dataesr/scientific-paragraphs-categorization huggingface dataset:
E. coli MS499 from bovine metritis has many of the characteristics typifying ExPEC, i. e. , elements that may contribute to pathogenicity, fitness, and resistance, and this initial genome sequence supports the previous proposal of EnPEC as a novel E. coli pathotype. This first reported genome sequence for EnPEC provides a resource for further defining this novel E. coli pathotype and forms the basis for systematic studies. Comparative genomic analyses are under way and will be reported separately in order to further define this E. coli pathotype. Nucleotide sequence accession numbers. This whole-genome shotgun project has been deposited at DDBJ/EMBL/GenBank under the accession no. JDRV00000000. The version described in this paper is version JDRV01000000.
Background The non-tuberculous mycobacterium Mycobacterium abscessus was long confused with Mycobacterium chelonae  [1]. Other closely related species include Mycobacterium salmoniphilum  [2] , Mycobacterium immunogenum  [3] , Mycobacterium massiliense  [4] , Mycobacterium bolletii  [5]  and Mycobacterium franklinii  [6]  altogether forming the Mycobacterium chelonae-abscessus complex. This complex is the third most frequent mycobacterial complex infecting humans in developed countries besides the Mycobacterium tuberculosis and Mycobacterium avium complexes  [7, 8]. Bibliometrics retrieving over 1,700 publications in the Medline database illustrates the fact that this complex is emerging, causing both sporadic cases and outbreaks of community-acquired and health-care associated infections  [9].
massiliense from M. bolletii. In this report, the previous nomenclature M. abscessus, M. bolletii and M. massiliense forming the M. abscessus complex, has been retained for clarity. The availability of 39 M. abscessus, 13 M. massiliense and two M. bolletii genomes in the National Center for BioInformatics (NCBI) genome database provides new opportunities to assess the diversity of this species. Here, we review 14 complete published M. abscessus complex genomes and compare them with the re-annotated M. tuberculosis H37Rv genome (Table  1 ) in order to in-depth analyse the diversity of M. abscessus.
M. abscessus complex diversity The average percentage of amino-acid sequence identity (AAI) of core proteins was determined as previously described  [29]. The AAI values indicate that M. abscessus complex forms three main clusters: cluster 1 (C1) includes M. abscessus type strain and strains M93, 94, M152 and Go06; cluster 2 (C2) contains two subclusters: cluster 2A (C2A) includes M. massiliense type strain and strains M154 and M18; cluster 2B (C2B) includes strains 47 J26, M115, M172 and M139; cluster 3 (C3) includes two subclusters: cluster 3A (C3A) includes M. bolletii type strain and cluster 3B (C3B) includes M. bolletii strain M24 (Table  3 ). M. abscessus complex proteomes were further aligned using Mauve software  [30]  to infer phylogeny using the Neighbor-Net algorithm in the package SplitsTree4  [31].
massiliense  [8, 32]. Our analyses indicate that strain Go06 have an ambiguous classification as a chimera between M. abscessus and M. massiliense and is the only example compatible with a lateral transfer of rpoB gene. Functional analysis using Clusters of Orthologous Groups database (COG)  [33]  and BLASTP indicates unique genes in C1, encoding hypothetical proteins, proteins implicated in transcription, energy production and transport, carbohydrate metabolism and transport, lipid metabolism, nucleotide metabolism and transport, amino-acid metabolism and transport, post-translational modification and inorganic ion transport and metabolism (Table  2 , Figure  2 ). Within C2, unique genes encode hypothetical proteins, proteins implicated in transcription and lipid metabolism. Within C3,  unique genes encode hypothetical proteins, proteins implicated in amino-acid metabolism and transport and translation.
M. abscessus complex resistome As all mycobacteria, M. abscessus complex is embedded into a hydrophobic cell wall barrier to hydrophilic antibiotics. Accordingly, M. abscessus is multidrug resistant organisms exhibiting different drug resistance  [42] [43] [44]. M. abscessus genomes encode many proteins potentially involved in drug-efflux systems, including members of the major facilitator family, ABC transporters and MmpL proteins; Small Multidrug Resistance-family, a family of lipophilic drug efflux proteins  [45] ; and a multidrug resistance stp protein similar to M. tuberculosis involved in spectinomycin and tetracycline resistance  [46]. M. abscessus, M. bolletii and M. massiliense were reported to be in-vitro susceptible to amikacin; however, comparison with the M. tuberculosis H37Rv resistome and the antibiotic resistance databases indicate that M.
Prophage detection and genome annotation Protein sequences were predicted using prodigal software  [26]  to generate normalized files containing the combined protein sequences of all 14 genomes. Prophage regions were detected using PHAST software (Table  4 ). Predicted proteins were annotated using BLASTp against the National Center for Biotechnology Information (NCBI) nonredundant (NR) database, UNIPROT (http://www. uniprot. org/), the Clusters of Orthologous Groups (COG)  [33]  and a home-made antibiotic resistance gene database.
Phylogenetic analysis M. abscessus proteomes were aligned using Mauve software  [30]  to infer phylogeny using the Neighbor-Net algorithm in the package SplitsTree4  [31]. The orthologous group data found by orthoMCL were used to construct a whole-genome phylogenetic tree based on gene content. We generated a matrix of binary discrete characters ("0" and "1" for absence and presence, respectively)  [68]. Using this matrix, we constructed a phylogenetic tree implementing the neighbor-joining (NJ) method within Split-sTree4  [31].
massiliense M18 lymph node biopsy specimen from a Malaysian Malysia PRJNA89593 patient suspected of having tuberculous cervical lymphadenitis C2A M. massiliense M154 bronchoalveolar lavage fluid of a Malaysian Malysia PRJNA89603 patient presenting with lower respiratory tract infection C2B M. abscessus 47 J26 sputum sample from a patient with Cystis fibrosis England PRJNA179981, PRJNA73255 C2B M. abscessus M115 sputum from a Malaysian patient presenting with Malysia PRJNA89601 persistent cough and loss of body weight suggestive of pulmonary tuberculosis C2B M. abscessus M139 sputum sample of a 26-year-old Nepalese Nepal PRJNA159701 male presenting with hemoptysis C2B M. abscessus M172 putum isolate from a Malaysian patient Malysia PRJNA89599 C3A M. bolletii Type strain respiratory tract specimen collected Marseille PRJNA180015, PRJNA73695 in woman with hemoptoic pneumonia C3B M.
Data collection Carcass and meat quality data were obtained from 15 contrasted pig farming systems from 5 different countries according to their category. They were defined in more details in the introductory paper  (Bonneau et al. , 2014a). They included five conventional (C), five adapted conventional (AC), two organic (O) and three traditional (T) systems. Data were collected by each of the country representatives and pooled together to be analysed.
Results Carcass and meat quality criteria Tables  2  and 3  show the number of observations, the mean and standard deviation of the observed carcass and meat quality criteria that were used to determine the market suitability in the various farming systems. In all the systems the minimum number of observations was achieved, although in some cases it was not possible to collect data from all the meat quality variables. To obtain an adequate representativeness of farms, in each system meat quality was determined in different type of animals. This is the reason we observed remarkable standard deviation values in some variables, content and DL. Moreover, the breed type itself presented higher intrinsic variability in some systems, especially when evaluating IMF content. Percentage of suitable carcasses in the various farming systems For each pork product category, the percentages of carcasses that met the requirements of the acceptability benchmarks, and were therefore considered as suitable, are shown in Table  4.
Introduction The European Commission published the European Community Biodiversity Strategy, providing a framework for the development of Community policies and instruments in order to comply with the Convention on Biological Diversity. This Strategy recognises the current incomplete state of knowledge at all levels concerning biodiversity, which is a constraint on the successful implementation of the Convention. The Fauna Europaea contributes to this Strategy by supporting one of the main themes: to identify and catalogue the components of European biodiversity into a database in order to serve as a basic tool for science and conservation policies. With regard to biodiversity in Europe, both science and policy depend on a knowledge of its components. The assessment of biodiversity, monitoring changes, sustainable exploitation of biodiversity and much legislative work depend upon a validated overview of taxonomic biodiversity.
Towards this end, the Fauna Europaea plays a major role, providing a web-based information infrastructure with an index of scientific names (including important synonyms) of all living European land and freshwater animals, their geographical distribution at country level and some additional useful information. In this sense, the Fauna Europaea database provides a unique reference for many user-groups, such as scientists, governments, industries, conservation communities and educational programmes. The Fauna Europaea started in 2000 as an EC-FP5 four-year project, delivering its first release in 2004. After 13 years of steady progress, in order to improve the dissemination of Fauna Europaea results and to increase the general awareness of work done by the Fauna Europaea contributors, novel e-Publishing tools have been used to prepare data papers for all 58 major taxonomic groups.
General description Purpose: The Fauna Europaea is a database of the scientific names and distribution of all living, currently known multicellular European land and freshwater animal species assembled by a large network of experts using advanced electronic tools for data collation and validation routines. The 'Helminths (animal parasitic)' is one of the 58 major Fauna Europaea taxonomic groups, covering 3,986 species. The data were acquired and checked by a network of 19 specialists (Tables  1, 2 ).
Personel: The taxonomic framework of Fauna Europaea includes partner institute, providing taxonomic expertise and information, and expert networks taking care of data collation. Every taxonomic group is covered by at least one Group Coordinator responsible for the supervision and integrated input of taxonomic and distributional data for a particular group. For helminths, the responsible Group Coordinator is David Gibson (versions 1 & 2). The Fauna Europaea checklist would not have reached its current level of completion without the input from several groups of specialists. The formal responsibility of collating and delivering the data for the relevant families rested with a number of Taxonomic Specialists (see ). Associate Specialists deserve credit for their important contributions at various levels, including for particular geographical regions or across taxonomic groups (see ).
An overview of the expert network for helminths can be found here: http:// www. faunaeur. org/experts. php?id=51. Data management tasks are taken care of by the Fauna Europaea project bureau. During the project phase (until 2004) a network of principal partners took care of diverse management tasks: the Zoological Museum Amsterdam (general management & system development), the Zoological Museum of Copenhagen (data collation), the National Museum of Natural History in Paris (data validation) and the Museum and Institute of Zoology in Warsaw (NAS extension). Since the formal project ended (2004-2013), all tasks have been undertaken by the Zoological Museum Amsterdam.
Data management. The data records could either be entered offline into a preformatted MS-Excel worksheet or directly into the Fauna Europaea transaction database using an online browser interface. The data servers are hosted at the University of Amsterdam. Data set. The Fauna Europaea basic data set consists of: accepted (sub)species names (including authorship), synonym names (including authorship), a taxonomic hierarchy/ classification, misapplied names (including misspellings and alternative taxonomic views), homonym annotations, expert details, European distribution (at the country level), Global distribution (only for European species), taxonomic reference (optional), and occurrence reference (optional).
Funding: Fauna Europaea was funded by the European Commission under various framework programs (see above). Furthermore, all Fauna Europaea data sets are intensively reviewed at regional and thematic validation meetings, at review sessions at taxonomic symposia (for some groups), by Fauna Europaea Focal Points (during the FaEu-NAS and PESI projects) and by various end-users sending annotations using a web form at the web-portal. Additional validation of gaps and correct spelling was effected at the validation office in Paris. In conclusion, we expect to get taxonomic data for 99. 3% of the known European fauna. The faunistic coverage is not quite as good, but nevertheless represents 90-95% of the total fauna. Recognised gaps for the helminths include: areas where the geographical divisions of the Host-Parasite Database of the Natural History Museum, London (the main source of the data), as outlined below, are not concordant with those of the Fauna Europaea.
It is also likely that, although an update to include new taxa was carried out in 2006, the inclusion of recent geographical data may be limited. Checks on the technical and logical correctness of the data have been implemented in the data entry tools, including around 50 business rules (http://dev. e-taxonomy. eu/trac/wiki/ IntegrityRulesEditPESI). This validation tool proved to be of huge value for both the experts and project management, and it contributed significantly to the preparation of a remarkably clean and consistent data set. This thorough reviewing makes Fauna Europaea the most scrutinised data sets in its domain. Step description: By evaluating the team structure and life-cycle procedures (data-entry, validation, updating, etc. ), clear definitions of the roles of users and user-groups, depending on the taxonomic framework, were established, including ownership and read and writes privileges, and their changes during the project life-cycle.
Geographic coverage Description: Species and subspecies distributions in the Fauna Europaea are registered at least at the country level, i. e. for political countries. For this purpose, the FaEu geographical system basically follows the TDWG standards. The covered area includes the European mainland (Western Palaearctic), plus the Macaronesian islands (excl. Cape Verde Islands), Cyprus, Franz Josef Land and Novaya Zemlya. Western Kazakhstan and the Caucasus are excluded (see Fig. 7 ). The focus is on species (or subspecies) of European multicellular animals of terrestrial and freshwater environments. Species in brackish waters, occupying the marine/freshwater or marine/terrestrial transition zones, are generally excluded. A large proportion of the helminth records for this compilation was acquired from the Host-Parasite Database maintained by the Parasitic Worms Group at the Natural History Museum (NHM) in London.
Taxonomic coverage Description: The Fauna Europaea database contains the scientific names of all living European land and freshwater animal species, including numerous infra-groups and synonyms. More details of the conceptual background of Fauna Europaea and standards followed are described in the project description papers. This data paper covers the Helminth (animal parasitic) content of Fauna Europaea, including 214 families, 3986 species, 32 subspecies and 435 (sub)species synonyms (see FaEu Helminths stats for a species per family chart. ) Taxa included:.
org/Data_papers/FaEu_Helminths_2. 6. 2. zip The name identifying the data set from which the record was derived (http:// rs. tdwg. org/dwc/terms/datasetName). version Release version of data set. versionIssued Issue data of data set version. rights Information about rights held in and over the resource (http://purl. org/dc/terms/ rights). rightsHolder A person or organization owning or managing rights over the resource (http:// purl. org/dc/terms/rightsHolder). accessRights Information about who can access the resource or an indication of its security status (http://purl. org/dc/terms/accessRights). taxonName The full scientific name of the higher-level taxon scientificNameAuthorship The authorship information for the scientificName formatted according to the conventions of the applicable nomenclaturalCode (http://rs.
Data format: CSV Column label Column description datasetName An identifier for the set of taxon information (http://rs. tdwg. org/dwc/terms/taxonID) parentNameUsageIDAn identifier for the name usage of the direct parent taxon (in a classification) of the most specific element of the scientificName (http://rs. tdwg. org/dwc/terms/ parentNameUsageID). scientificName The full scientific name, with authorship and date information if known (http:// rs. tdwg. org/dwc/terms/scientificName). acceptedNameUsage The full name, with authorship and date information if known, of the currently valid (zoological) taxon (http://rs. tdwg. org/dwc/terms/acceptedNameUsage). originalNameUsage The original combination (genus and species group names), as firstly established under the rules of the associated nomenclaturalCode (http:// rs.
tdwg. org/dwc/terms/taxonomicStatus). Download URL: http://www. faunaeur. org/Data_papers/FaEu_Helminths_2. 6. 2. zip The name identifying the data set from which the record was derived (http:// rs. tdwg. org/dwc/terms/datasetName). version Release version of data set. versionIssued Issue data of data set version. rights Information about rights held in and over the resource (http://purl. org/dc/terms/ rights). rightsHolder A person or organization owning or managing rights over the resource (http:// purl. org/dc/terms/rightsHolder). accessRights Information about who can access the resource or an indication of its security status (http://purl. org/dc/terms/accessRights). taxonName The full scientific name of the higher-level taxon scientificNameAuthorship The authorship information for the scientificName formatted according to the conventions of the applicable nomenclaturalCode (http://rs.
2 -species Character set: UTF-8 Download URL: http://www. faunaeur. org/Data_papers/FaEu_Helminths_2. 6. 2. zip Data set name: Fauna Europaea -Helminths (Animal Parasitic) version 2. 6. 2 - Data format: CSV hierarchy Column label Character set: UTF-8 Column description datasetName The name identifying the data set from which the record was derived (http:// rs. tdwg. org/dwc/terms/datasetName). version Release version of data set. versionIssued Issue data of data set version. rightsInformation about rights held in and over the resource (http://purl. org/dc/terms/rights). rightsHolderA person or organization owning or managing rights over the resource (http:// purl. org/dc/terms/rightsHolder). accessRights Information about who can access the resource or an indication of its security status (http://purl.
Normality of parasite burdens was analysed using the Shapiro-Wilk normality test  [37]. As their distribution was not normal, the Kruskal-Wallis test was used to establish levels of statistical significance. All analyses were performed using XLSTAT software (http:// www. xlstat. com/fr). Table  2  gives the prevalence and intensity of infection noted in bull calves for each season: autumn (September-November), winter (December-February), spring (March-May) and summer (June-August). A similar presentation is used for old cows in Table  3. To compare the distribution of parasite burdens noted for bull calves and cows in relation to season, individual values were classified into one of the following categories: 1-50, 51-100, 101-150, 151-200, 201-250, 251-300, 301-350, 351-400 and >400 worms per infected ruminant.
The sequences obtained were used to perform BLAST searches  [2]  via the National Center for Biotechnology Information's GenBank database in order to ensure that parasite and other potential contaminating sequences had not been obtained in error. Sequences were then corrected and translated into amino acid sequences using the invertebrate mitochondrial genetic code and inspected for stop codons using SeqScape v2. 5. Nucleotide sequences were multiply aligned using CLUS-TAL X  [42]. A unique sequence was obtained for each individual. The new sequences have been deposited in GenBank as LN610457, LN610458 and LN610459. Measurements of overall haplotypes and nucleotide diversity were calculated using DnaSP v5  [24]. Pairwise genetic diversity was calculated using Tamura and Nei's threeparameter model  [40]  and Mega v5.
Phylogenetic analyses were conducted by maximum likelihood (ML), maximum parsimony (MP) and neighbour-joining (NJ) using Mega v5  [23]. This analysis was subjected to 2000 bootstraps as a means of testing the reliability of individual branches within the generated tree. Paragonimus westermani (Kerbert, 1878) Braun, 1899  [5, 20]  (AB354218. 1) was nominated as the outgroup. The following GenBank data: AY790883. 1, C. daubneyi; GU735640. 1, Calicophoron microbothrium  (Fischoeder, 1901)   Eduardo, 1983 [9, 11] ; and HM026462. 1, Paramphistomum cervi (Zeder, 1790) Fischoeder, 1901  [11, 47]  were included in the analysis in order to examine the topology of the tree. The nomenclature used to identify paramphistome species was that adopted by Jones  [17].
20 For ease of interpretation, odds ratios (OR) for dichotomised age with a cutoff point at 15 years were also reported (with corresponding OR referred to as OR 15 ). Parameter estimation and signifi cance testing were done within the classical maximum likelihood framework. The analyses were done with R statistical analysis software (version 3. 1. 0, glm functions), together with the additional mfp (version 1. 4. 9) and ggplot2 (version 0. 9. 3. 1) [23].
Results 1511 patients with Buruli ulcer were treated between Jan 1, 2005, and Dec 31, 2011, at the CDTUB, Pobè, Benin. The appendix shows the distribution of cases according to year of diagnosis, month of diagnosis, and management characteristics (antibiotic therapy, surgery, hospital admission, and time to healing). 1251 (83%) cases were confi rmed by one or more laboratory tests. PCR results were positive in 1177 (78%) cases, Ziehl-Neelsen staining was positive in 842 (56%) cases, and culture was positive in 214 (14%) cases (appendix). To ensure maximum robustness and homogeneity in our dataset, we focused  Comparison with the median age of the Beninese population (18 years in 2010 24 ) shows that Buruli ulcer is over-represented in children. 1172 (96%) patients presented with one localisation and 444 (36%) patients presented with a lesion of more than 15 cm in diameter (fi gure 1).
In several instances, we recorded new Buruli ulcer lesions that occurred several years after healing of the initial episode (appendix). By analogy with tuberculosis, this fi nding suggests reinfection or perhaps long-term reactivation of the contained infection. We believe that further characterisation of these patients would be particularly relevant to better our understanding of the human immune response to M ulcerans, especially in the prospects of vaccine development (appendix). Finally, although we ensured the homogeneity of the dataset, the monocentric design of our study restricts the number of patients for some important aspects of the disease (eg, Buruli ulcer-HIV co-infection), calling for further research. The monocentric design of our study also raises the important question of the generalisability of our fi ndings.