dataesr/scientific-paragraphs-categorization huggingface dataset:
Data analysis The knock-down times for 50 and 95 % (KDT 50 and KDT 95 ) mosquitoes during exposure to insecticide impregnated papers in susceptibility tests were estimated using a log-time probit model  [27]. The log-probit analysis was performed using the WIN DL (version 2. 0, 1999) software. The KDT 50 recorded from fieldcollected mosquitoes were compared with that of the Kisumu reference susceptible strain of An. gambiae by estimates of KDT 50 Ratios (KDT 50 R). The minimum plausible Resistance Ratio (RR) was estimated based on lethal concentration for 100 % mosquitoes of the Pitoa samples and that of the Kisumu susceptible samples as followed: RR = LC 100 Pitoa/LC 100 Kisumu. Bio-efficacy of mosquito nets was estimated by means of mosquito knock-down rates 60 min post exposure to treated-nets (KD 60min ) and mortality rates 24 h post exposure via cone test.
EXPERIMENTAL PROCEDURES Crystallization and Data Collection Initial screening of Pds5T and Pds5T-Scc1 was performed by the EMBL Grenoble HTX laboratory. Pds5T was first crystallized in 0. 1 M MES (pH 6) and 1. 6 M ammonium sulfate. Crystals from which data were collected grew in 1. 5 M lithium sulfate, 0. 1 M MES (pH 6. 5), grown at 4 C, using manually set hanging drops and vapor diffusion and were cryoprotected in a solution containing 2 M lithium sulfate and 0. 1 M MES (pH 6. 5). The Pds5T-Scc1 complex first crystallized in 0. 1 M MES (pH 6. 5), 15% MPD. Pds5T-Scc1 crystals were manually refined and were directly flash-frozen in liquid nitrogen without additional cryoprotectant prior to data collection. Diffraction data for native and selenomethionine-derivatized Pds5T-Scc1 were collected at 100 K at an X-ray wavelength of 0.
5% and 29. 8%, respectively. No electron density was observed for residues 610-623 in Pds5. The register of Scc1 was verified by an anomalous difference map, generated from diffraction data collected from a selenomethione-labeled Scc1 L128M mutant. Analysis of the refined structure in MolProbity showed that there no residues in disallowed regions of the Ramachandran plot. The MolProbity all atom clash score was 5. 77, placing the structure in the 100 th (best) percentile of structures (n = 97) refined at comparable resolution  (Chen et al. , 2010). The structure of apo Pds5T was determined by molecular replacement with Pds5T 3-697, at a resolution of 5. 8 A ˚in space group I422. The initial model was used as both a starting and reference model for subsequent Deformable Elastic Network (DEN) refinement using CNS over a grid-enabled web-server hosted by SBGrid  (O'Donovan et al.
Data collection A semi-automated, anonymous record linkage was carried out in October 2014 by means of a previously validated record linkage procedure  [18]. We linked the database of the seroprevalence study and the database of the population-based CCR. HCC at CCR were identified according to International Classification of Diseases, 10th revision  [19]  and International Classification of Diseases for Oncology (ICDO, C22. 0-C22. 9 codes)  [20]. Individual data regarding the occurrence of new HCC diagnoses and vital status were updated to December 2012 (last date of cancer registration). Serum alanine transaminase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (γGT), and platelets counts were measured at enrolment with upper normal limits (UNL) of 40 U/L for AST and ALT; and 30 U/L for γGT  [11].
Statistical analysis Person-years (PY) at risk of HCC were computed from date of testing to date of HCC diagnosis; date of death or December 31, 2012, whichever occurred first. Incidence rates (IR) of HCC were computed by dividing the number of new cancers by PY at risk. The association between selected variables, collected at time of testing, and the occurrence of HCC at follow-up was estimated by using the Cox multivariable regression analysis through the calculation of hazard ratios (HR) and 95 % CIs adjusted for sex, age, HBV and HCV infection. The probability of surviving according to HCV infection was computed according to the Kaplan-Meier method  [21]. All statistical analyses were performed using commercially available software (SAS Institute Inc. , version 9. 4, Cary, NC, USA; and STATA version 13, StataCorp LP, College Station, Texas).
Results The 4492 cohort members included in this study (44. 7 % men) had a median age of 45. 7 years (interquartile range -IQR: 30. 5-60. 3 years), and they had been followed up for a median period of 8. 0 years (IQR: 7. 2-8. 6 years). The median time from testing to HCC diagnosis was 37 months, while the median age at HCC diagnosis was 73. 3 years (data not shown). Twenty-two cohort members developed HCC during the 34,749 PYs of follow-up: two were anti HCV-negatives and HBsAg-negatives; 15 were HCV RNA-positives; three were anti HCV-negatives and HBsAg-positives; and two were anti HCV-positives/HCV RNA-negatives and HBsAgnegatives. Table  1  shows IRs and multivariate HRs for HCC according to selected characteristics collected at baseline. Overall, the IR of HCC was 63. 3 cases/10 5 PY, and the cumulative incidence at the end of the follow-up period was 0.
1 ms and the signal of a single point was acquired at the echo maximum. Data were averaged over 64 acquisitions. The number of successive echoes recorded was adjusted for each sample according to its T 2. The recycle delay for each sample was adjusted after measurement of the T 1 with a fast-saturation-recovery sequence. The total time of acquisition of data for T 2 (including spectrometer adjustments and T 1 measurement) was about 10 min per sample. Fitting of the CPMG signal was performed using Scilab software according to the MEM  (Mariette et al. 1996) , which provides a continuous distribution of relaxation time components without any assumption concerning their number. In this representation, the peaks of the distribution are centered at the corresponding most probable T 2 values, while peak areas correspond to the intensity of the T 2 components.
Light microscopy For microscopy studies, mesophyll tissues from the leaves studied were collected from control and stressed plants of both genotypes. For each of the four conditions, one mature (leaf rank 0) and one senescent (lowest leaf rank available) were sampled and three to five bands 3-mm wide and 1-cm in length were cut perpendicularly to the central vein. This protocol has been applied on two biological replicates. The leaves were included as described by  Sorin et al. (2015). From each band, thin Sects. (1 µm) were cut with an ultramicrotome (LEICA RM 2165) and stained with toluidine blue before they were observed with a NIKON Eclipse 80i microscope. The numerical results of each leaf analyzed resulted from about 400 cells (200 per parenchyma) observed from 4 to 10 images. Image J software was used for the analyses of the micrographs.
The impact of the N stress on the leaf structure pattern evolution was observed before the changes in physiological parameters could even be measured, supporting the previous finding that leaf structural changes are an early event of the senescence process. The differences in yield between the two genotypes indicated a link between modifications of leaf tissue structure and the remobilization processes. Further studies will focus on mechanisms linked to these leaf structural changes that promote N and C remobilization and their effects on seed yield. A step further will also be to evaluate the NMR relaxometry for assessment of the effects of N depletion on senescence for genotypes screening for better response to such abiotic stress. Authors' contributions CS, LL, MC, AB, FM and MM carried out through cooperative work all the experiments presented in this paper, participated to data analysis and drafted the manuscript.
Acknowledgements We thank the  Regional Council of Bretagne  for financial support. This work was supported by the program " Investments for the Future"  (project  ANR-11-BTBR-0004  "RAPSODYN"). We also thank the  Genetic Resources Center (BrACySol, BRC, UMR IGEPP, INRA Ploudaniel, France)  for providing the seeds of.
These mutant collections are available in several laboratories around the world: CSIRO in Australia  [13] , NIAS in Japan  [14] , OSTID in Europe  [15] , OTL in France  [16] , POSTECH  [17]  and PMBBRC  [18]  in Korea, RMD in China  [19] , TRIM in Taiwan  [20] , and UCD in USA  [21]. These mutant collections contain insertion lines created with T-DNA, Tos17, Ds, and dSpm inserts mutagens and the engineered mutagens may additionally carry gene traps, enhancer traps and/or activation tags. They have been generated in different cultivars: Nipponbare (NB), DongJin (DJ), HwaYoung (HW), Zhonghua 11 (Z11), Zhonghua 15, Tainung 67 (TNG) and Kitaake. All these lines are listed based on their flanking sequence tags (FSTs) in two databases: RiceGE (http://signal. salk. edu/cgi-bin/RiceGE) and Ory-GenesDB (http://orygenesdb.
Plant material and genotyping Accession numbers of the mutant lines to be genotyped were defined on OryGenesDB (http://orygenesdb. cirad. fr/). Seeds were ordered to OTL, NIAS, Postech, RMD, and TRIM. Upon receipt, when available, 15-20 T1 or T2 seeds were sown in the greenhouse (28 • C, 60% humidity, 16:8 photoperiod). Some of these mutant lines have been genotyped by Southern blotting as described previously  [51] , others by a quick direct PCR method following manufacturer instructions (Phire ® Plant Direct PCR Kit, Finnzymes). For Southern blots, genomic DNA was extracted from leaves of 4 week-old plants. Briefly, tissues were freeze-dried overnight and disrupted the next day with a mixer mill. Powder was mixed with extraction buffer (Tris-HCl 200 mM (pH 7. 5), EDTA 25 mM (pH 8. 0), 0.
More than 90% of the LRR-RLK genes are putatively tagged by one insertion in international collections In this study, we used the method we described previously to establish our LRR-RLK gene set  [53]. Briefly, the hmmsearch program was run to extract peptide sequences containing both LRRs and a kinase domain (data not shown)  [54]. We ran the program on the MSU version 7. 0 of the Nipponbare genome and compared our gene list with the one published previously  [25, 47, 48]. We kept a list of 316 LRR-RLK genes considered for mutant analysis (Suppl. Table  1 ). These genes are unequally distributed on the 12 chro- mosomes, with chromosomes 2, 6 and 11 comprising ∼40% of the 316 genes (Table  2 ). Moreover, many of these genes (140, 44. 3%) belong to 40 tandem duplication clusters. These clusters contain 2 to 13 genes (Table  2  and Suppl.
Acknowledgements This project has been supported by grant # ANR-08-GENM-021  from  Agence Nationale de la Recherche  ( ANR, France ), by  European Commission   FP6  Project no. 015468CEDROME  (Developing drought-resistant cereals to support efficient water use in the Mediterranean area) and by  Generation Challenge Program "Rice Stress mutants " (Reverse genetic systems to validate function of stress tolerance genes). We thank  Pr G. An  and  Ms S. An  ( KHU, Korea ),  Dr M. J. Fan ,  S. M. Yu  and  Y. I. Hsing  ( Academia Sinica, Taiwan ),  Dr C. Wu  and  L. Yan  ( HZAU, China ),  Pr V. Sundaresan  and  Ms K. Galimba  ( UC Davis ) for making available to us seeds of the insertion lines used in this study. The technical assistance of  M. Portefaix ,  C. Chaine ,  R. Michel  and  E. Lorenzini  for seed service and greenhouse supports is greatly acknowledged.
We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) communityoriented database infrastructure and analysis tools. IMPORTANCE The spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine wholegenome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent.
We sequenced 308 S. aureus isolates responsible for invasive infections that were recovered from 186 hospitals in 21 countries across Europe in a 6-month period. We consider three analytical strands: (i) a representative phylogeographic analysis that defines HRCs on a population level, (ii) an analysis of the dynamics of virulence and resistance carried by mobile genetic elements (MGEs), and (iii) an in silico ascertainment of antibiotic resistance encompassing 19 antibiotic compounds of clinical relevance. To underline the added value for public health decision making when WGS data are supplemented with epidemiological metadata collected through structured surveys, we developed a web application (Microreact) that allows easy access and visualization of our data by medical and public health audiences and is available at the project URL (http://www.
One MSSA (green branches) cluster is resolved on the tree but is not geographically restricted. This cluster largely corresponds to spa type t002, and this observation is consistent with our previous work showing that MSSA genotypes are widely distributed across Europe (3). The 13 isolates within the ST225 cluster all contain SCCmec type II elements. Seven of these originate from Germany, six are from the Czech Republic, and the partitioning within the phylogenetic tree coincides perfectly with the country of origin, although some of these isolates originate from areas close to the shared border (e. g. , Ústí nad Labem in the Czech Republic and Grossenhain in Germany are just 122 km apart by road). The data thus point to the border between Germany and the Czech Republic as being a barrier to health care referral practices and thus MRSA spread.
Similarly, the loss of a BlaZ ␤-lactamase-carrying plasmid could explain the three false-negative predictions of penicillin resistance. We also determined the concordance of the antimicrobial susceptibility test (AST) results provided by the European Staphylococcus Reference Laboratories (SRLs), which contributed the isolates to our sample, with the EDL reference data. The SRLs submitted a total of 2,252 AST results. Of these, 2,203 (97. 8%) were concordant with the EUCAST test results (Fig. 2 ; Table  2 ). Thus, it is clear that a small amount of discordance between phenotypic tests can be expected, even when they are carried out by experienced reference laboratories. We note that the degree of discordance between the in silico predictions and the EUCAST data is comparable to the degree of discor- dance between the two sets of phenotypic data.
These data sets should conform to internationally curated standards for sets of genes and mutations that are recognized as key virulence or resistance determinants, and we propose the initiation of internationally curated data sets to act as a gold standard resource for genomic antimicrobial resistance determinants. The establishment of cumulative databases will engender a far richer understanding of the detailed dynamics underpinning clonal emergence and replacement, national and international transmission, and the horizontal transfer of core genes and MGEs. The increasing public health threat from bacterial pathogens is, in large part, down to the ability of these organisms to rapidly adapt through the dissemination of genes and mobile elements. Our best chance of managing these threats in the future is to emulate, as far as possible, this resource and data sharing through the development of international surveillance networks and a common data exchange infrastructure.
aureus reference genomes. The strain names and accession numbers are as follows: 04-02981, CP001844 (  6 ; TCH60, CP002110; TW20, FN433596 (48); USA300_FPR3757, CP000255 (23); USA300_TCH1516, CP000730  (49). Detection of SNPs in the core genome. The paired-end reads for the survey isolates and the 26 publicly available genomes were mapped with SMALT (http://www. sanger. ac. uk/resources/software/smalt/) against the chromosome of S. aureus strain HO 5096 0412 (EMRSA-15, ST22; accession number HE681097)  (8). The reference genomes were mapped by using simulated paired fastq data (54-bp paired ends with a 300-bp insert). SNPs were identified as previously described  (50). Indels were identified with the Genome Analysis Toolkit (https://www. broadinstitute. org/ gatk/)  (51). Unmapped reads and sequences that were not present in all of the genomes were not considered part of the core genome, and SNPs from these regions were not included in the phylogenetic analysis.
IVc IVk* IVk* IVk* IVk* IVk* V IV IV II II IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh IVh III III III III III III III III I IVa IVa IVa IVc IVc IVc IVc IVc IVc IVc IVc IVc IVc IVc IVc IVc IVc  ACKNOWLEDGMENTS D. M. A. , C. Y. , and A. F. were supported by  Wellcome Trust  grant  099202  and by  The Centre for Genomic Pathogen Surveillance  (R. G. ). J. D. , S. D. B. , J. P. , and M. T. G. H. were supported by  Wellcome Trust  grant  098051. B. G. S. was supported by  Wellcome Trust  grant  089472. S. C. -R. was funded by  UKCRC  grant  MRC G1000803. We thank the diagnostic laboratories across Europe that contributed their isolates during the structured surveys and whose efforts are crucial to the identification of HRCs and understanding of their spread through European populations.
Follow-Up for Cancer Incidence and Vital Status Incident cancer cases were identified using population cancer registries in Denmark, Italy, the Netherlands, Spain, and the United Kingdom. In France, Germany, and Greece, cancer cases were identified during follow-up from a combination of sources including health insurance records, cancer and pathology registries, and active follow-up directly through study participants or their next of kin. The end of follow-up for the current study was defined as the latest date of complete follow-up (of whole cohort) for both cancer incidence and vital status; this ranged from December 1999 to June 2003 for centres using registry data and from June 2000 to December 2002 for centres that used active follow-up procedures. Colorectal cancer cases were defined using the tenth revision of the International Classification of Diseases (ICD-10) and the second revision of the International Classification of Diseases for Oncology (ICDO-2).
Experiments were performed according to the Declaration of Helsinki and were approved by the hospital 0 s ethics committee. Peripheral blood samples were collected on EDTA tubes. Pure DNA was obtained using the QIAamp DNA blood Midi kit (Qiagen) according to the manufacturer 0 s instructions. The coding exons and intron-exon junctions were amplified with specific primers as previously described  (Vargas-Poussou et al. 2006). Direct sequencing was performed using the dideoxy chain termination method on an automated Perkin Elmer/Applied Biosystems (Foster City, CA). DNA mutations were identified using Sequencher software by comparison to ATP6V0A4 and ATP6V1B1 genes reference sequences: NM_130841 and NM_001692. Each mutation was confirmed by sequencing a second independent PCR product. Missense and splicing mutations were interpreted with Alamut V.
2. 5. 1 software (Interactive Biosoftware, Rouen, France; http://www. interactivebiosoftware. com). Complementary analyses were performed with SIFT (http://sift. jcvi. org/), PolyPhen-2 (http://genetics. bwh. harvard. edu/pph2/index. shtml), Mutpred (http://mutpred. mutdb. org/about. html), SNPs&Go (http://snps-and-go. bio comp. unibo. it/snps-and-go/info. htm), and mutation taster (http://www. mutationtaster. org/).
Quantitative multiplex PCR of short fluorescent fragments We adapted the Quantitative multiplex PCR of short fluorescent fragments (QMPSF) method  (Houdayer et al. 2004 ) to detect large deletions or duplications at the ATP6V0A4 gene. QMPSF consists of a fluorescent multiplex PCR that permits simultaneous amplification of multiple short exonic fragments under semiquantitative conditions. In each QMPSF, a fragment from the hydroxymethylbilane synthase (HMBS) gene was amplified as an internal control in each one of three multiplex reactions. After the PCR, the 6FAM-labeled amplicons are separated by capillary electrophoresis on an ABI Prism 3730XL DNA Analyzer Sequencer (Applied Biosystems). Data were analyzed using GeneMarker Software version 1. 85 (Applied Biosystems). For each patient, the mean value of each amplicon was obtained by comparing the peaks between the patient and a reference sample.
Indeed, they affect highly conserved amino acids and are predicted as pathogenic by all the in silico tools; in addition, they have a low frequency in ExAC database. A detailed classification of these variants is given in Table  S2. Concerning the large deletion of exons 18-21, to the best of our knowledge, this is the second description of a large rearrangement implicating this gene. Miura et al. described a deletion of exon 15 and a deletion of exons 1-8  (Miura et al. 2013). ATP6V0A4 mutations were found in one infant and three children without SNHL, and in one teenager and one adult with SNHL confirming the phenotypic variability in this trait. SNP haplotype analysis suggests that mutation p. Asp411Tyr, detected in four Mexican families, is a founder effect. Indeed, patients carrying this mutation shared the same haplotype (CTC) at the disease locus (Fig.
Acknowledgments We thank patients and families for their valuable participation. This work was supported by grant  IN214316   Programa de Apoyo a Proyectos de Investigacion e Innovacion Tecnologica  (PAPIIT; DGAPA,UNAM), Conacyt Grant  166913  and  253586 ,  Fondos Federales Hospital Infantil de Mexico ,  HIM/2012/036  and  Fundacion para la Acidosis Tubular Renal Infantil Mexicana AC  www. acidosistubular. unam. mx.
Crohn's disease (CD) is a chronic inflammatory bowel From the electronic database of the Pathology Department of the University Hospital Estaing of Clermont-Ferrand, France, we identified 205 patients who underwent an intestinal resection for CD, between 1986 and 2015, at the Institution. Only CD patients with a follow-up of at least 6 mo were considered for the study. Clinical, biological, pathological and endoscopic data were retrospectively collected from medical records (Table  1 ). As we aimed to be close to the real-life practice, we chose to include all the types of intestinal resection including patients with a definitive ostomy. For the patients with a temporary ostomy, the time point zero was defined as the time of the intestinal resection since we aimed to investigate all the potential factors influencing the time to recur (including type of resection and the presence of temporary or definitive ostomy).
Risk factors of endoscopic POR Among the 161 CD patients included in this study, 102 patients underwent a colonoscopy during their followup. The median interval for endoscopic POR was 2. 0 years (0. 6-3. 6). While 54 patients (33. 5%) received 5-ASA in prevention of endoscopic POR, 40 patients (24. 8%), 7 patients (4. 3%) and 41 patients (25. 5%) Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing (1) an intuitive interface for validated data entry; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for importing data from external sources. Statistical analysis was performed using Stata 13 software (StataCorp LP, College Station, TX, United States).