dataesr/scientific-paragraphs-categorization huggingface dataset:
Limitations of the study The limited number of subjects (n = 16) involved in the present study does not allow to investigate the possible influence of parameters such as age or demographic data on biomarker variability. Nevertheless, the workload and effort requested from the participant associated with repeated sample collection represented an important limitation, since about a thousand biological samples were collected over this sixmonth and required one year for their analysis with up-to-date methods. It thus does not seem realistic to conduct similar study on larger cohorts of hundreds or thousands of subjects, with large age distribution and better representativeness of general population. The results and conclusions presented here are therefore valid for the population under study, which was however well balanced regarding gender and age, and did not present extreme values of biomarker detection frequency and concentration that would suggest considering it as an unusual group regarding exposure.
For all except one treatment (Uninfected Untreated Control -UUC), birds were artificially challenged with ADVENT® coccidiosis vaccine 10x dose on day 14. Broiler chickens from the two challenged groups received either no supplementation (Infected Untreated Control -IUC) or a mix of arginine, threonine and glutamine together with grape extract polyphenols at a dose of 1 kg/Ton (IUC+MIX) from day 0 to day 35. Performance and livability were followed during the 35 days of the trial. Lesion scoring, duodenum morphology and fecal oocyst count were assessed on day 21. On day 25 nutrient digestibility was measured on a subset of birds. All data were subjected to an ANOVA and differences among means were detected by multiple range tests. During the course of the trial, coccidiosis challenge reduced growth (-3 g/d, P = 0.
Statistical analysis Performance data were analyzed using generalized linear mixed model with treatment as fixed factor and block as a random factor. The barn was divided into 8 blocks, each block including a pen/replication from the 3 treatment groups. This was followed by post-hoc Tukey tests. Pen was used as the experimental unit. For digestibility and gut morphology, data were analyzed using general linear model with treatment as a fixed factor. Oocyst count in fecal samples and lesion scoring were analyzed with Kruskall-Wallis tests. For oocyst count, pen was used as the experimental unit. For lesion scoring, individual chickens (two randomly selected per pen) were used as the experimental unit. Statistical tests were performed using Minitab. The level of significance was set at P < 0.
Identification of T. suis sequences related to the ACR-16 group Using the C. elegans ACR-16 deduced amino-acid sequences as a query, tBLASTn search against T. suis, T. muris and T. trichiura genomic data available in WormBase-ParaSite (version WBPS14; http://parasite. wormbase. org/) allowed the identification of two distinct hits for each species sharing identities ranging from 46% to 47% with the C. elegans sequence. Subsequently, a second tBLASTn search against nematodes genomic data available at the NCBI was performed with the retrieved Trichuris spp. sequences. Homologies could be identified with either of the acr-16 or acr-19 genes from nematode species representative from the nematoda phylum. Using a panel of representative C. elegans nAChRs subunits as references, a phylogenetic analysis including the Trichuris spp.
Molecular cloning of the Tsu-acr-16-like coding sequence In the present study, based on the current knowledge of the original mode of action of oxantel  [16, 29] , we hypothesized that the divergent ACR-16-like from Trichuris spp. could represent a preferential target for this narrow-spectrum anthelmintic. Using T. suis as a model, we cloned its acr-16-like full-length cDNA sequence as a matter of priority and deposited the sequence in GenBank under the accession number MT386096. During PCR amplification for the cloning, we observed several band sizes and tried unsuccessfully to clone all of them. Therefore, it is possibly that there are at least 2 other isoforms of the Tsu-ACR-16-like subunits. An alignment of the Tsu-ACR-16-like sequence with its closely related counterparts from T. muris, T.
Bioinformatics and sequence analysis The Asu-ACR-16 (accession number AKR16139) and the Cel-ACR-16 (accession number NP505207) were used as queries in database searches for Trichuris suis ACR-16 (Tsu-ACR-16) and ACR-16s from other Clade I parasitic nematodes (i. e. Trichuris spp. and Trichinella spiralis) in the protein-protein BLAST (BLASTp) service at the National Center for Biotechnology Information (NCBI) service  [74]. Cel-ACR-  16   Signal peptide was predicted using the SignalP 4. 1 server  [75]  and the transmembrane regions were predicted using the TMHMM version 2 server  [76]. Deduced amino-acid sequences were aligned using MUSCLE. Phylogenetic analysis was performed on deduced amino-acid sequences. Maximal likelihood phylogeny reconstruction was performed using.
Two-electrode voltage clamp of Xenopus laevis oocytes Two-electrode voltage-clamp (TEVC) recordings were obtained using an Oocyte Clamp Amplifier OC-725 B (Warner Instruments Corp. , USA) connected to an Axon Digidata 1440A digitizer (Axon Instruments, Molecular Devices, USA) and was performed at ~19˚C under continuous flow of Kulori medium with the oocytes clamped at -60 mV. Data were sampled at 2 kHz using the pClamp 10. 4 acquisition software (Axon Instruments, Molecular Devices, USA). The microelectrodes were pulled from glass capillaries (TW 120. 3, World precision instruments, USA) on a programmable micropipette puller (Narishige, Japan). The resistance when filled with 3 M KCl ranged from 0. 5 to 1. 5 MO. Ag/AgCl reference electrodes were connected to the bath with agar bridges. For a minimum of 4 hours prior to recording, all oocytes were incubated in BAPTA-AM at a final concentration of 100 μM to chelate intracellular Ca 2+ ions and hereby prevent activation of endogenous calcium activated chloride channels during recordings.
and Cel-ACR-19 were used in an alignment with the identified putative ACR-16 sequences from Clade I parasitic nematodes. The accession numbers of the sequences used for the alignment are: Caenorhabditis elegans: ACR-16 NP_505207, ACR-19 NP_001129756. Trichuris suis: putative ACR-16 KFD48832. 1 putative ACR-19 KFD70086. 1. Trichuris trichiura: putative ACR-16 CDW52185; putative ACR-19 CDW53523. Trichuris muris: putative ACR-16 WBGene00290200; putative ACR-19 WBGene00291941. Trichuris spiralis: putative ACR-16 KRY38920. 1, putative ACR-19 KRY27533. 1.
Background: The objective of the study was to describe the epidemiology, management and cost of nontuberculous mycobacteria lung disease (NTM-PD) in France. Methods: A retrospective analysis was performed using the SNDS database over 2010-2017. Patients with NTM-PD were identi ed based on the ICD10 codes during hospitalizations and/or speci c antibiotics treatment regimens. The study population was matched (age, gender and region) to a control group (1: 3) without NTM-PD. Results: 5,628 patients with NTM-PD (men: 52. 9%, mean age=60. 9 years) were identi ed over the study period and 1,433 (25. 5%) were treated with antibiotics. The proportion of patients still receiving treatment at 6 and 12 months was 40% and 22%, respectively. Patients with NTM-PD had more co-morbidities compared to controls: corticoids (57.
Background More than 190 species and subspecies of non-tuberculous mycobacteria (NTM) have been described. Among these, some like Mycobacterium avium complex (MAC), may cause pulmonary disease (NTM-PD) with increasing frequency in non-acquired immunode ciency syndrome (AIDS) patients (,,). The incidence and prevalence of NTM-PD has even overpassed that of tuberculosis in some settings (,). This increase has been observed in older individuals and those with underlying bronchiectasis and may be associated with multifactorial factors. In Europe, it is estimated that the annual prevalence rate of diagnosed NTM-PD cases is in the range of 3-6/100,000  (4,,). In France studies on NTM-PD have been conducted either based on cystic-brosis registries or from laboratory databases from university hospitals () but not on whole population.
Study Design We conducted a retrospective study using the French nationwide claims and hospitalisation database, the Système National des Données de Santé (SNDS) which covers more than 99% of the French population (nearly 66 million people) and represents one of the largest medico-administrative databases in the world. The SNDS database contains anonymous data on healthcare encounters (public and private), diagnostic-related groups, drugs, medical devices, procedures, laboratory tests (without results), date of death excluding cause, hospitalizations with ICD10 codes and discharge summaries with the main and secondary diagnoses. Patients with NTM-PD were identi ed in the database based on hospitalizations with ICD-10 codes speci c for NTM-PD infection and antibiotics combination for the treatment of the disease using outpatient drug consumptions.
Results A total of 5,628 patients with NTM-PD were identi ed in the SNDS database between 2010 and 2017, 4,898 patients from hospitalizations and 730 from outpatient drug consumptions. Among patients identi ed through hospitalizations, 703 had a speci c treatment for NTM-PD vs 4,195 with no treatment. The mean age was 60. 9 years (SD ± 19. 5) and 52. 9% were males. The Universal Health Coverage for lowincome individuals was observed in 8. 8% of patients (Table  1 ). A total of 3,954 patients were diagnosed with NTM-PD between January 01/2010 and December 31/2017; thus, the prevalence of NTM-PD was estimated at 5. 92 per 100,000 inhabitants over 8 years. The incidence rate of NTM-PD (Figure  1 ) remained stable over time, with a min of 1. 025/100,000 in 2010 (N=662) and a max of 1. 096/100,000 (N=732) in 2017 with slight variations in-between years.
Discussion This retrospective study using the SNDS, a French nationwide claims and hospitalisation database, described the epidemiology, comorbidities, management, mortality, and costs of NTM-PD in a real world setting in France. Thanks to its comprehensive coverage of the whole population (99%), the SNDS database allowed this study to include all NTM-PD patients identi ed with the ICD-10 codes in France. Our study not only has demonstrated the higher mortality rate in NTM-PD patients and the economic burden related to this condition but also suggested that guidelines are not always respected. Prevalence (6/100,000 inhabitants over 8 years) and incidence (1/100,000) were close to those reported in previous studies conducted in Europe with same or different methods including Delphi method, registry analysis, retrospective study of laboratory data (6,8,,,,).
$28,405) and second year ($48,114 vs. $28,990), respectively. Interestingly, cost for an NTM-PD patient clearly surpasses the annual cost per patient for chronic respiratory diseases including COPD (€1013) or asthma (€1950) among others (). The limitations of the SNDS database are inherent to those of claims databases. The paucity of clinical information and laboratory results did not allow the use of the ATS/IDSA guidelines which include clinical, radiologic, and bacteriologic criteria to pose a diagnosis of NTM-PD (2). We also did not have information on speci c NTM species to be able to have species-speci c results. Identi cation of NTM-PD cases using the ICD-10 codes along with the prescription of antimycobacterial treatments may have covered the majority of patients with NTM-PD; however, we may have missed patients who may have been misclassi ed with the ICD-10 codes.
However, there are global efforts within governments, nongovernmental organizations, academic research organizations, and industry sectors to bridge this gap and focus on achieving optimal health outcomes without the need for animal testing through recognition of the interconnectedness between people and all species that share the environment. With this in mind, it is recognized that focused and concerted efforts to advance methods for cross-species extrapolation that leverage existing toxicity data from both mammals and other model organisms can be used to protect all species. To expedite the development and regulatory acceptance of computational methods, particularly bioinformatics, for informing cross-species extrapolation for the evaluation of chemical safety, there is a need to bring together tool/database/ method developers and regulators in a global cross-sector collaborative consortium.
gov/research/ administrator-memo-prioritizing-efforts-reduce-animal-testingseptember-10-2019). Even more recently, the Scientific Committee on Consumer Safety (2021) produced its 11th revision of guidance for the testing of cosmetic ingredients to provide greater focus on the application of NAMs. Government pledges and changes to legislation such as these, along with a growing appreciation of the need to further develop relevant and predictive methods for safety assessment that do not necessarily rely on animals, show that the data landscape is also changing. There is now greater focus on the generation of mechanistic, cell-based, and computationally derived information for consideration as alternatives to animal testing. This shift is exemplified by data collected from available ecotoxicology literature curated in the ECOTOXicology Knowledgebase (ECOTOX; https://cfpub.
epa. gov/ecotox/) from the 1980s to the present. The number of growth and mortality studies added to ECOTOX have remained relatively consistent throughout the last four decades, whereas increases have been observed in the reporting of molecular and cellular effects data since 2000. To facilitate the use of the increasing influx of mechanistic data to establish causal links to apical changes in individuals or populations, the adverse outcome pathway (AOP) conceptual framework is being considered or actively adopted in many regulatory, industry, and academic settings  (Ankley et al. , 2010).
Although the magnitude of the challenge to connect potential for exposure to potential for effect in risk assessment should not be underestimated, the number of available models to better characterize and understand chemical concentrations and distribution within organisms is growing. Tools such as the MERLIN-Expo software (https://merlin-expo. eu/) and Gastro-Plus (https://www. simulations-plus. com/software/gastroplus/) provide increasingly good mechanistic modeling approaches for simulating chemical distribution in humans. More recent physiologically based pharmacokinetic models in fish provide options for increased cross-species extrapolation  (Rivetti et al. , 2020). Nonetheless, there remains a significant research challenge to address toxicokinetic modeling for less wellcharacterized species.
Acknowledgment-We thank  G. Ankley  and  T. Schlekat  for providing comments on an earlier draft. This manuscript has been reviewed in accordance with the requirements of the  Office of Research and Development, US Environmental Protection Agency. Disclaimer-The views expressed in this work are those of the authors and do not necessarily reflect the views or policies of the  USEPA , nor does the mention of trade names or commercial products constitute endorsement or recommendation for use. The views represented in this paper are those of the author and do not represent official policies of OECD.
ecotoxxplorer. ca/) OmicsNet (https://www. omicsnet. ca/) Tissue/organ Conservation of tissues and organs The Monarch Initiative (https://monarchinitiative. org) Phenotypic relationships among species Organism Phylogenetic relationships among species T-Rex (http://www. trex. uqam. ca/) MEGAX (https://www. megasoftware. net/) PhyML (http://atgc. lirmm. fr/phyml/) RAxML (https://github. com/stamatak/standard- RAxML) NGPhylogeny (https://ngphylogeny. fr/) IQTree (http://www. iqtree. org/) Population Population-sequencing approaches VSEARCH (https://github. com/torognes/vsearch) Metabarcoding SWARM (https://github. com/torognes/swarm).
ACKNOWLEDGEMENTS This study was funded under contract from  MP Labo. The authors are very thankful to owners and their dog who participated in the study. We thank our colleagues,  Laetitia Wiggers  and  Claire Diederich  for cortisol analyses at the  lab in Namur (Namur University-Unité de Recherche Vétérinaire Intégrée URVI) , and  Laureline Chaise  for useful help for statistical analyses. The work was carried at  Ecole Nationale Vétérinaire d'Alfort ,  Service Ethologie , 7 avenue du Général de Gaulle, 94700, Maisons-Alfort, France.
Caenorhabditis elegans possesses one of the most extensive, and diverse nAChR gene family  [33] , with 29 nAChR subunits divided into five groups based on sequence homology and named after the first of their number to be discovered  [34]. One of these groups, the ACR-16 group, contains 11 genes  [34] , which is in sharp contrast to the low number of nAChR subunits found within the ACR-16 group of Clade I parasitic nematodes. In our previous database search for a potential oxantel target within Trichuris spp. , we identified only two nAChR subunits from the ACR-16 group of Trichuris spp. [30]. This was in accordance with Williamson et al. [35] , who reported only two members from the ACR-16 group in the genomic data from the closely related Clade I parasitic nematode Trichinella spiralis. One was the ACR-16-like subunit, which constituted the O-AChR from T.
Identification of ACR-16-like and ACR-19 sequences from Trichuris muris Trichuris muris is, like T. suis, used as a model for T. trichiura. Oxantel was previously shown to act on the nAChR made of ACR-16-like subunits from T. suis  [30]. In order to investigate the ACR-16-like nAChR from T. muris, we identified and cloned the full-length coding sequence of the T. muris acr-16-like subunit cDNA (Tmu-acr-16-like). The cloned T. muris acr-16-like sequence differed from the putative full-length Tmu-acr-16-like cDNA sequence available in WormBase (accession number WBGene00290200) by two synonymous nucleotide substitutions (CCG → CCA at codon 327 and AGT → AGC at codon 427), and was therefore deposited in GenBank under the accession number MZ322663. In order to explore all the members of the ACR-16 group of Trichuris spp, we performed searches in genomic databanks that led to the identification of the C.
Sequence analysis and alignment The Tsu-ACR-16-like (accession number MT386096) and the Tsu-ACR-19 (accession number KFD70086) were used as queries in database searches for amino acid sequences of ACR-16-like and ACR-19 from T. muris using the protein-protein BLAST (BLASTp) service at the National Center for Biotechnology Information (NCBI) service  [53]. The Tsu-ACR-16-like and the Tsu-ACR-19 were used in an alignment with the identified sequences. The accession numbers of the identified sequences used for the alignment are: Trichuris muris: ACR-16-like MZ322663; ACR-19 WBGene00291941. Trichuris suis: ACR-16-like MT386096; ACR-19 KFD70086. Trichuris trichiura: ACR-16-like CDW52185; ACR-19 CDW53523. Signal peptide was predicted using the SignalP 4. 1 server  [54]  and the transmembrane regions were predicted using the TMHMM version 2 server  [55].
Statistical analysis All acquired electrophysiological data was analysed with Clampfit 10. 7 (Molecular Devices, Sunnyvale, CA, USA) and GraphPad Prism 9 (GraphPad Software, La Jolla, CA, USA). All data analysis was performed on normalized current values. For the efficacy tests, the normalized drug-group means were statistically analysed using a non-parametric Kruskal-Wallis Test with a Dunn's multiple comparison test, where P < 0. 05 was considered significant. The dose-response relationships were established by fitting the normalized currents as a function of drug concentration to a Hill equation using non-linear regression analysis with a variable slope model. The following equation was used: Irel = Imin + (Imax -Imin)/ (1 + 10^((LogEC50-[D])*nH)) where Irel is the mean relative current, Imax, is the relative current obtained at saturating agonist concentration, Imin is the relative current obtained at agonist concentrations 0 µM, EC50 is the concentration of agonist at which 50% of the maximal current response is obtained, [D] is the drug concentration and nH is the Hill coefficient.
and additionally processed in GeneDoc (IUBio). The accession numbers of the ACR-16-like and ACR-16 sequences from Clade I, III and V nematodes used for the alignment to show the ligand binding loops in the ECDs are: Trichuris muris: MZ322663; Trichuris suis: MT386096; Trichuris trichiura: CDW52185; Ascaris suum: KP756901; Parascaris equorum: AZS27834. 1; Caenorhabditis elegans: CCD64102. 1; Haemonchus contortus: AZS27833. 1; Ancylostoma ceylanicum: MT163735; Ancylostoma caninum: QEM53385; Necator americanus: MT163736.
RNA-Seq Analysis The CRAC software  (Philippe et al. , 2013)  was used to strandspecifically map the reads to the reference genomes of B. suis 1330 (NC_004310. 3 and NC_004311. 2 for chromosomes I and II, respectively) and B. microti CCM 4915 (NC_013119. 1 and NC_013118. 1 for chromosomes I and II, respectively), and to filter out multi-aligned reads. 96-98% of the total mapped reads of all samples were single-aligned reads to the corresponding reference genomes, except for B. suis at pH 7/20 min (61%), and only these reads were kept for further analysis. Following mapping, the read counts for each gene were determined with the "featureCounts" software  (Liao et al. , 2014). Based on the CRAC output, normalization and differential gene expression analysis for the two different pH-conditions in each species were performed with DESeq  (Anders and Huber, 2010) , calculating the ratios of normalized reads at pH 4.
5/normalized reads at pH 7. 0, and the corresponding log2values of the fold-changes, for each species and time point (20 min or 2 h). A threshold of ≥1. 5 or ≤-1. 5 was fixed for the log2-fold change. The sequencing reads from this study were deposited in the SRA database (NCBI) under the accession number PRJNA644280. The genes selected on the base of the ≥ 1. 5/≤ -1. 5 log2fold change threshold were classified by assigning the predicted proteins to their respective Cluster of Orthologous Groups (COG), using the Genoscope MicroScope platform from the French Sequencing Center 1   (Vallenet et al. , 2020) , and according to B. suis 1330 and B. microti CCM 4915 operons predicted in the Database of prokaryotic OpeRons (DOOR)  (Mao et al. , 2009). In addition, a search for genes reported as virulence-associated was performed using the Pathogen-Host Interaction Data Integration and Analysis System (PHIDIAS) -Virulence Factors (Victors) 2   (Sayers et al.
, 2019) , as well as on the Virulence Factor DataBase (VFDB) 3   (Liu et al. , 2019). The mapping tool available at the Pathosystems Resource Integration Center (PATRIC) 4  allowed the screening for possible clusters in the expression profiles. The metabolic pathway assessment was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database. 5.
Quantitative Reverse Transcriptase Polymerase Chain Reaction To validate RNA-seq results, 95 differentially expressed candidate genes were selected and their expression changes at the pH-values and time points chosen were confirmed by Quantitative Reverse Transcriptase PCR (RT-qPCR). Primers were designed with the Primer3 software (Supplementary Table  1 ). Complementary DNA (cDNA) was obtained by reverse transcription of 1µg of total RNA in a final reaction volume of 20 µl, containing 4 µl SuperScript VILO Master Mix, at 42 • C for 90 min. The working sample of cDNA was diluted 1:20 (2. 5 ng/µl). RT-qPCRs were performed in triplicate per sample and experimental condition, using a Light Cycler TM 480 qPCR machine (Roche) and SYBR Green I Master (Roche) in a final volume of 1. 5 µl per reaction.