dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We are grateful to the  French Ministry of Agriculture  for providing us with access to their equine mortality data, to the French horse and riding institute for providing access to the SIRE data and to the  Conseil Regional de Basse-Normandie  ( Z 3751 ) for its financial support. We would also like to thank the staff that manages the SIRE database, the  French  fallen stock companies for data entry,  Anne Praud  for her involvement in the first part of the data analysis work and  Delphine Libby-Claybrough , professional translator and native English speaker, for her review of the manuscript.
Molecular analysis individual-based approach The insects used for molecular studies were placed in absolute ethanol. Only adults and fifth instar nymphs (N5) were used for population genetic analyses to decrease sampling-strategic bias. Because older stages exhibit higher mobility, this strategy decreases the probability of sampling several relatives. Additionally, only populations with N 17 were used to ensure robust inferences. The resulting dataset for insect studies on population genetics was derived from 108 individuals distributed among five populations.
cruzi strains sequences were compared to those from the GenBank database using BLAST procedures. We only selected the best hit for each  search using the cut off values of 95% query coverage and 10 -100 E -value. The name of the putative host was retained at the specific level when the sequence identity was higher than 95%, but only at the genus level when it was in the range of 75-95% especially for the cold-blooded animals because sometimes they do not have an expressive representation in GenBank. For microsatellite genotyping, 108 adults and N5 were used, belonging to A (N = 22), B (N = 17), C (N = 23), D (N = 27) and F (N = 19) populations. The available primers for seven T. brasiliensis loci  [20]  were tested. We also revisited all the sequences with microsatellite inserts from our previous microsatellite-enriched genomic library and designed new primers for three loci (Tb8102, Tb 8150, Tb2146) using OLIGO software (version 4.
0; National Biosciences Inc. ). For each primer set, the optimal annealing temperature was determined using a gradient PCR (MJ Research). In total, eight microsatellite loci were used in this study, because some previously designed  [20]  were monomorphic for our dataset (Table  2 ). PCR amplifications were performed using dye-labeled primer (Applied Biosystem) and for 40 cycles (denaturation at 94°C for 30 s, annealing for 30 s, and extension at 72°C for 30 s; Table  2 ). Microsatellite data were collected on an ABI Prism 3100 (Applied Biosystem) and alleles analyzed using GeneMapper (Applied Biosystem), according to previous study  [20].
Population genetic analyses We used two procedures to confirm the specific status of T. brasiliensis. First, we applied the Automatic Barcode Gap Discovery (ABGD) method  [29] , using Kimura' genetic distances, gap width X = 1, and a set of prior minimum genetic distances ranging from 0. 001 to 0. 1 (http:// wwwabi. snv. jussieu. fr/public/abgd/abgdweb. html). Second, Bayesian inference (BI) was used to reconstruct phylogenetic relationships among unique haplotypes using MRBAYES v3. 1. 2 [30] , with the best-fit substitution model for the data under BI through the Akaike Information Criterion (AIC) determined with jModelTest 0. 1. 1  [31]. We ran 2,000,000 generations using the MCMC algorithm with a burn-in period of 500,000 using a GTR+I+Γ model. The dataset was composed of the sequences obtained in this study in addition to some downloaded from GenBank for members of T.
spixii were less than 1 km. Therefore, the identification of this rodent as vector feeding source is even more relevant. Recently some authors  [63] testing a set of a priori hypotheses about the drivers of site-occupancy by T. brasiliensisshowed that T. brasiliensis was strongly associated with key hosts, including rodents in peridomiciliary environments. In these findings the ecotope structure had small to negligible effects. Our study did not characterize completely the dietary habits of T. brasiliensis because the rate of determination via direct sequencing was limited. In order to have a better representation of the host diversity, metagenomics or metabarcoding approaches using high throughput sequencing (HTS) technology is currently being developed. Additionally, to improve host assignation, the set of sequences deposited in GenBank, including for the fauna of neglected and remote sites, must likewise be improved.
This limitation may have resulted in the low BLAST identity for some taxa not well studied. To exemplify this limitation, a sequence matched (with 79% of identity) an endemic lizard species (Mabuya spinalis) from Cape Verde Islands (Africa)  [64]. This low identity may be a result of feedings on a related reptile species because there are records of occurrence of some other Mabuya sp. in northeastern Brazil  [65]. Therefore, to improve host assignation, it will require the mobilization of taxonomists specialized on vertebrates and the constitution of a broader set of GenBank reference sequences. Because Chagas disease may be also transmitted through contact with hunted animals, as is suggested for the Amazon region in Brazil  [66] , caution is necessary when handling these animals. Moreover, educational campaigns should address this issue.
Infection and feeding source determination. We used two methods to determine Trypanosoma cruzi infection in bugs: direct examination (Dir-Inf) and PCR. Ni, is the number of positive individuals; Nf, the total number of examined individuals. Parasite characterization (TCII/TCI) was determined by PCR (see Materials and Methods). The number of feeding sources detected is indicated and their putative affiliation (putative feeding source) using BLAST searches. The Id (%) represents the identity of the sequences obtained from vector guts with those in GenBank (GB), with the GB code in the last row. Feeding sources detected in vectors infected by T. cruzi via PCR are in bold.
Funding: Financial support was provided by  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)  and  Fundação de Amparo à Pesquisa do Estado de São Paulo  ( FAPESP , process numbers  2010/17027-0  and  2011/22378-0 ), the agreement  CNRS/FIOCRUZ"  (project  24199 ) and the  French Agence Nationale de la Recherche  ( ADAPTANTHROP  project,  ANR-097-PEXT-009 ). The funders had no role in study design, data.
33 ppm in 1 H and to 22. 7 ppm in 13 C. New NMR signals were identified in treated RHE, in comparison to untreated control RHE. Then, 1 H and 13 C chemical shifts were assigned to potential metabolites and/or adducts of MI and MCI with amino acids by comparison with known chemical shifts of adducts obtained in previous studies in solution  (23, 27, 28). Also, the measured chemical shifts were compared with those calculated for suspected structures by using ChemDraw Ultra software (version 12. 0). 13 C-substituted molecules have been shown to be very efficient tools for the investigation of hapten-protein interaction mechanisms in buffered or semi-organic solutions  (29) (30) (31). In order to move forward into the comprehension of chemical interactions taking place in a system closer to that of human skin, we have reported the usefulness of keratinocyte based RHE in association with the high-resolution magic angle spinning (HRMAS) NMR technique  (24).
Scaffolds and contigs were randomly inspected in the genomes of S. bovis and S. haematobium for potential female specific sequences. The CNV-seq method was used to compare coverage between males and females along the genome. The minimum window size was set to 500 bp, log2 ratio to 0. 6 and p-value stringency to 10 -6. S. bovis and S. haematobium reference genomes were used, alternatively, and regions showing specific coverage for females were selected. Consensus candidate sequences were extracted using IGV, and primers were designed using the program Primer3Plus  [28]. In order to confirm specificity, primers were compared (by BLAST) against the genome that they were originally identified in.
Discussion In the present work, we used massive sequencing data from a field S. haematobium x S. bovis hybrid schistosome strain, allowing us to successfully identify 5 female-specific markers on 3 different scaffolds from the draft genome of S. haematobium, thus corresponding to previously unplaced W-specific regions. No sex marker candidates were confirmed by PCR when they were selected based on reads aligned against the genome of S. bovis. Furthermore, we could not locate the female-specific markers originating from the S. haematobium draft genome in the S. bovis genome. This can be explained by the relatively poor quality of the present genome for S. bovis, which emphasises the need to improve the assembly. Despite this, among 5 female-specific sex markers in S. haematobium, 3 can also be used for S.
Renin activity was measured by radioimmunoassay (RIA) with solid-phase-coated tube separation, c ET-1 by ELISA d and cortisol by enzyme-linked fluorescent assay (ELFA). e All samples were analyzed in duplicate by personnel blinded to dog identity, and mean values were used for data analysis. In-house duplicate coefficients of variation (CVs) were: renin activity 13. 8%, ET-1 7. 6%, and cortisol 10. 5%. Interassay CVs were: renin activity < 15%, ET-1 < 10%, and cortisol < 12%. Dynamic ranges were: renin activity 0. 17-3. 40 ng/mL/h, ET-1 0. 39-50 pg/ mL, and cortisol 5. 5-2,759 nmol/L; and limits of detection were: renin activity 0. 010 ng/mL/h, ET-1 0. 23 pg/mL, and cortisol 5. 5 nmol/L.
Therefore, even after accounting for differences in carcass traits, bulls still differ in eating quality when compared with females and steers Breed also influenced eating quality beyond differences in carcass traits. However, in this case, it was only for certain muscles. This should be taken into account when estimating the eating quality of meat. Additionally the coefficients used by the Australian MSA model for some muscles, marbling score and ultimate pH do not exactly reflect the influence of these factors on eating quality in this dataset, and if this system were to be applied to Europe then the coefficients for these muscles and covariates would need further investigation.
Animals and muscle samples The data set was formed through combining the records of animals selected for a number of specific, smaller, experiments. As a result this data set provides acrosssection of European cattle types (Table  1 ). The Polish carcasses were processed at three facilities situated in the north east of Poland. The Irish carcasses were processed at two commercial abattoirs and one pilot scale abattoir. The French carcasses were processed at a single facility in the west of France. The carcasses from Northern Ireland were processed at 5 different facilities distributed across the region. All cattle travelled less than five hours to reach the abattoirs. The cattle were slaughtered commercially according to standard practice in each country. Post slaughter carcasses were either hung by the Achilles tendon or they underwent tender-stretching, indicating they were instead hung by the obturator foramen or the pelvic ligaments.
There was an uneven distribution of cattle and samples amongst the effects controlled for in this study (Table  1, Table 3 ). This distribution within the dataset reflects the differences in beef production/consumption in the different countries. Animal breed was divided into three categories. Beef breeds, dairy breeds and crosses between the beef and dairy breeds. The beef breeds were made up of Angus (6), Hereford (3), Murray grey (19), Shorthorn (2), Belted Galloway (1), Belgian blue (26), Charolais (99), Blonde d'Aquitaine (11), Limousin (48), Montbeliarde (1), Romagnola (1) and Simmental (10). The dairy breeds were made up of Holstein (150), Ayrshire (1) and Normande (4). The cross breeds were crosses between the previously mentioned beef and dairy breeds, with varying percentages of beef and dairy genetics.
Meat quality score (MQ4) Within each country each muscle from each carcass was assessed by 10 individual untrained consumers. The tenderness, juiciness, flavour liking and overall liking values were weighted and combined to create a single MQ4 score. The weightings were calculated using a discriminant analysis, as performed by  Watson et al. (2008)  and are 0. 3*tenderness 0. 1*juiciness 0. 3*flavour liking 0. 3*overall liking. The highest and lowest two scores for each trait and MQ4 score were removed and an average calculated for the remaining six scores. These clipped scores were aligned with the muscle, carcase and animal traits for analysis. There is a high correlation between all four sensory scores with a minimum partial correlation coefficient between any of the scores of 0. 66 calculated on a subset of the data  (Bonny et al.
Statistical analysis Both the actual consumer observed MQ4, and the difference between the actual and the predicted MQ4, from the current MSA model (SP2009), were analysed using a linear mixed effects model (SAS v9. 1). Initially, a base model was established which included fixed effects for carcass hanging method, cooking method, muscle type, sex, country, and breed. Post-mortem ageing period in days was included as a covariate. The samples from Northern Ireland were split into two groups, NI MED, the samples from Northern Ireland from which were prepared to a medium doneness and NI WD, the samples from Northern Ireland from which were prepared well done. These two groups of samples were classed as separate countries in the statistical models, i. e. NI MED and NI WD, therefore encompassing the variation due to the different cooking doneness and negating the need for a cooking doneness term within the model.
Animal identification number within carcass source country, kill group (animals slaughtered on the same day at the same abattoir) and consumer country were included as random terms. Terms in the model and their first order interactions were removed in a step-wise fashion in non-significant. The predicted means for the sexes and breeds were compared using the least significant differences, generated using the PDIFF function in SAS (SAS v9. 1). The degrees of freedom were determined using the Kenward and Rodger technique (SAS v9. 1). For the model with the difference between the actual MQ4 and the MSA predicted MQ4 as the dependent variable, significant effects in the model indicated that the accuracy of the prediction differed between subgroups with numbers further away from zero indicating lower prediction accuracies.
Similarly when marbling score was added to the model as a covariate, the difference between the bulls and the females or the steers increased by approximately 1. 5 MQ4 points (data not shown) suggesting that the distribution of marbling score and pH in this dataset actually masked differences between the sexes and that the coefficients for marbling score and ultimate pH in the MSA model are not adequately describing the influence of these carcass traits on the eating quality of meat from bulls. There was no change in the difference between the females and the steers. No other covariates tested had an effect on sex in the model. Similar to the previous model predicting the Actual MQ4, balanced comparisons for the prediction accuracy of the different breed categories could only be made within subgroups of cooking method and hang method.
Our expectation that both sexes would be predicted with similar accuracy was based upon our assumption that IMF was the factor driving this difference, which would have been accounted for by the marbling score adjustment in the MSA model. Yet contrary to this, a further correction of the MSA prediction accuracy model for either marbling score or ultimate pH actually increased the differences in the prediction accuracy between the sexes. This demonstrates that the distribution of marbling score and ultimate pH within this dataset was actually masking or minimising the differences in prediction accuracy between the sexes. In the absence of differences in IMF driving the differences in eating quality, other factors such as variations in fibre diameter and collagen content could be playing a role  (Boccard et al.
, 1979 , Seideman et al. , 1989 , Chriki et al. , 2013). However these findings indicate that even after accounting for differences in carcass traits bulls still differ in eating quality when compared with females and steers and this would need to be taken into account when estimating the eating quality of meat sourced from bull carcasses. Additionally the coefficients used by the Australian MSA model for marbling score and ultimate pH do not exactly reflect the influence of these factors on eating quality in this dataset. However, as a result of the relatively small subsample of data used in this experiment, additional data is required to properly elucidate the slope of these relationships for European consumers. Within the data there was a suggestion of a reduced capacity of the meat from bulls to improve with ageing (data not shown), which could have resulted from differences in muscular calpastatin activity and rates of protein turnover between the sexes  (Morgan et al.
Acknowledgements This research was supported by  Meat and Livestock Australia and Murdoch University. Data were obtained through the financial contributions of the European research project  ProSafeBeef  (Contract No. FOOD-CT-2006-36241 ), the  Polish ProOptiBeef Farm  to Fork project funded by the  EU Innovative  ( POIG. 01. 03. 01-00-204/09 ), the  French 'Direction Générale de l'Alimentation' and FranceAgriMer , the  Irish Department of Agriculture Food  and  The Marine  under the  FIRM programme , and the  Northern Ireland Department of Agriculture and Rural Development 'Vision' programme. Furthermore , this project would not have been possible without the practical support of the  Association Institut du Charolais , the  Syndicat de Défense et du promotion de la Viande de Boeuf de Charolles  and the gourmet restaurants ' Jean Denaud ' and representatives of the beef industry across Europe.
3. 0. 3. All isolates were pair-end sequenced with 2 x 150bp base reads. Raw sequence data were submitted to the European Nucleotide Archive (http://www. ebi. ac. uk/ena) under study accession no. : PRJEB13610 (http://www. ebi. ac. uk/ena/data/view/ PRJEB13610). The raw reads were assembled using the Assemble pipeline (version 1. 0) available from the Center for Genomic Epidemiology (CGE) http://cge. cbs. dtu. dk/services/all. php, which is based on the Velvet algorithms for de novo short reads assembly. A complete list of genomic sequence data is available in the S1 Table. The assembled sequences were analyzed to identify the MLST sequence type (ST) for Salmonella enterica based on the publication by Jolley KA et al. , 2010  [8]. In addition, plasmid replicons, pMLST, and acquired antimicrobial resistance genes using the pipelines MLST (version 1.
7), PlasmidFinder (version 1. 2), pMLST (version 1. 4), and ResFinder (version 2. 1) available from CGE  [9] [10] [11]. Single Nucleotide Polymorphisms (SNPs) were determined using the pipeline CSI Phylogeny (version 1. 1) available from the CGE website  [12]. Basically, each of the raw reads was aligned against the genome of strain #2 due to the lack an appropriate reference genome, using Burrows-Wheeler Aligner (BWA) version 0. 7. 2  [13]. SNPs were called using 'mpileup' module in SAMTools version 0. 1. 18 [14]. SNPs were selected based on both coding and non-coding regions and when they met the following criteria: 1) a minimum distance of 15 bps between each SNP (e. g. to exclude homopolymer-rich regions), 2) a minimum of 10% of the average depth, 3) the mapping quality was above 30, 4) the SNP quality was more than 20 and 5) all indels were excluded.
, 2011). As well as a global approach, it may also allow identification of precise aspects of posture that could be useful and should be be more thoroughly examined. For example, the global approach identified neck shape as a major issue, and a correlation between neck A c c e p t e d M a n u s c r i p t shape and back disorders was revealed  (Lesimple et al. , 2012). The method uses free software (tps, http://life. bio. sunysb. edu/morph/) that allows automatic calculation of the shape of animals. In the present study we used geometric morphometrics, based on the method of  Fureix et al. (2011) , to assess potential variations of body posture in relation to rearing conditions in pigs, i. e. individual vs. group housing. The rearing environment influences pig behaviour and emotional state: social isolation is known to induce a high level of stress compared to group rearing, indicated by behavioural, endocrine and immune changes  (Barnett et al.
Preparation of the photographs and shape description Two landmarks could not be used: Landmark 1 because its position was not homogeneous due to movements of the pigs; Landmark 3 because it was often hidden behind the ear. We selected 1083 photographs that fitted two criteria. The animal had to be perpendicular to the camera, with the five remaining landmarks visible. Pictures of an animal moving to the right were reversed horizontally so that in all pictures the head of the pig was on the left. Shape was then described using Tps software (http://life. bio. sunysb. edu/morph/) following the method of  Fureix et al. (2011). Landmarks were digitised by one trained experimenter via "tpsDig2" positioning the landmarks on a grid to obtain their coordinates. Then files were loaded into "tpsUtil" to define the links between landmarks and create the shape, and the links file saved.
Acknowledgements This project was partially funded by a grant from Rennes 1 University (Projets émergents) and was made possible thanks to scientific meetings of the GIS CCS (Groupement d'Intérêt Scientifique, Cerveau-Comportement-Société). The authors are grateful to Patrice Roger, Jérémy Rissel, Vincent Piedvache, Fabien Guérin, Kardiatou Sy, Carole Guérin, Michel Lefèbvre and Sylvie Guérin for their participation in different phases of the experiment. We thank the ISAE and Mike Appleby, who kindly edited for readability and for correct English the revised manuscript.
Phylogenetic analyses and genetic diversity Accessible sequences from clinical Leptospira isolates from Mayotte were included in the study  [15]. Since icdA sequences were not provided for these clinical isolates, we used five out of the six markers of the MLST scheme in our analyses. In addition, we added bacterial sequences obtained from endemic terrestrial small mammals from Madagascar, Microgale cowani, Microgale dobsoni, Microgale majori, Microgale longicaudata and Microgale principula (Family Tenrecidae, Subfamily Oryzorictinae). The complete MLST of these Leptospira strains were sequenced in a previous study  [4]  and from cultures realized during field missions carried out in the Central Highlands of Madagascar, Réserve Spéciale d'Ambohitantely, in March and October 2014  [16]. Phylogenetic analyses were performed on each gene separately and subsequently on concatenated sequences using the best model of sequence evolution determined by jModelTest v.
0. 1. 1  [17]  for each dataset. Bayesian analyses were performed with MrBayes 3. 1. 2 [18]  and consisted of two independent runs of four incrementally heated Metropolis Coupled Markov Chain Monte Carlo (MCMCMC) starting from a random tree. MCMCMC was run for 10,000,000 generations with trees and associated model parameters sampled every 100 generations. The convergence level of each phylogeny was validated by an average standard deviation of split frequencies inferior to 0. 05. The initial 10% of trees from each run were discarded as burn-in and the consensus phylogeny along with posterior probabilities were obtained from the remaining trees. Bayesian trees were visualized and rooted to midpoint with FigTree v. 1. Genetic diversity was compared between the identified clades in the multilocus phylogeny by estimating the nucleotide diversity (π) within each clade from the concatenated sequences using DNASP v.