dataesr/scientific-paragraphs-categorization huggingface dataset:
Observed heterozygosity (Ho) was determined using R software (R core team 2016), and the hierfstat package  [37]. The spatial population genetic structure of H. contortus was first investigated using a sPCA (spatial Principal Component Analysis, library adegenet of R software)  [47, 48, 60]. We performed eigenvalue tests (n = 9999) to assess the significance of the local and global spatial structures  [60]. The connection network was set using the inverse of the Euclidean pairwise distances between individuals. We then ran 10 independent runs of the MCMC simulations implemented in GENELAND v. 4. 0. 8 software  [39] , using the correlated allele frequencies and the null allele models (see Results) to test for K varying from 1 to 10, with 1,000,000 iterations, a thinning of 100, and a burn-in of 1000.
Results Of the seven loci selected for genotyping, one (Hcms8a20, Supplementary Data 2) failed to amplify and was thus not included in the dataset. MICROCHECKER indicated higher than 0. 05 null allele frequencies for the loci Hcms22Co3, Hcms27 and Hcms40 (f = 0. 18, 0. 29 and 0. 20, respectively, Van Oosterhout et al. 's estimator,  [78] ). In addition, 28% of the sampled individuals failed to be genotyped at the Hcms27 locus which was thus excluded from the dataset. The five remaining loci considered in subsequent analyses showed a relatively high level of genetic diversity (Table  1 ). For all loci, the Fis value was 0. 16 and significant (p = 0. 01), suggesting overall deviation from Hardy-Weinberg equilibrium likely attributed to the high null allele frequencies observed for some loci  [19].
Acknowledgements. We warmly thank all the professionals from the  Office National de la Chasse et de la Faune Sauvage , the  Office National des Forêts  and the  Groupement d'Intérêt Environnemental et Cynégétique of Caroux-Espinouse  ( Patricia Michel  and all the hunters who allowed us to collect digestive tracts of mouflon). We thank all the technical personnel of LBBE for helping with the laboratory steps of the study and  Julien Maerten  and  Guillaume Pratviel  for parasitological analyses of mouflon. This work was supported financially by  Vetagro Sup , the  LBBE-UMR CNRS 5558  and the  Office National de la Chasse et de la Faune Sauvage. The authors declare they have no conflict of interest. The authors are grateful to the two anonymous reviewers for their help in improving the manuscript.
5% B (5 min). The signal was recorded at 205 nm (2 Hz) (Dionex Ultimate 3000 DAD and Chromeleon software version 6. 80) with regular checks for absence of ghost peaks (reagents or column). A home-made standard sample (mixture of MSF) was regularly injected to check the sustainability of the resolution. Excluding the distal whey protein peaks (not computed) with an elution time of 35 min, we found 143 peaks ranging up to 500 mAU, but only 35 predominant peaks common to all profiles were considered in this analysis. Peaks between 190 and 300 diode array spectra were found characteristic of peptidic substances (data not shown). The three successive zones of peak elution (Z1, Z2 and Z3) were designated. Peptide elution varied from zone Z1 (most hydrophilic substances) to zone Z3 (most hydrophobic substances).
05) and the following linear model (2) for continuous traits: Y m = μ + cluster m + ϵ m where Y m is dependent variable (milk yield response or environmental factor or trait), µ is the mean, the fixed effect is cluster m and ε m is residual error associated with each observation. Results for fixed effects in models were expressed as least-squares means and computed using the lsmeans package  (Lenth, 2014). Differences were considered significant at P < 0. 05.
Clusters were then characterized using stage of lactation, parity, milk yield level, milk composition and proteolysis, udder expansion and immune traits. Clusters 1, 2 and 3 did not differ significantly for stage of lactation, initial milk fat, protein and SCC concentrations and proportion of cows with blood plasma haptoglobin >400 mg/ml. A first overview clearly showed that clusters 2 and 3 shared roughly more similarity than with cluster 1. Examination of the other traits found that cluster-1 cows showed a higher initial milk flow rate, a greater increase in milk fat content and a lower Figure  1  Variables factor map of the principal component analysis (PCA) built on the control period (cTDM) milk yield and on milk yield responses in dairy cows to the 24-h milking inteval (24h-MI). Dimensions are defined as the linear combination of the variables used to build the PCA that explain the largest possible variance in the data set given two restrictions: (1) the vector of linear weights defining each dimension must be of length 1; and (2) the dimensions should not be correlated with each other (and so orthogonal).
Acknowledgements The authors thank the  Association GALA (Janzé, France)  for providing financial support for milk interleukin-8 analysis. The authors thank  A. Mottin  and all the staff at the  INRA experimental farm of Méjusseaume  for their help with animal care and handling. The authors also thank  P. -G. Marnet  for proofreading the discussion,  G. Théaud  and  M. Fargetton  for help in data collection, and the laboratory technicians ( F. Revardeau  ( INRA-URTAL) ) and  S. Daré-Michelot  ( INRA-UMR PEGASE ) for their help on analyzing the samples. This study is part of the first author's PhD thesis.
Acknowledgements We thank the  Centenary imaging facility core and Sydney Cytometry  staff  Drs Kristina Jahn ,  Angela Kurz , and  David Liu , for their assistance. Funding:  Australian National Health and Medical Research Council   CJ Martin Early Career Fellowship   APP1053407  and Project Grant  APP1099912 ;  The University of Sydney  Fellowship  G197581 ;  NSW Ministry of Health  under the  NSW Health Early-Mid Career Fellowships Scheme   H18/31086 ; the  Kenyon Family Foundation Inflammation Award; Australian-French Association for Research and Innovation (AFRAN) Initiative ;  The University of Sydney Marie Bashir Institute 2019 Seed Funding  to  SHO. Sydney Medical School Summer Scholarship to JYK. Post-doctoral fellowship  granted by  Labex EpiGenMed , an " Investissements d'avenir" program   ANR-10-LABX-12-01  to MDJ; The  Fondation pour la Recherche Médicale   DEQ20150331719  to LK.
Surveillance samples The badgers examined were those captured under a bovine TB eradication programme between 1995 and 2017, excluding 2010. These activities were coordinated through the National District Veterinary Offices organised on a county basis. Date, geographical location, age and sex of the badgers were recorded at the time of capture. Badgers were transported to the post mortem facility within 36 h of death, where they were stored at 0-4 °C until post mortem examination. The nature of the post mortem examination and sample collection were dictated by the requirements of the bTB eradication scheme rather than by an investigation into the occurrence/prevalence of lung-or heartworms specifically. There was no systematic bias in terms of geography, age or sex in the selection of badgers contributing to the dataset.
Data analysis and modelling All data manipulation and analysis was undertaken within Stata 14 SE. Maps were created using ArcGIS 10. 3. All lungworm results were used to assess prevalence and the overall temporal trends. Prevalence was presented with 95% CI estimated using exact binomial CI. The outcome for each badger was modelled in a binary logit model with year fitted as i. categorical variable and ii. as a continuous linear trend. Where sample sizes were too small to estimate 95% CI for a given year (e. g. 2015 there were four observations, all were negative), these point and CI estimates were derived from an exact binomial distribution. Univariable and multivariable modelling was undertaken on records where all covariate data were available. Covariate data included the county (location) where the animal was captured (n = 26), age-class (adult or juvenile), season (with winter: December, January, February; spring: March, April, May; summer: June, July, August and autumn: September, October, November) and sex of the animal (male/female).
The size, pulmonary location and morphology of the parasites detected excluded Crenosoma, Capillaria, Filaroides and Angiostrongylus species. Of the 15 badgers analysed by PCR in 2017, 12 were positive in at least 1 sample and 7 were positive in all 3 loci. All PCR products were 100% identical to each other and to the rRNA sequences and internal transcribes space are logged in the data base for P. falciformis accession number (KY365435). The badgers that tested positive for P. falciformis in this subset were located in Kilkenny (1/1), Kildare (4/4), Laois (1/1), Offaly (1/1) and Tipperary (5/6). The badgers sampled from Carlow (0/1) and Wexford (0/ 1) were negative. No other lung-or heartworm species were detected using molecular techniques. Pulmonary tissue sections positive for P. falciformis were never positive for typical bTB lesions.
Aspergillus PCR: Group 5 In considering Aspergillus PCR, target species, patient populations, appropriate specimens for testing, technical issues, comparison with other biomarker assays, and unique attributes of PCR assays were reviewed. The data were sufficiently robust for performing Aspergillus PCR on serum, plasma, whole blood, and BAL fluid in adults. The group acknowledged that Aspergillus PCR data have been evaluated most extensively for adults with hematologic malignancies and HSCT. Systematic reviews of Aspergillus PCR methods on blood and BAL fluid conclude that PCR provides a robust diagnostic test for screening and confirming the diagnosis of Aspergillus infection  [22, [48] [49] [50] [51] [52] [53]. There are relatively few commercial PCR assays, and most investigators have developed methods in-house.
Protocol A series of "basic" and "optional" parameters are proposed to be collected. The basic parameters correspond to the minimum parameters fundamental to accomplish the Criteria D10C3, while the optional parameters allow acquiring more knowledge on sea turtles' behavior/biology. An observation data sheet and a list of material necessary for sampling individuals in the field and analysis of litter in the laboratory are provided here in order to facilitate data recording and statistical analysis by following a standardized table. Marine litter subcategories are chosen according to the shape and type of items. Remains of sea turtle's food and anything natural that are non-food items (stone, wood, pumice, etc. ) are requested for considering thresholds and the animal's diet. All the experimental activities of this protocol have been conducted on dead turtles according to the law of the involved countries and international rules.
Acknowledgments Authors are grateful to the  French Rescue Centres (Jean-Batiste Senegas ), stranding networks ( Jacques Sacchi ) and veterinarian laboratories ( Joanne Belfort ) and  Jessiaca Martin  and  Marie Sabatte ,  Cetacean  and sea turtle stranding network of the  Valencia Community , including the  Marine Zoology Unit of the Cavanilles Institute (University of Valencia ) and the  Biodiversity Service of the Generalitat Valenciana , the  Portuguese Regional Fund for Science and Technology of the Azores (Maria Vale) , the  Italian Rescue Centres (Stazione Zoologica "Anton Dohrn" Naples and Sardinian CREs ) the veterinarian laboratories ( IZSLT M. Aleandri Roma ;  IZSAM G. Caporale Teramo ;  IZSS G. Pegreffi Otistano ;. IZS CReTaM Palermo ), members of the  INDICIT Advisory Board  and the  PO  for their suggestion, and the  Environmental Ministries and Regional Governments  of the participant countries for their support.
Design This multicenter, case-control study used the data from two prospective programs: the Surveillance des Aspergilloses Invasives en France (SAIF) program from the Institut Pasteur in Paris, France, and the European ProMISe registry. SAIF anonymously collected consecutive cases of IA diagnosed in university hospitals from three regions of France (Paris-Ile de France, Grand Ouest, and Rhône-Alpes) between 2005 and 2010 through a web-based file. 8 The ProMISe registry prospectively collects data on all consecutive HSCTs within the European Group for Blood and Marrow Transplantation (EBMT). These two databases are complementary: the SAIF database contains mainly clinical, imaging, and microbiological data focused on the definition criteria of IA and the ProMISe database mainly contains transplant-related data.
This study was registered with the Commission Nationale de l'Informatique et des Libertés (CNIL) (number 1882064 v 0). The timing of IA after transplant was classified as follows: early IA when diagnosed before day 40, late IA when diagnosed between day 40 and day 100, and very late IA when diagnosed after day 100. 9 All proven and probable cases of IA diagnosed in patients aged 15 years or over after an allogeneic HSCT were selected from the SAIF database. Only the first episodes of proven or probable IA after HSCT were considered. Patients with previous IA before transplantation were not excluded from the study. Of the 20 French HSCT centers that participated in the SAIF registry, 19 participated in the present study; 3 881 allogeneic HSCT were performed during the period from 2005 to 2010.
Data collection and definitions The pre-and post-transplant clinical and biological data of the case and control patients were collected from the ProMISe registry. The EMBT definitions were used for the terms. For example, the day of engraftment was defined as the first day of 3 consecutive days > 0. 5x10 9 /L. Acute GvHD was reported according to the staging by Glücksberg et al. 27  Secondary neutropenia was defined as the occurrence of a neutrophil count below 0. 5 G/L after engraftment. According to the EBMT recommendations, all patients signed a consent form before their transplant for their data to be entered into the ProMISe registry and used for retrospective studies.
Data were analyzed using the standard methods for estimating ORs and 95% confidence intervals (Cis) in case-control studies. For the univariate analyses, the adjusted ORs (aOR) were estimated separately for each potential risk factor yielding a P value < 0. 20 using unconditional logistic regression models forcing the matching variables, such as HSCT center, age of patient, and year of transplant, into all models. The quantitative variables were converted into categorical variables using a cut-off according to the literature when available or a median split. The whole population was studied for pre-transplant factors. However, only the controls and their corresponding cases were studied for post-transplant factors; the controls were followed for the same duration as their cases. For the post-transplant risk factors, we only analyzed the events that occurred before IA.
Due to the small number of patients in some groups, we pooled some modalities of the following variables: disease status, stem cell source, and donor (D)/recipient (R) CMV serology. All tests were two-tailed and a P value ≤ 0. 05 was considered statistically significant. P values for comparisons between each group of IA (early, late and very late) and the control group were corrected using the false discovery (FDR) method for multiple comparisons  29  Data were analyzed using Stata Statistical Software 12. 0 (Stata Corp. , College Station, TX, USA). This observational study was reported according to the Strengthening the Reporting of Observational Studies in Epidemiology statement. 30.
It can be hypothesized that IA acts both as a deadly infection and as a marker of deep immunosuppression associated with GvHD and other infectious complications. It should be noticed that in our study, the poor outcome was not modified by the introduction of posaconazole in 2008. We acknowledge the following limitations in this study. First, due to its design, some data were not available, including ferritin levels, neutrophil, lymphocyte, or monocyte counts, and post-transplant factors, such as chronic GvHD and steroid use. However, all IA data were prospectively collected in the HSCT centers and the transplant data were exhaustively registered in the ProMISe registry, which ensured the consecutive patterns of the collected data available for study. Second, we were unable to obtain individual data about antimold prophylaxis.
The choice of animal-based traits to identify and deal with production diseases is often a challenge for pig farmers, researchers and other related professionals. This systematic review focused on production diseases, that is, the diseases that arise from management practices, affecting the digestive, locomotory and respiratory system of pigs. The aim was to classify all traits that have been measured and conduct a meta-analysis to quantify the impact of diseases on these traits so that these can be used as indicators for intervention. Data were extracted from 67 peer-reviewed publications selected from 2339 records. Traits were classified as productive (performance and carcass composition), behavioural, biochemical and molecular traits. A meta-analysis based on mixed models was performed on traits assessed more than five times across studies, using the package metafor of the R software.
Literature search: search strategy and inclusion criteria Searches were carried out between April 2014 and May 2015 using Web of Science Core Collection as bibliographic databases. The search terms are presented in Supplementary Material S1. In order to reduce publication bias, additional studies of key authors in the field were searched for in the Web of Science's Core collection and Google scholar. Furthermore, the reference lists of included studies were assessed in order to ensure that references which may have not returned from the data base searches were included. Searches included documents published in peerreviewed journals in English and French between 1976 and 2015. The literature search retrieved a total of 2338 records that were filtered in a two-stage process (Figure  1 ). The retrieved articles were first scanned for title and abstract and 504 of them were deemed as relevant.
Data extraction Data were extracted from 67 articles in excel spreadsheets by a single reviewer. The information indicating the sex of the animals, their genetic background, the housing and dietary composition specifics over the majority of their lifetime and the type of feed (dry or liquid) and feeding system (collective electronic feeding system, collective trough or individual though), and the type of interventions were recorded. When the disease was experimentally induced, the nature and duration of the intervention and the age at which it was applied were recorded. The effect size of the traits was calculated as the difference, expressed in %, of the mean value of the trait between the affected and the control group. Therefore, a positive effect size Stavrakakis, Loisel, Sakkas, Le Floc'h, Kyriazakis, Stewart and Montagne indicates that the parameter observed is greater in the affected group than the control group, and vice versa.
Meta-analysis Mixed and random effect models were fitted to the data with a restricted maximum-likelihood estimator using the open source package Metafor  (Viechtbauer, 2010)  within the R software environment (R Core Team, 2013); significance level was set at 0. 05. The detailed procedure and information regarding explanatory and outcome variables in are outlined in Figure  2. The meta-analysis permits to analyse which traits were most affected (outcomes) and which diseases (explanatory variables) had biggest impact on assessed traits. This is so because the effect size of traits is always the difference between affected and unaffected animals so any 'production disease' is underlying the effect size value. Variances were imputed using a resampling procedure based on effect and sample size of each study, since variances were often unreported in relation to the effects of interest within publications.
Since there was a minimal level at which meaningful comparisons across studies based on magnitude and direction of effects size could be made, meta-analysis were conducted only on traits assessed at least five times across all included studies. A subset-analysis of significant factor groups was performed for each trait and typically comprised 'stage of the animal', 'type of disease' and 'type of intervention' as a grouping factor (additional explanatory Figure  2  Flowchart describing statistical approach using package metafor  (Viechtbauer, 2010)  in R software to analyse animal-based traits in pigs. AIC = Akaike's information criterion. variables). When other factors were significant, subgroups were created accordingly. Estimates of amount of heterogeneity exhibited between studies beyond chance (I2) were used to determine uniformity of response  (Higgins et al.
Results Study selection, profile of included studies and reporting quality On the basis of our assessment, 67 articles out of a total of 2338 retrieved records matched our inclusion criteria, consisting of 77 distinct experiments in which comparisons were drawn between 89 groups of animals affected by production diseases and 77 control groups. This represents a low inclusion rate (2. 9%, Figure  1  and Supplementary Table  S2 ). The list of articles included in the database can be found in Supplementary Material S3. Many studies were excluded on the basis of their statistical methodology, or the absence of statistical assessment, mainly because their target was the characterisation of the effects of the diseases from a qualitative perspective, such as on the level of histological, histopathological alterations, etc.
In numerous studies, particularly those of the respiratory system, no negative control group was available for comparison. A large number of full-text assessed intervention studies were excluded because they were comparing treatment groups with differing levels of the production disease as a result of various implemented interventions without comparing groups consisting of only affected individuals with control disease-free populations. The papers published on each production disease varied greatly (Supplementary Table  S2  and Figure  1 ), with a maximal number of studies available for disease conditions such as ulcer, colitis and arthritis (more than 500 articles). Few studies were published on rectal prolapse and organ torsion (less than 25 articles) and even less so on pododermatitis. Due to their limited representation in the literature, foot rot (two studies) and pododermatitis (three studies) were not included in the database because these studies did not meet the criteria of inclusion in the database.
In four studies, the disease was identified as leg weakness or lameness, but no indication allowed characterisation of the type of disease. These experiments were included in the database as leg weakness disease. Information provided by the studies such as the genotype and sex of the pigs, the type of the floor, the ambient temperature, the system of feeding and type of feed were recorded as markers of reporting quality, but they were not used as part of our inclusion criteria. It is worthwhile mentioning that the reporting quality of the included articles judged by the provision of such information was weak. Animal genetics was the most frequently available descriptor and was specified in 55 of 77 experiments; 36 experiments used commercial cross-breeds and 19 experiments used pure breed pigs.