dataesr/scientific-paragraphs-categorization huggingface dataset:
These results indicate that overexpression of IGF2 has no major effect on the expression of the members of its signaling pathway. We then examined whether the activation of the IGF, Erk, and Akt pathways was different between IGF2-high and IGF2-low ACC. We assessed the abundance of the phosphorylated forms of these proteins in 10 tumors from each group by western blotting. The phosphorylation of IGF1 and insulin receptors was higher in IGF2-high carcinoma than in IGF2-low carcinoma, but there was no difference in the phosphorylation status of Akt and Erk1/2 when normalizing to total Akt or Erk1/2 respectively (Figure  3 ) or actin (data not shown). These results are very surprising because the higher expression of IGF2 in IGF2-high ACC should result in a robust stimulation of these two pathways.
Study design and patient eligibility This was a multicenter, open-label, nonrandomized, phase 2 study that evaluated the safety and efficacy of MK-0457 in patients with either CML or Ph+ ALL and confirmed BCR-ABL T315I mutation (ClinicalTrials. gov identifier: NCT00405054; http://clinicaltrials. gov/ct2/show/ NCT00405054; Protocol 008). Bone marrow aspirate and blood for molecular analysis were collected at screening and analyzed locally to detect the BCR-ABL T315I mutation. Bone marrow aspiration and/or biopsy was conducted before every other cycle for the first 3 months and then every 3 months, at the time of discontinuation and every 3 months during follow-up, and/or as clinically indicated or to confirm a response. Locally available assays were used for detection of the T315I mutation (examples included direct sequencing, fluorescence resonance energy transfer hybridization probe detection and denaturing high performance liquid chromatography).
Enhancer function Human sequences were cloned upstream hsp70 zebrafish core promoter  60  or gata2 promoter 61 linked to a Venus reporter and used to inject >200 eggs from wild-type (AB*) and Tg(ins:mCherry)jh2 Zebrafish in three independent experiments. Reporter expression patterns were documented using NIS-Elements software (Nikon). Expression was quantified by counting the number of embryos showing Venus+ cells in different tissues (Supplementary Table  9 ). Islet-specific expression patterns from transient transgenics were confirmed in stable transgenic lines (Supplementary Figure  8 ). Transcription factor-bound C3 sites were also cloned in Gateway-adapted PGL4. 23 and cotransfected in triplicate wells with pRL in MIN6 and 3T3 cells, and luciferase activity was measured after 48 hr. Results were expressed as luciferase/renilla ratios in vectors carrying putative enhancers, relative to the ratio in empty PGL4.
Acknowledgments We thank  J. Rios  ( IDIBAPS ) for expert statistical advice,  M. Parsons  ( Johns Hopkins University ) for Tg(ins:mCherry)jh2 transgenics and  R. Stein  ( Vanderbilt University ),  J. Habener  ( Harvard University ) and  G. Gradwohl  ( Institute of Genetics and Molecular and Cellular Biology ) for MAFA, IDX1, and NGN3 DNA constructs. We thank the DIAGRAM and MAGIC consortia, the  Singapore Prospective Study Program , the  Singapore Consortium of Cohort Studies , the  Singapore Indian Eye Study , the  Singapore Malay Eye Study  and  Y. Y. Teo ,  E. S. Tai ,  T. Y. Wong ,  W. Y. Lim  and  X. Wang  ( National University of Singapore ; funded by the  National Medical Research Council of Singapore ,  Singapore Translational Researcher Award schemes , the  Biomedical Research Council of Singapore  and the  National Research Foundation (NRF)  Fellowship scheme).
This work was carried out in part at the  Centre Esther Koplowitz. This work was funded by grants from a  European Foundation for the Study of Diabetes Lilly fellowship (L. Pasquali) , the  Ministerio de Economía y Competitividad  ( SAF2011-27086  to J. F. ,  BFU2010-14839  and  CSD2007-00008  to J. L. G. S. ), the  Innovative Medicines Initiative  (DIRECT to M. I. M. and J. F. ), the  Andalusian Government  ( CVI-3488  to J. L. G. S. ), the  Biology of Liver and Pancreatic Development and Disease Marie Curie Initial Training Network  (F. M. and J. F. ), the  Wellcome Trust  ( 090532 ,  98381  and  090367  to M. I. M. , 095101 to A. L. G. , 101033 to J. F. ),  Juvenile Diabetes Research Foundation  ( 31-2012-783  to T. B. , F. P. and  L. Piemonti ) and  Framework Programme 7  ( HEALTH-F4-2007-201413  to M.
FAIRE and ChIP Human islets processed for FAIRE and ChIP as described 5,54,55 using 1-1. 5 μg antibodies against H3K4me1 (ab-8895), H3K4me3 (Upstate 05-745), H3K27ac (Abcam ab4729), CTCF (Millipore, 07-729), H2A. Z (Abcam ab4174, Millipore 09-862), Pdx1 (BCBC, AB2027), FOXA2 (Santa Cruz, sc-6554), Nkx2. 2 (Sigma, HPA003468), MafB (Sigma, HPA005653), Nkx6. 1 (Sigma, HPA036774). Expected cell-specific and subcellular patterns of formalin-fixed epitopes were ascertained by western blotting on human islet extracts and dual immunofluorescence of human pancreas (Supplementary Fig. 1b, c ).
ACKNOWLEDGMENTS This work was supported by the  Centre National de la Recherche Scientifique (CNRS). Morgane Batzenschlager 's PhD was funded by the  Ministère de l'Enseignement Supérieur et de la Recherche. The microscopy experiments were carried out using devices from the Strasbourg-Esplanade cellular imaging facilities sponsored by the  CNRS , the  Université de Strasbourg , and the  Région Alsace , the  Association de la Recherche sur le Cancer  and the  Ligue Nationale contre le Cancer  (http://ibmp. fr?id=micro). We are very grateful to  L. Blech  for his valuable advice.
This repartition a posteriori validates robust changes in gene expression hitherto obtained through dayscreenings as reported in the literature  [13, 16, 17, 18, 19, 20, 21, 22]. However, a substantial part of developmentally regulated changes in gene expression occurring specifically at night was totally overlooked so far. Transcripts modulated in microvine berries between green and ripening stages were compared with data extracted from  Fasoli et al. , 2012 [44]  conducted on Vitis vinifera cv Corvina berries, available in the Gene Expression Omnibus under the series entry GSE36128 (http:// www. ncbi. nlm. nih. gov/geo/query/acc. cgi?token = lfcrxesyciqgs joandacc = GSE36128). 1970 transcripts were detected in Corvina berries between the stages called ''post-fruit set'' (green berry) and ''ripening''.
Nimblegen 12x Microarray Hybridization cDNA synthesis, labeling, hybridization and washing reactions were performed according to the NimbleGen Arrays User's Guide (V 3. 2). Hybridization was performed on a NimbleGen microarray 090818 Vitis exp HX12 (Roche, NimbleGen Inc. , Madison, WI), consisting of 29,549 predicted genes on the basis of the 12X grapevine V1 gene prediction version V1 http://srs. ebi. ac. uk/. The chip probe design is available at the following url: http:// ddlab. sci. univr. it/FunctionalGenomics/. The raw data is available at the Gene Expression Omnibus (http://www. ncbi. nlm. nih. gov/ geo/info/linking. html) under the series entry GSE52829.
Statistical Analysis The Robust Multi-array Analysis (RMA) algorithm was used for background correction, normalization and expression levels  [168]. Differential expression analysis was performed with the bayes tstatistics from the linear models for microarray data (limma)  [169]. P-values were corrected for multiple-testing using the Benjamini-Hochberg's method  [170]. Transcripts were considered as significantly modulated when absolute change was. 2 fold (log 2 fold change. 1) and adjusted p. value was ,0. 05 between two conditions. Gene clustering was performed on mean centered values of RMA normalized and log 2 transformed expression data. This analysis was performed using the Multiple Experiment Viewer version 4. 6. 2H software package, and based on the kmeans method using Pearson's correlation distance calculated on the gene expression profiles.
This work is part of the  DURAVITIS program  which is financially supported by the  ANR (Agence national de la recherche)  - Genopole  (project  ANR-2010-GENM-004-01 ) and the Jean Poupelain foundation (30  Rue Gate Chien ,  16100  Javrezac, France). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Cdc42 regulates fusion pore dynamics Next we monitored exocytosis in BON cells with a submillisecond time resolution using carbon fiber amperometry  (Chow et al. , 1992; Fisher et al. , 2001; Amatore et al. , 2003; Desnos et al. , 2003). This technique, which involves carbon fiber electrodes apposed onto the cell surface, measures the oxidation of serotonin molecules released upon exocytosis and reports single fusion events as current spikes. Typical recordings are shown in Figure  2A. To evaluate the secretory activity, amperometric spikes >0. 4 pA, that is, five times the magnitude of the root mean square electrical noise, were automatically counted. In sharp contrast with data obtained by TIRFM, we could detect only subtle or nonsignificant reduction of the occurrence of exocytosis in Cdc42-knockdown cells compared with control cells (Figure  2C ).
Bar, 5 μm. (J) Single SGs imaged by TIRFM were tracked, and the D xy values were computed along trajectories using a rolling analysis window. Subtrajectories characterized by a D xy lower than the threshold value of 5 × 10 -4 μm 2 /s were defined as an immobilization period. A survival plot of immobilization events is shown. Control, 19 cells, 2978 trajectories; siCdc42-A, 18 cells, 2283 trajectories; siCdc42-C, 17 cells, 2917 trajectories; from three independent experiments. Data were fitted with the sum of two exponentials. Cdc42 silencing did not significantly alter SG immobilization, suggesting unimpaired SG attachment at the plasma membrane. blebbistatin impairs fusion pore expansion. We therefore conclude that membrane tension is a driving force for fusion pore dilation and that Cdc42 controls this force (see Figure  8D  for a schematic representation of this conclusion).
Bar, 500 nm. (C) Dot plots of SG diameter. Diameters were computed from the area of the segmented SGs, assuming a circular shape. Each dot represents the mean value of SG diameter in a given cell. The data indicate that Cdc42 knockdown did not change SG size (p = 0. 67, one-way ANOVA). (D) BON cells were transfected with bVMAT1 and control, siCdc42-A, or siCdc42-C siRNA duplexes, as indicated. Three days later, the cells were incubated for 2 h at 37°C with [ 3 H]serotonin in the presence or the absence of 1 μM reserpine, an inhibitor of the vesicular monoamine transporter. The mean (N = 3 wells/ condition) amount of [ 3 H]serotonin taken up by the cells after subtraction of the signal measured in the presence of reserpine were expressed as percentage of the value measured in cells transfected with control siRNAs and averaged (±SEM) over three independent experiments.
Cell culture, transfection, and immunoblotting Cell culture media, sera, and reagents were purchased from PAA Laboratories (Linz, Austria). Other chemicals were from Sigma-Aldrich. Blots were scanned and quantified using ImageJ software (National Institutes of Health, Bethesda, MD). Levels of β-tubulin were used to normalize the results from different samples. BON cells were kindly provided by C. M. Townsend (University of Texas Medical Branch, Galveston, TX). Experiments were done with a subclone named N13  (Tran et al. , 2007). Cells were maintained in DMEM F12 with l-glutamine, supplemented with 10% fetal calf serum and penicillin (100 U/ml)/streptomycin (100 μg/ml) at 37°C under 5% CO 2. Confluent cells were harvested on the day of transfection. Cells were electroporated as described previously  (Desnos et al.
To eliminate bias due to electrode gum-up, the electrode was briefly polished after every three cells, and its response was verified in fresh 50 μM dopamine. Amperometric traces were analyzed with custom-written routines in Elphy (G. Sadoc, Centre National de la Recherche Scientifique UPR3293, Gif sur Yvette, France) and Minianalysis (Synaptosoft, Decatur, GA) with a detection threshold set at 0. 4 pA. To facilitate the detection and analysis of PSFs, traces were smoothed in Elphy with a sliding average window of 500 data points. Nonresponding cells were discarded from the analysis.
For all of the tests, the significance threshold was fixed at 0. 05. All analyses were performed with R statistical software. For other statistical analyses, one-way ANOVA and a Bonferroni posttest or nonparametric tests (Mann-Whitney or Kruskal-Wallis followed by Dunn's posttest), as indicated, were run under Prism 5 (GraphPad Software, La Jolla, CA). *p < 0. 05; **p < 0. 01; ***p < 0. 001. Errors are shown as SEM. averaged. The displacement of the bead (and therefore the force necessary to pull the tether) from the resting position was measured by averaging the plateau at a tether length between 2 and 3 μm (i. e. , 1-3 s after the spike). The bead was tracked offline using a custom-made program developed in MATLAB (MathWorks, Natick, MA) by G. Toombes (Institut Curie, UMR168, Paris, France) and P.
ACKNOWLEDGMENTS We thank  E. Karatekin  and  P. Nassoy  for critical reading of the manuscript;  I. Brito  for contribution to the statistical analyses;  V. Calco  for technical assistance in generating Cdc42 rescue constructs;  G. Toombes ,  C. Campillo , and  G. Cappello  for technical advice; and  Marcel Lauterbach  for help with the STED microscope. This work was funded by grants from the  Young Investigator Program of the City of Paris , the  European Research Council  to  A. -M. L. -D. ( Strapacemi 243103 ), and the  Agence Nationale pour la Recherche  to F. D. ( ANR-06-BLAN-0211-02 ), P. B. ( ANR-2010-JCJC-1504-01 ), and  A. -M. L. -D. ( ANR-12-BSV3-0014-02 ). F. D. is supported by the  Institut National de la Santé et de la Recherche Médicale , and M. B. was supported by the  Centre National de la Recherche Scientifique  and the  Fondation pour la Recherche Médicale.
Acknowledgments We are very grateful to  J. Bertherat  and  J-D. Chiche  for providing us with human insulin and glargine, to  S. Bourdoulous  for providing us with cetuximab and trastuzumab, and to  M. Scott  for English correction of the manuscript. We thank  P. Le  ´cine for the gift of phRluc-Nter Gateway destination vector.
Hydroxymethylated DNA immunoprecicpitation (hMeDIP) hMeDIP assays were performed as described in  (34). Immunoprecipitated DNA was normalized to background DNA recovery using average recovery from six different negative control regions. All real-time PCR primers used are listed in Supplementary Table  S2. Library preparation and sequencing was performed using Illumina HiSeq 2000 at the CNRS U8199 genomics platform using standard protocols from the manufacturer (Illumina). The hMeDIP-seq data obtained using mouse primay adipocytes of the epididymal white adipose tissue were deposited to the Gene Expression Omnibus database under accession number GSE57582.
Public functional genomics data recovery and processing Public functional genomics data  (6, (11) (12) (13) 15, (35) (36) (37) (38) (39) (40) (41) (42)  used in this study were downloaded from the Gene Expression Omnibus (GEO), ArrayExpress or DNA Databank of Japan (DDBJ) databases or from the UCSC Genome Browser  (Raney et al. 2011)  and are listed in Supplementary Table  S1. 3T3-L1 pre-adipocytes were grown and differentiated using the MDI cocktail under standard and therefore comparable conditions in all these studies  (34). All raw data from 3T3-L1 cells were mapped to the mm9 version of the mouse genome using Bowtie  (43). Wig files used to define signal intensities were generated at 25 bp resolution from raw data and were normalized to the total number of uniquely mapped sequenced reads (extended to 200 bp for chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq) and hMeDIP-seq data).
Data were visualized using these wig files and the Integrated Genome Browser  (44). RefSeq gene coordinates and transcription start sites (TSS) as well as vertebrate PhasCons conservation scores were downloaded from the UCSC Genome Browser  (45). CTS from mouse tissues (bone marrow, cerebellum, cortex, heart, kidney, liver, lung, spleen) and cells [C2C12 myoblastic cells, CH12 B-cell lymphoma, embryonic stem (ES) cells, G1E erythroid progenitor cells, embryonic fibroblasts (MEF), erythroleukemia cells (MEL)] were obtained from the CTCFBSDB 2. 0 database  (46)  and from ENCODE  (45).
Transcription factor binding site identification and comparisons CTCF and PPARG chromatin binding sites were identified using model-based analysis of ChIP-seq (MACS)  (47). Input DNA was used as control and parameters recommended for analysis of TF ChIP-seq data were applied  (48) , except that a more stringent cut-off P-value (10 -9 ) was used. Peaks overlapping with regions that systematically give rise to the highest tag counts in 3T3-L1 ChIP-seq datasets (issued from 98 different datasets) were considered as potential false positives (49) and were therefore discarded. Genomic annotation of CTS was performed using CEAS from the cistrome analysis platform  (50). Peaks with at least one overlapping base pair were considered as overlapping and were identified using the cistrome analysis platform  (50).
Cluster-based identification of different classes of dynCTS As a pre-requisite, data were analyzed using NGS QC Generator (51) to ensure they were of comparable quality. For cluster-based analyses, the size of CTS was standardized by using a central 300 bp window, which was then used to monitor CTCF ChIP-seq signal intensities in differentiating 3T3-L1 cells at days -2, 0, 2 and 7. Quantitative differences were obtained by normalizing to ChIP-seq signal at day -2 using Manorm and conCTS as common binding sites  (52). Finally, k-means clustering was performed using MAnormderived quantitative differences in ChIP-seq signal intensities and the function 'Kmeans' (53) of 'amap' package in R. The number of clusters was varied and the final k was selected as the minimum number of clusters revealing the full diversity of CTCF dynamic binding.
Transcriptomic data analyses and gene association with transcription factor binding sites Raw transcriptomic data from 3T3-L1 and human adipose stromal cells  (12)  were downloaded from GEO and analyzed using the GeneSpring GX software using Robust Multichip Average (RMA) normalization (Agilent). Genes significantly induced at day 7 compared to day -2 were identified (P < 0. 05, fold change > 2) and were then discriminated based on the presence of CTS and/or PPARG binding sites within 25 kb of their TSS.
Gene ontology (GO) analyses Genes whose TSS was localized within 25 kb of a CTS were identified using the 'Peak2gene' tool of the cistrome analysis platform  (50). The Database for Annotation, Visualization and Integrated Discovery (DAVID) was then used to identify biological processes over-represented [biological process-level 5 (BP5) with P-value < 0. 01] in the created gene lists  (57). GO terms comprising gene lists that were more than 90% identical were merged into a single class. GO terms related to similar biological processes were identified and the classes of CTS were clustered according to their percentage of shared GO terms. This was performed through agglomerative hierarchical clustering using the function 'hclust' (58) of the 'stats' package in R.
(F) Percent of 3T3-L1 conCTS and dynCTS that were identified at least once as a CTS within the CTCFBSDB 2. 0 database  (46). (G) 3T3-L1 conCTS and dynCTS were compared to the CTCFBSDB 2. 0 database  (46)  to monitor the number of different tissues/cells in which each single binding site was also detected. The bar graph shows the percent of 3T3-L1 conCTS and dynCTS that were specific to adipocytes (0 sites shared with other tissues/cells) or found in an increasing number of mouse tissues/cells (from 1 to 14). ure 1D) and weaker evolutionary conservation (Figure  1E ) at dynCTS compared to conCTS. Since these properties have been associated with cell-specific chromatin binding of TFs  (60, 61) , we compared 3T3-L1 conCTS and dynCTS to CTCF cistromes from multiple mouse tissues or celltypes (see 'Materials and Methods') obtained from the CTCFBSDB 2.
0 database  (46). While ∼80% of dynCTS and almost all conCTS had already been identified at least once as recruiting CTCF in these datasets (Figure  1F ), we found a pronounced difference in the number of different tissues/cells in which conCTS or dynCTS had also been identified (Figure  1G ). Indeed, the median number of different tissues/cells where 3T3-L1 conCTS had also been found was 10 compared to 2 for dynCTS, which included ∼20% of sites not identified elsewhere (Figure  1G ). Hence, the CTCF cistrome exhibits pronounced plasticity during adipogenesis at newly identified adipocytespecific binding sites, which are distinct from ubiquitous CTS that remain constitutively bound during cell differentiation.
All CTS were centered (arrowhead) and a region spanning 1 kilobase (kb) on each side was analyzed. (E) Average vertebrate PhasCons conservation score for conCTS and dynCTS. All CTS were centered (arrowhead) and a region spanning 1 kb on each side was analyzed. (F) Percent of 3T3-L1 conCTS and dynCTS that were identified at least once as a CTS within the CTCFBSDB 2. 0 database (46). (G) 3T3-L1 conCTS and dynCTS were compared to the CTCFBSDB 2. 0 database (46)  to monitor the number of different tissues/cells in which each single binding site was also detected. The bar graph shows the percent of 3T3-L1 conCTS and dynCTS that were specific to adipocytes (0 sites shared with other tissues/cells) or found in an increasing number of mouse tissues/cells (from 1 to 14).
ACKNOWLEDGMENTS The authors are indebted to  Jér ôme Vandomme  ( INSERM U837, Lille, France ) for help with imaging of ORO staining experiments,  Stéphane Avner  ( CNRS U6290, Rennes, France ) for help with bioinformatical analyses and to  Jeremy Alexandre ,  Claire Mazuy  and  Eloise Woitrain  ( IN-SERM U1011, Lille, France ) for technical assistance. The authors thank  Pr Rainer Renkawitz  ( Justus-Liebig University, Giessen, Germany ) and  Dr Anjana Rao  ( La Jolla Institute, USA ) for providing plasmids. We also acknowledge the  CNRS U8199  genomics platform for the processing of hMeDIP-seq samples. B. S. is a member of the  Institut Universitaire de France.
Genome sequencing, annotation and bio-informatics The genome of P. freudenreichii ITG P20 was previously sequenced and annotated  [4]  and the draft assembly deposited in the European Nucleotide Archive (EMBL-EBI accession number: CONTIGS: CCBE010000001-CCBE010000111; SCAFFOLDS:HG975453-HG975511). Prediction of subcellular localization of encoded proteins were done in this work using SurfGþ  [2].
08% (vol/vol) formic acid, and 0. 01% (vol/vol) TFA in deionized water). A linear gradient from 10% to 50% of solvent B in 40 min was applied for the elution at a flow rate of 0. 3 μL/min. Eluted peptides were directly electrosprayed into the mass spectrometer operated in positive mode. A full continuous MS scan was carried out followed by three data-dependent MS/MS scans. Spectra were collected in the selected mass range 400-2000m/z for MS and 60-2000 m/z for MS/MS spectra. The three most intense ions from the MS scan were selected individually for collisioninduced dissociation (1 þ to 4 þ charged ions were considered for the MS/MS analysis). The mass spectrometer was operated in data-dependent mode automatically switching between MS and MS/ MS acquisition using Analyst QS 1. 1 software. The instrument was calibrated by multipoint calibration using fragment ions that resulted from the collision-induced decomposition of a peptide from β-casein, β-CN  (193) (194) (195) (196) (197) (198) (199) (200) (201) (202) (203) (204) (205) (206) (207) (208) (209).