dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2013; Kornaś et al. , 2015). However, larval stages encyst into the colonic mucosa as part of their life cycle and their massive emergence (larval cyathostominosis) can result in abdominal pain, diarrhea  (Love et al. , 1999; Matthews, 2014)  and eventually death  (Giles et al. , 1985). Drug inefficacy reports have accumulated worldwide over the recent years, and resistant cyathostomin isolates are now to be found in Europe  (Geurden et al. , 2014; Sallé et al. , 2017) , America  (Smith et al. , 2015) , and Oceania  (Scott et al. , 2015). It is therefore Abbreviations: ADF, acid detergent fiber; ADL, acid detergent lignin; AFNOR, Association Française de Normalization; ANOSIM, analysis of similarities; ANOVA, Analysis of the variance; CA, correspondence analysis; DM, dry matter; FEC, fecal egg counts; KEGG, Kyoto Encyclopedia of Genes and Genomes; NDCS, neutral detergent soluble carbohydrate; NDF, neutral detergent fiber; NFC, Non-fiber carbohydrate; NMDS, non-parametric multidimensional scaling; OTU, operational taxonomic units; PCIT, partial correlation and information theory; PCoA, principal coordinates analysis; PERMANOVA, Permutational Multivariate Analysis of Variance; PICRUSt, phylogenetic investigation of communities by reconstruction of unobserved states; QIIME, Quantitative Insights Into Microbial Ecology; qPCR, real time quantitative PCR; RDP, Ribosomal Database Project naïve Bayesian classifier; SCFA, short chain fatty acids.
Selection of Animals Twenty female Welsh ponies (10 resistant, R, and 10 susceptible, S; 5 ± 1. 3 years old) were selected from an experimental herd of 107 ponies (INRA, UEPAO, Nouzilly, France) regularly monitored for fecal egg counts (FEC) during the grazing season since 2011. Selection was based on the FEC records database consisting of 753 observations (n = 146, 278, 214, and 115 for spring, summer, autumn, and winter measures) of the whole herd. Every individual pony had been recorded at least three times over a minimum of 2 years (seven observations per pony on average across the whole herd). FEC data were log-transformed to correct for over-dispersion and fitted a linear mixed model accounting for environmental fixed effects (month of sampling, year of sampling, time since last treatment, age at sampling).
6, the first quartile was 0, and the third quartile was 150; Figures  S1A, B ). As it has been previously established that gut microbiota profiles might be shaped by host genetics  (Lozupone et al. , 2012; Goodrich et al. , 2014) , this information was considered to understand the individual variance underlying microbiota composition. The "kinship2" package in R was used to create the genetic relationship matrix. Both pedigree tree and correlation structure matrix are depicted in Figures  S1C, D , respectively. All the procedures were conducted according to the guidelines for the care and use of experimental animals established by the French Ministry of Teaching and Research and the regional Val de Loire Ethics Committee (CEEA VdL, n • 19). The protocol was registered under the number 2015021210238289_v4 in the experimental installations with the permit number: C371753.
py command in QIIME. We applied a default base call Phred threshold of 20, allowing maximum three low-quality base calls before truncating a read, including only reads with >75% consecutive high-quality base calls, and excluding reads with ambiguous (N) base calls  (Navas-Molina et al. , 2013). Subsequently, the sequences were clustered into OTUs against the GreenGenes database (release 2013-08: gg_13_8_otus)  (DeSantis et al. , 2006 ) by using the uclust  (Edgar, 2010)  method at a 97% similarity cutoff. The filtering of chimeric OTUs was performed by using Usearch version 6. 1  (Edgar et al. , 2011)  against the GreenGenes reference alignment  (DeSantis et al. , 2006). A phylogenic tree was generated from the filtered alignment using FastTree  (Price et al. , 2010). Singletons were discarded from the dataset to minimize the effect of spurious, low abundance sequences using the "filter_otus_from_otu_table.
py" script in QIIME. To confirm the annotation, the resulting OTU representative sequences were then searched against the Ribosomal Database Project naïve Bayesian classifier (RDP 10 database, version 6;  Cole et al. , 2009)  database, using the online program SEQMATCH (http://rdp. cme. msu. edu/seqmatch/seqmatch_intro. jsp). Finally, consensus taxonomy was provided for each OTU based on the taxonomic assignment of individual reads using GreenGenes and RDP databases. Using OTU abundance and the corresponding taxonomic classifications, feature abundance matrices were calculated at different taxonomic levels, representing OTUs and taxa abundance per sample. The "Phyloseq"  (Mcmurdie and Holmes, 2012)  and "Vegan"  (Dixon, 2003 ) R package were used for the detailed downstream analysis on abundance matrix.
In the end, a total of 8,010,052 paired-end 250 bp reads were obtained, 6,428,315 of which were retained as high-quality sequences (Table  S1 ). On average, a total of 58,015 sequences per sample were obtained in the study, with a mean length of 441 ± 15 bp. These sequences were clustered into 15,784 OTUs using the open reference-based OTU-picking process (Table  S2 ). Among them, 12,069 were classified taxonomically down to the genus level (Table  S2 ). OTU counts per sample and OTU taxonomical assignments are available in Table  S2. The unclassified taxa were filtered out from the analysis because the main goal of the current study was to identify specific taxa related to host susceptibility to strongyle infection. The α-diversity indexes (observed species richness,  Chao, 1984 and Shannon, 1997)  were calculated using the "Phyloseq" R package  (Mcmurdie and Holmes, 2012 ).
The Permutational Multivariate Analysis of Variance (PERMANOVA) on unweighted and weighted UniFrac distance matrices were applied through the adonis2 function with 9,999 permutations from "Vegan" R package to test for groups effect. Moreover, Bray-Curtis similarity coefficients were calculated from genera count matrix and plotted in a NMDS and CA graph to show the similarity among samples using the "Vegan" R package. Then after, the PERMANOVA test was also applied to test for groups' and time points' effect. In addition to multivariate analysis, we used the analysis of similarities (ANOSIM) to test for intragroup dispersion. ANOSIM is a permutation-based test where the null hypothesis states that within-group distances are not significantly smaller than between-group distances. The test statistic (R) can range from 1 to -1, with a value of 1 indicating that all samples within groups are more similar to each other than to any other samples from different groups.
R is ≈0 when the null hypothesis is true, that distances within and between groups are the same on average. Because multiple comparison corrections for ANOSIM were not available, the number of permutations being used on those calculations was increased to 9,999. The Wilcoxon rank-sum test with Benjamini-Hochberg multiple test correction was used to determine the differentially abundant OTUs, phyla, families, and genera between groups. An adjusted p ≤ 0. 25 was considered significant. This threshold was employed in previous microbiome studies because allows compensation for the large number of microbial taxa and multiple comparison adjustment  (Lim et al. , 2017). This targeted locus study project has been deposited at DDBJ/EMBL/GenBank under the accession KBTQ01000000. The version described in this paper is the first version, KBTQ01000000.
Functional Metagenomic Predictions The functional prediction for the 16S rRNA marker gene sequences was done using the phylogenetic investigation of communities by reconstruction of unobserved states. (PICRUSt)  (Langille et al. , 2013). After excluding the unknown OTUs from the GreenGenes reference database and normalizing by 16S rRNA gene copy number, functional metagenomes for each sample were predicted from the Kyoto Encyclopedia of Genes and Genomes (KEGG) catalog and collapsed to a specified KEGG level. We used Wilcoxon rank-sum test with Benjamini-Hochberg multiple test correction to evaluate predicted pathway-level enrichments between groups. An adjusted p < 0. 05 was considered as significant.
Based on correlation coefficient and p-values for correlation, we constructed cooccurrence networks. The cutoff of p-values was 0. 05. The cutoff of correlation coefficients was determined as r ≥ |0. 35|. Network properties were calculated with the NetworkAnalyzer plugin in Cytoscape. We used the "iGraph" package in R to visualize the network. Strong and significant correlation between nodes (r ≥ |0. 60|) were represented with larger edge width in the network. Real-Time Quantitative PCR (qPCR) Analysis of Bacterial, Anaerobic Fungal, and Protozoan Concentrations Concentrations of protozoa, anaerobic fungi and bacteria in fecal samples were quantified using a QuantStudio 12K Flex real-time instrument (Thermo Fisher Scientific, Waltham, USA). Primers for real-time amplification of protozoa (FOR: 5 ′ -GCTTTCGW TGGTAGTGTATT-3 ′ ; REV: 5 ′ -CTTGCCCTCYAATCGTWCT-3 ′ ), anaerobic fungi (FOR: 5 ′ -TCCTACCCTTTGTGAATTTG-3 ′ ; REV: 5 ′ -CTGCGTTCTTCATCGTTGCG-3 ′ ) and bacteria (5 ′ -CAGCMGCCGCGGTAANWC-3 ′ ; REV: 5 ′ -CCGTCAATTC MTTTRAGTTT-3 ′ ) have already been described in  Mach et al.
Indeed, ponies shifted from an indoor lifestyle (associated with a hay-concentrate based diet) to an outdoor pasture-based diet at day 0. Additionally, a heat wave took place over the first 43 gd resulting in almost no rainfall (0. 2 mm) and high temperatures peaking at 37. 7 • C (Figure  S3A ). This situation ultimately led to grass senescence and lowered pasture quality (Figure  S3B ). Mild dehydration also occurred in ponies as supported by a constant rise in measured hematocrits from 32. 33 to 39. 63% during the first 43 gd (Figure  2B ). To account for this, blood cell counts were corrected by hematocrit through time. Recorded hematological data showed that ponies were neither anemic nor thrombocytopenic throughout the experiment (Figure  S4 ). Concomitantly to these challenging conditions, increased levels of some white blood cell populations were observed, namely eosinophils (2.
ACKNOWLEDGMENTS We are grateful to  Jean Marie Yvon ,  Yvan Gaude ,  Thierry Blard ,  Thierry Gascogne ,  Philippe Barriere ,  Francois Stieau , and  Adelaide Touchard  for the animal sampling and management, and to  Marine Guego ,  Marine Beinat , and  Julie Rivière  for participating to the sample collection during the project. We also thank  Diane Esquerré  for preparing the libraries and performed the MiSeq sequencing. Lastly, we are grateful to the  INRA MIGALE bioinformatics platform  (http://migale. jouy. inra. fr)for providing computational resources.
As can be inferred from these examples, a variety of challenges are shared broadly across different veterinary vaccines. Additional file 1 synthesizes some of these general limitations associated with many current veterinary vaccines, based on an assessment of an OIE ad-hoc Group on Prioritisation of Diseases for which Vaccines could Reduce Antimicrobial Use in Animals (see next section) and a review of research gap data for more than 50 infectious diseases of animals produced by expert groups and captured in DISCONTOOLS, a database created as part of the Action Plan of the European Technology Platform for Global Animal Health and funded under the EU 7th framework program  [47]. As shown in Additional file 1, current veterinary vaccines often fall short with regard to efficacy, safety and/ or user-friendliness.
In vitro parasite development assays Invasion assays were performed as described previously  [21]. Briefly, 2 × 10 5 epithelial cells per well (MDBK, m-IC cl2 , CLEC-213) were co-cultured on glass coverslips with 4 × 10 5 purified sporozoites (Wis-YFP) for 3 h at 41 °C, 5% CO 2 ; in preliminary experiments, the infection rate was higher at 41 °C than at 37 °C in all cell lines, confirming the data described by Tierney et al. [8]. After washing and fixing the cells with paraformaldehyde (4%; Santa Cruz Biotechnology, Dallas, TX, USA), monolayers were mounted in Vectashield mounting media with DAPI (1. 5 μg/ml; Vector Laboratories, Burlingame, CA, USA). For each coverslip, a minimum of three microscope fields were observed (Zeiss Axiovert 200 microscope, Carl Zeiss, Göttingen, Germany). More than 200 cells were counted per condition using ImageJ software.
The relative transcript expression of Etgam56 and Etfoa1 was defined relative to the E. tenella housekeeping gene, Et18S. Statistical analysis was performed using ANOVA followed by Dunn's test. *P < 0. 05 and **P < 0. 01 indicate a statistically significant difference compared to previous free parasite stages (Sp and M1) or previous days of infection. Data are the mean ± SD of at least two biological replicates and three technical replicates. b Immunofluorescence analysis of microgametocytes and macrogametocytes production in CLEC-213 infected with merozoites II from E. tenella Wis strain (i, ii) or sporozoites from the precocious Wis-F-96 strain (iii, iv) was performed using anti-FOA1 mouse sera (i, iii) and anti-GAM56 rabbit sera (ii, iv) and the appropriate secondary antibodies (Alexa 594).
Acknowledgements We are thankful to  Alain Vandewalle  ( UFR de Médecine Bichat, France ) for the cell line, m-IC cl2 , to  Janene Bumstead ,  Damer Blake  and  Fiona Tomley  ( Royal Veterinary College, University of London, UK ) who kindly provided us the Wis and Wis-F-96 strains of E. tenella and the MDBK cell line. We are also grateful to  Sébastien Lavillatte  and  Edouard Guitton  ( INRA Centre Val de Loire-PFIE, France ) for their skills in animal care.
, 2012; Sidhu-Muñoz et al. , 2016 ). b Underlined sequences in 25OVL-F, 25cOVL-F, and 31OVL-F correspond to regions overlapping with 25OVL-R, 25cOVL-R, and 31OVL-R, respectively. c Target gene is the B. ovis gene to be deleted or PCR-amplified for the verification of mutant strains. Primers Universal-F and Universal-R target pGEM-T Easy and its derived recombinant plasmids at both sides of the cloned insert and were used for sequencing of the DNA insert. The remaining primers target the B. ovis genome and were designed according to the published genome sequence of B. ovis 63/290 (ATCC 25840) (accession numbers NC_009505 and NC_009504 for chromosome I and II, respectively). mutant strains was performed with specific PCRs targeting each inactivated locus.
136 ± 0. 011 g) (data not shown). Additionally, B. melitensis Rev1 was detected in spleen (log CFU/spleen values of 3. 66 ± 0. 07), while the omp10 ugpB omp31 mutant was cleared by this time (data not shown). Splenocytes were stimulated with B. ovis PA whole cells to evaluate, by specific ELISA tests, the production of cytokines. Splenocytes of mice inoculated with PBS secreted limited amounts of IFN-γ, while about 30 and 60 times higher levels (P < 0. 05) were detected in the groups vaccinated with the omp10 ugpB omp31 mutant and B. melitensis Rev1, respectively (Figure  8A ). In a lesser extent, splenocytes from vaccinated mice also produced more IL-10 (P < 0. 05) than those obtained from mice of the PBS group (mean values of 14. 7, 9. 9, and 1. 4 ng/well for the B. melitensis Rev1, B. ovis omp10 ugpB omp31, and PBS groups, respectively) (Figure  8C ).
, 2013). The number of animals introduced from other herds instead did not seem to play an important role. The aim of this study was to quantitatively assess the vulnerability of Italian regions to bovine brucellosis to explain the extremely diverse epidemiological situation reported in the country, with strong regional differences. Adopting a network perspective for veterinary epidemiology and policy assessment  (Dubé et al. , 2009; Martínez-López et al. , 2009) , we developed a mathematical model describing the spread of bovine brucellosis from farm to farm associated with the movement of infected animals in the region. The model is based on the complete database of daily cattle trade movements for the whole country from January 2006 to December 2012, and it is parameterized with outbreak data reported to the Italian National Veterinary authority in the period 1983-2015.
Cattle trade movement data Data on cattle trade movements were obtained from the Italian National Database for Animal Identification and Registration (NDB) that is managed by the Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise (IZSAM) on behalf of the Italian Health Ministry  ("Sistema Informativo Veterinario," n. d. ). The database details the movements of the entire Italian population of bovines among animal holdings, providing a comprehensive picture of where cattle have been kept and moved within the country. Each movement record reports the unique identifier of the animal, the identifiers of the holdings of origin and destination, and the date of the movement. Holdings are georeferenced. Here we examined the daily records from January 1, 2006 to December 31, 2012. A total of 11,775,842 bovines were tracked, counting for 3,693,593 recorded displacements among 190,596 animal holdings in Italy (Table  1 ).
Model parameterization Data on brucellosis control activities were collected from the Italian National Animal Health Managing Information System, an informatics system developed by IZSAM on behalf of the Ministry of Health to monitor the progress of the eradication plan and measure the degree of achievement of its objectives  (Italian Ministry of Health, 2012; "Sistema Informativo Veterinario," n. d. ). The database reports on all surveillance and eradication activities and their results at farm and individual animal level. We used records of bovine brucellosis outbreaks occurring in Italy between February 1983 and September 2015. For each outbreak, we considered data reporting the identifiers of the affected animal holding, its production type, and the dates of start and end of the outbreak, based on the date of first infection detection and date of clearing of the infection, respectively.
, 2009; Abernethy et al. , 2011; Calistri et al. , 2013; Cowie et al. , 2014). These movements are not included in the cattle trade database used in this study as Italian regulations do not require their compulsory tracking. Using a different dataset, we were able however to find a moderate association of the brucellosis vulnerability of each region with the number of premises with pastures. Direct contact between cattle at pasture was found to be the most likely driver for bovine brucellosis transmission in Northern Ireland  (Abernethy et al. , 2011) , where several neighboring herds reported epidemics breaking out during summer (when they more likely moved to pastures), and epidemiological investigations identified deficiency boundary fencing in the area. Similar results were obtained also in Spain, where the number of farmers sharing summer pastures was identified as a significant risk factor for brucellosis  (Dias et al.
An important part of brucellosis control is the ban on movements as soon as an infection is detected in a given holding. By crossing the database of animal movements (NDB) and the database of brucellosis surveillance and eradication activities (SANAN) ("Sistema Informativo Veterinario," n. d. ), our study allowed for the first time the assessment of farmers' compliance to restrictions on trade while experiencing an ongoing outbreak. Approximately 15% of farmers with infected herds continued to trade despite the policy in place, and half of them moved about the same number of animals or more than they were used to move in the same seasonal period. Most importantly, the number of outbreaks occurring in a given premises is clearly associated with the number of incoming traded herds received from infected premises.
This is especially important for diseases characterized by a silent spreading phase with a latent sub-clinical infection that may hide epidemiological links between premises due to the long interval between infection and disclosure. Finally, we stress the importance of cross-matching different databases such as the one for bovine identification that tracks animal movements and the database for the continuous monitoring of surveillance and control activities, in order to uncover unexpected behaviors weakening the progress of efficient brucellosis eradication, as we showed here. We suggest that such cross-matching is performed routinely by veterinary authorities to considerably enrich the knowledge on the health status of animal populations and improve the accuracy of the evaluation of veterinary policies for updates and replanning.
Together with the previously published RNA-Seq data of two apple snails, we conducted de novo transcriptome assembly of eight species that belong to five genera of Ampullariidae, two of which represent Old World lineages and the other three New World lineages. There were 20,730 to 35,828 unigenes with predicted open reading frames for the eight species, with N50 (shortest sequence length at 50% of the unigenes) ranging from 1320 to 1803 bp. 69. 7% to 80. 2% of these unigenes were functionally annotated by searching against NCBI's non-redundant, Gene Ontology database and the Kyoto Encyclopaedia of Genes and Genomes. With these data we developed AmpuBase, a relational database that features online BLAST functionality for DNA/protein sequences, keyword searching for unigenes/functional terms, and download functions for sequences and whole transcriptomes.
RNA isolation and sequencing Total RNA was extracted separately from each tissue sample using TRIzol® reagent (Invitrogen, MA, USA) following the manufacturer's protocol. In general, two RNA samples, including one of the albumen gland (AG), and one of other tissues (OT), which contained equal amounts of RNA extracted from three to four tissue types, were prepared for sequencing (Table  1 ). AG was always processed separately, because this organ, which secrets the perivitelline fluid that protects and nourishes the embryo, is expected to play a crucial role in the reproduction and evolution of ampullariids  [24, 25, 38]. More tissue types of P. canaliculata were sequenced due to the need for producing tissue-specific gene expression data in another project for this species. To enhance the comprehensiveness of the transcripts for P.
canaliculata, we combined our new data with the transcriptome data we generated from a previous study  [29]  for assembly. The transcriptome data of P. canaliculata from another study  [39]  were not included here because of uncertainty of sample preparation, and because more data would not likely improve the assembly metrics  [40]. Raw reads of P. maculata were obtained from a recent publication  [25] , and re-assembled as described below. In P. scalaris, only AG was sequenced due to the lack of high quality RNA in OT preserved in RNAlater. For all samples, the quality of extracted RNA was determined using an Agilent 2100 Bioanalyzer (Agilent Technologies, Germany). Samples with an RNA Integrity Number ≥ 8 were used for cDNA library construction using a TruSeq RNA Sample Prep Kit v2 (Illumina, California, USA), and sequenced in paired-end mode on an Illumina HiSeq sequencer (Illumina, California, USA).
Transcriptome assembly and annotation Illumina raw reads were cleaned by removing adaptor sequences, reads with > 5% unknown "N" bases or > 20% bases with a quality score ≤ 10 (Table  1 ). Trimmomatic v0. 33 was then used to further remove low quality reads with a quality score < 20 and a length < 40 base pairs (bp)  [41]. For each species, clean reads from different tissue samples were pooled for de novo assembly using Trinity 2. 2. 0 under default settings  [42]. The assembled transcripts (ranging from 126,582 to 388,329; Table  2 ) were clustered with CD-HIT-EST 4. 6. 6 to reduce redundancy using a threshold of 95% sequence similarity  [43]. Open reading frames (ORFs) were predicted with Trans-Decoder 3. 0. 0 (https://transdecoder. github. io/) using a threshold of ≥100 amino acids. Only the single best ORF per transcript was retained.