dataesr/scientific-paragraphs-categorization huggingface dataset:
BRSV diagnosis and virus shedding Bovine respiratory syncytial virus was diagnosed by serology and virus detection in both respiratory outbreaks in the herd. In 2016, the virus was detected in nasal swabs from 9/10 sampled cattle, by RT-qPCR and virus isolation. In 2020, BRSV was detected by RT-qPCR in nasal swabs from 12/12 sampled cows (all sampled once, on the same day and in the same section of the loose range system), including in seven cows that had been present in the herd during the outbreak in 2016. However, the samples from these seven cows contained lower virus quantities than samples from five younger and previously naïve cows (0. 41-2. 04 (mean 1. 33) log 10 TCID 50 equivalents and 2. 31-4. 96 (mean 3. 79) log 10 TCID 50 equivalents, respectively, p<0. 001, S1 Fig). In 2020, the virus was additionally detected by RT-qPCR in environmental swabs from the food tray of a milk robot but not in a watering cup (data not shown).
HRSV F-reactive antibody in serum Since antibodies specific to the F-protein may be neutralising, the dynamics of F-reactive antibodies was investigated by competitive ELISA. The monoclonal antibodies with which serum antibodies competed in this assay recognise the antigenic site IV on the HRSV F protein. Data between both virus-neutralising and F-competing assays agreed to some extent. Indeed, cow 403 had the lowest level of both neutralising and F-competing serum antibodies within its group (Figs  2A  and 5A ) and cow 399 had the highest level of both neutralising and F-competing serum antibodies within its group (Figs  2B  and 5B ). On the other hand, cow 618, which barely had any detectable neutralizing antibody response, had high levels of F-competing antibodies throughout the 2 years after infection (Figs  2D  and 5D ).
In all animals born before the outbreak, such antibodies increased by a wide (tenfold) range of titres after infection but dropped rapidly within 4 to 6 months and remained thereafter stable at moderate or low titres for at least four years. This initial drop in antibody titre, which was most striking in heifers, might have been due to a loss of short-lived plasmablasts, whereas the low but stable and durable antibody titres, observed in all age categories, indicate presence of long-lived plasma cells (LLPC)  [35]. These latter cells are elicited in germinal centers and are not dependent on reactivation of memory cells  [35]. The added effect of persistent antibody titres and memory responses was studied. Exposure to a previous infection significantly decreased virus shedding following reinfection after 50 months, although this needs to be verified by a larger dataset including kinetics of virus shedding.
Acknowledgments We thank the staff at the  Swedish Livestock Research Centre  and the  Clinical Science laboratory, SLU , for valuable help with animals, data collection and samples. The cells for life platform,  SLU , is thanked for providing facilities and equipment. Isabelle Schwartz  is acknowledged for coordinating the SAPHIR-project within the  European Union 's  Horizon 2020 Program  for research, technological development for scientific support.
T-cell receptors (TR), the antigen receptors of T cells, specifically recognize peptides presented by the major histocompatibility (MH) proteins, as peptide/MH (pMH), on the cell surface. The structure characterization of the trimolecular TR/pMH complexes is crucial to the fields of immunology, vaccination, and immunotherapy. IMGT/3Dstructure-DB is the three-dimensional (3-D) structure database of IMGT ® , the international ImMunoGenetics information system ®. By its creation, IMGT ® marks the advent of immunoinformatics, which emerged at the interface between immunogenetics and bioinformatics. The IMGT ® immunoglobulin (IG) and TR gene and allele nomenclature (CLASSIFICATION axiom) and the IMGT unique numbering and IMGT/Collier-de-Perles (NUMEROTATION axiom) are the two founding breakthroughs of immunoinformatics.
IMGT-ONTOLOGY concepts and IMGT Scientific chart rules generated from these axioms allowed IMGT ® bridging genes, structures, and functions. IMGT/3Dstructure-DB contains 3-D structures of IG or antibodies, TR and MH proteins of the adaptive immune responses of jawed vertebrates (gnathostomata), IG or TR complexes with antigens (IG/Ag, TR/pMH), related proteins of the immune system of any species belonging to the IG and MH superfamilies, and fusion proteins for immune applications. The focus of this chapter is on the TR V domains and MH G domains and the contact analysis comparison in TR/pMH interactions. Standardized molecular characterization includes "IMGT pMH contact sites" for peptide and MH groove interactions and "IMGT paratopes and epitopes" for TR/pMH complexes. Data are available in the IMGT/3Dstructure database, at the IMGT Home page http://www.
The CD8 expressed on most cytotoxic T cells binds the MH class I (MH1) that is expressed ubiquitously on cells of the organism  [7]. The CD4 expressed on most helper T cells binds the MH class II (MH2) that is expressed by professional antigen presenting cells (dendritic cells, macrophages, monocytes, and B cells)  [7]. IMGT ® , the international ImMunoGeneTics information system ® , http://www. imgt. org, is the global reference in immunogenetics and immunoinformatics  [1] , founded in 1989 by Marie-Paule Lefranc at Montpellier (Universitede Montpellier and CNRS). It is a high quality integrated knowledge resource comprising 7 databases, 17 online tools, and more than 25,000 pages of web resources  [8] [9] [10] [11]. IMGT ® is specialized in the sequences, structures, and genetic data of the IG, TR, and MH of human and other vertebrate species, in the immunoglobulin superfamily (IgSF) and the MH superfamily (MhSF) of vertebrates and invertebrates, and in related proteins of the immune system (RPI), fusion protein for immune applications, and composite proteins for clinical applications  [1, [8] [9] [10] [11].
IMGT/3Dstructure-DB  [12] [13] [14]  is the three-dimensional (3-D) structure database of IMGT ®. This database provides the standardized IMGT annotation and analysis of the 3-D structures of the TR, pMH, and TR/pMH complexes and comprises detailed molecular characterization and description of their interactions  [15] [16] [17]. The standardized analysis is based on the concepts of IMGT-ONTOLOGY, the first ontology in immunogenetics and immunoinformatics  [18] [19] [20] [21] [22] [23] [24]. The IMGT-ONTOLOGY concepts are generated from seven axioms  [25] [26] [27] [28] [29] [30] [31] , of which the CLASSIFICATION axiom (IG and TR gene and allele nomenclature) (see Note 1) at the birth of IMGT ® and immunoinformatics  [1, 25]  and the NUMEROTATION axiom (IMGT unique numbering  [7, [26] [27] [32] [33] [34] [35]  and IMGT Colliers de Perles  [28, 29, [36] [37] [38] [39] ) allow bridging sequences, structures, and functions.
Clicking on the "References and links" tag in the IMGT/3Dstructure-DB card gives access to external links. Links to the Immune Epitope Database (IEDB)  [51, 52]  are provided. Clicking on the "IMGT numbering comparison" displays, per chain, a table providing the correspondence between the IMGT unique numbering per domain and the PDB numbering of the chain entry. Next-generation sequencing (NGS) data, analyzed by IMGT/ HighV-QUEST, provides a standardized characterization of the TR repertoire diversity and expression in normal (e. g. , before and after vaccination) and pathological situations. The results include the IMGT variable (V), diversity (D), and joining (J) gene and allele names (identified at the nucleotide level) and the identification of the JUNCTION lengths and amino sequences, which, together, characterize the IMGT clonotypes (AA)  [53].
Availability and Citation Authors who use IMGT ® databases and tools are encouraged to cite this article and to quote the IMGT ® Home page, http://www. imgt. org. Online access to IMGT ® databases and tools is freely available for academics and under licenses and contracts for companies. 6 Notes "Group," "Subgroup," "Gene," and "Allele," generated from the IMGT-ONTOLOGY CLASSIFICATION axiom. The IMGT ® gene nomenclature for IG and TR genes was approved at the international level by the Human Genome Organisation (HUGO) Nomenclature Committee (HGNC) in 1999 and by the WHO-IUIS  [56, 57]. The IMGT ® IG and TR gene names  [2, 6, 58, 59 ] are the official reference for the vertebrate genome projects and, as such, have been entered in IMGT/ GENE-DB, the IMGT ® gene database  [60] , in National Center for Biotechnology Information (NCBI) Gene  [61] , in European Bioinformatics Institute (EBI) Ensembl, and in the Vega Genome Browser (Wellcome Trust Sanger Institute).
Anchor positions for V domains (V-DOMAIN and V-LIKE-DOMAIN) are positions 26 and 39, 55 and 66, and 104 and 118  [34]. By analogy, anchor positions were defined in C domains at positions 26 and 39, 45 and 77 (delimiting the transverse CD strand), and 104 and 118  [35]. Anchor positions are shown in squares in the IMGT Colliers de Perles. 4. "1ao7" is the code of a 3-D structure entry in the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (PDB)  [62] , or "PDB code" (comprising four letters and/or numbers). IMGT ® uses the "PDB code" as "IMGT entry ID" for the 3-D structures in IMGT/3Dstructure-DB, http://www. imgt. org [12] [13] [14]. An additional letter separated by a "_" identifies the different chains in a 3-D structure. For example, the 1ao7 entry (a TR/pMH1 3D structure) comprises the following chains: 1ao7_D (TR-ALPHA) and 1ao7_E (TR-BETA-1) for the TR, 1ao7_C for the peptide, and 1ao7_A (I-ALPHA) and 1ao7_B (B2M) for the MH1.
Acknowledgements We thank  Patrice Duroux  for the IMGT/3Dstructure-DB database and associated tools computing management,  Anjana Kushwaha  for the IMGT/3Dstructure-DB entries biocuration, and  Francois Ehrenmann  for help with the 3-D structure figures. We are grateful to the  IMGT ® team  for its expertise and constant motivation. We thank  Cold Spring Harbor Protocol Press  for the pdf of the IMGT Booklet available in IMGT references. IMGT ® is a registered trademark of CNRS. IMGT ® is member of the  International Medical Informatics Association (IMIA)  and a member of the  Global Alliance for Genomics and Health  ( GA4GH ). All figures are used with permission from  M-P. Lefranc  and  G. Lefranc , LIGM, Founders and Authors of IMGT ® , the international ImMunoGeneTics information system ® , http://www.
Funding: IMGT ® was funded in part by the BIOMED1 (BIOCT930038), Biotechnology BIOTECH2 (BIO4CT960037), fifth PCRDT Quality of Life and Management of Living Resources (QLG2-2000-01287), and sixth PCRDT Information Science and Technology (ImmunoGrid, FP6 IST-028069) programs of the European Union (EU). IMGT ® received financial support from the GIS IBiSA, the Agence Nationale de la Recherche (ANR) Labex MabImprove (ANR-10-LABX-53-01), the Region Occitanie Languedoc-Roussillon (Grand Plateau Technique pour la Recherche (GPTR), and BioCampus Montpellier. IMGT ® is currently supported by the Centre National de la Recherche Scientifique (CNRS), the Ministere de l'Enseignement Superieur, de la Recherche et de l'Innovation (MESRI), and the University of Montpellier.
It had a turnaround time of 65 minutes  [12]. Nevertheless, it remains the case that little is known about the diagnostic and prognostic significance of microbes detected from the upper respiratory tract  [11]. The respiratory tract harbours a range of microorganisms, which may not necessarily cause infection. One way to distinguish pathogenic from commensal microbes is to investigate whether the presence of microbes influences disease prognosis. Knowledge of form, a link to which can be found on this web page. The dataset title is 'Data from TARGET cohort study (subset)' and the accompanying DOI number is: 10. 5523/bris. 2if1hyn6u9bdx2wh70yqv24ifv. Following completion of the external user data request from and approval of access, the dataset itself can be located by accessing the University of Bristol Research Dataset Repository (https://data.
bris. ac. uk/data/) and searching for the dataset using the dataset name or DOI number. The dataset can also be located directly at the following URL: https://data. bris. ac. uk/data/dataset/ 2if1hyn6u9bdx2wh70yqv24ifv. this relationship could inform care and safety netting recommendations to parents. There is a paucity of evidence for this in children  [3]. Therefore, the objective of the present study was to use an existing dataset to investigate the prognostic significance of upper respiratory tract microbes in children presenting to primary care with RTIs.
Recruitment was coordinated by centres in Bristol, London, Oxford and Southampton, and study methods and main results have been reported  [14, 15]. Here we report results from 2,296 children recruited to the Bristol centre who, in addition to the baseline demographic and clinical data collected by parents and general practitioners or nurse practitioners using a structured proforma (S1 Fig) , were invited to provide a pharyngeal swab and for parents to complete a daily symptom diary. The final analytic sample in this study consisted of children with complete microbiological data and symptom diary data for two or more of days 2-4 post-consultation. This interval was selected as the period when symptoms are usually most severe  [16, 17] , and close enough to the microbiological sampling time to be considered relevant.
Prognostic outcome As previously reported  [18] , parents were invited to complete a validated  [19]  symptom diary. This has previously been shown to accurately predict the proportion of children recovering within two weeks  [20]. Parents completed either a paper-based or online version of the diary depending on personal preference. The severity of six symptoms (cough, shortness of breath, impaired sleep, being unwell, reduced level of activity, and temperature) were recorded once daily using a 7-item Likert scale from zero ('normal') to six ('as bad as it could be'). Parents were asked to continue recording for up to 28 days post-consultation, or until all symptoms were scored 'normal' for two consecutive days, where 'day 1' was the day of consultation and recruitment. Study team administrators telephoned parents to support diary completion up to 3 times during the first 7 days and then at least once per week until day 28 if no data had been obtained that week.
Text messages and postcard reminders were also used to maximise diary completion and return. All diaries were checked for accuracy and completion Two attempts were made to contact parents to clarify any data queries. Scores were converted into a mean symptom score across the six symptoms for days 2, 3 and 4 (mSS 2-4 ). To create the mSS 2-4 outcome, we took the mean severity for each symptom across days 2-4 post-consultation, then took the mean of these scores across all symptoms, giving a final value on a 0 to 6 scale. Where children were missing symptom data for a single day of days 2-4 (n = 27), mSS 2-4 was calculated using the data for the two days with complete data. As indicated in the original study protocol, microbiological sample results were not made available to recruiting clinicians, since the clinical significance of the results had not been established  [14].
Baseline characteristics Of the 2,296 children recruited by the Bristol centre, 893 (39%) were excluded due to incomplete symptom score data for two or more of days 2-4. A further 61 and 25 children respectively had incomplete virological and baseline characteristic data, leaving 1,317 participants contributing to the analysis (Fig  1 ). Baseline characteristics of included and excluded children were similar, except that excluded children were from more deprived households (S1 Table ). Table  1  presents the characteristics of the participants testing positive (869; 66%) and negative (448; 34%) for one or more respiratory virus. Compared to those testing negative for all viruses, children testing positive were younger (mean 4. 3 vs. 5. 8 years); presented sooner after illness onset (median 5 (IQR 3-9) vs.
This study was funded through a  National Institute for Health Research (NIHR)  (https://www. nihr. ac. uk/) Programme Grant for Applied Research  (reference number  RP-PG-0608-10018 ) and  Senior Investigator Award  ( NIHR200151 ) for AH. HC is funded by a  NIHR Career Development Fellowship  ( CDF-2018-11-ST2-015 ) and the  NIHR Health Protection Research Unit in Behavioural Science and Evaluation. The views expressed are those of the authors and not necessarily those of the  NIHR  or the  Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Papers and other sources of data were excluded when the earliest point of infection was determined purely by subtracting a known incubation period from the date of the suspicion of the outbreak. The ELS was restricted to studies conducted in Europe or describing results obtained in Europe. If none or very few articles were retrieved (less or equal to 5) in the first search, the search was extended to the rest of the world. The general protocol used for the ELS is shown in Annex 5 of the Technical report on Methodology (EFSA, 2020). To answer Scenario 5 of ToR 2 in relation to semen, an ELS was performed, to determine the time to seroconversion as it can be identified by different laboratory methods. This work was outsourced by EFSA to an expert (EOI/EFSA/SCIENCE/2020/01 -CT 02 ALPHA).
Extensive Literature Search The search was carried out on 10/06/2021 identifying 98 unique references. As no references were available for outbreak data from the EU/EEA, the search was extended to data from the rest of the world and to simulation data. Among the 98 references, six were selected to be included in the qualitative review. The full selection process is displayed in Figure  8. Four of the six references reported dates instead of periods. Therefore, the dates were used to calculate the different periods of interest (as described in Section 2. 1 -PICOS table ). Tables  5  and 6  provide an overview of the data that were extracted for the main outcome of interest, i. e. the period between the earliest point of infection and the suspicion report, for which three references were retrieved:   (1)   NA: not applicable.
No data on the sensitivity and specificity of clinical examination exist in the literature: i) the specificity cannot be considered high and ii) the sensitivity decreases when the animals enter the chronic phase. For the purposes of this assessment the sensitivity of clinical examination is considered 90% and the specificity 80%. Laboratory examination c-ELISA is highly specific (Sp>99. 5%) and the sensitivity can be considered 70%. Clinical examination is recommended to identify animals most suitable for sampling for further laboratory examinations. Samples from dead animals with a history of respiratory disease and preferably without receiving antimicrobial treatment (lungs with lesions, regional lymph nodes and pleural fluid when available) should be collected to be cultured and/or tested with PCR.
Methods: COMMUTE-a (NCT04861259) will enrol 3 cohorts of patients with aHUS aged $ 12 years (Figure): Naive: complement inhibitornaive patients; Switch: patients switching from eculizumab/ravulizumab; and C5 SNP: patients with a known single-nucleotide polymorphism (SNP). COMMUTE-p (NCT04958265) will enrol three cohorts of patients with aHUS aged $ 28 days to < 18 years (Figure): Naive: complement inhibitor-naive patients; Switch: patients switching from eculizumab/ ravulizumab; and Pretreated: patients who received and discontinued prior eculizumab/ravulizumab treatment. Figure: Study SchemaIn both the COMMUTE-a and COMMUTE-p trials, patients will receive weight-based crovalimab as a weekly loading series (Weeks 1-4), followed by self-administered, subcutaneous maintenance doses (Weeks 5 and after; once every 4 weeks or once every 2 weeks if < 20 kg).
In addition, patients with PNR were less likely to respond to second-line ustekinumab than patients with LOR, but there was no difference between patients treated with vedolizumab. These findings may be attributed to the pharmacokinetics and pharmacodynamics of anti-TNFs in patients with PNR. Some data suggest that biologic-naïve patients respond better to therapy than anti-TNF experienced patients. For example, post-hoc analyses of efficacy data from the GEMINI 2 and GEMINI 3 studies reported rates of response and remission to be numerically higher in patients with CD receiving vedolizumab as a first biologic than in patients who had previously experienced an inadequate response with anti-TNFs (65); clinical efficacy of vedolizumab appeared similar between the different types and number of anti-TNFs previously used.
Despite their diversity in sequence and structure, most of the HDPs possess a common structure with an overall positive charge and a substantial number of hydrophobic amino acids conferring them an amphipathic nature. Their length usually varies between 10-50 amino acid residues. The two major abundant families of naturally occurring HDPs preferentially adopt β-sheet (defensins) or α-helix (cathelicidins) secondary structures upon interacting with the bacterial membranes  [2]. Although AMPs exhibit a high potential as therapeutic agents, their application in human medicine has been up to now quite limited (several peptides reached phase III in clinical trials and colistin is used in human and veterinary medicine  [3, 4] ; see Dramp Database). Clinical translation of the AMPs has been mainly hampered by their structural instability and poor stability in biological fluids  [5, 6].
Acknowledgments We are grateful to  Drs. P. Giammarinaro ,  S. Niehus ,  R. Bruna , and  J. Nguyen  for help in some experiments;  W. J. Lee  and the  Bloomington Stock Center  ( NIH P40OD018537 ) for fly stocks. A. A has been supported by the  Higher Education Commission Pakistan , G. D. V and  M. La  by  ANPCyT  ( Agencia Nacional de Promoción Científica y Tecnológica, Argentina ) and  CONICET  ( Consejo Nacional de Investigaciones Cientifícas y Técnicas, Argentina ), and B. S. R by an  IdEx fellowship  ( Université de Strasbourg-France ). The work in E. G. V laboratory has been funded by  CONICET (Argentina)  and the work in D. F laboratory has been funded by  CNRS  ( Centre National De La Recherche Scientifique ),  Fondation pour la Recherche Médicale (Equipe FRM  to DF), and  ANR  ( Agence Nationale de la Recherche, France)  (DROSOGUT, ENTEROCYTE_PURGE_RECOVERY).
Funding This study did not receive specific grant from funding agencies in the public, commercial, or not-for-profit sectors. This work was realized in the context of (i) the  LabEx ImmunoGraftOnco program  ( National Research Agency ;  ANR-11-LABX-0016-01 ) and (ii) the  University Hospital of Angers -University  of  Angers joint program  (project  3I-Impact ).
(2010a). Data obtained from the State of the World's Sea Turtles (www. seaturtlestatus. org) database tonirina & Cooke 1994). Several regional workshops were held in the 1990s that provided overviews of population status and threats, most notable of which was held in 1996 when a marine turtle conservation strategy was devised for the WIO  (IUCN 1996 , IUCN/UNEP 1996 , Wamukoya & Salm 1998 ). In the 1990s and 2000s, studies in the region further increased and diversified, making use of satellite telemetry and genetics to gain insight into the connectivity of regional marine turtle populations  (Broderick et al. 1998 , Mortimer & Broderick 1999 , Pelletier 2003 , Formia et al. 2006 , Luschi et al. 2006 , Bourjea et al. 2007b , 2015b , Dalleau et al. 2014 , Vargas et al. 2016). Concerted long-term nest monitoring efforts at the island rookeries and South Africa have continued  (Bourjea et al.