dataesr/scientific-paragraphs-categorization huggingface dataset:
Simple and multivariate regression analyses were performed to study the relationship between the GSI and the accumulated degrees day (ºD) and the accumulated CPE-doses, using the software provided by Statgrafics Plus 5. All the values are expressed as mean ± standard error of mean (SEM). Differences were considered significant when p<0. 05. All the statistical procedures were run using Statgraphics Plus 5. 1 (Statistical Graphics Corp. , Rockville, MO, USA).
Acknowledgements Funded by the  European Community 's  7th Framework Programme under the Theme 2 "Food, Agriculture and Fisheries, and Biotechnology ", grant agreement n°245257 (PRO-EEL). Ilaria Mazzeo  and  Victor Gallego  had predoctoral grants from  Generalitat Valenciana  and  Spanish Ministry of Science and Innovation (MICINN) , respectively. David S. Peñaranda  has a postdoc grant from  UPV  ( CEI-01-10 ), mobility grants from  UPV  ( PAID-00-11 ) and the  Research Council of Norway  (EJ/hsm IS-STP, 2009) and also has been supported by a contract co-financed by  MICINN  and  UPV  ( PTA2011-4948-I ). F. -A. Weltzien received funding from The  Norwegian University of Life Sciences.
List of the terminal taxa included in the current version of the database (last update, July 2013) Chrysochromulina acantha  Leadbeater & Manton (1971) ; Chrysochromulina adriatica  Leadbeater (1974) ; Chrysochromulina arenghotii  Jensen & Moestrup (1999) ; Chrysochromulina alifera  Parke & Manton (1956)  in  Parke et al. (1956) ; Chrysochromulina apheles  Moestrup & Th omsen (1986) ; Chrysochromulina bergenensis  Leadbeater (1972) ; Chrysochromulina birgeri  Hällfors & Niemi (1974) ; Chrysochromulina brachycylindra  Hällfors & Th omsen (1985) ; Chrysochromulina brevifi lum  Parke & Manton (1955)  in  Parke et al. (1955) , now Haptolina brevifi la (Parke & Manton) Edvardsen & Eikrem 2011; Chrysochromulina breviturrita  Nicholls (1978) ; Chrysochromulina camella  Leadbeater & Manton (1969) ; Chrysochromulina campanulifera  Manton & Leadbeater (1974) ; Chrysochromulina chiton  Parke & Manton (1958)  in  Parke et al.
Software used Th e interactive key is developed using Xper2 version 2. 2 software. It is free software available with multilingual interface and compatible with diff erent OS (Windows, MacOS and Linux) under a creative commons license (BY-CC-ND). You can download it on http://www. infosyslab. fr and fi nd on this website a complete documentation with technical details, user manual and knowledge bases. Xper2 off ers an editor to structure and analyse descriptive data and an interface for interactive free access key  (Ung et al. 2010). Keys of various taxonomic groups are already available with Xper2  (Kerner et al. 2011)   (Mathieu et al. 2012 ) (Th omas and De Franceschi 2013). We installed the interactive key on a web server with Apache2, choosing the English interface. Th is content is under a creative commons license (BY-CC-ND), except when a special information is attached to images.
Descriptors and character states are also documented and illustrated. At each step, the user may ask the software to fi nd the best characters to distinguish the possible taxa. Th ree diff erent measures are proposed Xper, Jaccard, and Sokal & Michener (as "Best descriptors" in the select box). For each pair of remaining taxa, each coeffi cient measurement compares the possible states and the fi nal result is the sum for all the pairs. Xper coeffi cient checks only if there is no overlap (it means the two taxa may be completely distinct on this character) and so the measure for one pair of taxa is 0 (if overlapping) and 1 (if no overlapping). Jaccard coeffi cient was initially developed to compare sets of binary characters; here the states are considered as the binary characters and the.
ACKNOWLEDGMENTS We thank  Stephen McGovern  for providing purified DnaC protein. This work was supported by the  Agence Nationale de la Recherche  ( 2010-BLAN-1303-01  to  Ivan Mijakovic  and  Marie-Françoise Noirot-Gros ) and the  Federation pour la Recherche Medicale  ( SPF20111223359  to  Ivan Mijakovic  and  Lei Shi ). The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U. S. C. Section 1734 solely to indicate this fact. Protein-protein interaction data reported in this paper has been submitted to the  IMEx consortium through IntAct  (http://www. imexconsortium. org) and assigned the identifier IM-22270.
Acknowledgments We thank three anonymous reviewers and  G. Isabel  ( Toulouse ) for useful comments and corrections. M. G. thanks  U. Mu ¨ller  (Saarbrucken) and  D. Eisenhardt  ( Berlin ) for fruitful information exchange and discussions. Y. M. thanks the  Fyssen Foundation  for postdoctoral support. J. -M. D, J. C. S , and M. G. thank the  CNRS  and the  University Paul Sabatier  for financial support. M. G. acknowledges the specific support of a scientific grant of the  University Paul Sabatier  ( Project Apigene ) and the valuable support of the  Institut Universitaire de France.
The second group of methods all use a more direct approach, direct sequencing of mutant genomes and subsequent identification of causative EMS-induced mutations by comparing them to a reference genome, thereby eliminating the need for outcrossing  [15]. However, a reference genome is needed as a scaffold in both approaches, although a method based on comparing k-mers in WGS datasets that eliminates the need for segregating populations and reference sequences has been recently described  [16]. The full potential of the abovementioned methods can only be exploited in particular situations (e. g. when two or more alleles are isolated in the same screen) and/or require specialized software. Here we used a reliable alternative that can be used when single or multiple alleles are identified in the same screen, in reference or non-reference accession backgrounds.
DNA Preparation and Sequencing Approximately 1 g samples were collected from pools of 25 homozygous sur2-1gl1, homozygous 494 (F 3 generation after the 4 th backcross) and homozygous 2035 (F 3 generation after the 2 nd backcross) mutant plants, respectively, and bulked. DNA was extracted from each sample as described by Hanania et al. [27]  and eluted in 200 ml of water. The concentration and quality of the DNA were determined using a NanoDrop 2000 spectrophotometer (Thermo Scientific) then the samples were freeze-dried for shipping. Extracts from each line containing more than 5 mg of high-quality DNA, meeting the quality requirements for sequencing, were sequenced at Beijing Genomics Institute Shenzhen (BGI) using the Illumina HiSeq 2000 high-throughput sequencing system. The sequencing conditions, data processing procedures and alignment results are summarized in Tables  S1  and S2  in File S1.
DNA libraries covering 4. 29 giga base pairs (Gb), 4. 54 Gb and 4. 29 Gb (clean data) were generated for sur2-1gl1, 494 and 2035, respectively. Very high quality data were obtained from all samples, with Q20 values (error rate ,1%) of 96. 88 for sur2-1gl1, 96. 2 for 494 and 96. 8 for 2035, respectively. The deep-sequencing datasets have been submitted to the European Nucleotide Archive (ENA), and are available through the following link: https://www. ebi. ac. uk/ena (accession ID: ERA296179).
Analysis of the Sequence Data The Col-0 (TAIR10) sequence was used as reference genome, while both sur2-1gl1 and 494 are in Wassilewskija-4 (Ws-4, N5390) background. Consequently, to construct a Ws-4 reference genome for the mutant 494, sequencing reads of the parental genotype sur2-1gl1 were first aligned against the reference genome sequence (TAIR10) using SOAP2 (http://soap. genomics. org. cn/soapaligner. html), and SNPs of the sequenced genome were detected using SOAPsnp (http://soap. genomics. org. cn/soapsnp. html). Using SNPs from the sur2-1gl1 sequence the corresponding sites in the TAIR10 were replaced, and the newly constructed sur2-1gl1 genome was subsequently used as reference for 494. To identify the 494-specific mutation, credible SNPs (which are likely mutations between 494 and sur2-1gl1) were filtered from credible loci differing between 494 and sur2-1gl1-TAIR10.
Confirmation of the Causal Point Mutation in 494 and Genotyping The putatively causal mutation identified in the mapped region of 494 by analyzing the NGS dataset was subsequently reconfirmed by Sanger sequencing. To confirm the splicing defect and intron retention in the 494 mRNA, total RNA was extracted from seedlings of both 494 and sur2-1gl1 mutants using the RNAquous isolation kit (Ambion), treated with rDNase I, using the DNA-free Kit (Ambion), and subsequently cDNA was synthesized using the iScript cDNA Synthesis Kit (BIO-RAD), according to the manufacturers instructions. Furthermore, genespecific primers (At4g02570. F_TGGCTATCCCGCTTCTT-CTA and At4g02570. R_TTGCAAACACAACCAGCAAT) spanning the splicing site altered by the 494 mutation were used to amplify the cDNAs, using standard PCR procedures.
To genotype the 494 point mutation, new derived cleavedamplified polymorphic sequence (dCAPS) primers (494+Eco-NI. F_CTTGCCCTGATTACCTGTTGAA and 494+EcoNI. R_ GCCACTCTCTCCCTCTCCTT) were designed using dCAPS Finder 2. 0 software (http://helix. wustl. edu/dcaps/dcaps. html) [28]. One mismatch (underlined) was introduced in the F primer to incorporate a restriction site in the PCR product of one allele. After amplification, the PCR products were digested with EcoNI (Fermentas Fast Digest) following the manufacturer's recommendations and electrophoretically separated on a 4% agarose gel. The wild type yielded two fragments of 133 and 16 bp, respectively, while the 494 allele gave one band of 149 bp. To genotype sur2-1, which carries a 61 bp insertion in the cytochrome P450 CYP83B1 gene  [29] , primers were designed (Sur2-1F_AGCTTGGTTTCGGACAGTACAC and Sur2-1R_ ACTTAGATCAACGGTGCCTGAT) that amplify a 237 bp fragment in sur2-1, and a 176 bp fragment in wild type, respectively.
Conclusions To our knowledge, only two reports describe the identification of either a spontaneous  [49]  or EMS induced point mutation  [15]  in non-reference Arabidopsis accessions by NGS, and none promote the advantages of combining MBC with NGS to identify point mutations. Liu et al. [50]  have used targeted parallel sequencing of defined genomic regions to identify Arabidopsis mutants, but although their method combines MBC with deep sequencing we found more advantageous to combine NGS and mapping. Our strategy has potentially the broadest applicability in Arabidopsis analyses for several reasons. Firstly, coarse mapping to the Arabidopsis genome is now straightforward, and facilitated by recent updates to TAIR (The Arabidopsis Information Resource; http://www. arabidopsis. org/) marker database  [5].
Acknowledgments The authors would like to acknowledge the support of  Nicolas Delhomme  and  Chanaka Maduranga Mannapperuma  (https://bioinformatics. upsc. se)for handling the NGS dataset. We are very grateful to  Marcel Quint  ( Leibniz Institute of Plant Biochemistry ),  Mark Estelle  ( UC San Diego ) and  Judy Callis  ( UC Davis ) for kindly providing the axr6-3, cul1-6 and cul1-7 mutant lines.
Recordings were conducted at room temperature (ϳ23°C). The recording electrodes were filled with the following (in mM): 100 potassium gluconate, 0. 6 EGTA, 5 MgCl 2 , 8 NaCl, 2 ATPNa 2 , 0. 3 GTPNa, phosphocreatine 7, and 33 HEPES (pH 7. 3 adjusted with KOH). The extracellular solution comprised the following (in mM): 130 NaCl, 24 NaHCO 3 , 3. 5 KCl, 1. 25 NaH 2 PO 4 , 2. 5 CaCl 2 , 1. 5 MgCl 2 , and 10 glucose, saturated with 95% O 2 and 5% CO 2 , pH 7. 4. Data were filtered at 2 kHz, digitized at 10 kHz, acquired on-line, and analyzed off-line using pCLAMP 9 or pCLAMP10 software (Molecular Devices). Action potential (AP) firing was induced by injecting a positive current (ϳ30 -100 pA) to bring the resting membrane potential (RMP) to ϳϪ50 mV to induce a basal AP firing frequency of 0. 2-1 Hz unless stated otherwise.
Transfection and electrophysiological recordings from transfected cells. Detailed procedures for transfection of HEK293 cells and electrophysiological recordings from the transfected cells were described previously  (Deng et al. , 2007 (Deng et al. , , 2009;; Xiao et al. , 2009). Briefly, HEK293 cells were transfected with NTS1 alone, or together with WT TREK-2 channels or TREK-2 mutant. GFP was cotransfected for each experiment to identify the transfected cells. cDNA constructs coding for a human NT Type 1 receptor (GenBank accession number AY429106, subcloned into pCDNA3. 1 vector) was obtained from the Missouri S&T cDNA Resource Center (www. cdna. org). cDNA for the mutant TREK-2 channels was kindly provided by Dr. Donghee Kim (Rosalind Franklin University of Medicine and Science, Chicago)  (Kang et al.
, 2006). cDNA constructs coding for TREK-2 (NM_021161, subcloned into the pCMV6-XL4 vector) were purchased from Origene. An empty pEGFP N-3 GFP fusion protein vector (GenBank accession number U57609) was purchased from Clontech. Transfected HEK293 cells were subsequently used for electrophysiological recordings 24 -48 h after transfection. HCs at Ϫ55 mV were recorded from the HEK293 cells that showed fluorescence under a fluorescence microscope (Olympus 1X70) by whole-cell recordings. The extracellular solution contained (in mM) 130 NaCl, 3 KCl, 2 MgCl 2 , 2 CaCl 2 , 1. 25 NaH 2 PO 4 , 10 HEPES, and 10 glucose (pH adjusted to 7. 4 using NaOH and HCl). The above K ϩ -gluconate internal solution was used for this experiment. A continuous gravity perfusion system (flow, 5-7 ml/min) was used to change solutions.
, 2006; Kreneisz et al. , 2009). Application of NT to the HEK293 cells cotransfected with NTS1 and TREK-2 mutant induced sig-nificantly smaller HCs (Ϫ8. 2 Ϯ 1. 4 pA, n ϭ 7, p ϭ 0. 002 vs NT-induced HCs in the cells transfected with WT TREK-2; Fig. 4 D, E ). These data demonstrate that NT-induced depression of TREK-2 channels is mediated by PKC-dependent phosphorylation of TREK-2 channels on S326 and S359. We further corroborated NT-induced phosphorylation of TREK-2 channels in the EC. We treated entorhinal slices for 5 min with or without NT in the absence or presence of the PKC inhibitor (GF109203X). Slices were then lysed, and the lysates were immunoprecipitated with TREK-2 antibody. The immunoprecipitates were resolved by SDS-PAGE and Western blotted with anti-phosphoserine antibody. As shown in Figure  4F , treatment of slices with NT for 5 min induced persistent increases in the phosphorylation of TREK-2 channels when the slices were kept in NT-free solution for ϳ1 h (n ϭ 3 experiments, p Ͻ 0.
05% crystal violet (Sigma-Adrich) in a 5% ethanol solution, and positive colonies (>50 cells) were scored. The plating efficiency was calculated by dividing the number of positive colonies that grew in the absence of treatment and irradiation by the number of cells that were seeded. Apoptotic detection assay. Apoptotic cells were quantified 6 days after irradiation according to Riccardi and Nicoletti  (12). Briefly, cells (5x10 5 ) were fixed in cold 70% ethanol for at least 1 h, then they were washed in phosphate buffered saline [PBS; (pH 7. 2)] and resuspended in 100 µl of PBS containing 25 µg of RNase A, 2 mM EDTA and 10 µg of propidium iodide (PI). After incubation in the dark at 37˚C for 30 min, the fluorescence of 10,000 cells was analyzed using a fACScan flow cytometer and Cell Quest software (both from Becton Dickinson, San Jose, CA, USA).
Cells with a sub-diploid DNA content were recorded as being apoptotic. Autophagic detection assay. for autophagy determination 6 days after irradiation, we used the Cyto-ID™ Autophagy detection kit (Enzo Life Sciences, Plymouth Meeting, PA, USA) according to the manufacturer's instructions. This test measures autophagic vacuoles and monitors autophagic flux in live cells using a fluorescent cationic amphiphilic dye that selectively labels autophagic vacuoles. Briefly, cells (5x10 5 ) were washed in PBS (pH 7. 2), and resuspended in 500 µl of freshly diluted Cyto-ID ® Green Detection Reagent to a final volume of 2 ml with PBS, according to the manufacturer's instructions. The fluorescence of 10,000 cells was analyzed using a fACScan flow cytometer and Cell Quest software (Beckton Dickinson).
Classification and information A strain belonging to the clonal population of Staphylococcus capitis NCRS-A pulsetype (Table  1 ) was isolated from the blood culture of a preterm infant with LOS, hospitalized in the NICU of the Northern Hospital Group Center (Hospices Civils de Lyon, Lyon, France) and suffering of LOS. Species identification of the bacterial isolates and antimicrobial susceptibility testing (AST) were performed, respectively, using Vitek MS (bioMérieux, Marcy l'Etoile), 16S rDNA sequencing, the automated BD Phoenix system (Becton Dickinson, Sparks, MD) and with Shimadzu-MALDI-TOF MS system (Shimadzu Corporation), as implemented on  [21]. The strain was identified as being aStaphylococcus capitis by VITEK MS with 99. 9% and at 93. 7% by the MALDI-TOF MS, using the Shimadzu Launchpad software program and the SARAMIS database application (AnagnosTec GmbH) for automatic measurement and identification (Figure  1 ).
Standards in Genomic Sciences   The 16S rRNA sequences were aligned using the MUSCLE software, with the default parameters as implemented on Seaview version 4  [24] , and a tree was inferred based on 1285 sites using the distance model of observed divergence, as imple-mented in the BioNJ algorithm, and a bootstrapping process repeated 500 times. The final tree was rooted using the 16S rRNA sequence of Macrococcus equipercicus Type strain that belongs to a closely-related sister genus.
Genome sequencing information The genome sequence of S. capitis strain CR01 was determined by high-throughput sequencing performed on a Genome Sequencer FLX + system (454 Life Sciences/Roche) using FLX Titanium reagents according to the manufacturer's protocols and instructions, with approximately 47-fold coverage of the genome. This platform provides longer read lengths than other sequencing platforms to obtain raw sequences. De novo assemblies were performed using the Roche Newbler (v 2. 7) software package.
Genome sequencing and assembly The isolated DNA of S. capitis CR01, was used to create 454-shotgun libraries following the GS Rapid library protocol (Roche 454, Roche). The resulting 454 DNA libraries were sequenced using a whole-genome shotgun strategy by GS FLX Titanium sequencing kit XL+  [25]  (202,108 reads totaling 2. 5 Mb, X48 fold coverage of the genome). Genome sequences were processed by Roche's sequencing software according to the manufacturer's instructions (454 Life Science). The resulting shotgun reads were assembled de novo using the Roche Newbler assembly software 2. 7 (454 Life Science) and 26 large contigs (Contig00001 to Contig00026) were obtained. The N50 was 176239 bp.
Genome annotation An automatic syntactic and functional annotation of the draft genome was performed using the Mi-croScope platform pipeline  [26, 27]. The syntactic analysis combines a set of programs including AMIGene  [28] , tRNAscan-SE  [29] , RNAmmer  [30] , Rfam scan  [31]  and Prodigal software  [32]  to predict genomic objects that are mainly CDSs and RNA genes. More than 20 bioinformatics methods are then used for functional and relational analyses: homology search in the generalist databank UniProt  [33]  and in more specialized databases as COG  [34] , InterPro  [35] , PRIAM profiles for enzymatic classification  [36] , prediction of protein localization using TMHMM  [37] , SignalP  [38]  and PsortB  [39]  tools.
8% nonunique haplotypes), significantly lower in urban (0. 9%) than rural (2. 1%) and highest in endogamous groups (14. 3%). Analysis of molecular variance revealed 99. 98% of variation within populations, 0. 018% among populations within groups, and 0. 002% among groups. Of the 2,372 newly and 156 previously typed male relative pairs, 29% were differentiated including 27% of the 2,378 father-son pairs. Relative to Yfiler, haplotype diversity was increased in 86% of the populations tested and overall male relative differentiation was raised by 23. 5%. Our study demonstrates the value of RM Y-STRs in identifying and separating unrelated and related males and provides a reference database.
However, to fully explore the potential for the RM Y-STR set in differentiating unrelated as well as related males for various purposes, much more data are needed. Therefore, the International RM Y-STR Study Group, a worldwide collaboration between 52 laboratories, was formed. Group members, chosen based on preexisting practical experience in Y-STR analysis, genotyped under quality-controlled conditions the 13 RM Y-STRs in 14,644 males including 12,272 unrelated males from 111 worldwide populations and 4,744 closely related males. To compare the RM Y-STR set with conventional Y-STRs, Yfiler data were gathered in a subset of 7,784 unrelated men from 65 worldwide populations as well as in most of the male relatives analyzed for RM Y-STRs. The large collection of RM Y-STR haplotypes presented and explored in the present study enables a better understanding of their value to differentiate related and unrelated male individuals and populations, and additionally provides a suitable reference database for future use of RM Y-STRs in forensic, genealogical, anthropological, and population genetic studies.
DNA Samples With a worldwide coverage in mind, contributing laboratories were identified and recruited based on their previous submission of Y-STR population data to the Y-chromosome Haplotype Reference Database (YHRD; www. yhrd. org), hence having proven experience in Y-STR analysis. Each of the 52 contributing laboratories within the International RM Y-STR Study Group genotyped a selection of their own in-house population sample sets, each consisting of seven to 634 individuals (median 100 individuals per population sample) across 111 defined population samples per laboratory. Population sets were to include only unrelated males. Three population samples were notable exceptions-the Biaka Pygmy group and the Bhutanese Lhokpu and Mönpa language groups. These populations, and particular sample sets used here, are known to contain high numbers of male relatives (Biaka), or were specifically selected as having extremely low resolution with Yfiler (Bhutan).
Because these samples were ascertained differently to the other 108 populations within the study, they were excluded from the continental groups during analysis to avoid bias. The Aboriginal Australian samples used here were also not ascertained completely randomly, as they were selected based on Y-SNP haplogroups known to be authentic for Aboriginal Australians to avoid admixture effects as described elsewhere  [Taylor et al. 2012]. A subset of 7,784 individuals from 65 populations were additionally genotyped with the AmpFlSTR Yfiler PCR Amplification Kit (Life Technologies) for the most commonly used panel of 17 Y-STRs. Relative pairs were also analyzed, with 2,339 newly genotyped father-son pairs, 30 brother pairs, and three uncle-nephew pairs, for which relationship had previously been confirmed by autosomal DNA analysis; this dataset of male relatives was supplemented by 156 previously published relative pairs  [Ballantyne et al.
RM Y-STR Nomenclature The nomenclature of the RM Y-STRs was updated to comply with the guidelines of the International Society of Forensic Genetics-ISFG  [Gusmão et al. , 2006] , and to incorporate new variation observed in repeat structures. As such, all data collated were translated to comply with the updated nomenclature. Supp. Table  S3  shows the repeat structure and allele designations used during the project, determined in collaboration with Life Technologies and L. Gusmao  (IPATIMUP, Porto, Portugal). The RM Y-STR nomenclature used in the present study is in agreement with that used in the Powerplex R Y23 kit (Promega, Madison, WI) and in the Yfiler Plus Y-STR kit (Life Technologies) for the RM Y-STR markers included, respectively.