dataesr/scientific-paragraphs-categorization huggingface dataset:
Perhaps most importantly, AM-001 is the inaugural study that has established the infrastructure and collaborative network for future prospective interventional studies to advance treatment and to explore clinical and pathologic markers of disease severity, prognosis and treatment response under the umbrella of the ABNL MARRO, an clinical trial platform for the MDS/MPN International Working Group. • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year.
Study participants We conducted a genome-wide association study (GWAS) in confirmed carriers of HNF1A variants associated with diabetes. Patients were enrolled in six countries: Czech Republic, France, Poland, Slovakia, the UK and the US (Boston). A group of 121 participants from the US (Chicago) served as a validation set. Given the results of previous GWAS studies on MODY patients  (Locke et al. 2018)  we set out to perform the GWA study on a combined cohort of MODY patients. Our basic assumption was to reach the level of at least 500 individuals (which is larger than any previous study). At the same time, the power estimates were heavily dependent on the size and structure of families, therefore we do not present these estimates in the manuscript. Detailed information about number of families included in the analysis as well as family structures is provided in Additional file 1: Data S1.
Genotyping and quality control DNA was extracted in the country of sample origin. Samples were gathered at the Center for Medical Genomics OMICRON in Kraków, Poland where they were genotyped using Illumina Human Core arrays (Illumina, San Diego, CA, USA) according to the manufacturer's instructions. Quality control (QC) was performed as described previously  (Ludwig-Słomczyńska et al. 2020)  and is presented in detail in the Additional file 1: Data S2. A total of 282,876 autosomal polymorphisms were eligible for the analysis. The genotyping of the replication set was performed by the Molecular Phenotyping and Genotyping Core of the Joslin Diabetes Center, USA.
Genotype and tissue expression project Tissue-specific RNA sequencing and phenotype data were acquired from the Genotype and Tissue Expression (GTEx) project via the database of Genotypes and Phenotypes (dbGaP) Project #5358 (dbGaP accession number: phs000424). For further details see Lonsdale et al. (Lonsdale et al. 2013 ) and the GTEx website (http:// www. gtexp ortal. org/ home/ docum entat ionPa ge). Testing for expression quantitative trait loci (eQTLs) was performed via the GTEx online search tool  (Aguet et al. 2017).
The list of HNF1A target genes was based on the Transcriptional Regulatory Relationships Unraveled by Sentence-based Text Mining (TRRUST) database  (Han et al. 2015). The analysis on the validation set was performed with the use of linear mixed models as implemented in the package 'coxme' in R. The trait (age of onset) was logtransformed to avoid the inflation of estimated due to overdispersion. In the model, we included: current age, sex and location of the causative HNF1A variant. The kinship matrix was included as provided from the pedigree data by the University of Chicago. The p-values refer to the ANOVA-type test with the likelihood ratio test statistics for model comparison.
Clinical characteristics Study participants consisted of 843 carriers of HNF1A causative variants, including 309 probands and 534 of their family members (coming from 175 families). Salient clinical characteristics of study subjects are presented in Table  1  and Additional file 1: Data S1. The variants observed among studied participants along with their ACMG classification are listed in Additional file 4: Table  S1. 216 variants were observed among studied patients. 102 of them were pathogenic according to ACMG criteria, 37 were likely pathogenic, 72 of uncertain significance (VUS) and only 5 were benign. Among VUS only 4 had "BS" mark indicating evidence of benign impact, while 5 "BP" mark, which would support their benign characteristics. Given progress in MODY research, improvements in clinical diagnostic criteria and new diagnostic methods, we reasoned that date of birth should be included in the statistical model analyzing the determinants of age at onset.
eQTL analysis for identified variants We next used GTEx data to examine whether the identified variants influenced the expression of the genes in which they are located. The two HK1 SNPs, rs2305198 and rs7079157, are in linkage disequilibrium (LD) and the former is more frequent in the European population. In the GTEx database, the minor allele of rs2305198 was associated with higher HK1 expression in whole blood and lower HK1 expression in many other tissues,   including those of the cardiovascular system (heart and aorta) and the nervous system (some brain regions and tibial nerve) (Fig. 3A ). The minor allele of rs10865231 was significantly associated with lower expression of STON1-GTF2A1L across many human tissues (Fig. 3B ). Also, the minor allele of rs2637248 was associated with higher expression of LRMDA (aka C10orf11) in several regions of the brains, including the hypothalamus (Fig.
Common variants in HNF1A target genes and their influence on age at onset Since HNF1A is a transcription factor, variation in its target genes might affect its binding affinity, and thereby influence target gene expression and ultimately the age at diabetes onset. We therefore searched the TRRUST database to identify HNF1A target genes  (Han et al. 2015). For each of the target genes, variants in the intergenic regions (covering 500 kb up-and downstream) (based on imputed genotypes) were selected for the analysis. As previously, HNF1A causative variants were grouped according to their location in the dimerization, DNAbinding or transactivation domains. Association between common variants in genes and age at onset that depended on causative variant location was found for 16 variants at the AFP/AFM, CYP1A2, SLCO1B3, MTTP, CRP and CSRP1 loci (Table  5 ).
Funding This study was funded by a  European Foundation for the Study of Diabetes  grant " New Approach  to  Existing MODY Biomarkers  and the  Development of Novel Ones". The HNF1A gene analysis of Czech samples was supported by the  Ministry of Health of the Czech Republic , grant number  NV18-01-00078. The study of Slovakian samples was supported by grants  APVV-187-12  and  Ministry of Health  of the Slovak Republic  2019/20-LFUK-8  and  VEGA 1/0211/18. The genetic analysis of US samples was supported by  NIH  grants  R01DK55523  (to A. D. ) and  P30DK36836  (Genetics Core the  Diabetes Research Center at the Joslin Diabetes Center ). The study of the validation set was supported by grants from the  National Institute of Diabetes and Digestive and Kidney Diseases  ( R01DK104942  and  P30DK020595 ).
Dietary intake assessment Participants were asked about their habitual dietary intake over the past month (to reduce recall bias) and dietary intake data were collected immediately after breast cancer diagnoses (at recruitment) before any cancer treatment. A validated and reproducible culture-specific QFFQ was used together with food models, food portion pictures and household utensils alongside the South African Food Composition Tables to determine habitual dietary intake  (31) (32) (33). The QFFQ entailed of 145 food items reported by recently published literature as regularly consumed staple foods and foods less regularly consumed. The dietary intake frequency included the amount of times foods were consumed per day/week/month or never. Life size colour photographs of thirty-seven foods (in three portion sizes) were displayed in the food portion picture booklet  (32).
Statistical analysis Descriptive analyses were presented by mean values and standard deviations (data which were normally distributed) and median; 25th-75th percentile (for data with skewed distributions). Differences between breast cancer cases and controls were assessed using paired sample t test (normal distributed data) and Wilcoxon signed rank test (skewed data) for continuous variables and paired χ 2 test for categorical variables (presented as percentages). For each participant, the relative energy contribution (percentage kJ of total EI/d) of each NOVA food group in the diet was calculated and then categorised into tertiles. Conditional logistic regression was applied to compute OR and associated 95 % CI to determine the associations with each NOVA food group (dose-response analysis of tertiles) and breast cancer risk and when stratified by oestrogen positive and progesterone positive (PRþ) receptors.
Thus, a possibility of biased dietary data for cases due to changes in dietary intake, but dietary intake may also depend on the stage of cancer at diagnoses and therefore, require more research. Our study has some strengths and limitations. Strengths include that cases were recruited prior to any breast cancer treatment and questionnaires used to obtain data were proven to be validated. Trained personnel were used to administer all questionnaires (not self-reported). Data used in the analysis were standardised and the categorisation of the food items according to the NOVA system was discussed with experts involved in the development of the NOVA system. Limitations include the relatively small sample size of this study, especially for subgroup analyses, and the fact that dietary intake was measured over the past month (at recruitment of the study) when habitual dietary intake of case participants could have changed due to illness (increased possibility for reverse causation, but may be dependent on the tumour size and requires more research).
Acknowledgements The authors would like to thank the participants of the SABC study and the  Directors of the Chris Hani Baragwanath Academic Hospital and Chris Hani Baragwanath Breast Unit. The authors would also like to thank the fieldworkers involved in this study:  Phindile Mathe ,  Yvonne Chaka ,  Victor Shandukani ,  Siphesihle Sibiya  and  Maria Sihlo  and the  SABC  study project coordinators from the  International Agency for Research on Cancer ,  Tracy Lignini  and  Robyn Smith. We also acknowledge the contribution towards dietary data collection, coding of QFFQ's and scientific input of prof H. H. Vorster (posthumous) in this study. This study was supported by a research grant secured from the  WCRF , international grant number  2012/591. The WCRF had no role in the study design, analysis or writing of this article.
However, they do not demonstrate that %HbF has predictive value in their data set. It is possible that the problem lies in a small and noisy dataset, and not in oxygen gradient ektacytometry. Similarly, did the authors find significant and relevant odds ratios of other markers of disease severity, such as levels of Hb and coinheritance of α-thalassaemia in relation to pain? It would be helpful to provide additional data of other laboratory parameters with regard to the eight patients whose RBCs have a high elongation index (EI) during a hypoxic state (EI min >0. 4) and low EI under normal oxygen tensions (EI max <0. 6). These characteristics could be considered favourable, as suggested by the authors. However, six children reported a pain crisis in the past 2 years, one of whom was admitted for pain four times in past 12 months.
Protein Human PAD4 (hPAD4) was purchased from Proteogenix, Schiltigheim, France. Its activity and non citrullinated status were checked before immunization. Purity of recombinant hPAD4 protein produced by Proteogenix was higher than 90%. Purity evaluation was made on SDS-PAGE gel using the GelAnalyzer software by Proteogenix. This software identifies each protein band on a track, calculates its intensity and subtracts the background to evaluate the protein of interest's purity. To test the capacity of hPAD4 to citrullinate, native human fibrinogen was incubated in 0. 1 M Tris HCl (pH7. 4), 10 mM CaCl2, 5 mM dithiothreitol buffer with human PAD4 for 2 hours at 37°C. Citrullinated human fibrinogen was detected by ELISA using sera from ACPA positive RA patients. The absence autocitrullination of hPAD4 was checked by i/ using sera from ACPA positive RA patients in ELISA assays, ii/ using the anti-modified citrulline Western blot detection kit, Millipore, France.
2 and drying, the array was scanned at 635 nm (Axon Genepix Scanner 4300 SL50, JPT Peptide Technologies, Berlin, Germany). Images were quantified using spot-recognition software GenePix (Molecular Devices). For each spot, mean signal intensity was extracted (between 0 and 65535 arbitrary units). For each mouse strain, mean background signal intensity was obtained for every peptide using all the sera from mice immunized with PBS. A positive serum was defined by a ratio (mean test signal/mean background signal) higher than 3. Ratios are listed in Supplementary Figures  1, 2.
Consistent with a growing appreciation of CpG methylation signatures as a more robust disease classifier than gene expression, it is now possible to diagnose rare diseases and different types of cancers and guide clinical management based on such signatures. Recently, it has been observed that in autism spectrum disorders, abnormalities of methylation on the X chromosome are detected more often than on the other chromosomes. This observation prompted Lasalle to take a closer look at the relationship between the male bias typical of ASD and the inactivation of the X chromosome. In particular, she asked whether anomalies of X inactivation might play a greater role than previously appreciated in the etiology of neurodevelopmental disorders. Along this theme of neurodevelopment, Kong et al. , incorporated parent-of-origin effects (POE) into a genome-wide association analysis of behavioural disinhibition (characteristic of many neuropsychiatric disorders) on a large dataset.
PLOS PATHOGENS STM or SPA) were collected. In parallel, RNA was extracted from six independent extracellular STM (N = 3) and SPA (N = 3) cultures that were grown in LB to stationary phase microaerobically, prior to cells infection. Isolated RNA from these 12 samples was deep-sequenced (RNA--Seq), aligned to the corresponding Salmonella genome and compared between all conditions. Principal Component Analysis (PCA) of normalized gene read counts of these RNA-Seq data indicated a unique expression profile for each condition and good reproducibility between independent biological triplicates (Fig  1A ).
From 6-8 h p. i. at least 100 infected cells per strain (for SPA fliC at least 50) were examined for intracellular phenotype. Data represent the means with standard deviations (SD) for three biological replicates for each strain and condition. Statistical analysis was performed with One-way ANOVA and is indicated as n. s. , not significant; � , p < 0. 05; �� , p < 0. 01; ��� , p < 0. 001. https://doi. org/10. 1371/journal. ppat. 1010425. g009 HeLa cells were infected by invasive Salmonella, at a defined time point of 8 h p. i. , host cells were osmotically lysed, and released bacteria were used to reinfect new epithelial cells. The number of viable bacteria in inoculum, released from initially infected host cells, and the number of bacteria in the second round of invasion were quantified (Fig  10A).
Bacterial strains, growth conditions and data sets Bacterial strains utilized in this study are listed in S6 Table. S. Typhimurium 14028 S  [92]  and S. Paratyphi A strain 45157, an epidemic strain responsible for a paratyphoid outbreak in Nepal  [9]  were used as the wild-type strains. Bacterial cultures were routinely maintained in Luria-Bertani (LB; BD Difco) liquid medium at 37˚C. An M9 medium  [33. 7   , with or without 0. 1% Casamino acids, and with one of the following carbon sources glucose (11 mM), ethanolamine hydrochloride (51 mM) or sodium citrate (34 mM) was used as a minimal growth medium. For HeLa cell infections, Salmonella cultures were grown to the stationary phase under microaerobic conditions (see below). The final dataset for RNA-Seq included 12 samples resulting from three independent cultures in LB or infection experiments that were used for RNA extraction: (i) S.
Genome annotation and quality control A flowchart summarizing the RNA-seq pipeline and bioinformatic analyses is shown in S3 Fig. Annotation of SPA 45157 and STM 14028S genomes was performed using EugenePP 1. 2  [96]  with general and targeted evidence to predict coding genes and noncoding features (S1 Fig). Functional prediction was produced with InterProscan v5. 15-54. 0 with GO terms, COG version COG2014  [97] , REBASE v708  [98] , IslandViewer4  [99]  and PHAST  [100]. Structural and regulatory non-coding RNA were annotated using RNAspace software v1. 2. 1  [101]  together with the following tools: RNAmmer 1. 2 for rRNA  [102] , tRNAScan-SE 1. 23 for tRNA  [103]  and blastn 2. 2. 25 against RFAM 10. 0 for other ncRNA  [104]. The gff3 files produced by Eugene and RNA annotation were merged by a semi-manually procedure using BEDTools-2.
Reads mapping and counting The remaining, non rRNA reads were mapped with STAR-2. 6. 0c [106] , with default parameters, against a "hybrid" genome composed by the Ensembl GRCh38 human primary assembly (release 92) and the SPA (accession number CP076727) or STM (accession number CP001362 -CP001363) genomes. In addition, in order to analyze bacterial samples, we indexed each bacterial genome separately by decreasing the parameter "genomeSAindexNbases" to 10 for STM and to 9 for SPA, while producing the alignment (. bam) files sorted by coordinates. Samtools flagstat v1. 8 was used to obtain mapping statistics. Then we added read groups to trace the origin of each read with AddOrReplaceReadGroups of Picard tools v2. 18. 2. Next, we merged the bam files that originated from resequencing of the same sample using the Merge-SamFiles command of Picard tools.
Differential gene expression analysis Normalization and differential analysis were carried out according to the DESeq2 model and package  [109]  using adjusted p-value with FDR correction and the Wald test to infer the probability value. Genes that had too few reads (the sum of reads for all the samples was less than 10) were discarded. To compare DEGs between SPA and STM, we created a count matrix composed of the shared protein-coding and ncRNA genes between these two serovars. The heatmaps were created by applying DESeq2 variance stabilizing transformations (the vst command) on the counts followed by subtracting the mean of the gene across all samples. The heatmaps were drawn using the ComplexHeatmap R package  [110].
This work was supported by the  Infect-Era program ,  SalHostTrop  project (" Understanding the Human-Restricted Host Tropism of Typhoidal Salmonella ",  2016-2020 ) and by the  France Genomique National  infrastructure, funded as part of " Investissement d'avenir" program  managed by  Agence Nationale pour la Recherche  ( ANR-10-INBS-09  contract). The work at the  Gal-Mor laboratory  was supported by grant numbers:  2616/ 18  from the joint  ISF-Broad Institute program ;  3-12435  from  Infect-Era /Chief Scientist Ministry of Health ;  I-41-416. 6-2018from the  German-Israeli Foundation for Scientific Research and Development (GIF , awarded to OGM and MH); and  A128055  from the  Research Cooperation Lower Saxony -Israel (The Volkswagen Foundation , awarded to OGM, MH and GG). The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.
To generate two equally balanced groups, the subjects were assigned by body weight, relative peak power, and relative VO 2max (maximal oxygen consumption) measured on the equipment Metalizer 3B (Cortex, Germany), which were recorded during the initial incremental test (IT). After the assignment, the data revealed no significant differences in absolute and relative mean power between the groups. The test persons were assigned to the verum NaNO 3 group (N) and the placebo NaCl group (PL). Then, they followed the same high-intensity, highvolume (HIHVT) training protocol. One training session was performed on day 9 of the supplementation (Scheme 2).
Physical Exercise and Blood Sampling All physical tests were carried out on a cycle ergometer (Excalibur Sport, Lode, Netherlands). Each test was carried out in the same daytime for the same subject. The individual height of the saddle and handlebar was adjusted in each test and training session. In the first week of the trial, pretests were performed. To determine the maximum power of each participant, an incremental test was accomplished. The data from this test were the basis for the training. These tests were performed before any supplementation was given. During the second to fourth week, the participants had to exercise three times a week, in addition to their individual recreational workouts. The subjects were instructed not to make any changes in their regular workout routine during the trial.
Statistical Analyses Univariate statistical analysis and preparation of graphs including receiver operating characteristic curves (ROC) were performed with GraphPad Prism (version 7 for Windows, La Jolla, CA, USA). Normality was tested by using the D'Agostino and Pearson normality test. Data are reported as the mean ± standard deviation (SD) for normally distributed data and as the median with 95% confidence intervals otherwise. Correlations between parameters were performed after Pearson or Spearman as appropriate. One-way ANOVA and Mann-Whitney test were used for in-group analyses. A two-tailed p-value of 0. 05 was considered statistically significant. Multivariate statistical analyses were performed on SAS ® OnDemand for Academics and used to describe the relationships among plasma amino-acid concentrations and related parameters such as K gaa , K harg , time, and treatment (NaNO 3 vs.
Results Cardiac abnormalities associated with null alleles for 705 genes. We generated and analyzed phenotype data using TTE and ECG from 3,894 IMPC mouse lines homozygous for a single-gene null knockout mutation or heterozygous if homozygous mutation was lethal. All mutants and corresponding control animals were young adult mice (12 weeks of age) of the C57BL/6N background. This dataset included 3,836 of 3,894 lines with ECG data, 1,398 of 3,894 lines with ECG and TTE data and 58 lines with TTE data only. We identified 705 lines (genes) with at least one abnormal cardiac phenotype by applying the statistics of a soft windowing approach  8  that compensates for temporal batch effect combined with q-value correction of the genotype contribution P values (R package qvalue  9  , version 2. 14.
1a ). Pla2g10 encodes phospholipase A2 group 10, a calcium-dependent enzyme, Fig. 1  | Candidate genes for cardiac conduction system disease and cardiomyopathy in mice. representative electrocardiograms from conscious mutant and control mice with indication of eCG parameters and interval durations. a, Gatm loss (Gatm -/-) caused lower heart rate with prolonged QrS width and QTc and ST interval lengths. b, Pla2g10 loss (Pla2g10 -/-) lowered heart rate and prolonged Pr, PQ and QTc intervals in female null mice. c, Cap2 depletion (Cap2 -/+ ) induced lower heart rate and lengthy QTc and ST durations in male null mice compared with C57bL/6N controls. Data are presented by Mouse Specifics software. Interval durations are given in milliseconds. M-mode recordings are through a short-axis view tangential to the papillary muscle from representative mutant and control mice.