dataesr/scientific-paragraphs-categorization huggingface dataset:
Database The vendor of the D-IPC software provided a customized script for structured database export as an extensible markup language file (. XML). We processed this data with the MS Excel 2016 software package (Microsoft Cooperation, Redmond, WA, USA) and analyzed the prevalence of red flags, marked questions, and the rate of answered questionnaire items. Also, we compared for each patient the prevalence of documented red flags in C-PR and D-IPC. The information documented with C-PR included data from previously collected analog informed consents, the written requests from the referring physicians, and the documented risk factors and complications from previous examinations, each directly documented in the RIS. The information archived during D-IPC for the same patient was retrieved from the.
Statistics If applicable, we provide mean and standard deviation in the case of normal distribution. Median and interquartile range (IQR) with 75th and 25th percentiles are given when normal distribution was not assumed. Total patient counts for several questionnaire items do not sum to the same number for every category because multiple answers for pre-existing conditions or medications were allowed for most items. Moreover, there was no constraint in answering every questionnaire item. Normally distributed data were compared with paired t-tests. The Wilcoxon signed-rank test was used for further analysis if the normal distribution was not assumed. The significance level was defined as p < 0. 05. We performed statistical analysis with the software package SPSS Statistics Version 21 (International Business Machines Corporation [IBM], Somers, NY, USA).
Database comparison Patient history and clinical context information were completely missing in four (0. 2%) patients. For 1276 (75%) patients, only the clinical question for the CT examination was fully provided. However, the clinical context (e. g. , the kind of malignancy, current symptoms, recent changes in therapy) was incomplete. Consequently, missing patient information had to be retrieved from D-IPC, RIS, and the hospital information systems. Some severe discrepancies between the documented red flags by D-IPC and C-PR were found (Table  6 ). None of the D-IPC cases with a history of thyroid hyperfunction was documented in the C-PR (34 vs 0 cases). Also, for reduced kidney function (65 vs 2 cases), infectious diseases (51 vs 0 cases), hemodialysis (12 vs 1 case), and claustrophobia (214 vs 4 cases), large discrepancies between the documentation with D-IPC versus C-PR were apparent.
Indeed, we did not observe changes of CT examination numbers during this clinical routine study, which indicates comparable total time effort. Fifth, in the retrospective database evaluation, we could only count the total number of marked questions for each patient, but we had no insight into which questions were marked. Sixth, we could not register the number of patients who refused D-IPC before the assignment. Such patients were never digitally registered in the D-IPC software. Seventh, the CBA is based on calculations highly influenced by local prices (e. g. , IT services, national wage contracts). Therefore, international institutions should especially consider the local personnel's operational costs. Lastly, future developments will indicate, how many institutions and radiology sites are able and willing to pay the additional charges accompanied by D-IPC.
Funding Open Access funding enabled and organized by Projekt DEAL. We acknowledge financial support by Deutsche Forschungsgemeinschaft and Friedrich-Alexander-Universität Erlangen-Nürnberg within the funding programme "Open Access Publication Funding". Also, our research was funded by the Bavarian State Ministry for Economic Affairs, Regional Development, and Energy. Project title: Intelligent Examination Protocols for Personalized CT (iQCT, MED-1810-0020).
Studies that compared speed-effects between younger and older adults, reported that both groups' gait is more variable and stable at lower speeds (120-80%PWS), but older compared with younger adults are more variable and unstable at the same speeds  [18, 19, 22]. Gait symmetry increased with overground walking independent of age, but in old older adults (82. 5 ± 2. 2) HRs in AP direction decreased with speed  [16]. Other gait quality measures, amongst which gait smoothness and regularity, tended to increase with speed (treadmill, 0. 63-1. 72 m⋅s -1 ) in older adults  [23] , but such data are lacking in younger adults. The aim of the current exploratory study was to determine the effects of walking speed on quantitative and qualitative gait measures in younger and older adults. Specifically, we examined if age and the type of walking speed (absolute, PWS) would affect the relationship (linear, non-linear) between walking speed and measures of gait quality and quantity.
Gait measures During gait, AP, ML, and V trunk accelerations were recorded at 100 Hz by a built-in accelerometer of an Iphone SE (iOS 12, Apple Inc. ), fixed with a belt near the level of lumbar segment L3  [26]. Acceleration signals were analysed off-line using MATLAB (version 2020a, the Mathworks Inc. ). After detrending, signals were corrected for horizontal tilt, and except for the calculation of gait stability and predictability, low-pass filtered (Butterworth filter, 2nd order, cut-off frequency 20 Hz). Twenty steps were removed at the beginning and end of the signal, leaving 300 steps of steady-state data for analysis. The following gait measures were computed from the acceleration signals (see Appendix for detailed description): Stride length (Mean, SD), Stride time (Mean, SD), Stride frequency, Gait regularity (V, AP), Stride frequency variability (V, ML, AP), Gait smoothness (V, ML, AP), Gait symmetry (V, ML, AP), Gait stability per stride (V, ML, AP), Gait predictability (V, ML, AP), Gait synchronization (V-ML, ML-AP, AP-V).
Generalized additive modelling Using the mgcsv package (version 1. 8-34;  [35] ) in R software (R version 3. 6. 1, R core team, 2019), generalized additive mixed models (GAMMs) were used to model the effects of age and speed on gait measures  [27]. So-called smooth functions were constructed using a thin plate regression spline, which models (non)linear patterns by using a combination of increasingly complex basis functions  [28]  (e. g. , linear logarithmic, quadratic, etc. ) and were fitted with the maximum likelihood (ML) estimation method. Table  1  shows an overview of the GAMM models defined. To select the model that best fit the data, models 1-3, were compared using the Akaike Information Criteria (AIC). An AIC score of at least 2 AIC units lower indicates an improved model with a more accurate (relative) goodness-of-fit  [27].
Discussion We examined the relationship between walking speed and quantitative and qualitive gait outcomes in younger and older adults. As expected, gait measures were sensitive to walking speed but the type of relation with walking speed was outcome-dependent in younger and older adults. Slower vs. faster walking was associated with shorter strides, longer stride times, and a lower stride frequency, with more variability in these spatiotemporal measures independent of age. For gait quality measures, in agreement with previous data  [23] , decreasing walking speed was associated with decreases in gait symmetry, stability and regularity in all directions. Speed-effects of gait smoothness were direction dependent, as it decreased in V direction, but increased in AP and ML directions with decreasing speeds.
Acknowledgements This work was supported by the  French National Research Agency (France)  in the framework of the  Investissements d ′ avenir program  ( ANR-10-AIRT-05  and  ANR-15-IDEX-02 ). The sponsors had no involvement in the review and approval of the manuscript for publication. This work forms part of a broader transnational and interdisciplinary project, GaitAlps (NV).
Relation between bulls fertility and overall sperm DNA methylation profiles To assess the contribution of bull fertility to variations in the DNA methylation pattern, we performed principal component analysis (PCA) (Fig. 1A ) and hierarchical clustering (Fig. 1B ). Although we could distinguish three major clusters using a dendrogram (Fig. 1B ), interindividual variability in terms of DNA methylation was larger than intergroup resulting in no obvious clustering according to bull fertility status. To explore known effects of age on DNA methylation  [39, 40] , we analysed the PCA and hierarchical clustering results also with respect to age at ejaculate collection (Additional file 1: Fig. S1 ). These analyses demonstrate that in our dataset, neither fertility nor age of the bulls were major determinants of sperm DNA methylation patterns.
Bioinformatic analysis The sequences displayed the expected nucleotide composition based on MspI digestion and bisulphite conversion according to FastQC quality control. Subsequent quality checks and trimming were carried out using Trim Galore v0. 4. 5, which removed adapter sequences, poor quality bases and reads (Phred score below 20) and reads shorter than 20 nucleotides. High quality reads were aligned to the bovine reference genome (ARS-UCD1. 2) in which the sequence of the Y chromosome has been incorporated (GenBank: CM011803. 1) using Bismark v0. 20. 0 in the default mode with Bowtie 1  [104, 105]. The sequence of Y chromosome was extracted the paternal haplotype from a Bos taurus x Bos indicus hybrid (UOA_Angus_1 assembly). The bisulphite conversion rate was estimated from the unmethylated cytosine added in vitro during the end-repair step and was on average 99.
Genes containing DMCs at a maximal distance of 10 kb were subjected to enrichment analyses with the Database for Annotation, Visualization, and Integrated Discovery (DAVID) using default parameters  [41] , and using the gene list covered by the 1,880,513 background CpGs10 as the reference. Clusters of terms showing EASE enrichment scores above 1. 3 were considered significant. All other statistical analysis related to graphs plotting were computing using MATLAB software v. R2021a (The MathWorks Inc. , Natick, MA, USA).
Molecular investigation Genomic DNA from F92 was isolated using QIAsymphony (QIAGEN) with the DSP DNA Mini Kit (QIAGEN). Whole genome sequencing (WGS) and bioinformatic analysis were performed as described  [5, 6] , and sequencing reads are available at DNA Data Bank of Japan (DDBJ)/European Nucleotide Archive (ENA)/GenBank (Accession number: JAPIVM000000000). F92 belonged to multilocus sequence typing (MLST) sequence type (ST) 1901, a new N. gonorrhoeae multi-antigen sequence typing (NG-MAST) ST (porB-2553, tbpB-2459), and the novel N. gonorrhoeae sequence typing for antimicrobial resistance (NG-STAR) ST4837, because of the new penA allele, in the NG-STAR clonal complex 199 (CC199). Resistance to ESCs was conferred by the novel mosaic penA allele designated as penA-237. 001, encoding an amino acid sequence 99.
9 , 10 However, the link between graft thickness and visual outcomes is not consistent,  [11] [12] [13]  which could therefore question the pertinence of T/UT-DSAEK. Most of the published results relate to grafts generally > 100 µm. 12 , 14 , 15 Currently, no data are available for grafts < 100 µm. Thus, to assess the influence of graft thickness within T/UT-DSAEK grafts, we conducted a systematic review and meta-analysis on the efficacy of T/UT-DSAEK on postoperative outcomes (ie, visual acuity, pachymetry, cell count, spherical equivalent, and rebubbling and rejection rates), depending on the graft thickness. were pachymetry as central corneal thickness ( µm), endothelial cell count (cells per square millimeter), spherical equivalent (diopters [D]), graft rejection rate (%), and rebubbling rate (%).
Acknowledgment : We thank  Nathalie Piñol-Domenech , librarian at  Clermont Auvergne University , and the  librarians of University Health Sciences Library in Paris  for their support in the elaboration of database search strategies and the collection of the full-text articles. All authors have completed and submitted the ICMJE form for disclosure of potential conflicts of interest. Funding/Support: This study received no funding. Financial Disclosures: The authors indicate no financial support or conflicts of interest. All authors attest that they meet the current ICMJE criteria for authorship. Author Contributions: L. B. , V. N. , and F. D. were responsible for the design and conception of the study. L. B. and V. N. searched and collected studies and data. L. B. , V. N. , F. C. , F. D. , and B.
Data collection procedure Potential patients were identified from hospital CCU by the research team and were screened for eligibility. Once eligibility was confirmed, and if patients' health conditions were hemodynamically stable, they were transferred to the medical unit where post-PCI patients in a stable health condition are routinely transferred. The eligible patients were met in the medical unit and were introduced to the researchers and the nature of the study, and were invited to participate; those who wished to take part were asked to give their written informed consent 24 to 48 hours after transfer from the CCU, and when they were haemodynamically stable. The Socio-Demographic and Clinical Data Questionnaire and CSEQ were given to patients whilst they were in-patients of the medical unit (T1), and were followed by mobile and then the researcher met them personally during their follow-up appointments in the outpatient cardiac clinics to collect the data at three (T2) and six months (T3) after hospitalisation.
The study assessed 326 patients for eligibility. A total 255 patients with AMI were identified as potential and eligible patients at T1, therefore, the study included 255 patients. During the data collection procedure, 19 patients withdrew after T1 and 10 after T2 for personal reasons; 7 patients changed their telephone number so the researchers unable to contact them; and 9 died during the data collection period. The remaining 210 patients completed all measurements time points (Figure  1 ). The data collection procedure began in March 2019 and ended in October 2019, lasting approximately seven months.
Socio-Demographic and Clinical Data The Socio-Demographic and Clinical Data Questionnaire was developed by the research team, covering socio-demographic factors such as age, gender, marital status, educational level, and occupation status. In addition, clinical data including type of AMI and type of treatment modalities were obtained from patients' medical files (with appropriate ethical permission under their written informed consent). Sullivan, LaCroix, Russo, & Katon, Cardiac Self-Efficacy Questionnaire Cardiac self-efficacy was measured by the self-administered CSEQ developed by Sullivan, LaCroix, Russo, & Katon,  20. CSEQ is a valid and reliable questionnaire, with a Cronbach's alpha of 0. 90 for control symptoms and 0. 87 for maintenance function  20.
Data analysis The collected data were statistically analysed using SPSS version 22 for Windows (SPSS, Inc. , Chicago, IL, USA), while descriptive statistics were used to present the patients' sociodemographic characteristics. Repeated measure analysis of variance (ANOVA) was used to examine the impact of each type of AMI and different treatment modalities on changes in cardiac self-efficacy between T1 and T2, T2 and T3 and between T1 and T3. In addition, correlation in self-efficacy were examined based on socio-demographic characteristics, Pearson correlation was used with continuous variables such as age. Differences in self-efficacy were examined by repeated measure ANOVA, with categorical variables such as education and employment, and independent t-test was used with dichotomous variables, such as gender.
Patients presenting with symptoms at baseline, including exertional dyspnea, angina, presyncope, or syncope, were excluded. However, patients presenting with mild symptoms (New York Heart Association [NYHA] functional class II) not considered by their treating cardiologist to be related to MR were included. Moreover, patients with equivocal clinical history or symptoms underwent exercise testing to confirm asymptomatic status. The clinical and echocardiographic data were collected prospectively in the context of heart valve clinics, and the analyses were performed retrospectively. The methods for collection of clinical and echocardiographic data are described in detail in the Supplemental Material. Briefly, fasting blood samples were measured using automated techniques standardized with the Canadian and France reference laboratory, MR severity was evaluated by echocardiography as per an integrative multiparameter approach, and all other echocardiographic data were measured or remeasured in the research echo laboratories of each institution, as recommended by current American Society of Echocardiography guidelines.
Study Limitations and Strengths Although the clinical and echocardiographic data were prospectively collected, the present analysis is of retrospective nature and is, thus, subject to inherent limitations related to such design. The small sample size of the present study is a limitation, but this study includes a "real-life" population comprehensively followed, in which the symptomatic status was carefully assessed and monitored in the context of heart valve clinics. We elected to include patients with mild symptoms (i. e. , NYHA class II), which were considered not related to the MR by the treating cardiologist, because the therapeutic management and the determination of the optimal timing for intervention are also challenging in these patients. We also included patients with moderate MR at baseline because a substantial proportion of these patients may exhibit rapid progression to symptoms or LV dysfunction and be at an increased risk for mortality and cardiovascular hospitalization.
Funding This work was supported by a research grant ( FDN-143225 ) from the  Canadian Institutes of Health Research (CIHR) ,  Ottawa ,  Ontario ,  Canada. J. B. is supported by a doctoral scholarship from the  CIHR. L. T. is supported by a doctoral scholarship from  Fonds de Recherche en Sant e-Qu ebec(FRSQ) , Montr eal, Qu ebec, Canada. M. A. C. holds a New National Investigator award from the  Heart and Stroke Foundation of Canada  and an  Early Career Investigator award  from  CIHR. P. P. holds the  Canada Research Chair in Valvular Heart Diseases  from  CIHR ,  Ottawa ,  Ontario ,  Canada.
For the grounding, a needle was subcutaneously inserted in the back of animal (Supplemental Figure  S1 ). Measurements were performed simultaneously in both eyes using the Ganzfeld VisioSystem device (Siem Biomedicale, France). Scotopic ERGs were elicited with full-field light flashes corresponding to four levels of stimulus intensity (0. 04, 0. 32, 3. 19, 8 Cd. s/m 2 ). The responses were amplified and filtered (1 Hz-low and 300 Hz-high cutoff filters) with a 1 channel DC/AC-amplifier. The stimuli and ERG recordings were coordinated using Visiosystem (Siem Biomedicale, France) program software. The photoreceptor response of the scotopic ERG is represented by the negative a-wave. The positive (scotopic) b-wave reflects the function of the neurons in the inner retina, mostly bipolar cells (Supplemental Figure  S1 ).
Immunoreactive proteins were revealed using the Western Lightning Chemiluminescence Reagent Plus Kit (Perkin-Elmer, Whatman, Villebon sur Yvette, France), followed by densitometric analysis with Image J software (Win 32, Rasband, WS, Image J, US National Institute of Health, Bethesda, MD, USA). The optical density (OD) measured for each immunoreactive band was normalized to β-actin. The results were expressed as relative optical density (ROD).
Statistical Analysis GraphPad Prism 5 (GraphPad Software, San Diego, CA, USA) was used for all the statistical analyses. The results are expressed as means ± mean standard error of the mean (SEM). After normality was confirmed using the Shapiro-Wilks test of normality, two-tailed, unpaired Student's t-tests were used to compare the two groups of mice (WT versus TG APP/PS1). In all cases, significance was noted at p < 0. 05 (*) and p < 0. 01 (**).
Statistical Analysis GraphPad Prism 5 (GraphPad Software, San Diego, CA, USA) was used for all the statistical analyses. The results are expressed as means ± mean standard error of the mean (SEM). After normality was confirmed using the Shapiro-Wilks test of normality, twotailed, unpaired Student's t-tests were used to compare the two groups of mice (WT versus TG APP/PS1). In all cases, significance was noted at p < 0. 05 (*) and p < 0. 01 (**).
Funding: This work was supported by INSERM, CNRS and Fondation pour la Recherche Médicale (operating grant FRM n • DVS 20131228910 to SK), from Région Ile-de-France (DIM Cerveau et pensée to SK) and by French state funds managed by the Agence Nationale de la Recherche within the Investissements d'Avenir LABEX LIFESENSES [ANR-10-LABX-65] and IHU FOReSIGHT [ANR-18-IAHU-01]. Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Ethics Committee n • 005 of Direction Générale de la recherche et de l'inovation (protocol code APAFlS#7609-20l70l1713538844v2; date of approval 4 August 2017).
Acknowledgments: We are grateful to  Manuel Simonutti  for his expert help in setting the ERG recording conditions and  Ambra Masuzzo  for technical help with biochemical experiments during the initial phase of this project. We would also like to acknowledge the support from the laboratory directed by  Francine Behar-Cohen  at the Cordeliers Research Center where this work was performed. We would like to thank  Emmanuelle Gélizé  for the expert technical assistance throughout the study and for the critical reading of the manuscript and also  Cédric Ayassami  for the help regarding animal facilities.
Natraemia is often abnormal in critically ill patients and may change rapidly during renal replacement therapy (RRT). This database study in a single intensive care unit (ICU) evaluated natraemia before and after the first RRT session for acute kidney injury. Of 252 patients who required RRT in 2018-2020, 215 were included. Prevalences were 53. 9% for hyponatraemia (≤ 135 mmol/L) and 3. 7% for hypernatraemia (> 145 mmol/L). Dialysate sodium was ≥ 145 mmol/L in 83% of patients. Median dialysis sodium gradient was 12 mmol/L, with a value above 16 mmol/L in 25% of patients. Median natraemia increased from 135 before to 140 mmol/L after RRT, the median hourly increase being faster than recommended, at 1. 0 mmol/L [0. 2-1. 7]. By multivariate analysis, the only variable significantly associated with the RRT-induced natraemia change was the dialysis sodium gradient [odds ratio, 1.
Methods The study database was reported to the French data protection authority (Commission Nationale de l'Informatique et des Libertés, #220969, on 24 November 2018). The data were anonymised before use for the study. French law does not require written informed consent for retrospective analyses of anonymised healthcare data (Journal Officiel de la République Française n°0160 on 13 July 2018). However, all patients or families were informed of the study, in writing, at the time of prospective data collection; those who were unwilling to participate were not included. This study protocol was approved by the ethics committee of the Société de Réanimation de Langue Française (#CE-SRLF 20-74 on 29 September 2020) and registered on the French national healthcare database (Institut National des Données de Santé).