dataesr/scientific-paragraphs-categorization huggingface dataset:
Although pain related facial expressions cannot be completely suppressed by voluntary control (e. g. in humans,  (Williams, 2002) ), studies on horses  (Torcivia and McDonnell, 2020)  and rabbits  (Pinho et al. , 2020 (Pinho et al. , , 2023) )  have demonstrated that in the presence of a human the animals displayed less in facial expression of pain or discomfort behavior than when the human was not present. Therefore, the human presence in our study may have prevented cows from displaying facial expression of pain. Third, we used the data from one observer (Obs1) to check FAU's expression and selectivity (through construct validity and responsiveness), and to evaluate Specificity and Sensitivity. Data from Obs1, Obs 2 and Obs 3 were used only to test intra-observer reliability (repeatability) and inter-observer reliability (reproducibility).
Acknowledgements This work is part of the  LongHealth  project that received financial support from  INRAE (GISA [Gestion Intégrée de la Santé Animale] metaprogram) , and from  Conseil Régional Auvergne-Rhône-Alpes  ( CPER 2015-2020   PhD grant ). The NSAID used was kindly supplied by  CEVA Santé Animale. The authors thank  Charlotte Bagnard  for her help with video-recording,  Eric Delval  and  Cecilia Brooks  for coding the videos,  Romain Lardy  for his precious help with pain threshold definition,  Marie-Laure Delignette-Muller  for her advices in statistics,  Isabelle Rautenbach ,  Gilles Foucras  and  Pierre Germon  for their help throughout the project, and  Caroline Boulocher  and  Didier Pin  for their help with cattle facial anatomy. We also thank  Metaform  for valuable Englishlanguage proofing support.
Microbiota analysis Fecal microbiota was analyzed by 16S rRNA gene sequencing as described before  [10]. Briefly, DNA was extracted from fecal samples using Quick-DNA Fecal/ Soil Microbe 96 Kit (ZymoResearch, Irvine, CA) and PCR amplicons of the V3-V4 region were sequenced by MiSeq Illumina Sequencing. Reads were deposited in the National Center for Biotechnology Information Sequence Read Archive (SRA accession: PRJNA881232). Sequences were analyzed with the 'FROGS' bioinformatic pipeline, following the standard guidelines  [33]. Amplicons were selected based on their size (350 -500 nucleotides). Clustering was performed with Swarm using an aggregation distance of 1. Chimera was removed and operational taxonomic units (OTUs) with an abundance lower than 0. 005% of the total of sequences were excluded.
Calculations and statistical analysis The ADG (g/day) and ADFI (g/day) were calculated from the BW gain and the feed consumption, respectively. Feed conversion ratio was calculated as the feed-to-gain ratio (kilogram of feed consumed per kilogram BW). Statistical analyses were carried out separately for each period using the SAS software (version 9. 3, SAS Inst. Inc. , Cary, NC). The presence of outliers was evaluated through the residual analysis of data and by daily records of anomalies. Through UNIVARIATE procedure, Box-Cox and Shapiro-Wilk tests were used to check homogeneity of the variances and normality of the studentized residuals, respectively. The data were analyzed using linear mixed effects models (MIXED procedure) and were presented as least squares means and pooled residual standard errors.
10 was discussed as a trend. The microbiota analysis was performed using the R software (version 4. 2. 0) with the phyloseq package (version 1. 40. 0). Bray-Curtis distances were calculated on the rarefied count matrix and analyzed with PERMANOVA. Microbiota richness, Shannon, and Inverse Simpson α-diveristy indexes were calculated on the rarefied count matrix. When the relative abundance was lower than 0. 05%, the OTUs were removed from the statistical analysis. Microbiota richness, Shannon and Inverse Simpson α-diveristy indexes and bacterial abundances at the phylum, family and genus levels were analyzed by ANOVA with linear mixed models including the fixed effects of experimental diet, sex and their interactions. Random effects included the litter, the pen and the repetition. Bacterial relative abundances were square root transformed before analysis.
Study population Blood and serum samples of cats (n = 600) were included in the study, as part of a multicenter survey on feline leishmaniosis. One hundred cats per each geographical region (i. e. , France, Greece, Israel, Italy, Portugal and Spain) with a history of regular outdoor access (preferably colony or stray cats), not treated with ectoparasiticides or repellents in the previous 6 months, and with clinical-pathological information were primarily included in this study. Data on the animals, including signalment (i. e. , age, sex, breed), housing conditions and geographical provenience, were recorded at the enrollment (Table  1 ). Health status and laboratory parameters, including complete blood cell count (CBC) and serological biochemical parameters (Creatinine, Urea, Alanine-aminotransferase, Albumin, Total proteins, Total globulins and A/G ratio), were recorded when available (Table  2 ).
Amplified PCR products were visualized by gel-electrophoresis in 2% agarose gel containing GelRed nucleic acid gel stain (VWR International PBI, Milan, Italy) and viewed on a GelLogic 100 gel documentation system (Kodak, New York, USA). The positive PCR products were purified and sequenced in both directions using the same forward and reverse primers, employing the Big Dye Terminator v. 3. 1 chemistry in a 3130 Genetic analyzer (Applied Biosystems, California, USA) in an automated sequencer (ABI-PRISM 377). Nucleotide sequences were edited, aligned and analyzed using the Geneious platform version 9. 0 (Biomatters Ltd. , Auckland, New Zealand)  (Kearse et al. , 2012) , and compared with available sequences in the GenBank database, using the Basic Local Alignment Search Tool (BLAST; http:// blast.
Phylogenetic analysis Phylogenetic analysis was based on 471 bp of the 18S rRNA gene sequences of Hepatozoon spp. detected in the study and those available from the GenBank database. Phylogenetic relationship was inferred by the Maximum Likelihood (ML) method based on Tamura's 3-parameter model  (Tamura, 1992)  and Gamma distribution used to model evolutionary rate differences among sites (+G) selected by best-fit model  (Nei and Kumar, 2000). Evolutionary analyses were conducted on bootstrap replications using the MEGA X software  (Kumar et al. , 2018).
Statistical analysis Exact binomial 95% confidence intervals (CIs) were established for proportions herein found. A Chi-squared test (χ2) was used to assess any statistical association among TBP infection and signalment data, outdoor activity, geographical origin, health status and laboratory parameters. A p-value (p) less than 0. 05 was considered significant. Odds ratios (ORs) were calculated to assess the infection risk according to the several variables (i. e. , age, sex, breed, housing condition and geographical provenience) of the participants. The 95% CIs, chi-square, p-value and OR values were calculated by using the software Epitools -Epidemiological Calculators  (Sergeant, 2018).
Results The overall prevalence of Hepatozoon spp. infection was 14. 5% (87/ 600, 95% CI: 11. 9-17. 5), and was significantly higher in cats from Greece (30%, 95% CI: 21. 8-39. 6) and Portugal (23%, 95% CI: 15. 7-32. 2), followed by Spain (15%, 95% CI: 9. 2-24. 4), Israel (15%, 95% CI: 9. 2-24. 4) and France (4%, 95% CI: 1. 2-10. 6). All cats from Italy scored negative (Fig. 1 ). Hepatozoon felis was identified in 86 cats and H. silvestris in one shelter cat from Portugal. No co-infections and no DNA of piroplasmids were detected. The phylogenetic relationships are depicted in Fig. 2  with three sequence types of H. felis, submitted to GenBank under accession numbers OP144204 for ST1, OP144205 for ST2 and OP144206 for ST3, clustering with those feline sequences available in this database, regardless of their geographical provenience and host species.
Materials and methods The habitat use sequences were obtained from roe deer movement trajectories of the Eurodeer database  (Urbano and Cagnacci, 2021)   S1. 2 for a description of each population). Because we were interested in modelling seasonal variations in day-night alternation, we removed individuals which had less than 10 biweekly habitat use sequences. Our final dataset consisted of 3900 habitat use sequences from 154 animals (95 females and 59 males, made up of 44 juveniles/yearlings and 132 adults, with 22 animals switching from fawns to adults during monitoring; Table  S1. 2).
Acknowledgments This paper was conceived and written within the  EUROMAMMALS/EURODEER collaborative project  (paper no. 017  of the EURODEER series; https:// www. eurod eer. org). The co-authors are grateful to all members for their support to the initiative. We thank all the field assistants that contributed to the collection of the data in the field. The EUROMAMMALS spatial database is hosted by  Fondazione Edmund Mach. We are grateful to the  Copernicus  project for the use of free data (European Union, EEA - European Environment Agency ). Here we confirm that all conditions are met for free, full and open access to this data set, established by the  Copernicus data and information policy Regulation (EU)  No  1159/ 2013  of  12 July 2013.
Molecular species identification of Schistosoma spp. cercariae DNA was prepared from individual cercariae stored on the Whatman FTA cards, using the alkaline elution method, as previously described  (Webster et al. , 2015). Six cercariae were analysed from each snail. Individual cercariae were characterised using three molecular markers: a partial region of the mitochondrial cox1 gene, the nuclear rDNA (ITS1-5. 8S-ITS2) region and a partial region of the 18S rRNA gene, to determine the species of Schistosoma or hybrid status of each cercaria as described in  Pennance et al. (2020). Sequence identity from trimmed and manually edited data were confirmed by comparison to reference data  (Webster et al. , 2010). Following successful sequencing and analysis, the mitochondrial (cox1) and nuclear (ITS þ 18S rDNA) profiles were asigned to each cercaria to determine species or hybrid status.
Results and discussion From the 98 Bulinus snails collected from the study area, 62 were morphologically identified as B. senegalensis and 36 as B. umbilicatus. Of these a single snail of each species shed Schistosoma spp. cercariae (Fig. 1 ). The morphologically identified B. senegalensis (Fig. 1D  and E ) was molecularly confirmed as B. senegalensis (GenBank: OP779241), with 99. 32% mitochondrial cox1 similarity to published sequences from B. senegalensis sampled in Senegal (GenBank: MW167056) (Fig. 2 ). The morphologically identified B. umbilicatus snail showed clear morphological features matching this species as detailed in  Brown (1994) , with a broadly reflexed columella lip (Fig. 1A ) and large umbilicus (Fig. 1B ). However, a comparison of our B. umbilicatus cox1 sequence and those published by Zein-Eddine et al.
(2014) (GenBank: KJ157490 and KJ157491) revealed that sequences were extremely divergent. Further analysis of the data from Zein-Eddine et al. (2014) (GenBank: KJ157490 and KJ157491) suggested that the published sequences were not from a species of Bulinus but from an annelid, and therefore, should not be used as reference data for B. umbilicatus. We further confirmed the validity of our B. umbilicatus cox1 sequence data through comparison with independently collected Bulinus specimens from Bandafassi, Senegal (Ruben Schols and Tine Huyse, personal communication). The partial ITS sequence of our B. umbilicatus (720 bp) was therefore also analysed further confirming the sequence identity as a species of the Bulinus africanus species group  (Brown, 1994) , and so we provide novel molecular data for B.
umbilicatus (GenBank: OP779242 (cox1) and OP778350 (ITS)). (Kane et al. , 2008; Zein-Eddine et al. , 2014; Zhang et al. , 2018; Pennance et al. , 2020). The haplotype network shows clear species divergence for B. globosus, B. truncatus, B. senegalensis and B. umbilicatus. The unlabelled circles represent unsampled haplotypes; the hatch marks on the connecting lines indicate the number of mutational steps between haplotypes. The cercariae shed from the B. senegalensis, were molecularly confirmed as S. haematobium (GenBank: OP779237), S. bovis (GenBank: OP779238) and S. haematobium-S. bovis hybrids (GenBank: OP779239), with the hybrids presenting a S. bovis mitochondrial/S. haematobium nuclear DNA profile. For the infected B. umbilicatus, all of the cercariae were identified as S. haematobium (GenBank: OP779240) with all of the S.
Acknowledgments We would like to thank  Ruben Schols  and  Tine Huyse  ( Royal Museum for Central Africa ) for their discussions and the sharing of unpublished sequence data related to the identification of B. umbilicatus in the present study. We also thank  Dr David Rollinson  for help in proofreading the final manuscript draft and the  Schistosomiasis Collection at the NHM (SCAN)  project team members ( Dr Aidan Emery ,  Dr Fiona Allan  and  Muriel Rabone ) for curation of the samples at the NHM. SCAN was funded by the  Wellcome Trust  grant number  104958/Z/14/Z.
32-mm internal diameter, 0. 25-μm film, reference 19654; ALLTECH Associates Inc. , Templemars, France), using the Chromeleon software (Thermo Fisher Scientific, Courtaboeuf, France). FA identification was made referring to known FA profiles obtained from injection of standard FAME (FA methyl esters) mix (Supelco 37 components FAME mix, ref 47885-U, Sigma). Quantitative profiles were established for each sample whereas qualitative profiles were expressed as % of total FA. In the results, data are expressed after normalization to total FA in the sample.
Differential Analysis There were no significant differences in live weight between groups that have been compared at the same lactation stage nor within groups at different stages. Similar results were obtained for BCS and for ADG. Since weight, BCS and ADG are colinear, only live weight after foaling was finally considered as a cofactor in the models. For all qualitative measurement, colostrum and milk were analyzed independently. For measurements in colostrum, linear models were performed with mare live weight 24 hours after foaling and group as fixed effects. Permutation tests were applied as data were not normally distributed using pgirmess package  [34]. Results of these analyses were presented. Linear mixed models were performed using nlme package  [35]  to evaluate differences in M2 yield and quality.
According to the comparison (age, OM vs. YM; parity, YP vs. YM; lactation, NOM vs. OM), M2 yield, foal ADG and all significant qualitative milk measurements were graphically represented using the median and the interquartile range for each lactation day studied with GraphPad Prism software 8. 0. 1 for Windows (Graphpad Software, San Diego, CA, www. graphpad. com ).
Acknowledgments The authors are grateful to the staff of the  Institut Français du Cheval et de l'Equitation (IFCE) experimental farm  ( Plateau technique de la station expérimentale de Chamberet, Chamberet, France ) for care and management of animals. The authors thank the " Institut Français du Cheval et de l'Equitation " (grant numbers  CS_2018_23 ,  2018 ) and the  National Research Institute for Agriculture, Food and Environment (INRAE) department Animal Physiology and Breeding Systems  for funding this research.
PLOS NEGLECTED TROPICAL DISEASES High Sensitivity Assay Kit (Life Technology, Villebon-sur-Yvette, France). Genome sequencing was conducted combining the Oxford Nanopore GridION (Oxford Nanopore Technologies, Oxford, UK) and Illumina Miseq (Illumina, San Diego, CA, USA) sequencing platforms. Illumina and Nanopore sequencing reads were quality-controlled using FastQC (v0. 11. 5) software (Babraham Bioinformatics-FastQC A Quality Control tool for High Throughput Sequence Data)and NanoPlot (version 1. 19. 0)  [14] , respectively. Adapter sequence and lowquality bases were removed using Trimmomatic (v0. 39)  [15]  for Illumina data and porechop (v0. 2. 4)  [16]  for Nanopore reads and sequences < 1,000 bases for Nanopore reads were removed using filtlong (v0. 2. 1) (settings, min = 1000, K = 90)  [17].
Clean Nanopore and Illumina reads were combined by a hybrid assembly approach using Unicycler (v0. 5. 0)  [18]. De novo assembly graphs were visualised using Bandage v0. 8. 1  [19]. Contigs were combined into a single molecule using the online Fasta dataset joiner (http://usersbirc. au. dk/biopv/php/ fabox/fasta_joiner. php)  [20].
Genome annotation and comparative genomics The quality and contiguity of assembled genomes was assessed using QUAST (5. 0. 2)  [21]  and the completeness of the assembled genome was assessed using Busco (v5. 1. 1)  [22]. Single-copy orthologous gene sets were searched, and gene content was compared with 569 genes in the Betaproteobacteria database (available at BUSCO v1 (ezlab. org)). Final genome assembly adjustments were performed by polishing using Pilon (v1. 24)  [23]  with Illumina's own reads and the quality was then evaluated. Protein coding sequences (CDSs), tRNAs and rRNAs were predicted using Prokka  [24]  and the number of pseudogenes was calculated using the script get_pseudo. pl (VFDB: Virulence Factor Database (mgc. ac. cn)). Pathogenicity and antibiotic resistance analyses were conducted using the VFDB (Virulence Factors of Pathogenic Bacteria)  [25]  and CARD (Comprehensive Antibiotic Research Database) (The Comprehensive Antibiotic Resistance Database (mcmaster.
Genomic analyses The four investigated B. trematum WGSs produced between one and six contigs with > 96% completeness, establishing the reliability of the datasets for downstream analyses (Fig A and  Specifically, a flagellar system associated with mobility in all genomes examined accounted for 34% to 39% of annotated virulence factors; in addition to pili/fimbriae-associated proteins, filamentous hemagglutinin and LPS O-antigen, involved in Bordetella adhesion, accounting for 25% to 31% of genes. All B. trematum isolates expressed eight genes (pagP, bplA, bplB, bplC, bplD, bplE, bplL and kdsA) encoding lipopolysaccharide biosynthesis. We also noted the presence of a gene encoding the cytolethal distending toxin B subunit (CdtB). All isolates contained genes involved in biofilm formation (adeF, adeG and adeH), antiphagocytic activity (algW, wcbT), efflux (mexA, mtrD), and immune evasion, invasion, iron and magnesium absorption and stress adaptation.
Sampling The 1,074 isolates analyzed in this study came from 52 countries across 6 continents (Figure  1  and Supplementary Table  1 ). Whole genome sequencing data for B. abortus isolates were downloaded on June 23, 2023. Paired-end Illumina sequencing data were downloaded from the Sequence Read Archive  (Leinonen et al. , 2010). Genome assemblies were downloaded from GenBank  (Benson et al. , 2012)  and the Bacterial and Viral Bioinformatics Resource Center (BVBRC). 1  Genomes were removed from the data set if they aligned poorly to the reference genome (quality breadth <80% in program NASP), were identified as poor quality by Geographic locations of the 1074 Brucella abortus genomes used to construct the phylogenies in Figures  2, 3. Country or state centroid is given except when more specific location information was known.
Colors refer to the four clades: clade A is green, B is red, C is orange, D is purple, and light blue is undetermined. BVBRC, or were outliers (i. e. , other Brucella species). We removed obvious duplicate genomes from the dataset, but retained potential duplicates when we could not determine which genome should take priority. These duplicate genomes served as a doublecheck of our analysis methods, which was confirmed, as all duplicates were identical or highly similar to each other. The United States (US) was the origin of the largest number of genomes within this study (n = 365), with a majority from the Greater Yellowstone Ecosystem (n = 264). The United Kingdom (UK) had a relatively large number of isolates (n = 93), although as a central repository for strains that have been collected globally, some of these isolates likely originated elsewhere.
Ireland, India, Russia, Kazakhstan, Brazil, Egypt, Italy, and Costa Rica were the source of 26-94 isolates each, while the remaining countries were the origin of 1-15 isolates each. The origins of genomes in each lineage and sub-lineage of our phylogeny and basic metadata such as GenBank accession, strain ID, country and collection location, year of collection, host, and phylogenetic lineage are detailed in Supplementary Table  1. Isolates were primarily collected from cattle, but the 16 other hosts included bison (Bison bison), elk (Cervus canadensis), humans (Homo sapiens), water buffalo (Bubalus bubalis), goats (Capra hircus), swine (Sus domesticus), yak (Bos grunniens), dog (Canis lupus familiaris), camel (Camelus dromedarius), llama (Lama glama), reindeer (Rangifer tarandus), sheep (Ovis aries), chamois (Rupicapra rupicapra), red fox (Vulpes vulpes), cat (Felis catus), and mouse (Mus musculus).
SNP discovery Core-genome single nucleotide polymorphisms (SNPs) were called within NASP  (Sahl et al. , 2016)  using paired-end Illumina reads as input. For genome assemblies, paired-end Illumina sequencing data were simulated from publicly-available genome assemblies with ART (MountRainier)  (Huang et al. , 2012). Reads were aligned to B. abortus strain 2308 (GCA_000054005. 1) as the reference genome using BWA-MEM  (Li, 2013)  and SNPs were called with the Unified Genotyper method in GATK  (McKenna et al. , 2010; DePristo et al. , 2011). Positions were removed from the analysis if the depth of coverage was less than ten or if the allele proportion was less than 0. 9 for a genome. Duplicated regions of the reference genome were identified with self-alignments using NUCmer  (Delcher et al.
, 2002; Kurtz et al. , 2004)  and removed from the analysis. A maximum parsimony phylogeny was generated from high-quality, core-genome SNPs (bestsnp. fasta) with the R package phangorn  (Schliep, 2011). A consistency index (excluding parsimony uninformative SNPs) and retention index were calculated with phangorn. The consistency index allows one to determine the amount of homoplasy that is occurring within the genetic markers being used in the phylogeny, with values close to 1 indicating limited amounts of homoplasy. To determine the root of the B. abortus tree, we first generated a phylogeny that included 10. 3389/fmicb. 2023. 1287046 B. melitensis strain 16M (GCA_000740415. 1) as an outgroup due to this taxon being sister to B. abortus  (Wattam et al. , 2014). The core genome in these analyses was estimated with the quality breadth metric in NASP  (Sahl et al.
Bayesian time-structured coalescent analysis We plotted the divergence of each tip from the root against the date of sampling (a root-to-tip plot) in the program TempEST. Thus, this temporal signal allowed us to construct a time-structured phylogeny. For the molecular clock estimation, BEAST v1. 10. 1  (Suchard et al. , 2018)  was used to generate a time-structured phylogeny including only a subset (n = 607) of the GenBank genomes with known isolation year. For this analysis, NASP was run again, as described above, to generate a core SNP matrix specific for this subset of isolates. The matrix included only variable positions, but the BEAST XML input file was modified to specify the number of invariant sites, by nucleotide, in the B. abortus genomes. Six different combinations of molecular clock and coalescent models were evaluated using path-sampling and stepping-stone marginal likelihood estimation approaches  (Lartillot and Philippe, 2006; Fan et al.