dataesr/scientific-paragraphs-categorization huggingface dataset:
Thus, our work reveals the clinical interest of defining CAF subsets content in LNs at diagnosis. Source data provided in Source Data file, with R scripts used. areas in representative invaded LNs were further analyzed. Images were aligned using elastic transformation from Fiji software plugin (bUnwarpJ). This plugin uses landmarks manually defined on hematoxylin & eosin staining of the sections to compute the optimal correlation between images and alignment at cellular level. Images were divided into tiles of 225 µm 2 to mimic the approximate size of one fibroblast and each tile was annotated according to the position in the section. Aligned and annotated images of the CAF markers were then submitted to color deconvolution and the intensity of each DAB staining was measured by densitometry analysis using ImageJ software.
5 million paired-end reads. Read length was 100 bp. Reads were mapped on reference human genome (hg19/GRCh37 from UCSC genome release) using Tophat_2. 0. 6 algorithm with the following parameters: global alignment, no mismatch in seed alignment (of size 22), three mismatches in read length. Quality control was performed using FastQC software and duplicates were removed using Samtools rmdup. Gene expression quantification was performed using HTSeq-count and featureCounts (implemented in Bioconductor R package Rsubread (1. 18. 0)). Only genes with at least one read in 5% of all samples were kept for further analyses. Normalization was performed with DESeq2 R package (1. 8. 2) method. Analysis strategy includes unsupervised analyses such as PCAs and HC, as well as paired differential expression analyses (done with DESeq2 bioconductor package).
To assess CXCL12 involvement in CAF-S1 attraction of BC cells, 10 5 CAF-S1 were plated as described above, after 48 h of transient silencing (see 'Silencing of CXCL12, CXCR4 and transient transfection'). BC cell number was increased to 3 × 10 5 cells per insert and plated in triplicates. Three independent experiments including at least two different CAF-S1 cell lines per BC cell type were performed. At the end of the experiment, the remaining cells in the upper side of the Transwell device were gently removed with cotton swabs moistened with PBS. Migrating cells at the bottom side of the Transwell device were fixed and stained with crystal violet for 30 min and then counted in seven different representative fields per insert (X5 objective, Zeiss Axioplan microscope, AxioCamERc 5s, manual counting on Fiji software) and averaged per condition.
When we adjusted the migration to proliferation rate, we divided the migration capacity by the fold change in tumor cell proliferation in presence/absence of CM from CAF subsets. Cell exclusion zone assay. For cell exclusion zone assay, Ibidi culture inserts (#80209) were added to 12-well plates (one insert per well) and 10 4 CAF-S1 or 10 4 CAF-S4 were plated per chamber of each insert, in duplicates. After cell attachment, inserts were gently removed, delicately washed with PBS and 2 ml of medium was added to each well. Time-lapse videos were then immediately acquired with an inverted motorized Leica video-microscopes, equipped with motorized stage, 37 °C incubator and CO 2 controller (Leica DMi8 with a Retiga R6 camera and illumination by Lumencor SOLA SE 365). The automated imaging system was controlled by the software Metamorph (Universal Imaging).
Transmission images were acquired every 15 min until 50 h and one position per insert (hence two per condition) was taken with a 5× objective as it encompassed 80% of the cell-free zone. For data analyses, Fiji software was used. In each position, manual tracking of 40 CAF-S1 and CAF-S4 cells per condition positioned on the free edges were tracked over 24 h, taking into consideration the first image of each hour. Velocity (distance of migration divided by the interval time) and direction (absolute value of sin(α), where α is the angle between the velocity and the initial cell-free zone borderabsolute because cells were taken from both sides of the cell-free zone) were calculated for each successive pair of time points for each cell. Means per cell over the global tracking are shown. Persistence of cell trajectory, defined as the ratio d / l where l is the contour length of the total trajectory and d the direct endto-end distance, was also calculated per cell over the same 24 h.
Two different CAF-S1 and CAF-S4 pairs were tested in two independent experiments. CAF spheroids and invasion assay. For spheroid invasion assays, CAFs were trypsinized and resuspended at a concentration of 4 × 10 5 cells/ml. Atotal of 20 μl drops were pipetted down on a 10-cm dish lid. Lids were then gently put back on the plates filled with medium to humidify the system. After 4 days, CAF spheroids -formed in the hanging drops-were carefully transferred into 2. 5 mg/ml collagen solution drops (Corning, #354249) in the center of 6-well plates. At least six different spheroids per CAF were embedded in collagen and further analyzed. After polymerization, 0. 5% FBS medium was added to the wells. Spheroids were imaged 3 days after inclusion on a Nikon Eclipse TE300 microscope with a 4× objective equipped with a Nikon DS-Fi1 camera and invasion was assessed with Fiji software as an invasion index defined as the total area covered by CAFs (encompassing single cells escaped from the spheroid and the spheroid) divided by the area of the spheroid core center.
Three CAF-S1 and CAF-S4 pairs were tested in three independent experiments. For time-lapse imaging, time-lapse videos were immediately acquired after collagen polymerization with an inverted motorized Leica videomicroscopes, equipped with motorized stage, 37 °C incubator and CO 2 controller (Leica DMi8 with a Retiga R6 camera and illumination by Lumencor SOLA SE 365). The automated imaging system was controlled by the software Metamorph (Universal Imaging). Transmission images were acquired every 15 min until 42 h with a 5× objective to encompass the full spheroid. Videos were mounted with eight frames per second. Collagen contraction assay. To assess force-mediated collagen contraction, 3 × 10 4 CAFs were embedded in 100 μl of a 2. 5-mg/ml collagen solution (Corning, #354249) and seeded in triplicates in 96-well plates.
After polymerization, culture medium was added on top of the gels and in the surrounding empty wells to limit evaporation. To assess DAPT (Sigma, #D5942), BLEBBISTATIN (Sigma, #B0560) and Y27632 (STEMCELL Technologies, #72302) impact on CAF contractility, 10 μM of each drug was added to the medium, DMSO as control. Gel contraction was assessed 4 days after plating: plates were scanned (EPSON Perfection V700 Photo scanner) and quantification was performed on Fiji software. Percentage of contraction was calculated using the formula: 100 Area well ÀMean Area Gel ð Þ 3replicates Area well. Six CAF-S1 and CAF-S4 pairs were tested in four independent experiments. For DAPT experiments, three independent experiments were performed, including four different CAF-S4 cell lines. Traction force microscopy.
Images of the relaxed gels were acquired after removing the cells with trypsin. Beads images (with and without the cells) were first aligned using the ImageJ plugin "Align slices in stack". Bead displacements (with respect to the resting state after trypsination) were measured and converted to cell traction stresses using the open source Fourier transform traction cytometry Fiji plugins (available at https://sites. google. com/site/ qingzongtseng/tfm or org. insb. bib. cnrs. fr/10. 1016/bs. mcb. 2014. 10. 008) Images were processed with ImageJ software. Further analyses were performed with Matlab (MathWorks, Natick, MA). To quantify cell contractility, we measured the strain energy (SE) which is the total energy transferred from the cell to the elastic substrate, the strain energy density which is the energy per unit area (SE divided by the cell area) and the mean traction stress amplitude which corresponds to the average stress per cell.
Collagen was visualized by second harmonic generation (SHG) using the excitation wavelength 910 nm. 3D stacks were acquired at a step size of 1 µm intervals to encompass one whole cell. Images were further analyzed with Fiji software. All collagen images were processed in the same way: light was adjusted (min = 0 and max = 50), thresholded (min = 0, max = 30), converted to mask, smoothed, despeckled and collagen area was measured on all slices of each 3D-stack. Collagen density around each cell was then computed as d ¼ P n i¼1 Δz surf :coll sliceðiÞ V stack , where Δz is the step between two slices in the stack, n the number of slices in the stack, V stack the volume of the stack and surf. coll slice(s) the area covered by collagen in the slice i of the stack (Fiji output). Proliferation assays.
At least two independent experiments were performed for each setting and each BC cell line (one CAF pair for CAF-S1 versus CAF-S4 impact in two independent experiments; three CAF-S1 in three independent experiments for CXCL12 involvement; two CAF-S1 in two independent experiments for CXCR4 involvement; at least three CAF-S1 in at least three independent experiments for TGFβ-R involvement). Tumor cell density, E-cadherin in BC cells, F-actin and Vinculin in CAF. For tumor cell density and assessment of staining in CAF subsets, quantifications were performed in two steps on FiJi software. (1) Masks were manually drawn on each merged image to either keep tumor cell zones of CAF zones according to the analyses. Masks were then applied to the corresponding single channel (Dapi, Ecadherin, F-actin or Vinculin depending on the analyses) images.
8 NA oil immersion objective. 3D stacks were acquired at a step size of 10 µm intervals to encompass all invading cells (initial Z set up so that membrane pores were in focus and highest Z where no MDA-MB-231-GFP cells could be detected anymore). Fluorescence channels were recorded using the excitation wavelengths 405 nm (for CAF-S4), 488 nm (for BC cells) and 561 nm (for CAF-S1). At least four stacks were acquired per insert, x and y = 566. 8 μm; z = 200 μm. Images were further analyzed with IMARIS software to retrieve the distance of invasion of all BC cells in each stack, after modeling cells on GFP signals done with the same parameters across stacks (surface detail 2 μm; threshold absolute intensity 3. 00; option "enable splitting of touching objects" was selected; seed points diameter 15 μm; filtered on voxels above 350).
Cells were embedded in 2. 3 mg/ml collagen hydrogels (PureCol, Advanced Matrix, # 5005 diluted in MEM medium (Sigma Aldrich, # M0275) containing 0. 28% NaHCO 3 (pH = 8) to adjust the final pH to 7). MCF7-GFP or T47D-GFP targeted density was 1. 2 × 10 6 cells/ml, CAF density was 3 × 10 5 cells/ml. When DAPT (Sigma, #D5942) was used, CAF-S4 were pre-treated overnight before inclusion in collagen and a final concentration of 10 μM was added to the medium. We verified that DMSO did not interfere with BC cell velocity in the system. Time-lapse videos were then acquired with an inverted motorized Leica video-microscopes, equipped with motorized stage, 37 °C incubator and CO 2 controller (Leica DMi8 with a Retiga R6 camera and illumination by Lumencor SOLA SE 365) in a 20% O 2 environment. The automated imaging system was controlled by the software Metamorph (Universal Imaging).
Transmission and fluorescent (GFP) images were acquired every 2 h over 30 h and at least four positions per condition were recorded with a 10× objective. For data analyses, Fiji software was used. In each position, cells were manually tracked over all frames ('Manual tracking' plugin, at least 65 cells per condition). Cell velocity (distance of migration divided by the interval time) was calculated for each successive pair of time points. Means per cell over the global tracking are shown. For CAF-S1 versus CAF-S4 experiments, for each BC cell line: three independent experiments were performed, with three different CAF-S1 and CAF-S4 pairs. For DAPT experiments, for each BC cell lines: three independent experiments were performed, including two different CAF-S4 cell lines. Cytokine antibody-pair-based assay.
Cytokine antibody-pair-based assays were performed using human cytokine array kit (R&D Systems, #ARY005B) according to the manufacturer's protocol. In brief, 80,000 CAF-S1 or CAF-S4 fibroblasts were cultured alone or in presence of 80,000 BC cells (MCF7 or T47D) in 1 ml of DMEM medium in 12-well plates at 1. 5% O 2 during 48 h. Culture supernatants were next collected (CM) and centrifuged at 13,000 rpm during 10 min for eliminating debris. Array membranes, previously spotted with capture antibodies by the manufacturer, were incubated with 0. 5 ml of CM overnight at 4 °C. Membranes were then washed three times with 50 ml of washing buffer at RT, and incubated with a streptavidin-horseradish peroxidase-coupled antibody (1:2000) for 30 min at RT and revealed using Chemi-Reagent Mix. The immunoblot images were captured and visualized using the ChemiDoc Imaging System (Bio-Rad) and intensity of each spot in the captured images was measured using ImageJ software.
Two spots per membrane were used to measure the levels of each cytokine. Intensity mean of the two spots-revealing each cytokine level per experimentwas reported to the intensity mean of three internal controls spotted on the membrane and assessed by the following ratio: specific intensity mean / control intensity mean, to take into consideration variation in hybridization efficiency in the different experiments. Software. Software used for the above analyses are: R (https://cran. r-project. org, R versions 3. 3. 1, 3. 4. 0 and 3. 5. 0), Fiji (ImageJ v2. 0. 0-rc-19/1. 49m, v2. 0. 0-rc-65/1. 52b), IMARIS (v8. 4. 1), Matlab. Statistical analyses. Data graphical representation and statistical analyses were done using R or GraphPad Prism environment. Barplots represent means ± standard errors of the mean (SEM).
Boxplots: box limits indicate the inter-quartile range (IQR) (25th to 75th percentiles), with a center line indicating the median. Whiskers show value ranges up to 1. 5 × IQR above the 75th or below the 25th percentiles, with outliers beyond those ranges shown as individual points. The number of independent experiments is specified in each figure legend, with at least three independent experiments, unless otherwise specified. The statistical tests used are in agreement with the data distribution: normality was first checked using the Shapiro-Wilk test and parametric or non-parametric two-tailed tests were applied according to normality. Statistical test types are indicated in figure legends. Survival analyses were carried out with survival R package by Kaplan-Meier curves (pvalues from Log-rank test) and by univariate and multivariate Cox regressions using additive hazards regression models.
Data availability RNAseq data from EPCAM + , CAF-S1 and CAF-S4 sorted from BC samples, without or with culture, generated in this study are available on European Genome-Phenome Archive platform (https://ega-archive. org) under accession number: EGAS00001003238. A source data file corresponding to all panels of the figures and supplementary figures that support the findings of this study is provided with the paper.
Acknowledgements We thank  Dr. V. Mieulet  and  G. Gentric  for critical reading of the manuscript and all members of F. M. -G. 's laboratory for fruitful discussions. We are grateful to  Dr. V. Becette ,  M. Toutain  and  A. Duchenne  for providing access to some tumor samples. We thank  Z. Maciorowski ,  S. Grondin  and  A. Viguier  from the  Flow cytometry platform at Institut Curie (IC). We also thank  R. Leclere ,  E. Martel  and  A. Nicolas  from the experimental pathology platform (IC);  S. Baulande ,  S. Lameiras ,  V. Raynal ,  M. Bohec  and  P. Legoix  from the  NGS platform (IC)  for their help and advice. We acknowledge the Cell and  Tissue Imaging  ( PICT-IBiSA) and Nikon Imaging Centre (IC ) member of the  French National Research Infrastructure France-BioImaging  ( ANR10-INBS-04 ).
In particular, we thank  O. Renaud  and  O. Leroy  ( IC ) for technical assistance with microscopy and IMARIS software. We thank  K. Laud  for her help with spheroids experiments. F. P. was supported by funding from  Ecole des Mines de Paris  and from the  Foundation ARC (Association pour la Recherche sur le Cancer ). F. M. -G. and C. B. are supported by  Institut National de la Santé et de la Recherche Médicale (Inserm). Y. K. was funded by the  Foundation pour la Recherche Médicale (FRM) ,  SIRIC (INCa-DGOS-4654)  and  INCa  ( INCa-DGOS-9963 ). M. C. P. was supported by  FRM  ( ING20160435436 ) and  Inserm  ( EQ2016-01 ). The experimental work was supported by grants from  Ligue Nationale Contre le Cancer (Labelisation) ,  Inserm ,  Institut Curie  ( PIC TME/T-MEGA  and  PIC3i CAFi), ICGex  ( ANR-10-EQPX-03 ),  SIRIC (INCa-DGOS-4654)  and  INCa  ( INCa-DGOS-9963 ,  INCa - 2016-166 ,  INCa-11692, INCa-DGOS-Inserm-12554 ) and ARCS.
Study design and population: From 2013 to 2015, we prospectively conducted a single-center survey on mHLA-DR monitoring in a large cohort of patients admitted to the surgical ICU. The present cohort was listed from the database when they had at least one measurement of mHLA-DR performed within the first 3 days following ICU admission. Four main clusters of life-threatening conditions were defined according to the motif of admission: 1/ Sepsis, defined by the criteria of the American College of Chest Physicians/ Society of Critical Care Medicine;  12  2/ Neurologic disorders, related to acute brain injury such as hemorrhagic or ischemic stroke; isolated severe brain trauma; post-neurosurgery; 3/Post-surgery, related to major abdominal surgery, orthopedic surgery or others; 4/ Miscellaneous etiologies including respiratory failure, hemorrhagic shock from gastrointestinal bleeding or obstetric emergencies.
Circulating Monocyte HLA-DR measurements (mHLA-DR): The quantification of the expression of HLA-DR on monocytes was assessed using the number of antibodies per cell (AB/C) by flow cytometry ( FACS Canto II instrument , FACS Diva software , Becton Dickinson , San Jose, CA USA) as previously described  8  (see detailed protocole in the supplementary appendix). In our center, the median and IQ range of mHLA-DR expression in healthy people (n = 13) was a median log mHLA-DR value of 10. 6 (IQR: 10. 5 -10. 7). The first blood sample and measurement of mHLA-DR was performed within the first 3 days after admission. The 2 nd measurement of mHLA-DR was obtained at fixed days (Monday or Thursday) until the patient's discharge or death. Only patients having two measurements were analyzed to investigate the relation with ICU-acquired infection.
Statistical analysis: Baseline characteristics (age, sex, comorbidities) were collected on admission. SAPS II and SOFA scores were computed after 24hrs. The data were described as number and percentage for categorical variables and median (interquartile range (IQR)) for continuous variables. Comparisons relied on the Fisher exact test or χ2 test for categorical data and the Kruskal-Wallis or Wilcoxon test for continuous data. Because of non-linearity, all the mHLA-DR values were log-transformed. Age, SAPS II score and SOFA score were categorized based on the median value. A p-value of less than 0. 05 was considered statistically significant. The association between mHLA-DR measurements and outcomes was assessed using adjusted Fine and Gray subdistribution competing risk models. 16 For that purpose, first, the subdistribution hazard of mHLA-DR measurements on death at day 28 took into account the competing ICU discharge.
As previously reported, mHLA-DR measured early after admission was lower than control values in healthy subjects for the whole cohort and the 4 clusters of patients. The lowest values were observed both in "sepsis" and "post-operative" patients. If mHLA-DR expression decrease is associated with day 28 mortality, it does not improve the prediction observed with SAPS II. Few data have shown relationship between the amplitude of mHLA-DR reduction and mortality. 8, 10 In contrast with to previous studies, our analyses were provided after adjustments for confounding factors. However, as for previous publications, our conclusions might be limited by the fact that patients dying before day 4 were not enrolled. The expression of mHLA-DR seems to be a reasonable approach as tested in the present study.
Statistical analysis. All statistical analyses were performed using GraphPad Prism 7 (GraphPad) and SAS version 9. 4 (SAS Institute Inc. ). Quantitative variables were compared using the Mann Whitney U test and a P-value < 0. 05 was considered as statistically significant. Linear regression was performed, and slopes were compared using Spearman correlation test. Because selected human biological samples (peripheral blood or heart tissues samples taken from acute myocarditis patients) were of very limited availability and because number was not extendable; we did not have prior data to calculate it and we did not a priori calculate the number of subjects to include in the present study.
Acknowledgements The authors thank the staff at the collaborating clinical sites and references laboratory. We are grateful for  Nora Chapman  and  Steven Tracy  ( University of Nebraska Medical Center, USA ) for helpful discussions. Funding: This work was supported by grant from the  "Fédération Française de Cardiologie" (FFC  grant  2019  " Etude CardioVir ") and by a local research grant for emerging research teams from the  University of Reims Champagne-Ardenne (URCA) , France. M. G. is supported by a  University of Reims Champagne-Ardenne (URCA)  PhD grant. M. G. was supported by  Boehringer Ingelheim  and the  National Institutes of Health  grants funded the author to present a part of this work (Poster abstract number:  x2065-7588-50505 ,  P39-2 ) at the 38th American Society for Virology (ASV) congress, in July 2019, at the  University of Minnesota, Minneapolis, USA.
Study design and population The EDEN mother-child study is a prospective cohort designed to assess pre-and postnatal determinants of child health and development  [24]. In brief, 2002 pregnant women (< 24-weeks' gestation) aged 18-44 years were recruited between 2003 and 2006 in two university hospitals located in Nancy and Poitiers, France. Exclusion criteria were multiple pregnancies, history of diabetes, inability to speak or read French and any plan to move out of the region within the next 3 years. A total of 1903 children were born alive and then followed up periodically by postal questionnaires and clinical examinations. At age 2 and 5, respectively 1436 and 1195 parents (usually the mother) completed a postal questionnaire, the data of which were used to construct the obesity-related behavior clusters of children.
Children's anthropometric and BIA measurements Anthropometric and BIA data were collected during the clinical examination that took place at the Nancy and Poitiers university hospitals when the child was 5 years old (mean 5. 6 years, standard deviation 0. 2 years). Trained investigators using standard procedures performed measurements. The children's heights were measured as they stood barefoot, their weights while they wore light underwear and skinfold thickness at the left triceps and subscapular sites, with a Holtain skinfold caliper. Height and weight were measured twice and skinfold thickness three times. Children underwent BIA measurements twice, with a single-frequency impedance analyzer (Model BIA 101, Akern-RJL, Italy) after 5 min of rest and with an empty bladder  [25]. Body fat percentage was estimated from the mean of each anthropometric and BIA measurements and calculated with the equation of Goran et al.