dataesr/scientific-paragraphs-categorization huggingface dataset:
Interestingly, we showed that the Verdun Cl3 strain did not colonize the mouse kidney, although both Manilae and Copenhageni did so, confirming previous data  [20, 54, 64, 65]. This lack of renal colonization by the Verdun Cl3 was not expected considering the clinical features of severe leptospirosis recorded after high dose infection and determined using an evaluation scoring, including weight loss and clinical signs. This is surprising, since other murine rodents such as rats are known worldwide as renal carriers of a large array of Leptospira serovars, including Icterohaemorrhagiae  [15]. However, although the Icterohaemorrhagiae Verdun strain is pathogenic  [66, 67] , and like other serovars may cause pulmonary hemorrhages, a syndrome also frequently described in guinea pigs, and reported associated with the most severe human leptospirosis cases  [68] , it has also been reported that experimental infection with Icterohaemorrhagiae strains in outbred mice and hamsters results in subclinical infections  [67].
These results are difficult to reconcile with the data showing that the antigenic cross-protection of fcpA was due to antibodies directed against highly conserved proteins of leptospires, rather than neutralising antibodies directed at serovar specific LPS  [49]. One or two months after challenge, we measured the leptospiral loads in kidneys of control and pre-infected mice. As expected, the M895 mutant that has shown potential as a live attenuated vaccine, protected against kidney colonization upon challenge. The interpretation of results obtained with the virulent Manilae L495 and Copenhageni Fiocruz LV2756 preinfected mice is more complicated. Indeed for Manilae L495, we did not find leptospires in the kidneys. At the 2×10 7 dose it was surprising since although it was in a different experiment, we had renal colonization one month p.
This work has been supported by the  Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases"  Grant  ANR-10-LABX-62-IBEID  to IGB from the  French government 's  Investissement d'Avenir program. Work at  Monash University  was supported by grants to BA from the  National Health and Medical Research Council  ( 54826 ) and the  Australian Research Council  ( CE0562063 ),  Canberra ,  Australia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Plant materials Fresh leaves and dried fruits of P. nitens were collected at the campus of the Institute of Biosciences, Humanities and Exact Sciences of São Paulo State University (UNESP), São José do Rio Preto, SP, Brazil (20 • 47 ′ 02. 4 ′′ S 49 • 21 ′ 36. 0 ′′ W), in July 2014. A voucher specimen (HISA 10,291) was deposited in the Ilha Solteira Herbarium (HISA) at the Faculty of Engineering of UNESP in Ilha Solteira, SP. Brazilian biodiversity access number A85B7D5 was registered with National System for Management of Genetic Heritage and Associated Traditional Knowledge.
Statistical analyses The percent of inhibition of egg hatch (EHA) was calculated by the following equation: % inhibition = A/ (A + B) × 100, where A is the number of unhatched eggs and B is the number of L 1 larvae. The percent of inhibition of larval development (LDA) was calculated using the following equation: % inhibition = (A/B) × 100, where A is the number of L 1 + L 2 larvae and B is the total number of larvae (L 1 + L 2 +L 3 ). Data are presented as the mean percentage ± standard error (SEM). One-way ANOVA followed by the Tukey test (p ≤ 0. 05) was used to assess statistical significance depending on two factors: treatments and concentrations. In order to provide another parameter for comparison between the tested extracts and natural compounds, the concentrations at which occurred 50 % egg hatching inhibition and larval development inhibition (EC 50 ) of the parasites were also calculated.
Acknowledgements This work was supported by the  Office the Coordinate for the Improvement of Higher Education Personnel (CAPES) ,  Brazilian Council for Scientific and Technological Development (CNPq)  (grants  471129/ 2013-5 ,  306251/2016-7  and  429322/2018-6 ), and  São Paulo State Research Foundation (FAPESP)  (Project  2017/01626 , grants  2014/ 18330-0  and  2018/15083-2 ). C. S. L. thanks  CAPES  (finance code  001 ).
Microbiota Analysis 2. 4. 1. Data Analysis of 16S Sequences For the 16S analysis, we performed an OTUs (Operational Taxonomic Unit) analysis. The FROGS pipeline (Find Rapidly OTU with Galaxy Solution) implemented on a galaxy instance (http://sigenae-workbench. toulouse. inra. fr/galaxy/, accessed on March 2019) was used for data processing  [41]. Briefly, paired reads were merged using FLASH  [42]. After denoising and primer/adapters removal  [43] , de novo clustering was done using SWARM, which uses a local clustering threshold, with aggregation distance d = 3 after denoising. Chimeras were removed using VSEARCH  [44]. We filtered out the singletons and performed taxonomic assignment using Blast+ against the Silva database (release 128). All statistical analyses were done using R v3. 3. 1 (R: a language and environment for statistical computing, 2008; R Development Core Team, R Foundation for Statistical Computing, Vienna, Austria [http://www.
R-project. org, accessed on July 2018). We used the phyloseq R package for community composition analysis  [45]  to infer alpha diversity metrics as well as beta diversity (between-sample distance). Beta diversity was examined by Principal Coordinate Analysis (PCoA) using the Bray-Curtis distance matrices. We performed a Mann-Whitney U test (p < 0. 05) to compare alpha diversity and one-way PERMANOVA with a Benjamini-Hochberg post-hoc to analyse beta diversity between the experimental groups. To analyse the phylum dynamic during infections we used Mann-Whitney test. For all analyses, the threshold significance level was set at 0. 05.
Antimicrobial Response An antimicrobial transcriptome was built from transcripts known to be involved in Biomphalaria immune response against bacteria (antimicrobial peptides: biomphamacin or antimicrobial proteins: LBP/BPI and achacin; see Table  S2  for details). The fulllength sequences of these transcripts were recovered from GenBank and the Biomphalaria genome  [46]  and joined in a subset that represents the antimicrobial transcriptome of B. glabrata. This antimicrobial transcriptome was then concatenated with a de-novo assembled transcriptome of Biomphalaria available in our laboratory (see  [25, 32, 47]  for details) and uploaded on the Galaxy server. Before concatenation, a blastn (70% identity and 90% coverage) was conducted to identify redundant transcripts across the transcriptomes.
Differential Expression Analysis High-quality reads (Phred score > 29) were aligned to the concatenated transcriptome using Bowtie2 (v. 2. 0. 2), which was run locally on a Galaxy server. The DESeq2 (v2. 12) R package was used to identify differential expression levels between uninfected (B0. 1 and B0. 2) and infected conditions (adjusted p-value < 0. 05).
primary infection (Permanova Analysis and Post-Hoc Benjamini-Hochberg, p = 0. 003) and naive vs. secondary challenge (Permanova Analysis and Post-Hoc Benjamini-Hochberg, p = 0. 003)), by the time of infection (early (1 day) vs. late (4 days)) (Permanova Analysis and Post-Hoc Benjamini-Hochberg, p = 0. 006) and also by the strain of parasite used for primary infection (SmBRE vs. SmVEN) (Permanova Analysis and Post-Hoc Benjamini-Hochberg, p = 0. 016) (Table  S8 ). Principal Coordinate Analysis (PCoA) based on Bray-Curtis dissimilarities between the core microbiota (Figure  S2 ) yielded very similar results to those based on the entire dataset (Figure  4A ). In addition, we observed that 69. 4% (43 families) of the core microbiota families were significantly affected by infection. Among those, 6.
The mean concordances between the masked autosomal SNVs and imputed SNVs were 91. 97% and 95. 86% for SNVs imputed from the Illumina -22k SNV panel to the higher density Affymetrix Axiome Canine Genotyping array and from the Illumina 173K SNV Canine HD panel to the higher density Affymetrix Axiome Canine Genotyping array, respectively. These concordances are similar to those described by the work of Friedenberg and Meurs, which describes a genotype concordance of up to 92. 4% with Beagle software  [39]. The addition of BMD cases and controls to the first BMD GWAS (GWAS_1_HS_BMD) resulted in a total of 403 cases and 347 controls imputed to form a final data set of 488,872 SNVs (GWAS_6_HS_BMD_with_imputed_SNV). Statistical analysis allowed the identification of 1,730 SNVs significantly associated with HS (Table  2 , Fig 4A  and 4B ).
This GWAS, after increasing the number of BMD cases and controls, confirmed the involvement of the CFA11 locus as well as the role of other loci (CFA5 and CFA14), and identified a new locus on chromosome 2 in HS BMD predisposition. By the addition of 28 FCRs (13 cases and 15 controls) to GWAS_6_HS_BMD_with_impu-ted_SNV to form a final dataset of 525,657 SNVs (GWAS_7_HS_BMD+-FCR_with_imputed_SNV), we identified 1,558 SNVs that were significantly associated with HS (Table  2 , Fig 4C  and 4D ), confirming the involvement of the CFA2, CFA5, CFA11, and CFA14 loci in HS predisposition. (LD) structure. B) Regions delimitated by the SNPs in LD with the best GWAS SNVs (R 2 > 0. 6) in cases; minimal region between the three GWAS (CFA5:28309815-34321500) is delimitated by red lines. C) Close up view of the genes (with available symbols) located in this minimal region (28-34 Mb) of CFA5.
https://doi. org/10. 1371/journal. pgen. 1009395. g002 The addition of 60 Rottweilers (37 cases and 23 controls) to GWAS_7_HS_BMD+-FCR_with_imputed_SNV formed a final dataset of 532,053 SNVs (GWAS_8_HS_BMD+FCR +Rottweiler_with_imputed_SNV), and led to the identification of 1,505 SNVs that were significantly associated with HS (Table  2 , Fig 4E  and 4F ). This GWAS confirmed the involvement of the CFA2, CFA5, CFA11, and CFA14 loci in HS predisposition. SNVs in LD with significant SNVs in cases (R 2 � 0. 6) allowed us to identify large regions spanning several Mb (up to 23 Mb for CFA11; Table  2 ). The analysis of these SNVs within the three breeds allowed us to reduce the CFA11 locus region to. These analyses identified SNVs that were significantly associated with HS risk and were shared between the three predisposed breeds on at least chromosomes 2, 5, 11, and 14.
Causal variants Like previous studies on canine HS predisposition  [26]  and human cancers  [44, 59] , capture and targeted sequencing of the three HS candidate loci did not allow the identification of potential coding variants and risk variants that are common in the predisposed breeds. While the genotype concordance of imputed SNVs with the Beagle software was reliable, imputation of SNVs identified by the capture could limit the detection of causal variants. However, as in humans, majority of the loci identified from cancer GWAS do not directly affect the amino acid sequence of the expressed protein, and thus elucidation of causal variants is challenging, since all closely linked variants that are in LD with the best GWAS SNV are relevant candidates  [44]. In this study, the best SNVs were either in the intronic part of the candidate genes (FHIT, SPNS3, etc.
GWAS DNA samples were genotyped on an Illumina 173K SNV Canine HD array at the Centre National de Genotypage (Evry, France) and on Affymetrix Axiom Canine Genotyping Array Set A and B 1. 1M SNV array at Affymetrix, Inc. (Santa Clara, CA, USA; Table  1 ). SNV genotypes were filtered with pre-sample call rate >95%, per SNV call rate >95%, and minor allele frequency (MAF) = 0. 01. Breed check was performed with a cluster tree and genetic matrix distances obtained from common SNVs of our data and in publicly available data  [15, 16]. Sex check was performed via the Plink 1. 9 option "-check-sex "  [60]. For GWAS including multiple breeds, we conducted this quality control protocol for each breed before merging the dataset. We used mixed linear model analyses by taking into account the population structure and kinship with R package "Eigenstrat-GenABEL" 1.
8  [61]  on R studio software (version 1. 1. 463; Vienna, Austria). P-values corrected for inflation factor λ were used, and we identified all SNVs with significant association exceeding 95% confidence intervals as defined empirically using 1,000 random phenotype permutations with the Eigenstrat-GenABEL 1. 8 software  [61]. For imputation, the Beagle software  [62]  version 4. 1 was used to impute the Illumina 20K SNV and Illumina 170K SNV arrays to the Affymetrix 712K SNV array format as well as to input 21,614 variants identified from the capture and targeted sequencing of 16 dogs. Thereafter, 113 BMDs and 21 FCRs, representative of the BMD and FCR populations, were selected and genotyped on the Affymetrix 712K SNV array. These dogs were used as a reference panel for the imputation. SNVs for imputation were filtered for MAF > 0.
Paired-end adaptor oligonucleotides from the NEB kit were ligated on repaired A-tailed fragments, then purified and enriched by eight polymerase chain reaction (PCR) cycles. Next, 1200 ng of these purified libraries were hybridized to the SureSelect oligo probe capture library for 72 h. After hybridization, washing, and elution, the eluted fractions were PCR-amplified with nine cycles, purified, and quantified by quantitative PCR (qPCR). Based on this quantification, an equimolar pool was acquired and quantified again by qPCR. Finally, the pool was sequenced on an Illumina HiSeq 2000 platform as paired-end 75 bp reads. Image analysis and base determination were performed using the Illumina RTA software version 1. 12. 4. 2 with default settings. Bioinformatics analyses of sequencing data were based on the Illumina pipeline (CASAVA 1.
Predictive modeling For model selection, we extracted the data only for the 1,505 significant SNVs identified by GWAS_8_HS_BMD+FCR+Rottweiler_with_imputed_SNV, and recoded them as 0 for AA genotype, 1 for AB genotype, and 2 for BB genotype. For the first model selection method, we used a Stepwise Forward selection based on a 0. 05 alpha inclusion and exclusion threshold inspired from Zapata et al  [20]. Briefly, the selection process began with a model with no terms. Independent variables were sequentially added based on their lowest p-values in the generalized model. Before adding the next term, the selection method would remove any variables that became non-significant after the inclusion of the previous term. The selection process was terminated when no more terms could be added or removed from the model.
Methylation analyses Methylation analyses were performed on 12 HS cell lines, including one commercial cell line (DH82; American Tissue Type Culture, CRL-10389; RRID:CVCL_2018) and 11 cell lines developed from HS-affected fresh dog tissue samples. These eleven cell lines are available on request (S6 Table ). The cells were cultivated in complete Roswell Park Memorial Institute Medium (RPMI) medium containing RPMI 1640 GlutaMAX supplemented medium (Gibco Life Technologies) with 10% fetal bovine serum (HyClone, GE Healthcare, Life Sciences, Logan, UT) and 0. 025% primocin (InvivoGen, Toulouse, France) at 37˚C in a humidified 5% CO 2 incubator. All cell lines were tested for mycoplasma using the MycoAlert Plus kit (Lonza, Rockland, ME) by following the manufacturer's protocol, and were found to be mycoplasmafree cells.
Genotyping for validation on independent cohorts Genotyping of the SNVs of Chr5_30488886, Chr11_41252822, and Chr14_11021670 was performed by targeted sequencing using Ion AmpliSeq technology with Ion GeneStudio S5 Prime System (Life Technology, ThermoFisher Scientific, Courtaboeuf, France). Probes were designed using the AmpliSeq design service, and Torrent Suite Software (v5. 12) was used for sequencing data processing. Torrent Mapping Alignment Program (TMAP) software was used to perform read processing and mapping on the loaded genome (canFam3) using default parameters. Variant Caller Plugin was used for variant calling, and two independent cohorts were selected from the BMD samples collected between 2012-2020. The first independent cohort for genetic analyses was made of 186 cases and 176 controls.
Acknowledgments We thank the veterinarians who provided anatomopathological diagnoses, especially  Olivier Albaric  and  Laetitia Dorso  ( Laboniris, Oniris, Ecole Nationale Veterinaire de Nantes, France ),  Marie-Odile SEMIN  ( LAPV, Amboise, France ),  Caroline Laprie  ( Vet-Histo, Marseille, France ),  Marie Lagadic  ( Idexx Alfort, France ), and  Frederique Degorce-Rubiale  ( LAPVSO, Toulouse, France ). We also thank the veterinarians for providing us with clinical data and samples as well as the dog owners, breeders, and breed clubs, especially the  French club AFBS, European clubs, American club BMDCA, IWG International Working Group (for Bernese mountain dogs) , and  US Berner-Garde foundation , and especially  Pat Long  for her dedicated trust and follow-up of our study. We also warmly thank  Clotilde de Brito ,  Laetitia Lagoutte ,  Annabelle Garand ,  Anne Sophie Guillory ,  Melanie Rault , and  Ronan Ulve  ( IGDR, Rennes, France ) for their technical support and helpful discussions, Stephane Dreano ( IGDR, Rennes, France ) for Sanger sequencing and Biogenouest bioinformatics platform.
CA received fundings from  INCa PLBio  (https://www. e-cancer. fr/Institut-national-ducancer/)(Grant "canine rare tumours" funding ( N2 012-103 ;  2012-2016 ) and Aviesan (https:// aviesan. fr/)(Grant  MTS 2012-06 ) for the work describe here. BH received fundings from American Kennel Club Canine Health fundation (https://www. akcchf. org/)(Grant N  2446 ). This research is also funded by  ANR  (Grant  ANR-11-INBS-0003 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Statistical analysis All analyses were performed in R statistical software (version 3. 4. 0). A dummy variable 'Injury' (presence or absence of injury) was calculated and analysed according to the housing system, parity, and the live weight of the rabbit at artificial insemination using a logistic regression. The live weight of the female rabbits was analysed using a linear mixed effect model including housing system (IH or PGH) and female parity order (primiparous or multiparous) as fixed effect and female as random effect. The live weight of female rabbits at artificial insemination was added as a co-variable. The number of kits born and weaned, and the live weight of kits at weaning were also analysed using a linear mixed effect model including the housing system and parity order of female rabbits as fixed effect and female as random effect.
Histomorphology of Duodenum, Jejunum, and Ileum Samples Tissue sections from duodenum, jejunum, and ileum were opened longitudinally, placed on cork boards with hedgehog spines and fixed in a 4% phosphate-buffered formaldehyde solution for 24 h. After dehydration and infiltration with solidified paraffin wax, the samples were embedded. The paraffin blocks were cut at 4 μm with a sledge microtome (SM 2000 R, Leica, Nussloch, Germany). Obtained sections were mounted on glass slides. Tissue slides were stained with Haematoxylin-Eosin and analyzed with a light microscope (Photomicroscope III, Zeiss, Oberkochen, Germany) equipped with a digital camera (DP72, Olympus, Tokyo, Japan). Histomorphometric parameters were measured using an image analysis software (CellSense Software, Olympus, Tokyo, Japan).
Statistical Analyses The statistical analyses were performed using the software package SPSS (IBM SPSS Version 25). Prior to one-way ANOVA based on treatment number, zootechnical, and physiological data were tested for normal distribution by Shapiro-Wilk test and variance homogeneity by Levene's test. Potential covariates (sex, BW at weaning, and room) were considered and included to the statistical model in case of significant impact on single target parameters. All treatment means were compared with each other using Tukey test or Games-Howell test depending on variance homogeneity. As a rank variable, fecal score per day was analyzed using the Kruskal-Wallis test. The number of days with diarrhea (fecal score <2) as a metric variable was analyzed by ANOVA and Tukey test. The statistical tests used are shown in the footnotes of the respective data tables.
Mean differences with a probability of P < 0. 05 were accepted as statistically significant, also mean differences with P-values ranging from 0. 06 to 0. 10 were considered as trends. The gene expression data of jejunal tissue were analyzed by  REST 2009 software (Qiagen GmbH, Munich, Germany; Pfaffl et al. , 2002). In the REST, gene expression analysis, the treatment groups AAB-1, and AAB-2 were compared with the CTRL group after PCR efficiency correction and normalization by reference genes (RPL13 and SDHA).
However, since the average rectal temperatures were higher than reference values for piglets of this age  (Heinritzi et al, 2006)   CTRL, control group; AAB-1, control feed + 0. 3% amino acid blend 1 (=0. 125% arginine + 0. 1% branched-chain amino acids + 0. 075% cystine); AAB-2, control feed + 0. 3% amino acid blend 2 (=0. 094% arginine + 0. 075% branched-chain amino acids + 0. 056% cystine + 0. 075% tryptophan); branched-chain amino acids = leucine:valine:isoleucine (2:1:1); 1 Data are presented as means (n = 10). (Ren et al. , 2014 ), and Trp (Koopmans et al. , 2006 , 2012)  are increased in case of immune system stimulation. To evaluate the dietary potential, particularly that of BCAA supplementation, on endocrine growth factors, plasma IGF-1 was analyzed. IGF-1 is described as a mediator of the anabolic and mitogenic activity of growth hormone  (Laron, 1999).
b-High-resolution LC-MS colostrum analysis All LC-MS data was acquired with a Thermo Q-Exactive Orbitrap ® mass spectrometer coupled to an Agilent 1290 HPLC system. Analytes were resolved by hydrophilic liquid interaction chromatography (HILIC) with a 350 ul min -1 flow rate. Two microliters of sample was injected onto a PEEK lined Agilent HILIC-Z (2. 1 × 100 mm, 2. 7 µm; Agilent) column maintained at 35 °C. Compounds were resolved with mobile phases of 10 mM ammonium formate + 0. 1% formic acid in water (A) and 10 mM ammonium formate + 0. 1% formic acid in 90% acetonitrile (B) operating with the following gradient: 0 min, 90% B; 1. 0 min, 90% B; 5. 0 min, 62% B; 5. 5 min, 30% B; 10. 5 min, 30% B, 11. 0 min 90% B and 15. 5 min, 90% B. Sample of 100 μl of each raw colostrum sample was diluted with 400 μl of ddH2O.
2 m/z isolation window and 25,35 steeped collision energy. Thermo. raw files were converted to. mzml format using Protewizard  32  with peak peaking filter applied. Features were detected using the XCMS package  33  with the centWave method (ppm tolerance 1. 0  34  ). The signal to noise threshold was set to 5, noise was set to 1×10 6 and pre-filter was set to six scans with a minimum 5,000 intensity. Retention time correction was conducted using the obiwarp method  35. Grouping of features was set to those present in at least 25% of all samples (retention time deviation 10 s; m/z width, 0. 015). The 'fillPeaks' function with default settings. Remaining zeros values were imputed with two thirds the minimum value on a per mass basis. Compounds were identified by accurate mass, comparison of retention times to authentic standards or by accurate mass and also comparison of fragmentation patterns to MS/MS databases  36.
Sequences were processed using FROGS 3. 2 pipeline on Galaxy platform  39. Briefly, sequences were clustered in Operational Taxonomic Units (OTUs) using SWARM algorithm  40. Chimeric sequences detected by samples using UCHIME algorithm  41. A total of 464 858 reads were merged and processed and 437 504 sequences were kept after chimera removal. Singleton OTUs were excluded and the remaining 2 311 OTUs were affiliated with SILVA 138. 1 database using BLAST algorithm (97% sequence identity threshold).