dataesr/scientific-paragraphs-categorization huggingface dataset:
Epigenomics Methods For the past two decades, the advent of HTS allowed researchers to extend the knowledge of different epigenetic marks at the whole genome level and their interplay in several tissues. Several consortia emerged such as the ENCODE project (Encyclopedia of DNA Elements,  [37] ), the National Institutes of Health (NIH) Roadmap Epigenomics Project Mapping Consortium  [38] , the International Human Epigenome Consortium  [39]  and modENCODE (Model Organism Encyclopedia of DNA Elements  [40] ). The goal of these consortia was to streamline experimental design and analyses, to provide guidelines and to coordinate the sequencing efforts. They produced several databases containing a collection of epigenomes (mostly based on mammalian species). Since 2015, the willingness to better understand genetic, epigenetic and phenotypic diversity of domesticated species such as the chicken has driven to create a consortium called FAANG (Functional Annotation of Animal Genomes,  [41] ).
Design of Epigenomic Studies HTS techniques are in continuous evolution and are nowadays well documented in extensively studied model species such as human, mouse, Drosophila and Arabidopsis. Here we summarize considerations for avian epigenome investigation from sequencing considerations to the data analysis involving huge datasets. The importance of a carefully designed and executed experimental design has been addressed in previous reports  [90, 91]. In particular, experimental design should take into account parental history (such as rearing conditions and nutrition) and hatchery practices. Confounding factors such as flock age, transport of eggs and storage or care of animals should be minimized as much as possible, while the tissue homogeneity has to be maximized. The use of inbred strains may also provide an interesting opportunity to study epigenetic variations in a situation in which genetic variation is greatly minimized and therefore facilitates the interpretation of epigenetic changes, especially for the detection of DNA methylation based on the bisulfite-induced polymorphism  [92].
Acknowledgments: This work was supported by the  Region Centre Val de Loire , by the  Department of Animal Genetics  and the  Department of Animal Physiology and Livestock Systems at the French National Institute of Agronomical Research (INRA). This work is funded by  French ANR "ChickStress " grant  ( ANR-13-ADAP-0014 ) and by the  INRA   PHASE division project  " STRESSEPIMARK ".
Laser damage was induced 24 h after treatment with AsiDNA (16μM), olaparib (1μM) or both. Images were captured at 2s intervals for the following 52s. All images were processed using the freely available software ImageJ complemented with the LOCI bioformat plugin (http://www. loci. wisc. edu/ome/formats. html) to open images generated by the Leica SP5 confocal system. A macro was written to automate data extraction from images. Briefly, it consisted of retrieving two regions of interest (ROI), namely the photodamage spot and the nucleus area excluding the spot, and quantifying the total intensity within these ROIs. The latter was used to correct fluorescence intensity for the observational photobleaching. Intensity within the former ROI was normalized to 1, based on quantifications before photodamage, then plotted against time to get the recruitment kinetics.
High-throughput data sources and analysis mRNA expression analysis-mRNA expression data for BC cell lines were produced using Human Exon 1. 0 ST Affymetrix microarrays. Raw data were RMA normalized and summarized with FAST DB annotation (version 2013_1) (24)  (25). Gene expression were log2 transformed and mean centred over all the cell line samples and then grouped into the four groups (AsiDNA sensitive, AsiDNA resistant, olaparib sensitive, olaparib resistant). Each gene was assigned with a score using median expression level across samples of the same group and the data was visualized on ACSN map. Mutation data analysis-Mutation data sets for BC cell lines were retrieved from COSMIC database v71 (http://cancer. sanger. ac. uk)  (26). The frequency of mutations for each gene across cell lines in the same groups (AsiDNA sensitive, AsiDNA resistant, olaparib sensitive, olaparib resistant) was calculated and the data was visualized on ACSN map.
For each treatment, a list of correlated genes is ranked by correlation p-value. In order to discover the most unique correlated genes with one treatment, a stepwise p-value selection was used so that no gene whose correlation p-value under the selected p-value were retrieved in both treatment. The unique, non-overlapping set of gene robustly correlated with survival to each one of the drugs is provided. The selected p-value (threshold p-value) determined for the ranked genes included in ACSN (29) is 0. 005. The Supplementary figure  S3-A  illustrates the relationship between the number of overlapping genes and the p-value from LOO Spearman correlation analysis. (29)  uses NaviCell environment to navigate maps  (30) ; to analyze and visualize data in the context of maps  (31). The enrichment of the ACSN modules with unique genes robustly correlated with survival to each one of the drugs is calculated in the NaviCell toolbox using the standard hypergeometric test, computing the enrichment p-values (P value <0.
Acknowledgements We acknowledge financial support from the  China scholarship council (CSC)  and the  IRTG Soft Matter Science (Freiburg, Strasbourg). The financial contributions of the  Agence Nationale de la Recherche  (project  LabEx Chemistry of Complex Systems   10-LABX-0026_CSC ), the  University of Strasbourg , the  CNRS , and the  RTRA International Center of Frontier Research in Chemistry  are gratefully acknowledged.
Enzymatic activity assays To measure enzymatic activity of recombinant proteins and NCE on different substrates, each reaction was prepared following doses, time points and buffers specified in detail into the legend of each experiment. Final volume for each reaction was 10 l. At the end of all reactions, samples were blocked with a stop solution, containing 99. 5% (v/v) formamide (Sigma-Aldrich, Milan, Italy) supplemented with 10× Orange Loading Dye (Li-Cor Biosciences, Milan, Italy) and heated at 95 • C for 5 min. Then, all samples were loaded onto a 7 M denaturing 20% polyacrylamide gel in TBE buffer pH 8. 0 and run at 4 • C at 300 V for 1 h. Then, the gel was visualized with an Odyssey CLx Infrared Imaging system (LI-COR GmbH, Germany). The signals of the nonincised substrate (S) and the incision product (P) bands were quantified using Image Studio software (LI-COR GmbH, Germany).
The specificity of the PCR amplicon (size and product) and absence of primer-dimer were verified by melt-curve analysis using LightCycler 480 equipment and software (Roche). Samples were normalized to the 6S rRNA level for quantification of the mRNA transcript and with the snU6 level for quantification of mature miRNA. The relative expression levels of miRNAs and mRNAs were determined using the standard 2 -ΔΔ CT Livak and Schmittgen method.
Image sizes were set to 512 × 512 pixels. Zstack images were acquired randomly for each condition, and representative images from the focal plane of the nucleus were analysed by Image J v1. 4. 9 software. Regions of Interest (ROIs) were selected using the polygon select tool of the software and the mean fluorescence intensity (MFI) determined. For quantification studies, ratios between MFI expressed in pixels and the selected area of ROIs expressed as relative unit of surface (RUS) were calculated and plotted on graphs.
Reconstruction of SPECT images was performed with the HiSPECT (v1. 4. 24. 21, Scivis) software. The fusion of SPECT and CT images was obtained using the VivoQuant (v1. 23, InVicro) software. From the reconstructed images, ROIs were drawn automatically except for liver and stomach in which ROIs were drawn manually using the VivoQuant (v1. 23, InVicro) software. Radioactivity counts within ROIs were then quantified using the VivoQuant software.
In vivo bioluminescence imaging Bioluminescence imaging was performed as previously described  [18, 23]. Briefly, mice received intraperitoneally in vivo 2 mg of Luciferin substrate and were isoflurane-anesthetized 5 min later. Then, after a further 5 min (10 minutes after injection of the luciferin substrate), the mice were placed in an IVIS Lumina II imaging scanner (PerkinElmer, USA) coupled to an isoflurane ventilation system to maintain constant anaesthesia. The acquisition parameters were 2 min integration time, F/Stop = 1, binning 8. Bioluminescence signals were collected from ROIs drawn manually and quantified using the living Image Software (Perkin Elmer). The final data were expressed as photons/second/pixel/sr. The sensitivity of the imaging scanner was tested monthly with commercially available positive sources of bioluminescence.
This result indicated that the saturation of radiotracer uptake in pRINES/122T-transfected cells could not be explained by a saturation of hNIS mRNA production. Therefore, we quantified the expression of hNIS protein located at the plasma membrane of the cells. We performed this analysis by confocal immunofluorescence microscopy to distinguish the location of hNIS at the plasma membrane from hNIS in the perinuclear region of the cells. The Image J software was used to quantify the relative immunofluorescence intensity of the region of interest (ROI) covering the whole cell periphery of transfected cells. An indicated that the expression of hNIS at the plasma membrane was heterogeneous in all experimental conditions tested and tended to increase when the amount of pRINES/122T used to transfect the cells shifted from 0.
36 ± 0. 25 x 10 6 cpm/mg, 2. 76 ± 0. 41 x 10 6 cpm/mg and 3. 41 ± 0. 52 x 10 6 cpm/mg, when 1 nM, 5 nM and 10 nM of miRNA-122 mimic were delivered to the cells respectively. Noteworthy, all of these mean values were found to be significantly different (P 0. 05) from the mean value detected in control cells, not transfected with miRNA mimics (0. 45 ± 0. 041 x 10 6 ). We conducted a similar set of experiments with control mimics (data not shown) or an irrelevant miRNA mimic (miRNA- 133 or -1). The mean values of 99m TcO 4 -uptake detected in these cells were similar (P ! 0. 05) to that detected in control cells, not transfected with miRNA mimics. Furthermore, the addition of sodium perchlorate, a well-known specific inhibitor of hNIS-mediated 999m TcO 4 uptake totally inhibited accumulation of radiotracer in the pRINES/122T-transfected cells.
Highlighted by Jarkko Rautio A collaborative effort from the Scripps Research Institute, the University of Lausanne, Bristol-Myers Squibb and the Salk Institute ingeniously demonstrates a chemical proteomic platform to map small-molecule fragment-protein interactions directly in human cells. Typically, fragment-based ligand and drug discovery (FBLD) emphasizes the identification of structurally simple hit compounds by screening ~10 3 low-molecular weight compounds (<300 Da) at high concentrations (>100 µM) in in vitro assays only with purified proteins. The group used the photoaffinity/click-label combination to discover more than 2000 fragment-binding proteins in HEK293T cells, only a few of which are found in DrugBank database. Using the quantitative MS-based SILAC (stable isotope labeling with amino acids in cell culture) technique, they quantified and identified labeled proteins and tracked down poorly characterized transmembrane protein PGRMC2 (progesterone receptor membrane component 2) for which selective ligands were previously lacking.
1 isoform (Figure  1B , top). Hereafter, the term "TPM4" is used to indicate both protein isoforms TPM4. 1 and TPM4. 2 (in humans) or solely TPM4. 2 (in mice). A truncating mutation in TPM4 causes macrothrombocytopenia in humans. We next performed a look-up in the database for the Biomedical Research Centres/Units Inherited Diseases Genetic Evaluation (BRIDGE) Bleeding and Platelet Disorders (BPD) collection. To date, over 1,000 participants have been enrolled and genome-sequenced as part of the BRIDGE-BPD study for genome sequencing along with approximately 5,000 participants with other rare diseases enrolled to the NIHR BioResource-Rare Diseases  (16). Two high-impact rare variants in TPM4. 1 and 1 in TPM4. 2 were identified. The variant affecting the product of TPM4. 2 was a nucleotide substitution of C to T at position 16192795 of chromosome 19 (build GRCh37).
It was present on 1 allele in 2 unrelated BPD cases and was absent from the Exome Aggregation Consortium (ExAC) database  (17)  as well as the UK10K database  (18). The 2 cases do not share any other rare variants, and their estimated genome-wide kinship, based on common unlinked SNVs  (19) , was estimated to be zero, suggesting that the variant did not arise in a recent common ancestor. Predicted loss-of-function variants in TPM4. 2 are rare in the general population, with only 2 heterozygotes observed among the Tropomyosins, which form copolymers with actin, are a prime example, with SNVs rs3809566 and rs8109288 marking the genes encoding tropomyosin 1 (TPM1) and tropomyosin 4 (TPM4), respectively. It has been reported that expression of transcripts from the TPM4 locus strongly increases in the later stages of megakaryopoiesis  (5, 6).
Filled symbols: macrothrombocytopenia; gray symbols, unknown; open symbols: normal platelet count and volume and absence of macrothrombocytes. +/M, heterozygous; +/+, WT. (C) Platelet TPM4 RNA levels measured by RT-PCR using GAPDH as housekeeping gene. Graph depicts representative data from a total of n = 3 measurements from 1 (case 1-II-5) or 3 (case 1-III-7) patient samples. (D) Platelet TPM4 protein is reduced in heterozygous carriers of the TPM4 variant. Graph depicts representative data from a total of n = 3 measurements from 1 (case 1-II-5) or 3 (case 1-III-7) samples. Left: Densitometry analysis performed using ImageJ. Right: Protein levels of platelet TPM4 in controls and cases 1-II-5 and 1-III-7. β-Actin was included as an internal loading control. Similar results were obtained when GAPDH was used as a loading control (not shown).
2) was purchased from BioLegend. Fluorogold (Sigma-Aldrich) was used to exclude dead cells. Investigation of the effect of the Plt53 mutation in megakaryocytes by RT-PCR Fetal liver cell-derived megakaryocytes from Tpm4 +/+ , Tpm4 Plt53/+ , and Tpm4 Plt53/Plt53 embryos E13. 5 were generated as described below. mRNA was isolated using the RNeasy Plus Kit (Qiagen), and cDNA was synthesized using SuperScript III Reverse Transcriptase (Invitrogen) according to the manufacturer's protocols. The primers used were 5′-AAAGAAGCCAAGCACATCAC-3′ (Tm4_F3) and 5′-AGC-CCACATTCTCTTCTTTG-3′ (Tm4_R7). The expected product size Generation of Tpm4. 2 knockout mice. Target sites in exon 1b of the mouse Tpm4 gene were analyzed by the MIT CRISPR Design Tool  (51). Two high-scoring (>85) guide RNA (gRNA) sequences were chosen, as they created a 93-bp deletion that interrupted the ATG start codon.
Two-step quantitative PCR (qPCR) reactions were performed in duplicates using SYBR Green chemistry (Brilliant II SYBR Green QPCR Low ROX, Agilent Technologies) on an Mx3000P instrument (Agilent Technologies). Relative gene expression was calculated by the ΔΔCt method using GAPDH housekeeping gene for normalization. PCR primer pairs were designed to amplify only cDNA, had no reported off-target matches searching the human NCBI RefSeq database, and were within 80%-120% PCR efficiencies with single dissociation curves. qPCR oligonucleotide primer pairs were as follows: TPM1-F, AGTCGAGCCCAAAAAGATGA; TPM1-R, TCGCTCTCAATGATGA-CCAG; TPM2-F, GGACAGAGGATGAGGTGGAA; TPM2-R, GCAT-CAGTGGCCTTCTTCTC; TPM3-F, CCTGCAAAAGCTGGAAGAAG; TPM3-R, TCTGCCTCTTCTGCAATGTG; TPM4-F, GGAGATG-CAGCTCAAAGAGG; TPM4-R, CCTCCAGGATGACCAGCTTA; GAPDH-F, TATCGTGGAAGGACTCATGACC; GAPDH-R, TAGAG-GCAGGGATGATGTTCTG.
TPM4 knockdown in human megakaryocytes Short hairpin vector cloning. Oligonucleotides were selected from the RNAi consortium database. Short hairpin or control nontarget sequences were annealed before cloning into the pLKO. 1 lentiviral vector backbone (Addgene 10878) downstream of the human U6 promoter and checked for sequence integrity. Viral particle production. Replication-deficient lentiviral vector particles (LVPs) were produced by transient cotransfection of HEK 293T/17 cells (ATCC CRL-11268) with pLKO. 1-short hairpin constructs along with the psPAX2 and pMD2. G helper plasmids (Addgene 12260, 12259) using TurboFect transfection reagent (Thermo Fisher Scientific). Crude supernatants containing LVPs were concentrated by PEG-based precipitation (LentiX-concentrator, Clontech) and functional titers determined by qPCR measurement of provirus copy number in genomic DNA of transduced HCT116 cells (ATCC CCL-247).
2 knockout mouse. WHO directs the Bleeding and Platelet Disorders project of the NIHR BioResource-Rare Diseases. PWG contributed to the design and interpretation of experiments on the detection and function of tropomyosins. ET analyzed and interpreted human genetic, RNA, and proteomic data. MRT conceived the study in humans, designed experiments, interpreted data, and wrote the paper. BTK conceived the study, designed experiments, interpreted data, and wrote the paper. ture for the indicated time periods. After fixation with 4% paraformaldehyde in PBS for 10 minutes, the coverslips were thoroughly rinsed with PBS, and platelets were visualized with a Deltavision Elite microscope equipped with CoolSnap2 CCD Detector (×100/1. 4 oil immersion objective). Images were analyzed using ImageJ software.
(C) Platelet TPM4 RNA levels measured by RT-PCR using GAPDH as housekeeping gene. Graph depicts representative data from a total of n = 3 measurements from 1 (case 1-II-5) or 3 (case 1-III-7) patient samples. (D) Platelet TPM4 protein is reduced in heterozygous carriers of the TPM4 variant. Graph depicts representative data from a total of n = 3 measurements from 1 (case 1-II-5) or 3 (case 1-III-7) samples. Left: Densitometry analysis performed using ImageJ. Right: Protein levels of platelet TPM4 in controls and cases 1-II-5 and 1-III-7. β-Actin was included as an internal loading control. Similar results were obtained when GAPDH was used as a loading control (not shown). (E) Sex-stratified histograms of platelet count (PLT) and mean platelet volume measurements obtained using a Sysmex hematology analyzer from 48,345 blood donors from the INTERVAL study after adjustment for technical artifacts.
Acknowledgments The research participants were enrolled in the  Biomedical Research Centres/Units Inherited Diseases Genetic Evaluation (BRIDGE) Bleeding and Platelet Disorders (BPD) study  ( UK REC10/H0304/66 ). We are grateful to all the donors who allowed us to use their samples for this study. We thank  Sofia Papadia  from the  NIHR BioResource  for organizing the recalls of BRIDGE-BPD participants. The genome sequencing of the BRIDGE-BPD participants was supported by the  NIHR BioResource-Rare Diseases  (to ET, KD, and WHO). The  NIHR BioResource-Rare Diseases  is responsible for the delivery of the rare diseases pilot phase of the 100,000  Genomes  Project and is funded by the  National Institute for Health Research (NIHR ; http://www. nihr. ac. uk). Research in the Ouwehand laboratory also receives funding support from the  European Commission ,  NIHR ,  Wellcome Trust, Medical Research Council  (MRC), and  British Heart Foundation  under numbers  RP-PG-0310-1002  and  RG/09/12/28096.
We are grateful to  Janelle E. Collinge  for outstanding technical assistance with gene mapping studies. We thank  E. Major ,  S. Ross ,  T. Carle ,  T. Gibbs , and  S. Green  for outstanding animal husbandry assistance,  J. Corbin  for Advia analysis, and  Emma C. Josefsson  for the purification of human platelets. Confocal microscopy work on human samples was supported by the  Cambridge NIHR Biomedical Research Centre Cell Phenotyping Hub. We thank  Jeremy Skepper  and  Janet Powell  of the  Cambridge University Advanced Imaging Centre  for technical support with electron microscopy imaging. SKW is supported by an  MRC   Clinical Training Fellowship  ( MR/K023489/1 ). ADM receives support from the  Bristol NIHR Biomedical Research Unit for Cardiovascular Disease. This work was supported by a  Project Grant  (no.
+/M, heterozygous; +/+, WT. (C) Platelet TPM4 RNA levels measured by RT-PCR using GAPDH as housekeeping gene. Graph depicts representative data from a total of n = 3 measurements from 1 (case 1-II-5) or 3 (case 1-III-7) patient samples. (D) Platelet TPM4 protein is reduced in heterozygous carriers of the TPM4 variant. Graph depicts representative data from a total of n = 3 measurements from 1 (case 1-II-5) or 3 (case 1-III-7) samples. Left: Densitometry analysis performed using ImageJ. Right: Protein levels of platelet TPM4 in controls and cases 1-II-5 and 1-III-7. β-Actin was included as an internal loading control. Similar results were obtained when GAPDH was used as a loading control (not shown). (E) Sex-stratified histograms of platelet count (PLT) and mean platelet volume measurements obtained using a Sysmex hematology analyzer from 48,345 blood donors from the INTERVAL study after adjustment for technical artifacts.
MeTHODs Patients This multicentre, randomised, double-blind, placebo-controlled, parallel-group trial was conducted at 103 centres in 15 countries (Austria, Belgium, Canada, France, Germany, Japan, Netherlands, Norway, Poland, Serbia, Slovakia, South Africa, South Korea, Spain, USA), beginning in April 2011 and was completed in October 2015. The protocol was approved by the institutional review board or ethics committee at each centre. (Protocol amendment information is provided in the online supplementary text. ) All patients gave written, informed consent. All authors had access to study data and have reviewed and approved the final report. The study is registered on ClinicalTrials. gov (NCT 01276509). Eligible patients were aged 18-75 years with moderate-to-severe ileal (terminal ileum), ileocolonic or colonic CD (Crohn's Disease Activity Index (CDAI) score 220-450 and ulcers on colonoscopy performed and interpreted locally at the study site during or within 8 weeks prior to screening).
efficacy and safety assessments Patients were evaluated at weeks 0 (baseline), 2, 4, 6, 8, 10 and 12 (or at the withdrawal visit). At each visit, electronic diarycard data were collected, a clinical assessment of CD and a physical examination were carried out, disease activity measured by CDAI, adverse events (AEs) and concomitant medications reported and samples taken for laboratory analysis. At each visit, patients underwent neurological assessment, which consisted of five tests: confrontational visual fields, timed 25-foot walk, ninehole peg test, symbol-digit modality test and Multiple Sclerosis Neuropsychological Questionnaire. Neurology consultation was requested if significant unexplained changes were observed.
The family-wise error rate is controlled at one-sided 0. 05 using the Bonferroni method for two time points (week 8 or week 12). Because this was a phase II study, the family-wise error rate was controlled at 5% rather than at the 2. 5% that is typically used for phase III studies. Posthoc analyses were performed to assess CDAI-70 response and CDAI remission in subgroups of patients with baseline hsCRP concentrations>5. 0 mg/L and >18. 8 mg/L (median) and patients with baseline median Simple Endoscopic Activity Score-Crohn's Disease (SES-CD) 16 >10 (25th percentile) and >17 (median). In most patients, the SES-CD was calculated using data from endoscopies performed at baseline; in patients who underwent endoscopy 8 weeks prior to randomisation, the SES-CD score was calculated using data from that procedure.