dataesr/scientific-paragraphs-categorization huggingface dataset:
db (version 8. 4. 0), with expression profiles for immune cell types referenced from the work of Jojic et al. (72). An enrichment score was calculated for each immune cell type (73), and we examined differentially expressed genes in the top 1% of the score distribution for each cell type and compared these to equally sized cohorts of randomly selected genes (see Table  S2  in the supplemental material). This analysis was conducted separately with up-and downregulated gene sets in the two-group comparison. Ontology analysis was performed using the R/Bioconductor package GO. db (version 3. 4. 0) and the gene2go file from the NCBI Gene database (downloaded 3 March 2016), using modified code from the R/Bioconductor package ontoTools (version 1. 28. 0) (74). To test if differentially expressed genes associated with specific gene sets, we constructed 2-by-2 contingency tables and categorized genes based on whether they were differentially expressed or not for each included Gene Ontology biological process (GOBP) term.
Random assignment was tested using Fisher's exact test  (75)  and corrected for the number of terms by use of the Benjamini-Hochberg correction  (76). We filtered terms by using their information content (IC)  (77) , based on a frequency of occurrence between 3 and 4, resulting in a set of 157 included terms that represent an appropriate trade-off between the total number of included terms and the specificity of functional insight. The entire R workflow and input data files are available online (https://github. com/rbhwilliams/Kline-polymicrobial-infection-paper). Statistical analysis. Statistical analyses were performed using GraphPad Prism software (version 6. 05 for Windows). SEAP assays were analyzed using one-way analysis of variance (ANOVA) with Tukey's post hoc test for multiple comparisons.
Cytokine readings for Luminex MAP analysis were analyzed using the Kruskal-Wallis test. CFU titers were compared using the nonparametric Mann-Whitney U test. P values of Ͻ0. 05 were deemed significant. Cytokine comparisons were performed using the Mann-Whitney U test, and further comparison was done using principal component analysis in R (version 3. 3. 2), with the packages factoextra (version 1. 0. 4) and FactoMineR (version 1. 34). Heat map data reflect log 2 transformation of the raw data and were plotted in R (version 3. 3. 2) by using the R package pheatmap (version 1. 0. 8). Ethics statement. Mouse experiments were performed with ethical approval by the Nanyang Technological University Institutional Animal Care and Use Committee (protocol ARF-SBS/NIE-A0247), which adheres to the National Advisory Committee for Laboratory Animal Research (NACLAR), a national guide which establishes the best practices for the use and care of animals for scientific purposes.
ACKNOWLEDGMENTS We thank  Krithika Arumugam  for her assistance with sequence data processing. We also thank  Gary Dunny  and  Jennifer Dale  for providing the E. faecalis transposon mutants used in this study. This work benefitted from data assembled by the  ImmGen Consortium (41). B. Y. Q. T. , H. M. S. G. , K. K. L. C. , S. B. -T. , S. H. , R. B. H. W. , and K. A. K. were supported by the  National Research Foundation  and the  Ministry of Education Singapore  under its  Research Centre of Excellence Programme. B. Y. Q. T. , H. M. S. G. , K. K. L. C. , S. B. -T. , S. H. , and K. A. K. were supported by the  National Research Foundation  under its  Singapore NRF fellowship program  (grant  NRF-NRFF2011-11 ) and by the  Ministry of Education Singapore  under its tier 2 program (grant  MOE2014-T2-1-129 ).
These data may be useful in determining the optimal harvest time at which phenolic compounds reach their maximum content, which, in turn, are related to a higher antioxidant activity. The results obtained allowed the authors to point out that perilla may constitute a new functional food and could be an important dietary source for the prevention of diseases caused by oxidative stress. This special issue also includes the study performed by I. Jerez-Martel et al. in which the phenolic composition and the antioxidant activity of crude extracts from both microalgae and cyanobacteria strains have been studied. The seaweed extracts have been proposed as additives for food enrichment due to their preservative properties and/or nutritional benefits. Thus, different extracts of several microalgae and cyanobacteria were studied for their antioxidant activity and phenolic contents.
Isolated colonies were obtained by subculture on 5% sheep's blood-enriched Columbia agar (bio-Mérieux, Marcy l'Etoile, France) at 37°C in anaerobic atmosphere using AnaeroGen (bioMérieux) after 48 hours. The colonies were circular, beige and nonhaemolytic with a diameter of about 1. 0 mm after 3 days of incubation on 5% sheep's blood agar. The strain Marseille-P2434 T is a strict anaerobic, motile and Gram-positive bacterium, rod shaped (0. 6-0. 8 μm × 3. 5-5. 5 μm) and spore forming. Catalase and oxidase were negative. A molecular identification was performed by sequencing the complete 16S rRNA gene using a 3130-XL sequencer (Applied Biosciences, Saint Aubin, France) and the fD1-rP2 primers as previously described  [3]. The obtained sequence was 95. 2% similar to the 16S rRNA gene sequence of Clostridium perfringens ATCC 13124 (GenBank accession no.
ACKNOWLEDGEMENTS We thank the members of the  TMIT team  for critical discussions on the topic of the involvement of cytokines in thymic Treg development. This work was financially supported by the  "Fondation pour la Recherche Médicale " ( FRM-DEQ20160334920 ), the  "Agence Nationale pour la Recherche"  ( ANR-16-CE15-0015-01 ), and the  IdEx Toulouse.
Continuous connectivity was not necessarily, as the app stored videos and repeatedly attempted to transmit them, until a network was detected and transmission succeeded. Study participants who already owned a smart phone could use their own phone to participate in the study. Low-cost smartphones with 3G connectivity were loaned to patients who did not own a smartphone. Cellular data charges were paid for by the study. At enrolment, consenting study participants received a 30 minute training session about how to use the smartphone and the VDOT app. This included practice recording and uploading a video and provision of written instructions. Additional face-toface training was provided by the study staff to any patients reporting technical difficulties during the intervention period. Adherence monitoring using VDOT was to be carried out for at least 60 days.
Acknowledgements This project was supported by a  Harry Windsor Research Grant , awarded by the  Australian Respiratory Council. Dr Greg Fox  was supported by a  CJ Martin Fellowship (NHMRC Grant  App  ID 1054107 ). Professor Richard Garfein  ( University of California San Diego ) provided input into technical aspects of the study protocol, and provided advice about the use of the VDOT platform. Dr. Kelly Collins  ( SureAdhere Mobile Technology Inc ) provided technical assistance in implementing the SureAdhere VDOT platform. Professor Garfein  is also a SureAdhere cofounder.
Acknowledgements Claire GOUMARD  was a recipient of a grant from the  Institut National du Cancer (French National Cancer Institute). The funding source had no role in study design, data collection, data analysis, data interpretation or the writing of the report. The authors thank  Pr Olivier ROSMORDUC  and  Dr Laëtitia FARTOUX  for their contribution to the care of patients with HCC. They further thank the  HUEP tumor biobank  ( Pathology Department, Saint-Antoine Hospital, Hôpitaux Universitaires Est Parisien, AP-HP ) for providing good quality tumor samples, as well  Sylvie DUMONT  for her expert technical help in managing them (LUMIC histomorphology technological platform,  UMS30 ,  UPMC, Paris ).
Statistical analyses A total of six markers of oxidative balance [damage to proteins (carbonyls), nitric oxide (NO)], enzymatic antioxidants (GPX, CAT, and SOD), and glutathione [ratio: GSH (reduced form)/GSSG (oxidized form)] were analyzed with generalized linear mixed effects models using a Bayesian approach with Markov chain Monte Carlo (MCMC) algorithms implemented in the MCMCglmm R package (Hadfield 2010). We ran a preliminary model on data of all birds which included a fixed effect for sex in addition to the below mentioned fixed effects. This model revealed strong effects of sex on the oxidative balance (see results) and males and females were analysed separately to account for sex-specific resistance to oxidative stress. The fixed effects included in the models were: prenatal condition (hatched from early or late laid eggs), postnatal condition (size advantaged or size disadvantaged), and inbreeding status (inbred or outbred).
The results are presented as the estimates of the sampled iterations with a 95% confidence interval. Statistical significance of the estimate can be assumed when confidence intervals do not overlap with zero. The correlation between parameters (X, Y) of the adult oxidative balance was calculated by dividing the covariance (cov(X, Y)) between parameters by the product of the standard deviations of the variance (SD(X)*SD(Y)). The effect size of differences between inbred and outbred birds within each experimental group was calculated with the R package "compute. es" (Del Re 2013) using the mean, standard deviation, and sample size. Hatching from an early laid egg matched a size advantaged position in the nest, whereas hatching from a late laid egg mismatched a size advantage, and vice versa for birds reared in size disadvantaged positions.
Structural biology and mechanism of exfoliative toxins The crystal structure of ETA was the first to be determined in atomic detail  [51] , followed by ETB  [52]  and by ETD  [24]  and currently, the atomic coordinates of six ET structures have been deposited with the Protein Data Bank (www. rcsb. org). The crystallographic structures of ETs have revealed much about their mechanisms of action, lack of hydrolytic activity against substrates in the native state, and the susceptibility of certain constituent layers of the epidermis to disruption by ETs.
Background The population of patients with established coronary artery disease (CAD) is growing because of an improvement in outcomes and survival from acute disease episodes. Nevertheless, these patients remain at high risk of cardiovascular events. Thus, CAD management is important in prevention of disease progression. The objective of this analysis was to describe disease management and clinical outcome of Austrian outpatients with stable CAD over 5 years by using data from the international CLARIFY registry. Methods CLARIFY was an international prospective observational registry of outpatients with stable CAD, defined as prior myocardial infarction or revascularization (CABG or PCI), coronary stenosis of more than 50% by coronary angiography or chest pain with myocardial ischemia. We analyzed demographic characteristics, risk factors, treatments and clinical outcomes of 424 Austrian outpatients with established CAD who Trial registration.
g. EUROPA  [8] ). In order to generalize the findings from these trials, real-life aspects regarding demography and disease management of outpatients with stable CAD are needed. Because of the improvement in outcomes and survival from episodes of acute disease, the population of patients with established CAD is growing. All these patients remain at high risk of cardiovascular events and therefore disease management is important in prevention of disease progression  [9, 10]. The prospeCtive observational LongitudinAl Reg-Istry oF patients with stable coronary arterY disease (CLARIFY) registry was initiated to improve knowledge regarding patients with stable CAD. The registry was designed to collect data on the current status of outpatients with stable CAD, including demography, clinical profiles, therapeutic strategies and clinical outcomes.
Data collection and data management Investigators completed electronic case report forms (eCRFs) at baseline and at patient visits 1 year, 2 years, 3 years, 4 years and 5 years after enrolment (±3 months). Data collected at baseline included demographics, risk factors and life style, medical history and current symptoms, physical examination including heart rate determined by pulse palpation and the results of the most recent electrocardiogram (ECG) performed within the past 6 months, laboratory values (if available: fasting blood glucose, HbA1c, cholesterol, including total cholesterol, highdensity lipoprotein cholesterol (HDL), LDL, triglycerides, plasma creatinine, and hemoglobin), and current chronic medical treatments taken by the patient for more than 7 days prior to inclusion in the registry.
During annual follow-up visits the following information was collected: employment status, risk factors and life style, current symptoms, physical examination including heart rate, laboratory values (if available), current treatments and clinical events occurring since the last visit, e. g. all-cause death, fatal or non-fatal myocardial infarction (MI), fatal or nonfatal stroke, cardiovascular death, unstable angina, major bleeding, coronary angiography, and revascularization percutaneous coronary intervention (PCI) and CABG, transient ischemic attack (TIA), hospitalization for congestive heart failure (CHF) and cardiovascular hospitalization. Completed eCRFs were electronically sent to the data management center in Glasgow (Robertson Centre for Biostatistics, University of Glasgow, UK) where checks for completeness, internal consistency and accuracy were run.
Statistical analysis All data were collected and analyzed at an independent academic statistic center at the Robertson Centre for Biostatistics, University of Glasgow, UK which was responsible for data management, statistical analyses and storage of the data according to regulations. The main analyses were designed to describe patient characteristics at baseline and to estimate the annual cardiovascular event rates, and the outcome event rates by region and country. Baseline variables as well as parameters collected in the annual follow-up visits were summarized as means, standard deviations (SD), medians, interquartile ranges (IQR), and ranges for continuous data and as counts and percentages for categorical data. Summaries were provided for CLARIFY Austria and for CLARIFY Austria and subjects with angina.
Revascularization was performed in 9. 2% of patients, but most patients had a history of PCI or CABG. In patients with acute coronary syndromes revascularization reduces cardiovascular death and MI compared with conservative treatment  [44, 45] ; however, controversy exists over the benefit of revascularization in patients with chronic stable CAD compared with medical management  [44, 46] , and large studies are underway to settle this issue (ISCHEMIA trial, clinicaltrials. gov, NCT01471522). Results from the COURAGE study implicated that PCI did not reduce risk of death, MI and other cardiovascular events when added to current medical treatment in patients with stable CAD  [47]. In contrast, a large meta-analysis resulted in a benefit of revascularization. The positive effects of revascularization are clearly shown in patients with anginal symptoms.
To ensure the reliability and specificity of our method, genomic DNA from well-characterized cell lines were used; high-resolution KIR typing results obtained were then compared to those previously reported. Two different bioinformatic pipelines were used allowing the attribution of sequencing reads to specific KIR genes and the assignment of KIR alleles for each KIR gene. Our results demonstrated successful long-range KIR gene amplifications of all reference samples using intergenic KIR primers. The alignment of reads to the human genome reference (hg19) using BiRD pipeline or visualization of data using Profiler software demonstrated that all KIR genes were completely sequenced with a sufficient read depth (mean 317× for all loci) and a high percentage of mapping (mean 93% for all loci).
Overall, various KIR genotypes can be observed in a population. All KIR genes, and especially for inhibitory KIR, a high degree of allelic polymorphism has been described. The latest KIR Immuno Polymorphism Database (IPD-KIR) describes 753 KIR alleles. KIR allele polymorphisms need to be investigated throughout the exon and the intron regions, and regulatory regions as shown for KIR3DL1  (19). In contrast to HLA class I genes, structure and length of KIR genes vary. KIR allele polymorphisms impact both KIR + NK cell phenotype and function, as we and other groups having described for KIR3DL1  (20) (21) (22) (23) (24) (25)  and for KIR2DL2/L3  (26). Differences in the intensity of expression (strong, weak, or null) have been described for the KIR3DL1 receptor, defining different allotypes according to the KIR3DL1/3DS1 allele combinations present in healthy individuals  (21, 27).
MaTerials anD MeThODs samples Thirty B-EBV cell lines from the 10th International Histocompatibility Workshop (IHW) were selected from a wellcharacterized panel known for their KIR gene content. KIR genotype information, including KIR allele typing of some KIR genes for all these B-EBV cell lines, was obtained either from the IPD/KIR database or from literature for specific KIR loci. Known KIR genotypes and allele typing of these 30 B-EBV cell lines are provided in the Table  S1  in Supplementary Material. Kir long-range (lr) Pcr and Primers DNA genomic extractions were performed from B-EBV cell lines using a Nucleospin blood kit (Macherey-Nagel, Duren, Germany). The concentration and the purity of all DNA samples were checked on a NanoDrop 2000C spectrophotometer (ThermoFisher, Wilmington, DE, USA) by measuring the ratio of absorbance at 260 and 280 nm.
sequencing Data analysis and Kir allele assignment The quality of the Illumina raw data sequences obtained was monitored by using the Sequencing Analysis Viewer Illumina software. The quality of the base calling from images and sequences was determined by the quality score (Q30) which must be ≥75% for 2 × 250 bp reads. KIR reads were mapped to the human genome reference sequence hg19 (GRCh37) by using the Burrows-Wheeler Aligner Memory Efficient Mapping (BWA-MEM) tool. The binary alignment map (BAM) files containing mapped reads were then visualized on Integrative Genomics Viewer (IGV) algorithm  (48). In parallel, raw KIR sequences were aligned and visualized using the Profiler software version 1. 70, initially developed by Dr. M. Alizadeh (Research Laboratory, Blood Bank, Rennes, France) for NGS-based HLA typing  (49).
A flowchart for data analysis using the Profiler software is provided in Figure  S1  in Supplementary Material. The first step of analysis consists by merging R1 and R2 sequences to each other when at least 10 complementary bases were found between R1 and R2 of the same cluster. During this phase, for each inconsistency of base calling, the quality value was used to select the best assignment. All sequences issued from a cluster for which we could not determine complementary between R1 and R2 remained unchanged. All sequences were transformed to FASTA format at the end of this step. The second step of analysis consists of phasing each of the sequences obtained in step one by using Blast algorithm. The third step of analysis consists by merging all sequences together using Blast information.
In this step, the depth for each position and the number of sequences for each allele were calculated. The first three steps are managed in a Linux environment. The last step is presentation and assignment of each construction based on database information in a friendly interface for user, all mismatches and differences to the database are extracted and presented to the user. For KIR allele assignment, a manual bioinformatic pipeline was first used in the absence of available softwares. This consisted of exporting from IGV, all exon sequences of each KIR gene and comparing polymorphic bases with those referenced from the IPD-KIR database. Then, two different bioinformatics algorithms were used: the first one, hereafter called "BiRD, " was developed by the BiRD platform (E. Charpentier, U. Guyet, Genomics and Bioinformatics Core Facility GenoBiRD, Nantes, France) and consists of an analysis pipeline built with Snakemake on the same logic as the manual method.
Determining Presence/Absence or KIR Genes Absence or presence of KIR genes is evaluated using GATK DepthOfCoverage on the BAM and using a browser extensible data (BED) file describing the chromosome position of each gene (except KIR2DP1 and KIR3DP1). Coverage mean is calculated on each gene position, and a threshold of 10 is applied in order to ascertain its absence or presence. Presence/absence of KIR genes defined by NGS is concordant to the KIR genotype of the 30 IHW samples, stratified by AA vs Bx genotypes, previously validated in our laboratory by PCR-SSP multiplex method (data not shown).
Determining KIR Alleles Allele-specific nucleotide positions are extracted manually using IPD-KIR alignment tool. 1 For every gene, the Nucleotide-CDS of all alleles are aligned against the default reference allele. A python script is then used to reformat the multipage alignments in order to have one allele alignment per line. A second python script is utilized to extract all variations from the default reference allele and map the exon position number of these variations to the chromosome position. A file is created for each gene listing all the variations found for every allele. Bases at these positions are then called using SAMTools (v1. 2-2) mpileup for all samples. Finally, KIR alleles are determined by calculating the percentage of nucleotide matches between the base calls and the allele variations for each KIR allele, the highest percentage giving the most confident allele.
The second algorithm used for KIR allele assignment was the Profiler software, previously described in Figure  S1  in Supplementary Material, version 1. 70  (49) , which permits to 1 https://www. ebi. ac. uk/ipd/kir/align. html. directly assign KIR alleles at the highest level resolution (seven digits) since full intron and exon sequences were considered and also provides quality data such as mean coverage for each KIR locus. The fragment size percentage of sequences for each allele/ locus was also considered as well as percentage of mapping for each KIR gene. Overall, KIR allele assignment for each locus and for all samples corresponds to the combined KIR results obtained using manual pipelines, BiRD, and Profiler softwares. KIR alleles were assigned on the basis of the known DNA sequences identity within the IPD/KIR database.
complete sequencing of all Kir genes In order to check the specificity of KIR LR-PCR obtained, amplicons were further fragmented and sequenced on paired end 2 × 250 bp from Illumina MiSeq platform. The sequencing of all amplicons yielded a total of 6. 3 Gb, which was generated from a 755 ± 31 K/mm 2 cluster density (data not shown). Approximately 88. 2% of the clusters passed QC filters and on  average, 82. 4% of both reads passed with a Q30 > 82% (data not shown). Thus, analysis of FastQ data obtained from all IHW samples reported an excellent quality control. The entire length of KIR genes was sequenced with good coverage as illustrated for KIR2DS1, KIR2DS2, and KIR3DS1 (Figure  2A ) activating genes, and for KIR2DL1, KIR2DL3, and KIR3DL1 (Figure  2B ) inhibitory genes using either IGV or Profiler software, respectively.