dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We are grateful to  Dr Olivier Schwartz  (from  Pasteur Institute, Paris, France ) for the gift of the hACE2-mScarlet1 expression plasmid, and to  Ms Virginie Sutter  (Master student from  Strasbourg University, France ) for helping MG in VLP production, immuno-spotting and western blots. Confocal and TIRF microscopy were performed at the  Montpellier Imaging Center for Microscopy (MRI)  and the correlative fluorescence  Atomic Force Microscopy at CEMIPAI CNRS Montpellier, France , which was funded by the  REDSAIM program  ( Montpellier University ).
Data availability The datasets of the humanized CoV-2 sequences generated during the current study are available in the Gen-Bank repository with the ID number 2570843. The GenBank accession numbers for humanized SARS-CoV-2 protein nucleotide sequences used in this study are: BankIt2607198 hE(SARS-CoV2) OP095355, BankIt2607198 hM(SARS-CoV-2) OP095356, BankIt2607198 hN(SARS-CoV2) OP095358, BankIt2607198 hS(SARS-CoV2) OP095359.
During many years, chemo-immunotherapy fludarabine-cyclophosphamiderituximab (FCR) was the gold standard for first line treatment of medically fit patients with symptomatic B-chronic lymphocytic leukemia (CLL). Over the last decade, targeted biotherapies have revolutionized the treatment of B-CLL patients and almost entirely supplanted FCR. However, no biomarker still exists to predict the complete remission (CR) with undetectable minimal residual disease (uMRD) in bone marrow (BM), which remains the best predictive factor for survival. MicroRNAs represent a class of molecular biomarkers which expression is altered in B-CLL. Our study aimed at identifying before treatment blood miRNAs that predict treatment outcome in previously untreated B-CLL patients (NCT 01370772, https://clinicaltrials.
gov/ct2/show/NCT01370772). Using hierarchical clustering of miRNA expression profiles discriminating 8 patients who achieved CR with BM uMRD from 8 patients who did not achieve CR and displayed detectable BM MRD, we identified 25 miRNAs differentially expressed before treatment. The expression of 11 miRNAs was further validated on a larger cohort (n=123). Based on the dosage of 5 miRNAs at diagnosis, a decision tree was constructed to predict treatment outcome. We identified 6 groups of patients with a distinct probability of being CR with BM uMRD to FCR treatment, ranging from 72% (miR-125b, miR-15b and miR-181c high) to 4% (miR-125b and miR-193b low). None of the patients displaying high expression levels of miR-125b, miR-15b and miR-181c relapsed during study follow-up. In contrast, patients with low miR-15b.
Gene expression profiling Gene expression profiles (GEP) were obtained using RNA sequencing (RNA-seq). The RNA-seq library preparation was completed with 150 ng of input RNA using the Illumina TrueSeq Stranded mRNA Library Prep Kit. Pairedend RNA-seq was performed with an Illumina NextSeq sequencing instrument (Helixio, Clermont-Ferrand, France). RNA-seq read pairs were mapped to the reference human GRCh37 genome using the STAR aligner  (26). All of the statistical analyses were performed with the R statistics software (version 3. 2. 3; available from https://www. r-project. org) and with R packages developed by the BioConductor project (available from https://www. bioconductor. org/) (27). The expression level of each gene was summarized and normalized using the DESeq2 R/Bioconductor package  (28).
Statistical analyses Distributions of data were tested with the Shapiro-Wilk test. X 2 or Fisher test was used for categorical data. For numerical data, comparisons of medians were performed using Student T or Mann-Whitney test. Spearman's correlation test was used to assess the association between two numerical data. Multivariate analysis was performed using logistic regression by backward selection using Student T test (p<0. 05 as significant model). To establish the decisional tree, the receiver operating characteristics (ROC) of miRNA was constructed to determine the threshold able to predict complete response with blood and BM uMRD associated with the best sensitivity and specificity according to the Youden index  (29). A probability p<0. 05 was considered statistically significant. Progression Free Survival (PFS) was measured from the date of the initiation of the treatment to the date of relapse and/or progression as a result of B-CLL or acute treatment toxicity.
Moreover, the expression of miR-125b and miR-181c in B-CLL purified B cells is downregulated in comparison with healthy donors  (46, 47) , which is consistent with the negative regulation of the TCL1 oncogene by miR-181 B-CLL B C A FIGURE 4 Gene expression profiling of three prognostic groups defined by the five-miRNA decision tree signature. Clustergram of the 1373 differentially expressed genes between HHH group and HLH and LL groups (FDR < 0. 05). Signals are displayed from low (deep blue) to high (deep red) expression (A). Molecular signatures enriched in HHH group (B) or HLH and LL groups (C) using GSEA Database (all curated gene sets), and relevant pathways are presented (FDR q value ≤ 0. 05). (48) and of several transcripts involved in cell metabolism by miR-125b  (47) , and with the observation that miR-125b up-regulation is associated with aggressive leukemia in human and mice  (49, 50).
Funding The French Innovative Leukemia Organization (FILO) group funded the clinical trial that served for this experimental work. FILO was the sponsor and was involved in managing the clinical study, statistical analyses, and data review. Roche provided rituximab (MabThera) but had no role in study design or data collection, analysis, or interpretation. The authors declare that experimental work presented in this article received fundings from a public grant overseen by the French National Research Agency (ANR) ANR-18-CE15-0010-01 and as part of the "Investissements d'Avenir" program (reference Labex MAbImprove: ANR-10-LABX-53-01), INSERM (Institut National de la Santéet Recherche Medicale), the University of Montpellier, the Institut Universitaire de France, the "Groupement Interreǵional de Recherche Clinique et d'Innovation Sud-Ouest Outre-Mer Hospitalier" (APIK 2017) and the "Canceŕopole Grand-Sud-Ouest".
Study Design, Sites and Period This study is part of the ARTHR-IS project (registered at clinicaltrials. gov: NCT03826108) and was designed to evaluate the incidence, risk factors and predictors of SA-PJI TF after primary hip and knee arthroplasty. A retrospective cohort study was conducted in 19 European hospitals to identify patients older than 18 years who received a primary arthroplasty between 1 January 2014 and 31 December 2016 and developed post-surgical knee or hip PJI due to S. aureus within the first year after the procedure. The participating sites, located in Spain, Italy, France, Germany, UK and the Netherlands, were selected using the CLIN-NET network (https://www. combacte. com/about/clinnet/), based on their research experience and data collection capability. The STROBE recommendations were followed for the reporting of the study (Supplementary Table  S1 ).
Participants Patients with post-surgical hip or knee PJI due to S. aureus diagnosed within the first year after primary arthroplasty were included. The criteria used to define SA-PJI were as follows: presence of at least one sign or symptom of PJI, including joint pain and/or swelling, or a sinus tract communicating with the prosthesis; and the isolation of S. aureus from (a) C one joint aspirate culture, (b) C two periprosthetic tissue samples and (c) blood cultures with no other obvious source of infection. The patients were identified by reviewing medical records from microbiological laboratory databases, local PJI surveillance databases and discharge reports.
Patient Characteristics and Treatment Failure Rates A total of 130 cases of SA-PJI were detected, and 128 were included (relevant follow-up data were missing for the other two). The median number of cases per hospital was 7 (interquartile range [IQR] 5-9). The median age of patients was 73 years (IQR 59-81 years); 65 (50. 8%) were males; 77 (60. 2%) had hip arthroplasty (50 total and 27 partial) and 51 (39. 8%) knee arthroplasty (47 total and 4 partial). Patient characteristics are presented in Table  1. Infection-related symptoms started a median of 24 (IQR 15-36) days after the primary arthroplasty (Supplementary Fig. S1 ), while the first surgical procedure for treatment of infection was performed a median of 4 days (IQR 1-11) after symptom onset. Bacteraemia occurred in 25 cases (19. 5%).
Data Availability. The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. Open Access. This article is licensed under a Creative Commons Attribution-NonCommercial 4. 0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
ACKNOWLEDGEMENTS We thank all study participants for their collaboration, without which this manuscript would have been impossible. Other members of the ARTHR-IS group are:  Nienke Cuperus and Giuseppe Manfre(Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht , the Netherlands) collaborated in the selection process of the participating centers. Ana Isabel Suarez-Barrenechea  and  Alvaro Pascual-Hernandez  ( Department of microbiology, Hospital Universitario Virgen Macarena ),  Alba Rivera  ( Deparment of Microbiology, Hospital de la Santa Creu i Sant Pau ),  Xavier Crusi  and  Marcos Jordan  ( Department of traumatology, Hospital de la Santa Creu i Sant Pau ),  NicoloRossi  ( Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy ),  Tessa van de Kerkhof (Department of Orthopaedic Surgery & Trauma, Maxima MC, Eindhoven , the  Netherlands ;  Department of Orthopaedic Surgery & Trauma, Catharina Hospital, Eindhoven , the Netherlands),  Juan P.
Funding. This work was supported by the  Innovative Medicines Initiative Joint Undertaking  (grant agreement No. 115523 ),  COM-BACTE-NET consortium  ( European Union   FP7/ 2007-2013  and  GlaxoSmithKline Biologicals SA , as EFPIA partner). R. E, L. S, O. M, R. E-S, J. L-T, J. P, J. R-B and MD. del T are members of the  Spanish Network for Research in Infectious Diseases (REIPI) , supported by  Plan Nacional de  I ?D ?i 2013-2016 and  Instituto de Salud Carlos III, Subdireccion General de Redes y Centros de Investigacion Cooperativa, Ministerio de Ciencia, Innovacion y Universidades ,  Spanish Network for Research in Infectious Diseases  ( REIPI RD16/0016/0001 ;  0002 ;  0005; 0009; 0011; 0015 ), co-financed by  European Development Regional Fund  ''A way to achieve Europe'', Operative Program Intelligence Growth 2014-2020.
Study design and ethics This retrospective single-center cohort study was performed in the Ophthalmology Department of Metz-Thionville Regional Hospital Center, Grand Est, France and was approved by the Ethics Committee of the French Society of Ophthalmology (IRB 00008855). All procedures conformed to the principles of the Declaration of Helsinki. All patients were informed before surgery that their surgery-related data might be used for research purposes. All consented to this possibility. The consent procedure was conducted in accordance with the reference methodology MR-004 of the National Commission for Information Technology and Liberties of France (No. 588909 v1).
Preoperative, perioperative, and postoperative variables The following data were obtained from the prospectively maintained clinical database: patient age and sex, donor age, graft ECD before and 6 and 12 months after surgery, BSCVA before and 6 and 12 months after surgery, preoperative mean anterior keratometry, triple DMEK, difficult surgery, surgical time, and number of rebubbling sessions. DMEK surgery was labelled as "difficult" if any part of it was not standard. Examples include difficult graft dissection, graft defects, abnormal graft elasticity, difficulties unfolding the scroll in the anterior chamber, or any condition hindering the normal course of surgery or requiring more maneuvers than usual. Surgical time was defined as the time taken from starting graft preparation to placing the suture.
Study limitations The present study has several limitations. First, its retrospective design may lend itself to selection and information bias. However, the data were recorded prospectively. Second, it is a monocentric study. However, all surgeries were conducted by one experienced surgeon, which may limit confounding due to surgeon differences. Third, postoperative ECD was measured at the cornea center with specular microscopy: a recent study found that such measurements may not accurately reflect postoperative ECD throughout the entire graft  [82]. This could also partly explain the inconsistencies between studies in terms of the relationships between postoperative ECD and pre/perioperative variables. Fourth, since all patients underwent surgery for FECD, our results cannot be extrapolated to DMEK for other endothelial disorders.
Data collection After agreeing to participate and completing a consent form, the research team conducted IDIs in Thai at the respective health facility. IDIs lasted 30-90 min, had no other people present, were audio-recorded and participants received 500 Baht (US$16) compensation for their time. General conversation was initiated prior going to main interview questions to build rapport. Data were collected from July to October 2020. All audio recordings were transcribed verbatim in Thai, complemented with field notes. Deidentified transcripts were stored on a password protected computer. There was no further contact with the research participants after the IDI. The interview guides were developed based on the implementation challenges identified in the Cochrane qualitative review  4  and covered a range of topics including: (1) values and needs around the childbirth period, (2) prenatal education, (3) preferences and decision-making processes regarding mode of birth and (4) labour companionship (online supplemental appendix 1: interview guide).
Interview guides were piloted and refined prior to data collection. This analysis focuses on the labour companionship module. In addition to IDIs, a readiness assessment was conducted to describe and assess the service delivery context ahead of the intervention implementation and was carried out concurrently with the IDIs (online supplemental appendix 2: readiness assessment). The readiness assessment provides a systematic approach to assessing readiness to engage in the implementation, in order to inform and tailor the interventions in a way best suitable to the local context. 10 Readiness assessments were conducted by members of the QUALI-DEC research team who were professors of nursing, but not employed by the study hospitals. During data collection, the researchers Open access used a semistructured form to observe the service delivery context in each facility setting related to possibility or barriers for companionship implementation such as the sign for visiting information, and the physical environment in the labour room and postpartum room.
Reflexivity The QUALI-DEC research team consists of Thai and international social scientists, nurses, doctors and epidemiologists with maternal health expertise. The research team believed that labour companionship is beneficial for women and families and may help reduce caesarean section rates. The research team was aware of their assumptions and mindful through the study process to mitigate any potentially negative biases that could influence participant responses or interpretations of responses. Six members of research team conducted the IDIs, all were female nursing professors with extensive qualitative experience, no prior relationship with any participants and did not work at the study sites. Prior to starting data collection, the research team underwent a 3-day training on caesarean section globally and in Thailand, QUALI-DEC project and data collection and management.
Data analysis Thematic analysis was performed by hand according to the following steps: organising the data; generating categories, themes, patterns; testing emergent hypothesis; searching for alternative explanations. 12 Four members of the research team were involved in the data analysis. First, the researchers repeatedly read the interview transcripts to develop initial codes of the data. Second, the researchers conducted a systematic identification of themes from the codes such as support, being a representative and shorten labour. Third, from the themes and codes, researchers identify emerging patterns from the data, such as benefits of having labour companion. Last, the researchers review the coded data extracts for each theme to consider whether they appear to form a coherent pattern.
In this stage, the research team considered how the different themes were similar and different across different participant groups (eg, women and healthcare providers) and explored hypothesis for why these similarities and differences may exist. If we found inadequacies in the initial coding and themes, we revisited the themes again and iterated on necessary changes when needed. For trustworthiness, during data analysis, the findings were discussed among the research team and emergent findings were presented to a representative obstetrician (QUALI-DEC opinion leader) from the study settings. Key themes emerging from the IDIs were combined with data from the readiness assessment to identify and prioritise barriers and to develop potential implications for implementation. Data analysis was conducted in Thai in order to retain the original meaning, and excerpts from the interview transcripts in this article were translated by a bilingual Thai-English translator who is a member of the research team.
We collected the data during the COVID-19 pandemic, which may have introduced additional barriers to implementation around people's presence on the labour wards (during the data collection period July to October 2020, there were typically less than 10 COVID-19 cases per day in Thailand). We note that WHO COVID-19 clinical management guidance recommends that during the pandemic, all women should have access to woman-centred, respectful care, including a companion of their choice; this includes women with suspected, probably or confirmed COVID-19. 20 Key strengths of our study include triangulation of results from qualitative research and the facility readiness assessment and mapping of key factors affecting implementation to the COM-B model to guide decision-making during QUALI-DEC intervention design and support a systematic, targeted and theory-based development of implementation strategies.
Acknowledgements We thank the woman, potential companions and health workers for their valuable time and are grateful to the social scientist team for their hard work in data collection:  Nilubon Rujiraprasert ,  Sasitara Nuampa ,  Natthapat Buaboon ,  Waraluk Kittiwatanapaisan  and  Dasavanh Bounmany. We are indebted to  Miss Nampet Jampathong  for her professionalism as a project coordinator during the data collection process and her assistance in data transcription. Contributors SR, AR, PL, CH, AD, MdL, APB and MAB designed the study. SR, AR and PL led data collection with support from CH, AD, MdL, APB and MAB. SR led data analysis with support from  RIZ  and  MAB. SR and MAB drafted the manuscript, and all authors reviewed the manuscript. MAB was responsible for the overall content and acted as guarantor.
Funding This study is part of the  QUALI-DEC -project which is cofunded by the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  847567  and by  UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP) , a cosponsored programme executed by the  World Health Organization (WHO) in the Department of Sexual and Reproductive Health and Research (SRH). MAB is supported by an  Australian Research Council   Discovery Early Career Researcher Award  ( DE200100264 ) and a  Dame Kate Campbell Fellowship  ( University of Melbourne Faculty of Medicine, Dentistry , and  Health Sciences ).
| Study setting and population After the first mailshot to NHs in the region of West Occitania, a total of 46 NHs volunteered to participate in the study (13%) including a total of 2819 residents. An onsite visit was then organised to meet the coordinating physician and explain the project. The NHs enrolled in the study were located in different departments of West Occitania: Ariège: 3 (14%), Aveyron: 3 (6%), Haute-Garonne: 22 (18%), Gers: 1 (4%), Hautes-Pyrénées: 5 (17%), Lot: 4 (14%), Tarn: 3 (5%) and Tarn et Garonne: 5 (22%). We conducted a retrospective study on the 2819 residents of the 46 NHs participating in the PAAPI programme between 1 January 2017 and 31 December 2018. The coordinating physician in each NH then forwarded anonymous data to us regarding the residents' medical data and drug prescriptions with the consent of their respective general physician (GP).
| Data collection The following sociodemographic and clinical data were collected for each resident: age, gender, medical history and comorbidities and iso-resource group (IRG) and drug prescriptions. The IRG measures an older individual's degree of autonomy on a scale of 1 to 6: IRG 1 corresponds to total dependency, long-term prescriptions and their dosages. Drug prescriptions were reviewed on three occasions in the Pharmacovigilance Centre: by the PAAPI assistant who recorded anonymous data in an Excel database and then transmitted the data to a resident pharmacist for the first analysis and MR and finally to a senior pharmacologist for final MR and review of the previous analysis. For each PIM identified, a comment was added to emphasise the potential risk labelled as 'Risk identification' along with a suggestion to improve the drug prescription labelled as 'Recommendation'.
| Identification of DRP Following our initial request and the collection of data relating to 46 NHs, a total of 17 850 prescription lines were registered for 2819 residents. As explained in Section 2, DRP could not be identified for 359 lines of prescription, concerning amiodarone (n = 119) and PPI (n = 240). A DRP was identified for 4524 prescription lines (25%) classed as follows: wrong drug (inappropriate drug) in 45% (n = 2042), unnecessary drug prescription in 31% (n = 1416), ADR in 13% (n = 595), excessively high dose in 8% (n = 367) and the need for additional therapy in 2% (n = 104) of prescriptions. Each category of DRP could lead to different types of recommendation. Recommendations were as follows: drug withdrawal in 39% of cases (n = 1777), drug change in 24% (n = 1078), reduced dose in 18% (n = 832), warning in 16% (n = 749) and drug initiation in 2% of cases (n = 88).