dataesr/scientific-paragraphs-categorization huggingface dataset:
Funding: This study was funded by the  AP-HP Foundation  and its donators though the program " Alliance Tous Unis Contre le Virus ", by the  Clinical Research and Development Department , by the  French Ministry of Health  and by the foundation of the  University hospitals of Geneva, Geneva, Switzerland. The Reseau European de recherche en  Ventilation Arti cielle (REVA)  network received a 75,000 € research grant from  Air Liquide Healthcare. Sponsor: The sponsor was  Assistance Publique Hôpitaux de Paris  ( AP-HP ). Role of the funder: The funder had no role in the design and conduct of the study, collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
All tests demonstrated significant differences between controls and patients (p <. 01). Principal components analysis demonstrated that a one-factor solution best fits our dataset (64. 8% of the variance). High Cronbach alpha was found (. 85). The BACS composite scores were significantly correlated with the standard battery composite scores in patients (r =. 73, p <. 001) and healthy controls (r =. 78, p <. 001). Also, correlation analysis between the BACS subscores and the standard battery sub-scores showed significant results (p <. 05).
Sample size calculation In order to calculate the minimum sample size needed for our research, the Gpower 3. 1. 9. 2 software was used with a power of 80% (1-β = 0. 8) and an error α of 0. 05, an effect size of 0. 47 was calculated based on the original study done by Keefe et al. [14]. The BACS battery composite score was shown to be strongly related to a standard battery composite scores of both schizophrenia patients (r = 0. 76) and stable controls (r = 0. 90) in the study of Keefe et al. [14]. Taking into consideration a ratio of 2:1 in each group, the results showed that the minimal sample size needed was 164 (55 in the healthy control group and 109 in the patient group).
Data analysis The SPSS software version 25 was used to conduct the data analysis. The Shapiro Wilk test was used to verify the normality distribution of the BACS scale. The major dependent variable was normally distributed. A descriptive analysis was carried out where quantitative variables were expressed as means and standard deviations, while categorical variables were expressed as absolute frequencies and percentages. In order to evaluate categorical variables, the Chi-square and Fisher exact tests were used while to compare continuous variables between groups the Student T-test was used. The Arabic-BACS composite scores and the standard neurocognitive battery were determined by averaging all the subscales of each instrument and converting them to z-scores. Pearson correlations with the equivalent scales of the standard battery were used to assess the concurrent validity of the Arabic-BACS subscales.
Conclusion The psychometric properties of the Arabic version of the BACS were adequate, with high consistency, appropriate concurrent validity, and good overall discriminant validity. In daily psychiatry clinical practice and in research studies, we suggest that Arabic BACS is a reliable and useful tool for measuring cognitive performance in inpatients with schizophrenia. However, it is unclear if the results of this study can be applied to other Arabian communities that speak different dialects. In order for the BACS to fulfill all of the criteria of a good cognitive tool, normative data from a healthy population should be collected in the future.
Acknowledgments This work was supported by the  Psychiatric hospital of the Cross -Lebanon (PHC) , the  Psychiatric hospital center in Limoges -France  ( CH Esquirol ) and the  UMR INSERM 1094 Limoges -France. The authors would like to thank  Vanessa Mortada  and  Layale Hanna  who helped in participant recruitment and thank all the individuals (patients and employees) who participated in this study. Also, the authors express their deepest gratitude to  Professor Richard SE Keefe  for providing scientific feedback and granting permission to use the Arabic version of the BACS.
Study design and participants Patients were recruited across eight centres in the UK (supplementary material) to an open-label single-arm study. The study (TRANSFORM-UK, ClinicalTrials. gov number NCT02676947)  [19]  was approved by the local research ethics committee (Leicester Central 15/EM/0401). Patients on stable therapy aged 18-70 years with a diagnosis of group 1 PAH were enrolled: specifically, idiopathic or heritable PAH and PAH associated with CTD excluding SLE, RA and mixed CTD. Selected exclusion criteria included subjects on continuous intravenous (i. v. ) or subcutaneous prostacyclin infusions, active infection, peripheral blood platelets <100×10 9 cells•L -1 , neutrophil count <2×10 9 cells•L -1 , concomitant treatment with biologics, evidence of coronary artery and left heart disease, total lung capacity ⩽60% of predicted, forced expiratory volume in 1 s ⩽60% of predicted and a 6-min walk test (6MWT) distance <100 m (full inclusion/exclusion criteria can be found in the supplementary material).
Procedures Participants were given i. v. tocilizumab monthly (8 mg•kg -1 ; Roche Pharmaceuticals) for 6 months on day 1 and weeks 4, 8, 12, 16 and 20 (six doses). Patients attended monthly for infusions and safety data collection. Worsening of PAH was defined by the occurrence of three of the following: a decrease in the 6MWT distance of at least 15% from baseline; the need for additional treatment for PAH; and the worsening of symptoms of PAH, including at least one of a change from baseline to a higher World Health Organization (WHO) functional class and the appearance or worsening of signs of right heart failure unresponsive to oral diuretic therapy. Peripheral blood sampling was undertaken at trial baseline and end of study. Blood was collected for flow cytometric evaluation of leukocyte subsets, RNA sequencing (RNAseq) and serum mediators of inflammation (C-reactive protein (CRP), IL-1β, IL-6, IL-8 and tumour necrosis factor-α (TNF-α)) (supplementary figure  S1 ).
An additional Bayesian analysis, considered to be more informative of the treatment response of PVR to tocilizumab, was pre-specified using an expert-elicited prior. Any predictor effects on secondary outcomes are reported with confidence intervals. All analyses reported here were performed using the R-Project (version 3. 3. 3; www. r-project. org). Principal component (PC) analyses of the RNAseq dataset, t-test with Benjamini-Hochberg procedure/false discovery rate (FDR) and penalised regression model (LASSO) using all immunophenotyping variables (cytokines, flow cytometric subsets and RNAseq) as predictors and assessing predictability of response performed best on cross-validation were all undertaken using the R-Project, as were Kaplan-Meier plots.
1) (supplementary figure  S3 ). Overall, none of the immunophenotyping data correlated with treatment response or predicted responders from non-responders either individually or using integrative modelling. Consistent with a treatment effect on gene expression, in PC analysis there was modest evidence that pre-and post-treatment categorisation could be differentiated in two dimensions on the basis of the first two PCs (Peacock test, p=0. 033). In a penalised regression model (LASSO) using all immunophenotyping variables as predictors and assessing predictability of response, the model performed best on cross-validation when no variables were included in the predictive model (supplementary figure  S4 ). Therefore, there was no additional value added by analyses that utilised all of the inflammatory dataset, and no inflammatory marker predicted treatment response either individually or in combinatorial modelling.
Methods : A comprehensive search in PubMed, CENTRAL and EMBASE was conducted. Screening, data extraction and risk of bias were performed by two authors. The certainty of the evidence was assessed using GRADE. PROSPERO ID: CRD42020205143. Results: After abstract and full-text screening, 36 studies comprising 18,096 infants were included. Most CDSAs evaluated heart rate (HR)-based parameters. Two publications derived from one randomised-controlled trial assessing HR characteristics reported significant reduction in 30-day septicaemia-related mortality. Thirty-four non-randomised studies found promising yet inconclusive results. Conclusion: Heart rate-based parameters are reliable components of CDSAs for sepsis prediction, particularly in combination with additional vital signs and demographics.
| Literature search We performed a systematic search of PubMed, CENTRAL and EMBASE using a combination of free text and controlled vocabulary without language or time limitations current to 17 August 2020 and a hand search of Google Scholar current to 20 January 2021 (Table  S1 ). We included studies employing CDSAs evaluating noninvasive vital sign monitoring, meaning the data is automatically collected from monitoring tools and manually entered, to predict sepsis in neonates. Case reports and case series were excluded. We performed reference list checking of similar systematic reviews. All.
Wound-healing assay Cell monolayers grown on plastic supports were injured mechanically (3 wounds per well) as previously described  [24, 25]. Afterwards, cells were washed with their culture medium to remove detached cells and treated with either α-MT (1, 2. 5 or 5 mM) or MeOH which acted as vehicle control (respective equivalent volumes of MeOH alone). Photographs of the wounds were taken at two different positions on each wound using an inverted microscope with a X4 objective at t = 0 h and t = 6 h post-wounding. Images were analyzed with Image J software (https://imagej. nih. gov/ij/index. html) to measure areas of the wounds at t = 0 h and t = 6 h and mean wound closure (% of the area at t = 0 h) were calculated.
In vitro data All data are presented as mean ± SEM and the number of repeated experiments is indicated in the gure legends. GraphPad Prism version 7. 05 (GraphPad Software, San Diego, CA, USA) was used to analyze all data. Paired or unpaired t-tests were used to compare two groups. One-way ANOVA were used for comparison of more than two groups and followed by appropriate post-hoc tests as indicated in the gure's legends. Values of p<0. 05 were considered to be signi cant. In gures, statistical differences are indicated as p < 0. 05 (*), p < 0. 01 (**) and p < 0. 001 (***) or non-signi cant (NS).
SLC6A14 rs3788766 genotype affects SLC6A14 promoter activity The SLC6A14 SNP rs3788766, located within SLC6A14 promoter (Fig. 1a ), is likely to affect SLC6A14 mRNA expression. Quantitaive-trait Loci (QTL) expression data extracted from GTEx (https://www. gtexportal. org/home/) show that rs3788766 G is associated with a decrease of SLC6A14 transcript expression in different tissues (Fig. 1b ), including the pituitary (p-value = 3. 0x10 - 8 ) and the minor salivary gland (p-value = 1. 8x10 - 5 ). In the lung, a diminished but not statistically signi cant expression is observed (AA vs GG genotypes). It is worth mentioning that, for the GTEx project, the prefered location for the lung tissue collection is in the inferior segment of the left upper lobe, 1 cm below the pleural surface, avoiding any large arteries, veins, and bronchi.
Acknowledgements We would like to thank the patients, care providers and clinic coordinators at CF Centres, as well as the Principal Investigators in the several contributing French CF Centres:  M. ABELY ,  American Memorial Hospital, Reims / C. BAILLY PICCINI, CHU de Nice, Nice / C. BELLEGUIC, Hôpital Pontchaillou, Rennes / K. BESSACI, American Memorial Hospital, Reims / T. BIHOUEE, Hôpital Mère-Enfant, Nantes / Y. BILLON, Hôpital de Brabois, Vandoeuvre les Nancy / F. BRÉMONT, Hôpital des Enfants de Toulouse, Toulouse / J. BROUARD, Centre Hospitalier Universitaire de Caen, Caen / S. BUI, Hospitalier Universitaire Charles Nicolle ,  Rouen / L. MELY ,  Hôpital Renée Sabran, Giens / M. MITTAINE, Hôpital des Enfants de Toulouse, Toulouse / A. MUNCK, Hôpital Robert Debré, Paris / M. MURRIS-ESPIN, Hôpital Larrey, Toulouse / R.
Ethics statement The study has been approved by the Ethics Committee of the University Hospital of Saint-Etienne (No. IRBN 102 2019). The biological samples studied were received at the laboratory to carry out a schistosome search (presence of Schistosoma eggs in urine, on the 1st morning urination or on the 24-hour urine (French cost, 6. 75 euros) on the basis of a medical prescription. All data were analyzed anonymously. According to the French law on public health  [22] , these types of protocols are exempt from the requirement of formal informed consent.
Probes and selected primers As specified by Hamburger et al  [20] , we chose to amplify the highly repetitive Dra1 sequence of Sh (accession number DQ157698. 1), and to use the following primers (Sh-FW 5'-GATCT-CACCTATCAGACGAAAC-3 '; Sh-RV 5 0 -TCACAACGATACGATACGACCAAC-3 0 ). The probe was chosen as described in 2013 by Cnops et al  [17]  (Sh-sonde 5 0 -TGTTGGTGGAAGTGCCTGTTTCGCAA-3 ') and was marked 5 'FAM, BHQ1 in 3'. Based on the work of Wichmann et al  [21] , we have chosen to target the Sm1-7de S sequence. mansoni (GenBank accession number M61098), and to use the following primers (SRA1 5 0 -CCACGCTCTCTCGCAAATAATCT-3'; SRA2 5 0 -CAACCGTTCTATGAAAAAT CGTTGT-3 0 ), as well as the probe (SRP 5 0 -TCCGAAACCACTGGACGGTTTTGAT) marked 5'FAM, BHQ1 in 3'.
This will help stratify mRCC patients more accurately in future and improve the management of mRCC patients. Abstract: Precise management of kidney cancer requires the identification of prognostic factors. hPG 80 (circulating progastrin) is a tumor promoting peptide present in the blood of patients with various cancers, including renal cell carcinoma (RCC). In this study, we evaluated the prognostic value of plasma hPG 80 in 143 prospectively collected patients with metastatic RCC (mRCC). The prognostic impact of hPG 80 levels on overall survival (OS) in mRCC patients after controlling for hPG 80 levels in non-cancer age matched controls was determined and compared to the International Metastatic Database Consortium (IMDC) risk model (good, intermediate, poor). ROC curves were used to evaluate the diagnostic accuracy of hPG 80 using the area under the curve (AUC).
Recent clinical trials have used the International Metastatic Database Consortium (IMDC) model for prognostication  [11] [12] [13]. This model is based on six clinical variables as risk factors for short survival (time from diagnosis to initiation of therapy of less than 1 year, Karnofsky performance status of less than 80%, serum hemoglobin below the lower limit of normal and corrected calcium, neutrophil count, and platelet count greater than the upper limit of normal) and classify patients into good-(0 risk factor), intermediate-(1 or 2 risk factors) and poor-risk (≥3 risk factors) groups  [14]. As a result, targeted therapeutics in metastatic RCC uses non-molecular based clinical prognostic variables for initiating novel drug interventions and combinations highlighting the need for enhancing prognostic markers in metastatic RCC  [15, 16].
Non-Cancer Age and Non Age Matched Control Cohorts A young-aged cohort of plasma samples (18-25 years old) was obtained from nonfasting 137 healthy blood donors, from the French blood agency (Etablissement Français du Sang). This cohort was assumed to be at very low risk of cancer in order to maximize the likelihood of the control group being cancer-free  [31]. A second, over 50 years old cohort of plasma samples (range 50-80 year old; median value 55 year old) was collected from fasting 252 healthy subjects, from the interim analysis from the PROCODE study (NCT03775473, https://clinicaltrials. gov/ct2/show/NCT03775473).
Characteristics of the Study Population The demographic characteristics of the mRCC patients and control cohorts (143 mRCC patients to assess the diagnostic and prognostic values of hPG 80 ) are shown in Table  1. A flowchart describing the selection of the patients for the study analysis is shown in Figure  1. The median patient age is 63 years and 74. 8% were male (Table  1 ). The majority of the patients had metastatic clear cell renal carcinoma (77%). The median level in the mRCC cohort of plasma hPG 80 is 7. 23 pM (Figure  2A  and Table  2 ). The diagnostic accuracy of hPG 80 were evaluated in mRCC patients. While the mRCC cohort of 143 patients was divided into IMDC prognostic categories to evaluate hPG 80 as a prognostic factor in mRCC stage, we performed survival analysis using OS as the clinical outcome only in patients who had survival data available.
Abstract: Background & Aims: There is limited data regarding the role for systemic treatment in patients with Hepatocellular Carcinoma with Child-Pugh B cirrhosis. Methods: This was a multicentric prospective non-comparative randomized trial. Patients were randomized to receive sorafenib (Arm A), pravastatin (Arm B), sorafenib-pravastatin (Arm C) combination, or best supportive care (Arm D). Primary endpoint was Time To Progression (TTP), secondary endpoints included safety and Overall Survival (OS). Results: 160 patients were randomized and 157 patients included in the final analysis. 86% of patients were BCLC C and 55% had macrovascular invasion. The safety profiles of the drugs were as expected. Median TTP was 3. 5, 2. 8, 2. 0 and 2. 2 months in arms A, B, C and D, respectively, but analysis was limited by the number of patients deceased without radiological progression (59%).
Study design and patients The PRODIGE 21 trial was designed as a multicentre, open-label, randomised phase 2 trial. The study was conducted in 35 centres in France, within the PRODIGE (FFCD/UCGI/GERCOR) intergroup. The study was referenced in clinicaltrials. gov (NCT01357486). The trial was approved by the Ethics Committee 'Comité de protection des personnes Sud Ouest et Outre Mer III' on the 23/02/2020. The protocol is provided as supplementary material. The main inclusion criteria were: age older than 18 years, HCC diagnosed by biopsy or by radiological criteria according to AASLD guidelines, patient non eligible to curative or locoregional therapy, Child-Pugh Score B7 to B9, Performance Status 0 to 2, stage B or C of BCLC classification, adequate biological parameters (Hb ≥ 8 g/dl, Platelets ≥ 50 G/L, creatinine < 2 times the upper limit of normal, Neutrophils ≥ 1000/mm 3 ).
Acknowledgments: We thank the FFCD operational team (statisticians, data managers and CRAs):  Karine Le Malicot ,  Fadil Masskourri ,  Caroline Choine ,  Florence Guiliani ,  Nouredine Lasmi ,  Guillaume Arnould ,  Nathan Guiet ,  Morgane Maury-Nègre ,  Hicham Fattouh ,  Nicolas Le Provost ,  Jérémie Bez , and  Cécile Girault. We also thank research teams at each participating center.
Funding: The study was funded by the '' Programme Hospitalier de Recherche Clinique" (PHRC)  in 2010 ( Institut National du Cancer [INCa ], grant  PHRC10_04-02 ). Pravastatin was supplied by  Sanofi, France. Funding: The study was funded by the '' Programme Hospitalier de Recherche Clinique" (PHRC)  in 2010 ( Institut National du Cancer [INCa ], grant  PHRC10_04-02 ). Pravastatin was supplied by  Sanofi, France.
Usual quality measures and normalization for the Affymetrix GeneChip (3 0 /5 0 ratios and trimmed mean normalization) were used. Raw data were imported into GeneSpring GX10 software (Agilent Technologies, Santa Clara, CA) and subjected to Robust Multichip Average (RMA) normalization. Differentially expressed genes were identified using the unpaired t test (P <. 05 with Benjamini-Hochberg false discovery rate (FDR) multiple testing correction). Given the strict statistical parameters, the fold-change cutoff was set to at least 50% change in mRNA abundance. MicroRNA profiling was performed by subjecting total RNA (500 ng) to high-capacity quantitative polymerase chain reaction (q-PCR) using a megaplex reverse-transcription primer set for $754 human microRNAs (Sanger miRBase database v. 14), analyzed by Applied Biosystems TaqMan Low Density Arrays (TLDA, TaqMan Array Human MicroRNA Panel A v2.
1 and B v3. 0) on the ABI 7900HT Sequence Detection System (Applied Biosystems, Waltham, MA), as described previously. 17 The reactions were incubated in a 384-well plate at 50 C for 2 minutes and 95 C for 10 minutes followed by 40 cycles of 95 C for 15 seconds and at 60 C for 1 minute and were then held for 10 minutes at 72 C. The data were collected and processed using GeneSpring GX10 software (Agilent Technologies, Santa Clara, CA). The miRNA abundance was determined by the 2 ÀCt value formula which was followed by quantile normalization of all data. A union of unpaired t test (corrected P value <. 05) and Pavlidis Template Matching (P <. 01) yielded the differentially abundant miRNAs. Multiple-testing correction for t test was performed using Benjamini-Hochberg FDR. The fold-change cutoff was set at 1.
| Pathway analysis and bioinformatics Gene Spring GX10 software (Agilent Technologies, Santa Clara, CA) was used for data management, analysis and visualization. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used for annotation of specific genes and pathways. Ingenuity Pathway Analysis (IPA, QIAGEN Redwood City, Redwood CityCA, www. qiagen. com/ingenuity) based on the TargetScan high-confidence predictions and experimental validation was used to identify the mRNA targets of miRNAs (Table  S5 ). The TargetScan algorithm in IPA searches for the presence of conserved 8-mer and 7-mer sites matching the seed region of a given microRNA, while the experimentally observed miRNA-mRNA relationships are based on the combined TarBase and miRecords database contents as well as the Ingenuity Knowledge Base containing information from published literature manually curated by the Ingenuity expert team.
miRconnX was used to identify the top-ranking microRNA-mRNA relationships (http://mirconnx. csb. pitt. edu). NIH DAVID (Database for Annotation, Visualization and Integrated Discovery)  18  and gene set enrichment analysis (GSEA), collections C2 and C5  19  were used for pathway analysis. Disease Association Protein-Protein Link Evaluator (DAPPLE) was used to determine and visualize significant physical connectivity among proteins encoded for by miRNA target genes, based on protein-protein interactions reported in public domain. 20 Additional data visualization was done using CIRCOS version 0. 63  21  while MutSpec was used for mutation analysis  22  and non-negative matrix factorization method for mutational signatures analysis using an R package. 23, 24 Statistical analysis of the tissue microarray (TMA) data were performed using GraphPad Prism version 7.
| RNA sequencing and data processing RNA sequencing (RNA-seq) libraries were sequenced deeply (for number of generated reads, see Table  S6 ), with either single-end for UTUC_20 or pair-end for UTUC_03 and UTUC_18 (at 51 bp read length) using the Illumina HiSeq 2000 sequencer. All reads in FASTQ format were generated using Illumina CAS-AVA version 1. 8 by trimming of 2 bp from both the 5 0 end and 3 0 end and yielding 47 bp sequence reads. All passed filtered and qualified reads were aligned to human genome version GRCh37 (hg19) using eland software of CASAVA version 1. 8 with default settings. Binary alignment map (BAM) files and single base substitution (SBS) calls were generated by variant detection and counting software of CAS-AVA version 1. 8. The bulk sequencing metrics for the RNA-seq are listed in the Table  S6.
After removing duplicate reads, postprocessing steps have been applied to the raw SBS calls in order to obtain SBSs with confidence. SBSs with coverage less than 10Â were removed. SBSs with <10% reads supporting for variant or >90% reads supporting for reference nucleotide per site were also filtered out. Last, we filtered out all SBSs that match the common database of single nucleotide polymorphisms (dbSNP) version 137 with minor allele frequency (MAF) ≥1%. S6.