dataesr/scientific-paragraphs-categorization huggingface dataset:
Dendritic spine image stacks were taken with a 0. 125 μm step-size, and deconvolved using ImageJ software (NIH). For analysis of Eg5 stainings, single-plane images of neuron somas and dendrites were acquired with an Orca AG camera (Hamamatsu) coupled to a Leica DMI6000B microscope equipped with a 100×/1. 40 OIL objective. 20×/0. 50 DRY, and 40×/1. 25 OIL objectives were additionally used for standard imaging and for mosaics generation of complete axons/dendritic arbors and replated neurons. "Proximal dendrite region" corresponds to a distance of ~50 μm from the soma, while "distal dendrite region" corresponds to a distance of ~50 µm from the tip. Time-lapse microscopy. Hippocampal cultures were plated in glass-bottom dishes (MatTek), transduced with virus expressing shRNA, or treated with drugs, transfected with EB3-tomato reporter at 7 or 8 DIV and imaged 24 h later, or with mEOS3.
14 μm were taken at 10 s intervals during 4 min for mEOS experiments. mEOS3. 2 was photoconverted using a 405 nm laser at 5% for 1 s. Image analysis. All images were processed and quantified using the ImageJ software (NIH). Blinding was used in the sample imaging and image quantifications. For all fluorescence intensity measurements, background signal was measured in an adjacent area and subtracted. Dendritic EB3 comet analysis was performed using the kymograph macro (ImageJ software), with lines drawn on the trajectories of comets. The spatial distribution of mEOS3. 2 alone or of tagged proteins was measured using the Dynamic ROI Profiler plugin (ImageJ software). The average fluorescence intensities of α-tubulin and acetylated α-tubulin staining were measured along the imaged dendritic trace.
Whole axon and dendrite length were measured using the NeuronJ macro (ImageJ software). Sholl analysis was performed using the Sholl analysis plugin  65  using binary versions of the dendrite tracings generated with the NeuronJ macro. Dendritic spine morphology and density analysis was performed along the principal dendrite (thickest dendrite at 14 DIV) before the first branching, on deconvolved image stacks using NeuronStudio Software  66  or IMARIS software (BITPLANE). Tissue preparation and biolistics. Adult (3/4 months old) animals were killed through intracardiac perfusion. A quick perfusion was applied, consisting of an initial 10 ml of PBS 0. 1 M, followed by 40 ml of PFA 4% (20 ml/min). The brains were extracted from the perfused animals, incubated for 10 min in PFA 4% at 4 °C, and then stored in PBS at 4 °C for up to 48 h.
The results are detailed in the figures and the figure legends. Sample sizes were determined based on experience from previous work and based on other similar published studies. The number of Nek7 gt/gt embryos and adult animals used in this study was as high as possible (due to sub-Mendelian birth rates). No data were excluded and samples/cells were randomly allocated to experimental groups. Microarray raw expression files (CEL format) from all samples were normalized using the "rma" function from the oligo R package  68, 69  summarizing to probeset level. For each transcript, the 50% most variable probes (interquantile value) were selected. Gene expression was summarized by applying median polish to the selected probesets (function "medpolish" of the R stats package). Technical effects due to experimental batches were adjusted by fitting a linear model ("lmFit" of the limma package 70 ) for each gene with time and batch as covariates and removing the estimated coefficient for date of experiment.
Samples corresponding to times 20 h and 2 days were combined through the mean expression of each gene. The resulting matrix was centered and scaled. Clusters of genes with similar behavior along time points were found using the function "cutHclust" of the R ClassDiscovery package from the OOMPA suite (http://oompa. r-forge. r-project. org) with the "complete" linkage method and "pearson" metric. The number of clusters was set to 20. Data availability. The authors declare that all the data supporting the findings of this study are available within the article and its supplementary information files. All primary microarray data are available from the Gene Expression Omnibus (GEO) database: GSE113680.
Acknowledgements We are grateful to  Anne Straube  ( University of Warwick, UK ),  Ferran Azorin  ( IRB Barcelona, Spain ),  Carme Gallego (IBMB, Barcelona, Spain) ,  Michael Davidson , and  Tim Mitchison  ( Harvard University, USA ) for providing reagents. This study was supported by grants  BFU2009-08522 ,  BFU2012-33960 , and  BFU2015-69275-P  ( MINECO/FEDER)  to J. L. ,  BFU2014-58422-P  to J. R. , and  SAF2016-76340-R  to E. S. ( MINECO, Spain) , and  IRB Barcelona  intramural funds. J. L. and Y. M. acknowledge additional support from the  Ramón y Cajal and Juan de la Cierva Programmes , respectively (MINECO, Spain). F. F. was supported by a  La Caixa PhD fellowship ('La Caixa' Foundation, Spain).
Sections were rinsed three times in 3% BSA and then in PBS. Hoechst staining was performed for 30 min at RT before pursuing the immunohistochemistry protocol as described above. Image acquisition, analysis, and quantification. Images were acquired on a fluorescence microscope (Leica MZ16 F), a fluorescent microscope (Leica DM5000 B) or a confocal microscope (Leica TCS SP5). Images were then processed with ImageJ and Adobe Photoshop software. For cell density and colocalization analysis, three different rostro-caudal striatal levels of the striatum were initially defined, using the anterior commissure as an anatomical landmark. Single-plane confocal images were taken at each level in three different animals for each condition. For cell distribution analysis in Fig. 7 , a high-definition tilescan of the whole striatum at medial level was imaged on a single confocal plane in at least three different animals for each condition.
For time-lapse movie analysis, eventual drift in the three dimensions was first corrected using IMARIS software (Bitplane, Oxford); subsequently, z-stacks were flattened on a two-dimensional plane. The high number of cells present in each single movie rendered automated analysis of cell displacement unadvisable. Therefore, single cell displacement was measured manually frame-by-frame using the "Manual Tracking" plugin in ImageJ. Cells included in the analysis responded to two criteria: being readily identifiable from the first to the last frame of the movie and showing a total net displacement of more than 50 μm. In order to examine directionality and migratory pattern of iSPN migration, stationary (total net displacement less than 50 μm) cells were not included in the analysis. RNA-sequencing.
95 million passing Illumina quality filter reads was obtained for each of the 9 samples. Analyses were performed using the Eoulsan pipeline, including read filtering, mapping, alignment filtering, read quantification, normalization and differential analysis. Before mapping, poly N read tails were trimmed, reads ≤ 40 bases were removed, and reads with quality mean ≤ 30 were discarded. Reads were then aligned against the Mus musculus genome from Ensembl version 81 using STAR (version 2. 4. 0k). Alignments from reads matching more than once on the reference genome were removed using Java version of samtools. To compute gene expression, Mus musculus GFF3 genome annotation version 81 from Ensembl database was used. All overlapping regions between alignments and referenced genes were counted using HTSeq-count 0.
Acknowledgements We thank members of the S. G. lab,  M. Casado ,  J. A. Girault ,  C. Goridis ,  D. Hervé ,  C. Lena , and  E. Valjent  for stimulating discussions. We are grateful to  C. Auger ,  D. Souchet ,  A. Boudjouher , and  C. Le Moal  for excellent technical assistance. We thank  A. de Kerchove ,  E. Thierion , and  L. Danglot  for scientific input. We are grateful to the  IBENS Imaging Facility (France BioImaging , supported by  ANR-10-INBS-04 ,  ANR-10-LABX-54   MEMO LIFE  and  ANR-11-IDEX-000-02   PSL* Reseach University, "Investments  for the future";  NERF N°2011-45 ;  FRM DGE 20111123023 ; and  FRC Rotary International France) , the  IBENS Genomics Facility  (supported by the  France Génomique national infrastructure , funded as part of the  "Investissements d'Avenir" program  managed by the  Agence Nationale de la Recherche ,  ANR-10-INBS-09 ) and the IBENS acute transgenesis facility.
A. T. is part of the  ENP doctoral program. A. T. was supported by a doctoral fellowship from  Boehringer Ingelheim Fonds (BIF) , the  ENP program  and the  Labex Memolife « Investements  for the future » ( ANR-10-LABX-54   MEMO LIFE  and  ANR-11-IDEX-0001-02 PSL* Research University ). This work was supported by grants from  INSERM, CNRS , the  ANR program  ( ANR-12-BVS4-0010-01 ) and the  ERC NImO  ( 616080 ) to S. G, from the  ANR program  ( ANR-12-JSV4-004 ) to D. P. and from  NIH  ( R01 MH090740 ) to K. C.
No perforin + cells were detected by flow cytometry among CM CD4 T cells. A small proportion of perforin + cells were detected among CD28 + EM CD4 T cells in some donors and these cells were CCR5 +. Mean fluorescence intensity analysis indicated high perforin expression by CD4 CTX cells and low and comparable expression in naive, CCR5 + CM (CM Th1 ) and CCR5 + CD28 + EM (EM28 + Th1 ) CD4 T cells (Figure  3c  and Figure  3 -source data 1). In contrast, PRF1 mRNA expression analysis of sorted cells (sorting strategy shown in Figure  3 -figure supplement 1a) indicated that the PRF1 gene was already expressed at higher levels in CM Th1 as compared to naive cells and was further upregulated in EM28 + Th1 cells and in CD4 CTX cells (Figure  3d  and Figure  3 -source data 1). Notably, this pattern of progressive up regulation of gene expression was similar for RUNX3 and TBX21 and contrasted with the high expression of IFNG and EOMES mRNA already detected at the CM Th1 stage of differentiation (Figure  3d , and Figure  3 -source data 1 and Supplementary file 1).
Similar gene numbers were downregulated in the two subsets. As expected, genes upregulated in CD4 CTX T cells as compared to CM Th1 cells included cytotoxicity-related molecules, among which GNLY (granulysin), granzymes, CD107a (LAMP1), CX3CR1 and CD8A as well as TF RUNX3 and EOMES (Figure  5c-d ). T-bet was not up regulated in the transcriptome dataset, in line with reported lack of sensitivity of the Illumina array for this gene  (Dimova et al. , 2015). Expression of IFNG, TNF and GZMK was increased in CM Th1 as compared to naive cells but was not further up regulated in CD4 CTX T cells (Supplementary file 1). Additional TF were upregulated in CD4 CTX T cells (Figure  5d ). Most of them were selectively upregulated in CD4 CTX T cells as compared to CM Th1 cells or were up regulated from naive T cells to CM Th1 cells and from CM Th1 cells to CD4 CTX T cells.
Transcriptomic and methylomic analyses were conducted on 3 CMV-seropositive women, aged 38, 48 and 60 years, and 2 CMV-seropositive men, aged 40 and 52 years. The number of samples analyzed in each experiment was defined on the basis of previous experience of the investigators or on published literature. No sample size was computed. Peripheral blood mononuclear cells (PBMC) were purified by density gradient centrifugation and stained with titrated conjugated antibodies. Cells were sorted on a BD FACS Aria III or acquired with a BD LSR Fortessa cytometer and data were analyzed using the FlowJo software (v9. 2). The RAW 264. 7 murine macrophage cell line (RRID:CVCL_0493; obtained from ATCC) and the HEK-293 human kidney cell line (RRID:CVCL_0045, obtained from ATCC) were cultured in DMEM (Lonza) supplemented with 10% fetal calf serum, 1% AAG, 1% Na Pyruvate and 1% Pen/strep.
The HEL-299 fibroblastic cell line (RRID:CVCL_2480; obtained from ATCC) was cultured in EMEM (Lonza) supplemented with 10% fetal calf serum, 1% NEAA, 1% Hepes, 1% Glutamine, 1% Na Pyruvate and 1% Pen/strep. All cell lines were tested negative for mycoplasma infection (MycoAlert, Lonza). Because they were used only as tools to produce lentivirus particles, as targets of cytotoxic cells, and as a negative control in one methylation analysis, they were not re-authenticated after purchase.
Membrane staining was then performed as mentioned above. Cells were resuspended in complete antibiotics-containing medium, sorted and collected in the same complete medium, centrifuged and lysed in RLT Plus buffer +10 ml betamercaptoethanol for later nucleic acid extraction or immediately tested for cytotoxic activity. Cell purity was 98 [95-99]% (Median [IQ]). Single cells were sorted on a FACS Aria III cell sorter (BD) following staining and suspension in an EDTA-containing sorting buffer. Quality of sorting was assessed using the staining index from the DIVA software version 8. 0.
Raw data were analyzed using the fit points method and fold change was calculated with the Delta-Delta Cp method using the housekeeping gene EEF1A1 (EF1) as a reference. Primers and fluorescent probes were designed using Primer3 and purchased from Eurogentec. A Taqman Gene Expression assay was used for RUNX3 (Hs00231709_m1, Thermo Fisher) and PLZF (ZBTB16, Hs00232313_m1, Thermo Fisher) analyses. Oligonucleotide sequences are presented as Supplementary file 2c.
Bisulphite pyrosequencing The PRF1 promoter was divided into 11 amplicons covering 34 CpG sites as previously described  (Narasimhan et al. , 2009). Genomic DNA was bisulphite-converted using the Qiagen FAST Epitect bisulfite kit and sequenced using a Pyromark Q96 device after isolation of single strand biotinylated DNA from the PCR product using streptavidin and a pyromark Q96 vacuum prep station. Quality assessment and methylation level calculation were performed using the software Pyro Q-CpG and the CpG assay 1. 0. 9 (Biotage).
Gene expression and methylation microarrays Total RNA was amplified with the Illumina TotalPrep RNA Amplification Kit (Ambion) and hybridized with the HumanHT-12 v4 array containing 47,323 probes for 44,053 annotated genes, according to the instructions of the Whole-Genome Gene Expression Direct Hybridization Assay (Illumina). Chips were scanned with the HiScan Reader (Illumina). For methylation analyses, genomic DNA was bisulphite-converted using an EZ DNA methylation Kit (ZYMO). DNA methylation level was measured using the Illumina Infinium HD Methylation Assay. Bisulphite converted DNA was hybridized with the Illumina HumanMethylation450 BeadChip 450K array (12 samples/chip), as described previously  (Dedeurwaerder et al. , 2011). Data from both arrays are available on GEO (https://www.
ncbi. nlm. nih. gov/geo/) under the accession number GSE75406. Chromatin immunoprecipitation (ChIP) and ChIP-qPCR MACS-purified CD4 T cells were stained and fixed with 1% formaldehyde. Glycine was added at a final concentration of 0. 125 M to quench the crosslinking reaction. Cells were washed twice with icecold PBS and resuspended in complete medium for FACS sorting. Dry pellets of sorted cells were frozen at À80 ˚C. Thawed pellets were lysed in 1% SDS-containing buffer and sonicated to obtain DNA fragments of 300-800 bp using a Bioruptor device (Diagenode). Chromatin of 200,000 cells was immunoprecipitated with an anti-histone antibody and protein G magnetic-activated beads. Chromatin was incubated overnight at 4 ˚C with the following antibodies: 1 mg anti-H3K4me3 (Millipore 17-614 rabbit monoclonal), 0.
Illumina Expression HT12 Arrays Raw data were quantile normalized using the normalization method from the lumi package  (Du et al. , 2008). Unsupervised clustering (Uc) analysis of gene expression datasets was performed using the pvclust package of the R software (R)  (Suzuki and Shimodaira, 2006). The robustness of the Uc tree was tested by multiscale bootstrap resampling using Pearson's correlation as distance and Ward. D2 as clustering method, with 1000 iterations. An AU (approximately unbiased) p-value (percentage) was calculated and placed on the nodes of the cluster dendrogram. Principal component analysis (PCA) on the expression dataset was performed using the MultiExperiment Viewer (MeV) tool and the scatter plot function in R. The GeneSign module of the BubbleGUM software  (Spinelli et al.
, 2015)  was used with the Min/max method to identify lists of genes specifically expressed in cell subsets. A probe was considered specific of a given cell subset if its minimal expression value across the replicates of the cell subset of interest (test population) was higher than its maximal expression value across the replicates of the cell population used as reference (reference population). To obtain a limited number of genes, probes for which the ratio between the maximal and minimal expression values across all samples was below 1. 2 were considered not regulated in any cell subsets and thus excluded from the analysis. Finally, probe lists were transformed into gene lists (or GeneSets). Heatmaps were generated using the heatmap. 2 function of gplots package of R.
The statistical significance of the differential methylation was then assessed using a paired t-test applied on these M-values. In parallel, a Delta-b was computed as the absolute difference between the median b-values. Cytosine showing a p-value<1e-4 together with an absolute delta-b>0. 1 were reported as differentially methylated. Heatmaps were generated based on the scaled beta values of all the probes located in the promoter region of each represented gene, using the heatmap. 2 function of gplots package of R. Promoter regions included 5'prime, TSS1500, TSS200 and 1 st exon.
Gene Set Enrichment Analysis (GSEA) GSEA was used to analyze the enrichment of GeneSets obtained by GeneSign on the pairwise comparisons of our gene expression microarray data  (Subramanian et al. , 2005). Catalog c3 from MsigDB was added to our GeneSets for robust statistical analysis. GSEA was used with 1000 Gene-Set-based permutations and 'difference of classes' as a metric for ranking the genes since the expression values were in Log2 scale. The software quantifies enrichments by computing the Normalized Enrichment Score (NES) and the False Discovery Rate (FDR). FDR below 0. 25 was considered significant  (Subramanian et al. , 2005). Genes showing no differential expression between CD8 CTX and CD4 CTX were used as negative control. GSEA was also used to quantify the correlation between gene expression and methylation.
The identifiers of the genes included in the GeneSets were transformed to match the DNA methylation probe identifiers (Perl scripts included in Supplementary file 3). GSEA Pre-ranked analysis was then used to assess the enrichment of our expression-based Gene-Sets on the pairwise comparisons of the pre-ranked methylation delta b values. Genesets of catalog c3 from MsigDB were similarly converted to probe identifiers and added to our GeneSet file for robust statistical evaluation.
TCR repertoire Raw sequencing reads from fastq files (both reads) were aligned to reference V, D and J genes specifically for 'TRA' or 'TRB' to build CDR3 sequences using the MiXCR software version 1. 7. (Bolotin et al. , 2015). CDR3 sequences were then assembled and clonotypes were exported and analyzed using the tcR package  (Nazarov et al. , 2015).
Acknowledgements We thank the blood donors and ImmuneHealth for the clinical sample collection. We are grateful to  Veronique Olislagers ,  Sandra Lecomte ,  Margreet Brouwer ,  Muriel Nguyen , Severine Thomas, Ines  Vu Duc ,  Charlotte Givord  and  Iain Welsby  for technical assistance,  Ariane Huygens  for precious expertise in flow cytometry and  Charles Dehout ,  Nicolas Dauby ,  Muriel Moser ,  Alain Le Moine  and  Fabienne Willems  for helpful discussions,  Sophie Lucas  ( Institut de Duve -UniversiteCatholique de Louvain ) for providing single cell PCR reagents as well as  Thierry Voet  and  Koen Theunis  ( Katholieke Universiteit Leuven ) for single cell PCR analyses. YS is research assistant, SG senior research associate and AM research director at the  Fonds de la Recherche Scientifique (FRS -FNRS ),  Belgium.
Five Perl scripts were created to prepare the file required for GSEA. : https://doi. org/10. 7554/eLife. 30496. 028. Transparent reporting form DOI: https://doi. org/10. 7554/eLife. 30496. 029 European Regional Develop- Research Project Grant Stanislas Goriely ment Fund and Walloon Re- (411132-957270) Arnaud Marchant gion Fonds De La Recherche Scien- Research Project Grant Francois Fuks tifique -FNRS (PDR) Stanislas Goriely Arnaud Marchant Fonds Erasme PhD Student Fellowship Alice Hoyois Major datasets The following dataset was generated: Database, license, and accessibility Author(s) Year Dataset title Dataset URL information Serroukh Y, Kashani 2017 Genome-wide study of https://www. ncbi. nlm. Publicly available at BH, Gu-Trantien C, transcriptional and methylation nih. gov/geo/query/acc.
the NCBI Gene Defrance M, Vu profile of human cytotoxic CD4 T cgi?&acc=GSE75406 Expression Omnibus Manh TP, Azouz A, cells (accession no: Detavernier A, Das GSE75406) J, Bizet M, Pollet E, Tabbuso T, Ca- lonne E, van Gis- bergen K, Dalod M, Fuks F, Goriely S, Marchant A DOIDOI.
GC-MS analysis was performed with a Waters GCT Premier mass spectrometer fitted with an Agilent 6890 gas chromatograph and a Gerstel MPS2 autosampler. Data were collected using MassLynx 4. 1 software (Waters). Metabolites were identified and peak area was recorded using QuanLynx. Data were normalized for extraction efficiency and analytical variation by mean centering the area of D4-succinate. 14 C incorporation into intracellular lipids and TAG quantification. Fatty acid esterification rates were measured in the remaining liver piece or from primary cultured hepatocytes by tracing newly synthesized triglycerides from  14  C-oleate or 14 C-glucose. 14 C-TGs were extracted using chloroform/methanol (2:1, v/v) and separated by TLC as previously described and counted in scintillation liquid.
After 10 min, mice were ip injected with a mix of ketamine/xylazine, imaged on the PhotonImager system (Biospace Lab) and analyzed with the M3Vision software (Biospace Lab). For in vivo measurement of ROS (H 2 O 2 levels), using the PCL-2 probe, mice were infected with both adenovirus overexpressing the luciferase and the RSV β-gal (5 × 10 8 pfu each). Mice were studied 1 week later in fed state. The PCL-2 probe was used as previously descried  62. Briefly, mice, overexpressing the luciferase in the liver, were anesthetized with isoflurane and ip injected with a mixture of the PCL-2 and D-cysteine (0. 05 μmol each, in 150 μL of 1:1 DMSO:PBS). Following injections, mice were imaged with the PhotonImager system (Biospace Lab). The following setting was used, 1 min exposure, 60 images (60 min total).
Cytosolic supernatants were collected. Nuclear pellets were washed three times in 1 mL of hypotonic lysis buffer and resuspended in 200 µL of nuclear extraction buffer (50 mM Hepes pH 7. 4, 420 mM NaCl, 10 mM NaF, 1 mM EDTA, 0. 5 mM DTT). Samples were sonicated and centrifuged at 13,000 rpm for 30 min. Nuclear supernatants were collected. ChIP-sequencing. All the ChIP-Seq experiments were performed using samples collected from primary hepatocytes. ChIP-Sequencing (ChIP-seq) sample preparation and computational analysis of Illumina GA I/II data were performed by Actif Motif INC as follows. Primary cultured hepatocytes were incubated 24 h in the presence of 25 mM glucose and 100 nM insulin and were subjected to standard ChIP, using indicated antibodies, as described above. ChIP DNA-samples were then subjected to preparation for ChIP-Seq library construction: the libraries were constructed following Illumina's Chip-Seq Sample prep kit.