dataesr/scientific-paragraphs-categorization huggingface dataset:
Community Type Clustering across Time The intra-and inter-individual variations in the gut microbiota composition across time were studied based on the conceptual framework of enterotypes, or more generically, community types  (Arumugam et al. , 2011). According to this framework, the samples are clustered into bins based on their taxonomic similarity  (Ding and Schloss, 2014). Briefly, we used the R Script available at: http://enterotype. embl. de/enterotypes. html; Arumugam et al. , 2011)  using the genera abundance of each individual (n = 34) in each time point (n = 6). Optimal number of communities' types in each time point was determined by the Calinski-Harabasz index. Species richness differences were calculated between communities type using the "Phyloseq" R package. The non-parametric Wilcoxon rank-sum test with Benjamini-Hochberg multiple test correction was used to compare the Chao1 index and the abundance of genera between gut community types in each time point.
Despite the lack of systematic differences in gut microbiota composition in horses subjected to the two different weaning methods, we investigated putatively associated functional modifications. To this aim, we used PICRUSt, which predicts the gene content of a microbial community from the 16S rRNA gene survey by querying an existing database of microbial genomes. Most of the enzyme-level functional pathways were not significantly affected by any of the weaning methods. However, the A group displayed an enrichment (q < 0. 05) of the glutamatergic synapse pathway, as well as amino acid metabolism (i. e. , phenylalanine, tyrosine, tryptophan and lysine biosynthesis) before the weaning day (Table  S7 ). To understand how the gut microbiota functioned, SCFAs, pH measurements and the loads of fungi, protozoa and total bacteria in feces were investigated.
ACKNOWLEDGMENTS We are grateful to  Jean Marie Yvon ,  Yvan Gaude ,  Thierry Blard ,  Thierry Gascogne ,  Philippe Barriere ,  Francois Stieau , and  Adelaide Touchard  for the animal sampling and management, and to  Marine Guego  and  Marine Beinat  for participating to the sample collection during the project. We also thank  Marine Guego  for helping us with DNA extraction and RT-qPCR, and  Catherine Philippe  for her kind advice and help on SCFAs analysis. MB acknowledges support from the  Spanish MEC-FSE  through the  Ramón y Cajal Program. Lastly, we are grateful to the  INRA MIGALE  bioinformatics platform http://migale. jouy. inra. fr for providing computational resources.
Acknowledgements We thank Paris municipality to have allowed us to survey pigeons in the three studied pigeon houses. We are very grateful to  Gérard Leboucher ,  Hélène Corbel  and  Philippe Lenouvel  for the help they provided at different stages of the study. This work was financed by grants from the local government (Ile-de-France:  Sustainable Development Network   R2DS , No. 2008-07 ). L. Jacquin was supported by a Ph. D. fellowship from the  French Ministry of Research. L. Dauphin was supported by the  ATM "Relations hommes-nature sur le long terme ", from the national museum of natural history.
T he neglected, but devastating, tropical disease Buruli ulcer is the third most common mycobacteriosis worldwide after tuberculosis and leprosy. It is associated with extensive subcutaneous necrosis caused by the human pathogen Mycobacterium ulcerans  (1). Surprisingly, since the sequencing of the first genome of this species in 2007 (2), there has been only one other genome submitted to the public nucleotide databases (draft sequence, strain Harvey, accession number JAOL01000000). Here, we report the draft genome of isolate S4018, recovered from a cutaneous lesion of patient with Buruli ulcer in Benin, Africa. The isolate was cultivated on Lowenstein-Jensen medium for 5 months. Prior to DNA extraction, it was grown on Middlebrook 7H10 agar and enriched with an OADC (oleic acid, albumin, dextrose, and catalase) supplement.
We attributed the high number of contigs to the characteristic accumulation of the IS2404 and IS2606 mobile elements in the genome of M. ulcerans  (2, 7) , since it has been shown that such repeated elements may interfere with the sequence contiguity of assemblies from short reads (Ͻ1,000 bp)  (8, 9). Therefore, even though Illumina is one of the most established platforms, more recent "third-generation" approaches performing at longer read lengths, such as the approach with the PacBio platform  (10) , might be more suitable for sequencing M. ulcerans genomes. Accession number(s). The draft genome of M. ulcerans S4018 sequenced under this project has been deposited at DDBJ/EMBL/GenBank under the accession number MDUB00000000. The version described in this paper is the first version, MDUB01000000.
ACKNOWLEDGMENTS We acknowledge  Tim Stinear  and  Jessica Porter  from the  University of Melbourne  for their technical advice, and we are most grateful to the  GenoBIRD Core Facility  for its technical support. This work was supported by the  ARMINA consortium (Alliance de Recherche sur les Maladies Infectieuses Nantes-Angers) of La Région des Pays de la Loire, France  (grant no. 201209680 ), and  Fondation Raoul Follereau.
Indeed, the evolution of oxidative status with age has not been described in growing mammals. Furthermore, in commercial farms, weaning can be carried out in variable management conditions which can affect growth of piglets and health, mainly through the expression of diarrhea  [11] , and the impact of these conditions on oxidative status has not been described. The aim of this study was to assess the opportunity to use indicators of oxidative status as biomarkers of piglet health in the context of weaning. For this purpose, blood indicators of antioxidant potential of the animals (Blood Antioxidant Potential (BAP), vitamin A and E concentrations, and hydroperoxides (HPO) were measured together with clinical and growth data in two experiments. A study carried out in experimental facilities was first designed to dissociate effects of age, weaning, and management conditions just after weaning on the evolution of oxidative status (trial A).
This does not alter our adherence to PLOS ONE policies on sharing data and materials. week later, 4 animals from each pen were moved to an empty pen and replaced by 4 nonexperimental animals. Feed change from starter to weaner feed was done abruptly at 32 days of age. In optimal conditions (OC), 16 entire males and 18 females were moved from farrowing rooms to a post-weaning room previously cleaned, disinfected and heated at 28˚C. Each of the 9 pens contained 2-4 piglets (1. 2 x 1. 3 m, 0. 40 m 2 / piglet) from only two litters. Transition of OC piglets from starter to weaner feed was done progressively on 3 days (from 32 to 35 days of age). At 61 days of age, all the piglets (21. 8 +/-5. 1 kg) were transferred to common standard growing facilities until slaughter. No antibiotic treatments were used during the study.
Statistical methods Analysis of variance were done using the lmer function from lme4 package  [15]  of R software  [16]. The effect of age (from 12 to 147 days of age in trial A, at 26, 33, 47 or 75 days of age in trial B) on growth and blood variables was analyzed in models including age as main effect, and piglet (Trial A) or piglet nested in the farm (Trial B) as random effect. In trial A, to investigate the variations of average daily gain (ADG), weight and blood variables around weaning, only data collected from 9 days before to 19 days after weaning were used and the models included time to weaning (from -9 to +19 days), management conditions (OC vs DC), age at weaning (W21 vs W28) and their interactions as main effects, and piglet as random effect. The number of days with diarrhea for each piglet during the 19 days following weaning was analyzed with management conditions and weaning age as main effects.
Time-course of pro-and antioxidant blood variables between 12 and 147 days of age (trial A) For this analysis, data from OC, DC, W21 and W28 piglets were pooled and analyzed for the age effect only. Plasma HPO increased transiently at 33 compared to 12 days of age (P < 0. 001), dropped back to initial levels at 47 days of age, and then continuously increased until 147 days of age (P < 0. 001, Fig  1A ). Blood Antioxidant potential (BAP) decreased at 47 compared to 12 days of age (P < 0. 01), came back to initial levels on day 54 and then remained stable until 147 days of age. Consequently, OSI followed HPO kinetic from 0. 23 (± 0. 008) at 12 days to 0. 30 (± 0. 008) CARRU. μmol -. L of equivalent vitamin C at 33 days and increased until 0. 40 (± 0. 008) CARRU. μmol -.
Influence of weaning age and management conditions on growth, diarrhea and on pro-and antioxidant blood variables (trial A) Only data collected around weaning were included in this analysis. The statistical model included the effects of weaning condition (OC vs DC), age at weaning (W21 vs W28), and the time relatively to the day of weaning (from 9 days before to 19 days after). ADG was severely reduced after weaning, whatever age at weaning and management conditions compared to ADG during the lactation period (P < 0. 001, Table  1 ). Between 5 and 11 days after weaning, ADG was lower for DC compared to OC piglets (P < 0. 05), whereas it was similar for W21 and W28 piglets (P > 0. 1, S1 Table ). From 0 to 19 days after weaning, 55% of piglets exhibited at least one day of diarrhea (S2 Table ).
Acknowledgments Authors gratefully thank  A. Lacoste ,  B. Lieubeau ,  J. Herve, G. Mignot P. Mormede ,  JN. Sialelli  and  E. Terenina  for their scientific contributions to the project,  N. Le Floc 'h for its critical advices on the manuscript and  JY. Audiard ,  D. Boutin ,  B. Carrissant ,  R. Comte , S. Dare,  J. Delamarre ,  H. Demay ,  B. Duteil ,  F. Guerin ,  P. Knapen ,  A. Lecorgne ,  M. Lefebvre ,  G. Martin ,  N. Me  ´zière,  H. Renoult ,  P. Roger ,  Y. Surel ,  F. Thomas  and  P. Touanel  for their technical assistance in lab and animal care and all pig producers who participated to this experiment. This experiment was supported by a grant from the  Integrated Management of Animal Health metaprogram of INRA  for the " GISA-SEVROBUST " project (www. gisa. inra. fr/en). andCooperl  Arc Atlantique.
Animals The sample size was calculated using a commercial software program (SigmStat and SigmaPlot 12) to detect a Visual Analogue Scale (VAS) difference between groups of 10 mm with a standard deviation of xx using a T-test with 80% power and 5% significance. Forty-nine clients owned female cats undergoing elective ovariectomy were included in the study (Fig. 1 ). Cats underwent routine preanaesthetic physical examination in order to assess their health status according to the American Society of Anesthesiologists (ASA) classification. Exclusion criteria were ASA ≥ II, fractious personality and age greater than eight years.
Conclusion and clinical relevance In this randomized prospective clinical trial, both anaesthesia protocols were suitable for cats undergoing ovariectomy and were comparable in quality of anaesthesia and analgesia. When combined with methadone and dexmedetomidine, alfaxalone and ketamine showed comfortable and reliable recoveries. Table  1  Data after injection of intramuscular (IM) dexmedetomidine (15 µg kg -1 ), 479 methadone (0. 3 mg kg -1 ) and alfaxalone (3 mg kg -1 )(DAM, n=22) or dexmedetomidine 480 (15 µg kg -1 ), methadone (0. 3 mg kg -1 ) and ketamine (3 mg kg -1 ) (DKM, n=22) to cats 481 undergoing ovarioectomy. Cardiorespiratory measurements were taken every 5 minutes 482 during surgery. The number of supplemental doses were the number administered after 483 the first supplemental dose (1 mg kg.
After 1 hour incubation at room temperature in the dark, 32 μL of streptavidin-coated donor beads (40 μg/ml final concentration) were added. Plates were analyzed after 30 min incubation in the dark at room temperature, using the Enspire1 reader and Manager software (PerkinElmer, USA). The minimum level of detection was 5. 3 mUI/L. Intra-and inter-assay coefficients of variation were 6% and 7%, respectively. The assay was validated by dilutional parallelism between standard curve and endogenous insulin and expected values against obtained values. Calculation of glucose homeostasis parameters from modified FSIGT assays. Glucose effectiveness (Sg), acute insulin response to glucose (AIRg), insulin sensitivity (IS) and the disposition index (DI) were calculated using the Bergman's minimal model  [34] [35] [36]  on the Min-Mod Millennium software (Ver 6.
Radiographic evaluation of osteoarticular status in yearlings Yearlings were sedated using butorphanol (Dolorex1, 0. 02 mg/kg IV, Intervet, France) combined with romifidine (Sedivet1, 0. 06 mg/kg IV, Intervet, France) for radiographic examination at 24 months of age. Examinations were performed as previously reported  [19]  but development was made with a Vetray CR 2430 scanner (Sedecal, Spain). Radiographs were examined with an Examion CR Vita 45 (Carestream Health, USA) and analyzed blindly by two experienced examiners in a digital format with the Vita CR System Software V. 3. 2. (Carestream Health, USA). OC was diagnosed according to the presence of lesions that were previously described  [19, 41, 42]. Yearlings were classified as OC-positive according to the presence of one or more OC lesions identified by both examiners.
Acknowledgments The authors are grateful to the staff of the  Institut Francais du Cheval et de l'Equitation (IFCE) experimental  farm ( Domaine de la Valade, Chamberet, France ) for care and management of animals and assistance during castrations, metabolic tests and radiographic examinations and to the  CMABIO3 platform (Unicaen) , especially  Nicolas Elie  (PhD) for his help. The authors are members of  COST Actions FA0702 GEMINI  " Maternal interaction with gametes and embryo ",  FA1201 EPICONCEPT "Epigenetics and periconceptial environment"  and  BM1308  " Sharing advances on large animal models (SALAAM) ".
Blood samples were collected three times from each subject: once between 18:00 and 19:00 after a day's work, once between 18:00 and 19:00 after a day's rest and once between 08:00 and 09:00 (around one hour after their first meal of industrial pellets). We chose these schedules so as to take into account both circadian variations  [59] [60] [61] [62] [63] [64]  and a potential impact of working activities (physical exercise, and also agitation and noise in the stable during daytime) on cortisol levels. Samples were taken in spring and in early summer 2007. Plasma cortisol levels were measured using Immunotech kits for cortisol determination (Beckmann and Coulter). The kit was modified for equine plasma as follows: 1) the quantity of plasma per dose was 25 μL instead of 50 μL; 2) a two-hour preliminary incubation at 20˚C between plasma and antibodies was added; 3) we used two standard curves: the first with increasing cortisol contents in buffer (as indicated by the manufacturer) and the second with increasing cortisol contents in equine plasma (from pooled data for controls totaling less than 2 ng/mL of cortisol).
This technique was chosen as radiographic imaging is limited by the thickness of the surrounding soft tissues  [76] ; ultrasonic and scintigraphic approaches remain difficult to apply in the field and on large samples of horses  [76, 77]. Examinations were based on bony and soft tissue manual palpation to localise regions of vertebral stiffness based on spinal mobilisation and palpable areas of muscle hypertonicity  [78, 79]. Comparisons of data from different practitioners have shown high agreement and therefore repeatability as well as correlations with electromyogram (EMG) data in other studies  [37, 42, 44]. In the present study, a second examination by another practitioner (G. Bohn) gave 94% agreement. Examinations were performed outside the horses' working hours, in their individual boxes.
The horse was lightly restrained by one unknown (to the horses) experimenter (M. Hausberger) also blind to horse's results in behavioral tests. Horses were classified by the practitioner as totally exempt, slightly affected (one slightly affected vertebral site) or severely affected (at least two severely affected vertebral sites). Data included also the number of affected vertebral sites. Haematological data. At the same time as the morning cortisol sample was taken a blood sample was collected for each horse, between 08:00 and 09:00 and taken within the hour to a veterinary laboratory for analysis (Laboratoire Veterinaire Departemental Ille et Vilaine, Rennes, France). Haematological data analysed were numbers of red blood cells (millions / mm 3 ), white blood cells (million / mm 3 ) and platelets (mille / mm 3 ), percentages of neutrophils, eosinophils, basophils, lymphocytes, monocytes, hematocrit and haemoglobin (g/100ml), haemoglobin / hematocrit (g/100ml) and hematocrit / number of red blood cells per L (μm 3 ).
Acknowledgments We are grateful to the directors and staff of the riding centers for their help with data collection; C. Fureix ,  L. Dupont  and  C. Lavertue  at the  University of Rennes 1  and  E Klobetz-Rassam  at the  University of Veterinary Medicine, Vienna , who aided with sample collection and analyses. This work was funded by the  Caisse Centrale de la MutualiteAgricole, University of Rennes 1  and the  Le Centre national de la recherche scientifique (CNRS).
Statistical analysis Data were submitted to ANOVA using the IBM SPSS Statistics software  (v. 21, 2012). To compare litters of different sizes and to determine whether position of the piglet in the birth order (BO) affected within-litter birth Regression analyses were used to determine the relationship between BW 0 and TB (with the exception of mummies and 4 stillbirths which were not weighed), BW 0 and BA piglets, CI and RBO. Regressions analyses were also used to determine the relationship between CI and BW 0 , serum IgG concentrations of piglets at 2 d of age (IgG2d), and between IgG2d and RBO. In order to consider the litter effect, the values used for each regression were the unstandardized residues previously obtained by ANOVA, using litters as fixed effect. To compare the characteristics of piglets that either died or survived during the suckling period within each litter, piglets were classified as either "light" (LG) [BW 0 ≤ (x-one SD)] or "normal" (NM) [BW 0 > (x -one SD)], where x is the average BW 0 of the litter, and SD its standard deviation.
We used generalized linear mixed models to verify predation events and the size of carcasses using spatiotemporal characteristics as predictors. STPSS uses a probability model to compare expected cluster size (space and time) with the observed size. We applied this method retrospectively to data from 2006 to 2007 to compare our method to random GPS site selection. In 2013-2014, we applied our detection method to visit sites one week after their occupation. Both datasets were collected in the same study area. Our approach detected 23 of 27 predation sites verified by visiting 464 random grizzly bear locations in [2006][2007] 187    of which were within space-time clusters and 277 outside. Predation site detection increased by 2. 75 times (54 predation events of 335 visited clusters) using 2013-2014 data.
, 2009). A growing practice is to visit GPS point clusters that are identified visually or using automated detection methods. Tools such as Python scripts defined clusters by constraining points in space and time  (Cristescu et al. , 2014b; Miller et al. , 2013) , k-means clustering  (VanMoorter, Visscher, Jerde, Frair, & Merrill, 2010) , spatially joining buffered GPS points  (Zimmermann et al. , 2007) , or spatial only noise (DBScan) clustering  (Ebinger et al. , 2016)  have proven effective. When predators kill large prey or scavenge large carcasses, they often spend more time near to the carcass  (Cristescu et al. , 2014a; Knopff et al. , 2009). This may create detectable space-time patterns in GPS data, characterized by relatively long periods spent by the predator in relatively small areas.
| Cluster detection protocol To detect spatiotemporal clusters in the datasets collected at two different times, we used the retrospective space-time permutation scan statistic (STPSS)  (Kulldorff, Heffernan, Hartman, Assunção, & Mostashari, 2005)  in SaTScan 9. 4  (Kulldorff, 2015). The STPSS selects event clusters (e. g. , bear GPS points) by centering spacetime cylinders on each event. The cylinder's base represents two-dimensional geographic space, and its height represents time, in hours. The outcome is numerous overlapping cylinders considered to be potential clusters. The STPSS then applies a Poisson-distributed probability function to compare the expected number of GPS points to fall in each potential cluster to the observed number of GPS points. This method allowed us to detect clusters of "cases" with distributions in space and time that potentially differ from an expected spatiotemporal pattern.
We considered only space-time clusters within the 95% confidence interval determined by SaTScan's Monte Carlo testing that compares the Poisson generalized likelihood ratio (GLR) for each cluster to the GLR obtained from 999 randomly simulated clusters  (Kulldorff et al. , 2005; Webb et al. , 2008). We ran the STPSS on 14-day periods of individual grizzly bear GPS points. We chose two weeks based on a doubling of the seven-day maximum grizzly bear occupancy of kill sites estimated by  Ballard et al. (1981). Each dataset intentionally overlapped the consecutive period by 7 days to prevent exclusion or alteration of clusters that might potentially overlap two arbitrarily selected periods (e. g. , a cluster composed of 20 hourly GPS points might appear as of 10 if unintentionally bisected). Duplicate clusters were visually detected and removed from further analyses.
| Field data collection One location per day for each bear was examined (stratified random design) about 26 days (SD = 5) after the bear had visited that location. Although clusters were detected the same way for both datasets, for the 2006-2007 period, clusters were generated a posteriori to assess whether a location fell within the start and end time of a generated cluster and within that same cluster's 50 m spatial constraint. If a cluster fit those criteria, the location was considered within a cluster (n = 187), otherwise outside a cluster (n = 277) (Figure  3 ). In 2013-2014, clusters were explored by searching a 50-m-radius area starting from the GPS point closest to the geometric mean of the detected space-time cluster and spiraling outward. In previous studies, geometric centroids have been used as starting points  (Knopff et al.
| Model formulation Carcass size information was not available for the 2006-2007 dataset, because sites, when visited, often did not contain enough remains to indicate size of prey. Using just the 2013-2014 dataset of focused cluster visits (for which carcass size data were also available), we therefore formulated generalized linear mixed models (GLMM)  (Dobson, 2008)  to predict predation events or prey size using cluster spatiotemporal characteristics and bear sex and age as predictors. We used bear ID as a random effect in both models to account for multiple clusters from the same individuals with potentially unique behaviors  (Gillies et al. , 2006). Outcome (dependent) variables included: the presence or absence of a predation event, and the size of the carcass or prey (small/medium or large).