dataesr/scientific-paragraphs-categorization huggingface dataset:
This MNA™ criterion was applied regardless of the age of the residents. The study was validated by the Ethics Committee and the Board of Directors of the LINUT Network, a structure of the Agence Regionale de SanteNouvelle Aquitaine, in accordance with the agreement signed with the nursing homes for the use of data collected for scientific purposes, after acceptance by the residents or their legal representatives. The databases were set up prospectively. They were processed anonymously using Statview™ software (SAS, Cary, USA). The quantitative values are presented as means ± standard deviation and the qualitative values as percentages. The analysis used Fischer's exact test, Student's t test and ANOVA. There was no multivariate analysis, given the limited number of criteria available in NH.
This study was carried out in accordance with approved guidelines. Equipment for behavioral testing. All the behavioral tests were conducted in free field in an acoustically treated booth. The stimuli were presented from a loudspeaker (B&W 600 Series) placed 180 cm from the subject, via a sound card (Fireface 800) controlled by a MATLAB (The Mathworks, Natick) graphical user interface running on a computer. All stimuli for the behavioral discrimination test were equalized in level in terms of loudness using a loudness model  30  implemented in Matlab (The Mathworks, Natick). A half-inch Brüel & Kjaer microphone was used for calibration. Stimuli were presented at an overall level of 20 sones, measured at the subject position with the subject absent. Speech perception tests were calibrated using a Matlab user interface and a Brüel & Kjaer Hand-Held Analyzer type 2250.
Audiological assessment. Otoscopy was performed before pure tone audiometry was performed using insert earphones ER3 and an Interacoustic AD 28 Diagnostic Audiometer  31. Hearing thresholds were measured at octave frequencies between 0. 25 and 8. 0 kHz in each ear using standard procedures  32. The four-frequency average (4FA) hearing loss was calculated by computing the mean of the thresholds obtained at 0. 5, 1. 0, 2. 0, and 4. 0 kHz in each ear. The hearing aids used by HI participants at their personal settings were measured using an HA2-2cc coupler and a broad-band speech-weighted stimulus using the Aurical Hearing Instrument Test (HIT) box and the OTOsuite software (Natus Medical Inc. , Taastrup, Denmark). Average real-ear-to-coupler differences were used to estimate levels of an amplified signal in the real-ear  33.
Electrophysiological procedure. Testing was conducted in the free field using a single loudspeaker, positioned 100 cm from the subject, at 0° azimuth. All recordings were obtained in a sound-treated booth while the subject sat in a comfortable chair attending to a muted, close-captioned movie of their choice. EEG recording was conducted using four electrodes: one reference electrode placed at FCz and two active electrodes ("M1" on left mastoid and "M2" on right mastoid). The ground electrode was placed on the forehead  35. For each stimulus, 120 epochs were recorded. The presentation order of stimuli was randomized across participants using a Latin square design  36. Each condition lasted 13 min for a total of an hour and fifteen minutes approximately. The EEG data were post-processed using a custom-designed Matlab script.
Audibility was estimated as the maximum value across different bands of one-third octave spectrum on the basis that audibility will most strongly be determined by the frequency region in which it is greatest. Data analysis. To determine the influence of hearing status (NH or HI) on performance in speech perception, PID, and cortical onset and ACC responses, analysis of variance (ANOVA) with repeated measures was used. To determine the influence of presentation level (normal and low), and frequency (HP or LP) on cortical onset and ACC responses, ANOVA with repeated measures was used. To examine the relationship between PID and cortical responses, and between PID and speech perception, and between cortical responses and speech perception, Pearson's product moment correlation analyses were carried out.
Acknowledgements Research reported in this study was partly supported by the  National Health and Medical Research Council  Grant  APP1088931  awarded to TYCC. The research was also partly supported by the  National Institute on Deafness and Other Communication Disorders of the National Institutes of Health  under Award Number  R01DC008080  awarded to TYCC. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We acknowledge the contributions of  Bram Van Dun ,  James Galloway , and  Harinath Garudadri  to the design of the research. We acknowledge  Mark Seeto  for his assistance with statistical analysis,  Vicky Zhang  for her assistance with hearing aid measurements, and  Carmen Kung  for her comments on an earlier version of the manuscript.
Background: The objective of this systematic review is to appraise evidence on the economic evaluations of advanced practice physiotherapy (APP) care compared to usual medical care. Methods: Systematic searches were conducted up to September 2021 in selected electronic bibliographical databases. Economic evaluation studies on an APP model of care were included. Economic data such as health care costs, patient costs, productivity losses were extracted. Methodological quality of included studies was assessed with the Effective Public Health Practice Project tool and the Critical Appraisal Skills Programme checklist. Meta-analyses were performed and mean differences (MD) in costs per patient were calculated using random-effect inverse variance models. Certainty of the evidence was assessed with the GRADE Approach.
Data extraction Data of included studies were extracted with a predefined standardized form that documented study design, population, study setting, number of participants, patients diagnoses and characteristics, types of APP MoC and UMC, the costs measured (health care system costs, patient costs and productivity losses), types of economic evaluations (cost-minimization, cost-effectiveness, costutility or cost-benefit analyses) and length of the follow-up. Cost-minimization represents an analysis of the difference in costs between APP care and UMC when the clinical effectiveness of the two approaches is considered equivalent. Data extraction was performed by one evaluator (SL) and verified by a second evaluator (AD). When data were missing or incomplete, original authors were contacted to obtain complete data and results.
Methodological quality assessment The methodological quality of included studies was assessed with the Effective Public Health Practice Project (EPHPP) tool (available at http://www. ephpp. ca/tools. html). The EPHPP tool is a generic appraisal tool developed for use in public health research. The tool can evaluate any study design and it appraises selection bias, study design, confounding, blinding, data collection method and number of withdrawals/dropouts. The EPHPP tool has appropriate content and construct validity  [20]  as well as good intra-and inter-rater reliability  [20, 21]. Since the EPHPP tool is not specific to economic studies, sections A and B of the Critical Appraisal Skills Programme (CASP) checklist developed by the Public Health Resource Unit, was also used in order to assess specifically the quality of the economic analyses  [22].
Data synthesis All costs were adjusted for inflation according to the study's original country and then converted to euro for the 2020 fiscal year based on the Bank of England's inflation and conversion rates, since the majority of the original studies calculated costs to euro  [23]. Rates used for conversion and inflation adjustment are available in supplementary material. Randomized controlled trials (RCTs) and cohort studies that measured costs from similar perspectives, such as the costs from the health care system, patients' costs or productivity losses were pooled together into separate meta-analyses through Review Manager (RevMan 5. 4, The Cochrane Collaboration, Copenhagen, Denmark). Meta-analyses were also calculated according to the clinical settings (primary, emergency, orthopaedic or paediatric orthopaedic care).
Strength and limitations Strengths of this review include systematic searches of four important bibliographical databases and the use of the validated Effective Public Health Practice Project tool to assess global methodological quality and of the CASP checklist to assess the quality of the included studies and their economic evaluations. The use of GRADE also represents a strength of our review, as it allowed a more objective and standardized analysis of the quality of evidence. Our review also included studies in different clinical setting and countries therefore increasing the generalizability of the results. However, some limitations need to be highlighted in the interpretation of our results. First, this review is mainly limited by the quality of the available evidence as only one high quality study was included.
Histological and Immunostaining Procedures Four µm paraffin-embedded kidney sections were stained with Masson's trichrome for morphological analysis. For immunohistochemistry, 4 µm sections of frozen kidney were fixed in acetone, incubated for 1 h in 5% bovine serum albumin (Euromedex, Souffelweyersheim, France), followed by 1 h 30 min at room temperature with biotinylated mouse antihuman IgA (Catalogue number 555884) or anti-mouse CD11b (Catalogue number 553309) (both from BD Biosciences, Le Pont de Claix, France). Detection was performed with vectastain elite ABCkit (Vector, Burlingame, CA, USA). Slides were mounted with Immuno-mount (Thermo Fisher Scientific), read with an upright microscope, DM2000 (Leica, Wetzlar, Germany) at ×400 magnification using IM50 software (Leica) and scanned with AperioScanScope CS System (Leica Microsystems SAS, Nanterre France) and staining was quantified using TRIBVN CaloPix software (TRIBVN, Chatillon France).
For CD89 kidney staining, 4 µm sections of frozen kidney were fixed in acetone, incubated for 1 h in 5% bovine serum albumin, followed by anti-CD89 mAb (clone A3, homemade) and developed by staining with anti-mouse Ig coupled with FITC. Slides were mounted with Immuno-mount, read with an upright fluorescence microscope (Leica, Wetzlar, Germany) at ×40 magnification using IM50 software (Leica).
Quantitative Real-Time PCR Analysis Total RNA from mouse kidneys was extracted using RNABLE (Eurobio), and reverse transcription was carried out using 1 mg of total RNA and Moloney murine leukemia virus reverse transcriptase (Invitrogen). The quantitative transcription profile of TNF-a, TGF-b, MIP-2, MCP-1 and KC expression in kidneys was determined in triplicate with a TaqMan real-time PCR assay using a CFX96 PCR system (Bio-Rad). PCR data were reported as the relative increase in mRNA transcripts using the levels of b-actin mRNA as normalizer. Primers for TNF-a and TGF-b are listed in Supplementary Methods; all other primer sequences are available in Rosatto et al. (31).
The sequences of primers are: 16S Amplicon PCR Forward Primer = 5' TCGTCGGCAGC GTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWG CAG. 16S Amplicon PCR ReversePrimer=5'GTCTCGTGGGC TCGGAGATGTGTATAAGAGACAGGACTACHVGGGTAT CTAATCC. Forward overhang: 5' TCGTCGGCAGCGTCAGA TGTGTATAAGAGACAG-[locus specific sequence]. Reverse overhang: 5' GTCTCGTGGGCTCGGAGATGTGTATAAGA GACAG-[locus specific sequence]. PCR and sequencing analyses were carried out according to the protocol of Genomix4life. Quality control (QC) and taxonomic assignments were undertaken according to the QIIME and the Ribosomal Database Project Bayesian classifier in combination with a set of custom designed informatics pipelines implemented by Genomix4life for analyses of microbial communities. Taxonomic attribution was carried out using the BLAST search in the NCBI 16S rRNA sequences database  (33).
The percentage of each bacterial OTU was analyzed individually for each sample  (34). Alpha-diversity indexes (including: number of OTUs, Chao1 species richness, and Shannon index) were calculated using QIIME  (35, 36). The raw sequences were deposited in NCBI Sequence Read Archive (BioProject accession number: PRJNA732260; https://www. ncbi. nlm. nih. gov/sra/PRJNA732260).
Statistics Kruskal-Wallis test with Dunn's multiple comparisons test or Mann-Whitney U test were performed for comparisons between groups. Correlations were analyzed with Spearman's test. Statistical analyses were performed with GraphPad Prism 6. 0 (GraphPad Software, Inc. , San Diego, CA). For the microbiological analysis, differences between sampled groups were analyzed using the two-tailed Student's t-test for independent samples, with a significance level of p-value (P) ≤ 0. 05. For metabolomic analysis, one-way ANOVA analysis of variance with a post-hoc Tukey test was performed for comparisons between groups. Permut-MatrixEN software was used to identify clusters among the sampled groups and taxa  (38).
Fecal Microbiota Transplantation Is Able to Modulate Volatile Organic Compounds Profile A comparison of metabolomic patterns in fecal samples of mice after FMT was performed based on qualitative and quantitative differences in VOCs using HS-SPME GC-MS methodology. Fifty-nine volatile compounds were identified and grouped according to chemical classes, i. e. , alcohols  (14) , aldehydes  (11) , organic acids  (7) , ketones  (6) , phenols  (5) , indoles (2), esters (3), terpenoids (3), hydrocarbons (3) and others (5) (data not shown). The content of metabolites largely varied among the groups; indeed, some significant differences were evaluated within alcohols, aldehydes, phenols, organic acids, ketones and indoles (Supplementary Table  5 ). Indole and p-cresol were significantly higher (P ≤ 0.
Prevalence of exposure The study used the data from the 2015 European Working Conditions survey (EWCS) to assess the prevalence of exposure (Pe) to psychosocial work factors. This survey is a periodical survey on working conditions among the European working populations set up by the European Foundation for the improvement of living and working conditions (EUROFOUND) since 1990. This survey is an important source of information for the assessment of occupational exposures in European countries, as it relies on the same protocol and questionnaire all over Europe. The sixth edition of the survey was performed in 2015 and covered 35 European countries, including the 28 European Union (EU) countries (the UK was still part of the EU in 2015). The sample was representative of all workers, employees and self-employed workers, aged 15 or more, living in private households, and in employment at the time of the survey (i.
e. who worked during the week preceding the interview according to Eurostat definition). The sampling procedure was a multistage stratified random sampling. More information about the survey protocol and sampling design can be found elsewhere  (EUROFOUND 2017). The survey sample included 43,850 workers. The sample was restricted to employees, as self-employed workers were not always asked the same questions in the survey. Consequently, the study sample included 35,571 employees, including 17,109 men and 18,453 women. There were 9 employees without information about gender, and their data were used when all men and women together were studied. The sample size of employees according to country ranged between 553 (Albania) and 2762 (Spain) with a mean value of 1016 in each country (Supplementary Table  S1 ).
Five psychosocial work factors were assessed using the 2015 EWCS data as follows: job strain, ERI, job insecurity, long working hours, and bullying. The list of the items from the 2015 questionnaire used to construct these factors is presented in Appendix. The construction of the factors was close but not strictly identical to the construction of the factors of job strain, ERI, and job insecurity in our previous publication  (Niedhammer et al. 2014a) , as some items were removed or added in the 2015 questionnaire compared to the 2005 questionnaire. To make the factor construction possible, the coding of some items (with reverse formulation) was reversed and the coding was made homogeneous if the coding was different between items. Job strain was defined by the combination of high psychological demands and low decision latitude following the job strain model  (Karasek et al.
73). There was no major change in Cronbach's alpha coefficients between countries. Job insecurity was measured using the same one item (strongly or tend to agree to lose job in the next 6 months). Long working hours (one item) was defined by 55 h or more a week, this threshold being chosen to be consistent with the literature. Bullying was measured using one item, which was exposure to workplace bullying/ harassment within the past 12 months. The prevalence of exposure to these five factors was calculated from weighted data to provide estimates that were representative for Europe as a whole (35 countries), for the 28 EU countries, and for each country. The calculation of 95% confidence intervals also took weighting into account. The difference in exposure between countries was tested using the Wald test.
Limitations and strengths of the study The strengths of the study were the following: We used the data from the 2015 EWCS that is a large survey at European level covering both men and women in all countries. Weighted data were used to make the extrapolation possible at European and national levels. We were able to provide estimates for the prevalence of exposure that were based on the same questionnaire and the same definition for exposure, i. e. that were comparable across Europe and between European countries. We were thus able to provide up-todate estimates of exposure prevalence for Europe and each country  (Niedhammer et al. 2012). Five exposures were studied: job strain, ERI, job insecurity, long working hours, and workplace bullying, that constitute major psychosocial work hazards in developed countries.
Study design and patients We conducted a prospective observational cohort study at a single center between January 2016 and January 2019 at the medical ICU of the university hospital of Poitiers in France. The study was approved by the independent ethics committee of Poitiers (CPP Ouest III) with the registration number 2015-A01726-43, and was registered at http:// www. clini caltr ials. gov with the trial registration number NCT02911506. Patients and/or their next of kin were informed and gave their written consent before being included in the study. Patients were extubated after having successfully undergone a spontaneous breathing trial using T-piece for 1 h  [15]. All patients extubated after at least 24 h of mechanical ventilation could be included if they were at high-risk of extubation failure according to the following criteria  [16, 17] : older than 65 years of age, with any underlying cardiac or chronic lung disease, or intubated more than 7 days prior to extubation.
Preparing for PMA's baseline survey begins with a 2-week in-person training for the country team project staff and field supervisors, followed by a 2-week training of interviewers. Before each subsequent survey round, teams hold shorter refresher trainings, typically between 3 and 5 days, to review challenges from the previous round and train on new survey topics. Facilitators employ a variety of formats, including lecture, small group activities, individual assessments, and field exercises. In late 2019 and early 2020, teams in 4 of the 8 PMA countries-Burkina Faso, the Democratic Republic of the Congo (DRC), Kenya, and Nigeriacollected baseline survey data in-person, obtaining consent and phone numbers from women willing to participate in follow-up surveys. These teams also had previous experience with conducting remote surveys over the phone as part of PMA Agile, a separate project within the PMA platform.
They then shared links to the training content for each session, which video lectures previously recorded and uploaded to the PMA YouTube channel, as well as activity instructions, and links to individual assessments. They posted training content to the "Info" group in the order given in the agenda, with time between each post for interviewers to watch the videos or complete the activity. If interviewers had questions, they posted them to the "Q&A" WhatsApp group. Small group activities were completed in their assigned "My Groups" WhatsApp group. Interviewers completed assessments using Open Data Kit or GoogleForms that facilitators then graded. The lead trainer moderated the "Q&A" group and coordinated with facilitators moderating the "MyGroups" and grading assessments to post any information that was relevant to all interviewers to the "Info" group.
They relayed responses back to interviewers via the county groups, thus standardizing training content for all interviewers. In the DRC, KSPH recruited a subset of 25 interviewers who had participated in the baseline survey and/or PMA Agile. To translate the COVID-19 questionnaire into Lingala, a language not widely written, the team invited interviewers to participate in a pretraining competition. Interviewers submitted audio files of their questionnaire translations in Lingala. The central team reviewed submissions and sent the most accurate and specific translations to all interviewers as the standard translation for each question. In calls enabled interviewers to socialize and discuss training content further. CRERD continued using the WhatsApp "Q&A" group during data collection to reinforce learning and enhance general communication.
Acknowledge Trade-offs Between Country Ownership and Timelines Acknowledgments: We thank  Performance Monitoring  for Action field supervisors and interviewers who led and participated in remote interviewer training. We appreciate their commitment to making training a success during a challenging time. We also acknowledge  Johns Hopkins Bloomberg School of Public Health  staff who devoted considerable effort to creating high-quality training materials quickly and the particular support of  Blake Zachary  and  Shulin Jiang. Funding: The  Bill & Melinda Gates Foundation  supported this work under grants  OPP1198339  and  OPP1198333.
This in turn enables reasoning both on the classes themselves (to verify the coherence of the model) and the data (instances) to discover new relationships between data pieces. Ontologies are different than terminologies. Multiple terminologies exist worldwide in the biomedical domain, including the Unified Medical Language System (National Library of Medicine, Bethesda, MD, USA) that relate different terminologies representing the same concepts (e. g. , diabetes), or the Health Canada drug product database containing codes for the available commercial drug products. Nevertheless, these resources do not describe the structure of biomedical documents nor the rules governing their subparts (mereology). Terminologies consequently do not, by themselves, enable error checking (is there an important missing part, a contradiction, etc.
The use of independent documentation of prescriptions and distributions, as described in PDRO 2. 0, can completely describe these issues. Finally, empirically, previous experience in automated surveillance systems for potential inappropriate prescriptions  [35]  has shown that, taken alone, drug distribution information is limited in its discriminatory power to arbitrate if a treatment is appropriate or not. Clinical care (helped by algorithms or not) could benefit greatly from the added information provided by other health care data such as medical history, laboratory tests results, habitus, or quantified self. Being able to follow weight and diuretic use in heart failure or hypotension episodes would certainly enable a much more personalized approach to medication monitoring. The orthogonal set of ontologies in the OBO Foundry can contribute to and facilitate the advent of this vision.