dataesr/scientific-paragraphs-categorization huggingface dataset:
Compression force at 20 and 80% was analysed using a Shimadzu EZ-SX texturometer, coupled with Trapezium X software, operating in the compression mode and using a 25 kg load cell  [27]. For rheological tests of shear force, the equipment was fitted with a Warner-Bratzler knife. Samples of 1 cm 2 (square cross-section), with muscle fibres parallel to the longitudinal axis of the sample were placed on the table, under the V blade, and were cut through as the blade moved down with a constant speed (10 mm min -1 ). Results were expressed in Newton's (N). For these determinations six replicates per storage time and packaging films were recorded.
Statistical Analysis Development of statistical methods for repeated measures data has been an active area of research in the past two decades because of advancements in computing hardware and software  [28]. In the present experiment, a repeated-measures mixed model was fitted using the R packages lme4  [29]  and lmerTest  [30]. For the purposes of the model, ageing-length was considered a fixed effect. The animal was considered as a random effect. y i = X i β + Z i b i + ε i with X i β = β 0 + β x 1 x 1 +. + β x k x k ; β: fixed effects; Z i b i = b 1 x 1 +. + b k x k ; b: random effects; ε i : error. This model used a random intercept to account for repeated measures of the same individual during ageing. Two Principal Component Analysis (PCA) were then carried out according to  [31]  in order to characterize the links between muscular properties: whatever ageing duration (using a PCA with all the 4 × 8 = 32 samples): PCA1 -according to the evolutionary kinetics of the muscular properties with maturation (using a PCA with only 8 samples, the values for each muscular properties being equal to the difference calculated between T1 and T4): PCA2.
This evolution favours the evolution of the colo less red, less shiny and darker (more blackish) meat with ageing, confirmi previously established. Indeed, it has been shown in several studies and th strumental measurement of colour that long dry ageing results in darker a meat and that this process contributes to the stabilisation of the colour wh the ageing time  [34] [35] [36]. When calculating the colour differences ΔE betwe measurements (T1 and T2; T2 and T3; T3 and T4), it was found that the colo between different ageing times were always greater than 3 (data not show to  [37] , when ΔE > 3, colour differences are obvious for the human eye. Ou indicate that the colour differences measured by the chromameter are perc human eye. The instrumental measurement of colour makes it possible to determine the luminance (L*), the hue and saturation from green to red (a*) and the hue and saturation from blue to yellow (b*) of a given sample (Figure  3 ).
Acknowledgments: The authors would like to thank Pascal Faure (INRAE-Herbipôle) and Jingjing Liu (INRAE-UMRH) for carcass grading according to MSA guidelines, Lionel Bombrun (Bordeaux Sciences Agro) and John Albechaalany (INRAE-UMRH) for their assistance in the statistical processing of the data. The authors warmly thank the students who worked on this project during their internships: Amani Daly and Claire Cruzaud.
To further investigate a possible infectious etiology, the third CSF sample was submitted in our laboratory to clinical metagenomics, which is used in our hospital as a last-resort approach in patient with high suspicion of infection but negative microbiological analysis. A specific extraction combining mechanical (bead biting), enzymatical (proteinase K based) and chemical (lysis buffer) steps was performed before DNA and RNA library prep using Nextera and Total RNA kits (Illumina), and sequencing with NextSeq500 (Illumina)  (4, 5). Bioinformatic analysis was performed using the MetaMIC software  (4, 5). From a total of 36'882'731 reads generated from the CSF sample, 7'862 matched with Nocardia cyriacigeorgica's genome, corresponding to a 2. 13x10 -4 pathogen/human nucleic acid ratio and a concentration of 250 genome copies/mL.
This sample was also sent to the French Observatory of Nocardiosis (Lyon), where a specific PCR confirmed the presence of Nocardia, as well as species identification. Finally, the diagnosis of cerebral nocardiosis due to N. cyriacigeorgica with central nervous system vasculitis was retained. In the absence of possible phenotypic susceptibility testing, resistance genes were sought from metagenomics data. After alignment of raw reads with BWA (Burrows-Wheeler Aligner) on the reference genome identified by MetaMIC, we found a consistent coverage on overall the genome (Supplementary Figure  1 , GenBank PRJNA640158). However, although the coverage almost encompassed the complete genome of the reference strain, the sequencing depth was insufficient to allow the formal identification of resistance genes, probably because of the early initiation of antibiotic treatment.
In silico prediction of metabolites To better understand the metabolic transformations that may occur following exposure to phenoxyethanol, predictions of in vivo metabolism were made. The major routes of metabolism predicted by the software are summarised in Fig. 1  and comprised: aromatic hydroxylation, oxidative dealkylation, glucuronidation, oxidation of primary alcohols and O-sulphonation. Meteor Nexus predicted 19 unique metabolites (30 in total). Eight of these metabolites were predicted to be formed directly from the parent compound (level 1 metabolism) with a further metabolite (M5 in Fig. 1 ) predicted to be formed by dealkylation of phenoxyacetic acid (PAA, M1).
In vitro biokinetics MCF7, HepG2 and HepaRG cells The levels of phenoxyethanol and PAA in the media were measured during incubations with HepG2 cells (seeded at 51,000 cells/well) for up to 24 h. Data generated on HepG2 cells are presented in Fig. 3  because this cell line provided the lowest NOTEL/PoD. Measurements in HepG2 cells seeded at 3000 cells/well, MCF-7 and HepaRG cells are shown in Supplementary Figures  3, 4  and 5 , respectively. Phenoxyethanol concentrations in the medium of all three cell types were stable over 24 h. Very little of the applied amount of phenoxyethanol was detected in the cell lysates at any of the time points measured. PAA was detected in the lysates and medium in HepG2 and HepaRG cell incubations, the levels of which increased over time. PAA was not detected in MCF-7 cell lysates and only trace amounts were detected in the medium of these incubations.
Data Collection Broilers were weighed per cage on days 1 and 21 to estimate BW. Feed intake was measured daily. These data were used to estimate average daily gain (ADG), average daily feed intake (ADFI), Feed Conversion Ratio (FCR), and European Production Efficiency Factor [EPEF,  (19) ]. EPEF is defined as follows: Dead chicks were counted and removed daily. Broilers were euthanized at 21 days old to proceed to intestinal lesions scoring according to the scoring system published by Johnson and Reid  (20).
Statistical Analysis Data were analyzed using R (  21 ) with emmeans and nnet packages. All quantitative data were analyzed using the following model: Y ijk = Treatment i + Trial j + Treatment : Trial ij + ǫ ijk (2) where Y ijk was a dependent variable of a repetition k, within treatment i and trial j. Treatment, trial, and their interaction were fixed factors, due to the low number of levels within each factor  (22). All observations were weighted according to the number of broilers they represented. Body weight gain (BWG), ADG, ADFI, FCR, and EPEF were analyzed using a linear model. Results are reported as means and standard error of the means (mean ± SEM). Individual survival analysis and scores for the intestinal lesions were analyzed using logistic regression, results being reported as odds ratio (OR) to the base level and confidence interval (CI) [OR (lower confidence interval-upper confidence interval)].
The CTL group received a pre-measured spoon of the blank dilution matrix to avoid bias. The farmer distributed daily 10 g of the diluted supplementation or the blank dilution matrix per animal per day and checked their uptake by the heifers. A particular appetence for the matrix (blank or supplemented) was reported by the farmer with total consumption observed daily. The RPGE contained >60% total polyphenols, mainly constituted of oligomeric and monomeric flavanols and anthocyanins (suppliers data sheet), rumen-protected through a micro-encapsulation with an organic plant-based matrix. Polyphenol percent was measured by using the spectrophotometric method of total polyphenol quantification at 280 nm (European Commission, 2017) and confirmed this value.
The percentage of hybrids in the different populations was tested using the χ 2 test under the null hypothesis of equal distribution. Each miracidium was genotyped using a set of microsatellite markers previously developed for S. haematobium  [41]  as these markers have recently been found to crossamplify with S. bovis  [33]. These markers are grouped in two multiplexes of 9 microsatellites ranging from 183 and 366 bp: panel 1 (C102, Sh1, Sh14, C131, Sh6, Sh9, Sh13 and Sh7) and panel 2 (Sh2, Sh5, Sh13, Sh4, Sh10, Sh12, Sh8, Sh11 and Sh15). Of the 18 microsatellites tested, 14 successfully amplified the parasite samples and were therefore used in the present study. The remaining four markers (C131, Sh4, Sh8 and Sh15) were successful on less than 20% of the specimens and were eliminated from our dataset.
Population genetic analyses from microsatellites Linkage disequilibria and deviations from Hardy-Weinberg's expectations were tested using exact tests (1,200 permutations) as implemented in the FSTAT software, version 2. 9. 3. 2  [42]. The significance level has been adjusted for multiple tests using the standard Bonferroni corrections  [43]. The genetic diversity of the miracidia of each population was assessed by calculating the expected heterozygosity (He) and the allelic richness (Ar) using the FSTAT software, version. 2. 9. 3. 2  [43]. These populationto-population parameters were compared using Friedman's pairwise rank tests, followed by Nemeyi's multiple comparison test implemented in the Rstudio PCMPplus package. The link between the genetic diversity indices (He or Ar) and the percentage of hybrids was assessed using linear regression method of SPSS 18.
0 (SPSS Inc. , Chicago, USA). In addition, after identifying the hybrids, we calculated the number of private alleles they carried in their respective populations. Genetic differentiation between localities was assessed using pairwise FST values according to Weir and Cockerham  [44]. We calculated these values and their associated significance using global tests implemented in the FSTAT software, version 2. 9. 3. 2  [42]  with a significance threshold adjusted for multiple tests according to Bonferroni's standard corrections  [42]. In addition, at the individual level, we combined Euclidian geographic distances (calculated from geographic coordinates) and genetic distances in a simple Mantel test using Genetic differentiation between sites was assessed using pairwise FST values according to Weir and Cockerham  [44].
We calculated these values and their associated significance using global tests implemented in the FSTAT software  [42]  with significance threshold adjusted for several tests according to Bonferroni's standard corrections  [42]. In addition, at the individual level, we combined Euclidean geographic distances (calculated from geographic coordinates) and genetic distances in a simple Mantel test using GenAlEx 6. 51b2  [45]. Finally, we determined the highest level of genetic structure for all individuals using the Bayesian clustering approach implemented in the STRU CTU RE software, version 2. 3  [46]. The run-in period for each trial was set to 50,000, followed by 500,000 MCMC iterations. We performed 10 independent runs for each K value from 1 to 12. We estimated the most likely number of genetic clusters (K) using the method implemented in the STRU CTU RE HARVESTER, version 0.
6. 9 [47, 48]. Finally, we determined the uppermost level of genetic structure of all individuals using the Bayesian clustering approach implemented in the STRU CTU RE software, version 2. 3  [46]. The run-in period for each trial was set to 50,000, followed by 500,000 MCMC iterations. We performed 10 independent runs for each K value from 1 to 12. We estimated the most likely number of genetic clusters (K) using the method implemented in the STRU CTU RE HARVESTER, version 0. 6. 9 [47, 48].
Discussion Basic analysis on our microsatellite dataset showed deviation from Hardy-Weinberg's expectations among several pairs of loci/populations. However, it is difficult to interpret these deviations from Hardy-Weinberg's expectations, as the populations analyzed include parasites collected from several hosts and not a panmictic parasite populations. Thus, this absence of Hardy Weinberg's equilibrium and especially the excess of homozygote could be due to a Wahlund effect resulting from a sampling in different hosts. Few populations genetic studies have been undertaken on S. haematobium compared to S. mansoni (see  [49]  for a review). According to these studies, S. haematobium populations are generally less genetically structured than those of S. mansoni  [49, 50]. To document the divergence between S.
haematobium showing either a lower FST value for shorter distances between sites (FST = 0. 4% between 8 km separated sites  [52] ) or higher FST values for higher distances between countries (FST = 17. 3% between Cameroon, Kenya, Mali, Niger and Tanzania  [49] ). As a result, our findings reveal a significant pattern of IBD. By comparing parasites from separate countries at the continental level, IBD was previously observed using a microsatellite dataset  [49]  but was not confirmed using SNP  [53]. The overall genetic differentiation inferred either by a principal component analysis or by the Bayesian approach showed a partial structure. In the Bayesian method the ΔK value was very low, suggesting little convergence between the runs. This echoes the fact that the Bayesian method implemented in the STRU CTU RE software is sensitive to IBD patterns and may discern multiple clusters where there is only a single large area with IBD  [54].
Statistical analyses We analysed our data in a Bayesian framework, using R (version 4. 2. 0, R Core Team, 2022) and the brms R package  (Bürkner, 2017)  as frontends for the Stan language  (Carpenter et al. , 2017). We used the tidybayes, bayesplot, patchwork packages for data preparation, model evaluation and plotting, as well as the tidyverse suite of packages  (Gabry et al. , 2019; Kay, 2019; Wickham et al. , 2019; Pedersen, 2020). One snail (out of 180) died during the experiments and was excluded from statistical analyses, but was used for natural history information (see Results). We ran two models, which both included at least effects of population of origin, number of shell bands, as well as population × banding interactions as categorical explanatory variables (hereafter "morph and population effects").
• live nematode abundance was modeled as trematode abundance, with one change. As no live nematodes were found in the shaded population, we only fit this submodel to data from the open population and removed the population fixed effect. Importantly, keeping all data instead does not change our conclusions (see Data availability). • food consumption (mean-centred and scaled to unit 1SD) was analysed using a Gaussian model including the same fixed and random effects as trematode abundance. Although food consumption data are proportions (of total food), and so are well-suited to Beta models  (Douma & Weedon, 2019) , the Gaussian model behaved much better regarding posterior predictive checks (Data availability). As individuals were measured twice, the individual random effect here allows separation between within-and among individual variation.
Data availability Data and R scripts to reproduce all analyses presented here are on Github (https://github. com/mdahirel/cepaea-parasite-behaviour-2019) and archived in Zenodo (DOI: https://doi. org/10. 5281/zenodo. 6327265). Representative images of parasites trapped in shells are also archived in Zenodo (DOI: https://doi. org/10. 5281/zenodo. 6326305). Funding MD was a postdoctoral researcher funded by the French Agence Nationale de la Recherche (PushToiDeLa, ANR-18-CE32-0008), during the course of this research.
They had free access to fresh water, straw, and mineral supplements. Heifers were then inseminated on the first detected natural heat, starting December 1st. They were turned back out to pasture in the spring (March 2019) and received no additional feed except for grass, along with supplemental vitamins and minerals. Data recording for this experiment stopped 2 months (on average) before the expected start of the calving season. All diets (Table  1 ) were formulated for each stage of growth, according to the recommendations and procedures of Agabriel and Meschy  [14] , with the goal of reaching a targeted average daily gain per period, based on the initial BW and feeding treatment (see also  [15]  for more details). Health and treatment information was recorded for all heifers, but no problems occurred during the course of the experiment.
Measurements Heifers were weighed every 14 days from birth to weaning, every 21 days from weaning until turning out to pasture (183 to 230 days of age), and every 28 days until the end of the experiment. Weighing usually occurred between 10:00 and 12:00 to keep conditions similar. Between weighing dates, BW was interpolated in order to have data for all heifers at similar ages. Daily gains were then calculated for each animal. Each heifer passed through the Morpho3D device (3D Ouest, Lannion, France) once a month, from November 2017 to August 2019, so that 3D images could be captured. Image acquisition was rapid when animals were getting used to the device and took on average 6 s. The dates of image capture usually corresponded to the weighing dates, and if not, BW was interpolated as described above.
After processing, a 3D reconstruction of the heifer is generated, i. e. , a single point cloud representation of the entire heifer (see  [12]  for additional details about Morpho3D). Finally, surface normals are estimated from the point cloud, and a screened Poisson surface reconstruction algorithm is applied to build a triangulated mesh  [16]  using Meshlab open-source software  [17]. Metrux2α software (3D Ouest, Lannion, France) was used to perform linear measurements and estimate morphological traits, BSA, and volume  [12]. For 3D images, the quality of the reconstruction has a strong influence on the measurements that can be obtained. In some cases, the main body of the heifer was digitized properly but its head or legs were not, meaning that the animal had moved slightly during image capture.
Analysis Metrux2α software (3D Ouest, Lannion, France) was used to quantify morphological traits such as heart girth (HG), chest depth (CD), hip width (HW), and buttock width (KW) from the 3D images (see  [12]  for details). The validity (repeatability and reproducibility) of this method of measurement had been verified by earlier work in which we compared imaging data to "gold standard" manual measurements  [12]. We therefore performed no manual measurements on the animals in this study. The selected morphological traits were chosen because farmers can perform them on-farm, using rule-tape for example. Body surface area (BSA) and/or volume determined from the Morpho3D device were used to estimate BW using the equations of Elting  [10]  and Le Cozler et al. [13]. Even though more recent authors have published updated versions (described by Le Cozler et al.
[13] ), the equations of Elting  [10]  are still commonly used, probably because BSA remains difficult to routinely determine. Elting  [10]  published equations for adult cows Equation (1) and growing heifers Equation (  2 ). More recently, our group published equations to estimate BW as a function of BSA Equation (3) or other morphological traits Equation (  4 ), but only for adult cows  [13]. In that same study, we also created an equation to calculate BW based only on volume Equation (  5 )  [13]. Here, we used these equations to calculate body weight for each animal, and these values were then compared to measurements recorded directly from animals. BSA = 0. 0839 × BW Data were first visualized using the ggplot2 package (v. 3. 2. 1) [18]  of R software  [19]  and the difference between estimated and recorded values was plotted.
Statistical analysis Statistical analyses using the SPSS software package were carried out using analyses of variance (one-way analysis of variance, ANOVA, and Mann-Whitney non-parametric test when data were over-dispersed). The life traits and fitness of Tcirc S were compared against Tcirc R following the F2 and F3 passage (where data was available) and following the experiment in immune-suppressed lambs. The life traits and fitness were also compared within each isolate, to explore if their performance differed significantly between the F2 and F3 passage. The FEC were log transformed (log x + 1) prior to one-way ANOVA comparisons to stabilize the variance of the highly dispersed data.
These results are potentially relevant to a farm scenario, specifically where selective breeding programs are harnessing similar genetic traits and GIN protective mechanisms across the flock. It is conceivable that the GIN population could encounter several resistant hosts in succession, modifying their infection dynamics for the more susceptible individuals on pasture, with greater associated health and production costs. There were however, experimental limitations to this study when extrapolating the results to field scenarios. Notably, the data were obtained from relatively few individuals that were immunosuppressed. Even within a sheep breed, individual variation in susceptibility to GIN infection has been well documented  [37] , thus, consequent studies using greater sample sizes would provide more accurate mean values to approximate what we could expect from the Tcirc S and Tcirc R infection dynamics in a field situation.
Acknowledgments The technical help of  J. Cortet ,  C. Sauvé  and the staff from Langlade  INRAE  genetic experimental unit during the pre-selection of T. circumcincta in the field is gratefully acknowledged. With thanks to  S. Athanasiadou  for comments on an earlier draft of the manuscript. E. S. was funded by  General Pico Faculty of Veterinary Science in Argentina and Fonamer project. C. C. is a grateful recipient of  Marie Curie programme 'NematodeSystemHealth' grant. Preliminary results were presented as an oral communication at the  British Society of Parasitology, Spring Meeting, Bristol, UK , April 2013.
Statistical analysis The data were analyzed using SPSS Statistics 26. 0 (IBM). Prior to the analysis, all the variables were assessed for normality according to the Kolmogorov-Smirnov test. When they were normally distributed, the reproductive performance variables, BFT and BW at farrowing, as well as ADFI of sows during the first week of lactation were submitted to an analysis of variance with sow dietary treatment, room, parity and their interactions as main effects. The litter performance variables between days 7 and 21, BW and BFT at weaning, BW and BFT loss during lactation, and the ADFI of sows in weeks 2, 3, and overall were analyzed submitted to an analysis of variance and analyzed according to a 2 × 2 factorial approach with sow dietary treatment, litter diet, room, parity and their interactions as main effects.