dataesr/scientific-paragraphs-categorization huggingface dataset:
2012). We thus expect the constraint to improve significantly with the forthcoming Planck polarization data release. We verified that adding BAO, HST or highL data to Planck+WP improves the constraints only marginally, as these datasets are not able to break the degeneracy between p ann and n s. On the other hand, we observe a substantial improvement in the constraints when we combine the Planck+WP data with the Planck lensing likelihood data. For this data combination we find an upper limit of p ann < 3. 1×10 -6 m 3 s -1 kg -1 (95%; Planck+lensing+WP). ( 100 ) The improvement over Eq. (  99 ) comes from the constraining power of the lensing likelihood on A s and n s , that partially breaks the degeneracy with p ann. Our results are consistent with previous work and show no evidence for DM annihilation.
Acknowledgements. The development of Planck has been supported by:  ESA ;  CNES  and  CNRS/INSU-IN2P3-INP (France) ;  ASI ,  CNR , and  INAF (Italy) ;  NASA and DoE (USA) ;  STFC  and  UKSA (UK) ;  CSIC ,  MICINN  and  JA (Spain) ;  Tekes, AoF  and  CSC (Finland) ;  DLR  and  MPG (Germany) ;  CSA (Canada) ;  DTU Space (Denmark) ;  SER/SSO (Switzerland) ;  RCN (Norway) ;  SFI (Ireland) ;  FCT/MCTES (Portugal) ; and  PRACE (EU). A description of the Planck Collaboration and a list of its members, including the technical or scientific activities in which they have been involved, can be found at http://www. sciops. esa. int/index. php?project=planck&page=Planck_Collaboration. We thank the referee for a comprehensive and helpful report. We also thank  Jean-Philippe Uzan  for his contributions to Sect.
Affymetrix analysis Large-scale mRNA expression profiling was done on MDA-MB-231, MCF-7 and PC3 cells untreated and treated with LPA (1 mM) for 45 min. Total RNAs were purified as described above. Labeled cRNA probes from two independent replicates were hybridized to GeneChip Human Genome U1033 plus 2. 0 (Affymetrix). Data were analyzed using Affymetyrix expression console (v. 1. 1) software by ProfilExpert (Lyon, France). Mean fluorescent signals of duplicated probe sets were calculated. All probe sets with more than 1. 3-fold increase in presence of LPA defined LPA-dependent upregulated genes. The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus  [29]  and are accessible through GEO Series accession number GSE56265 (http://www. ncbi. nlm. nih. gov/geo/query/ acc.
Microarray correlation analysis Publicly available gene expression data for Prostate Tumor (GSE2109); Lung Tumor (GSE43580) and Colon Tumor (GSE21510) were obtained. Log2 tranformed values for HB-EGF and LPA1 expression were extracted from these database using R2 genomics analysis and visualization platform. Scatter plots were constructed. Analysis of correlation and computation of linear regression of the data were performed using Prism v5. 0b (GraphPad Software, Inc. ). P values ,0. 05 were considered significant.
We also observed that there was a statistically significant positive correlation between LPA 1 and HB-EGF in these samples (Figure  3B ). To further confirm our findings, we then looked into publically available databases for Prostate Tumor, Lung Tumor, and Colon Tumor. We observed that in the prostate tumor database there was a moderate but highly statistically significant positive correlation between LPA 1 and HB-EGF (Figure  3C ). In addition, in lung and colon tumor databases we observed a low but still highly statistically significant positive correlation between these two genes (Figure  3D  and 3E ). Therefore, this result supports the hypothesis for a positive correlation between LPA 1 expression and HB-EGF expression in vivo. PC3 cells in the right flank of male BALB/C nude mice. After 35 days, post-tumor cell injection animals were treated subcutaneously with Ki16425 (25 mg/kg) for 5 d.
LPA was previously shown inducing the shedding of proHB-EGF in VeroH cells through a Ras-Raf-MEK-dependent pathway  [39]. LPA also induces the shedding of proHB-EGF from the membrane of in human bronchial epithelial cells involving activation of matrix metalloproteinases leading to down-stream stimulation of EGFR and the secretion of IL-8  [40]. However, these works did not characterize which LPA receptor transmitted LPA signals. Our results demonstrated at mRNA and protein levels that LPA induces HB-EGF expression through an LPA 1 -dependent mechanism. Our study was based on manipulating breast and prostate cancer cells and on analyzing publically available tumor databases of breast, prostate, lung and colon cancers. Therefore, the significance of HB-EGF as a biomarker of LPA 1 activity in other pathologies, such as tissue fibrosis  [14, 25] , obesity  [41] , rheumatoid arthritis  [15] , osteoporosis  [5] , and neuropathic pain  [42] , remains to be determined.
Scatter plots of LPA 1 and HB-EGF expression were constructed with the Log2 tranformed values extracted from publically available databases using R2 genomics analysis and visualization platform for (C) Prostate Tumor (GSE2109; n = 72; R Spearman = 0. 45; p,0. 0001); (D) Lung Tumor (GSE43580; n = 150; R Spearman = 0. 29; p,0. 0001) and (E) Colon Tumor (GSE21510; n = 148; R Spearman = 0. 27; p,0. 0001). doi:10. 1371/journal. pone. 0097771. g003.
This study was supported by grants from the  INSERM (OP and PC) , the  ComiteDepartemental de la Loire de la Ligue Nationale Contre le Cancer ,  Lyon Science Transfer , and the  French Association pour la Recherche sur le Cancer ARC (OP). MD is a recipient of a fellowship from  ARC. DS is a recipient of a fellowship from the  Seventh Framework Programme  ( FP7/2007-2013 ) under agreement n u 264817-BONE- NET. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
0001) in the same RT-QPCR data. Scatter plots of LPA 1 and HB-EGF expression were constructed with the Log2 tranformed values extracted from publically available databases using R2 genomics analysis and visualization platform for (C) Prostate Tumor (GSE2109; n = 72; R Spearman = 0. 45; p,0. 0001); (D) Lung Tumor (GSE43580; n = 150; R Spearman = 0. 29; p,0. 0001) and (E) Colon Tumor (GSE21510; n = 148; R Spearman = 0. 27; p,0. 0001). doi:10. 1371/journal. pone. 0097771. g003.
However, the precise thermal structure of the dayside atmosphere remains unknown without higher resolution observations, and the planet's global energy budget and atmospheric heat-redistribution efficiency is poorly constrained without observations of the nightside. the Hubble Space Telescope (HST) to observe three nearly-consecutive orbits of WASP-43b. The planet orbits so close to its host star that it is tidally locked. Therefore, orbital phase is equivalent to rotational phase for the planet, and observations over a complete orbit allow us to map the entire surface of the planet. HST also acquired data for three primary transits and two secondary eclipses, where the planet passes in front of and behind its host star, respectively, between 9 November 2013 and 5 December 2013. All of the observations used the G141 grism (1.
Unlike Spitzer data, our spectrum samples the planet's flux near the peak of its Planck curve, allowing a more robust determination of the total dayside luminosity. This data set suggests that derived day-night differences may be strongly wavelength dependent and that mid-infrared photometry may not give a complete picture of planetary circulation. Brightness temperature maps, being functions of both longitude and atmospheric depth, reveal the dynamics of a planet's atmosphere. Phase-curve peaks prior to the time of secondary eclipse (as seen in Fig. 1 ) have previously been reported in hot Jupiters  (1, 6)  and match predictions from 3D circulation models  (30) (31) (32). Such models show that the eastward offset results from a strong jet stream at the equator; our observations thus suggest that WASP-43b exhibits such an eastward-flowing jet.
Materials and Methods Each phase curve visit consists of 13 or 14 HST orbits and each primary transit or secondary eclipse visit consists of four orbits. To improve observational efficiency, the telescope operated in spatial scan mode, scanning at a rate of 0. 08 s -1 and alternating between the forward and reverse directions. In each scan direction, the instrument made 15 non-destructive reads (SPARS10 sampling) over 103 seconds, the maximum duration possible with these settings. The observations achieved a duty cycle of ∼73%. Typically, we acquired 19 exposures per HST orbit and 1151 exposures total over all visits. In the extracted 1D spectra, we achieved a signal-to-noise ratio (S/N) of ∼1,300 per pixel. This corresponds to a S/N of ∼3,300 per spectrophotometric bin of width 7 pixels. The WFC3 spatial scan data contain a previously-documented orbit-long systematic that we fit with an exponential ramp model component.
6σ with respect to the null hypothesis (no correlation). These data have a Pearson product-moment correlation coefficient of -0. 85, where 0 is no correlation and -1 is total inverse correlation. We use Chauvenet's criterion on the measured peak offsets to identify the three white squares as outliers. This can be seen in Fig. S7  where the 1. 2825, 1. 3525, and 1. 3875 µm channels do not have peak offsets that vary smoothly with wavelength as influenced by the broad water feature. At higher atmospheric pressures, we detect a stronger deviation in the phase-curve peak offset relative to the time of secondary eclipse. This trend qualitatively matches the predictions of three-dimensional circulation models. Movie S 1: Time-lapse video of WASP-43b over one planet rotation. The left and right panels display the phase-resolved emission spectrum and thermal profile, respectively, with 1σ uncertainty regions.
Acknowledgments This work is based on observations made with the  NASA/ESA  Hubble Space Telescope that were obtained at the  Space Telescope Science Institute , which is operated by the  Association of Universities for Research in Astronomy, Inc. , under  NASA  contract  NAS 5-26555. Data are available through the  Mikulski Archive for Space Telescopes (MAST). We thank  Alison Vick  and  Merle Reinhart of STScI  for scheduling these observations, which are associated with program  GO-13467. Support for this work was provided by  NASA  through a grant from the  Space Telescope Science Institute , the  Sagan Fellowship Program  (to K. B. S. ) as supported by  NASA.
The Affymetrix 6. 0 microarray contains approximately 946,000 CNV probes. We looked for large areas of CNV, with a minimal size of 100 kb, and found three deletions and four duplications in the fibroblast samples (versus the Hg19 reference sequence). All these CNVs are polymorphic (reported in the Database of Genomic Variants), and their presence was confirmed in all the iPSC lines. We then focused on additional CNVs detected in at least one iPSC line (Fig. 4A ). The number of deletions for each iPSC line, with respect to the parental fibroblasts, was between 0 and 7, and the number of duplications was between 0 and 4. Results were highly heterogeneous, depending on the iPSC line considered: some iPSC lines seemed less affected (P1, A22) than others (P2, A17). However, by contrast to our observations for SNV analyses, no clear relationship was found between the number of CNVs and the reprogramming method, suggesting that the reprogramming method used had no direct impact on the CNV number.
ACKNOWLEDGMENTS We thank  Vincent Saravaki ,  Dominique Pineau , and  M élanie Point  for excellent technical assistance. C. S. and N. D. were supported by fellowships from  Association Française Contre les Myopathies and R égion Ile de France  ( DIM Stem Pôle ), respectively. E. L. was supported by Grant  2011-Rare-006  " HEMO-iPS ," and S. A. -T. by  FP7-HEALTH. 2011. 1. 4-2-278152 " InnovaLiv. "This work was supported by  ANR-2010-RFCS-004  " Liv-iPS " and  FP7-HEALTH. 2011. 1. 4-2-278152 " InnovaLiv. ".
Acknowledgements The simulation was done on the Earth Simulator. This work is partially supported by  MEXT/JST KAKENHI  (H. S. and Y. S. : 25400473; H. S. :  22106006 ). P. K. acknowledges the support of  IFREMER  (through the  MOU IFREMER-JAMSTEC) ,  CNRS (France)  and the  Agence Nationale pour la Recherche  (Contracts  ANR-09-BLAN-0365-02  ( REDHOT ) and  ANR-10-LABX-19-01 (LabexMER) ). B. Q. acknowledges support from  NASA 's SWOT mission through Grant  NNX13AD91G. We thank  Pascal Riviere  and  Aurelien Ponte  for their useful remarks on the manuscript, Matsuoka for making the images. At last, we dedicate this study to our colleague and friend  Bach-Lien Hua , whose intellectual curiosity and scientific ideas much inspired our thoughts during this work.
Microarrays and data analysis 3T3-L1-differentiated adipocytes were stimulated with live C. burnetii or heat killed bacteria (50 bacteria per cell) for 8 hours. Total RNA was extracted using an RNeasy Mini Kit (Qiagen) and DNase treatment. The integrity and the amount of RNA were assessed and microarray studies were performed according Agilent Technologies, as recently described  [21]. Briefly, four samples per experimental condition (stimulated and not stimulated) were used. Labeled cRNAs were obtained from 300 ng of RNA using T7 RNA polymerase and cyanine 3-labeled CTP (Cy-3) fluorescent dyes with One-Color Microarray-Based Gene Expression Analysis (Agilent Technologies). Labeled cRNAs were hybridized onto Whole Mouse Genome Oligo Microarrays 4644k kit (G4852A), representing 44,000 60-mer oligonucleotides, for 17 hours at 65uC.
Slides were scanned at a 5-mm resolution with a G2505B DNA microarray scanner (Agilent Technologies). Image analysis and intra-array signal correction were performed using Agilent Feature Extractor Software A. 9. 1. 3. Supervised analyses were carried out with R (R for statistical computation and graphic version 2. 15) and the BioConductor library  [25]. False Discovery Rate (FDR) was set to 0. 05 to filter modulated genes. The selected probes were further filtered for differentially expressed genes using an absolute fold change (FC) $1. 5. Functional annotation was performed using the DAVID Bioinformatics Resource 2008  [26, 27]. The gene networks were generated using the PathwayS-tudioTM software (Ariadne Genomics). The data have been submitted to the NCBI Gene Expression Omnibus (GEO) and are accessible through GEO Series accession number GSE46335.
Microscopy and quantification. Fluorescent and bright field image capture was performed using an epifluorescent (Leica) or confocal (Meta 510 LSM or LSM 710; Zeiss) microscope. In myoblast cultures, all DAPIpositive cells and antigen-positive cells were counted and the percentage of Antigen +ve cells was calculated. Data from three or more cultures were pooled to give a population mean ± SEM. For the quantification of the intensity staining, all samples were stained simultaneously and the pictures were acquired with an LSM 710 confocal microscope at the same ratio of emissions. For the analysis with ImageJ software (National Institutes of Health), the shape of each Pax7 +ve cell was drawn around the nucleus and the intensity of Bmi1 staining calculated for each cell as mean of integrated density (mean intensity × area).
Satellite cells prepared from mdx;STOPFloxBmi1 EDL muscles were transfected with A-Cre to overexpress Bmi1 and a proportion then treated with LV-shMt1. Cells infected with A-GFP were used as controls. Proteins were extracted from the cells and concentration was measured by BCA protein assay kit (Thermo Fisher Scientific). The amount of 3-NT protein in the lysates was determined by the Nitrotyrosine ELISA kit (Abcam) according to the manufacturer's protocol. The OD was recorded at 450 nm and the data were analyzed with the program XLfit 5. 3. 1. 3 (IBDS). density between all measured cells) was calculated out of the total number of measured cells per each muscle section analyzed. For the analysis of satellite cells in vitro, satellite cells were stained for Bmi1 and counterstained with DAPI.
Aliquots of RNA (250 ng) samples were amplified according to the specifications of the Illumina TotalPrep RNA Amplification kit (Ambion). The cRNA samples obtained were applied to the MouseWG-6 v2. 0 Expression BeadChip arrays (Illumina) and hybridized according to the manufacturer's specification. Each array on the BeadChip targets >45,200 transcripts using 3-µm beads bearing covalently attached 50-base oligonucleotide probes. The BeadChips were scanned with the BeadSrray system scanner (Illumina). The hybridization images signal intensity was extracted and background subtracted using Bead-Studio software  (version 3. 3. 7 Illumina). The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession no. GSE41878. Modified biotin switch assay to detect SNO-MEF2c.
Tiredness was defined as the inability of the mouse to go back to the treadmill belt despite five mechanical stimulations (De Luca, Statistical analysis. For the histological analysis on muscle sections, the number of fibers in each range of areas (µm 2 ) was counted and the percentage of fibers in each range was calculated. Percentages from different animals were pooled and the mean calculated. For the ratio of regeneration, the mean CSA of CNF was divided by the mean CSA of mature fibers. Unless specified in the text, all the graphs represent population mean ± SEM. Statistical analysis was performed using Prism statistical analysis software (Graph-Pad), and tests applied included Student's t test for single comparisons and ANOVA, Kruskal-Wallis, or Student's t test with Bonferroni correction for multiple comparison.
We thank  S. Brandner  for critically reading this article and for many useful suggestions on the Definiens software;  P. Pallier ,  J. Bestwick , and  Paul Creeke  for advice on the behavioral experiments and on statistics, respectively; all members of the  Marino Lab  for helpful discussions; and  S. Fukada  and  S. Takeda  for the gift of the SM/C-2. 6 antibody. We are grateful to the  BSU  staff for help in the daily care of our mouse colony. This work is supported by grants of the  Medical Research Council UK  ( G0802546/1 ) and  Muscular Dystrophy Campaign  ( RA4/788/4 ) to  S. Marino  and  L. G. Robson. F. Muntoni  is supported by the  Great Ormond Street Children's Charity. R. W. Taylor  is funded by the  Wellcome Trust  ( 096919/Z/11/Z ) and the  Medical Research Council UK Centre for Neuromuscular Diseases  ( G0601943 ).
[ 27 ] The time constant, τ , is used as a fi gure of merit for the electrical characterization of the ion fl ow through epithelia as measured by the OECT. Extended information on determination of τ has been reported previously. [ 18 ] For electrical characterization of MDCK-I cells seeded onto the OECT, the channel current was measured upon application of a positive square-pulse gate voltage. Similar to the charge and discharge of a capacitor in an RC electronic circuit, the channel current can be fi t by an exponential equation (see materials and methods) and the τ value extracted as a fi t parameter. The data is then normalized between 0 and 1, where 1 is the highest τ value obtained (corresponding to the lowest amount of ion fl ux across a functional cell monolayer), and 0 is the lowest value τ obtained (corresponding to a device with no cells).
The measurement parameters were chosen to avoid exposing the cell monolayers to a voltage drop above 0. 5 V, as high voltages have been shown to damage bilayer membranes. [ 42 ] The recording of the OECTs was performed using a Keithley 2612 Source Meter and customized Labview software. OECT data were collected using the following parameters: V DS = -0. 2 V, V GS = 0. 3 V, V GS on time = 2 s, off time = 28 s. Data Analysis : Data analysis was performed using a customized Matlab program to isolate and fi t the time constant for each pulse as described previously. [ 18 ] In Figure  2  and 4  , the data are then normalized using the following equation: NR = ( τ no cells -τ )/( τ no cells -τ cells ), where τ cells refers to the tau value in response to the application of the gate voltage of a barrier forming monolayer, and τ no cells refers to the tau value in response to the application of the gate voltage of no barrier, with the dataset subsequently normalized to [0,1] scale, where 1 corresponds to intact cell monolayer and 0 to a disrupted one or absence of barrier monolayer.
Only 5 fungal species were isolated through culture-dependent methods, including Alternaria alternata, Cladosporium sp. , Malassezia restricta, Malassezia globosa, and Malassezia pachydermatis. All of the 171 sequenced clones from the fungal ITS clone library that were generated using the ITS1-F/ITS-4R primer set were related to fungal sequences that were found in the GenBank databases with the exception of one clone belonging to the Viridiplantae (green plants) (Tables  1  and 4 , Fig. 1 ). This amplification alone allowed for the identification of 25 different fungal species (roughly half of the fungal species detected and 28. 7% of all eukaryotic species recovered in this study) (Fig. 1 ). The majority of the fungal sequences in this clone library were of ascomycete origin (91. 2% of the total number of clones and 80.
Finally, intestinal eukaryotes were identified by comparing the resulting sequences with those that were deposited in GenBank using the basic local alignment search tool (BLAST), which is available at the National Center for Biotechnology Information (http://blast. ncbi. nlm. nih. gov/). Phylogenetic analyses were performed using MEGA5. 04 and a distance matrix neighbor-joining (NJ) approach  57. Real-Time PCR Assay for Detection of human pathogen. Primers and probes specific to some human eukaryotic pathogens were used as described previously (Supplementary Table  3 ). For the primers and probes used for first time in this study, sequences corresponding to each species were collected in GenBank and aligned using multiple sequence alignment ClustalW2, and the PRIMER 3 software 58 was used to design primer sets in the conserved regions of aligned sequences.
The gender of gorillas was determined by amplification of a region of the amelogenin gene that contains a deletion in the X, but not the Y chromosome  56. To exclude the allelic dropout, all loci were amplified four times. Aliquot 1 mL of PCR products was mixed with 10 mL of formamide and 0. 25 mL of the ladder marker (ROX GeneScan 400HD, Applied Biosystem), The resulting amplifications were analyzed by 3130xl Genetic Anlayser sequencer (Applied Biosystem, Foster City,CA). Amplification products were visualized and sized using Genemapper 3. 7 software (Applied Biosystems). Culturing and identification of fungal species. The fecal samples were serially diluted, and six-fold dilutions were spread onto potato dextrose agar (FlukaH Analytical, France), Czapek dox agar (FlukaH Analytical, France) and Dixon agar.
Acknowledgments Fadi BITTAR was supported by a  Chair of Excellence IRD  provided by the  Institut de Recherche pour le Developpement/IHU Mediterranee Infection. We thank  Amandine Esteban  for microsatellite analyses. This work was supported in part by grants from the  National Institute of Health  ( RO1 AI 50529 ) and the  Agence Nationale de Recherches sur le SIDA  ( ANRS 12255 ).