dataesr/scientific-paragraphs-categorization huggingface dataset:
Methods for additional analyses (eg, subgroup analyses) We plan to conduct a subgroup analysis on the severity of ARDS: PaO 2 /FiO 2 ratio below 150 mm Hg, PaO 2 /FiO 2 ratio above 150 mm Hg (or equivalent SpO 2 /FiO 2 ratio). We will test if the treatment effects differ with severity of ARDS by putting their main effect and interaction terms in the logistic regression. Adjusted analyses will be nested in the intervention group to evaluate the effect of duration of PP on the risk of intubation or death, as well as the analysis of prognostic factors associated with PP such as comorbidities, age, body mass index and so on. Methods in analysis to handle protocol non-adherence and any statistical methods to handle missing data We do not expect any patient to be lost to follow-up. The only missing data could relate to patients who withdraw their consent.
Open access Data management, transfer and deposition The details of data management procedures can be found in the original protocols (online supplemental files). Each investigator is responsible for the confidentiality of the data collected during his or her trial. The data sets will use pseudonymised data. Interim analyses will be performed by centralising the aggregated data of the primary endpoint per trial. The confidentiality of data will be preserved when the coded, depersonalised data will be transmitted and stored at the location of the statistician in charge of the final analysis.
Acknowledgements The trial is supported by the following international clinical research networks: Réseau europpéen de recherche en ventilation artificielle (REVA: www. reseau-reva. org) and Clinical research in intensive care and sepsis -Trial group for global evaluation and research in sepsis (CRICS-TriggerSEP: www. triggersep. org www. triggersep. org endorsed by the French clinical research infrastructure network: www. fcrin. org). Contributors BM, IP, OR, YP, JoL, SM, DC,  J-PF , SE and JiL conceived the trials. ET provided methodological expertise in the meta-trial design and prepared the first draft of this study protocol. BM, IP, OR, YP, JoL, SM, DC,  J-PF , SE and JiL contributed to the rewriting; all of the authors approved the final manuscript and reviewed it for important intellectual content.
Materials and methods Radiological images and demographic data were acquired for 142 aneurysms treated with FDS. Vascular resistance values were estimated from patient-specific anatomical data. Correlation analysis was used to identify correspondence between anatomical data and clinical outcome. Computational Fluid Dynamics was performed on a typical patient-specific model to evaluate FDS-specific influence on flow. Relevant haemodynamic variables along the bifurcating vessels were quantitatively analysed and validated with in vitro data obtained using power Doppler ultrasound.
Blood flow distribution throughout the cardiovascular system is highly influenced by R PER , which can be described as the viscous impediment to blood flow in a vessel as described by the Hagen-Poiseuille relationship that links pressure to flow  [16]. This relationship shows that resistance, or impediment to flow, increases with higher values of blood viscosity (hematocrit), vessel length and smaller vessel radii. The aim of this study is to perform a quantitative estimation of the factors affecting hemodynamics of FDS-jailed arteries, with a focus on the quantification of the impediment to flow from the FDS (R FDS ) in relation to the overall artery resistance (R TOT ) to flow, and for a larger cohort of datasets. The study also includes an experimental validation of our theoretical and numerical observations using power doppler-ultrasound (PD-US).
DISCUSSION The aim of the study was to investigate, for a cohort of 142 aneurysm datasets, the role of resistance to flow in the context of flow changes induced by FDS treatment that may relate to vessel narrowing/occlusion in a subacute phase. The effect of FDS on flow distribution at symmetric and asymmetric bifurcations was studied in the past, but this was contrasted to a small number of cases  (25)  which was not enough to explain the changes in vessel diameter  [13]. The statistical analysis results of this study showed significant correlations between flow resistance attributed to the presence of the FDS and vessel narrowing at follow-up. Analysis of R FDS were considered as values relative to the overall resistance to flow, R TOT , encountered by the viscous flow of blood through the jailed vessel and distal R PER.
For these calculations lumen caliber data were derived from imaging data of 142 datasets. It is well established that flow distribution and WSS are heavily dominated by vessel anatomy and the viscous nature of blood as smaller vessels, such as the OphthA, will oppose higher resistance to flow than relatively larger vessels like MCA branches. So the presence of a FDS will not affect the resistance in the OphthA because it is already high. The distribution of R FDS to flow as a percentage of R TOT between cases showing jailed vessel patency and narrowing/occlusion was much higher (2 to 6 fold) in this latter group. In the not narrowing cases, a series of outliers ranging from 4. 5 to 6. 5 fold the R FDS % can be observed. This can be explained by the fact that the data have been collected from follow up images.
Bifurcation aneurysms from middle cerebral artery (MCA), basilar artery with hypoplasia of posterior communicating artery and anterior communicating artery aneurysms with agenesis of contra-lateral anterior cerebral artery and treated with FDS between December 2010 and December 2015 were included (25 aneurysms from 25 patients). OphthA aneurysms data were collected from December 2014 to December 2017 (117 aneurysms from 117 patients). All patients included had 3Dangiography prior to FDS positioning and at 3-6 months follow-up. Images were acquired using a biplane X-ray system (General Electric Healthcare Innova IGS 650, Marlbourough, Massachusetts, USA) and were obtained during a 240 degrees rotation for a duration of 5 seconds and for a total of 244 projections. This resulted in a 3D volume dataset of 512x512x512 voxels covering a field of view of 116 mm.
Generation of plants expressing PROMOTER:GUS-VENUS fusions The transcription promoter regions of NtRbcS-T1 (1993 pb; GenBank accession: NtCPS2 (1448 bp; GenBank accession: HE588139. 1) were defined as previously  (Wang et al. 2002; Ennajdaoui et al. 2010; Choi et al. 2012; Sallaud et al. 2012). Promoter regions were amplified by PCR using as a template genomic DNA prepared from N. tabacum or N. sylvestris leaves and the primers listed in Supplemental Table  S2. The amplified fragments were inserted in the pGEM®-T Easy Vector (Promega, Madison, Wisconsin, USA; www. promega. com) and sequenced. Cloned fragments were cleaved using HindIII (or NotI for pNtMALD1 and pNtRbcS-T1) and KpnI, prior to their insertion in a pAUX3131 construct  (Navarre et al. 2011) , upstream of the GUS-VENUS coding sequence.
MG493459. 1) and NtMALD1 (1974 pb; GenBank accession: MG493458. 1) were identified blasting the EST corresponding to NtRbcS-T1 (GenBank accession: DV157962) and NtMALD1 (GenBank accession: FS387666) coding sequences to the genome of N. tabacum TN90 in the Solgenomics database (http://solgenomics. net). The promoter regions of NsCBTS2α (985 bp; GenBank accession: HM241151. 1), NtLTP1 (849 bp; GenBank accession: AB625593. 1), NtCYP71D16 (1852 pb; GenBank accession: AF166332. 1), and.
Acknowledgments The authors are grateful to  Joseph Nader  for his technical contribution. This work was supported by the  Belgian Fund for Scientific Research  (Grant ID:  MIS -F. 4522. 17 ), the  Interuniversity Poles of Attraction Program (Belgian State, Scientific, Technical and Cultural Services) , and an  EU Marie Skłodowska-Curie  fellowship (Project  ID :  658932 ) to MP.
05% and Tween 20, a 1 hour incubation with peroxydase-conjugated goat anti-rabbit or anti-mouse IgG (1:5000; Dako) was performed. After three additional washes, immuno-complexes were revealed using the Enhanced ChemiLuminescence (ECL) detection system (GE Healthcare). Protein bands were quantified by densitometry using ImageScanner III and ImageQuant TL software (GE Healthcare).
Statistical analysis Statistical analysis was performed using GraphPad Prism 5. 0 (GraphPad software Inc, San Diego, CA, USA). To compare two groups, t-test or Mann-Whitney test was used, as appropriate. If variances significantly differed between groups (Bartlett's test) or if normality test was not passed (Kolmogorov-Smirnov test), Mann-Whitney test was performed. To compare three groups or conditions, statistical analysis consisted in two-way ANOVA (WAS x Treatment (TT)) followed by Bonferroni post-tests. For all tests, p<0. 05 was considered significant.
However, the number of output feces was lower in HFD-WAS than in SD-WAS. Ob/ob mice showed a similar response with an increase of colonic motility in response to WAS (Figure  3A ). Serum corticosterone was unchanged in SD-WAS compared to SD-C that is in accordance with previous data  [16]  and in HFD mice (Figure  2B ). By contrast, HFD-WAS mice exhibited a marked increase of serum corticosterone compared with other groups. Both ob/ob-C and ob/ob-WAS mice had an increase of corticosterone compared with lean mice (Figure  3B ). To evaluate whole intestinal permeability, mice were administered by oral gavage with FITC-dextran 4kDa that was then measured in plasma. Plasma FITC-D concentration was increased in HFD-C mice (+37%) but more markedly in HFD-WAS mice (+152%) compared with SD (Figure  2C ).
Study Design The ABLE Trial was a single-arm intervention study in patients with metastatic breast cancer conducted at the Léon Bérard Comprehensive Cancer Centre, Lyon, France. The ABLE Trial protocol has been published previously  [19]. The protocol was approved by the French Ethics Committee (Comité de Protection des Personnes Sud-Est IV). The study was reported to the National Commission for Data Protection and Liberties (CNIL; reference number: 1994192) and registered at ClinicalTrials. gov (trial number: NCT03148886). Briefly, participants were identified during the weekly multidisciplinary board meeting for metastatic breast cancers. The study was proposed by medical oncologists to eligible patients being treated with chemotherapy at the day care unit. Patients treated with hormone therapy received an information letter signed by their oncologist and a study brochure via postal mail; a clinical research assistant contacted them by telephone one week later to know whether they agreed to be enrolled in the study.
Study Participants Women were eligible to participate in the study if they were between 18 and 78 years of age, with de novo or secondary metastatic breast cancer that has been histologically confirmed. Subjects needed to be newly diagnosed patients (ie, within the last 3 months) in order to have comparable patients at inclusion. Patients were treated with chemotherapy, hormone therapy, targeted therapy, and/or radiation therapy. Additional eligibility criteria were as follows: having a medical clearance of no contraindications to physical activity; having an Eastern Cooperative Oncology Group performance status of less than 2; being able to speak and understand French, to complete questionnaires, and to follow instructions in French; and having a valid health insurance affiliation. An active list of patients was extracted from the center's data to estimate the number of potential subjects and the age range for the inclusion criteria.
These data were extracted from the numbers of patients treated at the center in 2015 for metastatic breast cancer with our inclusion criteria. Patients with contraindications to physical activity (eg, uncontrolled hypertension or cardiac disease and unstable bone metastases) who were unable to be followed for medical, social, familial, geographical, or psychological reasons over the study period, or with deprivation of liberty by court or administrative decision, were deemed ineligible for the ABLE Trial.
Demographic and Clinical Data Demographics, including birth date, age at diagnosis, living situation, and employment status, were collected at baseline  [19]. All clinical data were extracted from the participants' electronic medical records: hormone receptor status for both estrogen and progesterone receptors, tumor histology, personal history of breast cancer, sites of metastases, number of metastatic sites, and current treatment. The Response Evaluation Criteria In Solid Tumors (RECIST) V1. 1 was used to assess tumor progression between diagnosis and the end of the physical activity intervention  [23].
2 METs). The number of steps per day measured by the wrist activity tracker was collected by regular transfer through the activity tracker mobile phone app (Nokia Health Mate) available on the participants' mobile phones or tablet PCs. For participants with no mobile phone, the number of steps was transferred when they came to the hospital for their weekly or biweekly consultation. Data were uploaded to the study phone and a screenshot was taken that was then sent to the participant by email. The physical activity instructor was able to use the activity tracker interface to monitor the number of daily steps and any change in the activity level in order to set the target number of daily steps and adapt physical activity recommendations.
Statistical Analysis Participants' characteristics were described using means and SDs or 95% CIs for quantitative data and were described with frequencies and percentages for qualitative data. The recruitment rate was calculated as the proportion of participants who provided informed consent to participate in the ABLE Trial among eligible participants to whom the study was presented. The reasons for refusal were described. For the primary outcome, paired proportions before and after the intervention were compared using the McNemar test. For secondary outcomes, changes of continuous parameters during the physical activity intervention were analyzed using nonparametric tests, since the distributions of physical activity data were highly skewed. The algorithm of the activity trackers detects when subjects do not wear it using an integrated triaxial accelerometer.
Multivariate analyses were not possible given the limited sample size. Exploratory analyses on the relationship between variables were performed using Spearman rank correlations or Mann-Whitney tests when appropriate. The quality-of-life scores of the participants were compared with reference values for women with recurrent or metastatic breast cancer with a one-sample t test  [31]. All P values under. 05 were considered statistically significant. As the result of the exploratory setting of the analyses, no adjustments were performed in this feasibility study. Data were analyzed using SAS software, version 9. 4. (SAS Institute Inc).
Principal Findings The ABLE Trial is the first European study to investigate a physical activity intervention for patients with metastatic breast cancer and to obtain preliminary data on anthropometrics, functional fitness, physical activity level, sedentary behavior, quality of life, fatigue, and tumor progression. One of the key findings is the high participation rate among women eligible for this trial (94%), stressing the willingness of the targeted population to participate in physical activity interventions. The low attrition and high adherence clearly demonstrated the feasibility of the proposed physical activity intervention in women with metastatic breast cancer. While a deterioration of the physical activity level and quality of life would have been expected due to treatment and disease  [4, 31, 32] , women maintained their physical activity levels and number of daily steps as well as their quality of life.
Acknowledgments The authors would like to acknowledge the contribution of  Nokia  for providing activity trackers, free of charge, for participants and the contribution of  Florian Celli  for the creation of the study logo and patient brochures. LD was supported by a research grant from the  French League Against Cancer. The study was funded by the  Cancéropôle Lyon Auvergne Rhône-Alpes , via the association  Odyssea and Activ'Ra.
Library construction, RNA-sequencing, and quality control For each of the twelve samples (2 strains * 2 pH conditions * 3 biological replicates), sequencing libraries were generated using 2 µg of total RNA per sample with the TruSeq RNA sample preparation protocol from Illumina according to the manufacturer's recommendations. Tags were added to each sample for identification. The sequencing reaction was performed using the Illumina HiSeq v3 chemistry on a HiSeq 2000 in 100 bp single read run according to the manufacturers recommendations (GATC Biotech, Konstanz, Germany). Sequence data quality control was evaluated using the FastQC program. Adapter sequences were removed using Flexbar, and Sickle was used to clean bases with substandard quality (PHRED 28) before removing reads under thirty bases length.
Raw reads are available at the European Nucleotide Archive database system under the project accession number PRJEB34060. Read mapping to the reference genome and transcript counting STAR v2. 5. 2a_modified  [17]  was used to align the reads to the published genome of Ggt strain (https://fungi. ensembl. org/Gaeumannomyces_graminis/Info/Index). This available reference sequenced genome is from the R3-111a-1 Ggt strain, different from the strains used in our study  [15, 18]. FeatureCounts v1. 6. 0  [19]  was used to count the number of reads on each annotated Ggt gene, giving the raw counts. Genes with low count levels (under 1 count per million of mapped reads in three samples at least) were removed from the data.
Differential expression analysis and gene clustering DESeq2 R package  [20]  was used to product lists of DEGs between two experimental conditions. This program has its own normalization method "Relative Log Expression" (RLE) and needs to have raw counts as input. The p-values were adjusted to control multiple testing using the Benjamini and Hochberg's method. Genes with an adjusted p-value < 0. 05 were considered as significantly differentially expressed between conditions. The clustering of gene expression profiles was performed using HTSCluster R package  [21]  by making groups of co-expressed genes on the DESeq2 normalized counts.
Gene Ontology term (GO-term) enrichment GO enrichment analysis of DEGs was achieved with TopGO R package  [22]  using weight01 algorithm, Fisher's exact statistic test and a nodeSize parameter set to 5 (to remove enriched GO-term with less than five genes in the genome). GO-terms for each gene were first imported from BioMart database (Ensembl Fungi) via Blast2GO software (https://www. blast2go. com). For each GO category (Molecular Function, Cellular Component and Biological Process), Top 10 Enriched GO-terms (p-value < 0. 05), enrichment ratios (> 5), and number of genes under each enriched GO-term were represented using ggplot2 R package.
The oligonucleotides designed with the Primer 3 software are described in S2 Table. Quantitative PCR reactions (20 µL) containing 1 µl of cDNA, 0. 4 µM of each primer and 1 X SybrGreen I Master (Roche) were performed on the LightCycler ® 480 Real-Time PCR System (Roche). The quantitative PCR profile consisted of an initial denaturation at 95°C for 5 min, followed by 45 cycles of 95°C for 15 sec and hybridization-elongation temperature for 40 sec (S2 Table ). A dissociation stage was applied at the end of the PCR to assess that each amplicon generated was specific. Moreover, each specific amplicon was sequenced (Genoscreen, Lille, France) to confirm it corresponds the expected sequence. The expression levels of transcripts were normalized using external RNA controls  [23, 24]  from three independent biological replicates, each with three technical PCR replicates.
The heatmap was generated with scripts based on heatmap. 2 function as available in the "gplots" R package. A: acidic pH and N: neutral pH In order to better characterize the different expression profiles of the expressed genes, we performed a co-expression clustering analysis based on Poisson Mixture models  [21]. The analysis described 6 different profiles (Fig. 4 ). One profile (cluster 1) showed genes with strong expression in PG6, especially at acidic pH (1,167 genes) and another profile (cluster 2) showed genes with high expression in PG38 at neutral pH (445 genes). Both clusters 1 and 2 were representative of the higher growth rates of both strains according to pH. On the contrary, clusters 3 (1,168 genes) and 4 (503 genes) depicted the genes expressed in PG38 and PG6, respectively, in the pH where their growth were the lowest.
RT-qPCR validation of RNA-Seq analyses Eight genes, which were significantly differentially expressed at least twice among the four main comparisons, were selected to validate the RNA-Seq data by RT-qPCR assay. RT-qPCR primers are described in S2 table. The selected genes take part of the Pal pathway (palB, palC, palF, and pacC) or are related to pathogenesis (lac1, lac2, gmk1, and exo)  [8]. This panel provided a large range of expression levels and enabled us to compare log2FoldChange values between RT-qPCR and RNA-Seq experiments. We found a moderate correlation (r 2 = 0. 51) between log2FoldChanges of both types of experiments but with a very strong significance according to Pearson correlation test (p-value < 0. 01), confirming the validity of the RNA-Seq data (Fig. 8 A ). The similarity of the data between RT-qPCR and RNA-Seq was more precisely confirmed by comparing the pacC (GGTG_01809) expression (Fig.
II. Computational details Total energies, structures and electronic states are carried out using density functional theory (DFT)  [43]  as implemented in the Quantum ESPRESSO ab initio plane-wave pseudopotential code  [44]. Two different levels of approximation in the exchangecorrelation functional were used: the generalized-gradient approximation (GGA)  [45]  and the local density approximation (LDA)  [46]  are used to describe the exchange and correlation potentials. Single-particle Kohn-Sham wave function was extended using the plane wave with cutoff energy of 60Ry and an energy of 500Ry was included for the charge density. The studied ZnO polytypes include five possible ZnO polymorphs (3C, 2H, 4H and 6H) and a body-centered-tetragonal phase (referred as BCT-4, space group P42/mnm, No. 136).
20 unitinib, is an oral multikinase inhibitor approved for the treatment of advanced RCC. 2] [23]  The activity of sunitinib in PRCC was previously reported in a single-arm study in the first-line setting: median progression-free survival (PFS), was 6. 6 months (95% CI, 2. 8-14. 8) in type-1 PRCC and 5. 5 (95% CI, 3. 8-7. 1) in type 2. Median overall survival (OS) was 17. 8 (95% CI, 5. 7-26. 1) months and 12. 4 (95% CI, 8. 2-14. 3) months in type 1 and type 2, respectively. 24 Despite limited responses to vascular endothelial growth factor tyrosine kinase inhibitors (VEGF-TKIs) like sunitinib observed in these phase 2 studies, there are no proven treatments approved specifically for PRCC. Here, we report the results of SAVOIR (NCT03091192), a phase 3, open-label, randomized clinical multicenter study to assess the efficacy and safety of savolitinib vs sunitinib in patients with MET-driven, unresectable, and locally advanced or metastatic PRCC.
Study Design and Treatment In this sponsor-blinded study, patients were randomized in a 1:1 ratio to receive treatment with 600 mg of oral savolitinib (or 400 mg if <50 kg) once daily, given continuously, or 50 mg of oral sunitinib once daily in 6-week cycles of 4 weeks of treatment followed by 2 weeks without treatment. Patients were stratified based on the International mRCC Database Consortium risk-group criteria 27 using the number of predefined risk factors to assign patients into favorable, intermediate, or poor prognostic groups, as well as whether they were treatmentnaïve or previously treated with or without a VEGF-TKI. The investigational agent savolitinib was provided by the trial sponsor, AstraZeneca. The comparator sunitinib was purchased from Pfizer, Inc.