dataesr/scientific-paragraphs-categorization huggingface dataset:
RNA-seq data computational analysis The initial whole transcriptome paired-end reads obtained from sequencing were mapped against the latest version of the human genome (version GRchr37/hg19) by using the Life Technologies mapping algorithm (http://www. lifetechnologies. com/; version 1. 3). The aligned records were reported in BAM/SAM format  [19]. The Picard Tool (http://picard. sourceforge. net/; version 1. 83) was used to eliminate insufficient quality reads (Phred score <10). Subsequently, gene predictions were estimated by the Cufflinks method  [20]  and the expression levels were calculated by using HTSeq software  [21]. This method eliminates the multi-mapped reads, only the unique reads are considered for gene expression estimation. The differential expression analysis between conditions was assessed by the edgeR method (version 3.
2. 4) [22]. This method relies on different normalization process based on the depth of global samples, the CG composition and the gene length. Moreover, is based on a Poisson model that estimates the variance of the RNA-seq data for differential expression. Finally, we selected genes showing differential expression at a significance threshold of P < 0. 05. The data presented in this manuscript have been deposited in NCBI's Gene Expression Omnibus (GEO)  [23]  and are accessible through GEO Series accession number GSE55296 (http://www. ncbi. nlm. nih. gov/geo/query/ acc. cgi?acc=GSE55296).
Multivariate linear regression analysis was achieved using ejection fraction (EF) and stroke volume as dependent variables and age, gender, and LV diameters as independent variables. Best model discrimination was based on the principle of least mean square and greatest r 2. P < 0. 05 was considered statistically significant. All statistical analyses were performed using the SPSS software (version 20. 0) for Windows (IBM SPSS Inc. ; Chicago. IL, USA).
Introduction During its 2729 days in orbit, the faint stars channel of the CoRoT (COnvection ROtation & planetary Transits;  Baglin et al. 2006 ) mission observed about 163 600 targets over 26 runs, 18 of which were long runs with durations of more than 150 days, while 8 were short runs with typical duration of 30 days. This resulted in the detection of 33 planets to date. The extremely precise photometric time series provided by the faint stars channel can also serve a large number of additional scientific objectives. To ensure the selection of the targets and the exploitation of the light curve, a minimum knowledge of the targets is required, such as their colours or spectral type and luminosity class. This is one of the reasons why the Exodat  (Deleuil et al. 2009 ) database was built. Its prime objective is to provide positions, colours, and stellar classification for the stars in the observable zones of CoRoT, the so-called CoRoT eyes.
Those eyes are two circular regions of about 15 • radius each, centred on the Galactic plane (i. e. in the direction perpendicular to the polar orbit of CoRoT), in opposite directions at 6 h 50 m and 18 h 50 m in right ascension (RA) (see Fig. 1 ). While not close to the centre of the Galaxy, these two directions of pointing are referred to as the anticentre and centre directions. Exodat is an information system and a database that gathers an extended body of data of various origins. It includes a search engine for exploring and displaying data, which is available to the community through a user friendly web interface 1  (Agneray et al. 2014). It contains data for more than 51 million stars to provide information for both the potential targets of the exoplanet programme (with 11 ≤ r ≤ 16), and also the fainter background sources (down to about the 19 th V magnitude) to estimate the level of light contamination of the targets.
The stellar classification of the potential targets required the design of a classification method suited for the needs and time frame of the mission. Considering the extent of the database, the use of spectroscopy was deemed impossible. Consequently, a first order stellar classification (FOSC) was conducted with the aid of broadband multi-colour photometry in a wide spectral range. Of course, any detailed analysis of targets of particular interest would require complementary observations for a better characterisation. Indeed this has been applied on a target-totarget basis, especially for planet hosting stars, but also on more consequential samples (see Sec. 5). Overall, no more than 15 % of the targets observed over the lifetime of the mission were the object of complementary observations.
Broadband multi-colour photometry Very little was known about the faint stars in the CoRoT eyes prior to the launch. Thus a large observational campaign was performed to prepare the pointings and target selection of the satellite. Photometric observations started in June 2002, with observing campaigns in winters and in summers in order to cover the centre and anticentre directions. These observations were described in  Deleuil et al. (2009). They formed the first catalogue of the database that we name "Obscat" 3. This catalogue provides photometry in Harris B and V, Sloan-Gunn r and i filters. An RGO U filter was also used, but because long exposures are required, Obscat only provides U-band photometry over small areas. The magnitudes are calibrated in the Vega system. To ensure a better classification of late-type stars, the spectral coverage was extended, and the infrared magnitudes of the point source catalogue issued by the 2 Micron All Sky Survey were also used (2MASS;  Kleinmann et al.
1994). This formed the second catalogue of the database that was crossmatched with Obscat. To fulfil the objectives of other scientific programmes, some runs were chosen in regions that were not covered by Obscat. Photometry in these regions needed to be obtained from publicly available catalogues that could complement Obscat, and therefore more catalogues were added to the database. Eventually, the PPMXL catalogue was chosen as the reference catalogue for Exodat when it became available. The PPMXL catalogue  (Roeser et al. 2010 ) combines the USNOB1. 0 (Monet et al. 2003 ) and 2MASS catalogues and provides accurate position and mean motions in the ICRS. The PPMXL catalogue aims to be complete from the brightest stars down to about V ≈ 20, and covers both CoRoT eyes. Essentially, USNO-B1. 0 is a threecolour (photographic ''blue", ''red", and ''infrared"), two epoch catalogue.
It is one of the largest surveys in the visible that is publicly available, and the only survey that is deep enough to fulfil the two main purposes of the database: spectral typing and assessing of the level of contaminating light from background sources. To ensure the homogeneity of the whole database, Obscat was carefully crossmatched with PPMXL. Thus, the FOSC is carried out using visible magnitudes from Obscat when available and from PPMXL when not available from Obscat, and infrared magnitudes from 2MASS are used. Since PPMXL gives blue and red magnitudes for two epochs, we use in priority the more precise photometry of the second epoch, and only resort to using the first epoch magnitude when no other blue or red magnitude is available. Overall, the statistics of the magnitudes used as input for the FOSC are listed in table  1.
Comparison with spectroscopic data To further test the FOSC, we have chosen catalogues of spectral types, in the available literature, containing a large number of targets and obtained with homogenous methods. As a result, we compare the result of the FOSC with two different spectral catalogues. The first catalogue contains the fundamental stellar parameters for 1127 stars in the LRa01, LRc01, and SRc01 CoRoT fields, for which intermediate-resolution spectroscopy was acquired with the FLAMES/GIRAFFE multi-fibre facility as ESO-VLT  (Gazzano et al. 2010, hereafter Ga10). The second catalogue gives an estimate of the spectral type obtained for 11 466 stars in the IRa01, LRa01, LRa02, and LRa06 fields, using the AAOmega multi-object spectrograph mounted on the Anglo-Australian Telescope  (Sebastian et al.
Conclusions In this paper, we have described the latest version of the FOSC, which is the procedure used to estimate the spectral type of CoRoT targets. The spectral type and E B-V are products of the CoRoT mission and are delivered together with the CoRoT light curves in their FITS format. They are also available online through the Exodat database. Because of the faintness and the number of the targets, the FOSC is based on broadband photometry. The photometry obtained during a mission-dedicated observational campaign is used whenever possible, but it was necessary to resort to USNO-B1. 0 data for about a third of the targets. Using a synthetic set of stars, we were able to quantify how the performance of the classification are affected by the use of different photometric catalogues. We also provide a statistical estimate of the precision and accuracy of the classification.
The performances of the FOSC are significantly improved by limiting the range of possible values for the reddening. This was only performed in the latest version of the FOSC and previous versions are expected to produce significantly more uncertain results. An accurate estimation of the maximum reddening in the CoRoT fields was made possible by the use of reddening maps produced thanks to a new parametrisation of dust emission that covers the whole sky, which is one of the products associated with the 2013 release of data from the Planck mission. Eventually, the third data release of the GAIA mission that is scheduled in summer 2018 6 should give the spectral classification of all stars observed in the faint stars channel, as well as their binary nature and proper motions, to an unprecedented level of precision.
Acknowledgments The authors are grateful to the referee for valuable comments that improved the manuscript. CD acknowledges support by  CNES  grant  426808  and  ANR (Agence Nationale de la Recherche, France)  programme  IDEE  ( ANR-12-BS05-0008 ) " Interaction Des Étoiles et des Exoplanètes". Figure 1 uses images from the Digitized Sky Survey , which was produced at the  Space Telescope Science Institute  under  U. S. Government  grant  NAG W-2166. The images of these surveys are based on photographic data obtained using the  Oschin Schmidt Telescope on Palomar Mountain  and the  UK Schmidt Telescope. The plates were processed into the present compressed digital form with the permission of these institutions. The Obscat catalogue was 6 see http://www. cosmos. esa. int/web/gaia/releasederived from photometry acquired with the Isaac Newton Telescope (INT), operated on the island of  La Palma  by the  Isaac Newton group in the Spanish Observatorio del Roque de Los Muchachos  of the  Instituto de Astrofisica de Canarias.
This publication makes use of data products from the  Two Micron All Sky Survey , which is a joint project of the  University of Massachusetts  and the  Infrared Processing and Analysis centre/California Institute of Technology , funded by the  National Aeronautics and Space Administration  and the  National Science Foundation. This work is based in part on services provided by the GAVO data centre. This research has made use of the VizieR catalogue access tool,  CDS, Strasbourg, France. This research uses observations obtained with Planck, an  ESA  science mission with instruments and contributions directly funded by  ESA Member States ,  NASA , and  Canada. The authors thank  M. -A. Miville-Deschênes  for providing them with the Planck data. CD is grateful to  P. -Y. Chabaud  and  F. Agneray  for their work on the Exodat database and information system.
Genome Mining Strategies as a Tool to Discover Antibiotics in Pseudoalteromonas The last two decades were marked by the onset of genomic area with cheaper and faster technologies for genome sequencing. To date, 29,000 complete bacterial genomes have been deciphered and another 31,000 bacterial genome sequences are still in progress under way (GOLD database: http://www. genomesonline. org; date of access: May 2016). This has led to the development of genome-based strategies to discover new drugs and antibiotics  [94]. As a consequence, bioinformatic tools have been developed to improve the metabolite-pathway analysis, allowing access to putative metabolites and therefore to the investigation of the biotechnological potential of bacterial strains. Thanks to this genome mining approach, the metabolome can be predicted.
Furthermore, bioinformatic tools enable the identification of new and potentially novel compounds via the expression of silent genes. Indeed, it is estimated that less than 10% of secondary metabolite gene clusters are expressed in sufficient amount for detection in current lab conditions  [95]. As NRPS, PKS, and hybrid NRPS-PKS pathways exhibit repeated motifs in genomic nuclear sequences, they have led to the development of powerful bioinformatics programs such as antiSMASH  [96] , NapDos  [97] , SBSPKS  [98] , or Np. searcher  [99]. Moreover, the description of a specificity-conferring code in the NRPS A-domain  [100]  has resulted in the development of specialised chemical structure prediction tools, e. g. , NRPS predictor2  [101]  and NRPS substrate predictor  [102]. Another tool dedicated to ribosomally-produced peptides (bacteriocins), BAGEL3  [103]  can be useful in a genome mining approach focusing on the discovery of new antimicrobial compounds.
This is also in agreement with the divergence, as it is shown later, of the interfacial thickness as T ! T c. For the other CG and UA models, we have checked that results are equivalent. We have also estimated the location of the critical point resulting from our direct MD simulations. The critical coordinates (temperature, T c , density, ⇢ c , and pressure, P c ) are obtained following the procedure explained in Section II. In Table  V  we report the values of the critical temperatures, densities, and pressures as obtained from this procedure. In addition to that, we have also included the literature THF critical coordinates. The vapor-liquid phase envelopes of the di↵erent CG and UA models for THF are depicted in Fig. 2. We have also included the experimental data 37 corresponding to the coexistence curve of THF.
We have examined the density profiles, interfacial thickness, and surface tension in terms of temperature. In addition to that, we have calculated the coexistence phase envelope and vapor pressure, including the location of the critical point from an analysis of the density profiles and the surface tension. All properties have been determined for the six molecular models studied. Predictions obtained from MD simulation are compared with experimental data taken from the literature for all properties except for the case of interfacial thickness. The vapor-liquid phase envelope of THF is predicted remarkably well by the three CG models proposed. In particular, agreement between experimental literature data and predictions from the CG dimer model are comparable with the best united atoms models used in this work.
ACKNOWLEDGMENTS We thank  Dr. Andres Mejía  ( Universidad de Concepción, Chile ) for stimulating discussions. This work was supported by  Ministerio de Economía and Competitividad (MINECO, Spain)  through Grant Nos. FIS2013-46920-C2-1-P  and  FIS2015-68910-P , both cofinanced with  EU FEDER  funds. We also acknowledge  CESGA  (www. cesga. es) in  Santiago de Compostela ,  Spain , and  MCIA (Mésocentre de Calcul Intensif Aquitain) of the Universités de Bordeaux and Pau et Pay de l'Adour, France , for providing access to computing facilities. J. M. G. acknowledges the doctoral scholarship from  Conicyt (Chile)  and from  Red Doctoral REDOC. CTA ,  MINEDUC  Project No. UCO1202  at  U. de Concepción. J. M. M. acknowledges  Xunta de Galicia (Spain)  for the Postdoctoral Grant. J. A. F. acknowledges  Contrato Predoctoral de Investigación from XIX Plan Propio de Investigación de la Universidad de Huelva.
The time of acquisition was between 30 seconds and 1 minute per spot. The 20 SIT1 T spectra were imported into MALDI BioTyper 3. 0 software (Bruker) and analysed by standard pattern matching (with default parameter settings) against the main spectra of 7379 bacteria. The method of identification included the m/z from 3000 to 15 000 Da. For every spectrum, a maximum of 100 peaks were compared with spectra in the database. The resulting score enabled the identification of species whether tested or not: a score of 2 with a validly published species enabled identification at the species level, a score of 1. 7 but <2 enabled identification at the genus level and a score of <1. 7 did not enable any identification. Identification of bacteria continued with a 16S rRNA standard PCR coupled with sequencing.
That was performed using GeneAmp PCR System 2720 thermal cyclers (Applied Biosystems, Bedford, MA, USA) and ABI Prism 3130xl Genetic Analyser capillary sequencer (Applied Biosystems) respectively  [16]. The 16S rRNA nucleotides sequence was corrected using Chromas Pro 1. 34 software (Technelysium, Tewantin, Australia), and the BLASTn searches were performed in the online PubMed National Center for Biotechnology Information (NCBI) database (http://blast. ncbi. nlm. nih. gov. gate1. inist. fr/ Blast. cgi).
Automated cluster generation and a single 39-hour sequencing run were performed at a 2 × 251 bp read length. All 8. 2 Gb of information was obtained from a 947K/mm 2 cluster density, with a cluster passing quality control filters with 99% (18 111 784 clusters). Within this run, the index representation for Bacillus andreraoultii was determined to 9. 27%. The 1 513 908 paired reads were filtered according to the read qualities. The reads obtained from applications were trimmed, and an optimal assembly of 14 scaffolds and 58 contigs was obtained through the SOAPdenovo software, which generated a genome size of 4. 09 Mb.
Genome annotation and comparison Open reading frames (ORFs) were predicted using Prodigal  [18]  with default parameters, but the predicted ORFs were excluded if they spanned a sequencing gap region (contain N). The predicted bacterial protein sequences were searched against the Clusters of Orthologous Groups (COGs) database using BLASTP (e-value 1e-03, coverage of 0. 7, and an identity percentage of 30%). If no hit was found, it search against the NR database using BLASTP with an e-value of 1e-03, coverage of 0. 7 and an identity percentage of 30%. If sequence lengths were smaller than 80 amino acids, we used an e-value of 1e-05. The tRNAScanSE tool  [19]  was used to find tRNA genes, whereas ribosomal RNAs were found by using RNAmmer  [20]. Lipoprotein signal peptides and the number of transmembrane helices were predicted using Phobius  [21].
ORFans were identified if all the BLASTP performed did not retrieve positive results. Such parameter thresholds have already been used in previous works to define ORFans. Genomes were automatically retrieved from the 16s RNA tree using Phylopattern software  [22]. For each selected genome, complete genome sequences, proteome genome sequences and Orfeome genome sequences were retrieved from the FTP site of NCBI. All proteomes were analysed with Proteinortho  [23]. Then for each couple of genomes a similarity score was computed. This score is the mean value of nucleotide similarity between all couple of orthologues in the two genomes studied (average genomic identity of orthologous gene sequences, AGIOS)  [9]. The resistome was analysed with the ARG-ANNOT (Antibiotic Resistance Gene-ANNOTation) database and BLASTp in GenBank  [24].
The exhaustive bacteriocin database available in our laboratories (Bacteriocins from the URMITE database) (http://drissifatima. wix. com/bacteriocins) was performed by collecting all currently available sequences from the databases and from NCBI. Protein sequences from this database allowed putative bacteriocins from human gut microbiota to be identified using BLASTp methodology  [25]. PHAST (PHAge search tool) was used to identify phage sequences  [26]. An annotation of the entire proteome was performed to define the distribution of functional classes of predicted genes according to the clusters of orthologous groups of proteins using the same method as for the genome annotation.
Strain identification and phylogenetic analyses No significant MALDI-TOF score was obtained for strain SIT1 T against the Bruker database, suggesting that our isolate was not a member of a known species. We added the spectrum from strain SIT1 T to our database (Figure  1 ). Then a gel view was performed to show the spectral differences with other members of the genus Bacillus (Figure  2 ). Using 16S rRNA phylogeny analyses, we demonstrated that strain SIT1 T exhibited a 96% 16S rRNA sequence identity with Bacillus thermoamylovorans (GenBank accession no. HM030742), the phylogenetically closest bacterial species with standing in nomenclature (Figure  3 ). Its 16S rRNA sequence was deposited in GenBank under accession no. LK021120. This value was lower than the 98. 7% 16S rRNA gene sequence threshold recommended by Stackebrandt and Ebers  [5]  to delineate a new species without carrying out DNA-DNA hybridization.
1 to 0. 3 mm. The cells had a mean width and length of 0. 5 μm and 3 μm, respectively, and exhibited flagella. They were catalase positive and oxidase negative. Bacillus andreraoultii SIT1 T was resistant to trimethroprimsulphamethoxazole, macrolide (erythromycin), vancomycin    The genome is 4 092 130 bp long, and the G+C content is 35. 42%. The 16S rRNA gene sequence and whole-genome shotgun sequence of B. andreraoultii strain SIT1 T are deposited in GenBank under accession nos. LK021120 and CCFJ00000000, respectively. The type strain SIT1 T (= CSUR P1162 = DSM 29078) was isolated from the stool of a 2-yearold Nigerien boy with kwashiorkor, a severe form of acute malnutrition.
Microbes and New Infections, Volume 10 Number C, March 2016 NMNI New Microbes and New Infections © 2015 The Authors. Published by Elsevier Ltd on behalf of European Society of Clinical Microbiology and Infectious Diseases, NMNI, 10, 25-35 This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4. 0/) 16S rRNA sequence similarity to other members of the Bacillus genus. It was part of a culturomics study aimed at isolating all bacterial species from human digestive flora in patients with kwashiorkor, an acute form of malnutrition. It is the first sequenced genome from B. andreraoultii sp. nov. The European Molecular Biology Laboratory (EMBL) accession number of B.
30 New 30 Microbes and New Infections, Volume 10 Number C, March 2016 NMNI New Microbes and New Infections © 2015 The Authors. Published by Elsevier Ltd on behalf of European Society of Clinical Microbiology and Infectious Diseases, NMNI, 10, 25-35 This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4. 0/) 16S rRNA sequence similarity to other members of the Bacillus genus. It was part of a culturomics study aimed at isolating all bacterial species from human digestive flora in patients with kwashiorkor, an acute form of malnutrition. It is the first sequenced genome from B. andreraoultii sp. nov. The European Molecular Biology Laboratory (EMBL) accession number of B.
858526 Amino acid transport and metabolism F 71 1. 9096289 Nucleotide transport and metabolism H 95 2. 5551372 Coenzyme transport and metabolism I 116 3. 119957 Lipid transport and metabolism P 181 4. 8682084 Inorganic ion transport and metabolism Q 47 1. 2641205 Secondary metabolites biosynthesis, transport and catabolism R 344 9. 252286 General function prediction only S 245 6. 589564 Function unknown - 1298 34. 911243 Not in COGs COGs, Clusters of Orthologous Groups database.