dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The authors' laboratories were supported by grants from the  Spanish Ministry of Economy & Innovation  ( SAF-2011-29405 ) and the  Madrid Autonomous Community  ( MITIC S2010/BMD2502  Program). Pedro Escoll ,  Ismael Ranz ,  Norman Muñoz-Antón , and Ana van-den-Rym were research associates at the  UAH  supported by a  UAH-148/2010  contract to  Eva Sanz ,  Melchor Alvarez-Mon , and  Antonio de-la-Hera. Melchor Alvarez-Mon  and  Eva Sanz  are  UAH Professors. Carlos Martínez-Alonso and Antonio de-la-Hera are CSIC Staff Researchers. The views expressed are those of the authors and not necessarily those of the  UAH , the  CSIC , the  Madrid Autonomous Community  or the  Ministry of Economy and Innovation. The authors gratefully acknowledge  Dr. Ana Muñoz  for her wise critical comments and long-standing support,  Dr.
Flow Cytometry. After antibody staining, cells were washed and dead cells were excluded by Propidium Iodide staining (250 ng/mL, Sigma-Aldrich). Cells were stained intracellularly using Foxp3 Permeabilzation/Fixation Kit according to manufacturers notice (eBiosciences). Cells were then incubated for 5 min with DAPI (4,6-diamidino-2phenylindole, 2 g/mL, Life Technologies), and washed prior to cell acquisition. FACSCanto II and LSR Fortessa (BD Biosciences) were used for flow cytometry acquisition, with Diva6 software (BD Biosciences), and analyzed with FlowJo v8 software (TreeStar). For visual purposes, only 8000 events maximum are shown in each FACS dot plot. Cells were purified with a FACSAria III sorter (BD Biosciences). Cells were recovered in PBS for cell injection, or OPTIMEM (Gibco) plus 10% FCS for cell culture.
Acknowledgments The authors thank  A. Goldrath  for providing Id2 Yfp/+ mouse strain. This study is supported by the  Ministère de la recherche  ( Sylvestre Chea ,  Thibaut Perchet ),  Association pour la Recherche sur le Cancer  ( Sylvestre Chea ,  Rachel Golub ),  Institut Pasteur (Ana Cumano) ,  Université Paris Diderot  ( Rachel Golub ,  Sylvestre Chea ,  Thibaut Perchet ),  Institut National de la Santé et de la Recherche Médicale  ( Ana Cumano ),  Institut National du Cancer  ( Rachel Golub ,  Maxime Petit ), and the  Agence Nationale de Recherches  ( Rachel Golub ).
Cells and viruses The BRSV Snook strain was isolated in calf kidney cells  [11] , and then passaged three consecutive times in gnotobiotic calves by inoculation by respiratory route, and prepared from bronchoalveolar lavage (BAL), as previously described  [13]  (BRSV-Snk inoculum). BRSV isolate no. 9402022 Denmark  [5]  was isolated in fetal lung cells, passaged in bovine turbinate cells, and prepared as described previously  [21]  (passage 8, BRSV-Dk inoculum). Aliquots of the BRSV-Snk and BRSV-Dk inocula were titrated by plaque assay using calf kidney cells, as previously described  [11]. Through inoculation of appropriate cell cultures and mycoplasmal or bacterial media, all cells and virus preparations were determined to be free from bovine viral diarrhea virus and bacteria, including mycoplasma (data not shown).
Measuring lung function Lung function was passively measured before and after BRSV challenge, on PID 0 and 6, by the forced oscillation technique (EquineOsc Calf measurement head, EEMS, Harts, UK), using the same face mask described for aerosol inhalation. Values for resistance (R) and reactance (X)(kPa/L/s) were obtained at 3, 5, 7 and 10 Hz, as described by Reinhold and colleagues  [25]. Each calf was tested at least twice on each day and the data sets with optimal coherence selected (coherence > 0. 9; majority of data sets > 0. 97). In the event of clear artifacts of breathing, such as cough or breath holding, the series were repeated. Daily calibration was performed using a 2. 26 m long tube, with a 21 mm internal diameter.
Nonetheless, virus was isolated and high quantities of viral RNA were detected by RT-qPCR in samples from the upper and lower airways from all infected calves in both studies, including calves A1 and B1, although BRSV-Snk infected calves from both studies shed 10 3 times more virus in nasal secretions than BRSV-Dk infected calves. Despite the differing data of calves A1 and B1, and although the number of animals in the first study was low (n = 3 + 3), we concluded that BRSV-Snk infected calves tended to be more severely affected in the 7-day experimental infection model, compared to BRSV-Dk infected calves, when summarizing clinical, pathological and virological parameters (Figure  5B ). Thus, results from study 1 were reproduced in study 2, using aerosol inoculation of the BRSV-Snk inoculum in an additional five BRSVnaive calves, with moderate levels of MDA.
Samples of the cells populating the lower airways were collected via BAL seven days after infection, and in addition, from three healthy uninfected calves (Control). Cells in BAL samples were analyzed by light microscopy (panel A), and expressed as group mean ×10 6 cells/ml. The concentrations of indicated inflammatory cytokines in BAL sample supernatants were measured using specific ELISAs, and are expressed in ng/ml: (panel B) interleukin (IL)-4; (panel C) IL-6; (panel D) IL-8; (panel E) interferon gamma (IFNγ); and (panel F) tumor necrosis factor alpha (TNFα). Individual data are indicated by rings and group means by horizontal lines. Probability (p) of statistically significant differences between groups is given in each panel, where p ≤ 0. 05 was considered statistically significant. similar to that reported following natural BRSV infection in calves  [32].
Acknowledgements This project was funded by the  Swedish Research Council (Formas, Sweden) , the  Biotechnology and Biological Sciences Research Council (BBSRC, UK)  and  L'Agence Nationale de la Recherche  ( ANR, France ), through the  Emerging and Major Infectious Diseases of Livestock (EMIDA)  project  in the European Research Area Network (ERA-NET ), grant no FP# 87. We thank the technical staff at  SVA  for their care of experimental animals,  Annika Rikberg ,  SLU , for her help with histological samples,  Ewa Westergren ,  SVA , for the histological sections and immunohistochemistry,  Prof. L. E. Larsen ,  DTU, Denmark  for kindly sharing the BRSV isolate no. 9402022 , and  Dr. Mikael Andersson Franko  ( SLU ) for providing feedback on statistical analysis.
Data shown in Fig. 2a  show that EE affects cell proliferation, reducing the extent of BrdU þ cells in tumour mass. Astrogliosis is also reduced by EE (Fig. 2b ), while M/Mf infiltration is not affected (Fig. 2c ). In contrast, CD68 þ cells are significantly reduced in EE in comparison with SE and are only detected in the tumour region, and not in healthy parenchyma (Fig. 2d ). CD68 staining is confined to M/Mf population (as verified by co-labelling with GFP þ cells in CX3CR1 þ /GFP mice, Supplementary Fig. 2 ), being completely absent in glioma cells. Cerebral slices were also analysed for glioma cell invasiveness towards the healthy brain parenchyma in SE and EE conditions. We observe that EE mice have a reduced number of glioma cells protruding more than 150 mm from the main tumour mass (Fig.
4). Transverse hippocampal slices (350-mm thick) were cut with a vibratome (DSK, Japan), allowed to recover for 2 h and transferred to the interface slice-recording chamber (BSC1, Scientific System Design, at 30-32 °C and superfused at 1. 5 ml min À 1 ). A concentric bipolar stimulating electrode was positioned in the stratum radiatum (0. 05 Hz) of the Schaffer collateral pathway. Orthodromically evoked fEPSPs were recorded with artificial cerebrospinal fluid-filled glass micropipette (0. 5-1 MO) and averaged over 1 min (n ¼ 3). For LTP experiments, fEPSPs (35-45 min post induction) were normalized to baseline values (0-10 min) before LTP induction (HFS, 1 train, 100 Hz, 1 s). fEPSPs were recorded and filtered (1 kHz) with the Axopatch 200A amplifier (Axon Instruments, CA, USA) and digitized at 10 kHz with A/D converter (Digidata 1322A, Axon Instruments).
The images were taken with a charge-coupled device camera (ORCA AG, Hamamatsu, France) through a 617/73 filter on a macroscope, equipped with a PlanApo Â 1/0. 25 or Â 2/0. 5 objective (MVX10, Olympus, France). The image acquisition piloted by the mManager  41  software was synchronized with the z-stage movement (10 or 20 mm steps) to obtain three-dimensional image stacks of the sample. Brain and tumour volume measurements. The three-dimensional images were analysed using the ImageJ software (http://imagej. nih. gov/ij/, 1997-2012). Multiplying the surface measurement (after maximal projection of the image stack and thresholding or outlining the brain or tumour) by the height (number of slices including the brain or tumour multiplied by the z gap between slices) gave cylinder-like volume estimations of the brains and the tumours.
For BrdU staining, sections were incubated 15 min in 1 N HCl for 25 min in 2 N HCl and then neutralized in 0. 1 M borate buffer. For F4/80 staining, coronal sections were first heated in 20 min in citrate buffer (pH 6. 0) at 95-100 °C. Image acquisition and data analysis. Fuorescence images were digitized using a CoolSNAP camera (Photometrics) coupled to a ECLIPSE Ti-S microscope (Nikon) and processed using the MetaMorph 7. 6. 5. 0 software (Molecular Device). Slices were scanned by consecutive fields of vision ( Â 10) to build a single image per section. Data were expressed as area occupied by fluorescent cells versus total tumour area (by converting pixel to mm 2 ). For comparison between different treatments, at least 12 coronal sections per brain around the point of injection were analysed.
Cells were then blocked by incubation in ice with anti-CD16/CD32 (24G2) to prevent nonspecific and Fc-mediated binding. After 10 min, a mixture of the appropriate antibodies was added. Cells were further incubated on ice for 30 min, washed and analysed using a FACSCanto II (BD Biosciences). Data were elaborated using the FlowJo Version 7. 6 software (Tree Star). NK1. 1 þ cell depletion. Depletion was performed using a blocking Ab against NK1. 1, which recognizes an epitope of the NKR1Pc-activating receptor (PK136). C57BL/6 mice (n ¼ 5 per group, EE or SE) were i. p. injected with 200 mg (in 100 ml) of anti-NK1. 1 Ab 2 days before, during and 2 and 7 days after glioma transplantation. Seven and seventeen days after glioma surgery, NK cell depletion from the blood sample was monitored with FACS.
Acknowledgements We thank  Professor Felicita Pedata  ( Firenze University ) for help with the osmotic pump surgery,  Professor BertilB. Fredholm  ( Karolinska Insitute, Stockolm ), FlaviaTrettel,  Claudio Babiloni  and  Francesca Grassi  ( Sapienza University of Rome ) for stimulating discussion. This study was supported by the grants  AIRC  to  C. Li. (IG 2012, n. 12774); ITMO Cancer in 'plan Cancer 2009-2013' for ultramicroscopy development (to F. B. ) and  AIRC  to A. S. ( IG2014 , n. 16014).
Cell labelling and flow cytometry Single or multiple indirect labelling of surface receptors was performed on purified ovine cells using Abs against the molecules NCR1, CD8, TCR1, CD16 and CD25 revealed by subtype-specific secondary Abs. Direct intracellular perforin labelling was performed with the perforin-FITC kit and the Cytofix/Cytoperm and Permwash solutions (BD Pharmingen). The samples were analysed on a FACS CALIBUR flow cytometer (Becton Dickinson), equipped with Cell-Quest Pro software. At least 2 × 10 5 viable cells were analysed for spleen, MLN and PPs and at least 10 6 cells for the jejunum. The analyses of labelling were performed with the FCS express software; percentages of perforin+ and CD25+ cells and median fluorescence intensity (MFI) were determined using the histogram subtraction and statistics functions of the software.
RNA isolation and real-time RT-PCR RNA was extracted from tissues with TRIZOL solution (Invitrogen), according to the manufacturer's instructions. Purified RNA was reverse-transcribed using oligo (dT) primers and M-MLV reverse transcriptase (Promega, France). For PCR experiments, primer pairs were designed using Primer 3 software (Additional file 1). Each primer was designed on different exons to span the intervening intron and thus avoid amplification from contaminating genomic DNA. Q-RT-PCR assays were carried out by combining cDNA with primers and IQ SYBRGreen Supermix (Bio-Rad, USA) and were run on a Chromo4 (Bio-Rad). Samples were normalized internally using the average cycle quantification (Cq) of three reference genes Hypoxanthine phosphoribosyltransferase (HPRT), b-Actin and Glyceraldehyde-3-phosphate dehydrogenase (GAPDH).
Statistical analyses For the morphometric analysis of the density of CD8+ cells, it was necessary to compensate for natural variability between individuals; therefore the non-parametric Wilcoxon-van Elteren  [45]  test was used to calculate the significance of differences between the two groups. Twotailed tests were performed and differences considered significant for p-values < 0. 05. Flow cytometry data were analysed with GraphPad software: the nonparametric Mann-Whitney test was used to test the significance of differences between means from inoculated lambs and matched controls, the Wilcoxon test to compare different subsets of cells from the same animals and the paired t test to compare groups of paired lambs.
C. parvum induces typical enteritis lesions with immune cell recruitment in the segments of the neonatal ovine small intestine In neonatal lambs infected on the day of birth, the kinetics of C. parvum oocyst excretion was evaluated daily (Figure  1A ). The C. parvum infected or uninfected status was verified by measuring the expression of a cryptosporidium specific gene in gut tissues by RT-PCR (data not shown). The excretion of oocysts started from day 3 pi coinciding with the onset of watery diarrhoea and mild dehydration and reached a peak at 6 dpi (Figure  1A ). At necropsy, there was a mild to moderate enlargement of mesenteric lymph nodes (MLN) in the inoculated lambs from day 2 pi (1. 5-3 fold weight increase on average compared to controls) while no visible change of the spleen was observed.
The up-regulation of IFNγ and IL22 during the infection may participate in the clearance of the infection and the recovery of the epithelial integrity, respectively. The proportion of NCR1+ lymphocytes did not change with infection although a slight increase in their absolute numbers was observed in the small intestine of infected lambs NCR1+ lymphocytes are known to be IFNγ producing cells and important players of the innate response. As an increase of lymphocytes in the gut segments was observed early in the infection at 3 and 6 dpi (Figures  1E-H, K ) and even earlier at 1-2 dpi (data not included in Figure  1K ), we analysed the local changes of NCR1+ lymphocytes in the GALTs at different time-points of infection. Preliminary studies revealed that the proportion of NCR1+ cells was rather low in the ileum compared to jejunum and JPPs; consequently immunohistology was preferred to flow cytometry to assess the cell recruitment in the IPP.
Interestingly, a cytotoxicity assay probe trial performed with CD16-/ NCR1+ and CD16+/NCR1+ FACS-sorted subpopulations, failed to show any difference between the two subpopulations (Drouet unpublished data). These data suggest that the expression of CD16 on sheep NK cells might be associated with a function different from that of their human homologs, perhaps more linked with antibody dependent cell cytotoxicity than direct cytotoxicity. Finally, considering the cytokine profile during the first days of infection, the up-regulation of IFNγ gene expression observed in inoculated lambs, is in agreement with our data obtained from rodent neonates where an early production of IFNγ is known to be a determinant for the resolution of the infection in neonatal mice  [32]. Both cNK cells and T lymphocytes are known to be significant producers of IFNγ and it will be of interest to ascertain in future studies their relative contributions to its production during the course of C.
Acknowledgements The authors thank  Thierry Chaumeil  ( INRA-PFIE ) for the practical organization of the animal experimentations,  Tore Engen ,  Kristian Franer ,  Vanessa Rong ,  Gaëtan Brunet ,  Laila Aune  and  Lene Hermansen  for excellent technical support,  Yves Le Vern  ( INRA cytometry platform ) for his advice,  Muriel Naciri  and  Geneviève Fort  for their parasitology expertise and support,  Jacques Cabaret  for his expertise of statistical analyses and  Daniela Pende  for her kind supply of the KD1 monoclonal antibody. This work was supported by the  bilateral mobility Aurora program  ( N°27417ND ), financed by the  Norwegian Research Council  and the  French Ministry of Foreign Affairs.
Differentially expressed genes (DEGs) were selected on statistical significance (P < 0. 1) and a fold change above 2 for up-regulated genes (Fig. 5 B ) and below 0. 33 for down-regulated genes (Fig. S5 ). After clustering and heat map representation of the top regulated genes, resistin-like-α, Ccl24, and arginase 1 were found to be the most up-regulated by IL-4, as previously described in macrophages  (Van Dyken and Locksley, 2013). Venn diagrams showed that out of all probes tested, 187 DEGs defined a core IL-4 differential gene expression signature (Table  S1 ). DEGs were submitted to two different pathway analyses, Voronto and Ingenuity Pathway Analysis (IPA) softwares. Voronto uses tessellation Voronoi diagrams to integrate expression data and hierarchical ontologies extracted from public databases  (Santamaría and Pierre, 2012).
In agreement with these observations, upstream regulators of majorly IL-4-down-regulated genes included TNF, IL-6, and IL-1β. Up-regulated DEGs were compared with previously curated lists of IL-4-stimulated genes to identify novel IL-4-regulated genes. We restricted the comparison to the IPA and to a recently published analysis of the genes defining the core of alternatively activated mouse and human macrophages  (Martinez et al. , 2013). We could only find 26 genes from our list that were present in either of these two databases (Fig. 5 C ), confirming that despite the ontogenic proximity of macrophages and GM-CSF-derived DCs, IL-4 induces a great heterogeneity in their respective gene expression program. When the IL-4-DC signature was compared with available monocyte/phagocyte gene signatures  (Gautier et al.
As these results were obtained with cells differentiated with IL-4, it is tempting to speculate that mTOR reprogramming and autophagy induction could be linked to arginase-1 expression, which by decreasing cytosolic amino acids concentration could influence mTOR activity. The Rufy4 gene is located on chromosome 1 in mouse (Chr 2 in human), and its promotor region contains several potential STAT6 consensus binding sites (TRA NSFAC database). Rufy4 is immediately adjacent to the CXCR2 gene, which is also strongly up-regulated by IL-4 treatment (Fig. 5 C ), indicating that this area of the genome is transcriptionally active upon GM-CSF-and IL-4-induced differentiation. Rufy4 has appeared relatively late in evolution (reptile) and is clearly not part of the core autophagy machinery characterized in yeast  (Deretic et al.
Immunofluorescence and confocal microscopy were performed at 20°C with a LSM580 (Carl Zeiss) or a TCS SPX5 (Leica) using a 40× and 63× objective and accompanying imaging software. Fluorochrome or biotin directly coupled antibodies for FACS were CD8α (RM2201) from Invitrogen; I-A/I-E (M5/114. 15. 2), CD80 (16-10A1), CD4 (RM4-5), and DEC205 (205yekta) from eBioscience; and CD11c (N418), CD86 (GL-1), CD40 (HM40-3), and H-2K b (HB-176) from BD. Anti-K b / SL8 25D1. 16  (Porgador et al. , 1997)  was purified and fluorochrome coupled using the Alexa Fluor 647 protein labeling kit (Invitrogen). Data were acquired on a FACS LSR II or Canto II (BD) and analyzed using FlowJo (Tree Star). For immunoprecipitation, 0. 4 × 10 6 HeLa cells were transfected with mock or the Myc-tagged hRUFY4 (WT and mutants) plasmids for 24 h.
DAL IS scoring Cells on coverslips were pre-extracted with cold 0. 1% Triton-X for 2 min at 4°C before fixation with 3. 5% PFA. Detection was performed with an anti-P62 (SQTM1; sc-25575; Santa Cruz Biotechnology, Inc. ) and anti-rabbit Alexa Fluor A568 (A11011; Molecular Probes), mounted with Prolong Gold with DAPI (P-36931; Life Technologies). DAL IS quantification was performed by mosaic image acquisition with an Axioplan video microscope (Carl Zeiss). Images were then analyzed using a multiparameter protocol based on the Physiology Analyst module of ASS AY Builder software (Carl Zeiss). This protocol allows the automatic recognition and characterization of the cell population and intensities, areas, and spot number in the cellular regions. cDNA cloning, in vitro transcription, and gene transduction or silencing All plasmids were generated using standard cloning, PCR, and fusion PCR techniques and based on pcDNA3.
Each gene transcript was quantified by SYBR Green method with 7500Fast (Applied Biosystems). The relative amount of each transcript was determined by normalizing to internal housekeeping gene expression. Primer sets were as follows: mouse Rufy4, 5′-TGG CCCCT GGACA CTGCA TA-3′ and 5′-AGA GCAGG CGTGG CAAAC CA-3′; human Rufy4, 5′-TGC TCTCA ATGGG GTGGC CT-3′ and 5′-GGG TTTGG GTGGA ACTGG AGCA-3′; mouse GIM AP1, 5′-ATG CAGAG GCGCA CCAGG TT-3′ and 5′-TGG CCACA CCCAG GAAGA CA-3′; mouse cyclophilin B, 5′-ATG TGGTT TTCGG CAAAG TT-3′ and 5′-TGA CATCC TTCAG TGGCT TG-3′; mouse GAP DH, 5′-GGG TGTGA ACCAC GAGAA ATA-3′ and 5′-CTT CCACA ATGCC AAAGT TGT-3′; and human GAP DH, 5′-CAA TGACC CCTTC ATTGA CC-3′ and 5′-GAC AAGCT TCCCG TTCTC AG-3′.
Microarray and bioinformatics analyses Equal amounts of RNA extract (500 ng) from each replicate were amplified and Cy3 labeled using the Low Input Quick Amp Labeling kit (Agilent Technologies). Hybridizations were performed according to the manufacturer's instructions for One-Color Microarray-Based Gene Expression Analysis using Whole Mouse Genome GE 4 × 44K v2 microarrays (Agilent Technologies). Images were scanned on an Agilent G2565AA microarray scanner, and raw images were quantified using the Agilent Feature Extraction 10. 5. 1. 1 software and the GE1_105_Dec08 protocol. The signal intensity was aligned and normalized between microarrays by centering the median of the signal distribution using BRB-ArrayTools v3. 8. 1. The microarray data have been submitted to the GEO database and can be accessed under accession no.
GSE56929. Raw gene expression data obtained from the Agilent Feature Extraction software were background corrected using the "normexp" method and quantile normalized, using the limma package through Bioconductor in the R statistical environment (version 2. 15. 0). Quality control of the expression data was assessed by boxplots of raw expression data, density plots of the normalized data, and calculation of the Pearson's correlation coefficients between arrays. The Cluster and Treeview softwares were used to classify samples according to the similarity of their gene expression profiles as assessed by hierarchical clustering with average linkage as a clustering method and Pearson correlation as a metric distance, considering the genes having a minimal fold change of two across all samples. PCA was computed with the MeV software across all probes, using the median-centered method and 10 neighbors for KNN imputation.
The 3D plot was generated using the scatterplot3D package in the R statistical environment. Genes differentially expressed between each sample in a statistically significant manner were selected as having a fold change >2× and an FDR (Benjamini-Hochberg correction) <0. 1 after empirical Bayes processing using the limma package. These gene lists were submitted to Venn software for comparisons or uploaded into IPA and Voronto  (Santamaría and Pierre, 2012)  to test for significant enrichment of functional annotations.