dataesr/scientific-paragraphs-categorization huggingface dataset:
To be represented on the maps, incidence rate were discretised using rounded values of the classes obtained by the Jenks method in ArcGIS, which enabled maximization of contrasts. Analysis of spatial clustering. To address the question of whether cases occurred at random in the district or according to a given spatial pattern, we performed several statistical analyses. First, a general statistic of global aggregation, Moran's Index (I), was calculated to assess spatial autocorrelation  [41]. Statistical significance was calculated using bootstrap methods. Then, we evaluated the relative risk of BU over the Akonolinga region using the Spatial Oblique Decision Tree algorithm (R package SPODT). This method was used to identify homogeneous risk areas on the time-aggregated series and to quantify the risk associated with each zone.
BU case data From January 2002 to May 2012, 915 patients originating from Akonolinga health district were diagnosed and treated free of charge at the Akonolinga district hospital by the BU management intervention. Out of these patients, 853 were new cases and among those, 787 cases had a documented place of residence in one of the 154 villages of Akonolinga district included in the analysis. The total population of the study villages was 60,188 inhabitants and the study area had a surface of 3,685 km 2. The north part of the district, 16 villages totalling 10 cases and 2,750 inhabitants, was excluded because the area was only documented in the forest LULC database. Among the 787 clinical BU cases in the database, 513 (65%) had received a laboratory-confirmed MU infection diagnosis (396 by PCR and/or microscopy, 117 by microscopy only).
The main limitation of this work was that it relied on ''semiactive'' case detection. We analysed data from cases which were diagnosed and treated at Akonolinga district hospital. They may not represent all the cases that occurred in the Akonolinga health district over the study period, since patients tend to seek traditional treatments as a first option  [48]. However, since BU is a slowly progressing disease and difficult to cure even in hospitals, cases are likely to seek medical care at some point, eventually after failure of traditional treatment  [48]. We analysed the spatial incidence trends over large periods of time, which probably allowed us to capture a large proportion of the incident cases over the study period, even patients with long delay to diagnosis. In addition, we cannot be sure that cases were infected in a given location, but given the activity patterns and our study scale, we can be confident that our work focuses on the main environments frequented by the populations.
Acknowledgments The authors would like to thank  Tamara Giles-Vernick  for sharing her understanding of population practices in Akonolinga,  Juliette Paireau  for numerous tips using R and ArcGIS,  Benjamin Roche  and  Romulus Breban  for useful insights on data analysis,  Joachim Etouna  ( Institut National de Cartographie du Cameroun ),  Minia Vale  `re (BUCREP) who contributed population and administrative data, HerveChevillotte ( IRD Cameroon ), for environmental data from the  IFORA  project ( ANR-Biodiv grant IFORA ), the partner teams of the  EXTRA-MU  project, the  Mycobacteriology Service staff at Centre Pasteur du Cameroun  who performed diagnosis confirmation, and  Drs Gervais Folefack  and  Michae ¨l Tsoungui at Akonolinga district hospital  and their staff.
Analysis of resequencing datasets Illumina shotgun sequence reads from eight accessions (17×-110× depth; Table  1 ) were mapped to the haploid Clementine reference using bwa, and single nucleotide variants were identified using samtools and in-house scripts (Supplementary Note 6). Heterozygosity in diploid accessions was estimated in windows of 100-500 kb by dividing the number of confidently inferred heterozygous single nucleotide variant ("het") sites by the number of eligible sites in the window at which confident variant calls could be made, based on depth and alignment quality (Supplementary Note 6).
Acknowledgments National Science and  Technology Institute of Genomics for Citrus Breeding  ( FAPESP 2008/57909-2  and  CNPq573848/08-4 ) and  Brazilian Agricultural Research Corporation (Embrapa)  ( MAT, JF-A, MAMach ) and  Embrapa-Monsanto Agreement (JF-A) ;  Agence nationale de la recherche (ANR)  grant  CITRUSSEQ PCS-08-GENO  (OJ, XP, MR, PO, FL, KJ) and program  ANR Blanc-PAGE , ref:  ANR-2011-BSV6-00801  (JS, FM); US National Institute of Health  grant  HG00783  (MB, PB, AL); Grant  PrometeoII/2013/008  from the  Generalitat Valenciana, Spain  and grant ( AGL2011-26490 ) from the  Ministry of Economy and Innovation-Fondo Europeo de Desarrollo Regional (FEDER) ,  Spain  (PA, LN);  Conselleria de Agricultura, Pesca ,  Alimentación y Água  from the  Generalitat Valenciana (JPP, DR) ;  Ministerio de Economia e Innovación  grants  PSE-060000-2009-8  and  IPT-010000-2010-43  and  Citruseq-Citrusgenn consortium companies (Anecoop S.
in NCBI's genome database under Accession  XXXXX000000. WGS sequence for the sweet orange is deposited in NCBI's  Sequence Read Archive  (http://www. ncbi. nlm. nih. gov/Traces/sra/)under BioProject  PRJNA225968 (454 data ) and in the NCBI trace archive under SPECIES_CODE=' CITRUS SINESIS' AND CENTER_NAME='JGI '. Citrus resequencing data are in the  Sequence Read Archive at NCBI  under the following accessions: SRX372786  (sour orange), SRX372703 (sweet orange),  SRX372702  (Low.
After autogamy, F2 clones become homozygous for the rnai mutant (gray) or wild type (black) allele. Most other (UV-induced) mutations (m) are not linked with the target mutation (rnai) and segregate independently. F2 clones carrying the rnai allele were pooled for MAC DNA extraction and whole genome-sequencing. In this data set only the rnai mutation is covered by 100% of SNP-containing reads, whereas all other mutations are ideally covered by 50% SNP-containing and 50% wild type reads. carried out as described previously  (22, 38). NSF-depleted cells were checked for viability after 36 h, the time at which typically all cells were dead or dying in a successful silencing. To reveal partial loss-of-function phenotypes, ND169 dsRNA producing E. coli were typically mixed in 1:5 ratio with ICL7a dsRNA producing bacteria.
MACs were collected and purified from bacteria and cell debris by ultracentrifugation through a 2. 1 M sucrose cushion. Recovered MACs were lysed and DNA was extracted as described  (39). 5 g of RNaseA-treated genomic DNA were used for library construction. DNA was sequenced by single-end (75 bp lead length) or paired-end (50 or 100 bp read length) strategies using Illumina GAII and HiSeq next-generation sequencers (for overview of sequence output for each mutant F2 pool, see Supplementary Table  S2 ). The reads were mapped to the reference P. tetraurelia strain 51 genome (18,32) using the Burrows-Wheeler Alignment tool (BWA)  (40)  with default parameters and the mapping indexed with SAMtools  (41). Custom Perl scripts and the SAMtools mpileup function were used to identify positions where at least 80% of the calls differed from the reference genome, at positions with at least 10-X coverage and less than 300-X coverage.
Small RNA analysis by northern blot Total RNA extraction and small RNA northern blots were carried out as described  (22). As previously, two adjacent 50 nt sense oligonucleotide probes matching to the dsRNA region were used to detect ND169 siRNAs, as most of the produced siRNAs are antisense to the target transcript. Similarly, endogenous cluster22 siRNAs were detected with two adjacent 50 nt oligonucleotide probes, complementary to the top strand (relative to transcription of the 5 marginal open reading frame). S8B ). Hypomorphic alleles are shown in blue (rnai+/-phenotype). Gene accession numbers are available in supplementary data (Supplementary Table  S1 ). Co-segregation of the phenotype with the mutation in F2 was verified for alleles labelled with an asterisk (*). Alleles complemented by injection of linear DNA encoding the wild-type gene with its natural flanking regions are labeled with two asterisks (**).
Phenotypes were recorded 72 h after the first feeding. Bacteria were fed in equal amounts. Triple knock down experiments (CID3+CID4+ND169; CID3+CID5+ND169; CID4+CID5+ND169) did not show inhibition of ND169 reporter silencing (data not shown). Cross-silencing between CID1 and CID2 genes is unlikely, as the maximum length of perfect homology is 12 nt, and 18 nt with one central mismatch. (C) Northern blot analysis of associated ND169 siR-NAs. The ND169 probe corresponds to a 100 bp region of the dsRNA and is sense oriented. The lower panel shows hybridization to glutamine tRNA as a loading control.
05; n = 3; standard deviation is shown). Phenotypes were recorded 72 h after the first feeding. Bacteria were fed in equal amounts. Triple knock down experiments (CID3+CID4+ND169; CID3+CID5+ND169; CID4+CID5+ND169) did not show inhibition of ND169 reporter silencing (data not shown). Cross-silencing between CID1 and CID2 genes is unlikely, as the maximum length of perfect homology is 12 nt, and 18 nt with one central mismatch. (C) Northern blot analysis of associated ND169 siR-NAs. The ND169 probe corresponds to a 100 bp region of the dsRNA and is sense oriented. The lower panel shows hybridization to glutamine tRNA as a loading control.
ACKNOWLEDGMENTS We thank  Jean Cohen  for providing plasmid constructs and advice in UV-induced mutagenesis,  Michael Lynch ,  Thomas G. Doak  and  Casey McGrath  for sharing unpublished sequence data of Paramecium species,  Linda Sperling ,  Martin Simon  and  Vincent Récamier  for comments on the manuscript, and all lab members for critical discussions and continuous support. The sequencing of RNAi mutant MAC genomes benefited from the facilities and expertise of the high throughput sequencing platform of  IMAGIF (Centre de Recherche de Gif --www. imagif. cnrs. fr).
FUNDING Agence Nationale de la Recherche  [' Investissements d'Avenir' program   ANR-10-LABX-54 MEMO LIFE/ANR-11-IDEX-0001-02   Paris Sciences et Lettres* Research University ,  ANR-08-BLAN-0233  ' ParaDice ',  ANR-12-BSV6-0017  ' INFERNO ' to E. M. ];  Fondation pour la Recherche Médicale ['Equipe FRM ' to E. M. ] and  Fondation Pierre Gilles de Gennes  [post-doctoral fellowship to S. M. ]. National Science Foundation [NSF   EF-0328516-A006 ]. This study was carried out in the context of the CNRS-supported  European Research Group 'Paramecium Genome Dynamics and Evolution'  and the  European COST Action   BM1102. Funding for open access charge:  Agence Nationale de la Recherche. Conflict of interest statement. None declared.
Gene profiling and data analysis DNA and RNA were extracted as previously described  [12, [17] [18] [19]  and controled on Agilent Bioanalyzer (Agilent Technologies, Massy, France). Genomic profiles of the 188 BCs were established by using array-comparative genomic hybridization (aCGH) onto high-resolution 244K CGH microarrays (Hu-244A, Agilent Technologies, Massy, France). A pool of 13 normal male DNA was used as reference. Gene expression data from the same 188 BCs and 4 normal breast (NB) samples, which represented 1 pool of 4 samples from 4 women, and 3 commercial pools of respectively 1, 2 and 4 normal breast RNA (Clontech, Palo Alto, CA), were obtained using whole-genome DNA microarrays (HG-U133 Plus 2. 0, Affymetrix). Both approaches and analysis methods have been used in our previous studies  [12, 17, 18].
All probes for aCGH, gene expression and DNA promoters methylation analyses were mapped according to the hg18/NCBI human genome mapping database (build 36) to homogeneously integrate the data. The aCGH, gene expression, methylation data, as well as the integrated CNA/gene expression and DPMA/gene expression analyses are illustrated by pipelines (Figures  S2  and S3 , respectively). Validation and prognostic impact of candidate genes were evaluated in a large public series of BC samples. Thirty-six data sets, including a total of 5,765 non-redundant samples, were collected from public database i. e. Gene Expression Omnibus (GEO/NCBI), Array Express (EBI) and authors' websites (Table  S1B ). Raw data from each study were normalized using quantile normalization, and log2-transformed. The intrinsic molecular subtypes of each tumor sets were defined using Hu single sample predictor (SSP)  [4].
DNA promoter methylation profiling and data analysis We captured the methylated DNA of 117 (109 tumors+8 NB) samples by using the MethylMiner Methylated DNA Enrichment Kit (Invitrogen). Genome-wide DNA-methylation analysis was done on custom [A-MEXP-2178 (arrayexpress)] human promoter arrays 26400K (Agilent Technologies, Massy, France) using the MethylMiner Methylated DNA Enrichment Kit (Invitrogen)  [36]. Over 414,000 probes cover promoter regions approximately 2 3 kb to +3 kb relative to transcription start sites (TSSs) with a resolution of 280 bp in average. Scanning was done with Agilent Autofocus Dynamic Scanner (G2565C, Agilent Technologies). Raw data were obtained from Feature extraction 10. 7. 3 software (Agilent Technologies). Probes not mapped to exact positions in the genome as well as those under the background signal were removed with the control probes.
The final dataset contained 326,350 unique probes covering 18,297 promoter regions according to the hg18/NCBI human genome mapping database (build 36). The M (Log 2 Red-Log 2 Green) values of each probe on the array were then obtained and normalized according to their GC content. Then, inter-array quantile normalization was done for the correction of distribution differences among experiments. To estimate the global methylation level for a given gene in one sample, we computed a methylation score based on the sum of frequency of probes with a M value greater than zero combined with its amplitude and frequency of probes with a M value less than zero combined with its amplitude. Clustering was done with the Cluster program using Pearson correlation as similarity metrics and average linkage clustering.
Gene mutations Polymerase chain reaction (PCR) and direct sequencing were done using standard conditions with gene-specific primers designed to amplify coding sequence of ARID1A, ASXL1, FOXO3, L3MBTL4, MAP2K4, PIK3CA, RUNX1, RUNX3 (Table  S1C ). Most PCR amplifications were done in a total volume of 25 ml PCR mix containing at least 10 ng template DNA, Taq buffer, 200 mmol of each deoxynucleotide triphosphate, 20 pmol of each primer and 1 unit of appropriated Taq polymerase (Table  S1C ). PCR products were purified using Millipore plate MSNU030. The purified PCR products (2 ml) were used for sequencing using the Big Dye terminator v1. 1 kit (Applied Biosystems, Courtaboeuf, France). After G50 purification, sequences were loaded on an ABI 3130XL automat (Applied Biosystems). The sequence data files were analyzed using the Seqscape software and all mutations were confirmed on an independent PCR product.
Validation of methylation results The supervised analysis comparing methylation score data of ER+ and ER-tumors identified 3,484 gene promoters with methylation differences between the two groups (Table  S4B ) (t test, FDR,0. 05). Among them, 1,753 gene promoters (including those of APC, CAV1, CCND2, CDCA7, CDH3, CDKN2A, CDKN2B, HEY2, RASSF1, RECK) had a DNA methylation level higher in the ER+ group (t-test, FDR,0. 05). Conversely, 1,731 gene promoters (including those of BCL2, ESR1, HSD17B4, PISD, WNK4) had a higher level of methylation in the ER-group (FDR,0. 05). These For each region, heatmaps for genome copy number and gene expression profiles are consecutively drawn. Genome copy number was measured by aCGH on probes or groups of probes spanning each of these regions. Red indicates increased copy number and green indicates decreased copy number.
Financial support for this study came from  Inserm ,  Institut Paoli-Calmettes , and grants from  Ligue Nationale Contre le Cancer (Label DB) ,  GEFLUC (MC) ,  Institut National du Cancer  ( ACI2007 ,  AO2008 ,  AO/R-TRANS09 «identification, caracterisation et validation clinique de nouvelles cibles cellulaires et moleculaires dans les cancers du sein de mauvais pronostic» IVOIRES (INCA) ) and  DGOS  (SIRIC label: grant  INCa -DGOS-Inserm 6038 ). LAK and IB were supported by a fellowship from the  Franco-Algerian program  of high level formation in France (PROFAS) and the Algerian government, respectively. MM was supported by a fellowship from the  AVEROES European program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
All sequencing was performed using big-dye terminator chemistry on ABI3730 or ABI3700 capillary automated sequencers (Applied Biosystems). All assemblies were generated using Phrap. All repeat regions, gaps and low quality regions were bridged using large insert fosmid libraries, read-pairs, or endsequenced polymerase chain reaction (PCR) products. The sequences were manipulated to the community standard of "Finished"  (Chain et al. 2009). Nucleotide sequence position 1 of each chromosome was assigned according to that of published Escherichia coli genomes. Gene prediction and annotation were performed using Microbial Genome Annotation Pipeline  (Sugawara et al. 2009) , followed by manual curation on the basis of the results of BLASTP homology search against the public nonredundant protein database (http://www.
ncbi. nlm. nih. gov/, last accessed August 6, 2014). The annotated genome sequences of SM39 and Db11 have been deposited to the DDBJ/EMBL/GenBank database under the accession numbers AP013063 for the SM39 chromosome, AP013064 for the pSMC1 plasmid of SM39, AP013065 for pSMC2 of SM39, and HG326223 for the Db11 chromosome.
Genome-Wide Comparative Analysis Intra-and interstrain clustering analyses of protein coding sequences (CDSs) were performed based on the results of all-toall BLASTP analysis with a threshold of !90% amino acid sequence identity over !90% aligned length of the query sequence (supplementary fig. S1 , Supplementary Material online, for details). In Silico Molecular Cloning (InSilico Biology, Yokohama, Japan) was used for genome sequence comparison. The average nucleotide identity (ANI) was calculated using the JSpecies software  (Richter and Rossello-Mora 2009). Multiple alignments of sequences were constructed using the ClustalW program  (Thompson et al. 1994 ) and a neighbor-joining tree was generated using the Tamura-Nei model in MEGA5  (Tamura et al. 2007). Pathway analysis was performed using the KEGG (Kyoto Encyclopedia of Genes and Genomes) online database  (Kanehisa and Goto 2000).
Signal peptide-containing proteins were identified using the SignalP 4. 1 server (http://www. cbs. dtu. dk/services/SignalP/, last accessed August 6, 2014)  (Petersen et al. 2011). For the interspecies comparison, following four genomes were used: S. proteamaculans strain 568 (GenBank accession number CP000826) and S. plymuthica strains AS9 (CP002773)  (Neupane et al. 2012 ) and 4Rx13 (CP006250)  (Weise et al. 2014) , which were all isolated from plants, and S. odorifera strain DSM4582 (from human sputum) (ADBY00000000).
Acknowledgments The authors thank many members of the  Serratia research community , in particular  C. Wandersman , for their support,  Aurelie Blanc  for worm sorting, and  T. Nakamura  and  H. Takahashi  for providing strain SM39. This work was supported partly by a  Scientific Research Grant on Priority Areas  from the  University of Miyazaki  and the Program to Disseminate Tenure Tracking System from the  Japanese Ministry of Education, Culture, Sports, Science and Technology  to A. I. (http://www. miyazaki-u. ac. jp/ir/english/index. html), and  Grant-in-Aid for Scientific Research  ( 18390137  and  23590523 ) from the  Japan Society for the Promotion of Science  to  N. G. Sequencing of Db11  was made possible by the 2001 CNRS Sequencage aGrande Echelle programme, and that of SM39 was by the  Research for the Future Program of the Japan Society for the Promotion of Science  ( JSPS-RFTF 00L01411 ).
Crystallization of the C5a proteins Prior to crystallization, the buffer composition of the murine C5a proteins was adjusted to 20 mM HEPES pH 7. 5, 150 mM NaCl and the protein samples were concentrated to 25 mg ml À1 for hC5a-A8 and to 8-10 mg ml À1 for mC5a and mC5a-desArg. Initial crystallization experiments were carried out in 96-well sitting-drop plates using a Mosquito robot (TTP Labtech) and commercial screens from Hampton Research and Molecular Dimensions. For hC5a-A8, crystals appeared after one month at 4 C over a reservoir consisting of 20%(v/v) 2-propanol, 20%(w/v) PEG 4000, 0. 1 M sodium citrate pH 5. 6 with a protein:reservoir solution ratio of 2:1. For data collection, the crystals were cryoprotected by soaking them in the reservoir solution followed by flash-cooling in liquid nitrogen.
Data collection and structure determination Data sets for hC5a-A8 were collected at 100 K on beamline X06SA at the Swiss Light Source (PSI, Villigen, Switzerland). Data sets for mC5a and mC5a-desArg were collected at 100 K on beamline 911-3 at MAX-lab (Lund, Sweden). All data sets were processed with XDS  (Kabsch, 1993 ; Table  1 ). The hC5a-A8 crystals displayed C222 1 symmetry and diffracted to a maximal resolution of 2. 4 A ˚. The structure was solved by molecular replacement (MR) in Phaser  (McCoy et al. , 2005)  using a search model derived from the hC5a-desArg structure  (Cook et al. , 2010)  and encompassing residues Val694-Ser743 (i. e. where the N-terminal helix had been removed). Initial electron-density maps showed clear additional density for the missing residues in the hC5a-A8 N-terminus, which were rebuilt using phenix.
75 ml of the cell suspension was added to each C5a dilution and release was allowed to proceed for 3 min at 37 C. The reactions were then transferred to ice and centrifuged for 3 min at 400g and 4 C. NAG activity was assessed in the presence of 3. 53 mM p-nitrophenyl-N-acetyl--d-glucosamide (Sigma) for 60 min at 37 C. The enzymatic reaction was stopped by adding 0. 4 M glycine-NaOH pH 10. 4 and the spectral absorbance was measured at 405 nm. The maximal NAG release (100% reference) corresponds to the maximal NAG release activity obtained for commercial hC5a. The data are the means AE standard deviation of multiple independent experiments and were analyzed in GraphPad Prism (http://http://www. graphpad. com) using a four-parameter logistic nonlinear regression. Statistical analyses were performed using the paired twotailed Student's t-test in Excel.
Since the conserved core between all reported hC5a structures consists of a three-helix bundle encompassing helices H2, H3 and H4  (Zuiderweg et al. , 1989; Zhang et al. , 1997; Fredslund et al. , 2008; Cook et al. , 2010) , a model based on the hC5a-desArg structure and lacking the N-terminal helical segment (i. e. residues Val694-Ser743 of monomer A from PDB entry 3hqa;  Cook et al. , 2010)  was then used in the MR search. This three-helix bundle model gave a clear MR solution (log-likelihood gain of 946) and initial electron-density maps displayed well defined additional density for the missing N-terminal residues (Supplementary Fig. S3a ). The final model encompasses residues Thr678-Lys745 (residues 1-68 in C5a numbering) and the penultimate hC5a-A8 residue, Arg746, could be modelled in one of the four molecules related by NCS in the asymmetric unit on C atoms and all atoms, respectively, between all four NCSrelated molecules (residues Thr678-Lys745).