dataesr/scientific-paragraphs-categorization huggingface dataset:
Nonetheless, because there are few reads that map to more than one database, the overall results are robust to whether we preferentially mapped to Knob or the TE databases. Mapping siRNA and RNAseq libraries. After sequencing siRNA, we trimmed adapters and 39-end low quality nucleotides to ensure every read had three or more successive nucleotides with a quality score $20 at the 39-end. Subsequently, we selected reads of 22 and 24 nt using CutAdapt  [55]. These reads were filtered to eliminate rRNAs, rRNAs, miRNAs and snoRNAs and then mapped to the TEdb with bwa  [56] , using default settings. Uniquely and multiple mapped reads without mismatches were retained for further analyses. We divided the expression of reads with multiple targets by their number of targets. We applied the same procedure to two small RNA libraries from developing ear and shoot apex tissues from  [14, 44]  (SRX143311, and SRX143309).
(XLSX) Table  S2  Information about the subset of 340 TE subfamilies assessed between the mop1 mutant and the wild type. (XLSX) Table  S3  The Genbank references of the sequences in the Knob and CentC reference database. (XLSX) Text S1 Derivation of the test of proportionality, which tests the null hypothesis, for any single TE exemplar, that the ratio of TE copy number to siRNA targeting is equivalent between two accessions. (PDF).
This work was supported by  UC-MEXUS  grant # 49298  to BSG and  L. Eguiarte  as well as the  Agence Nationale de la Recherche ,  ANR-12-ADAP-002  to MIT. CMD was supported by a fellowship funded by the project  P09-AGR-5010  of the  Consejerı ´a Economı ´a, Innovacion Ciencia y Empleo de la Junta de Andalucı ´a, Spain  and the  Campus de Excelencia Internacional Agroalimentario , ceiA3. EM was supported by the  Balsells Fellowship at UC Irvine  and from  NIH Center of Excellence  Grant  P50GM76516. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Analysis Methods Qualitative data from the workshops (ie, moderator's notes), the proof of concept (ie, interviews), and the usability tests (ie, interviews and mistakes, difficulties or comments; observed and collected by the evaluator) were analyzed based on the thematic analysis method  [23]. After being familiarized with data JW and VCL coded the relevant extracts of material concurrently. Then, they analyzed the themes based on the recommendations of various usability authors  [13, 14, 24, 25]. Finally, they corroborated the pertinence of the selected topics, comparing them with initial verbatim. Assisted by the software "The Observer XT" and an observation grid, two trained psychologists (VCL and JW) collected, coded, and analyzed videos of usability tests. We measured the frequency of mistakes, requests for help, and the duration of task performance.
Usability Test of v1. 1 In this version, the overall program content was added to the website. Moreover, the readability improvements performed during the proof of concept phase were appropriate, as no participant reported any visual discomfort while browsing the website (except for the forum, as described in this section). Concerning the easy-to-learn perception, many participants asserted that they would have performed better if they had used the website more than once. Using the website would be easy provided I received training or that I spend more time using it. [Mrs. H, 71 y/o] However, various ergonomics issues were identified. Although the website home page was kept accessible using a script (JQuery Superbox) to display a screen with a light box effect (Figure  3 ), most participants did not know how to go back to the previous page.
Acknowledgments This study was partially funded by the  French Health Ministry (Projet de Recherche en Qualité Hospitalière   2009-PREQHOS 2009 ) and by the " Fondation Méderic Alzheimer " project grants  2012-2014. The authors thank all professionals of the Gerontology Department (ie, nurses, psychologists, physicians, physiotherapists, speech therapists, and social workers) who contributed to the program, and more specifically the other members of Diapason team ( Ps Sandra Boepsflug ,  Ps Mélodie Boulay ,  Dr Véronique Faucounau ,  Ps Emilie Gabillet, PhD Ps Hélène Kerhervé ,  Ps Grégory Legouverneur ,  Dr Hermine Lenoir ,  Ps Mathilde Riguet ,  Dr Marie-Laure Seux ,  Ps Ya-Huei Wu ), as well as  Marwan El Haj  and  Nawres Habib  for their contribution in the first development of the Diapason website, and  Julie Lecas  from the  Centre du Langues of University Paris Descartes  for English corrections.
The reads from 454 sequencing were assembled into contigs and scaffolds using Newbler version 2. 8 (Roche, 454 Life Sciences). The Illumina reads were trimmed using Trimmomatic (4) and then assembled with the SPAdes software  (5, 6)  while adding contigs generated from Roche 454. The obtained contigs were combined by the SSPACE  (7)  and Opera softwares  (8)  and helped by GapFiller  (9)  to reduce the set. Some manual refinements using CLC Genomics software (CLC bio, Aarhus, Denmark) and homemade tools improved the genome. Finally, the draft genome of L. massiliensis LegA T consists of 8 contigs without gaps, containing 4,387,007 bp and a GϩC content of 41. 19%. Noncoding genes and miscellaneous features were predicted using RNAmmer  (10) , ARAGORN  (11) , Rfam  (12) , Pfam  (13) , and Infernal  (14).
Coding DNA sequences (CDSs) were predicted using Prodigal  (15) , and functional annotation was achieved using BLASTϩ  (16)  and HMMER3  (17)  against the UniProtKB database  (18). The genome was shown to contain at least 60 predicted RNAs, including 7 rRNAs, 40 tRNAs, 1 transfer-messenger RNA (tmRNA), and 12 miscellaneous RNAs. A total of 3,767 genes were also identified, representing a coding capacity of 3,811,533 bp (coding percentage, 86. 88%). Among these genes, 174 (4. 62%) were founded as putative proteins and 1,326 (35. 2%) were assigned as hypothetical proteins. Moreover, 2,405 genes matched a least one sequence in the Clusters of Orthologous Groups (COGs) database  (19, 20)  with BLASTp default parameters. Nucleotide sequence accession numbers. The L. massiliensis strain LegA T genome sequence has been deposited at EMBL under the accession numbers CCVW01000001 to CCVW01000008.
All these differentially expressed genes (with t-test p-value ≤0. 05) plotted against their fold change values are shown in Figure  1. Transcripts that were up-or down-regulated at least 2 times were analysed in more detail (Additional file 1: Table  S1  and Additional file 2: Table  S2 ). The annotation and expression of each of these transcripts was checked against available data on the Medicago truncatula Gene Expression Atlas (http://mtgea. noble. org/v2/index. php) [22] , which shows gene expression in different plant organs and under various experimental conditions. The corresponding TC or EST sequences were retrieved and predicted amino acid sequences from these were used in BlastP searches to find predicted protein domains and matches to other known proteins (Additional file 2: Table  S2 ).
Validation of microarray results by RT-qPCR In order to validate the microarray results, we checked expression of seven up-regulated (Figure  2 ) and two down-regulated predicted transcripts in leaves, callus and SEs by RT-qPCR. Two of the up-regulated 2HA transcripts (Mtr. 47631. 1 Mtr. 10847. 1. S1) expressed throughout the culture period are putative transposases. The Mtr. 49328. 1. S1 transcript is highly expressed in the 2HA callus phase and Mtr. 47691. 1. S1is highly expressed in the transition to embryogenesis phase. Both are expressed in nodulation (Additional file 2: Table  S2 ). Both of the predicted down-regulated transcripts demonstrated nearly identical results in RT-qPCR (probes Mtr. 10439. 1. S1_at and Mtr. 1670. 1. S1). PCR amplification with different combinations of primers (F1-F6/R1-R6, Additional file 2: Table  S4 ) followed by sequencing revealed that the two transcripts were part of the same EIN3-like gene (Additional file 3: Figure  S1 ) which we called MtEIL1 and deposited as accession number GQ914771 in NCBI GenBank.
Analysis of the EIN3-like gene MtEIL1 and its protein It was of interest that only a single gene was downregulated more than two times and this gene was involved in ethylene signalling. Ethylene has been shown to be a significant regulator of SE  [15, 16]. Expression analysis with RT-qPCR for the down-regulated MtEIL1 transcript was also carried out using material from different organs of 2HA and WT plants (Figures  3a  and 3b ). Expression of this gene was increased during growth of Jemalong callus but remained low in the case of 2HA (Figure  3a ). The difference in expression between these two lines in callus was up to 30 times. Additional EIN3-like proteins were predicted by the FGENESH program (www. softberry. com) from available M. truncatula genomic sequences. Protein alignment and phylogenetic analysis of EIN3-like proteins from M.
Gene expression differences between embryogenic calli 2HA and non-embryogenic calli WT Transcription profiling obtained through microarrays revealed a relatively small number of differentially expressed genes. At the same time there was general up-regulation of transcription in 2HA compared to WT (Figure  1 ) that could have a cumulative effect on cell fate and mediate further developmental changes  [35]. Up-regulation of transposon-like genes with BED and hAT domains that we called BEDHAT1 and BED-HAT 2 (BH1 deposited in NCBI GenBank as accession KF679497, putative transposase), found in 2HA culture (Figure  2 ), could be an indicator of the general "openness" of chromatin in 2HA tissue cultures  [36]. Interestingly, BH2 is active in zygotic embryogenesis and BH1 is up-regulated during nodule formation and zygotic embryogenesis according to the Medicago Gene Expression Atlas  [22].
1. Roots were transferred to Fåhreus medium agar plates containing either 1 μM ACC, 0. 1 μM AVG or solvent (methanol at 1 μL/L) as a control on day 3. After a further 24 h incubation in the plant growth chamber to adapt to the altered hormone media, roots were inoculated with 10 μL of a culture of S. meliloti at the zone of emerging root hairs (i. e. on day 4 after germination). Plates were returned to the plant growth chamber (same conditions as above) and left to grow for four weeks. Nodules were counted under a dissection microscope. Lateral root numbers were counted and classified as either of <5 mm or >5 mm length. The root length covered with nodules (first to last nodule along the root) was measured with a ruler. All data were statistically analysed using InStat version 3. 06 for Windows (GraphPad Software).
mRNA microarray analysis Total RNA was isolated from four weeks culture for three 2HA and three Jemalong samples using the RNA-queous™-4PCR Kit (Ambion, http://www. ambion. com/). Hybridisations were performed according to the Affymetrix manual (Affymetrix, http://www. affymetrix. com/). Data processing was performed as described earlier  [21]. Raw data were background corrected, normalized, summarized and log2 transformed using the GCRMA algorithm (ver. 2. 2. 0) using the affy package of the bioconductor software  [48]  with default parameters. Normalised data are provided in Additional file 1: Table  S1. Differentially expressed genes were identified by evaluating the log2 ratio between embryogenic and non-embryogenic tissue culture in combination with a standard t-test.
RT-qPCR Total RNA was isolated as for microarray analysis. cDNA was synthesised with SuperscriptII (Invitrogen, http:// www. invitrogen. com/). PCR master mixes used Platinum Taq polymerase (Invitrogen) with the provided buffer and1. 5 μM SYTO9 dye, primers at 0. 4 μm and 3 mM dNTPs. A Corbett Rotor-Gene 6000 (Qiagen, www. qiagen. com/) machine was used to carry out real-time PCR. The qPCR cycling conditions comprised an initial denaturation at 95°C for 2 min followed by 40 cycles of 95°C for 10 s, 60°C for 30 s and 72°C for 30 s. Dissociation analysis (0. 5°C step) was performed in every run and products checked by gel electrophoresis to ensure product uniformity. Analysis of data was performed using Q-Gene software  [49]. The GAPDH gene was used as a calibrator. GAPDH is a suitable reference gene for M.
Promoter isolation Isolation of the MtEIL1 promoter was performed using a modified gene walking technique (Clontech, www. clontech. com) where the first gene-specific primer was biotinylated. After the first round of PCR the resulting product was immobilised on Dynabeads M-280 (Invitrogen), washed with the buffer provided and used for the second round of PCR with nested primers. The sequence of the MtEIL1 promoter was deposited in NCBI GenBank as accession EU499308 (Additional file 3: Figure  S1 ).
Acknowledgements This work was funded by the  Australian Research Council  ( CEO348212 ) through the  ARC Centre of Excellence for Integrative Legume Research (CILR). We thank  Mary Liu  and  S. J. Sim  for technical assistance,  Dr. Larry Croft  for assistance with the tiling arrays,  Dr. Feky Mantiri  for assistance with calli growth analysis and  Olga Berking  for assistance.
The Tarim Basin glaciers most likely stored water over 2003-2008 (+24 ± 33 m 3 s -1 discharge equivalent, DE). The glacier imbalance contribution to run-off is largest for Brahmaputra (-400 ± 60 m 3 s -1 DE), followed by the Indus (-220 m 3 s -1 DE), Ganges and Amu Darya (each -130 m 3 s -1 DE). Comparison of the discharge equivalent of glacier imbalance to measured river run-off is increasingly biased the further downstream the gauging stations are situated from the glaciers due to cumulative natural and manmade losses. It is also important to note that the available runoff data from literature and databases refer to various time periods, in parts considerably older than the ICESat period. Figure  2  illustrates thus only roughly the hydrological significance of the 2003-2008 glacier mass change in selected gauged catchments.
Acknowledgements. Sincere thanks are due to  Duncan Quincey , another anonymous referee, colleagues that commented on the study, and the editor  Andreas Vieli  for their valuable feedback that certainly improved our work. The study was funded by the  European Research Council  under the European Union's  Seventh Framework Programme  (FP/2007-2013)/ ERC  grant agreement no. 320816 , the  ESA  project  Glaciers_cci  ( 4000109873/14/I-NB ) and the  Department of Geosciences, University of Oslo. E. Berthier  acknowledges support from  TOSCA (CNES). We are very grateful to  NASA  and  NSIDC  for free provision for the ICESat data and the  USGS  for the SRTM DEM and Landsat imagery. Edited by:  A. Vieli.
Comparison of Gene Expression Profiles between Longissimus and Semimembranosus Muscles Gene expression microarray analysis was conducted on 180 muscle samples (90 LM, 90 SM). Comparison of LM and SM muscle transcriptome was achieved using the ''GenmascqChip'', a 15 k pig skeletal muscle microarray. Raw data sets were checked for quality criteria. The 10753 remaining probes were considered significantly expressed in both muscles. We observed a strong muscle effect on gene expression with 5582 (37%) of probes being differentially expressed between LM and SM (adjusted P value # 0. 05). As shown in Figure  1 , fold change (FC) ratios varied from 1. 1 to 15 and were for the most part quite low with median values ,1. 5 in the two muscles. These 5582 differentially expressed probes corresponded to 3823 annotated genes, with 1690 and 2133 genes overrepresented in LM (Table  S1 ) and SM (Table  S2 ), respectively.
2 Differentially expressed genes were clustered using GO BP terms semantic similarity between genes as distance, to group functionally similar genes together. 3 Fold Change is expressed as the expression ratio of Semimembranosus to Longissimus samples. 4  Benjamini and Hochberg adjusted P value. 5 Unique identifier and gene ontology term in the GO database (http://www. geneontology. org/). doi:10. 1371/journal. pone. 0096491. t002 FC observed in microarray analysis have been validated by quantitative PCR analyses using seven differentially expressed genes. We have considered that FC direction agreement between the two methods validates the differentially expressed genes set. Besides, there are few studies comparing gene expression of contrasted skeletal muscles in pigs, most of them focus on LM and none of them compared LM and SM  [16, 17].
Microarray Design The ''GenmascqChip'', a custom 15 k pig skeletal muscle microarray was used in this study  [15]. Microarray annotation was produces using BLAST 2. 2. 23+  [73]  for megaBLAST analysis of the 15198 oligonucleotides sequences (60 mers) printed on the microarray against ENSEMBL cDNA and NCBI refSeq mammal databases. Annotation was based on similarity and quality criteria  [74]. Among the 15198 probes of the GenmascqChip, 12939 probes (i. e. 85% of the oligonucleotides) have been linked to a unique annotated sequence and to 9169 unique genes (i. e. , 30% of redundancy). An 8615 K oligo-microarray Agilent format was chosen, therefore one probe per microarray and eight microarrays were fitted in each slide. Description of the GenmascqChip is publicly available into the GEO repository (http://www.
Microarray Hybridization Total RNA (350 ng) from each sample (90 LM, 90 SM) was individually labeled with Cy3 using the Low RNA Input Linear Amplification Kit PLUS, One-Color (ref 5188-5339, Agilent Technologies, Massy, France) following the manufacturer's instructions. Microarray hybridizations were carried out at 65uC for 17 hours in Agilent's SureHyb Hybridization Chambers containing 600 ng of Cy3-labeled cRNA sample. Slides were disassembled and washed in Gene Expression Wash Buffer 1 for 1 minute at room temperature and then in Gene Expression Wash Buffer 2 for 1 minute at 37uC. Microarrays were scanned at 5 mm/pixel resolution using the Agilent DNA Microarray Scanner G2505B, and images were analyzed with Agilent Feature Extraction Software (Version 9. 5), using the GE2-v5_95_Feb07 FE extraction protocol.
All effects exceeding the significant level of P,0. 2, were kept in the model. The muscle effect was kept in each model. P-values were adjusted according to Benjamini and Hochberg multiple testing correction procedure  [77]. Differentially expressed probes were selected using adjusted P-values of 0. 05 or less. Adjusted means for LM and SM were calculated using lsmeans function for the muscle effect (package lsmeans). Differentially expressed probes were assigned as overrepresented in LM or overrepresented in SM according to the greatest mean. Fold change value is expressed as ratio of the greatest to the least mean: the expression ratio of LM to SM muscle effect when genes are overrepresented in LM and as the expression ratio of SM to LM muscle effect when genes are overrepresented in SM.
Primers (Table  5 ) were designed from porcine sequences using Primer Express software 3. 0 (Applied Biosystems). Amplification was performed in triplicate, in 12. 5 ml with 5 ng of reverse-transcribed RNA and both forward and reverse primers (200 nM each) in 1X PCR buffer (Fast SYBR Green Master Mix, Applied Biosystems) containing Uracil DNA glycosylase to prevent any DNA contamination from previous PCR. A StepOnePlus TM Real Time PCR system (Applied Biosystems) was used. Thermal cycling conditions were as follows: 50uC for 2 min, 95uC for 20 s, followed by 40 cycles of denaturation at 95uC for 3 s and annealing at 60uC for 30 s. Specificity of the amplification products was checked by dissociation curves analysis. Three genes were selected as stable reference genes for normalization using geNorm algorithm  [78] : beta 2 microglobulin (B2M), TATAbox binding protein (TBP) and 18S (18S rRNA predeveloped TaqMan kit from Applied Biosystems).
Functional Analysis To facilitate functional categorization of differentially expressed genes, we used hierarchical clustering of genes based on semantic similarity of GO BP terms. Semantic similarity was calculated between each pairwise combination of differentially expressed genes with a muscle fold change ratio (i. e. ratio of the greatest to the least muscle effect) above 1. 5. Similarity was computed according to semantic similarity measures based on the method of Wang  [26]  implemented in the GOSemSim package  [79]. Two genes that shared several GO BP terms result in similarity value close to one, indicating that they are similar in terms of biological process. Conversely dissimilar genes result in similarity value close to zero. Then hierarchical clustering was performed using ''1semantic similarity'' as distance between two genes (similar genes have a distance close to zero) and ''ward'' as aggregation criterion to identify clusters of genes that share BP terms.
Acknowledgments The authors thank  Jean-Francois Nicolaon  and the staff from the  France Hybrides nucleus herd of Sichamps  for experimental animal care and identification,  Rachel Marie ,  Laurent Letelu ,  Caroline Cordebois  and  Najate Aı ¨t-Ali  for excellent technical assistance, and the Orleans-Viandes abattoir for their assistance in tracking animals and carcasses and  J. Glenisson ,  L. Letelu , and  J. Pires  ( Hendrix Genetics RTC, St. Jean de Braye, France ).
2 Differentially expressed genes were clustered using GO BP terms semantic similarity between genes as distance, to group functionally similar genes together. 3 Fold Change is expressed as the expression ratio of Longissimus to Semimembranosus samples. 4 Benjamini and Hochberg adjusted P value. 5 Unique identifier and gene ontology term in the GO database (http://www. geneontology. org/). doi:10. 1371/journal. pone. 0096491. t001 Interestingly, this cluster highlighted SM overexpressed genes also involved in the regulation of developmental and myogenesis signaling pathways or in the muscle regeneration process: fibroblast growth factor 18 (FGF18), members of the Notch signaling pathway (NOTCH3 and deltalike 4, DLL4), chemokine (C-C motif) ligand 21 and 23 (CCL21 and CCL23) and complement component and factor (complement component 1, q subcomponent, C chain, C1QC; complement component 1, r subcomponent, C1R; complement component 1, s subcomponent, C1S; complement component 3, C3; complement component 4A, C4A and complement factor B, CFB).
2D). The A-box and adjacent downstream region C[CG] [AC]GA[GC][TC]AGC[TC][GT]GG-[AC][CT] [TA]ACA (matching with the SE motif and ATE sequence) was found to be the most commonly occurring Alu-sub-sequence with 314 hits in the Stimulated dataset (MEME p D 2. 7E-1242) (Fig. 2D , topmost motif). The maximum enrichment of this subset of Alu sequence in Stimulated peaks was recapitulated by measuring the frequency of occurrence of the canonical Alu consensus sequence (using a window size of 20 bases and sliding the window by 1 base per iteration) in Stimulated peaks. Thus the occurrence of ATE sequence at location C10 to C46 bps from Alu start site was significantly higher than the other sequences of the Alus: locations C79 to C115, C99 to C155, C139 to C195 and C216 to C272 (ANOVA P <. 0001, Fig.
RNA extraction, affymetrix microarray assays and qRT-PCRs RNAs were extracted using Trizol (Invitrogen) protocol. Either total cells or purified nuclear fractions were used for RNA extraction. Total RNA were subjected to GeneTitan 1. 0 ST Affymetrix microarray hybridizations using standard protocols at Stockholm BEA Affymetrix facility. Data were analyzed by GeneSpring V12. 6. 1 using specified ANOVA settings. For qPCRs, cDNA was made out of total RNA using Vilo reverse transcription kit (Invitrogen) as recommended. qRT-PCRs were performed using cDNA template using 2£ SYBR-Green PCR mix from Fermentas or BioRad on Stratagene MX3005 machines. Separate thresholds were applied to each primer pair for Ct value calculation. ddCt calculations were performed on quadruplicate Ct values from different runs for relative quantitation.