dataesr/scientific-paragraphs-categorization huggingface dataset:
Next, we appraised the impact of CatS on the permeability of the 16HBE cells seeded on Transwell inserts, using FITC-dextran as a fluorescence reporter molecule. A conclusive increase in epithelial permeability was observed in the presence of CatS (p < 0. 01). On the other hand, there was a complete restoration of basal permeability of the 16HBE cells in the presence of LHVS, a specific CatS inhibitor (Figure  5b ). These data were corroborated by a cell-based transepithelial electrical resistance (TEER) assay, which demonstrated that the exposure of 16HBE cells to CatS led to decreased TEER (p = 0. 008, 12 h post-treatment) (Figure  5c ). experiments, in which each were performed in triplicate. Data were normalized to the control experiment. (d): NHBE cells were treated by CatS and FITC-dextran permeability assay performed as described above.
(e): NHBE cells were treated by CatS and TEER was measured. (f): FITC-dextran permeability assays were conducted on 16HBE cells that were grown at the air-liquid interface (ALI) and then treated with CatS as described above. (g): Identical FITC-dextran permeability assays were conducted on NHBE cells, which were grown at the air-liquid interface (ALI). Data corresponds to the average of five independent experiments. Bars represent median ± quartile. Statistical significance was assessed using non-parametric Kruskal-Wallis (a,b,d,f,g) or Mann-Whitney U (c,e) tests (* p < 0. 05; ** p < 0. 01). ns: not significant. A similar increase in permeability, linked to a drop in transepithelial electrical resistance, was observed following the incubation of normal human bronchial/tracheal epithelial cells (NHBE cells) with CatS (Figure  5d-e ).
Confocal microscopy studies indicated that the immunolabelling and distribution of occludin within tight junctions were drastically altered by CatS (Figure  6 ). CatS during 12 h. FITC-dextran was added on the upper chamber and fluorescence was measured on the basal chamber. Experiments were performed in presence or absence of LHVS (1 µM). (c): Transepithelial electrical resistance (TEER) of 16HBE cells. All the experiments were performed as three independent experiments, in which each were performed in triplicate. Data were normalized to the control experiment. (d): NHBE cells were treated by CatS and FITC-dextran permeability assay performed as described above. (e): NHBE cells were treated by CatS and TEER was measured. (f): FITC-dextran permeability assays were conducted on 16HBE cells that were grown at the airliquid interface (ALI) and then treated with CatS as described above.
(g): Identical FITC-dextran permeability assays were conducted on NHBE cells, which were grown at the air-liquid interface (ALI). Data corresponds to the average of five independent experiments. Bars represent median ± quartile. Statistical significance was assessed using non-parametric Kruskal-Wallis (a,b,d,f,g) or Mann-Whitney U (c,e) tests (* p < 0. 05; ** p < 0. 01). ns: not significant. A similar increase in permeability, linked to a drop in transepithelial electrical resistance, was observed following the incubation of normal human bronchial/tracheal epithelial cells (NHBE cells) with CatS (Figure  5d-e ). Beside standard (i. e. , submerged) cultures, the air-liquid interface (ALI) approach, in which the apical surface of the epithelial cells is exposed to air, is primarily used to mimic in vivo respiratory tract epithelia, since human bronchial/tracheal epithelial cells undergo muco-ciliary differentiation and possess a pseudostratified morphology.
Parameter estimation To reduce acquisition time, processing and measurements for images/videos were done separately using a custom software written in Matlab (R2019a) (MathWorks, Inc, Natick MA). In total 8 parameters were measured using the images/videos captured during each acquisition. First, the bone anatomy image (Fig. 1a ) was used to measure the MSC radius of curvature (ROC), opening angle (OA), and height (HE). Then, the second image (Fig. 1b ) was used to measure the skin thickness (ST) and the hypodermis thickness (HT). For the SWE videos of the third (Fig. 1c ) and fourth (Fig. 1d ) part of the acquisition, images were extracted and processed using a separate written code  [33]. The average value of the images of each video was calculated and then, the average of the three videos determined the shear wave velocity of one acquisition for: the skin (sSWE), the hypodermis (hSWE), and gluteus maximus muscle (mSWE).
Sample size and reliability assessment All the data were analyzed with the IBM SPSS for Windows (Version 27. 0. Armonk, NY: IBM Corp). The reliability study was conducted on the young, healthy group by two operators: a physician and an engineer. Both operators received extensive training consisting of two phases: first, measurements were repeated until reaching adequate reproducibility compared with an expert sonographer then, deviations were assessed, and possible problems were determined and corrected. The operators were asked to repeat the protocol three times on each subject, i. e. , captured three images for each of the bone geometry parameters and tissue morphology, and nine SWE videos for each tissue stiffness parameter. The reliability of our protocol was assessed by calculating the intra class correlation coefficient (ICC) for within-operator and betweenoperator for the young subjects group  [34].
Healthy young adults vs healthy elderly The same protocol was conducted once (one acquisition and measured once) on the older group by one operator: the physician. For the young adults group data, the measurements of one of the three acquisitions collected by the physician were chosen randomly. Normality was checked with the Shapiro-Wilk test and the equality of variance was assessed with the Levene's test. If both normal distribution and equality of variance of the different groups could be assumed, data were reported per parameter and per group as mean ± 1 SD and groups (young versus old) were compared using the student t-test. In case the normality or equality of variance assumption was violated, groups were compared with the Wilcoxon test. For all the tests, the significance level was set at 0.
In a final contribution, using data collected via an online panel in the State of New Jersey, Hannah Younes, Robert B. Noland and Wenwen Zhang (contribution 10) analyse factors associated with the decision to grocery shop online and whether this will persist in a post-Covid period. Their results highlight the importance of socio-economic and demographic factors as well as attitudes towards Covid-19. They also suggest that in-person grocery shopping will return to pre-pandemic levels, while pointing to some increased persistence in online grocery shopping after Covid. The collection of carefully refereed studies in this special issue of RSPP demonstrates the great relevance of quantitative (statistical and econometric) studies on the causal spatial links and effects of Covid-19 ('spatial coronametrics').
Survey of ASFC Members The ASFC association comprises 494 members who are most often diagnosed CFS or ME after clinical, biological, and imaging exams to eliminate other causes of fatigue (chronic infections, endocrine disorders, autoimmune diseases, depression, etc. ). We sent each member a specific questionnaire by private mail to determine if they met the SEID criteria and get their opinion on the new name SEID. The questionnaire was completely anonymous with return by mail or to the local committees of the ASFC association (paper version). The patients gave their consent by sending the answers to the questionnaire, but without giving their identity. The questionnaires were then numbered by the ASFC association and forwarded to the investigators. Data were collected over 9 months. All questionnaires were examined.
Symptoms Ranking We asked subjects to rate six symptoms (pain, activities limitation, PEM, unrefreshing sleep, cognitive impairment, and orthostatic intolerance) from 1 to 6 according to their disabling impact (Rank 1 for the most disabling, Rank 6 for the least). To display these observations, we built a radar chart that consists of a sequence of equi-angular spokes, with each spoke representing a rank. The data length of a spoke was proportional to the magnitude of the variable (proportion of subjects who classified the symptom at this rank). For each symptom, a line was drawn connecting the data values for each spoke (i. e. , each rank). The star-like appearance of the plot enabled comparison of the disabling impact of each symptom.
Statistical and Textual Analysis We used Epi Info™ software to analyze the data. To compare the two subgroups, SEID and non-SEID, we performed a non-parametric Mann-Whitney test for quantitative variables and a Chi-squared test for continuous variables. The scores, which were measured on the Likert scale, characterized the patient opinions and were calculated for the whole population. The text data were assessed by a semantic analysis of the key ideas associated with the SEID denomination.
As part of this toolkit, the IOM/NAM even feel that the development of clinical questionnaires or history tools that are valid across populations of patients should be an urgent priority  [9]. Rigorous recommendations when applying SEID diagnostic criteria were investigated by Asprusten et al. with an adolescent CFS cohort  [56]. This study used variables from a total of eight validated questionnaires to operationalize the SEID criteria, and then used baseline data to decide whether a patient fulfilled those criteria or not. Two CFS subgroups (SEID vs. non-SEID) were compared across baseline characteristics, as well as a wide range of cardiovascular, inflammatory, infectious, neuroendocrine, and cognitive variables. In the absence of a specific questionnaire for the identification of SEID criteria, we created an original questionnaire based on the recommendations of the IOM/NAM for identification of symptoms in patients who are characteristic of SEID.
Acknowledgments: We all spare an affectionate thought for  Françoise Bécavin , former President of ASFC, who was deeply involved in this project. We are very grateful to  Julie Ribes  ( ASFC ) for technical support in the preliminary treatment of the data, and to  Craig Morris  ( Vice-President  of  ME Support IOM/NAM ) and  Scott Brockett  for kindly reviewing the English language.
Materials and methods Study design and settings A retrospective observational study was performed in France using data collected between March 11, 2010, and March 10, 2022, from the FSN. The first year of the pandemic in France (March 11, 2020 to March 10, 2021) included two long national lockdowns (altogether, three months and ten days), two curfews (altogether, three months), and the prohibition of collective activities and closure of the associated venues (from seven months to one year, depending on the activity); the second year (March 11, 2021, to March 10, 2022) included a short lockdown (eighteen days) followed by the progressive reopening of venues for leisure activities, and access to vaccination (S1 Table ). While the lockdowns were nationwide, the level of contamination and deaths varied greatly between administrative regions: during the early part of the pandemic, the I ˆle-de-France and the North-East had the highest reported cumulative rates of hospitalization or death from COVID-19, and the South-Est had a low reported rate.
French primary care system particularities and data source France provides universal health insurance for its population under a system that reimburses GPs on the basis of a national fee schedule. This primary healthcare system offers coverage for all residents across the country. GPs do not serve a defined practice population: primary care offers coverage for all residents, and all residents may freely choose their GP. Since 1984, the FSN, a nationwide monitoring system, has collected near real-time epidemiological data from participating French GPs. For the purpose of this study, we used data on SAs and CSs reported by GPs to the FSN. The FSN comprises approximately 500 voluntary Sentinel GPs (1. 2% of the French GP population) who routinely report data on health indicators, including suicidal acts.
Data collection, case definition and inclusion criteria Each week, GPs report the number of suicidal acts among their patients through an online questionnaire. GPs report each suicidal act in their patients whether they were reported by the patient him/herself or by other professional caregivers or their family. Suicidal acts are defined as follows: "self-inflicted injury or self-poisoning with drugs in excess of the generally recognized therapeutic dose, excluding non-suicidal self-injury or self-poisoning  [31, 32] ". For each reported case, GP provide descriptive data. Collected data evolve according to research interests and context  [27, 31, 33, 34]. The data included sociodemographic characteristics, history of previous attempts, the method used for the suicidal act, the vital outcome (whether the patient survived or died), and the characteristics of the last consultation in primary care (date, reasons, exploration, and expression of suicidal ideation).
From January 2020, data on psychiatric disorders, psychosocial context (job insecurity, financial, sentimental, familial difficulties, social isolation), and potential links between the suicidal acts and the pandemic have also been collected. All cases reported by Sentinel GPs from March 11, 2010, to March 10, 2022 were included in the analysis, except those for which the vital outcome of the suicidal act was missing (n = 64).
Two geographical variables were created from the zip code of the GP who reported SAs and CSs during the periods of interest. The first was a five-category variable, defined according to the telephone area code (Ile-de-France, Northwest, Northeast, Southeast, Southwest), consistent with the various degrees of pandemic intensity across the French regions as described in the 'settings' subsection  [36]. The second was a rural/urban dummy variable created from the zip code of the GPs based on data from the French National Statistical Institute (INSEE, France).
Ethical statements The FSN is approved by the National Data Protection Agency (CNIL, registration number #47139). The protocol was conducted in agreement with the Helsinki Declaration. All GP participants are volunteers to participate. They are informed about studies conducted from their medical charts. Patients are informed that their GP belongs to the FSN. Data reported by GP to the FSN are anonymous. We performed this study on anonymous data without any way to identify patients. For this kind of studies, under French law, consent of the patients is not needed. But patients are well informed that they can refuse the transmission of their data. The ethics committee « Comitede protection des personnes Ile de France V » approved this procedure.
Population CoLaus|PsyCoLaus is a population-based cohort exploring the biological, genetic and environmental determinants of cardiovascular risk factors, cardiovascular diseases and mental disorders in the middle-to-older-aged population of Lausanne, Switzerland. The methodological aspects (participant recruitment and follow-up) have been previously reported. 15 Briefly, a simple, non-stratified, random sample of 6734 subjects from the Lausanne population aged 35-75 years was recruited between 2003 and 2006. The baseline and three follow-up evaluations included physical and psychiatric examinations, blood sampling and self-completed questionnaires. All data analysed in the present paper were obtained from the second physical follow-up evaluation (n=4881), which took place between 2014 and 2017.
Covariates The current socioprofessional category was selfreported by participants. Sociodemographic (age, sex) and lifestyle (smoking habit, alcohol intake, coffee consumption) data were collected by self-administered questionnaires. Educational level was categorised as low (primary), middle (apprenticeship or secondary school) or high (university). Smoking status was categorised as Open access never, former or current. Body weight and height were measured with participants standing without shoes in light indoor clothing. Body weight was measured in kilograms to the nearest 0. 1 kg using a Seca scale (Seca, Hamburg, Germany). Height was measured to the nearest 5 mm using a Seca height gauge (Seca, Hamburg, Germany). Body mass index (BMI) was defined as weight (kg)/height 2 (m 2 ). Obesity was defined as BMI ≥30 kg/m 2.
To assess collinearity between covariates, a linear regression analysis including all covariates was performed, and the variance inflation factor (VIF) was calculated. A VIF ≤5 was considered as absence of multicollinearity. Results from logistic regression are presented as OR values with 95% CI. Permanent day workers were considered as the reference group. All statistical analyses were performed using IBM SPSS Statistics V. 26. 0 for Macintosh (IBM Corp). Significant results were considered for a two-sided test with p<0. 05.
Acknowledgements The authors thank  Prof. Mehdi Tafti ,  Prof. Vincent Mooser ,  Daniela Andries  and  Nadia Tobback  for their important contribution to the  HypnoLaus and CoLaus|PsyCoLaus Cohorts , the Lausanne population who volunteered to participate in the CoLaus|PsyCoLaus and HypnoLaus studies, as well as the whole team of CoLaus|PsyCoLaus. Contributors VB, MB, PMV, MP and RH designed the study. JH-R, PM-V, M-PS, MP and RH collected the data. MB performed the statistical analysis. VB, MB, GS, JH-R, PMV, M-PS, MP, DL and RH interpreted the data. VB and MB wrote the first draft of the manuscript and GS, JH-R, PMV, M-PS, MP, DL and RH critically reviewed the manuscript. All authors undertake to give final approval of the version to be published and agree to be accountable for all aspects of the work.
Funding The HypnoLaus and the CoLaus/ PsyCoLaus studies were supported by research grants from  GlaxoSmithKline  ('not applicable'), the  Faculty of Biology and Medicine of Lausanne  ('not applicable'), the  Swiss National Science Foundation  (grants  3200B0-105993 ,  3200B0-118308 ,  33CSCO-122661 ,  33CS30-139468  and  33CS30-148401 ),  Leenaards Foundation  ('not applicable'), and  Vaud Pulmonary League  ('not applicable').
Materials and Methods Design A qualitative exploratory research was conducted using cross-sectional data from one center, in the hematology pediatric and internal medicine departments of the University Hospitals of Lyon. Semi-structured interviews with patients and HCPs were conducted by a researcher (DH, female), dedicated to this research and with prior training in the methodology, and then analyzed via the "inductive content analysis" method  [14] [15] [16]  by two researchers (DH, female; RG, male). The used method abides by the COREQ (consolidated criteria for reporting qualitative research) and SRQR (Standards for Reporting Qualitative Research) checklists.
The "inductive content analysis" was previously described,  16  and two researchers conducted the analysis to increase its objectivity. Also study results were compared to those in the literature to assess plausibility. The objective of the "inductive content analysis" was to identify raw and fundamental data significant to the object of the research. This analysis was chosen because it is more explorative in nature: the knowledge is produced from data as opposed to "deductive analysis" for which theoretical knowledge precedes the reading of reality. Our method was based on individual semi-structured interviews that allowed the exploration of participants' experience around a framework and without a priori. An individual interview setting was chosen over a focus group for collecting each participant's point of view in an equitable manner.
Only two participants accepted it. Regarding inclusion criteria, patients were interviewed face-to-face when they came to the study center for a medical consultation or follow-up visit, without any pre-selection. Our study sample is not meant to be representative. Regarding inclusion criteria, healthcare providers were interviewed at their place of work. The sample size of participants was chosen so that recruitment could be completed within one year of inclusion while meeting the COREQ quality criteria of a qualitative study. 19 It is an intrinsic limitation of this explorative study. This explains partly why data saturation was not reached but also since the study only reports one part of the 3-topic interview guide. Because the context of this research can never be exactly the same, this work cannot pretend to be reproducible.
In order to concentrate on the indicators' key data, a function for the automatic cleaning of outliers has also been implemented. Regional health care pro les combine data at a high level of spatial resolution (i. e. a total of 2,122 Austrian municipalities) and comprise 35 indicators. Indicators for each of the 2,122 municipalities are calculated as averages of all municipalities within a 10-, 15-and 20-minute car travel-time isochrone of the PHCU location municipality. We used mainly SQL scripting to pre-process the large amounts of data and a Microsoft Excel le as the automatic report generator. Record linkage at the level of anonymised individual personal identi ers played a role for four indicators (Rate of inpatients with heart disease within 2 years, Rate of inpatients aged 65 and above with femoral neck fracture within 2 years, Rate of inpatients with cerebrovascular disease within 2 years, and Rate of inpatients with cancer within 2 years).
We first carried out PCA for children with complete data for all EBRBs (girls, n = 98; boys, n = 91). Next, to test whether the input variables violated the normal distribution hypotheses, we performed PCA on the polychoric correlation matrix derived after considering the (initial) categorized EBRBs  [25]. To optimize the clinical interpretation, we further dichotomized health outcomes according to well-defined cut-offs and replicated our main analysis. Finally, to evaluate the robustness of our effect estimates to unmeasured confounding, we calculated E-values for each lifestyle pattern-outcome association  [24]. All statistical analyses were stratified by sex and performed with R software, which took into account the multiply imputed data and the sampling design.
Search strategy The search strategy was determined a priori, and the protocol was registered to PROSPERO (ID CRD42021275212). No deviation from the PROSPERO protocol was made. A literature search was conducted to retrieve eligible systematic reviews with or without meta-analysis that addressed the above research objective. Flowcharts, using the PRISMA method  (9, 10) , summarized the different steps of the article selection for each investigated cardiovascular risk factor. The following databases were searched for eligible reviews from inception to September 2021, updated to September 2022: Web of Science (including WOS, KJD, MEDLINE, PubMed, RSCI, SCIELO) and Cochrane review library. Moreover, screening the reference lists of the selected papers completed the searches. Relevant reviews listed and not found by the main step of research strategy were integrated, as it needed.
Inclusion and exclusion criteria and articles selection Any systematic review published in English or French, dealing with quantification of the relationship between nightshift work and studied cardiovascular risk factors in the working population was included. Narrative, comprehensive and mechanistic reviews were excluded, as well as research protocol without any result. Reviews focusing on long working hours, or atypical or irregular working hours were not considered here. The list of excluded articles with the reason of exclusion is available in Supplementary Table  B. For each investigated topic, two out of three independent experts in occupational health and cardiovascular epidemiology areas (YE, SB, EB) independently conducted the articles selection by using defined search terms in databases.