dataesr/scientific-paragraphs-categorization huggingface dataset:
Selected farms were visited from January 2015 to September 2017, and individual blood and urine samples from 19 animals were collected (aiming for !1 seropositive animal with a 95% confidence interval, using a conservative seroprevalence figure of !15% on a reference population of 1000 individuals; seroprevalence estimates from background serologic data in Uruguay are actually higher; the number of individual animals to sample was calculated with the software WinEpi http://www. winepi. net). Due to logistic constraints, in a few cases the number of animals per herd was slightly higher, overall sampling a total of 963 individual animals. Individuals to be sampled in each farm were selected according to recorded history when available, prioritizing animals with clinical signs of acute disease (especially calves with rectal temperature ! 39.
Determination of Leptospira species by PCR amplification and partial sequencing of the 16S ribosomal RNA gene DNA from Leptospira spp. bovine and human isolates were purified from 1 mL of EMJH culture using the PureLink Genomic DNA MiniKit (Invitrogen). Primers LeptoA (5´-GGCGGC GCGTCTTAAACATG-3´) and LeptoB (5´-TTCCCCCCATTGAGCAAGATT-3´) were used to amplify the 5'-terminal 331 bp fragment of the 16S rRNA gene (rrs) as previously described  [26]. The resulting amplicons were sequenced in both senses using internal primers LeptoC (Forward) (5´-CAAGTCAAGCGGAGTAGCA-3´) and Rs4 (Reverse)(5´-TCTTAACTGCTG CCTCCCGT-3´). Sequence quality was verified with the Chromas software, and consensus sequences were defined using BioEdit. All rrs sequences were deposited in GenBank (S2 Table ). Consensus sequences were then compared with available sequences in GenBank using BLAST.
Multilocus variable-number tandem repeat analysis Multilocus variable-number tandem repeat (VNTR) analyses were performed according to published methods  [27]  using five discriminatory markers for VNTR loci 4, 7, 10, Lb4 and Lb5. Purified DNA from each isolate was used to amplify the VNTR4, VNTR7 and VNTR10 loci in L. interrogans, and the VNTR10, VNTRLb4 and VNTRLb5 loci in L. borgpetersenii. The GelAnalyzer 2010a software (http://www. gelanalyzer. com) was used to analyze the ethidium bromide-stained agarose electrophoresis gels, in which PCR products were resolved in parallel to 100-bp DNA ladder (Thermo Scientific) as molecular weight marker. The number of repeats for each VNTR locus was determined as: number of repeats = [PCR product size(bp)flanking region (bp)] / repeat unit length (bp).
Partial secY gene sequencing and analysis DNA from Leptospira spp. bovine and human isolates were purified from 1 mL of EMJH culture using the PureLink Genomic DNA MiniKit (Invitrogen). The secY gene was partially amplified by PCR with primers SecYF (5´-ATGCCGATCATTTTTGCTTC-3´) and SecYR (5´-CCGTCCCTTAATTTTAGACTTCTTC-3´) as described  [28]. The resulting 549 bp amplicon was sequenced in both senses. Sequence quality was verified with the Chromas software, and consensus sequences were defined using BioEdit. All secY sequences were deposited in GenBank (S2 Table ) and compared to those available in PubMed, MLST (https:// pubmlst. org/leptospira) and PATRIC (https://www. patricbrc. org) [29]  databases. The phylogenetic analyses based on secY sequences were performed with MEGA 6. 0 software (www.
Phylogeny of Leptospira isolates based on secY gene sequence analysis Genetic analysis of the 501bp secY allele was performed on the 40 typed isolates described in this work. Comparison to other L. interrogans (serovars Pomona and Canicola), L. borgpetersenii (serovar Hardjo) and L. noguchii sequences, obtained from other geographical regions and available in public databases, allowed to build a picture of related groups. Also included in this analysis were secY sequences obtained from 4 Leptospira strains recently isolated from human infections in Uruguay by one of the groups of our consortium  [12, 13]. Only one homogeneous cluster was observed for the L. interrogans secY sequences, indicating that bovine isolates from Uruguay belonging to this species have close homology with isolates from South America (mainly from Brazil and Argentina)  [31].
The analysis involved 76 partial sequences of the secY gene including the 40 bovine isolates from Uruguay that we are now reporting. Uruguayan strains from bovine hosts (in blue) and human patients (green) are compared to 32 additional sequences (in red) corresponding to isolates obtained elsewhere and from a variety of hosts, as indicated within brackets. Asterisks indicate the known serovar for isolates where such information is known, following the code: Ã serovar Pomona ÃÃ serovar Panama ÃÃÃ serovar Autumnalis ÃÃÃÃ serovar Hardjo. Isolates obtained in Uruguay are named according to their strain denomination as "IP" (Institut Pasteur Montevideo) or "IH" (Instituto de Higiene) followed respectively by a 7-or a 4-digit number. GenBank accession numbers are indicated in parentheses. Well separated phylogenetic clades have a correspondence to different Leptospira species as indicated toward the right of the figure.
Sequences from 4 human isolates from Uruguay (green labels) were also included and plotted in comparison to 4 sequences corresponding to reference strains obtained elsewhere (red labels) and from different hosts, as indicated within parentheses. Isolates obtained in Uruguay are named according to their strain denomination as "IP" (Institut Pasteur Montevideo) or "IH" (Instituto de Higiene) followed by a 7-or 4-digit number, and after the vertical bar the GenBank accession number is reported for each one (S2 Table ). Well separated phylogenetic clades correspond to different Leptospira species as indicated toward the right of the figure. The Patoc strain at the bottom of the panel belongs to the saprophytic species L. biflexa, and is included as a phylogenetic distance reference. (DOCX).
Isolates obtained in Uruguay are named according to their strain denomination as "IP" (Institut Pasteur Montevideo) or "IH" (Instituto de Higiene) followed respectively by a 7-or a 4-digit number. GenBank accession numbers are indicated in parentheses. Well separated phylogenetic clades have a correspondence to different Leptospira species as indicated toward the right of the figure. The Patoc strain at the bottom of the panel belongs to the saprophytic species L. biflexa.
Acknowledgments We thank  Julie Collins Emerson  and  Peter Wilson  ( Massey University, Palmerston North, New Zealand );  Walter Lilenbaum  and  Ana Paula Loureiro  ( Universidade Federal Fluminense, Rio de Janeiro, Brazil ); and  Pascale Bourhy  ( Institut Pasteur, France ), for their helpful suggestions and lively discussions. We also thank  Dr. Jorge Mattos  ( MGAP, Uruguay ) for key assistance in obtaining samples at slaughterhouses.
This results in a tiered approach for genotoxicity testing, starting with a combination of several in vitro methods. In case of conflicting results, a suited in vitro or in vivo followup study needs to be chosen, in accordance with the relevant legal framework (e. g. , animal testing is prohibited for cosmetic products and ingredients in Europe  (Regulation No 1223 , EC, 2009a). A decade ago, it was shown that with the number of in vitro genotoxicity tests combined, the chance to obtain 'misleading' positive results rises  (Kirkland et al. , 2005). Several actions have been undertaken or are still underway to overcome this challenge, striving for a scientifically robust genotoxicity assessment that avoids in vivo follow-up tests  (Corvi and Madia, 2017; Kirkland et al. , 2007). These include the improvement of existing tests, the development of novel tests, the establishment and exploration of approaches to optimise in vitro testing accuracy, the development of databases and reference chemical lists  (Corvi and Madia, 2017).
g. physicochemical information, ADME and pharmacokinetics, mechanistic information, and in vitro and in silico methods) into Integrated Approaches to Testing and Assessment (IATA) (EURL ECVAM, 2014). The development of such IATA is challenging because of the limited mechanistic understanding of the numerous Adverse Outcome Pathways (AOPs) and modes-of-actions underlying systemic toxicity. There are several projects that aim to enhance the mechanistic understanding of AOPs and provide innovative methodologies for systemic toxicity testing, such as the EU FP7 SEURAT-1 project  (Gocht et al. , 2015) , its H2020 successor Eu-ToxRisk  (Daneshian et al. , 2016) , the Tox21 programme (Attene-Ramos et al. , 2013) and the ToxCast programme  (Judson et al. , 2010). It is expected that eventually mode of action and associated AOPs will provide a framework for the organization and integration of non-animal data and other relevant information to predict systemic toxicity for decision making.
Within the ab initio approach of the Cosmetics Europe Long Range Science Strategy the implementation of an in vitro safety pharmacology screen that covers a broad range of targets including receptors, ion channels, transporters, enzymes etc may help to avoid any undesirable pharmacological properties of cosmetic ingredients. In addition, this could serve to increase the knowledge on the mode of action. In Europe, as for acute toxicity, the SCCS states that "for repeateddose toxicity testing, currently no validated or generally accepted alternative method is available for replacing animal testing" (SCCS, 2016). The SCCS may accept nevertheless, on a case-by-case basis, methods that are scientifically valid, but have not necessarily gone through the complete validation process, if they have a sufficient amount of experimental data proving their relevance and reliability including positive and negative controls  (SCCS, 2016).
Waiving of the two-year carcinogenicity studies The EPAA has sponsored a project aiming at the reduction in the use of animals for assessing the potential for carcinogenicity, whilst identifying opportunities for improving the science supporting the regulatory testing of medicines and chemicals. In this project, the University of Wageningen collaborated with the Dutch Medicines Evaluation Board to compile and analyse a database on active pharmaceutical ingredients. The aim was to confirm and expand previous investigations by  Sistare et al. (2011) , and identify opportunities for waiving the two-years carcinogenicity studies based on in vitro genotoxicity testing and the results of (sub-)chronic toxicity studies. The study analysed 289 pharmaceutical compounds. In addition to the histopathological approach proposed by  Sistare et al.
(2011) , the pharmacological properties of the tested compounds also taken into account  (van der Laan et al. , 2016). When integrating the pharmacological properties of the compounds with respect to the presence or absence of a direct or indirect proliferative action, the results showed a prediction rate of 92% for non-carcinogens compounds and 98% for carcinogen compounds (van der  Laan et al. , 2016). These data provide evidence that a waiver could be granted based upon existing knowledge gathered during the earlier development of the compound, and that a two-year carcinogenicity study in rats could be waived without compromising human safety. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) is currently evaluating the possible revision of the rodent carcinogenicity testing of pharmaceuticals (ICH S1).
, 2014). The performance of an integrated approach to testing and assessment (IATA) designed to predict rodent genotoxic carcinogenicity covering different genotoxic mechanisms causing cancer has also been investigated by  Petkov et al. (2016). The IATA is docked to the OECD toolbox and uses measured data for different genotoxicity endpoints when available. Alternatively the system automatically provides predictions by SAR genotoxicity models. The study made use of the EU Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM) genotoxicity and carcinogenicity consolidated database of Ames positive chemicals which compiles available genotoxicity and carcinogenicity data for 726 Ames positive chemicals originating from different sources as recommended within an EURL ECVAM workshop  (Kirkland et al.
Miracidia used for drug coculture experiments were processed independently, as described below (histone methyltransferase inhibitors study). Data for cercariae and adult worms were obtained from (i) mixed sex infections or (ii) by monomiracidial infection of BgBre snails  [19]  and analysis of clonal female cercariae and adults. This latter approach allowed for a more detailed analysis without confounding genotype or sex effects but was done only for the female sex. Cercariae were collected three times from a single snail, 32-54 days after infection by gently pipetting from spring water, avoiding mucus and feces, and subsequently sedimented on ice. Water was removed, and cercariae were kept separately at -80˚C before being used for ChIP-Seq. Nine hundred of the same (single sex, clonal) cercariae were used to infect three mice (300 cercariae/mouse), as described in  [20].
Quality control, alignment and peak calling All data processing was performed on a local GALAXY instance (http://bioinfo. univ-perp. fr [29] ). Read quality was verified using the FastQC toolbox (https://www. bioinformatics. babraham. ac. uk/projects/fastqc/). All samples had a minimum average read quality score of 30 over 95% of their length, and no further cleaning steps were performed. Sequences were aligned to the S. mansoni reference genome v5  [30]  with Bowtie v2. 1 [31] using parameters-end-to-end,-sensitive,-gbar 4. BAM files generated by Bowtie2 were sorted and then filtered for unique matches with samtools v1. 3. 1  [32]  (samtools view -Sh -q quality value 40-42-F 0x0004 -| grep -v XS:i). PCR duplicates were also removed using samtools (samtools rmdup). Although not mandatory, we found that performing random sampling to use the same amount of uniquely mapped reads for each sample and each histone mark improved sensitivity and specificity when looking for chromatin structure differences.
Chromatin landscape We started our analyses by characterizing the genome-wide chromatin landscape in five developmental stages of S. mansoni. We used chromstaR (v1. 2. 0) for peak detection and comparative analysis, using epialleles that chromstaR detected in all replicates of a given developmental stage  [35]. ChromstaR is an R package that uses Hidden Markov Models (HMM) to perform computational inference of discrete combinatorial chromatin state dynamics over the whole genome. It can perform uni-or multivariate analyses using several replicates and identifying common and different peaks between conditions  [35]. ChromstaR was processed in two steps: (1) we fitted a univariate Hidden Markov Model over each ChIP-seq sample individually (i. e. each replicate for each developmental stage) and (2) we performed a multivariate HMM over the combined ChIPseq samples.
Data availability statement Chromatin landscapes of the different life cycle stages are available at the Schistosoma mansoni genome browser of http://genome. univ-perp. fr and as TrackHub at http://ihpe. univ-perp. fr/ acces-aux-donnees/. ChIP-Seq reads are available at the NCBI-SRA under the BioProjects numbers PRJNA219440 and PRJNA236156. Details are available in Tables  8  and 9.
In addition to these expeditions, another seven were conducted along the Petrópolis-Teresópolis Traverse trail, from which 47 samples were gathered. The samples from the felids that were caught and handed over to Parnaso were gathered by removing the feces from the floor of the enclosures where these animals were temporarily kept. These animals comprised one specimen of L. wiedii and one of L. guttulus. In addition to these samples, feces were also collected from a specimen of P. yagouaroundi that was found run over on highway BR-116. This animal was necropsied at the Park's facilities. At the time of sampling, all the fecal material was stored in plastic collectors of capacity 80 mL without chemical preservative, and these were identified with a number and the date of collection. The sampling points on the trails were georeferenced and analyzed using the Arc Gis  software.
Data analysis Fecal samples were considered positive when at least one stage of the life cycle of a parasite (egg, larva, cyst or oocyst) was detected. The frequency of detection was obtained by dividing the number of positive samples by the total number of samples collected, with emphasis on the samples from which felids were identified through trichological analysis. The data were presented descriptively. The lowest taxonomic level possible for each parasite was identified using the morphometric patterns of the various stages of the life cycles of the parasites.
Discussion Veterinary use of antimicrobials is believed to contribute to the emergence of antimicrobialresistant strains. Pathogenic Leptospira is responsible for chronic infections in livestock leading to abortions and other reproduction disorders. Some serovars are particularly associated with chronic infection, for example Hardjobovis in cattle and Pomona in swine. Re-infections of animals in the same farm are frequent  [11]. There is currently no comprehensive data about the antibiotic susceptibility of Leptospira strains in farm animals. Evaluating the antibiotic susceptibility of Leptospira strains in livestock provides a baseline for monitoring trends in antimicrobial resistance in this species. We therefore analyzed susceptibilities of strains isolated worldwide over an 80-year period to the antibiotics most commonly used in veterinary medicine.
End-point fluorescence reading (Ex 540 nm /Em 588 nm ) was done after incubation with 10% (vol/ vol) resazurin solution (0. 125 mg/mL, Sigma) for 24 h. Alternatively, MIC 50 was determined by the broth microdilution method 36 adapted for M. ulcerans. A volume of 150 μl of M. ulcerans culture (final OD 600 of 0. 02) was added to well containing a dose range of antibiotics, and the assay plates were incubated at 32 °C for 15 days. OD 600 values were recorded using a Cytation 5 Cell Imaging Multi-Mode Reader, and MIC 50 curves were plotted using the GraphPad Prism 5 software. MBC determination. M. ulcerans S1013 at an OD 600 of 0. 01 was incubated with and without Q203 at 32 °C. Q203 potency was tested at a concentration of 1, 4 and 16 nM. Viability was determined by CFU determination on agar plates over a period of 90 days.
Acknowledgements This work was supported by the  Singapore Ministry of Health's National Medical Research Council  under its  Cooperative Basic Research Grant  (Project Award  NMRC/ CBRG/0083/2015 ), and the  Lee Kong Chian School of Medicine, Nanyang Technological University Start-Up  Grant (K. P. ). S. S. T. was supported by an  Interdisciplinary Graduate School Scholarship  from the  Nanyang Technological University. The design and syntheses of IPAs ND-10885 and ND-11176 were supported by  NIH  grants  R01 AI054193  and  R37 AI054193  (M. J. M and G. C. M. ). We thank  M. Berney  for critical reading of the manuscript.
The perspective of a possible ban on surgical castration of male pigs in the EU is a real challenge for pork production systems aiming at (very) high-quality products. Information was collected from a total of 272 situations in 16 European countries, including 170 situations related to EU protected designations (Database of Origin & Registration (DOOR) database) and 102 other situations related to high-quality products or differentiated production systems, in order to evaluate their potential sensitivity to the use of entire male pigs along four dimensions: BT_Inc, likelihood of increased levels of boar taint compounds compared with conventional production of entire males; BT_Per, extent to which (some of) the associated pork product(s) are susceptible to perception of boar taint by consumers; FatQQ, likelihood that the quality of (some of) the related products is decreased due to the lower fat quantity and quality in entire males; Manag, increased likelihood of animal management and welfare problems compared with conventional production of entire males.
Sources of information The information used in the present study originated from the Database of Origin & Registration (DOOR) database and the CASTRUM network. The DOOR database  (DOOR, 2016)  contains the specifications attached to all the EU protected designations. The DOOR project supports the agricultural product quality policy by providing a modern IT system for the dissemination of public data with regard to registered Protected Designations of Origin (PDOs), Protected Geographical Indications (PGI) and Traditional Specialities Guaranteed (TSG) through Europe  (DOOR, 2017). A total of 170 situations (40 PDO, 116 PGI and 14 TSG) related to pork products were selected. The information used for the DOOR situations was extracted from the specifications in the database and completed as needed by national documents and/or the expertise of the national contact persons (see below).
The CASTRUM network was built within the CASTRUM project (CASTRUM, 2017 and acknowledgement section). The national contact persons identified in each of the 16 countries included in the study identified 102 other situations that were added to the 170 extracted from the DOOR database. The information used for the 102 situations came from national or chain specifications, literature and the expertise of the national contact persons themselves and/or other experts enlisted for the study. National contact persons were mostly scientists with a good knowledge of pork production chains in their respective countries, whereas the other Bonneau, Čandek-Potokar, Škrlep, Font-i-Furnols, Aluwé and Fontanesi experts were mostly actors in the studied production chains (industry, extension services, etc. ).
Results Situations included in the study Out of the 202 designations related to pork products that were first extracted from the 1566 designations contained in the DOOR database, 170 situations were included in the study. In addition, 102 situations were suggested by national contact people, resulting in a total of 272 situations included in the analysis, located in 16 European countries (Table  1 ; Supplementary Table  S1 ). Mediterranean countries accounted for most of the situations and, among them, four countries (France, Portugal, Italy and Spain) accounted for 64% of the situations. Dry products were, by far, the most common products, representing 59% of the total situations and 79% of the DOOR situations. Fresh products (Fresh meat + Fresh processed) represented more than half of the non-DOOR situations.
, 2012; Aluwé et al. , 2013). Genetic, nutritional and management factors that have a major influence on androstenone and skatole levels  Values within a row with different superscripts differ significantly at P <0. 05. 1 Average level for continuous variables ranging from 0 to 1; percentage of yes for discrete variables. 2 Situations extracted from the Database of Origin & Registration (DOOR) database (see Table  1 ). 3 ANOVA for continuous variables; χ 2 test for discrete variables. Bonneau, Čandek-Potokar, Škrlep, Font-i-Furnols, Aluwé and Fontanesi  (Zamaratskaia and Squires, 2009)  could not be taken into account with the limited information available in this study. Weight and age at slaughter have a limited role in accounting for boar taint compound levels in situations where their range of variation is limited  (Walstra et al.