dataesr/scientific-paragraphs-categorization huggingface dataset:
Sera were collected 6 h (D) or 3 d (E) after infection for ELI SA, and survival was monitored every 12 h (F). These experiments were repeated once with similar results, and data were analyzed by Student's t test and are presented as mean ± SD (D and E) or log-rank (Mantel-Cox) test (F; *, P < 0. 05; **, P < 0. 01; ns, not significant). RPMI 1640 medium containing 10% FBS (HyClone) and 50 ng/ml Flt3L (R&D Systems) and cultured for 5-7 d. Every 2 d, half of the media were replaced by fresh RPMI containing 10% FBS and 50 ng/ml Flt3L. Before use, suspension cells were sorted by FACS (Aria II; BD), and CD11c int /B220 + / CD11b -pDCs were collected. Splenic pDCs were prepared as described previously  (Vremec et al. , 2000). In brief, spleens were minced and digested with collagenase D (1 mg/ml; Sigma-Aldrich) in RPMI 1640 at 37°C for 30 min.
(C) 8-wk-old WT and Tet2 -/-littermates (n = 9) were intravenously infected with VSV (5 × 10 6 pfu) and monitored every 12 h for survival and weight loss. This experiment was conducted twice, and log-rank (Mantel-Cox) test was used for statistical analysis (data are presented as mean ± SD; *, P < 0. 05). struction. cDNAs were reverse transcribed from 0. 5 µg total RNAs by PrimeScript RT-PCR kit (Takara Bio Inc. ). Realtime PCR was performed with PrimeScript RT reagent kit (Takara Bio Inc. ) on an ABI 7900HT Fast Real-time PCR System. Relative expression levels of target genes were quantitatively normalized against the expression of GAP DH using the ΔΔCT method. All real-time PCR primers used in this study are described in Table  S2.
Microarray analysis Total mRNAs (1 µg) were obtained from Flt3L-differentiated WT and CXXC5 -/-pDCs either untreated or treated with 2 µg/ml CpG-A for 3 h and analyzed by Agilent Technologies Gene Expression Hybridization kit according to the manufacturer's protocols. Agilent Technologies Feature Extraction software (version 11. 0. 1. 1) was used to analyze acquired array images. Quantitative normalization and subsequent data processing were performed with the GeneSpring GX v12. 1 software package (Agilent Technologies). GEO accession no. is GSE79643.
Hydroxymethylated dnA immunoprecipitation and bisulfite sequencing Genomic DNAs were purified and fragmented by sonication to generate DNA fragments ranging from 200 to 500 bp. Sonicated DNAs (4 µg) were denatured and incubated with control IgG or anti-5hmC (0. 2 µl) at 4°C overnight. Antibody-DNA complexes were captured by protein A beads preincubated with salmon sperm DNA. Immunoprecipitated DNAs were purified with a PCR purification kit and quantified by real-time PCR against input DNAs. 500 ng of genomic DNAs prepared by phenol-chloroform extraction and ethanol precipitation, and treated with RNase A for 15 min at 37°C, were used for bisulfite conversion in an Epitech bisulfite kit (QIA GEN) according to the manufacturer's instruction. Bisulfite-sequencing primers were designed according to MethPrimer software.
Flow cytometry Fluorochrome-labeled antibodies for CD3 (145-2C11), CD8 (53-6. 7), B220 (RA3-6B2), CD11c (N418), mPDCA1 (ebi927), Ly6C (HK1. 4), and MHC-II (KH95) were from eBioscience. Antibodies for CD4 (GK1. 5), Ly6G (IA8), and CD11b (M1/70) were purchased from BD. All antibodies were tested for their specificity with respective isotype controls. Cell-surface staining was performed by incubating cells with specific antibodies for 30 min on ice and washing with MACS buffer twice. All samples were processed with a Fortessa flow cytometer (BD), and data were analyzed with FlowJo software (Tree Star).
This experiment was repeated three times, and similar results were obtained. The data are presented as mean ± SD. (D) Splenic pDCs (10 6 cells/ml) purified from WT and CXXC5 -/-mice (n = 4) were infected with HSV-1 for 24 h. Production of IFNα/β was measured by ELI SA. This experiment was repeated twice, and representative data (mean ± SD) are shown (*, P < 0. 05, analyzed by Student's t test). (E) WT and CXXC5 -/-mice (n = 6) were either uninfected or i. v. infected with HSV-1 (5 × 10 6 pfu/mouse) for 9 h, and splenocytes were sorted by FACS. Total mRNA was prepared from 10 5 pDCs (CD11c int B220 + /PDCA1 + / Siglec-H hi ) and quantified by real-time PCR. This experiment was repeated twice, and representative data are shown (***, P < 0. 001, analyzed by Student's t test). (F) WT and CXXC5 -/-mice (n = 3) were either untreated or treated with i.
AcknoWLedGMents We are grateful to  Prof. Gang Wei  and  Dr. Ying Li  from  Institute of Computational Biology  for their assistance in ChIP assay. We are also indebted to  Bangguo Qian  for his technical support in confocal microscopy. This study was supported by the  Ministry of Science and Technology of the People's Republic of China Key Development and Research Project  ( 2016YFA0502102  to  H. Xiao ) and National Science and Technology 973 project ( 2014CB541902  to  H. Xiao  and  N. Shen ), the  National Natural Science Foundation of China  (grants  31470847  and  91542206  to  H. Xiao ), and the  Strategic Priority Research Program  of the  Chinese Academy of Sciences  (grant  XDB19000000 ). The authors declare no competing financial interests.
Of these clones, twenty-four were selected randomly and sequenced using the GS FLX system. A summary of the assembly metrics of the twenty-four metagenomic inserts with antimicrobial activity is provided in Supplementary Table  S1. The full fosmid sequences are available in the GenBank database under the BioProject PRJNA264884; BioSample IDs: SAMN063330279 to SAMN063330302. Prediction of AMPs from the identified open reading frames (ORFs) yielded a total of 181 AMPs. A peptide library consisting of 135 of these AMPs (≤25 amino acids (AAs)) was synthesized and screened for antimicrobial activity using the SPOT technique (synthesis of large numbers of peptides on marked spots on cellulose membrane sheets allowing for subsequent highthroughput screening). 16 Twenty-five active AMPs were identified in this screen (Supplementary Table  S2 ).
Candidates, Lynronne-1 (19 AAs: LPRRNRWSKIWKKVVTVFS-NH 2 ), Lynronne-2 (20 AAs: HLRRINKLLTRI-GLYRHAFG-NH 2 ) and Lynronne-3 (20 AAs: NRFTARFRRTPWR LCLQFRQ-NH 2 ) encoded in fosmid clones SABPL29H11, SABPL5A1 and SABPL12(2)A3, respectively and were selected for further analysis due to their broad spectrum antibacterial activity and lower minimum inhibitory concentration (MIC) values. The nucleotide and protein sequences of the ORFs from which they were derived are available in the GenBank database under accession numbers KY628802, KY628803 and KY628804, respectively. Sequences upstream and downstream of these ORFs are shown in Supplementary Fig. S1. The likely producers of Lynronne-1, Lynronne-2 and Lynronne-3 were identified as Prevotella ruminicola 23 (CP002006. 1), Uncultured bacterium Contig939 (KC246977.
Sequence-based screening of putative antimicrobial positive fosmid clones Fosmids with putative antimicrobial activity were sequenced using the Genome Sequencer FLX platform (454 Life Sciences) according to manufacturer guidelines. Following sequence assembly using the default parameters on the gsAssembler software v. 2. 5. 3 (Roche Life Sciences), sequences were trimmed and vector sequence were removed using BioEdit (version 7. 1. 11). 27 VecScreen on NCBI was used to search the sequences for vector contamination. ORFs were determined using NCBI's ORF finder on the NCBI blast suite (v2. 2. 28). 28  silico identification of AMPs Prediction of AMP sequences within the identified ORFs was achieved using a variety of software available at various public databases. Specifically, we used the antimicrobial peptide database,  29  the Antimicrobial Sequence Scanning System (AMPA),  30  BACTIBASE,  31  collection of antimicrobial peptides (CAMP),  18, 32  and antibacterial peptides (AntiBP).
ACKNOWLEDGEMENTS This project was funded partly by the  Cross River State Government of Nigeria , the  Life Sciences Research Network Wales ,  RCUK Newton Institutional Link Fund  ( 172629373 ), and the  BBSRC UK  ( BB/L026716/1 ). P. N. G. acknowledges  ERA NET IB2  (grant Nr  ERA-IB-14-030 ) funded through the  BBSRC  grant  BB/M029085/1. We are also grateful to  Teri Davies  for her technical assistance in setting up some experiments and to  Dr Colin Greengrass ,  Prof Andrea Brancale  and  Prof Keith Harding  for their advice. The in vivo mouse studies were carried out by  Eurofins Panlabs.
PRRSV infection was controlled in the female herd by priming gilts (quarantine) with a modified live vaccine, and boosts at regular intervals with an inactivated vaccine. Serology performed during the trial later confirmed that all piglets seroconverted by 14 weeks of age (data not shown). The same was true for Haemophilus parasuis (all pigs seroconverted by week 22), while no seroconversion was measured against Actinobacillus pleuropneumoniae, nor SIV (H1N1, H1N2 and H3N2). Taken together, these results evidenced the presence of PRDC, in compliance with both its clinical expression and the association of pathogens described by Fablet et al. in Western France  [2]. This farm was among the better half of the farms belonging to the same production cooperative (see Table  1 ), and the producer accepted his practitioner's suggestion to add PCV2 valence to the piglets' vaccination schedule and to compare two options to vaccinate concurrently against M.
Differences between groups were determined by Mann-Whitney t tests (P≤0. 05). PLS-DA analysis were performed using the mixOmics package in R. Results: Frequencies of gp140 specific CD4 T cells were not different between ET and LT. However ET showed a better quality of these cells demonstrated by a higher proportion of cytokine producing T cells compared to LT. In particular, ET were enriched in polyfunctional T cells, defined by the simultaneous detection of 2+ cytokines, dominated by IL2 production. On the contrary, LT response was paucifunctional. The different CD4 T cell profiles induced by gp140 stimulation in ET and LT was confirmed by PLS-DA analysis where these 2 groups were clearly separated. Conclusions: Our results suggest that time of ART initiation in HIV-infected children has a long-term impact on the quality but not the quantity of the host HIV-specific T-cell immune responses and also reinforced the importance of early treatment initiation.
FUnDinG This work was supported by  Institut National de la Santé et de la Recherche Médicale (INSERM) ,  University Paris Descartes  ( Sorbonne Paris Cité), University Pierre et Marie Curie (Sorbonne University ), the  Labex Immuno-Oncology  ( LAXE62_9UMS872 ), and the  Institut National du Cancer  (INCa-PLBio 2014-2017 GDSTRESS).
B-cell proliferation was monitored by CFSE (carboxyfluorescein diacetate, succinimidyl ester; Molecular Probes) labelling. Phospho-p65 was determined as follows: 1-2 × 10 5 magnetically isolated CD27+ B cells were seeded in 100 μl of medium in a 96-well plate, incubated for 1 h, and then stimulated with CD40L for 5 min. Cells were then fixed with Cytofix (Becton Dickinson, Franklin Lakes, NJ, USA) and incubated for 10 min at 37 °C. After washing, cells were stained for surface markers for 15 min in ice. Afterwards the cells were washed and permeabilized by drop-wise addition of 50 μl ice-cold Phosflow Perm Buffer III (Becton Dickinson), gentle vortexing and incubation on ice for 30 min. This was followed by two more washing steps, and staining for intracellular phospho-NF-κB p65 (Ser536). The data were acquired with BD FACS Canto II (Becton Dickinson) and were analyzed with FlowJo software version 8.
PLA on BJAB cells was analyzed using unpaired t-test. PLA on B cells was analyzed using one-way ANOVA (non parametric Kruskal-Wallis test) with Dunn post-test. NF-κB luciferase reporter assay in BJAB cells was analyzed using one-way ANOVA with Tukey post-test. Differences between marginal zone and switched memory B cells were analyzed using unpaired t-test. All analyses were performed using GraphPad Prism version 5. 00 for Windows, GraphPad Software, San Diego, CA USA; www. graphpad. com.
Acknowledgements. We thank  Andrew Thorburn  for providing BJAB TRAILR2 -/TRAILR2 + cell lines,  Marie-Christine Rio  and  Fabien Alpy  for kindly providing ErbB-EYFP constructs,  Fabio Martinon  ( University of Lausanne ) for valuable advice regarding the generation of receptor-deficient BJAB cells and  Léa Zaffalon  ( University of Lausanne ) for help in the construction of lentiviral vectors. We thank  Sylviane Muller  ( UPR 3572 Strasbourg, France ), the  GDR2588  and the  French Network for Microscopy (RTmfm)  for scientific discussions and the microscopy facility platform of  Strasbourg Esplanade  for the use of the confocal microscope. This work was supported by grants from  Agence Nationale de la recherche  ( ANR-08-PCVI-0034-01 ) (to SF and GG) and the  Swiss National Science Foundation  ( 31003A-138065  to PS).
Samples were then imaged using an IMSTAR automated fluorescent microscope (IMSTAR S. A. , France), which took ~100 images per sample. Images were loaded into CellProfiler software (Broad Institute, Harvard, USA)  42  and metadata detailing the cell type in the image was extracted from the file name. Primary detection of the cell nucleus (DAPI channel), followed by secondary detection of the cell body (F-actin channel) were optimised following which the full dataset of images was analysed by the software and a database containing a range of cell descriptors such as perimeter, area, major and minor axes, etc. was generated. For each sample, the means of these descriptors were calculated and used for generating graphs and conducting statistical analyses.
Cytokine quantification Supernatants were collected and assayed for the cytokines TNF-α, IL-12, IL-1β, CCL18, and IL-1RA by ELISA as per the manufacturer's instructions (Table  1 ). from the gels or TCP as described in the section above (Flow cytometric analysis of MR and calprotectin). Cells were then harvested, washed once with PBA and resuspended in PBA prior to running on a MoFlo Astrios EQ flow cytometer (Beckman Coulter). Analysis was carried out using Kaluza Analysis 1. 5 software (Beckman Coulter). Mean number of particles per zymosan-positive cell was calculated using the formula: (Median fluorescence intensity (MFI) of zymosan-positive cells -MFI of untreated cells)/MFI of zymosan particles. Phagocytic index was calculated as: percentage of zymosan-positive cells x mean number of particles per positive cell.
Gene Microarray analysis Preliminary filtering and normalisation of data were carried out in JExpress Pro 2012 software. For each donor, data on gels were quantile normalised to their respective TCP controls to obtain relative expression values. Using R software, data from each individual array probe were processed. An ANOVA and a pairwise Tukey's post hoc test were conducted to identify conditions causing significant changes in gene expression. Principal component analysis and heatmaps of relative expression for all significant genes p<0. 01 and p<0. 05 were also generated for the R analysis.
Macrophage morphology on GelMA hydrogels Macrophages cultured on micropatterned GelMA hydrogels and tissue culture-treated plastic (TCP) both exhibited heterogeneous morphologies (Figure  1A ). Depending upon the hydrogel patterning employed, cell alignment was also altered, e. g. alignment in one direction on microgrooves/ridges compared with random attachment on micropillars and unpatterned hydrogels (Figure  1A ). However, analysis of macrophages cultured on these different surfaces using CellProfiler software  42  revealed that alterations in cell morphology were insignificant amongst hydrogel conditions. Instead, it appeared that macrophages cultured on GelMA hydrogels (regardless of topographies) were significantly smaller and had a significantly lower cytoplasm to nucleus ratio than those cultured on TCP (Figure  1B ).
Microarray analysis of macrophages cultured on patterned GelMA hydrogels Gene microarray analysis was carried out in order to gain a global picture of topography-induced changes in macrophage gene expression. Using R, the relative expression data was processed for each individual array probe. An ANOVA and a pairwise Tukey's post-hoc test was conducted to identify conditions causing significant changes in gene expression. Principal component analysis (PCA) and hierarchical clustering analysis of the significantly altered genes (p<0. 05) showed that the different gel conditions -microgrooves/ridges, micropillars, and unpatterned -formed distinct clusters (Figure  4A ), suggesting that this subset of genes can distinguish between macrophages cultured on different topographies. Hierarchical cluster analysis confirmed this (Figure  4B ).
A B AMD1 + + ++ IVNS1ABP 0 b 0 ++ ZSWIM7 -c + ++ SCFD1 0 0/- + DERA - 0/+ + EXOSC9 -- - 0/+ HMGN1 -- -- - GIMAP6 --- - - ODF3B --- - - a +, up-regulation, b 0, no change, c -, down-regulation, of expression compared to their respective TCP controls. Greater number of + or -symbols implies greater up-or down-regulation, respectively. Finally, the 89 unique genes corresponding to the 90 probes significantly differentially expressed were processed to identify enriched Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways and gene ontology (GO) terms using the R script "NIPA" (https://github. com/ADAC-UoN/NIPA). In the Biological Processes category, 31 terms were identified to be significantly enriched compared to all genes in genome (p<0. 05 hypogeometric test conducted with GOStats  43  ).
Epidermis imaging was performed with the probe S-1500, which covers a 300 µm circular diameter in a focal plane and provides images from the skin surface, with a slice thickness of 15 µm and a lateral resolution of 3. 3 µm. The Z-1800 probe was used for dermal imaging. This probe is 1. 8 mm in diameter and acquires fluorescent signals emitted from 100 µm in depth, with a lateral resolution of 3. 5 µm. Images were collected from at least 10 different areas per injection site from three independent experiments (n = 30). Images were analyzed with ImageJ 1. 6 software (National Institute of Mental Health, Bethesda, USA). Ex vivo imaging on skin explants. Microscopic studies of tissue explants were performed as described previously 53. Briefly, skin biopsies were performed 24 hours after the injection auxo-GTU ® -Luc-EGFP plasmid and 2 hours after the in vivo id injection of anti-HLA-DR-AF700 Ab (Ozyme, France).
Apoptotic cells were stained with AnnexinV and Propidium Iodide (Invitrogen, France) according to the manufacturer's instructions. Data were acquired on LSR Fortessa (BD Biosciences, Le Pont de Claix, France) and analyzed with FlowJo software 9. 4. 11 (Tree Star, Ashland, OR). Multiplex assay. Supernatants were collected after an 18 h incubation of skin biopsies in complete media. High-sensitivity cytokine detection was performed by Milliplex ® assay  (Merck Millipore, Billerica, Massachusetts)  to analyze the production of Granulocyte-Macrophage Colony Stimulating Factor (GM-CSF), interferon (IFN)-γ, interleukine (IL)-1β, IL-1ra, IL-2, IL-6, IL-8, IL-10, IL-12/23(p40), IL-17, Monocyte Chemoattractant Protein (MCP)-1, macrophage inflammatory protein (MIP)-1α, MIP-1β, Transforming Growth Factor (TGF)-α, tumor necrosis factor (TNF)-α, IL-18.
Acknowledgements We thank  FIT Biotech  for supplying the plasmid auxo-GTU ® -multiHIV and auxo-GTU ® -EGFP/Luc, and  Dr. B. Verrier for providing the anti-p24 Ab. Special thanks to  Lamya Irbah  and  Géraldine Pottier  for their support with the imaging experiments. We warmly thank the  ASW core lab  staff and in particular  M. Rathaux ,  B. Delache  and  S. Langlois  and the  FlowCyTech team  for technical assistance. This work was supported by  French government  " Programme d'Investissements d'Avenir" (PIA)  under Grant  ANR-11-INBS-0008  funding the  Infectious Disease Models and Innovative Therapies  ( IDMIT, Fontenay-aux-Roses, France) infrastructure and PIA  grants  ANR-10-LABX-77  and  ANR-10-EQPX-02-01  funding the  Vaccine Research Institute (VRI, Créteil, France) , the FlowCyTech facility, respectively.
RNA-seq-based analysis of the four B. glabrata strains Until now, most of the experiments done on compatibility between Schistosomes and Biomphalaria snails were conducted using targeted Quantitative PCR or micro-array approaches to identified differentially represented transcripts following infection. In the present paper a more global and powerful approach was conducted to identify the differentially regulated transcripts or differential level of constitutive expression between snail strains. This global approach will also ensure a gene discovery effort without foreseeing the molecules involved compared to targeted approaches. To investigate such differences, four B. glabrata strains were used. The global transcript representation was analyzed by RNAseq and correlated with their compatibility phenotypes.
BgBAR was the less compatible strain, while BgBRE, BgVEN and BgGUA present higher compatible phenotypes that were mostly similar (Fig  1 ). To compare the native immune potentials of the four Bg strains, we compared the biological replicates, BgBRE1 and BgBRE2, to the other Bg strains. BgBRE strain was selected for duplicate sequencing because it is the strain for which we have the largest number of individuals in the laboratory. To identify the differentially represented transcripts in the transcriptomes of the different strains, we used the DEseq2 software comparing the duplicate of BgBRE strain to the others transcriptomes. Of the 117,269 transcripts of the BgBRE transcriptome, 6555 (5. 6%) were found to be differentially expressed between BgBRE and the three other B. glabrata strains. Fig 5A and 5B present the numbers of BgBAR, BgVEN, and BgGUA transcripts that were significantly over-and under-represented, respectively.
Considering the previous results presented above, we decided to deepen our investigation of immune functions in the different Bg strains. We first identified genes bearing immunerelevant domains and examined their proportions in the studied strains. We referred to a previous study in which the whole transcriptome of BgBRE was screened for the presence of immune-relevant domains using Interproscan  [33]. Using these data, we determined the proportion of the relevant transcripts that were differentially expressed in the strains studied herein. The results are shown in Fig 6A. Given the focus of the present paper and our interest in FREPs, we found it interesting that 3% and 10% of all transcripts bearing an "Ig-fold" domain were over and under-represented, respectively, in BgBAR. This particular domain is shared by a family of variable immunoglobulin and lectin domain-containing proteins  [33] ; notably, this family includes numerous FREPs.
Characterization and expression analysis of FREPs in the four B. glabrata strains As several FREPs (available in GenBank databases) were revealed in the above described transcriptomic analysis, we decided to exhaustively study all transcripts in the transcriptomes of BgBAR, BgVEN, BgBRE, and BgGUA that could belong to FREP family members. We selected transcripts corresponding to proteins that contain immunoglobulin (IPR013783) and fibrinogen (IPR002181) domains using the Blast2Go and/or Interproscan software packages. This selection process yielded 258 transcripts. Most of them were not full-length, which meant they could potentially represent molecules that contain fibrinogen or immunoglobulin domains but do not follow the classical organization of FREPs [1 or 2 IgSF domain(s) associate with a fibrinogen domain].