dataesr/scientific-paragraphs-categorization huggingface dataset:
Together, these data suggest that the leptospiral PG could be sensed by both NOD1 and NOD2. Herein, we examined recognition of PG of pathogenic leptospires by NOD1 and NOD2 receptors. Unexpectedly, we found that an abundant lipoprotein, LipL21, of previously unknown function, is tightly bound to the PG and blocks its digestion by hydrolases in vitro, thus impairing the recognition of leptospiral muropeptides by NOD receptors. This peculiar mechanism would constitute a novel bacterial strategy to escape the NOD innate immune response.
Analysis and acquisition were performed using Living Image 3. 1 software (Xenogen Corp. ). Images were acquired using the automatic mode (acute phase) or 5 min of integration time (chronic phase and pictures) with a binning of 8 and with the emission filter in the "open" mode. All other parameters were held constant. Quantification was performed using a region of interest defined manually (kidneys) and the results were expressed as photons (P) per second (s) per cm 2 per steradian (SR).
Genomic sequencing and analysis Next-generation sequencing was performed on genomic DNA of the L495 parental and M58 strains by the Mutualized Platform for Microbiology (P2M) at Institut Pasteur, using the Nextera XT DNA Library Preparation kit (Illumina), the NextSeq 500 sequencing systems (Illumina), and the CLC Genomics Workbench 9 software (Qiagen) for analysis. Sequence reads were aligned with the sequenced and annotated L. interrogans serovar Manilae L495 genome (http://www. genoscope. cns. fr/agc/microscope/search/export. php?format=genbank&option= none&S_id=5570) by using the Burrows-Wheeler Alignment tool (BWA mem 0. 7. 5a)  [54]. SNP calling was done with the Genome Analysis Toolkit (GATK 2. 7-2) Unified Genotyper  [55]  by following Broad Institute best practices. To validate the call, candidate SNPs were further filtered by requiring coverage of greater than half of the genome mean coverage and 95% read agreement.
All data were submitted to the European Nucleotide Archive. A project was created in order to group M58 reads (ERR2192021) and L495 assembly (GCA_900236655. 1) associated to the genomes sequenced in this study and is available by using this accession number: PRJEB23342. Whole project: http://www. ebi. ac. uk/ena/data/view/ PRJEB23342 L495 assembly: https://www. ncbi. nlmhttp://www. ebi.
Data The anonymized Land Registration System (geographic database of parcels used for agriculture) of 2010 was obtained from the "Agence de Services et de Paiement" (ASP). This database collects data provided by farmers to claim the Common Agricultural Policy (CAP) subsidies. A CAP subsidy claim consists in a report made by a farmer specifying the geographic location and border of each land parcel she/he owns, and the usage of this parcel for agriculture (using a specific nomenclature) for a given year. Parts of these reports are controlled by local administrations. The number of such controls per member state is fixed by European legislation. Discrepancies between the control result and the farmer's report may lead to penal consequences for the farmer. CAP reports allow farmers receiving EU aids, but they are not mandatory.
However, although data may not be comprehensive, it can reasonably be assumed that the vast majority of farmers do claim CAP subsidies. We used a spatial layer in which each polygon represents a parcel. The accuracy of these polygons is considered good, with errors below a few meters. Attribute data were the parcel usage reported by the farmer (e. g. crops, grasslands. ), the parcel area and an anonymous farmer ID. Among their various usages, parcels dedicated to fodder crops, mountain pastures and permanent or temporary grasslands were considered as "pastures". The dataset described 6,123,259 parcels, of which 52% (3,159,787) were pastures. These pastures had been reported in 288,066 CAP reports. We assumed that each CAP report corresponded to a given farm, termed below "premises". Most of the pastures were located in the middle of the country ("Massif central" area).
There were also a high density of pastures in the mountains (in the Pyrenees at the Spanish border, in the Alps at the Italian border, in the Jura at the Swiss border and in the Vosges near the German border), near the Belgian border and in the western part of the country (the Brittany, the Normandy and the "Pays de la Loire" regions-Fig  1 ). On average, pastures were small (0. 05 km 2 on average) and two pastures of the same premises could be a couple of kilometres apart. Typical premises owned about ten pastures (Table  2 ). The dataset we used was anonymized, and the presence and type of livestock in premises was unknown. However, several arguments indicate that most of the premises of our dataset corresponded to cattle breeders: • According to the 2010 agricultural census, 19 million cattle were present in France in 2010, 8 million small ruminants (mainly sheep) and 1 million horses.
Cattle thus represent 68% of herbivorous livestock. • A strong correlation was observed between the number of pastures in the dataset we used and the number of cows per department (source: cattle tracing system database, described in  [19] ): 0. 82 (Spearman's rank correlation). • In 2010, the total number of cattle herds housing cows was 232,566 (source: cattle tracing system database) and, according to the 2010 agricultural census, 97% of the farms housing cows did own pastures and used it for breeding. The number of cattle breeders owning cows and pastures can thus be estimated at 225,589 (i. e. 97% of 232,566 farms). This number corresponds to 78% of the 288,066 premises of our dataset. Because the latter figure only concerns farms holding cows, it is a low estimate of the proportion of cattle farms in our dataset (some cattle farmers may own pastures and young cattle but not cows).
The vast majority of the premises (>78%) of our dataset can thus be considered as cattle farms. In order to build a network of pastures, buffer areas were drawn around parcels. Two pastures were considered "in contact" if their buffer areas intersected. Several buffer widths were used: from 1. 5 meters (to model contacts "nose-to-nose over the fence", while taking into account the accuracy of the database) to 500 meters (to model vector-borne transmission while maintaining a reasonable computation burden). For a given buffer width, a network (termed below "pastures network") was built with pastures as nodes and links for intersecting buffers. Links represented contacts that may allow disease transmission, between animals  located on distinct pastures. A second type of network (termed below "premises network") was built for each buffer width, by aggregating pastures per premise.
For the between-premises biosecurity, selected network elements were links and each of them was removed. This removal modelled, for example, the installation of double fences between pastures of a given pair of premises. Network analyses were performed using the Igraph package  [38]  for R 3. 1  [39]  and the SNAP software  [35]. Maps were drawn with the sp package  [40]  for R 3. 1  [39].
5-meter buffer width (99% for a 500-meter buffer width). This high connectivity level could be slightly underestimated, as our dataset did not allow identifying collective pastures, shared by several premises, which would increase the connectivity between premises. Such collective pastures are however rare in France (<1,500 reported in 2010, source: agricultural census). Neither the pastures nor the premises networks did show the properties of scale-free networks. The degree distributions on a log-log scale did not appear to be linear, and the networks were assortative, contrary to scale-free networks, which are disassortative, with highly connected nodes (so-called "hubs") being linked to weakly connected ones  [21, 24]. This was an expected result for the pastures networks due to the spatial constraints, but properties of scalefree networks could have been (at least theoretically) possible for the premises networks, as some premises owning many pastures in various locations could have played the role of hubs.
ACKNOWLEDGMENTS The authors wish to acknowledge the support of  Vaincre la Mucoviscidose-Association Gregory Lemarchal , the  ministery of Research and Higher Education , the  Ile de France Region , the  French National Research Agency  ( DIMYVIR ANR-13-BSV3-0007-01 ) to LK and JLH and the  Fondation pour la Recherche Médicale (FRM)   DEQ20150331719  to LK. DO acknowledges the federal funds from the  National Institute of Allergy and Infectious Diseases National Institutes of Health, Department of Health and Human Services ,  R21AIO99534-02  under principal investigator DO and  AIO99534-02 ,  NIH/NIAID  services under contracts  HHSN272201000009I/HHSN27200001  and  HHSN272201000009I/HHSN27200005 , principal investigator  Dr. A. J. Lenaerts , co-principal investigator, DO.
Yet, despite the comprehensive literature available tackling the life-cycle of H. contortus  [1] , including both the free-living (eggs to infective larvae) and parasitic stages (infective larvae to reproductive adult worms), a quantitative assessment of H. contortus population dynamics and ecology is still missing. The aim of this paper was to conduct a systematic review and meta-analysis of data collected on experimentally infected sheep with H. contortus, published before 2016, using the same methodology as Verschave et al. [16]. The main life history traits selected for study in the parasitic phase of H. contortus included: (i) larval establishment; (ii) adult mortality; (iii) female fertility and population level fecundity. To obtain robust estimates of the life history traits, several experimental variation factors were considered i.
Searching strategy and eligibility criteria An exhaustive data collection was performed using the Web of Sciences database (https://www. webofknowledge. com) using the following keywords: ((gastrointestinal AND nematode) or (gastrointestinal AND parasite*) OR haemonchus OR contortus)) AND (infect* OR pathogen* OR mortality OR establishment OR fecundity) AND (sheep OR lamb* OR ewe* OR wether* OR ram* OR dam*). Selection of the papers used in the present study was completed on January 7 th , 2016. In the first review phase, papers were selected based on title compatibility. Papers without full text accessibility, unavailable through library services or published in languages other than French or English were discarded. Finally, the eligibility of the remaining papers was decided following a full reading of the text to meet the following criteria: (i) natural infections were excluded due to unknown parasite exposure; (ii) experiments which used anthelmintic treatments prior to sheep slaughter were not considered; and (iii) papers reporting their results graphically i.
The general study description (country, year, number of sheep), sheep-host details (breed, gender, age, body weight, previous exposure to H. contortus), H. contortus details (isolate, drug resistance status, infection dose) and experimental conditions (infection duration, concomitant infection with other nematode species) were included in our database. Host resistance to gastrointestinal nematodes was inferred from the literature, where Barbados Black Belly, Saint Croix, Florida Native  [23] , Santa Ines  [24, 25] , Canaria hair breed  [26]  and divergent selection lines were considered resistant breeds. Two H. contortus isolates were included: anthelmintic resistant (thiabendazole-resistant strain) or H. contortus isolates (ISE isolates) obtained after serial passages in resistant hosts.
Meta-analysis Statistical analyses were performed using R version 3. 1. 3. [27]. The life history trait estimates and their associated variances were calculated for each experiment of our final database (Table  1 ). Each life history trait estimate was analysed using a linear fixed model (stats package) weighted by the inverse of their associated variance. The considered explanatory variables were the host age (in months), the host resistance (i. e. susceptible, resistant, unknown status), the infection dose (i. e. the number of L 3 inoculated per animal), the infection duration (i. e. number of days post-infection), previous exposure to H. contortus (i. e. immunologically naïve, natural preinfection assumed, experimental pre-infection). Due to the skewed distribution of the life history traits, they were studied with, and without, a log transformation in further analyses.
Quantitative explanatory variables (i. e. host age, infection dose and duration of infection) were clustered into balanced classes as the hypothesis of linearity between life history traits and explanatory variables was rejected. First, a backward variable selection was implemented based on AIC criterion  [28]. Then, only factors with a P-value < 0. 05 were kept in the final models. F-tests were calculated to select significant factors using the car R package  [29]. The estimation of means for each level of factors was performed using the lsmeans R package  [30]. As each life history trait had a different inverse variance weight, it was impossible to use the same criteria to weight the correlation between life history traits. Consequently, correlations between life history traits were weighted by the number of sheep involved in the experiment using the 'weight' R package  [31].
Results Figure  1  provides a description of the paper selection steps and the associated selection criteria. A total of 9480 references were retrieved from Web of Sciences that were narrowed down to 383 following title-based selection. The first review phase of the papers led to a selection of 81 eligible publications, reduced with the second review phase to 37 papers that estimate at least one H. contortus life history trait  [21,. This final database (see Additional file 2) comprised a total of 982 animals used in 115 different experiments (using different WB ID -ln WB ID ð Þ t FECnÃDFP WBÃFp FEC n Variance SE WB ð Þ 2 ID 2 SE WB ð Þ 2 tÃWB ð Þ 2 DFP 2 F 2 p Ã FECn 2 WB 2 Ã SE FECn ð Þ 2 FECn 2 þ SE WB ð Þ 2 WB 2 SE (FEC n ) Abbreviations: WB Worm burden, ID Infection dose, t days after infection, FEC n Faecal egg count at necropsy, DFP Daily faeces production, F p , proportion of female worms, SE Standard error experimental conditions as the duration of infection and/or the infection dose).
From our data, the infection dose did not significantly impact H. contortus female fertility, nor its adult mortality rate, but it affected the larval establishment rate. This unexpected result may be explained by the homogenous and relatively small infection doses used in our database to estimate female fertility and adult mortality which were mainly between 5000 L 3 and 10,000 L 3 and thus lower than the 10,000 L 3 threshold where a density dependence effect is generally expected  [73]. The only experiments with an infection dose of 30,000 L 3 used a small sample size (three animals) leading to highly variable estimations. In addition, all these experiments came from the same paper (  [47] ) with specific environmental conditions (i. e. parasite strain, sheep breed, body weight, sheep sex).
Data collection Retrospective analysis of case records was performed. Data collected for each horse included age, breed, sex, previous or intended use of the horse, reason for referral, history of trauma and duration of lameness before presentation, clinical findings, evidence of lameness as per subjective assessment by the attending clinician, lame limb and subjective lameness grade  [10]. Use of intra-articular diagnostic anaesthesia of the affected joint and clinical response to that was recorded. The following data on the imaging diagnostic investigations were retrieved: number and name of radiographic projections, visualisation of fracture on the radiographic images; number and size of fragments; other radiographic findings; any evidence of the fracture observed ultrasonographically; and other findings on ultrasonographic examination.
Acknowledgements The authors of this study wish to thank  Dr Raph Labens Mag. Med. Vet. CertES(Orth) MVM PhD DiplECVS DiplACVS  and  Dr Claire E. Wylie BVM&S MSc PhD MRCVS  for their contribution to the treatment of cases and retrieval of information. The authors of this study also wish to thank their colleagues at the different hospitals contributing to this study for their assistance in treating these clinical patients, and the owners of all the horses that participated in the study.
Subjects We tested 65 pet dogs of various breeds (41 females and 24 males), all naive for gaze-following and object-choice experiments. They were all between 1 and 12 years of age (average: 5. 1 years old) and had not shown noticeable signs of ageing. Pet dogs and their owners were recruited from the Clever Dog Lab database and participated on a voluntary basis. See the electronic supplementary material, table  S1  for more details on dogs participating in Experiments 1 and 2.
Data collection For both Conditions 1 and 2, in each trial, we recorded whether and how often the dogs looked (i. e. they visibly turned their head) in the direction indicated by the experimenter within 10 s after the gaze cue, and whether their first look to the side was into this direction or not. All trials were analysed by the experimenter (C. D. ) from the video records using SOLOMON CODER (copyright by András Péter, http:// solomoncoder. com/). Approximately 20% of the trials were coded for reliability by an uninformed experimenter, Geri Werhahn, and excellent consistency was found: (i) first look in gaze cue direction: Cohen's κ = 0. 90, 95% CI = (0. 62-0. 98), p < 0. 01; (ii) number of looks in gaze cue direction: Spearman's correlation r = 0. 85, p < 0. 001.
Subjects We tested 38 pet dogs of various breeds (22 females and16 males). They were all between 1 and 11. 5 years old (average: 4. 8 years old) and had not shown noticeable signs of ageing. Pet dogs and their owners were recruited from the Clever Dog Lab database and participated on a voluntary basis. Each dog was tested in 10 trials, in one of the two conditions (with repetitive non-ostensive (N = 19) or repetitive ostensive gaze (N = 19); see electronic supplementary material, table S1 for more details).
Data collection In each trial, we recorded whether and how often the dogs looked in the direction indicated by the experimenter within 5 s after the gaze cue, and whether their first look to a container was towards the  baited or the empty one. We also recorded whether and which pot the dogs chose. A choice was defined as approaching a container and inserting one's nose in it within 10 s after being released. All trials were analysed by the experimenter (C. D. ) from the video records using SOLOMON CODER (copyright by András Péter, http://solomoncoder. com/). Approximately 20% of the trials were coded for reliability by an uninformed experimenter, and excellent consistency was found: (i) first look in gaze cue direction (yes/no): Cohen's κ = 0. 96, 95% CI = (0. 93-0. 99), p < 0. 01; (ii) number of looks in gaze cue direction: Spearman's correlation r = 0.
Acknowledgements. We are grateful to all the owners and their dogs who participated in this research, for their patience and availability during the study. We also sincerely thank  Geri Werhahn  for performing the interobserver reliability coding, and  Corsin Muller  and  Marianne Heberlein  for their advice on the statistical analyses. We thank  Valérie Jean  for her drawing. Finally, we also greatly thank  Karin Bayer  for her administrative help,  Wolfgang Berger  and  Peter Füreder  for their technical help, and above all,  Ludwig Huber  for all his support, enabling us to realize this study under the best conditions.
The Welfare Quality® protocol was carried out on these farms. Data were collected on economic aspects, such as quantity of milk sold and labour, and on the environmental aspects required for a 'carbon footprint' estimation, which included fertiliser, land and fuel use. To simultaneously assess the welfare, environmental and productive performance of these farms, we developed Data Envelopment Analysis models. The models assess production efficiency (where high efficiency is defined as high production with low costs) while accounting for welfare and environmental impacts. The results provided a ranking of the farms based on their capacity to maximise welfare and production while minimising environmental footprint. Subsequently, the relationship between efficiency, welfare and environmental impacts was assessed by regressing the efficiency score for each farm against a number of variables such as no.
Technical efficiency (TE), i. e. the degree to which farms combine inputs to produce outputs, was assessed using data envelopment analysis with herd size, annual labour and concentrate use as production factors and milk yield as output. This method formulates a best-practice frontier over all observed data points (farms). Efficient farms lie on the frontier and the other farms are radially measured against this frontier with TE scores ranging from 0 to 1 (fully efficient farms). For the analysis of efficiency changes after the one year implementation period, the Malmquist index was used. Regression analysis revealed that farms with a higher health state achieved significantly higher technical efficiencies (efficiency increase of 5 percentage points with increase in WQ principle score 'Good health' by 10; slope=0.
Recorded data was also obtained from each farm on farm profitability measures: average milk production, somatic cell count (SSC), calving interval, breedings per year, % culling, and % of cows in third lactation or higher. Univariate regression and multivariate regression was used to analyse the association between passing each welfare criterion and the indicators of farm profitability. Passing the criterion for lameness prevalence interacted with the % of primiparous cows on the farm to affect annual milk production (P<0. 001), which increased with a higher % of primiparous cows on farms that passed the criterion. When milk production genetic index and the % of primiparous cows was controlled for, farms passing the lameness criterion produced 289 kg less milk per year. SSC was higher on farms passing the criterion for neck lesions (P=0.
WAFL 2017 The effects of sensors and robots on human animal relationship on farm Florence Kling-Eveillard 1 , Nathalie Hostiou 2 , Emeline Ganis 1 and Valérie Courboulay 3 1 Institut de l'Elevage, ASTRE, France, 2 INRA, UMR Métafort, France, 3 IFIP -Institut du Porc, France; valerie. courboulay@ifip. asso. fr The digital revolution arrives on farm and leads to the development of the 'precision livestock farming' (PLF). Sensors collect data about the animals (milk quality, physical activity, etc. ). These data are interpreted by computers and given back to the farmer through connected devices to help him to make decisions. Robots may be associated to the sensors. The aim of this study was to identify if PLF deteriorates the human-animal relationship and to analyse farmers' satisfaction with these tools.
A survey was carried out in 25 farms in France: dairy farms with a milking robot or a heat detector, pig farms with an automatic feeder, poultry farms with a housing management system or an automated weighing system. Semi-directive interviews were conducted with the farmers to collect data on their initial motivation to adopt the equipment, the way it was introduced on farm, the changes that occurred in their work and in the contact with the animals, and the pros and cons. A qualitative content analysis was conducted. A typology mixing the type of farmer-animal relationship and the use of the precision tools was built, using a multiple correspondence analysis followed by a hierarchical clustering analysis. Most farmers mentioned that their job became more modern and that the work was easier with these tools.