dataesr/scientific-paragraphs-categorization huggingface dataset:
Data collection. A pretested questionnaire was then completed, by reading a pretested questionnaire aloud to the selected participants and them completing it with their answers within their sight. The questionnaire was written in French, and was translated into local languages when read aloud to participants. The patients were interviewed just after their diagnosis, and the corresponding controls were interviewed at about the same time. For most of the youngest participants, family members were present during the interview and confirmed the responses given by the child. The questions related to contact with water and changes in behaviour over time. The interviews were designed to identify the targeted periods and to provide benchmarks over time to minimise bias. The questionnaire is available in the S1 and S2 Datas.
3. 4 Variables. The variables recorded in this study include: sociodemographic status (e. g. , age, sex, education, region of residence, professional activities), life habits, water uses and activities involving contact with water (e. g. , washing clothes, bathing, swimming, drinking, or cooking with river water or well water) and relation to disease (i. e. what did the cases know about Buruli ulcer before they contracted the disease and what did the corresponding controls known during the same period, and any special precautions taken in terms of hygiene, sanitation and other ancestral practices against Buruli ulcer). Quality control was performed systematically for all the data collected. Buruli ulcer diagnosis was treated as the dependent variable, and sociodemographic status (e. g. , age, sex, education, region of residence, professional activities), life habits, water uses and activities involving contact with water (e.
Spatial analysis Altitude data were collected from Landsat's 30-metre SRTM (Shuttle Radar Topography Mission). These data were particularly useful for defining the lowlands. Data concerning the area covered by water were extracted from radar images. The Sentinel 1 sensors of the European Space Agency (Copernicus) provided at least one image per month. On the radar images obtained, the pixels corresponding to water have values below 0. 05. A monthly time series of Sentinel 1 radar images consisting of 30 images was obtained over the southern part of the Ouemecatchment area for 2018. Using this time series, we were able to extract the area of the Ouemebasin covered by water and to reconstitute, for each district, the area under water for each month of 2018. We also distinguished between areas permanently and seasonally under water.
DNA was extracted according to the kit manufacturer's protocol and eluted in 50 μL RNase-and DNase-free water. 5. 3 qPCR. Oligonucleotide primer and TaqMan probe sequences were selected from the GenBank IS2404 sequences and the ketoreductase B (KR) domain of the mycolactone polyketide synthase (mls) gene from the plasmid pMUM001  [22]. We performed qPCR in a reaction volume of 20 μL containing qPCR mix, 300 nM primers, 100 nM TaqMan probe and 5 μL DNA or sterile water as a negative control. Reactions were run on an AriaMx Thermocycler (Agilent), with the following program: 10 min at 95˚C and 40 cycles of 15 s at 95˚C and 1 min at 60˚C. Quantitative readout assays were set up, based on an external standard curve generated with a ten-fold dilution series (over six orders of magnitude) of M. ulcerans DNA.
Acknowledgments We would like to thank  Life Science Editors  for editing services. We would like to thank the  ESA (European Space Agency)  for free access to the Sentinel  1&2 data  and the  THEIA  project supported by the  CNES  for providing Spot 6 images. We thank the  "Services de la Direction de l'Information sur l'eau" of the Ministry of Water at Cotonou, Benin  for sharing the datasets relating to the spatial distribution of water in the Ouemeand Plateau Districts. We would like to send our sincere thanks to  Bello Ade  ´yèmi, motorcyclist and translator for the field observation study.
Statistical analyses were done using SPSS21. 0. No statistically significant association was observed between ERAP1 rs30187 and rs10050860 polymorphisms and AS risk (p<0. 025). However, stratification by age and gender showed that the minor allele of rs30187 reduces the risk of developing AS in women with age >30 (OR=0. 13[0. 04-0. 39], p =6. 10 -5 ), TT genotype (OR=0. 09[0. 01-0. 6], p=5. 10 -3 ) and dominant model (TT+CT) (OR=0. 14[0. 03-0. 6], p= 4. 10 -3 ) in a sample of the Algerian population. Indeed, in our study, ERAP1 rs10050860 polymorphism did not predispose us to AS in our population. For the first time, the allelic and genotypic frequencies of ERAP1gene polymorphisms in the Algerian population. This work enriches the library of information about the ERAP1 gene.
Data analysis Behavioural data were analysed using ANOVA where repeated measures per horse (1-39) across observation days (1-8) was considered and with 'total insect-repelling behaviour' as response variable. The explanatory variables included treatment (indoor access vs. no access) as fixed factor, the continuous variables 'H-trap tabanid catch' (count: 0-285), 'outdoor sticky trap catch' (count: 3-192), and 'light trap mosquito and biting midges catch' (count: 0-337) as covariates plus all two-ways interactions between treatment and the three types of insect catches. The model had location (1-3) as random factor and the time structure was modelled using compound symmetry  (Littell et al. , 1996). The model was reduced by stepwise removing insignificant terms (P > 0. 10), starting with the two-way interactions and removing the term with highest P-value first.
The statistical software SAS (version 9. 4) was used for analysis (using the procedure 'Mixed'). Kenward-Roger correction was used for the denominator degrees of freedom  (Littell et al. , 1996). Compliance to the demands for dispersion (normal distribution) and variance homogeneity were evaluated from plots of the model residuals at each step. Since tail swishing and skin shivering were the predominantly occurring behaviours and therefore accounted for the main part of 'total insect-repelling behaviour', the same model was used to analyse the sum of other insect-repelling behaviour (i. e. , sum of head and body shake, stomp, ear flick, groom self, social groom and roll). Since baseline data on cortisol levels could not be collected in this  experimental setup and the treatment groups were not balanced according to cortisol levels, a direct comparison of FCM levels between treatments is not meaningful.
Weather conditions and insect trap catches An overview of the weather data on the eight observation days in each study location is provided in Table  4. The average indoor temperatures were slightly higher than the outdoor temperatures and varied between shelters/barns, reflecting differences in material, design and shelter/barn size (Group 1: 19. 0 ± 0. 4 • C; Group 3: 16. 7 ± 0. 3 • C; Group 6: 19. 2 ± 0. 5 • C; and Group 7: 18. 1 ± 0. 7 • C). Unfortunately, the logger in Group 9 broke down during the experimental period and data were lost. A total of 3235 insects were captured in the H-traps: 860 were tabanids of which the common horsefly, Haematopota pluvialis (L. ) dominated with 87. 6% of all captured individuals. The band-eyed brown horsefly, Tabanus bromius (L. ) occurred with 5. 7%, and several species of Hybomitra ssp with 5.
Materials and methodsexperiment 2 (follow-up study) The follow-up study was conducted July -September 2020 and conformed with the same legislation and guidelines as Experiment 1. The study aimed to investigate whether horses' saliva cortisol differed between days with low and high insect prevalence, in a cross-over design with each horse as its own control. Thirteen horses from one stud were included (Group 1: Free indoor access: 6 mares, 12-19 years, 9 ha pasture, and Group 2: No access, 3 yearling stallions and 4 adult geldings, 1-13 years, 15 ha pasture). We originally included an additional mare group without indoor access, but this group unfortunately moved location during the data collection period and was omitted. We selected two days with expected high insect prevalence and activity based on the knowledge gained in Experiment 1 (warm days with low wind speed: Aug.
Data analysis Data on behaviour and saliva cortisol were analysed in a Two-way RM ANOVA with insect day (Low1, Low2, High1, High2) and group (Indoor access or No access) as explanatory variables. Post-test analysis was performed using an all pairwise multiple comparison procedure (Holm-Sidak method). For saliva cortisol, the mean of the three daily samples for each horse was used in the analysis. Data from a few horses were removed from the analysis: Horse 4 (Group1) on Aug 6th as she had been placed in an adjacent pasture with a new horse in the morning, prior to our arrival; Horse 13 (Group 2) on Aug 9th as he was clearly unwell and died a few days later, i. e. data missing from him on Sept 13th as well; Horse 9 (Group 2) on Sept 13th as he had been sold and had left the stud.
Acknowledgements A huge thank you to the horse owners, and to  Clara Bardet ,  Anaïs Bossa ,  Alexia Durand ,  Agnete Gargulak  and  Laura Moeslund Eriksen  for your highly valued help with the data collection. Our thanks also go to  Torben Larsen ,  AU , for the saliva and FCM analysis, and to  Rupert Palme ,  University of Veterinary Medicine, Vienna , for co-operation on FCM analysis.
Acknowledgments The authors thank the  MIMA2 ,  INRAE ,  2018. Plateforme de Microscopie et Imagerie des Microorganismes, des Animaux et des Aliments , https: //doi. org/10. 15454/1. 55723482100 07727E12  ,  Josiane Aïoun  and  Audrey Geeverding  for the electron microscopy. The authors also thank  Audrey Prezelin , the  IERP, INRAE, 2018. Plateforme d'Infectiologie Expérimentale des Rongeurs et Poissons , https://doi. org/10. 15454/1. 5572427140471238E12  ,  Christelle Langevin  and  Maxence Frétaud  and the  Imaging Platform of INRAE IERP  unit for the preparation of samples and the lightsheet imaging of the placenta.
Study design After stabilizing the depth of anesthesia, heart rate and respiratory rate, the variables measured by the spirometer were recorded for 5 mins [T 0-5 -T 0 ]. Then (T 0 ) a hemostatic clamp was clamped (to the first notch) between two fingers of the left hind leg until a withdrawal movement was observed. If no reaction occurred, the clamp was left in place for 60s. After removal of the clamp, respiratory variables were measured continuously for another 5 mins [T 0 -T 0+5 ]. At T 0+5 morphine (Morphine Clorhydrate Aguettant, Aguettant Laboratory, France) 0. 2 mg kg -1 IV was administered. Five mins later (T 0+10 ), a second clamp test was performed, using the same procedure. At T 0+15 the data recording was stopped. Anesthesia was then continued and analgesia was provided as required to allow the surgery to be performed.
Acknowledgments We would like to thank  Mr. Renou  from the company Resmed ( St Priest, France ) for the loan of the Citrex measuring device. Our special thanks to Professor of  Statistics Marie-Laure Delignette  for her valuable help in processing and interpreting the data. We would also like to thank  Dr. Bruna Santangelo  and the students of the Veterinary School for their help in the implementation of the anesthesia and the data collection.
The above analysis revealed a minimum 5,564 bp, 14 SNP shared haplotype, significantly associated with racing performance within CBTs (ECA22: 46,713,478-46,719,042). The same variants were also significantly associated with racing performance in SBs. This allowed for the definition of an elite-performing haplotype (EPH: AAGCGTTTCTCAAA), and a sub-elite-performing haplotype (SPH: GGTTACCCTCTGGG) (Supplementary Table  S4 ) (Figure  1C ). Of note, the reference EquCab3. 0 genome represents the SPH variant. In step four, we assessed the potential functional impact of the minimal 5. 5 kb region and each of the 14 SNP haplotype variants. Using horse functional data from two Thoroughbreds (from the Equine Functional Annotation of Animal Genomes, FAANG), we found three SNPs (g. 46717860, g. 46718095 and g.
Increased frequency of the favorable haplotype coincides with the time of horse domestication For all 14 SNPs within the minimum shared haplotype in the trotters, we investigated the allele frequency over time using the mapDATAge package  (26). For all SNPs but two (SNP 6 and 7 in Figure  2 ) there was an increase of the alternate allele from 7,500-5,500 years ago (Figure  2 ). For all SNPs considered, the two alleles segregated in specimens pre-dating the rise and spread of the DOM2 genetic lineage of modern domestic horses (data not shown). The dataset considered included 431 ancient genomes previously characterized  (2, (27) (28) (29) (30) (31).
The highly abundant proteins contribute to approximately 90 % of the total protein content in plasma. In this study, plasma depletion of the most abundant proteins was performed to facilitate the quantification of less abundant proteins and to improve the sequence coverage  (60). However, a limitation of the present study is the quality of the available proteome database for Equus caballus, which only includes a limited number of proteins. Additionally, many proteins were excluded due to a low number of biological replicates, and in total, 383 proteins could be included in the comparisons between groups. When comparing protein levels at rest and during exercise for the different haplotype groups, we observed a clear difference in the number of regulated proteins (Supplementary Table  S8 ).
6. Given the high LD, a significance threshold was set at P ≤ 0. 05. All statistical analyses were performed in the R statistical environment. The performance data were tested for normality by computing the skewness coefficient using the package moments v0. 14. Non-normally distributed values were transformed, i. e. , log transformed values (log10 +1) were used for wins and placings, number of starts were square root transformed and earnings and earnings per start were transformed according to the previously reported formula (ln(earnings + 1000))  (83). Genetic variants were tested in a linear model using ANOVA as a post hoc test. Number of starts, age at first start, sex, birth year, country of birth, and the DMRT3 genotype were included as fixed effects, when significant. Significant values (P ≤ 0.
Additional variant discovery To find and assess variants missing from the Axiom Equine Array, but with the potential to influence racing performance, we performed both Illumina short-read WGS and MinION Oxford Nanopore targeted sequencing of PCR products. First, two CBTs and two SBs were selected for WGS based on their g. 46717860 genotype and their performance values. From each breed, horses homozygous for opposite alleles of SNP g. 46717860 (CC respectively TT) with either high (TT) or low (CC) earnings per start were selected for sequencing (Supplementary Table  S4 ). Paired-end 150 bp Illumina HiSeqX data was generated to a depth of 15X. Read data were processed according to the GATK.
Haplotype analysis Pairwise r 2 calculations with all 24 SNPs and g. 46717860 were performed using the LDfunction in R. Based on the high LD between all genotyped SNPs, it was possible to impute g. 46717860 alleles for ungenotyped samples. All SNPs with a pairwise r 2 value >0. 6, plus two flanking SNPs were selected for haplotype analysis. Haplotype racing performance association tests used a GLM regression analysis, which was performed in 180 CBTs and 38 SBs using the haplo. glm function from the haplo. stats package in R  (86). The model included the effects of sex, age, country of registration, DMRT3 genotype (only for the CBTs) and number of starts, when significant. All CBTs had been genotyped for the DMRT3 mutation, using the StepOnePlus Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA) with the custom TaqMan SNP genotyping assay  (82).
Functional bioinformatic analyses ChIP-seq data were provided by the Equine Functional Annotation of Animal Genomes (FAANG) team (www. faang. org) (24, 25)  including four histone marks (H3K4me1, H3K4me3, H3K27ac and H3K27me) across nine tissues (adipose, brain, heart, lamina, liver, lung, muscle, ovary and skin) from two Thoroughbreds. FAANG bam and bed files from the different available tissues, the four histone marks and the input DNA control (project: PRJEB35307) were downloaded to a local server. First, the integrity of the data was checked using checksums. Bam files were sorted with samtools and bedgraphs were subsequently created using bedtools  (87, 88). The Integrative Genomics Viewer (IGV) browser was used to visualize the output data along with the EquCab3. 0 fasta file and its gff3 annotation file  (84, 89).
The presence of H3K27ac and H3K4me1 was considered to mark active enhancers, whereas H3K4me1 and H3K27me3 marked poised enhancers. H3K27ac and H3K4me3 marked active promoters and H3K27me3 was considered to mark repressed regions. The region defined by the minimum shared haplotype (see above) was investigated using IGV for the different histone marks in all available tissues. A comparative analysis to hg38 was conducted for the minimum shared haplotype region. Co-ordinates were lifted in UCSC (liftOver) and potential overlaps between ENCODE Candidate Cis-Regulatory Elements (cCREs), ENCODE Integrated Regulation tracks and ORegAnno Regulatory elements were annotated  (90, 91). For each of the SNPs in the minimum shared haplotype region, the potential of alleles to alter transcription factor binding potential was tested with sTRAP  (92).
933), with the -baq 0, -remove_bads -minMapQ 25 -minQ 30 -rmTriallelic 1e-4 -SNP_pval 1 -C 50 parameters  (97). The resulting occurrences were tabulated together with metadata available for each individual, consisting of their corresponding archaeological site (name and GPS coordinates) and their average calibrated radiocarbon date (or age as assessed from the archaeological context otherwise). The tabulated file was visualized using the mapDATAge package  (26) , which provides spatial distributions within user-defined time periods and/or spatial ranges and estimates allelic trajectories (i. e. , allelic frequencies through time) based on the resampling of individual allelic counts. The final allelic trajectories were assessed considering time bins of 2,000 years (step-size = 500). To explore the genetic variation for the SNPs within the haplotype, we considered the 14 polymorphic sites i.
Proteomic data analysis The data files in each set were merged for identification and relative quantification using Tryptic peptides with zero missed cleavage, variable modifications of methionine oxidation and fixed cysteine alkylation were accepted. ProTMT modifications of N-terminal and lysine were selected. Percolator was used for the peptide-spectrum match validation with a strict false discovery rate (FDR) threshold of 1 %. The TMT reporter ions were identified with 3 mmu mass tolerance and no normalization was applied to the samples. For the protein quantification, only unique peptide sequences at a strict FDR threshold of 1 % with a minimum synchronous precursor selection match of 65 % and an average S/N above 10, were taken into account. The reference in each set was used to calculate protein ratios and quantified proteins were filtered at 5 % FDR.
Processing of quantitative proteome data The protein ratios of quantified and normalized proteins were processed in Microsoft Excel to calculate the group means and fold changes. All plasma samples were grouped into two sets; before and after exercise. Only proteins quantified in at least three horses from each haplotype group (EPH and SPH), i. e. , proteins with at least three biological replicates in each haplotype group, were included in the analyses. Perseus version 1. 6. 15. 20 was used to analyze differences between the groups, by applying t-test on log2 protein ratios. Five different comparisons were made; SPH and EPH at rest and during exercise as well as rest versus exercise within each haplotype. Additionally, paired ratio analysis was performed, to compare differences in protein levels during exercise vs.
at rest for each haplotype i. e. , (SPHrest/SPH-exercise)/(EPH-rest/EPH-exercise). For each comparison, fold change values were calculated by dividing the average values for the compared groups and P-values ≤ 0. 05 were considered to be significant. GO-annotations downloaded from the Uniprot database into Perseus were used to support the identification of changing biological processes. Furthermore, the GO enrichment analysis and visualization tool g:GOst from g:Profiler was used to identify the biological processes affected in each of the different contrasts  (32).
Thermo Fisher Scientific, Waltham, MA, USA). The Uniprot Equus caballus proteome database (July 2021, combined SwissProt and TrEMBL 44,488 entries) and Mascot search engine v. 2. 5. 1 (Matrix Science, London, UK) were used in the database matching with peptide and fragment ion tolerance of 5 ppm and 0. 6 Da.
Acknowledgements Thanks to all horse owners and trainers who participated in the study, The Swedish Trotting Association and the  Norwegian Trotting Association  for providing pedigree and performance data,  Anna Darlene van der Heiden  for the ONT sequencing,  Tytti Vanhala  for help with genotyping,  Anna Johansson  at the  National Bioinformatics Infrastructure Sweden at SciLifeLab  for bioinformatics advice, and the  Department of Clinical Sciences Clinical training center (KTC)  at  SLU  for providing the Cardell Veterinary monitor for the blood pressure measurements. Anna Svensson´s lab at the Department of Clinical Sciences SLU  for running ELISA. Adnan Niazi  at  SLU Bioinformatics Infrastructure (SLUBI) ,  Uppsala ,  Sweden SLUBI  for supporting Nanopore data analysis. WGS was performed by the  SNP&SEQ Technology Platform in Uppsala.
The facility is part of the  National Genomics Infrastructure (NGI) Sweden and Science for Life Laboratory. The  SNP&SEQ Platform  is also supported by the  Swedish Research Council  and the  Knut and Alice Wallenberg Foundation. The computations and data handling were enabled by resources in project  snic2018-8-226  provided by the  Swedish National Infrastructure for Computing (SNIC)  at  UPPMAX , partially funded by the  Swedish Research Council  through grant agreement no. 2018-05973. The global relative quantitative proteomic analysis was performed at the  Proteomics Core Facility ,  Sahlgrenska Academy  at the  University of Gothenburg, Gothenburg, Sweden.
Proteome Discoverer version 2. 4 ( 24 Thermo Fisher Scientific, Waltham, MA, USA). The Uniprot Equus caballus proteome database (July 2021, combined SwissProt and TrEMBL 44,488 entries) and Mascot search engine v. 2. 5. 1 (Matrix Science, London, UK) were used in the database matching with peptide and fragment ion tolerance of 5 ppm and 0. 6 Da.
The samples were loaded and sequenced on the MinION. Demultiplexed sequencing data were mapped to EquCab3. 0 ECA 22 (GCF_002863925) using minimap2 v. 2. 4 sequence alignment program (https://github. com/lh3/minimap2). The resulting SAM files were converted to BAM format using samtools v. 1. 8. Single nucleotide variants were called using the variant calling tool longshot v. 0. 4. 3 with default parameters (https://github. com/pjedge/longshot). Structural genomic variations were identified with NanoSV v. 1. 2. 4 software (https://github. com/mroosmalen/nanosv), with default parameters. Only variants with a quality above 20 were retained. 3. 8-0 best practices (https://software. broadinstitute. org). Briefly, raw data were trimmed with TrimGalore 0. 4. 4 and quality checked with QualiMap 2. 2.