dataesr/scientific-paragraphs-categorization huggingface dataset:
(2018). This Hi gas might be extra-planar gas that is not actually associated with the galaxy (e. g. Vargas et al. 2017) , and thus not affecting the dust properties. An overestimation of the galaxy gas mass would also lead to an overestimation of the metal mass and thus to lower dust-to-metal ratios. Dwarf galaxies (which typically have higher gas fractions) could be more strongly affected by this issue, thereby introducing a bias in our results. Roychowdhury et al. (in prep. )  are investigating DustPedia dwarf galaxies using resolved Hi data to study this issue in more detail.
Data products This work presents a large, homogeneous set of resolved and global metallicity measurements of 516 nearby galaxies (10143 individual regions). In combination with the available multiwavelength imagery and photometry  (Clark et al. 2018) , as well as galaxy properties from SED fitting (Nersesian et al. in prep. ) and the Hi measurements, this forms an unprecedented database which will be invaluable for future investigations of galaxy (chemical) evolution processes. The data in this work is available as four separate tables, which can be accessed on the DustPedia archive 15  , and from the VizieR catalogue service 16. The references used for our compilation and examples of each of the four tables are given in Appendix C. The first table list the Hi fluxes, uncertainties, and masses (Section 4.
Acknowledgements. DustPedia is a collaborative focused research project supported by the  European Union  under the  Seventh Framework Programme  (2007-2013) call (proposal no. 606847 ). The participating institutions are:  Cardiff University, UK ;  National Observatory of Athens, Greece ;  Ghent University, Belgium ;  Université Paris Sud , France;  National Institute for Astrophysics, Italy and CEA, France. We thank the referee,  Raffaella Schneider , for helpful comments. We gratefully acknowledge  Sebastian Sanchez  and  Laura Sanchez-Menguiano  for their help with the CALIFA data. We also thank  Leonid Pilyugin  for sharing the data from Pilyugin et al. (2014) and useful comments. This work is based on publicly available MUSE data obtained from the  ESO Science Archive Facility  under request number pdevis291121.
This research made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration. We acknowledge the usage of the HyperLeda database (Makarov et al. 2014; http://leda. univlyon1. fr). This research made use of the VizieR catalogue access tool (Ochsenbein et al. 2000),  CDS, Strasbourg, France.
The cell extracts were then spotted onto an MBT Biotarget 96 target plate, air dried and overlaid with 1 μL of a saturated α-cyano-4-hydroxycinnamic acid (HCCA). 24 mass spectra per strain were acquired on a Microflex LT mass spectrometer (Bruker Daltonics, Bremen, Germany). Re-analysis of the spectra was performed for the purpose of this work. Spectra were first preprocessed by applying smoothing and baseline subtraction with FlexAnalysis software using default parameters, exported as text files from the Brucker system and then imported and analyzed in a dedicated BioNumerics v7. 6. 3 (Applied-Maths, Belgium) database following the protocol described by Rodrigues et al. (22). To allocate proteins to the specific peaks detected, we extracted all the molecular weights from the genomes of the type strains (NTCT11397 T , FRC0043 T and FRC0190 T ) using a Biopython script (https://biopython.
org/DIST/docs/api/Bio. SeqUtils-module. html) and performed sequence alignments with ClustalW for the candidate proteins. Genomic sequencing was performed from Nextera XT libraries using a NextSeq-500 instrument (Illumina, San Diego, USA) with a 2 x 150 nt paired-end protocol. Contig sequences were assembled using SPAdes v3. 12. 0 (23) (Table  S1 ). JSpeciesWS (  24 ) was used to calculate the BLAST-based average nucleotide identity (ANIb). BLAST was used to extract 16S rRNA and rpoB sequences from genome assemblies and to determine the presence or absence of the narIJHGK nitrate reduction gene cluster using as query the cluster of strain NCTC 13129 (RefSeq accession number: DIP_RS13820 to DIP_RS13845)  (25). rpoB and 16S rRNA gene sequences of atypical C. belfantii strains from cats  (12)  were included for comparison.
For genome-based phylogenetic analysis, the pairwise p-distance (i. e. , proportion of aligned nucleotide differences) between each pair of genomes was estimated based on Mash (26) using a multiple hit correction  (27)  with JolyTree (https://gitlab. pasteur. fr/GIPhy/JolyTree). For 16S rRNA and rpoB gene sequences, sequences were aligned with MAFFT v7. 407  (28)  and the resulting alignment was used for phylogenetic tree inference with IQ-TREE v1. 6. 7. 2 (29) using the GTR+I+G4 model.
Data accessibility. Sequence data generated in this study were deposited in the European Nucleotide Archive database and are accessible under project number PRJEB22103. The EMBL (GenBank/DDBJ) accession numbers of the genomic sequences released in this study are ERS3795539 to ERS3795544. The annotated genomic sequence of strain FRC0190 T was deposited in the European Nucleotide Archive and is available under accession number ERZ1195831. rpoB and 16S rRNA gene sequences were also submitted individually under accession numbers MN542347 to MN542352 and MN535982 to MN535987, respectively.
Results and discussion Six isolates were isolated from five cutaneous lesions and one ascitic fluid sample (Table  1 ). Strikingly, human cutaneous lesions were all ulcerations due to underlying chronic arteritis. Ascitic fluid was sampled on a patient with a suspicion of spontaneous peritonitis. The dog was investigated in the context of purulent orbital cellulitis. The six isolates were tox negative (Table  S1 ); more specifically, they were negative for amplification of the expected 910-bp PCR product encompassing fragments A and B of the toxin gene  (20)  and also negative for the amplification of a 117-bp region of diphtheria toxin fragment A (30) by multiplex qPCR as described in  (19). We also confirmed by BLASTN that the tox gene sequence (query: tox gene sequence from strain NCTC 13129, RefSeq accession number: DIP_RS12515) was absent from the genomic assemblies.
diphtheriae and C. diphtheriae subsp. lausannense  (13). Here, we observed that the ANI value between the type strains of C. diphtheriae subsp. lausannense and C. belfantii was 99. 3%. Besides, the former was positioned within the phylogenetic branch of C. belfantii (Figure  1 , S1 and S2), and the descriptions of both taxa are very similar  (3, 13). Given that C. belfantii was validly published in October 2018, a few months before the taxonomic proposal C. diphtheriae subsp. lausannense was validated (https://www. microbiologyresearch. org/content/journal/ijsem/10. 1099/ijsem. 0. 003174; January 2019), the latter subspecies appears to be a later heterotypic synonym of C. belfantii. Based on the MALDI Biotyper Compass database version 4. 1. 90 (Bruker Daltonics, Bremen, Germany), the six isolates were identified as C.
diphtheriae. However, detailed analysis of their spectra led to the identification of six pairs of biomarkers  (12 peaks  corresponding to the same proteins, with either single and double-charged ion forms) corresponding to three different proteins within the range 3255-9495 m/z, which were associated either with the group of six isolates or with C. diphtheriae and C. belfantii (Figure  S4 , Table  S3 ). We presumptively identified the specific biomarkers as two ribosomal proteins, L30 and S20, and one putative stress response protein (CsbD). Consistently, their amino-acid sequences differed between the C. rouxii on the one hand, and C. diphtheriae/C. belfantii on the other hand (Figure  S5 ). Based on the current dataset, the specificity and sensitivity of peak distribution among the three species ranged between 95-100% and 76-100%, respectively (Table  S3 ).
MALDI-TOF MS thus allows the discrimination between C. rouxii and C. diphtheriae/C. belfantii. These results warrant future updates of reference MALDI-TOF MS databases to incorporate the novel taxon. C. rouxii conforms biochemically to the description of C. diphtheriae strains belonging to biovar Belfantii  (2, 21) , except that strains are negative for maltose fermentation (API coryne), being nearly negative or weakly positive with the Rosco Diagnostica test. Key characteristics that distinguish C. rouxii from other members of the C. diphtheriae complex are specific MALDI-TOF MS biomarkers as described herein. The G+C content of C. rouxii genomes ranges from 53. 2% to 53. 3%, with a value of 53. 3% for the type strain. So far, strains were isolated from 5 humans and a dog in France, as well as from two related cats in the USA.
The type strain is FRC0190 T (= CIP 111752 T = DSM 110354 T ), isolated in 2013 from a foot ulceration reported in Cahors, France. The genome accession number of strain FRC0190 T is ERS3795540. genome data for the taxonomy of prokaryotes. Int J Syst Evol Microbiol 68:461-466. 340 341    S1 ). C. diphtheriae strains isolated from domestic cats in the USA  (12)  were added for comparison (strain codes CD443-CD450; GenBank accession numbers: FJ409572 to FJ409575). Each taxonomic type strain is shown in bold. The scale bar indicates the number of substitutions per site. S1 ). C. diphtheriae strains isolated from domestic cats in the USA  (12)  were added for comparison (strain codes CD443 and CD450; GenBank accession numbers: FJ415317 and FJ415318). Each taxonomic type strain is shown in bold.
6% phenotypic variance explained by the SNP (% Var SNP ), P-value = 1. 5×10 -70 ; IMF: 24. 2% Var SNP , P-value = 1. 1×10 -88 ] at the SSC12 region harboring the MYH gene cluster (S1A and S1B Fig). The position of the most significantly associated marker (rs81437379) for the two traits was 54,956,054 (NCBI Sus scrofa version 11. 1). Using linkage analysis, instead of an association study, we could also replicate the major QTL for the two traits at rs81437379 (S2A Fig; a � : 20. 5% Var QTL , P-value = 1. 02×10 -49 ; IMF: 29. 4% Var QTL , P-value = 3. 2×10 -74 ). To refine the identified QTL on SSC12 in the LK cross, we conducted a joint linkage and linkage disequilibrium (LALD) analysis of a � and IMF using DualPHASE software  [13]. The test statistics of the LALD mapping for a � (P-value = 3.
The CAVIAR results revealed that the 99% credible set included only XM_013981330. 2:g. -1805_-1810del with an extremely high posterior probability of being a candidate causal variant (S4 Table ). Additionally, we performed bivariate Bayesian fine-mapping using the eCAVIAR program to provide evidence for whether XM_013981330. 2:g. -1805_-1810del has a pleiotropic effect on a � and IMF. The combined likelihood posterior probability from eCAVIAR provided evidence that the MYH3 6-bp deletion variant can be considered as a pleiotropic variant for both a � and IMF (S4 Table ). These results provide information on the contrast between this particular 6-bp deletion variant and other variants used for GRAMMAR based GWAS. The regional P-value plot showed that it is extremely difficult to distinguish which variant should be considered as a candidate causal variant from the GRAMMAR based GWAS; there are several variants that can be regarded as candidate causal variants based on their P-value (S10 Fig).
Joint linkage and linkage disequilibrium (LALD) analysis High-resolution mapping of the QTL was conducted by jointly exploiting linkage and linkage disequilibrium using a haplotype-based approach. First, we used CRI-MAP ver 2. 503, developed by Evans and Maddox (URL: www. animalgenome. org/bioinfo/tools/share/crimap), to construct the genetic linkage map of SSC12 using 935 SNP markers for the Landrace×KNP cross and 997 SNP markers for the Duroc×KNP cross. Second, founder haplotypes those found in the F 0 pigs were reconstructed using the DualPHASE program  [13] , which combines family (linkage and Mendelian segregation) and population (linkage disequilibrium) information in a Hidden Markov Model frame. A total of twenty founder haplotype clusters (K = 20) were used for the next step. Third, the haplotypes were incorporated into a mixed model including fixed (sex, batch and carcass weight), random (i.
Genotype imputation and fine-mapping of the 488. 1-kb critical region Prior to the fine-mapping approaches, we imputed genotype data in the critical region using FImpute program which can utilize information from both pedigrees and populations  [47]. The genotype imputation was conducted with the default settings of the FImpute program. For the imputation, we only used the variants from the 60K SNP chip and the 6-bp deletion variant for further fine mapping to fill in missing genotypes of the variants. To characterize the identified putative FSV in the 488. 1-kb critical region, a Bayesian fine-mapping approach based on the CAusal Variants Identification in Associated Regions (CAVIAR) program  [25]. The CAVIAR program incorporates association summary statistics (i. e. , Z-scores) and LD correlation structures to compute the posterior probability of being candidate causal for each variant in the region of fine-mapping.
The eCAVIAR program  [26] , a bivariate extension of CAVIAR, was also applied to fine-map the causal variant by colocalization analysis of association signals from a � and IMF. eCAVIAR calculates combined likelihood posterior probability (CLPP) to measure the degree of colocalization of the two QTLs by computing the probability that the variant is pleiotropic for both phenotypes. A threshold of 0. 99 for both posterior probability and CLPP was applied to select candidate causal variants in the CAVIAR and eCAVIAR analyses. To evaluate the uncertainty of the fine-mapping analyses, 99% credible sets were constructed for both CAVIAR and eCAVIAR analyses (S4 Table ).
NGS and Sanger sequencing A massively parallel sequencing technology was used to identify SNP markers in the porcine whole genome, including the MYH3 locus on SSC12, using genomic DNA of the 24 F 1 sires and the parental pigs [Landrace (n = 17) and KNPs (n = 19) for the LK cross; Duroc (n = 9) and KNPs (n = 5) for the DK cross] from the two crosses (i. e. , 18 pigs from the LK cross; 6 pigs from the DK cross). Adapter-ligated DNA libraries were prepared for single and paired-end sequencing. All sequence data were produced using HiSeq X (Illumina) according to the standard protocol. The average coverage depth was approximately 30×. In addition, the Sanger sequencing method using BigDye Terminator 134 v3. 1 Cycle Sequencing Kit (Applied Biosystems) was applied to determine the sequence of the 5' and 3' flanking regions and exon regions of the porcine MYH3 gene using DNA samples from the parental animals of the two cohorts [i.
This work was carried out with the support of " Cooperative Research Program for Agriculture Science & Technology Development (Project title: A research on performance improvement of 'Nanchukmacdon' , a high quality pig breed developed using Korean native black pigs (KNP) in Jeju Island, Project No. PJ01012301  and  PJ01262701 )"  Rural Development Administration  (http://www. rda. go. kr), Republic of Korea. This work was also supported by the  Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program, Republic of Korea  (www. kribb. re. kr). M. P. E work was funded by  AGL2016-78709-R  ( Ministerio de Economı ´a y Competitividad, Spain ; http://www. mineco. gob. es/portal/site/mineco/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data access Full-length MYH3 CDS sequence from KNP, KX538787; full-length MYH3 CDS sequence from Landrace, KX538788. Two-kb of 5 0 -flanking region MYH3 genomic DNA sequence from KNP, KX549312; 0. 5-kb of 3 0 -flanking region MYH3 genomic DNA sequence from KNP, KX549313. Two-kb of 5 0 -flanking region MYH3 genomic DNA sequence from Landrace, KX549311; 0. 5-kb of 3 0 -flanking region MYH3 genomic DNA sequence from Landrace, KX549314. Resequencing data access information is provided in S10 Table. In addition, Original data of the figures and table are found at https://doi. org/10. 5061/dryad. dr32n87/1.
■ Design and settings This study incorporated a cross-sectional design. The recruitment of parents was made from 4 specialized rehabilitation centres, from 9 residential facilities of the French Comited'E ´tudes, d'Education et de Soins Auprès des Personnes Polyhandicapees Association (CESAP), and from a specialized paediatric/neurological department of a university hospital (Service de ensure that data privacy law is applied to the collection, storage, and use of personal data. As the database of this study was authorized by the CNIL, we cannot make available data without prior agreement of the CNIL. Neuropediatrie, UPMC, Hopital Trousseau, Assistance Publique Hopitaux de Paris, France). This study was included in the French national PoLyHandicap (PLH) cohort (see above).
■ General organization of the PoLyHandicap cohort The general aim of the French PLH cohort was to identify the impact of potential (socioeconomic, environmental, epidemiologic) determinants on the health status of the individuals and the daily life of their (natural and institutional) caregivers (NCT02400528). Three different populations were eligible: i. individuals with severe PLH defined by the combination of motor deficiency (tetraparesis, hemiparesis, paraparesis, extra pyramidal syndrome, cerebellar syndrome, neuromuscular problems) and intellectual impairment (Intelligence quotient IQ <40), associated with everyday life dependence (functional independency measure FIM <55), restricted mobility (Gross Motor Function Classification System levels GMFCS III, IV and V), and age at onset of cerebral lesion below 3 years old; ii.
■ Data collection Two sources of data were used: the medical records and the parents themselves. a. From the medical records, characteristics of the individual were collected: age, gender, place in the sibling (elder or not), global health severity (severe for individuals who meet all the following criteria: motor handicap (paraparesia or tetraparesia and/or extrapyramidal syndrome and/or severe general hypotonia), IQ <25, FIM �20, and GMFCS IV and V; less severe for individuals who do not meet these criteria); global health stability (unstable for individuals who meet at least one of the following criteria: recurrent pulmonary infections (�5/yrs), drug-resistant epilepsia (�4 seizures/month); stable for individuals who do not meet any of these criteria), medical devices (at least one of the following list: invasive mechanical ventilation, non-invasive mechanical ventilation, tracheotomia, nasogastric tube, gastrostomy, permanent urinary probe, cerebrospinal fluid derivation, and central venous catheter).
b. The data collected from the parents themselves were gathered into a booklet. The booklet included the following data: Health and presence and nature of chronic diseases; hospitalization episode during the last 2 years; other health resources use during the past 3 months (anxiety and/or stress medications, psychological support, alternative medicines). 3. Psycho-behavorial data: Anxiety-mood disorders assessed using a score ranged from 1 (absence) to 10 (very important). The coping was assessed using the Brief Coping Orientation to Problems Experienced Scale (Brief-COPE), exploring 4 dimensions that include social support, problem solving, avoidance, and positive thinking  [11]. Scores ranged from 0 to 100. High scores reflect a high tendency to implement the corresponding coping strategies.
■ General procedure For each included PLH individual, data were collected from medical records obtained by a dedicated clinical research assistant and was supported by the referent physician of the PLH individual (a referent physician is designated for each individual). A maximum of 4 official familial referents were systematically identified in the medical record. The familial referents are the resource persons who should be contacted for any medical, administrative, and social issues. From March 2015 to December 2016, the booklet was sent by mail to each mother and each father identified as a referent person. To optimize the participation, a prepaid return envelope addressed to the coordination team was added to the mail to optimize the participation.
Acknowledgments The French Polyhandicap Group includes the following individuals:  Thierry Billette de Villemeur  (lead author, thierry. billette@trs. aphp. fr, Hopital Trousseau, Service de Neuropediatrie-Pathologie du developpement, Paris, France ),  Marie-Christine Rousseau  ( Hopital San Salvadour, Hyères, France ),  Sherezad Khaldi-Cherif  ( Union Generale Caisse Assurance Maladie (UGECAM), Ile de France, France ),  Catherine Brisse  ( Comited'E ´tudes, d'E ´ducation et de Soins Auprès des Personnes Polyhandicapees, Paris, France ),  Agnès Felce  ( Hopital d'Hendaye, Hendaye, France ),  Karine Baumstarck  ( EA 3279 , Self-perceived  Health Assessment Research Unit, School of Medicine, Aix Marseille Universite, France ),  Pascal Auquier  ( EA 3279 ,  Selfperceived Health Assessment Research Unit, School of Medicine, Aix Marseille Universite, France ),  Tanguy Leroy  ( EA 4163 ,  Laboratoire GRePS ,  UniversiteLyon 2, France), Cecile Freihuber (Hopital Trousseau, Paris, France ),  Sofiane Amalou  ( Hopital Trousseau, Paris, France ),  Julie Bonheur  ( Hopital Trousseau, Paris, France), Stephanie Valence (Hopital Trousseau, Paris, France ),  Marie-Christine Nougues  ( Hopital Trousseau, Paris, France ),  Laurent Luciani  ( Le Poujal, CESAP, Thiais, France), -Jean-Pierre Nouet (Le Poujal, CESAP, Thiais, France), Catherine Coiffie (Sessad, CESAP, Saint-Maurice, France ),  Sophie Mathieu  ( Hopital de La Roche Guyon, La Roche-Guyon, France ),  Moustafa Ardati  ( Hopital de La Roche Guyon, La Roche-Guyon, France ),  Delphine Heron  ( Hopital Trousseau, Paris, France ),  Alexandra Afenjar  ( Hopital Trousseau, Paris, France ),  Kim Maincent  ( Hopital Trousseau, Paris, France ),  Diana Rodriguez  ( Hopital Trousseau, Paris, France ),  Diana Doummar  ( Hopital Trousseau, Paris, France ),  Marie-Laure Moutard  ( Hopital Trousseau, Paris, France ),  Daniel Willocq  ( Hopital San Salvadour, Hyères, France ),  Maria Valkov  ( Hopital San Salvadour, Hyères, France), Stephane Pietra (Hopital San Salvadour, Hyères, France), Stephane Lenormand (Hopital d'Hendaye, Hendaye, France ),  Elizabeth Grimont  ( Hopital San Salvadour, Hyères, France ).
Using HTS of amplicons obtained with two markers (COI and 18S) and a metabarcoding approach, 12 NIS were identified and their temporal larval dynamics were monitored. Importantly, we chose to focus on a closed list of species, from four metazoan classes encompassing 52 NIS reported within the study area or nearby seas, with molecular references available or obtained locally for 42 of them. The use of a custom-designed database allowed the detection of three NIS otherwise not detected when using public databases. Interestingly, NIS known to have a short-lived larval stage were detected (e. g. , the bryozoan Bugula neritina or the tunicate Corella eumyota). For two molluscs Ruditapes philippinarum and Crepidula fornicata, metabarcoding results were compared to those obtained using traditional methods (i.