dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analysis. The UNIVARIATE procedure of SAS (SAS 9. 3; SAS Institute Inc. , Cary, NC, USA) was used to test the normality of residuals for zootechnical data, alpha-diversity indices, and relative abundances of main bacteria phyla. Non-normally distributed data were subjected to log transformation and then used to assess the effect of yeast supplementation on each variable. All pairwise comparisons among the treatment groups were tested using Tukey's studentized range adjustment, and statistical significance was defined at P < 0. 05. Trends were discussed at P < 0. 10. Permutational multivariate analysis of variance (PERMANOVA; implemented in PRIMER-6 software, PRIMER-E Ltd, Plymouth Marine Laboratory) was used to detect significant differences between β-diversity measures of microbial communities.
Statistical Analysis A post-hoc power analysis was performed to determine the impact of the sample size using a small observed effect size (Cohen's d = 0. 2) and a probability level of 0. 05. Answers provided in any multiple-choice question with an "other" option or in the open-ended questions were structurally coded using QSR International's NVivo 11 qualitative data analysis Software (Version 11. 3. 1 777, QSR International Pty Ltd. , Burlington, MA, USA). Coding categories were drawn directly from single words or phrases used by participants. In the case of questions which asked participants to describe their involvement in the industry (equine education, industry involvement, and discipline involvement), pre-existing categories were collapsed for a more streamlined analysis and some additional categories were created based on open-ended responses from participants.
This was due to the large number of available categories initially provided to respondents. Descriptive analysis was conducted using IBM Corp's SPSS Statistics for Windows Version 24. 0 (IBM Corp. , Armonk, NY, USA, 2016). A Chi-squared test for independence (IBM Corp. 's SPSS Statistics for Windows Version 24. 0) was used to examine potential relationships between demographic factors and opinions regarding horse sentience and related questions from welfare-focused sections. Some categories were collapsed in the event of low counts (<5). Data provided in the "other" category of multiple-choice questions was reported on but not included in chi-squared tests due to low counts. In the case of significant (p > 0. 05) 2 × 2 Chi-squared tests, Fisher's Exact test was used to determine directionality.
, 2012). Recently, using the first crystal structure of a nematode Pgp, Cel-Pgp-1, resolved at a resolution of 3. 4 Å (Protein Data Bank code: 4F4C)  (Jin et al. , 2012) , high affinity binding of several anthelmintic drugs, including IVM, on Cel-Pgp-1 has been predicted by in silico docking calculations  (David et al. , 2016). To understand the respective physiological functions of Pgps in H. contortus, it is of interest to consider their sites of expression. In both C. elegans and H. contortus, IVM resistance has been linked to defects in the morphology of the amphids  (Freeman et al. , 2003; Urdaneta-Marquez et al. , 2014; Menez et al. , 2016). Cel-Pgp-6 and Cel-Pgp-13 are expressed in the amphids  (Zhao et al. , 2004). H. contortus does not have a homolog of Cel-Pgp-6, but it has a homolog of Cel-Pgp-13, and it was therefore of interest to characterize Hco-Pgp-13.
Amplification of the Hco-Pgp-13 cDNA sequence A pair of primers, Hco-Pgp-13-F1 and Hco-Pgp-13-R2 (Suppl. Table  S1 ), were designed using the Geneious software version 5. 5. 6. (http:// www. geneious. com/; PO Box 5677, Wellesley St, Auckland 1141, New Zealand), across the 3' end of the predicted sequence of Hco-Pgp-13 from the Sanger Institute (ftp://ftp. sanger. ac. uk/pub/pathogens/Haemonchus/contortus)  (Laing et al. , 2013). A first PCR was run using these primers and the reverse transcribed cDNA of whole adult H. contortus as template. A fragment of 3488bp was obtained and sequenced (Genome Quebec Innovation Centre, McGill University, QC, Canada) using eight primers, Hco-Pgp-13-F1 to Hco-Pgp-13-R8 (Supplementary Table  S1 ). Four more primers were designed to identify the 5′-end of Hco-Pgp-13 by nested PCR: the nematode spliced leader sequence SL1  (Blaxter and Liu, 1996) , a specific forward primer Hco-Pgp-13-F9 (Supplementary Table  S1 ) and two specific reverse primers Hco-Pgp-13-R10 and Hco-Pgp-13-R11 (Supplementary Table  S1 ).
The 887 bp PCR products thus obtained were sequenced and aligned to the first 3488 bp product with MultAlin software  (Corpet, 1988) , and the overlap of the amplicons confirmed. The full-length sequence was then aligned against the cDNA of the predicted sequence of Hco-Pgp-13 using MultAlin (Supplementary Figure  S1 ). 2. 4. Determination of Hco-Pgp-13 protein sequence, phylogenic analysis and calculation of TMD homologies relative to Cel-Pgp-1 The translation of Hco-Pgp-13 cDNA into protein sequence was performed using ExPASy -Translate tool (http://web. expasy. org/ translate/). The parameters of the protein (molecular weight, length) were calculated with ExPASy -ProtParam (http://web. expasy. org. / protparam/). The presence of N-and O-glycosylation motifs was predicted using ExPASy -ScanProsite tool (http://prosite.
Expasy. org/), as well as that of consensus motifs, including the Walker A and the less conserved Walker B motif. Multiple sequence alignment of Pgps of various organisms, including Hsa-Pgp (Supplementary Figure  S2 ), was performed using Muscle algorithm under Seaview software  (Edgar, 2004a (Edgar, , 2004b)). The prediction of amino acids located within the transmembrane bilayer was performed with the Protter tool  (Omasits et al. , 2014)  and the TMHMM Server v. 2. 0 (http://www. cbs. dtu. dk/ services/TMHMM/). The visualization of the topology of the full length protein sequence across the plasma membrane was represented using the Protter tool (Fig. 1 ). The TM helices and eight N-glycosylation motifs were represented as predicted by this program, N518 being the only one not previously predicted by ExPASy -ScanProsite.
A PhyML phylogenetic tree with all Hco-Pgps, all Cel-Pgps, Hsa-Pgp and Mmu-ABCB1a protein sequences (Fig. 2 ) was constructed using Seaview software from the multiple alignments previously performed with Muscle (Supplementary Figure  S2 ) after removal of NBDs from all the considered protein sequences. The locations of the TMDs of all the proteins of this alignment were deduced from Cel-Pgp-1 4F4C crystal structure  (Jin et al. , 2012). The first amino acid of TMD1 of each Pgp was identified as the one aligned to the first amino-acid of TM1 of Cel-Pgp-1, thus excluding the small extra-helix TMa and TMb  (Jin et al. , 2012)  not previously described in other ABC transporters, and considered to be part of the N-terminal region. The similarity and identity percentages of the TMDs of Cel-Pgp-1 with the TMDs of all other Pgps were then determined using BlastP (http://blast.
DMSO (final concentration was 1%) was used as solvent for the drugs and in the control measurements. The reaction was initiated by the addition of 5 mM ATP and stopped with 5% SDS solution after 5, 15 and 30 min of incubation. The amount of Pi released was determined at each time point in triplicate and the mean initial hydrolysis rate was calculated in nmol Pi/min/mg of total membrane protein (+/-SD). The vanadate sensitive activity values were estimated as the difference between the rate in the presence and absence of vanadate. For studying ACD-induced ATPase, in each of the different membrane preparations, data were normalized to 100% with respect to the vanadate-sensitive activity measured in the absence of added drug. For studying IVM modulation of ATPase activity data are presented as absolute values.
Construction of 3D models of Hco-Pgp-13 and in silico docking calculations All Modeller and Autodock calculations were performed using the computing facilities of the CEA-DSV/GIPSI (cluster Gabriel) at Saclay, France and of INRA (Genotoul) in Toulouse, France. 3D models of Hco-Pgp-13 were built using Modeller 9v12  (Sali and Blundell, 1993; Webb and Sali, 2014)  based on the crystal structure of C. elegans Pgp-1 (PDB: 4F4C, determined at a resolution of 3. 4 Å), as a template  (Jin et al. , 2012). As the Cel-Pgp-1 sequence was lacking the following amino acids: M1-R3, A52-E54, K666-E715 and G1307-K1321, the full-length sequence of Hco-Pgp-13 was modeled without the corresponding aligned residues: M1-S3, E668-L725, and G1304-T1317. The pairwise alignment was deduced from the multiple alignment (Supplementary Figure  S2 ) in order to improve the accuracy of the homology modeling alignment used as input for Modeller 9v12.
Results 3. 1. The Hco-Pgp-13 corrected cDNA sequence encodes a protein matching the topology of an ABC transporter with high sequence similarity with Cel-Pgp-12, Cel-Pgp-13 and Cel-Pgp-14 RNA was extracted from adult male and female H. contortus, reverse transcribed into cDNA and amplified. Several primers (Supplementary Table  S1 ) were designed along the predicted sequence of Hco-Pgp-13 (ftp://ftp. sanger. ac. uk/pub/pathogens/Haemonchus/contortus)  (Laing et al. , 2013). The full sequence obtained, named Hco-Pgp-13, corresponds to a 3954 base pairs (bp) coding cDNA from the ATG start codon to the TGA stop codon (Supplementary Figure  S1 ) and is representative of the transcript RNA present in the parasitic worms (GenBank No. KX844966). Compared to the gene sequence previously published  (Laing et al.
Tertiary structure of Hco-Pgp-13 was generated by homology modeling to Cel-Pgp-1 Since Cel-Pgp-1 is the only crystallographic structure of a nematode Pgp (Protein Data Bank: 4F4C), the homologies of Cel-Pgp-1 TMDs sequences with the TMDs sequences of all other aligned Pgps (Supplementary Figure  S2 ) were calculated using BlastP (Table  1 ). As expected, Cel-Pgp-1 presented the highest homology for TMDs to Hco-Pgp-1, with 63% identity and 79% similarity of residues, followed by Cel-Pgp-9 and Hco-Pgp-9. Interestingly, N-terminal regions, in the multiple alignment, showed a sequence which extends to 70-90 amino acids for Hco-Pgp-10, Hco-Pgp-13, Cel-Pgp-1, Cel-Pgp-10, Cel-Pgp-11, Cel-Pgp-12, Cel-Pgp-13 and Cel-Pgp-14, against 30-50 amino acids for the nineteen other Pgp sequences aligned, including Hco-Pgp-1 (Table  1 , bold, and Supplementary Figure  S2 ).
Topology and 3D structural models of Hco-Pgp-13 We first corrected the predicted Hco-pgp-13 cDNA from the H. contortus genome  (Laing et al. , 2013)  by identifying a misalignment of contigs due to a 30-nucleotide repeat in the previously published genomic sequence, absent in the full-length amplified cDNA. In addition, 90 single nucleotide polymorphisms (SNPs) were found in the amplified cDNA, similar to the 2. 3% frequency of SNPs reported in different H. contortus populations. Based on the corrected sequence (GenBank No. KX844966), the full-length cDNA allowed prediction of a protein containing 1137 amino acids (MW 146 kDa), with typical domain arrangement of full-size ABC proteins, including 2 TMDs, and 2 NBDs containing the ABC transporter family consensus motifs, consistent with a primary active transporter.
The ability to bind ACD and IVM was confirmed in vitro by measuring modulation of ATPase activity in cell membranes expressing Hco-Pgp-13. ACD specifically stimulated the basal Hco-Pgp-13 ATPase activity. The ACD half-activating concentration for Hco-Pgp-13 stimulation (EC 50 = 0. 6-1 μM) was higher than that for Cel-Pgp-1 (EC 50 ≈ 0. 05 μM)  (Jin et al. , 2012) ; however, the experimental conditions differed between the two sets of measurements. The in silico docking of ACD on Cel-Pgp-1 showed that it interacts with a comparable binding energy as with Hco-Pgp-13, at a similar site located at the cytosolic opening of the inner chamber (David et al. to be submitted). Since ATP hydrolysis is required to drive active translocation across cell membranes, our data indicate that ACD is transported by Hco-Pgp-13 similarly to Cel-Pgp-1.
Since a major effect of ML on nematodes is paralysis of the pharyngeal Fig. 4. Modulation of the ATPase activity of Hco-Pgp-13 by actinomycin D and ivermectin. Vanadate-sensitive ATPase activity was measured on freshly prepared membranes from either untransfected P. pastoris (wildtype (WT); black cross), or P. pastoris transfected with pPICZ-HuMOR-cmyc-his-tag vector (HuMOR; black circles) or with pPICZ-Hco-Pgp-13-cmyc-his-tag vector (Hco-Pgp-13; white circles), at 37 °C, as a function of ACD concentration in the absence (white and black symbols) or presence (grey circles) of 5 μM IVM (A) or IVM concentration (B). In Panel A, the vanadate-sensitive activity, measured as described in Material and Methods, was normalized to the control activity determined without drug for the same strain. The data are the mean ± SD of triplicates made on two or three independent experiments carried out on HuMOR, Hco-Pgp-13 and WT membranes, respectively.
The lines are fits using GraphPad PRISM. muscles, Hco-Pgp-13 expression in pharyngeal neurons might protect worms from IVM effects. The expression of Hco-Pgp-13 in the epithelial cells of the larvae and adult gonad resembled previous finding of Hco-Pgp-9. 1 expression in the uterus  (Godoy et al. , 2016) , and an involvement in reducing toxic compounds reaching embryos, as was shown in C. elegans  (Brinke et al. , 2013)  and mammalian placental tissue  (Nakamura et al. , 1997; Kolwankar et al. , 2005). The Hco-Pgp-13 expression matches the global transcript localization of all of its closest ortholog genes in C. elegans with Cel-Pgp-12 expressed in the excretory cell, Cel-Pgp-13 in the posterior intestine and amphids of adults, Cel-Pgp-14 in the anterior region and first bulb of the pharynx in the adults and larvae, and Cel-Pgp-15 in the adult head and tail neurons, and in the embryo  (Zhao et al.
Acknowledgements The authors thank  Lea Lasvaux  and  Melanie Gentil  for their help in the ATPase activity measurements and Western-blot experiments,  Thierry Gauthier  for providing his expertise and access to confocal microscope. We also thank  Fabien Jourdan  and  Clément Frainay  for technical support with bioinformatics experiments and the  Genotoul Bioinformatics  hardware infrastructure that was used for computing. We also acknowledge the staff of the computing facility of the  Biology division of CEA/DRF/GIPSI at Saclay  for help and access to the national cluster Gabriel. This work was supported by the  Natural Sciences and Engineering Research Council of Canada  (grant No. RGPIN/2777-2012 ), the  FRQNT Centre for Host-Parasite Interactions, Quebec , and  EMIDA ERA-NET  project  CARES  n  11-EMID-003-02.
To calculate the toxic pressure, chemical analyses of compounds are used together with corresponding laboratory data. The toxic pressure of a mixture is determined by quantifying the potentially affected fraction (PAF) using species sensitivity distribution modelling for each compound in the mixture. In the following, mixture modelling is applied to estimate the mixture toxic pressure  [264]. This method can be used either to calculate water quality standards, to prevent adverse effects or to predict potential effects of the current exposure situation by calculating the multiple-substances potentially affected fraction (msPAF). The program to calculate the msPAF or rank substances based on their toxic contribution is freely available  [265]. To apply this method for eco-neurotoxicity risk assessment, laboratory data for neurotoxic effects for a variety of species are needed.
One possibility to reach this is to replace the third quadrupole filter by a high-resolution mass analyser (HRMS). The time-of-flight (TOF) or Orbitrap technology is used in such hybrid instruments. A further benefit of using HRMS is the detection of all ions which are generated in the ion source. Thus, the datasets can be screened for substances which were initially not anticipated (so-called non-target screening). In gas chromatography with mass spectrometric detection (GC-MS), the separation of analyte and matrix compounds (via the gas phase) usually takes place in capillary columns. Electron ionization (EI)-i. e. the interaction of energetic electrons with gas phase molecules-leads to ionization and fragmentation of analyte molecules. The fragment ions are subsequently detected. For the analysis of metals, the preferred analytical methods are atomic absorption spectroscopy (AAS) or inductively coupled plasma mass spectrometry (ICP-MS).
Computational toxicity approaches combined with literature-mining approaches and expert knowledge offer exciting ways to do this. Extensive work has already been performed by many research groups worldwide, screening drugs and potential neurotoxicants using various bioassays and collected into online resources such as ChEMBL and PubChem, including for instance the PubChem Classification Browser allowing sophisticated queries (e. g. results for Parkinson's disease  [288, 289]. In particular, the U. S. EPA National Center for Computational Toxicology provides their data for downl oad  [290] , including their in vitro data, and is incrementally releasing their data and computational models through the CompTox Dashboard  [291]. This provides access to chemistry data, integrates to in vitro assay and exposure data, and links to external resources and literature-mining functionality  [292].
For all of these AOPs, the focus is mostly on human health, although in some cases fruit fly, zebrafish or bobwhite quail data are included as weight of evidence. About 25 other AOPs currently being developed in the AOP-Wiki with a primary human toxicological perspective mainly focus on thyroid hormone disruption, and adrenergic, dopaminergic, serotonergic and opioid pathways. AOPs covering neurotoxicity in an ecotoxicological context (about 25 in total in the AOP-Wiki) are at this point in time less advanced in general. Development of eco-neurotoxicity AOPs currently focuses on interference with cholinergic pathways leading to colony loss in bees and acute mortality in multiple species  [309, 310] , serotonergic (5-hydroxytryptamine transporter, 5-HTT) pathways leading to population changes in bivalves  [311] , and histamine, glutamate and GABA pathways, while some well-characterized pathways in mammals are currently lacking.
By combining the data from studies that measured the concentration of several hundred different chemicals in three European river catchments (Danube, Rhine, Mulde/Saale), compounds with neurotoxicity/neuroactivity to any species were found as the largest group of chemicals with known MoA or target accounting for 13% of the 426 chemicals that were detected in at least one of the catchments  [9]. By assigning a major molecular target to each of the neurotoxic/neuroactive chemicals in the study of Busch et al. using databases (DrugBank, IRAC) and Fig. 4  AOP network showing all AOPs relevant to eco-neurotoxicity that are available in the AOP-Wiki (https ://aopwi ki. org; Accession date: April 30, 2018; AOP numbers  16, 77, 78, 79, 80, 82, 87, 88, 89, 90, 91, 93, 94, 95, 97, 98, 99, 113, 160, 161, 178, 195, 197, 203, 204 ; Network constructed using Cytoscape 3.
Acknowledgements We thank the  Federal Ministry of Education and Research (BMBF)  founded project NeuroBox and the  Norman Network  (http://www. norman-netwo rk. com/) for funding this study. Additionally, this work was conducted within the framework of the  Joint Research Program  of the  Dutch Water companies  ( BTO2018-2023 ) and the  SOLUTIONS  project (European Union's  Seventh Framework Program  for research, technological development and demonstration under Grant Agreement No. 603437 ). Henner Hollert is Editor-in-Chief of this Journal.
Immunohistochemical Examinations RNALater-fixed tissues of the ileum and cecum of 24 birds per group were embedded in paraffin, and 5 μm sections were cut and stained with haematoxylin and eosin. The villus length was measured in the ileum by random measurement of 10 villi per section and per animal using image analysis software (Leica Application Suite LAS V3, Wetzlar, Germany) as described previously  (Teirlynck et al. , 2009). Only intact villi were measured, i. e. , villi for which the tip as well as the base were in the plane of the section. To quantify the infiltration of T-lymphocytes in the cecum and ileum, immunohistochemistry was performed as described previously  (Van Immerseel et al. , 2002)  using a monoclonal antibody targeting CD3  (Dako, Glostrup, Denmark). The number of T-lymphocytes in the different sections was evaluated using image analysis software (Leica Application Suite LAS V3, Wetzlar, Germany) measuring the average area percentage occupied by labeled cells from 10 microscopic fields per tissue and per animal at a magnification of 400x.
The PCR 2 products were purified, and the quality and the fragment length were controlled using an Agilent DNA 7500 DNA chip (Agilent Technologies Inc, Santa Clara, CA 95051, USA) following the manufacturer's protocol. The resulting products were purified and loaded onto an Illumina MiSeq cartridge according to the manufacturer's instructions (Illumina Inc. , San Diego, CA). The quality of the run was internally checked using control libraries generated from the PhiX virus (Illumina PhiX control; Illumina Inc. , San Diego, CA) as previously described  (Drouilhet et al. , 2016). The resulting sequences were pre-clustered and then independently divided into operational taxonomic units (OTU). Singletons were eliminated, and the non-redundancy of the OTU was verified. The phylogenetic affiliation of one representative sequence per OTU was performed using the LTP database (www.
Statistical Analysis Regarding the variability of the parameters and the objective of the study (i. e. , the magnitude of the effect to detect statistically), the number of replicates to achieve a power of at least 0. 80 was 90 animals per treatment to detect a variation of 3% on the BWG at 14 d with a type I error set at 5%. The data were analyzed with IBM R SPSS R Statistics 22. 0 software. The Shapiro-Wilks test was used to test the normal distribution of the data. The results are given as the means ± SD. The sugar composition, AX content, A/X and DP were analyzed using oneway ANOVA. The BWG, FCR, FI, villus length, L-cell count, and T-lymphocyte infiltration were subjected to one-way ANOVA followed by a post hoc Tukey's multiple comparison test. The statistical power was ≥80%. Statements of statistical significance were based on P ≤ 0.
05. The pyrosequencing data were analyzed using the Phyloseq package  (McMurdie and Holmes, 2013)  in R software (Version 3. 2. 3). The α-diversity of the cecal and ileal microbiota, defined as the species richness within each sample (broiler), was measured using the Shannon index. The Shannon index (H') was calculated as H' =pi Ln pi, where pi is the proportion of individuals found in the i th OTU. Higher values indicate greater diversity, with 0 = complete homogeneity.
6 kDa, 54. 1 mL/g and 54, respectively). High performance anion exchange chromatography showed the absence of oligosaccharides with DP < 10 (data not shown). NMR was used to investigate the AX structure of the WE and WC fractions. Both fractions had a very similar substitution pattern of the xylose backbone by arabinose residues, as already suggested by their similar A/X ratio. WE contained 73% of un-substituted, 13% of mono-substituted, and 14% of di-substituted xylose, while WC contained 72, 13, and 15%, respectively.
ACKNOWLEDGMENTS The present study was financed by a grant from  Adisseo France SAS (Commentry, France). We thank  Laurent Cauquil  ( INRA Toulouse ) and  Friedrich Rouffineau  ( Adisseo France ) for assistance in the statistical analyses. We thank  Agnès David ,  Michèle Dalgalarrondo ,  Sylviane Daniel  ( INRA Nantes ),  Fabrice Frassetto ,  Sandrine Freuchet  ( ONIRIS-Nantes ),  Christian Puttevils ,  Delphine Ameye  ( Ghent University ), and all of the technical team at  CERN-Adisseo  for technical assistance. The authors' contributions were as follows: N. Y. was involved in the study design, conducted the experiments and the analysis, data interpretation, statistical.