dataesr/scientific-paragraphs-categorization huggingface dataset:
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A description of any restrictions on data availability -For clinical datasets or third party data, please ensure that the statement adheres to our policy Single-cell RNA-sequencing data have been deposited in Gene Expression Omnibus (GEO) with the accession code GSE205412 (https://www. ncbi. nlm. nih. gov/geo/ query/acc. cgi?acc=GSE205412). Genome annotation ENCODE VM9 (https://hgdownload. soe. ucsc. edu/gbdb/mm10/) was used for mapping single-cell RNAsequencing data. All other data supporting the findings of this study are included in the article, its supplementary materials or source data.
Animals and Samples Collection The study was performed on adult research pony mares housed in the Experimental Unit of Animals Physiology of l'Orfrasière (UEPAO; INRAE Val de Loire 1297, Nouzilly, France) between March 2016 and January 2017. Thirty-six Welsh pony mares, aged 5 to 18 years were included and 57 sets of samples were recovered. At sampling, seven mares were maiden while the other 29 mares had foaled at least once. Samples were obtained from mares once (n = 18), twice (n = 15) or three times (n = 3) during the reproductive season. Mares were examined by transrectal palpation and ultrasonography for genital health and to determine the reproductive stage. Data and samples were obtained during the breeding season from 29 mares in estrus (showing a dominant follicle and endometrial oedema) and 18 mares in diestrus (presenting a corpus luteum in absence of oedema).
Statistical Analysis In order to limit the effect of dilution and allow comparison between samples, results are expressed as total or active MPO/total protein ratio, referred to as R T and R A , respectively. A general linear mixed model (SAS version 9. 3) was used to compare data between groups including post hoc test and results are expressed as least square means. When the model did not converge, a general linear model was used to compare groups. Graph-Pad Prism version 9 was used to perform other statistical analyses. Normal distribution of parameters was tested with the Shapiro-Wilk normality test. Values of MPO concentration and total protein were non-normally distributed, and IRS values were normally distributed. Correlations were evaluated using the Spearman test. Statistical significance was established at p-value less than 0.
Material and methods. The MASCADI protocol was reviewed and approved by the regional Ethics Committee (Comité de Protection des Personnes Est, Dijon, France CPP Est III, CHRU Nancy, N° 2017-A00022-51) and recorded on ClinicalTrials. gov (clinical registration number: NCT03202823). Two-hundredand-one patients were enrolled. As described previously, patients enrolled in the present study were admitted to the Department of Cardiovascular Surgery at the University Hospital of Dijon (Burgundy, France) for the surgical treatment of an atheromatous internal carotid artery (ICA) stenosis whether symptomatic or not. 18  A stenosis was considered symptomatic if stroke or transient ischemic attack (TIA) attributed to the ICA lesion occurred within the previous 6 months before intervention. According to the trial category (Interventional research that does not involve drugs or non-CE-marked medical devices and that involves only minimal risks and constraints for the patient) and the ethics committee, all patients received written information note on the study.
Lysophospholipid quantitation by LC-MS2 For lipidomic analysis, carotid plaques were opened longitudinally and core samples of atheroma plaques were harvested by using 3 mm biopsy punches (Kai Medical, Solingen, Germany). Sites of harvesting were normalized between the samples by selecting the plaque area corresponding to the maximal stenosis. Plaque biopsies (2-10 mg) were crushed in an Omni Bead Ruptor 24 apparatus (Omni International, Kennesaw, USA) with 1000 µL of phosphate buffer saline and circa twenty 1. 4 mm OD zirconium oxide beads (S=6. 95 m/s, T=30s, C = 3; D = 10s). Lipids corresponding to 1 mg of tissue were spiked with a mix containing 1 mg of di14:0-PC, 1 mg of di14:0-PE, 1 mg of d18:1/17:0-SM and 0. 1 mg of 14:0-LPC used as internal standards. Phospholipids and lysophospholipids were analyzed by LC-MS/MS using a 6460 mass spectrometer (Agilent Technologies) equipped with an electrospray ionization source and MassHunter data system.
Statistical analysis We compared patients with diabetes to patient without diabetes. Normality was assessed using the Shapiro-Wilk test. Accordingly, quantitative data were presented as medians [interquartile range] or means (standard deviation) if normally distributed. Groups were compared with a Student's t-test or the Kruskall-Wallis nonparametric test. When indicated, significance was corrected for multiple comparison by the Benjamini-Hochberg procedure. Qualitative data are presented as absolute value and percentage and compared by chisquared or Fisher's exact tests, as appropriate. Correlations were evaluated with the Spearman correlation method. Missing data were considered to be at random and were omitted in the analysis. R studio was used for statistical analysis.
Among the MBLs, NDM, an enzyme composed of 270 amino acids, is the most common enzyme isolated worldwide. The first report of NDM-1 was from an isolate of K. pneumoniae recovered from a Swedish patient repatriated from New Delhi  [7]. In 2022, according to the β-lactamase Database (BLDB) (http://www. bldb. eu)  [8] , 41 variants of NDM have been identified. The NDM-14 variant differs from NDM-1 by one amino acid substitution at position 130 (D130G). This substitution is known to increase carbapenemase activity compared with NDM-1  [9]. This variant was identified in a clinical isolate of Acinetobacter lwoffii from a wound of a patient hospitalised in intensive care unit in Jinan, China  [9]. Although NDM has been identified in many species of Enterobacterales, Pseudomonas or Acinetobacter, it is more common in K.
Whole-genome sequencing and phylogenetic analysis A short-read next-generation sequencing (NGS) was performed on 431 K. pneumoniae ST147 isolates (including 37 NDM-14-producing isolates) using a HiSeq system (Illumina Inc, San Diego, United States) (GenBank accession numbers: BioProject PRJNA925084). Illumina reads were assembled using shovill v1. 1. 0 (https://bio. tools/shovill) and spades v3. 14. 0. MLST and resistome analysis were performed using PubMLST (https:// pubmlst. org/) and Resfinder (https://cge. food. dtu. dk/services/ResFinder/) databases. For phylogenetic single nucleotide polymorphism (SNP) based analysis, NGS sequence reads were mapped to a reference genome included in the study (NDM-14-producing K. pneumoniae 310H4) using SNIppy v4. 6. 0. Metadata and phylogenetic trees were visualised using iTOL v6.
5. 2 (European Molecular Biology Laboratory). All data resulting from the assembly and SNP analysis are provided in Supplementary Table  S2. The virulence score was assessed using Kleborate v2. 0. 0 (Institut Pasteur, France). Long-read sequencing was conducted on eight NDM-14producing K. pneumoniae isolates, one per outbreak, and one NDM-1-producing K. pneumoniae ST147 isolate phylogenetically close to the NDM-14-producing K. pneumoniae ST147 clone. This NDM-1-producing K. pneumoniae (312J6) isolate was from a patient hospitalised in Paris. Long-read sequencing was performed using Oxford nanopore MinION technology (Oxford Nanopore, Oxford, United Kingdom) as previously described  [31]. By combining data from Illumina and MinION sequencing, we fully assembled and annotated the different plasmids using RAST v2.
Molecular clock and Bayesian phylogenetic analysis For molecular clock and Bayesian phylogenetic analysis, only the 37 NDM-14-producing K. pneumoniae strains were used. First, the strength of the temporal signal was evaluated using IQTree v1. 6. 12 and TempEst v1. 5. 3 softwares (http://tree. bio. ed. ac. uk/software/tempest/)  [32, 33]. Bayesian analysis was performed using Beast v2. 6. 1 software (run with a Markov chain Monte Carlo length of 1 × 10 9 , sampling every 5 × 10 3 steps) as previously described  [34]. We used model parameters that had the best fit: generalised time reversible (GTR) substitution model, lognormal relaxed clock and constant population size as previously used with a K. pneumoniae ST147 population  [35]. Parameter estimates were visualised using Tracer v1. 7. 2 (https:// beast.
Plasmid analysis of NDM-14producing Klebsiella pneumoniae ST147 Several replicases were identified in the collection of NDM-14 producing strains. Plasmids IncFIB and ColRNAI were observed in all 37 strains, IncR in 36 strains and IncHIB in 29 strains (Figure  3 ). The bla NDM-14 -carrying plasmid has been entirely reconstructed using long-read sequencing on eight NDM-14producing K. pneumoniae isolates (Figure  4 ). All strains harboured an IncFIB plasmid of 54,061 base pairs (bp) in size (GenBank accession number PRJNA925431). Analysis of the close genetic context of bla NDM- 14 revealed the presence of a ISAba125 likely involved in the carbapenemase expression  [36]. By contrast to what is commonly reported in NDM-producing Enterobacterales, this ISAba125 was truncated by ISSpu-2 (Figure  4 ).
5 (± 2. 5 ) × 10 -7 transconjugant/donor. Escherichia coli J53 transconjugants carrying bla NDM-14 exhibited resistance to all tested β-lactams including aztreonam. Whole genome sequencing performed on one transconjugant revealed the presence two replicases of IncFIB-type and of IncH1B-type. The IncH1B-type plasmid was of ca 350 kilobases (kb) in size and was closely related to pVIR147Tu. 12PI (GenBank Accession Number CP072918). It possesses a complete transfer operon as well as aerobactin and tellurite resistance operons. This IncH1B-type plasmid probably behaves as a helper plasmid allowing conjugation of the bla NDM-14 carrying plasmid. A long-read sequencing was also performed on the isolate 312J6, a NDM-1 producing K. pneumoniae ST147 that is very close to the cluster of NDM-14 producers (30 to 36 SNPs).
This strain also harboured IncFIB, IncR, IncHIB and ColRNAI type plasmids, as well as the same antimicrobial resistance genes (bla CTX-M-15 , bla OXA- 1 , bla OXA-9 , bla TEM-1 , aac(6')-Ib-cr, qnrS1, oqxA, oqxB, sul1, dfrA5, mph(E) or catB3), except that bla NDM-14 was replaced by bla NDM-1. Comparison of both IncFIB-type plasmid sequences revealed only one SNP of difference in bla NDM-1. This result indicated that the bla NDM- 14 carrying plasmid derived directly from the plasmid carrying bla NDM-1. The BLAST analysis of the complete bla NDM-14 -carrying plasmid identified similar plasmids in database (100% coverage with 99% identity). However, all submitted plasmids carried bla NDM-1 gene and seem to have disseminate in Italy (GenBank accession number CP074090), in Thailand (LC521845) and in Switzerland (CP082992).
Acknowledgments We thank the staff of animal facilities, mouse supporting services, flow cytometry, histopathology, microscopy and imaging, and cell culture of IGBMC and ICS for excellent technical assistance. We would like to thank  Dr. N. Ghyselinck  and  Dr. N. Vernet  ( IGBMC, Illkirch ) and  Dr. P. Germain  ( CBS, Montpellier ) for their advices on RAR antagonists, and  Dr. William Paul  ( NIH, USA ) for providing 4C13R mice.
Funding We wish to acknowledge the funding supports from l' Agence Nationale de la Recherche   ANR-19-CE17-0021  (BASIN) to LM and  JB ,  ANR-22-CE14-0023-02  (nRegSKIN) to LM,  Fondation Recherche Medicale (Equipes FRM   2018 ) to LM, and the first joint programme of the  Freiburg Institute for Advanced Studies (FRIAS)  and the  University of Strasbourg Institute for Advanced Study (USIAS)  to LM. The study was also supported by the grant  ANR-10-LABX-0030-INRT , a  French State  fund managed by the  Agence Nationale de la Recherche  under the  frame program Investissements d'Avenir   ANR-10-IDEX-0002-02 ; the  Centre National de la Recherche Scientifique (CNRS) ; the  Institut National de la Santéet de la Recherche Medicale (INSERM) , and the  Universitéde Strasbourg (Unistra). CH, PMa, PMe  were supported by PhD fellowships from  University of Strasbourg  and  Region Alsace.
33, 95% CI = 0. 78-2. 27, Fig. 3 , Supplementary Data 2). In ANDIS, NogoR also replicated (HR = 1. 20, 95% CI = 1. 07-1. 34, Fig. 3 ). NogoR was also a risk factor for incident (OR = 1. 45, 95% CI = 1. 15-1. 83) and prevalent diabetes in AGES-Reykjavik (OR = 1. 77, 95% CI = 1. 60-1. 95). In the top associated proteins, four were protective including SMAC, coactosinlike protein, testican-1 and HEMK2, of which HEMK2 was the most protective (HR = 0. 78, 95% CI = 0. 59-1. 03). Levels of HEMK2 showed an interaction with C-peptide levels (P = 0. 01). In the AGES-Reykjavik study, HEMK2 was also protective for prevalent diabetes (OR = 0. 78, 95% CI = 0. 72,0. 85). Levels of testican-1 and HEMK, SMAC, coactosinlike protein were correlated (Supplementary Fig. 5 ). At baseline not all proteins showed a clear upregulation in level in incident insulin users; the most profound effects were observed for NogoR, IL-18 Ra, ENPP7, HSP 90b (Supplementary Fig.
Plasma sample and data used in this study deriving from the ACCELERATE trial were provided by Eli Lilly pharmaceutical company (data owners of the placebo arm of the trial; co-authors IP, KD, AE)  62. The multicentre trial involved 543 centres in 36 countries and for each of them the appropriate national and/or institutional regulatory and ethics boards approved the protocol independently (protocol number of internal approval at Lily, I1V-MC-EIAN-9/19/19)  62. All patients provided written informed consent. Use of existing de-identified samples from the ACCELERATE cohort for the present research is classified as non-human research, and thus IRB approval was not required. The AGES-Reykjavik study was approved by the NBC in Iceland (approval number VSN-00-063), and the National Institute on Aging Intramural Institutional Review Board, and the Data Protection Authority in Iceland.
L. , or the Animal Care Committee at the Institut de recherches cliniques de Montréal (J. E. ). Animals were maintained in approved institutional animal facilities overseen by qualified veterinary teams, under specific pathogen free conditions. Day to day monitoring of animal wellbeing was performed by facility technicians and by the researchers directly involved in the studies. None of the cell lines used feature in the list of known misidentified cell lines (https://iclac. org/databases/cross-contaminations). Discovery cohorts. Specific details on DCS  63  , GoDARTS 64 and ANDIS  65  have been described elsewhere  66. These cohorts were selected based in part on satisfactory quality control for biomarkers stability in stored samples. DCS. The Hoorn Diabetes Care System (DCS) cohort is a prospective cohort with currently over 14,000 individuals with routine care data  63.
ANDIS. In the All New Diabetics in Scania (ANDIS) cohort, people with incident diabetes within Scania County, Sweden were recruited from January 2008 until November 2016 and all participants gave written informed consent. Regional ethics review committee in Lund approved the study. An electro-chemiluminescence immunoassay was used to measure C-peptide on a Cobas e411 (Roche Diagnostics, Mannheim, Germany) or a radioimmunoassay (Human C-peptide RIA; Linco, St Charles, MO, USA; or Peninsula Laboratories, Belmont, CA, USA). The Clinical Chemistry database was used to obtain HbA1c levels. Validation cohorts. External validation was performed in four external cohorts, ACCELERATE, AGES-Reykjavik, MDC-CC and DESIR. ACCEL-ERATE is a clinical trial aimed at investigating the effect of evacetrapib on major adverse cardiovascular outcomes and has been described elsewhere  62.
Molecular measurements. A flowchart of the current study is given in the Supplementary Fig. 1. In the three discovery cohorts, those were selected with an age at diagnosis >35 years, not GAD positive, with GWAS data and with a blood sample close to diagnosis, with a median diabetes duration of 2. 6, 1. 4 and 0 years in DCS, GoDARTS and ANDIS respectively (Table  S1 ). The metabolomics, lipidomics and proteomics groups were of different sizes (see further details below). Individuals were ranked based on the time between diagnosis and sampling date and those with the smallest time between diagnosis and sampling were selected. For metabolomics, we selected 1267 in DCS, 900 in GoDARTS and 900 in ANDIS. For lipidomics, 900 individuals were selected in DCS, GoDARTS and ANDIS. For proteomics, we selected 600 individuals in DCS and GoDARTS.
org/10. 1038/ s42255-022-00628-3) and can be found in Supplemental Material. Lipid nomenclature is used and SwissLipids database identifiers are provided (Supplementary Data 3)  73. Samples (n = 2,608) were measured in batches of 84 samples each. Lipid identifications with a signalto-noise ratio >5, and a signal intensity 5-fold higher than in corresponding blank samples were considered for further data analysis. Validation of identity between cohorts was achieved by confirming that each TAG species was identified with a similar fatty acid profile. Spectra were analysed with in-house developed lipid identification software based on LipidXplorer  74. TAGs are quantified as species (e. g. TAG 48:1;0). Fatty acid amounts within TAG species were calculated based on intensities of neutral losses of fatty acid fragments.
Federated database. All main analyses were performed on a federated database system. Opal, an open-source data warehouse (Open Source Software for BioBanks, OBiBa) was used to store cohort data on local nodes and remote analysis was performed in R using DataSHIELD  78  and dsSwissKnife R packages  79. A central server was set up at the Swiss Institute of Bioinformatics to manage federated node access, user administrator and software deployment. Local nodes were set up at the respective cohorts. All data was harmonized according to the CDISC Study Data Tabulation Model (www. cdisc. org) prior to inclusion into the federated database. Mendelian randomisation. Genetic instruments for proteins, lipids and metabolites predictive of progression in the three cohorts were obtained from published GWASs.
Next, Stop & Glo reagent was added to each tube and the Renilla luciferase activities were measured. Measurements were read with PuTTY software and all Firefly luciferase activities were normalized with Renilla luciferase activities to obtain the NF-κB signalling ratios using Microsoft Excel software. Hepatocyte cell isolation and culture. Ethics approval for rodent studies was obtained from the Animal Care Committee at the Institut de recherches cliniques de Montréal (JE). Male C57B/6 N mice (Taconic Biosciences, East Greenbush, N. Y. ) were maintained on a 12-h lightdark cycle and fed regular grain-based diet (GBD) (Teklad Global 18% Protein Rodent Diet) from Teklad Diets, Envigo (Huntingdon, UK) consisting of 24 kcal% protein, 58 kcal% carbohydrates, and 18 kcal% fat. Animals were euthanized using isofluorane and CO 2.
Reporting summary Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. the data. Requests will be subject to consideration by the steering committees of the three cohorts (DCS, ANDIS, GoDARTS) and the management board of RHAPSODY. Time frame for a response will be within 4 months. Data requests under agreement will be considered for purposes of reproducing the data and subject to appropriate confidentiality obligations and restrictions. DCS and GoDARTS proteomics data: restricted access for the proteomics data can be obtained via the European Genome/Phenome archive under accession number EGAD00010002447. Requests via EGA will be forwarded to the corresponding authors and subjected to the same procedure and time frame as the metabolomic and lipidomic data as outlined above.
Replication data: Proteomics data of individuals with incident diabetes described in Gudmundsdottir et al. 32  were used for lookups of our protein top hits. Lipid top hits were compared to the lipid data of people with and without diabetes from Fernandez et al. The GWAS on lipids described by Tabassum et al. 80  was used to identify lipid QTLs (https://mqtl. fimm. fi). The GWAS data of Lotta et al. 81  was used to identify metabolite QTLs. The GWAS on type 2 diabetes from Mahajan et al. 82  was used to find diabetes risk variants. Functional studies: Source data for functional studies are provided with this paper. Source data are provided with this paper.
Acknowledgements We acknowledge the support of the  Health Informatics Centre, University of Dundee  for managing and supplying the anonymised data. The authors wish to thank the Core-IT group of  SIB Swiss Institute of Bioinformatics  and in particular  Jorge Molina  for expert technical help in setting up and maintaining the federated database. G. A. R. thanks  Claudio Elgueta Karstegl  for technical support. The authors thank participants of the included cohorts. We are grateful to  Mélanie Guévremont  and the  CRCHUM Cellular Physiology core facility  for beta cell mass analyses. The ANDIS study was financed by  Swedish governmental funding of clinical research (ALF) , the  Faculty of Medicine at Lund University , the  Swedish Research Council  project grant no. 2020-02191  and strategic research area grant no.
2009-1039  (EXODIAB), from the  Swedish Foundation for Strategic Research   IRC15-0067  ( LUDC-IRC ) and  Vinnova Swelife. E. R. P. holds a  Wellcome Trust New Investigator Award  ( 102820/Z/13/Z ). G. A. R. was supported by a  Wellcome Trust   Investigator Award  ( 212625/Z/18/Z ),  MRC   Programme grants  ( MR/R022259/1 ,  MR/J0003042/1 ,  MR/L020149/1 ), an  Experimental Challenge Grant  (DIVA,  MR/L02036X/1 ), a  Diabetes UK  Project grant ( BDA16/0005485 ) and  Innovation Canada  for a  John R Evans Leader Award. G. E. L. was supported by a  CIHR Project Grant  ( PJT-153144 ) and holds the  Canada Research Chair in Adipocyte Development. This project has received funding from the  Innovative Medicines Initiative 2 Joint Undertaking , under grant agreement no. 115881  (RHAPSODY). This Joint Undertaking receives support from the  European Union 's  Horizon 2020 research and innovation programme and EFPIA.
| Population genetic analyses For ticks collected in the Ossian Sarsfjellet colony, DNA from each tick was extracted individually following the protocol of  Kempf et al. (2009). These samples were then genotyped at eight independent microsatellite markers developed specifically for this tick species  (McCoy & Tirard, 2000). Microsatellite PCR amplification and allele size determination were performed as described in  Kempf et al. (2009). Genotypes were visualized using an ABI PRISM 3130xl Genetic Analyser and allele sizes were assigned using GeneMapper v. 4 (Applied Biosystems). The final corrected genotype data can be found here: https://doi. org/10. 5281/zenodo. 7547277. For the other tick populations included in statistical analyses, we used the microsatellite data previously published by  Dietrich et al.
Genetic diversity in each colony was estimated by calculating allelic richness using a rarefaction method, and Nei's unbiased gene diversity (H S ). Within-population departures from Hardy-Weinberg (HW) proportions were investigated by estimating the inbreeding coefficient (F IS ). The significance of this estimator was assessed by randomizing alleles among individuals within samples (2400 permutations). These basic analyses were all carried out using FSTAT  (Goudet, 2003). To examine population isolation, pairwise F ST estimates were calculated from microsatellite data according to  Weir and Cockerham (1984). Significance was assessed by permuting multilocus genotypes among populations using FSTAT  (Goudet, 2003) , with 2100 permutations and a significance level of 5%, corrected using the standard Bonferroni method for multiple tests.