dataesr/scientific-paragraphs-categorization huggingface dataset:
Global Level Based on All High-Quality Reads and Non-Redundant Gene Catalogue Metagenomic data were metabolically profiled by using HUMAnN. All high quality reads were aligned with Bowtie2 to the KEGG database  (Kanehisa et al. , 2012 ) (Release: February, 24, 2014) , from which sequences of eukaryotes had been excluded. The alignments were transformed into bam format with SAMtools (H. Li et al. , 2009)  and input into HUMAnN to obtain the abundance of KOs and pathways. The linear discriminant analysis (LDA) effect size (LEfSe)  (Segata et al. , 2011)  was used to identify enzymatic pathways that were significantly different between pre-and post-intervention. The protein sequences of formate-tetrahydrofolate ligase (GI|293416147|), Propionyl-CoA:succinate-CoA transferase (GI|218353245), propionate CoA-transferase (GI|7242549|), and butyryl-CoA transferase (GI|71081820|)  (Claesson et al.
Bacterial CAGs Level For each of the 118 bacterial CAGs, the open reading frames (ORFs) were identified using myRAST  (Overbeek et al. , 2014). The reference protein sequences of tryptophanase (K01667) were collected from the KEGG database. Sequences of choline TMA-lyase (GI|219868924|) and choline TMA-lyase-activating enzyme (GI|219868925|)  (Craciun and Balskus, 2012)  were downloaded from the NCBI database. The potential tryptophanase, choline TMA-lyase and choline TMA-lyase-activating enzyme in bacterial CAGs were identified by aligning the ORF protein sequences against the references with BLASTP (best-hit with E-value b1E-5, identity N30% and coverage N70%). Additionally, for identification of choline TMA-lyase and choline TMA-lyase-activating enzyme, we required that they co-exist as components in a cluster.
Association Between Microbiota and Urine Metabolome To aid interpretation of the relationship between the bacterial CAGlevel microbiota and metabolomics datasets, we integrated them using a multivariate method known as co-inertia analysis (CIA)  (Fagan et al. , 2007). PCA was applied to each of the individual datasets as inputs for the CIA. Ordinations of the two datasets that are maximally co-variant were identified to find the shared biological trends within the two datasets. CIA was performed by ade4 package in R. The bootstrapped Spearman correlation coefficients between bacterial CAGs and indoxyl sulfate or TMAO based on their abundance in all the samples were calculated.
Functional Modulation of the Gut Microbiota To see how the altered community structure of the gut microbiota affected its metabolic potential, we profiled the metagenomic data using HUMAnN to identify and quantify genes within biochemical pathways  (Abubucker et al. , 2012). In total, 5234 KEGG orthology groups (KOs) were recognized and quantified. The PCA score plot of all the KOs showed a significant shift after the intervention (MANOVA test, P = 2. 00e-7, Fig. 4a  and b ), indicating a modulation of the metabolic capacity of the gut microbiota concomitant with its diet-induced structural changes. There was no significant difference between the PWS and SO cohorts either before or after the intervention (MANOVA test P = 0. 712 and P = 0. 291, Fig. 4b ). Thus, gut microbiota between PWS and SO children shared similar structural and functional features both before and after the intervention.
Using the linear discriminant analysis (LDA) effect size (LEfSe) method  (Segata et al. , 2011) , 67 KEGG database biochemical pathways (P b 0. 05) were identified as significantly responding to the dietary intervention (Fig. 4c ). 41 of these pathways were significantly decreased and 26 were enriched after the intervention. Notable among the enriched pathways were those for carbohydrate catabolism, including starch and sucrose metabolism (ko00500), and amino sugar and nucleotide sugar metabolism (ko00520). Notable among the decreased pathways were those for fat and protein metabolism, including fatty acid biosynthesis (ko00061), phenylalanine metabolism (ko00360), and tryptophan metabolism (ko00380). In addition, lipopolysaccharide biosynthesis (ko00540), peptidoglycan biosynthesis (ko00550) and flagellar assembly (ko02040) pathways were decreased, suggesting reduced bacterial antigen synthesis after the intervention.
S21  and S22 ). The cytotoxicity of fecal water samples to cultured human Caco-2 cells was significantly reduced in SO and slightly in PWS cohorts after the intervention, indicating that the post-intervention microbiota may have produced less toxic metabolites in the gut (Fig. S25 ). To more closely examine how the dietary intervention changed the carbohydrate metabolism of the gut microbiota, we searched all the 2,077,766 non-redundant gut genes from our study against the dbCAN database to identify genes coding for carbohydrate-active enzymes (CAZy)  (Cantarel et al. , 2012; Scott et al. , 2013). 84,549 genes were assigned to 299 CAZy families, which significantly differ in the pre-and post-intervention samples, indicating a shift in the genes for carbohydrate metabolism in the gut microbiome (Fig.
Acknowledgment This work was supported by the grants from the  National Natural Science Foundation of China  ( 31330005 ,  81100632 ,  31121064 ,  20825520 ,  81401141  and  21221064 ); the  Ministry of Science and Technology of China  ( 2010CB912501 ); the  Science and Technology Commission of Shanghai Municipality  ( 14YF1402200 ) and the  National Science and Technology Major Project of China  ( 2012ZX10005001-009 ). A computing facility award on the PI cluster at  Shanghai Jiao Tong University  is acknowledged. We thank  Prof. Zhu Chen  from  Shanghai Center for Systems Biomedicine  for his insightful discussion and guidance in designing the experiment.
Because D3G is poorly absorbed, the intestine can be a target for this toxin  (De Nijs et al. 2012 , Nagl et al. 2012 , Nagl et al. 2014). The purpose of this study was to investigate the toxicity of D3G on the intestine. An in silico analysis indicates that D3G is unable to bind to the ribosome and suggests a lack of toxicity of this compound. The toxicity of D3G was further assessed on intestinal cells and explants; physiological, morphological and transcriptomic analysis confirmed the absence of adverse effects of D3G. Our paper provides the first insight into the toxicity of this plant conjugate on the small intestine. Material and methods (Additional data are available in Online resource (Online resource 1)) Toxins Purified DON was purchased from Sigma-Aldrich (St Louis, MO, USA). D3G was isolated from DON-treated wheat  (Berthiller et al.
32 ± 0. 83. Reverse transcription and RT-qPCR steps were performed as already described  (Halloy et al. 2005; Gourbeyre et al. 2015). Primers are indicated in the Table (Online ressource 2). Amplification efficiency and initial fluorescence were determined by the ΔCt method. Obtained values were normalized using two reference genes, ribosomal protein L32 (RPL32) and cyclophillin A. mRNA expression levels were expressed relative to the mean of the control. The 60K microarray  (Voillet et al. 2014 ) was used as described in the supplemental Material (see Supplemental Material, Part Methods). The experimental details are available in the Gene Expression Omnibus (GEO) database under accession GSE66918 (http://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?token=olixoosedvmdnqr& acc=GSE66918). Microarray data from Feature Extraction software was analyzed with R using Bioconductor packages.
8. 5. 1 software. All experimental details are available in the Gene Expression Omnibus (GEO) database under accession GSE66918 (http://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?token=olixoosedvmdnqr &acc=GSE6691 8). Microarray data from Feature Extraction software was analyzed with R (www. r-project. org, R v. 3. 0. 1), using Bioconductor packages  (www. bioconductor. org, v 2. 12, ((Gentleman et al. 2004).
We also performed chromatin immunoprecipitation and sequencing (ChIP-seq) on normal and cancer cell lines to assess Xi chromatin status. We investigated H3K27me3 (associated with the inactive state of the Xi), H3K4me3 (enriched at transcriptional start sites [TSSs] of active genes), and RNA Pol II. The comparison of quantile-normalized H3K27me3 profiles revealed major changes for the X chromosomes between normal and tumor cells (Fig. 6A ). In HMECs, low-resolution chromosome-wide profiles exhibited a pattern of domains that is highly reminiscent of the distinct nonoverlapping regions of the human Xi previously reported for H3K9me3 and H3K27me3  (Chadwick 2007; Chadwick and Willard 2004). Indeed, comparing the H3K9me3 and H3K27me3 data from the ENCODE Project Consortium (2012) with our H3K27me3 ChIP-seq data sets, these different types of heterochromatin domains are readily detectable in normal HMEC and WI-38 cells (Supplemental Fig.
Microscopy Images were generated using a Nikon confocal spinning disk microscope fitted with a 60×/1. 4 OIL DIC N2 PL APO VC objective. For super resolution imaging, structured illumination (3D-SIM) was performed using a DeltaVision OMX microscope (GE Healthcare). Human SNP Array 6. 0 DNA and nascent RNA experiments DNA copy number profiles Genomic profiling was performed at Institut Curie using Affymetrix Human SNP Array 6. 0; cell files were processed by Genotyping Console 3. 0. 2 (Affymetrix, reference model file HapMap270, version 29). Human SNP Array 6. 0 data were mined using the previously described and validated GAP method  (Popova et al. 2009). Segmental absolute copy numbers and allelic contents (major allele counts) were detected. R scripts and full details of the application are available at http://bioinfo-out.
Nascent RNA allelic expression Preparation of samples and analysis of nascent RNA were performed as described previously  (Gimelbrant et al. 2007 ). Briefly, we purified nuclei of assessed cell lines (Nuclei Pure Isolation Kit, Sigma) and subsequently purified nuclear RNA (by classical phenol:chlorophorm extraction). Then, we hybridized cDNA obtained by reverse transcription of nuclear RNA of each sample onto Affymetrix Human SNP Array 6. 0. Data was normalized by Genotyping console, and raw single-SNP intensities were taken as allelic expression of corresponding genes. Each SNP was characterized by (  1 ) global expression level score; (2) allelic expression ratio score; and (3) genomic status (loss or retention of heterozygosity score), which were summarized into a biallelic and monoallelic expression status.
Acknowledgments We would like to thank all members of the  Heard team  for helpful discussions and in particular  Julie Chaumeil  and  Simao da Rocha  for critical reading of the manuscript. We would also like to thank  Michel Wassef  and  Raphael Margueron  for discussions and feedback on this work. Support is gratefully acknowledged from l' Association pour la Recherche sur le Cancer (ARC)  (post-doctoral fellowship to R. C. );  FRM (Equipe FRM  to E. H. from 2006-2009);  Equipe labellisée "La Ligue Contre Le Cancer" (Equipe Labellisée  to E. H. since 2011);  EU   FP7 MODHEP EU  Grant no. 259743  (to E. H. );  Labex DEEP  ( ANR-11-LBX-0044 ) part of the  IDEX Idex PSL  ( ANR-10-IDEX-0001-02 PSL ); and  ERC Advanced Investigator  Award no. 250367. This work was also supported by the  AVIESAN-ITMO Cancer-INCa  grant " Epigenomics of breast cancer " (E.
H. , H. G. , and M. -H. S. ). Work in the laboratory of H. G. was supported by the  Agence Nationale de la Recherche  ( ANR-10-LABX-0030-INRT  and  ANR-10-IDEX-0002-02 ), the  Ligue Contre le Cancer  (H. G. ; Equipe Labellisée),  SATT Conectus Alsace , and the  Institut Nationale du Cancer. The authors greatly acknowledge the  PICT-IBiSA@BDD  ( UMR3215/U934 ) Imaging facility of the  Institut Curie , the cytometry platform of the  Institut Curie, and the "Centre de Ressources Biologiques " for access to the tumor materials.
These data supported the efficiency and specificity of our SSOs to mediate Cep290 exon skipping in vitro. We thus assessed the retinal distribution of SSOs and splicing alteration using the iv delivery route. To this aim, we examined retinal sections and Cep290 mRNA from 8-week-old C57BL/6J mice eyes at day 2 following a unique and unilateral iv injection of variable doses (1, 5, 10 nmoles) of a fluorescently-labeled (6-FAM)-m22D SSO in saline solution (NaCl 9 g/l; pH = 8. 7; 290 mOsm/kg); fellow untreated eyes were used as controls. Confocal microscopy analysis of retinal sections from injected eyes detected panretinal fluorescent signals (Figure  2a ; Supplementary Figure  S3 ). Signals in the photoreceptor cell layer were maximal at the highest SSO dose (10 nmoles; Figure  2a ). RT-qPCR analysis of retinal mRNA identified a transcript lacking exon 22 which in abundance increased with SSO concentrations (Figure  2b ).
To assess this hypothesis, we measured the wild-type and mutant mRNA abundance at 2, 6, and 10 dpi of 10 nmoles of the m22D SSO, which targets a part of intronic sequence, absent in the cytoplasm. We observed a moderate decrease of the wild-type mRNA abundance consistent with the production of a mutant mRNA at the expense of the Cep290 pre-mRNA (Supplementary Figure  S4 ). Together, these data are consistent with the hypothesis according to which SSOs recognizing exon-only sequences can be sequestrated by cytosolic mRNA molecules which are not subjected to nonsense-mediated mRNA decay. 16 The high expression of Cep290 in the retina  17  further supports this hypothesis. The subcellular expression of Cep290 mRNA in the mouse retina has not been documented to our knowledge. In the zebrafish, in situ hybridization analysis has shown that the gene is expressed in all retina cell layers, including the ganglion cell layer, the inner nuclear layer and the photoreceptors cell layer.
Design of SSOs and control oligonucleotides (ONs). SSOs were designed from the wild-type mus musculus Cep290 (UCSC accession number uc011xmr. 1) and AbcA4 (UCSC accession number uc008rel. 1) sequences using the m-fold and ESEfinder  48  programs available online at http://mfold. rna. albany. edu/ and http://rulai. cshl. edu/cgi-bin/tools/ESE3/esefinder. cgi, respectively. SSOs were designed to target ESE and donor-splice site sequences of Cep290 exon 22 and 35 and an ESE sequence of Abca4 exon 10, respectively. Sense versions of SSOs (control ONs) targeting Cep290 and Abca4 ESE sequences were designed to control the specificity of SSOs. SSOs and control ONs were synthetized as fluorescently labeled (6-FAM) and unlabeled 2'-O-methyl phosphorothioate oligonucleotides by Sigma-Aldrich (St Quentin Fallavier, France).
7 available at http://www. oligo. net. The specificity of primer pairs to PCR template sequences was checked against the NCBI database using the Primer-BLAST software (http://www. ncbi. nlm. nih. gov/tools/primer-blast). Primer sequences were as follows: Cep290ex22wt forward, 5′-tgactgctaagtacagggacatcttg-3′; Cep290ex22wt reverse, 5′-aggagatgttttcacactccaggt-3′; Cep290ex22mt forward, 5′-ctgg ccccagttgtaatttgtga-3′; Cep290ex22mt reverse, 5′-ctgttcccagg cttgttcaatagt-3′; Cep290ex35wt forward, 5′-tgactgctaagtaca gggacatcttg-3′; Cep290ex35wt reverse, 5′-aggagatgttttcacac tccaggt-3′; Cep290ex35mt forward, 5′-ctggccccagttgtaatttg tga-3′; Cep290ex35mt reverse, 5′-ctgttcccaggcttgttcaatagt-3′. Reference genes Tbp forward, 5′-tgacctaaagaccattgcacttcgt-3′; Tbp reverse, 5′-ctgcagcaaatcgcttggga-3′; B2m forward, 5′-cctg tatgctatccagaaaacccct-3′; B2m reverse 5′-cgtagcagttcagtatg ttcggctt-3′; Gusb forward, 5′-ctgcggttgtgatgtggtctgt-3′; Gusb reverse, 5′-tgtgggtgatcagcgtcttaaagt-3′; Hprt1 forward, 5′-gttgg atacaggccagactttgtt-3′; Hprt1 reverse, 5′-aaacgtgattcaaatccctg aagta-3′; Ppia forward, 5′-ccaaacacaaacggttcccagt-3′; Ppia reverse, 5′-gcttgccatccagccattca-3′; Alb forward 5′-gggacagtgagtacccagacatcta-3′; Alb reverse 5′-ccagacttggtgttggatgctt-3′.
Sevenmicron serial sections of tissues were prepared from paraffined treated and untreated eyes. To evaluate the dissemination of (6-FAM)-m22D, (6-FAM)-m35ESE SSOs and (6-FAM)-m35ESEsense oligonucleotide through the retina, the tissue sections were mounted onto glass slides with Prolong gold antifade mounting media containing 4′,6′-diamidino-2phenylindole (DAPI) (Invitrogen) to stain nuclei and examined by confocal microscopy (ZEISS LSM700). Images were generated using the ImageJ software. Statistical analysis. The statistical significance of the difference between three or more means was determined using a Mann-Whitney test. Statistical analysis was performed using the Biostatgv program available online at http://biostatgv. sentiweb. fr. *P values < 0. 05 were considered significant. experiments; X.
Acknowledgments. We thank  Michael Nicouleau  and  Gérard Pivert  for technical assistance. This work was supported by grants from the  Association Française contre les Myopathies (AFM)  to X. G. ,  Retina France  to  J. -M. R. , and the  JED  foundation to J. -M. R. X. G. , J. K. , A. M. , and J. M. R. conceived of and designed experiments; X. G. and I. P. performed.
Recent modelling studies have indicated that icebergs play an active role in the climate system as they interact with the ocean and the atmosphere. The icebergs' impact is due to their slowly released meltwater, which freshens and cools the ocean and consequently alters the ocean stratification and the sea-ice conditions. The spatial distribution of the icebergs and their meltwater depends on the atmospheric and oceanic forces acting on them as well as on the initial icebergs' size. The studies conducted so far have in common that the icebergs were moved by reconstructed or modelled forcing fields and that the initial size distribution of the icebergs was prescribed according to present-day observations. To study the sensitivity of the modelled iceberg distribution to initial and boundary conditions, we performed 15 sensitivity experiments using the iLOVECLIM climate model that includes actively coupled ice sheet and iceberg modules, to analyse (1) the impact of the atmospheric and oceanic forces on the iceberg transport, mass and melt flux distribution, and (2) the effect of the initial iceberg size on the resulting Northern Hemisphere climate including the Greenland ice sheet, due to feedback mechanisms such as altered atmospheric temperatures, under different climate conditions (pre-industrial, high/low radiative forcing).
Third, the initial size distribution of the icebergs is prescribed and based on presentday observations  (Dowdeswell et al. , 1992 ). Yet, this chosen size distribution may not be a valid representation of calving events in past or future climate conditions. We therefore propose in this study to extend the approach of  Bügelmayer et al. (2015) , evaluating in detail the impact of the modelled forcing fields and iceberg size distributions. We use the same earth system model of intermediate complexity (iLOVECLIM) coupled to an ice sheet/ice shelf model (GRISLI) and an iceberg module to answer the following research questions. 1. How do atmospheric and oceanic forcing fields affect the icebergs (their lifetime and movement) in the Northern Hemisphere under pre-industrial conditions? 2. How sensitive are the pre-industrial Northern Hemisphere climate and the Greenland ice sheet to spatial variations in the iceberg melt flux? 3.
Methods We use the earth system model of intermediate complexity iLOVECLIM (version 1. 0) which is a code fork of the LOVECLIM climate model version 1. 2  (Goosse et al. , 2010). iLOVECLIM differs in the ice sheet module included  (Roche et al. , 2014)  and the further developed iceberg module  (Bügelmayer et al. , 2015) , but shares some physical climate components (atmosphere, ocean and vegetation) with LOVECLIM.
Acknowledgements. M. Bügelmayer is supported by  NWO  through the  VIDI / AC2ME  project no. 864. 09. 013. D. M. Roche  is supported by  NWO  through the  VIDI / AC2ME  project no. 864. 09. 013  and by  CNRS-INSU. The authors wish to thank  Catherine Ritz  for the use of the GRISLI ice sheet model and all the anonymous reviewers for providing valuable comments. Institut Pierre Simon Laplace  is gratefully acknowledged for hosting the iLOVECLIM model code under the LUDUS framework project (https://forge. ipsl. jussieu. fr/ludus). This is NWO/AC2ME contribution number  08. Edited by:  R. Marsh.
Code availability The iLOVECLIM source code is based on the LOVE-CLIM model version 1. 2 whose code is accessible at http:// www. elic. ucl. ac. be/modx/elic/index. php?id=289. The developments on the iLOVECLIM source code are hosted at https: //forge. ipsl. jussieu. fr/ludus, but are not publicly available due to copyright restrictions. Access can be granted on demand by request to D. M. Roche (didier. roche@lsce. ipsl. fr). The specific experimental set-up used for this study is available at https://forge. ipsl. jussieu. fr/ludus. The Supplement related to this article is available online at doi:10. 5194/gmd-8-2139-2015-supplement.
Whole exome sequencing and follow-up screenings Whole exome sequencing of a patient with Dravet-like syndrome and his unaffected parents and downstream analysis only revealed a single de novo variant: a heterozygous missense mutation, c. 1,124G>A, p. Gly375Asp in  GPHN (NM_001024218, Fig 1A). We validated the mutation and confirmed the de novo status using classical Sanger sequencing. The nucleotide and the corresponding amino acid are both highly conserved (GERP: 5. 77; Fig  1B ). The mutation is not present in control databases (1000 Genomes Project, Exome Variant Server, dbSNP, in-house data), and only two other missense variants in the same exon have been detected in > 33,600 European individuals (ExAc Browser). The p. Gly375Asp mutation is predicted to be damaging by prediction programs (Polyphen-2: probably damaging [1], SIFT: damaging [0], MutationTaster: disease causing [1]).
Whole exome sequencing and data analysis Whole exome sequencing was performed on blood-extracted DNA of a patient with Dravet-like syndrome and his healthy parents at the Wellcome Trust Sanger Institute (Hinxton/Cambridge, UK). This patient was part of a larger cohort of patients with Dravet(-like) phenotypes that were selected for WES as part of the EuroEPI-NOMICS-RES project. As in approximately 80% of patients with Dravet syndrome an SCN1A mutation is found, SCN1A mutations had to be excluded upfront. 3 lg of genomic DNA was sonicated to fragments of 150-200 bp and purified. The exome was then captured using the SureSelect Human All Exon 50 Mb kit (Agilent), and next-generation sequencing (NGS) was performed on a HiSeq2000 (Illumina) platform as 2 × 75 bp paired-end reads. Mapping of the reads to the reference genome (hg19, UCSC Genome Browser) was done using Burrows-Wheeler Aligner (BWA)  (Li & Durbin, 2010).
The dataset was further filtered using the following criteria: (i) read depth in all individuals ≥ 8; (ii) allele balance in the patient ≥ 0. 95 and in the parents between 0. 25 and 0. 75 for filtering under a homozygous model and between 0. 25 and 0. 75 in the patient and his parents for the compound heterozygous model; (iii) exclusion of variants in tandem repeats and segmental duplications; and (iv) a frequency of ≤ 1% in control databases (1000 Genomes Project, Exome Variant Server, in-house data).
NGS was then carried out on the pooled amplicons using a MiSeq sequencer (Illumina) as 2 × 300 bp paired-end reads (v3 kit, Illumina). Using this assay, we screened 164 patients with epilepsy and ID. The generated reads were aligned to the reference genome (hg19, UCSC Genome Browser) using BWA, and variants were called using GATK Unified Genotyper  (McKenna et al, 2010)  and SAMTools  (Li et al, 2009). For the downstream analysis of the variants, we used GenomeComb  (Reumers et al, 2012). (II) In a second set of samples, we performed targeted capturing of all exons and 5 bp of flanking intronic sequence of the GPHN gene using MIPs as previously described  (Carvill et al, 2013). Briefly, following hybridization and capturing, sequences are PCRamplified, incorporating an Illumina adaptor and a sample-specific barcode to allow sample pooling.