dataesr/scientific-paragraphs-categorization huggingface dataset:
In a subsequent analysis, several biomarkers were included in 1 unique model (multimarker model). Both BNP and NT-proBNP were measured but we kept only NT-proBNP in this multimarker model. To deal with the risk of multicollinearity, we used the variance inflation factor method within the logistic model. Biomarkers with the highest variance inflation factor were removed 1 by up until all variance inflation factor were 10 or less. One final model was fitted by cohort, and, as for the mono-marker models, the increase in C-index on top of routine HF predictors was assessed. All statistical analysis were performed using R software (CRAN).
The results presented herein expand the knowledge derived from a previous work from the HOMAGE project. For the purpose of the current analysis, we merged the datasets of the 2 phases of the previously reported HOMAGE study  20  (totalizing 562 cases and 871 controls) and conducted the same analysis in 3 large casecontrol studies: HOMAGE (merged), ARIC and FHS. This new analysis provides an important increase in the level of external validity achieve by our results, as they arise from both American and European settings. From this analysis that maximizes external validity, 8 proteins (BNP, NT-proBNP, 4E-BP1, HGF, Gal-9, TGF-alpha, THBS2, U-PAR) appeared as the most replicable biomarkers predicting incident HF in all cohorts. This top list of biomarkers, in light of the strength of the combined analysis we report herein, should be considered in future biomarker studies aiming to predict incident HF.
The analysis of cytokines by RT-qPCR showed an increased production of TNF (Figure  2C ), IL1β (Figure  2D ), IL6 (Figure  2E ), and TGFβ (Figure  2F ) in female IL-10 -/-mice compared to IL-10 -/-males. Female IL-10 -/-mice developed more severe colitis that was quantifiable macroscopically. (A) Schematic representation of the experimental design where the female (♀) and male (♂) interleukin 10 knockout (IL-10 -/-) mice were monitored for 13 weeks. Feces and (B) body weight were collected every week, and (C) survival rate was calculated. At the endpoint, gastrointestinal organs were weighted and measured: (D) colon length, (E) colon weight/length ratio, and (F) spleen weight/body weight ratio. Data are represented as means ± SEM. Statistical analyses were performed using the Mann-Whitney U test.
(F) Taxonomic summary at the order level, highlighting (G) the most significantly modified specie, Akkermansia muciniphila. For bar and linear graphs, values are given as mean ± SEM. Data represented in violin plots show median ± quartiles. Statistical analyses were performed using the two-way ANOVA test, followed by a Bonferroni post hoc test. Significant differences were recorded as * p < 0. 05, ** p < 0. 01, *** p < 0. 001, **** p < 0. 0001, when compared to day 0 (D0); and # p < 0. 05, ## p < 0. 01, #### p < 0. 0001, when compared female vs. male at each time point. Next, the taxonomic analysis revealed that the Firmicutes/Bacteroidetes phylum ratio, widely accepted to have an important influence on maintaining normal intestinal homeostasis, was significantly reduced in female IL-10 -/-mice during mild and severe colitis and significantly lower than that of males at D42 and D91 (Figure  3D ).
Statistical Analysis Data are expressed as mean ± SEM and statistical analyses were performed using GraphPad Prism software (V. 8). Significance was determined using unpaired t-tests or the Mann-Whitney U test when data were normally or non-normally distributed, respectively. For data collected at different time points in line chart form, a two-way repeated-measures ANOVA or a mixed-effects model (if missing values) with a Bonferroni post hoc test was performed. The Spearman correlation coefficient matrixes were used to screen for the relationship between variables. Linear regressions of the most relevant identified conditions were represented and analyzed using linear regression. Significance was noted as follows: compared to day 0, * p < 0. 05, ** p < 0. 01, *** p < 0. 001, and **** p < 0.
Figure1. Female IL-10 -/-mice developed more severe colitis that was quantifiable macroscopically. (A) Schematic representation of the experimental design where the female (♀) and male (♂) interleukin 10 knockout (IL-10 -/-) mice were monitored for 13 weeks. Feces and (B) body weight were collected every week, and (C) survival rate was calculated. At the endpoint, gastrointestinal organs were weighted and measured: (D) colon length, (E) colon weight/length ratio, and (F) spleen weight/body weight ratio. Data are represented as means ± SEM. Statistical analyses were performed using the Mann-Whitney U test. Significant differences were recorded as ** p < 0. 01.
Data represented in violin plots show median ± quartiles. Statistical analyses were performed using the two-way ANOVA test, followed by a Bonferroni post hoc test. Significant differences were recorded as * p < 0. 05, ** p < 0. 01, *** p < 0. 001, **** p < 0. 0001, when compared to day 0 (D0); and # p < 0. 05, ## p < 0. 01, #### p < 0. 0001, when compared female vs. male at each time point.
Contributions: Conceptualization, E. V. ; methodology, E. V. , M. C. -B. and M. R. ; formal analysis, M. C. -B. ; resources, E. V. ; writing-original draft preparation, M. C. -B. ; writing-review and editing, E. V. ; supervision, E. V. ; funding acquisition, E. V. All authors have read and agreed to the published version of the manuscript. Funding: This research was supported by ANR-11-IDEX-0005-02 Laboratory of Excellence IN-FLAMEX and Association François Aupetit. EV was a recipient of an Individual Fellowship Marie Sklodowska-Curie grant from the European Commission Research Executive Agency. The funders had no role in the design of the study and data collection, analysis, or interpretation, or in the writing of the manuscript. Institutional Review Board Statement: The animal study protocol was approved by the local Ethics Committee and the French ministry of Research (APAFIS#23855-2020012916328162, Paris, France, 17 April 2020).
For bar and linear graphs, values are given as mean ± SEM. Data represented in violin plots show median ± quartiles. Statistical analyses were performed using the two-way ANOVA test, followed by a Bonferroni post hoc test. Significant differences were recorded as * p < 0. 05, ** p < 0. 01, *** p < 0. 001, **** p < 0. 0001, when compared to day 0 (D0); and # p < 0. 05, ## p < 0. 01, #### p < 0. 0001, when compared female vs. male at each time point.
Author Contributions: Conceptualization, E. V. ; methodology, E. V. , M. C. -B. and M. R. ; formal analysis, M. C. -B. ; resources, E. V. ; writing-original draft preparation, M. C. -B. ; writing-review and editing, E. V. ; supervision, E. V. ; funding acquisition, E. V. All authors have read and agreed to the published version of the manuscript. Funding: This research was supported by ANR-11-IDEX-0005-02 Laboratory of Excellence IN-FLAMEX and Association François Aupetit. EV was a recipient of an Individual Fellowship Marie Sklodowska-Curie grant from the European Commission Research Executive Agency. The funders had no role in the design of the study and data collection, analysis, or interpretation, or in the writing of the manuscript. Institutional Review Board Statement: The animal study protocol was approved by the local Ethics Committee and the French ministry of Research (APAFIS#23855-2020012916328162, Paris, France, 17 April 2020).
Patient samples Tumor tissue specimens were obtained from the breast cancer patients (n = 62, median age 57, min. 41-max. 92) who were treatment naïve and underwent oncological surgery (clinical grade I, n = 3; grade II, n = 32; grade III, n = 16; grade IV, n = 1). All tumors were histopathologically categorized as grade 3, and HR expression and HER2 amplification status were evaluated (HR + HER2 -, n = 20; HR + HER2 + , n = 15; HR -HER2 + , n = 10; HR -HER2 -, n = 17). Patient data are summarized in Additional file 1: Table  S1. Samples from histopathologically normal non-tumor breast tissue were also collected. The freshly obtained tissue samples were stored in a protective solution (RNAlater, QIAGEN, USA) and kept at -80 °C. The study was approved by our local ethical committee and informed consent was obtained from the participants.
In silico analyses The METABRIC EGAD00010000211 (Illumina HT-12 v3) normalized microarray data of breast tumors (n = 995) has been used for the analyses of gene expression correlations and prognostic assessments  [24]. SOFT file for Illumina HT-12 v3 platform (GPL6947) was downloaded from Gene Expression Omnibus (GEO). Probeset IDs for EDA (NM_002026. 2) and isoforms lacking the EDA domain (NM_054034. 2, NM_054034. 2) available in this platform were determined (EDA: ILMN_1778237, isoforms lacking EDA domain: ILMN_1675646, ILMN_2366463) using the SOFT file. M2 macrophage fractions of each sample in METABRIC cohort have been calculated using CIBERSORT Web tool with absolute mode  [25]. Samples with deconvolution p value less than 0. 05 were eliminated to filter out the results with a poor "goodness of fit.
Polarization assay Chamber slides (BD) coated with fibronectin (Sigma) or Matrigel (Corning) were used. Monocytes were seeded and then incubated for 16 h with the CM obtained from the breast cancer cell lines. Thereafter, slides were fixed in 4% paraformaldehyde for 30 min, treated with 0. 1% Triton X-100 (Sigma), and blocked with 10% BSA (Sigma). The cells were stained with Phalloidin-iFluor 488 (1:1000, Abcam) and DAPI (300 nM, Sigma). The morphological polarization of cells was analyzed by fluorescence microscopy and the images were processed (ImageJ, NIH, USA). The polarization was assessed according to the images of actin cytoskeleton stained with phalloidin. A polarization index was calculated on ImageJ software where an operation image filter was applied (Directionality; Fourier Components Analysis).
Statistical analyses Statistical tests and graphical outputs were performed on GraphPad Prism 6 Software (Prism, San Diego, USA). Cutoffs for the determination of groups in Kaplan-Meier plots were chosen as the expression value at which the lowest log-rank p value is obtained within the interquartile range as described previously  [30]. Student's paired or unpaired t tests or ANOVA with post hoc analyses were used where appropriate. A "p" value lower than 0. 05 was considered as an indicator of statistical significance. Otherwise noted, all data are given as the mean ± SEM.
FN-EDA expression is associated with triple-negative breast cancer and enhanced by IL-1β The triple-negative breast cancers (TNBCs) and the basal-like breast cancers (BLBCs) are characterized by mesenchymal features  [2, 31]. Firstly, we sought to determine the expression of the FN1 gene in patient-derived tumor specimens. Compared to the non-tumor breast tissue, the expression of all transcriptional variants of the FN1 gene (total fibronectin) was higher in the tumors (Fig. 1A ). When the data were distributed according to the HR and HER2 status of the patients, no difference was found in total fibronectin levels; however, FN-EDAcontaining variants were significantly upregulated in the triple-negative tumors compared to the HR + samples (Fig. 1A ). Analysis of an international cohort database of invasive breast cancers revealed that higher expression of FN-EDA variants significantly associated with decreased overall survival (Fig.
Triple-negative breast cancer-derived factors and FN-EDA contribute to inflammatory modulation in macrophages CD163 + CD206 + macrophages have been classified as belonging to the M2-subtype, which favors tumorigenesis and cancer progression  [35]. Although, the macrophages generated here are not expected to completely represent TAMs as in vitro conditions used cannot fully recapitulate the TME. Nevertheless, activation of STAT3 pathway is a signature of the M2 phenotype and TAM differentiation  [36, 37]. By using the international cohort database, expression of M2-related genes could be associated with FN-EDA mRNA levels in invasive breast cancers (Fig. 3A ). As expected, in TNBC tumor sections, TAMs were localized in the FN-EDA-rich matrix and pSTAT3 (Tyr705) was detected in the CD68 + macrophages (Fig.
Acknowledgements We thank the vaccinees and clinical staff for participating in and running the clinical trials essential for this study, especially  Fay Nugent ,  Jee-Sun Cho ,  Yrene Themistocleous ,  Thomas Rawlinson ,  Alison Lawrie ,  Ian Poulton ,  Rachel Roberts ,  Iona Taylor ,  Sumi Biswas ,  Julie Furze ,  Baktash Khozoee ,  Nicola Greenwood ,  Saumu Ahmed ,  Florence Milando , and  Neema Balige. We also thank  Jenny Reimer  and  Cecilia Carnot  at  Novavax  for providing the Matrix-M TM adjuvant,  Federica Cappuccini  for guidance developing the T cell flow cytometry assay,  Robert Hedley  and  Vasiliki Tsioligka  from the  Sir William Dunn School of Pathology Flow Cytometry Facility  for assistance with sample acquisition and training, and the qPCR team on the  NCT04009096  and  NCT04201431  trials ( Duncan Bellamy ,  Hannah Davies ,  Francesca Donnellan ,  Amy Flaxman ,  Reshma Kailath ,  Rebecca Makinson ,  Indra Rudiansyah , and  Marta Ulaszewska ).
CMN was supported by a  Sir Henry Wellcome Postdoctoral Fellowship  ( 209200/Z/17/Z ). SJD was supported by a  Wellcome Trust   Senior Fellowship  ( 106917/Z/15/Z ) and is a  Jenner  Investigator. The  NCT04009096  trial was funded by the  European Union 's  Horizon 2020 research and innovation program  under grant agreement  733073  for MultiViVax. The  NCT04201431  trial was funded by the  Wellcome Trust Malaria Infection   Study in Thailand (MIST) program  [ 212336/Z/18/Z ]. The DBPRII clinical trial was also supported in part by the  UK Medical Research Council (MRC)  [ G1100086 ] and the  NIH Research (NIHR) Oxford Biomedical Research Center (BRC). The views expressed are those of the author(s) and not necessarily those of the  NHS , the  NIHR  or the  Department of Health. Development of PvDBPII as a vaccine candidate was supported by grants from the  Biotechnology Industry Research Assistance Council (BIRAC), New Delhi  and  PATH Malaria Vaccine Initiative.
MVDP was supported by grants from the  Bill and Melinda Gates Foundation and Department of Biotechnology (DBT), Government of India. This work was also supported in part by grants from  Agence Nationale de Recherche to CEC  ( ANR-18-CE15-0026  and  ANR 21 CE15-0013-01 ). CEC is supported by the  French Government 's  Laboratoire d'Excellence " PARAFRAP " ( ANR-11-LABX-0024-PARAFRAP ).
]). In brief, two Phase I/IIa vaccine efficacy trials (NCT04009096 and NCT04201431) were conducted in parallel at a single site in the UK (Centre for Clinical Vaccinology and Tropical Medicine, University of Oxford). NCT04009096 was an open label trial to assess the ChAd63 and MVA viral-vectored vaccines encoding PvDBPII (VV-PvDBPII), while the NCT04201431 trial assessed the protein vaccine PvDBPII in Matrix-M™ adjuvant from Novavax (PvDBPII/M-M). NCT04009096 viral vectors were administered at 0, 2 months (VV-M) or in a delayed dosing regimen (0, 17, 19 months; VV-D). For NCT04201431, the protein/adjuvant was administered monthly (0, 1, 2 months; PA-M) or in a delayed dosing regimen (0, 1, 14 months; PA-D). A subset of vaccinees from the protein/adjuvant delayed dosing regimen returned for an additional booster at 19 months (PA-DB).
ChAd63-PvDBPII was administered at a dose of 5×10 10 viral particles, MVA-PvDBPII at 2×10 8 plaque forming units, and PvDBPII protein at 50μg mixed with 50μg Matrix-M TM. Delayed regimens were due to trial halts during the pandemic. Eligible vaccinees were healthy, Duffy-positive, malaria-naïve adults, aged 18 to 45 years. Trials were approved by the UK National Health Service Research Ethics Services (REC; references 19/SC/0193 and 19/SC/0330) as well as by the UK Medicine and Healthcare products Regulatory Agency (MHRA; reference CTA 21584/0414/001-0001 and CTA 21584/0418/001-0001). All vaccinees gave written informed consent. This study also includes analyses of samples from a further Phase Ib clinical trial with Plasmodium falciparum vaccine candidate RH5. 1 (50µg) in Matrix-M™ adjuvant (50µg) in malaria-endemic setting in Tanzania (NCT04318002).
Study design PERFUSE (NCT03662919) is a long-term, non-interventional, multicentre study. The study was submitted to the Committee for the Protection of Persons (CPP) SUD-EST II and was approved on 21 March 2018 (ID-RCB). Patients receiving SB2 as routine therapy, prescribed at physician discretion independently of study inclusion, were enrolled between June 2018 and July 2019 and were followed for 24 months at 21 specialist sites (12 gastroenterology and 9 rheumatology) across France. Findings from the rheumatology sites are reported in this article. Adults aged !18 years with a physician-confirmed diagnosis of RA, PsA or axSpA and who were either IFX naı ¨ve or had received IFX ref or IFX bs prior to being initiated on SB2  [6]  after September 2017 were enrolled into PERFUSE. (Other than SB2, the only other IFX biosimilar available for prescription during the study period was CT-P13.
) Patients who were not expected to be followed up at the same rheumatology clinic for 2 years after SB2 initiation; patients with a primary diagnosis of psoriasis, rheumatoid juvenile arthritis, uveitis or hidradenitis suppurativa; and women of childbearing potential intending to become pregnant during study follow-up were excluded. The switch was completely independent from study participation. The protocol was non-interventional and did not influence standard clinical practice. There were no protocolspecified assessments or procedures (including treatment adjustment). Switch was not mandatory in France. Patients and/or clinicians were able to refuse switch/continue reference/receive any other therapies according to Institution/local practice and standard of care. Clinical data were captured retrospectively and/or prospectively from patient records.
Effectiveness and safety assessments All data in PERFUSE were captured as part of routine clinical practice. As a non-interventional study, outcomes were measured according to the usual rhythm of patient visits, with flexibility at period milestones. For this analysis, outcomes were reported for three time points: baseline (time of SB2 initiation), and at month 6 (62) and month 12 (62) post initiation. The primary outcome measure of the study was SB2 treatment persistence from baseline to month 12. Patient characteristics at initiation of SB2 (age, gender, BMI, disease history and status, previous biologic treatments and treatments at the time of enrolment) were recorded, and outcomes related to the effectiveness, immunogenicity and safety of SB2 were assessed over 12 months. Treatment effect (i.
e. effectiveness)  [7]  was assessed via disease scores in routine use at each study site, including DAS28  [8, 9]  for RA and PsA and BASDAI  [10]  for PsA and axSpA, and by disease status (high/low disease activity or remission). DAS28 remission is defined as a score 2. 6. Low disease activity (LDA) is a score >2. 6 to 3. 2 according to DAS28 and a score <4 according to BASDAI. High disease activity (HDA) is a score >3. 2 according to DAS28 and a score !4 according to BASDAI. Safety outcomes include treatment-emergent adverse events (TEAEs) and serious adverse events (SAEs). All clinical and laboratory adverse events (AEs) were coded using Medical Dictionary of Regulatory Activities (MedDRA 24. 1). Investigators specified the reasons for discontinuation of SB2. Immunogenicity data were collected only from centres that routinely gathered these data, and immunogenicity was determined based on the detection of serum anti-drug antibodies (ADAs) using the Lisa Tracker ELISA kits (Theradiag, Croissy-Beaubourg, France)  [11].
Statistical analysis The 'all enrolled patients' population is defined as all eligible enrolled patients who had received at least one infusion of SB2 (i. e. infusion documented in the PERFUSE database). Baseline is defined as the date of SB2 initiation. Kaplan-Meier (KM) techniques were used to analyse the primary outcome measure (i. e. the proportion of patients who were still treated with SB2 at month 12). KM estimates of the quartiles (quartile 1, median, quartile 3), corresponding 95% CI and range (minimum, maximum) are presented. Given that disease scores were assessed and captured only at baseline and study months 6 and 12, no imputation/replacement of missing values was performed. Continuous variables are reported as the mean, standard deviation, minimum, 25th centile (quartile 1), median, 75th centile (quartile 3), maximum and 95% two-sided CIs, where appropriate.
Categorical variables are summarized as frequencies and percentages. Proportions are presented with 95% two-sided CIs. Disease remission and LDA are defined as a DAS28 score 2. 6, and >2. 6 to 3. 2, respectively, and as a BASDAI score <4. 0. SAS v. 9. 4 (Cary, NC, USA) was used in the statistical analysis.
The PERFUSE study has limitations related to variabilities in clinical practices in the real-world setting, including missing data. Data in Table  2  were based on a small sample size. When missing data points were queried, some sites confirmed that disease scores are not calculated. In clinics in France, it is not mandatory to report disease scores. In addition, DASs by indication were as reported from the clinical practices. Although the AS DAS has been shown to have a better discriminatory capacity and sensitivity to change than BASDAI  [22] , the clinics included in this study routinely use BASDAI disease activity scores. Another limitation is that there were no control groups of patients continuing on reference or other IFX bs, because all eligible patients had been transitioned to SB2.
A deeper understanding of HIV-1 transmission and drug resistance mechanisms can lead to improvements in current treatment policies. However, the rates at which HIV-1 drug resistance mutations (DRMs) are acquired and which transmitted DRMs persist are multi-factorial and vary considerably between different mutations. We develop a method for the estimation of drug resistance acquisition and transmission patterns. The method uses maximum likelihood ancestral character reconstruction informed by treatment roll-out dates and allows for the analysis of very large datasets. We apply our method to transmission trees reconstructed on the data obtained from the UK HIV Drug Resistance Database to make predictions for known DRMs. Our results show important differences between DRMs, in particular between polymorphic and non-polymorphic DRMs and between the B and C subtypes.
The fitness was measured as a ratio between transmission rates of hosts infected by drug-resistant strains and transmission rates of hosts infected by sensitive strains. They applied this model to the data from the Swiss HIV cohort study. They reconstructed a maximum likelihood tree for 5638 pol-gene sequences from the Swiss HIV cohort study and 4284 closely related sequences from the Los Alamos HIV database. On this tree, for each of the 15 major DRMs present in the Swiss cohort sequences, they identified transmission clusters of up to 250 sequences each, containing > 80% of Swiss sequences and at least one sequence with the mutation. Kühnert et al. [9]  estimated the model parameters on all the clusters for each mutation separately in a Bayesian setting. To account for the fact that DRMs appear under antiretroviral (ARV) selective pressure, they put the rates of state change (from sensitive to resistant and vice versa) to zero before significant usage of the related drug(s) in Switzerland.