlighted those that provided an ample description of the student's opinions on the topic being discussed. With support of the code sheet, we developed a summary of strengths, weaknesses, opportunities, and threats for each question and year and re-organized the students' responses accordingly using Word. The summary helped us identify students' steady and changing perceptions of the course for each year. While developing the narrative, we traced back to the students' responses and selected from those that were highlighted the most representative ones.
Patient Source and Enrollment The Algerian healthcare system is a wide network of hospitals, clinics, and dispensaries. It is mainly public, accessible and free of charge to all Algerian citizens; with a recent sharp increase in the private sector. According to their age, patients were initially assessed by pediatricians or other adult specialists, from either outpatient clinics or inpatient wards. Any patient with clinical signs suggestive of IEI was addressed to the department of medical immunology at Beni Messous University Hospital Center, with a request form and clinical information sheet that may suggest an IEI. Request forms were examined and entered into a dedicated database.
Data Collection and Evaluation The request forms contained the following information: i. referral centre's contact details ii. patient's demographics such as full name, date of birth, gender, place of birth, age at onset of suggestive symptoms, parental consanguinity, familial history of IEI, history of suspicious sibling death, patient's history of severe, atypical, recurrent or persistent infections, patient's immunizations iii. clinical data: particular examination findings and any specific clinical phenotype (autoimmunity, lymphoproliferation, allergy, or syndromic features) iv. previous work up results v. management and treatments prior to referral vi. potential suspected diagnosis and investigations requested Regarding confidentiality and patient data privacy, the collected data were listed in an electronic database with a highly restricted access.
Statistical Analysis Statistical analysis was done using a commercially available software package (SPSS Statistics 17. 0. 0; SPSS, Chicago, Ill). Descriptive statistics were reported for all variables in the cohort. All quantitative variables were reported with mean values, and median for continuous variables. Kaplan-Meier curve plots was used to distinguish survival curves; and logrank tests were used to compare these survival curves. A p-value of 0. 05 or less (p ≤ 0. 05) was considered as statistically significant.
Frequency and Distribution of IEIs From January 2008 to December 2021, more than 5,500 patients were screened for IEI in the department of medical immunology of Beni Messous University Hospital Center of Algiers. Among them, 807 were identified with confirmed IEI and included in the dedicated database. Up to 50 different IEI classified were identified, belonging to nine major categories (Figure  1 ) and, surprisingly, no patient was identified with an inherited bone marrow failure. The frequency and characteristic phenotypes of patients in each IEI category are represented in Table  1. The predominant category was the combined immunodeficiency (CID) (273 patients, 33. 8%), followed by predominantly antibody deficiencies (PAD) (198 patients, 24. 5%), combined immunodeficiencies with associated or syndromic features (SyCID) (194 patients, 24%), congenital defects of phagocytosis (57 patients, 7.
The diagnostic delay is defined as the time interval between the onset of symptoms and confirmed diagnosis of a disease. Significant diagnostic delay has been noted in Algeria (Figure  3B ), with an overall median diagnostic delay of months but over a broad age-range (from less than 1 month to 30 years), and it was more important in adult patients (9 years; 0-30 years) than children (12 months; 0-200 months). There were no antenatal diagnoses among patients registered in the database. The delay in diagnosis was shorter in CID (median: 4 months; range: 0-456 months) when compared to other groups of IEI. Among the most common CID, the shortest mean diagnostic delay was observed in SCID (median: 2 months; range: 0-10 months), followed by the Omenn syndrome/SCID-GVHD (median: 2. 5 months, range: 0-4.
DISCUSSION Most IEIs result from inherited defects in development and/or function of immune system; resulting in infections that develop and recur more frequently, autoimmune disorders and an increased risk of malignancies  (25). However, acquired forms have also been reported  (5, 26). This current report represents a single center study which provides epidemiologic, clinical, and genetic data on Algerian patients with IEI. At the time of analysis, a total of 807 IEI patients were registered, representing all provinces of the country, thus making this cohort a valid evaluation of the IEI in Algeria. Although our department represents the largest center for immunological investigation of IEIs in Algeria, the number reported in the current study does not represent all cases, therefore we are only able to report the minimal prevalence of these conditions.
ACKNOWLEDGMENTS We thank the patients who participated in the study and made this research study possible. We also would like to thank  Prof. Raif Geha  and  Dr. Janet Chou  for providing genetic analyses, and prof  Mohamed Ridha Barbouche  for his critical reading of the manuscript. Thanks to the  Laboratory of Human Genetics of Infectious Diseases  which is supported by the  Howard Hughes Medical Institute , the  Rockefeller University , the  St. Giles Foundation , the  National Institutes of Health (NIH)  ( P01AI06109 ,  R01AI095983 ,  R01AI127564 ,  UL1TR001866 ), the  French National Research Agency (ANR)  under the  "Investments for the Future" program  ( ANR-10-IAHU-01 ), the  Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence  ( ANR-10-LABX-62-IBEID ),  ANR - GENMSMD  ( ANR-16-CE17-0005-01 ),  ANR FNS   LTh-MSMD-CMCD  ( ANR-18-CE93-0008-01 ), the  French Foundation for Medical Research (FRM)  ( EQU201903007798 ), the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  824110  ( EASI-genomics ), the  Square Foundation, Grandir -Fonds de solidarité pour l'enfance , the  SCOR Corporate Foundation for Science, Institut National de la Santé et de la Recherche Médicale (INSERM) , and the  University Paris Cité.
AMPAR-mediated EPSCs were measured for 30 sweeps at 0. 05 Hz. Only the peak amplitudes of monosynaptic EPSCs relative to the prestimulation baseline were used for data analysis. For paired-pulse ratio (PPR) and NMDAR/AMPAR ratio experiments, the stimulation intensity was modified to the level that stably evoked 200-350 pA AMPAR-mediated EPSCs. For paired-pulse stimulation, two consecutive stimuli separated by 50 ms were delivered to LA principal neurons (voltage-clamped at -70 mV, 30 sweeps, 0. 05 Hz). Only recordings that displayed stable evoked first EPSCs were included for data analysis. PPR was determined by dividing the peak amplitude of the second AMPAR-mediated EPSC response by that of the first peak current amplitude. For NMDAR/AMPAR ratio experiments, LA principal neurons were first voltage-clamped at -70 mV, and 30 consecutive AMPARmediated EPSCs at a stimulus intensity that stably evoked 200-350 pA current responses were recorded (0.
Confocal imaging and image analysis GluN1, Shank2 or Shank3 and synapsin1/2 immunostaining in the LA and basal amygdala (BA) was imaged via confocal microscopy (FV1000; Olympus Corporation, Japan) at 63X magnification (UPLSAPO, 1. 35 NA) with 3X digital zoom using FluoView 4. 0 image acquisition software, yielding images with a size of 512 × 512 pixels (0. 138 µm/pixel, both x and y). Images were taken sequentially, and two counts of the line Kalman integration method were applied. For each section, z-stacks were obtained (30-35 images taken at 0. 3 µm apart) from a minimum of two regions in the LA and BA per brain slice, and a minimum of three brain slices were imaged per brain. Imaging parameters including laser power, amplifier gain, and offset, were optimised for each antibody and kept consistent for all subsequent imaging to enable direct comparisons between images of different genotype and zinc diet groups.
ImageJ software (NIH, USA) was used for puncta-by-puncta and colocalisation analysis. The postsynaptic GluN1, Shank2 or Shank3, and presynaptic synapsin1/2 immunolabelling was corrected for background intensity variation by subtracting a Gaussian (σ = 3 pixels) blurred version of the substack. The 3D Objects Counter tool in ImageJ was then utilised to analyse the number and intensity of GluN1, Shank2 or Shank3, and synapsin1/2 puncta and identify their colocalisation in a 3-dimensional space captured by the z-stack. Only GluN1, Shank2 or Shank3, and synapsin1/2 puncta colocalised in each z-plane were counted as colocalised. GluN1, Shank2 or Shank3 puncta that colocalised with synapsin1/2 were defined as synaptic to ensure data are directly relevant to changes occurring at synapses. For each data set, the image analysis criteria including intensity threshold and detection voxel size range were kept consistent for each experimental set, regardless of the genotype and diet manipulation.
In particular, thalamic-LA synapse function is significantly impaired, likely contributing to auditory fear memory deficits observed in Tbr1 +/-mice. We observed that the amplitudes of both AMPAR-and NMDAR-mediated EPSCs were decreased, and that presynaptic function (as measured by PPR) was altered at thalamic-LA synapses in Tbr1 +/-mice. Also, the synaptic puncta density of GluN1 and Shank3, was reduced in Tbr1 +/-amygdalae, indicating that diminished synaptic expression of  mice. Together our data suggest that normalisation of thalamic-LA synapse function in Tbr1 +/-mice is a central mechanism behind the dietary zinc-induced prevention of auditory fear memory impairment.
Acknowledgements We would like to thank members of the  Montgomery Lab  for helpful discussion and laboratory support, the  Vernon Jansen Unit Animal Facility of the University of Auckland , for assisting animal management,  Dr. Tzyy-Nan Eugene Huang ,  Emily He , and  Dr. Shane Ohline  for technical assistance with the auditory fear conditioning experiments, and  Dr. John Rubenstein  at  UCSF  for Tbr1 +/-mice.
Statistical analyses For subjects included between 2010 and 31 January 2014, data were recorded on the subject's file and then entered in the software dedicated to the study. For subjects included between 01 and 2014 and 31 August 2017, data were directly entered in the software system. Statistical analyses were performed using the SAS software, version 9. 4 (SAS Institute, Cary, NC, USA). The statistical analysis focused on subjects characteristics at first visit (inclusion). Quantitative variables were described using means, standard deviations (SD), medians, quartiles, minimal, and maximal values and qualitative data were described using number of cases and percentages. Missing data were not replaced, and percentages were calculated without accounting for missing data, unless otherwise specified.
Results Overall, 1337 subjects were included; 250 (18. 7%) had no data recorded, and 2 subjects refused their data to be analysed. Thus, the analysed population was composed of 1085 subjects. Main subjects' characteristics are provided in Table  1. The cohort was mainly composed of elderly subjects of 80 years old or above (73. 6% of subjects) and of women in majority (68. 3%), with a low/medium educational level (61. 9%), and living alone (53. 8%). Most subjects (88. 5%) had at least one cardiovascular risk factor and are exposed to polypharmacy, 83. 4% taking 5 and more medications daily. Clinical examination showed abnormal cardiovascular signs in 82. 2% of subjects, musculoskeletal signs in 44. 0%, and neurologic signs in 31. 9% of subjects.
Data Availability Statement: All the Spike gene sequences are publicly available on NCBI GenBank and registered with the following number: P1_D0: OL405044; P1_D4: OL405045; P2_D0: OL405046; P2_D4: OL405047; P2_D6: OL405048; P3_D0: OL405049; P3_D3: OL405050; P3_D5: OL405051; P3_D7: OL405052; P4_D0: OL405053; P4_D2: OL405054; P4_D4: OL405055; P5_D0: OL405056; P5D6: OL405057; P5_D19: OL405058; P5_25: OL405059; P5_52: OL405060; P5_68: OL405061; P6_D0: OL405062; P6_D2: OL405063; P6_D5: OL405064; P6_D7: OL405065; P7_D0: OL405066; P7_D4: OL405067; P7_D6: OL405068; P7_D8: OL405069; P8_D0: OL405070; P8_D0bis: OL405071; P8_D1: OL405072; P9_D0: OL405073; P10_D4: OL405074; P10_D6: OL405075; P11_D0: OL405076; P11_D3: OL405077; P11_D5: OL405078; P11_D7: OL405079; P12_D0: OL405080; P12_D4: OL405081; P12_D8: OL405082; P13_D-1: OL405083; P13_D0: OL405084.
Data analysis Absolute quantification of parasites Five lL of each serial dilution of the standard curve were used as positive controls for the qPCR. qPCR results were analyzed using CFX manager software, Version 1. 6 (Bio-Rad Laboratories GmbH, Munich, Germany). The mean logtransformed starting quantity estimated from the mean Ctvalues obtained for duplicates of each sample by the regression line from the dilution curve was used to determine the parasite load. The arithmetic mean log 10 -transformed DNA concentration was calculated and the detectable parasite burden was expressed as the number of parasites per gram of tissue/muscle, taking into account the weight of the sample and the volume of digested pellet.
Objectives Work-related stress is a major concern. One of the best performing models is the Job Content Questionnaire (JCQ) of Karasek, assessing job demand and job control using 18 items. However, the JCQ is long and complex. Visual Analogue Scales (VASs) are easy to use and quick to implement. VASs have been validated to assess pain and occupational stress; however, VASs demand and control have not been evaluated. Therefore, we aimed to validate the use of VAS demand and control compared with the 18 items of the JCQ. Design We implemented a cross-sectional observational study, by administering a self-reported questionnaire to the users of Wittyfit software, with a second test (retest) proposed 1 week later. In addition to JCQ, VAS demand and control, we measured sociodemographic outcomes, as well as characteristics of work, sleep, well-being, stress, depression and anxiety.