dataesr/scientific-paragraphs-categorization huggingface dataset:
Feed ingredients that represented less than 0. 5% of annual intake and that were absent from the EcoAlim dataset were not included in the LCI. Feed production at the feed factory was included in the LCIs of commercial feeds by assuming that it would occur in the same region as the pig production, and would require 41 kWh of electricity and 20. 5 kWh of natural gas per t of feed produced, for grinding and pelleting  (Garcia-Launay et al. , 2014). For on-farm feed production, grinding and mixing required 18 kWh of electricity per t of feed produced  (Badouard and Roy, 2011).
Emissions from pig production Emissions to the air were estimated separately for NH 3 , N 2 O, NO x, and CH 4 for sows, post-weaning piglets, fattening pigs, feed production, animal housing and manure management using SAS software (SAS Inst. Inc. , Cary, NC, USA). Housing condition was accounted to calculate the gaseous emissions (Table  2 ). For the periods in which the animals were kept outdoors, NH 3 , N 2 O, NO 3 and NO x emissions were calculated based on emission factors provided by  Basset-Mens et al. (2007). For the periods during which the animals were kept indoors, gaseous N emissions were calculated for housing and storage and field application of solid manure using the step-by-step procedure recommended by EMEP/EEA (2016). Emission factors for NH 3 and N 2 O came from  Rigolot et al.
Impact categories The analysis was based on the CML 2001 (baseline) method V3. 02 as implemented in SimaPro software V8. 03 and added the following categories: land occupation from CML 2001 (all categories) V2. 04 and total cumulative energy demand V1. 8 (non-renewable fossil + nuclear). The CML method was chosen because it was used in most pig LCA studies in the literature, which allows for comparison of our results to previous results. Thus, potential impacts of pig production on global warming potential (GWP, kg CO 2 -eq. ; 100-year horizon), eutrophication potential (EP, g PO 4 -eq. ), acidification potential (AP, g SO 2 -eq. ), cumulative energy demand (CED, MJ), and land occupation (LO, m 2 year) were assessed.
Acknowledgements The authors wish to thank the farmers surveyed during this study for their collaboration and the expert knowledge provided by scientific collaborators:  J. Faure  ( Agrocampus-Ouest ),  H. W. G. van der Werf  ( INRA SAS ),  D. Renaudeau  ( INRA PEGASE ),  A. Fonseca  ( Consortium du Noir de Bigorre ),  B. Lukač  ( Agricultural Institute of Slovenia ) and  E. Bartoletti  ( Fattoria Palazzo di Zattaglia ). This project received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement no. 634476 (project  TREASURE ). This article reflects the authors' viewpoints only; the  European Union  is not responsible for any use that may be made of the information it contains. We would also like to acknowledge financial support (core financing grant  P4-0133 ) from the  Slovenian Agency of Research  for MCP, NBL and  UT.
Behavioral Measures All horses were video recorded during the bridge test. The behavioral events observed were retreat (backward movement with at least one foot), swerve (sideways movement), jump (over the bridge), snort (forceful quick exhalation), and neigh (loud, prolonged high pitch call). Videos were then analyzed using The Observer XT (2011) software (Noldus Information Technology, Wageningen, The Netherlands). Offline continuous recording was used, and all behavioral event occurrences, number of trials, and the total time to cross the bridge were registered.
Physiological Measures Heart rate (HR) and heart rate variability (HRV) recordings were obtained using a Polar Equine V800 heart rate monitor system (Polar Electro Oy, Kempele, Finland). For each horse, a 5 min long data set during resting time was recorded  [13]. For this, after placing the polar system, a habituation to the monitor for 30 min was performed Then, a 5 min data set was obtained and the horse was led to the area where the bridge test was performed. A second data set from the beginning of the bridge test until its end was obtained. Additionally, heart rate was also recorded at the start of the bridge test (T1), when the horse crossed the bridge (T2), and 10 min after the bridge test (T3). For HRV analysis, information from the Polar system was synchronized with the Kubios HRV software (Kubios standard 3.
However, one methodological issue was the fact that the same data were used both to generate the predictive equation and then test its validity and, therefore, it is not surprising that the new equations better fitted the data  [17, 18]. Instead, confirming superiority of these alternative equations ideally requires crossvalidation with an independent dataset  [17, 18]. A second methodological issue with the study was the fact that both dry and wet foods were included within the same linear regression analyses. This meant that the regressions effectively assessed two distinct groups within the same his academic position is financially supported by the funder. The specific roles of these authors are articulated in the 'competing interests' section.
Eligibility criteria for feeding trials All feeding trials, conducted at a single location (Royal Canin Research Center, Aimargues, France), between January 2006 and December 2011 were reviewed. For inclusion, trials had to have been conducted according to according to AAFCO recommendations for Dog and Cat Food Metabolizable Energy Protocols (Method 1: Quantitative Collection) [3], meaning that details of proximate analysis and gross energy (GE) for both the diet and the faeces, as well as digestibility data from 6 animals were available (e. g. where GE had both been measured and predicted according to NRC 2006 equations  [2] ). Details of the diets included are summarised in Table  1 , and details of all diets is given (S1 File).
The runs with outdoor access were divided into an indoor part (of 13 m 2 ) and an outdoor part (of 14 m 2 ). Inside, temperature varied between 18-24˚C, depending on season, and artificial light was provided between 07:30 and 17:00 if natural light was judged to be insufficient by animal handlers. Again, humidity data were not recorded. For all cats, care-givers stimulated play behaviour for approximately 2h, per run, per day. During digestibility period (5 days), cats were housed in individual lodges (1. 4 m 2 ) in order to obtain individual data. These lodges were environmentally enriched with raised platforms at different heights, to make best use of vertical space. All cats remained healthy for the duration of the studies.
Statistical analysis Data were analysed using different statistical software packages (JMP 5 ME predictions calculated using species-specific equations based upon crude fibre  [2]. 6 GE: gross energy content of food, determined either by measurement [3] or prediction  [2]. 7 ME predictions calculated using species-specific equations based upon total dietary fibre  [2]. 8 ME predictions calculated using species-specific equations reported by Hall et al. [16]. https://doi. org/10. 1371/journal. pone. 0223099. t004 compared against measured ME. Deming regression was used to compare associations between ME predicted with each equation and ME measured in the feeding trial  [20]. Acceptability was further assessed by constructing Bland-Altman plots  [21]. For each plot, average bias and 95% limits of agreement were calculated, with results analysed further by with a 1-sample T test (to assess the significance of any bias between measured and predicted ME), and simple linear regression analysis (comparing mean of and differences between the two methods) to assess for possible proportional errors.
A total of 26 canine feeding trials on wet food were also eligible for inclusion, and sufficient data were available from 25 of these to calculate ME by all methods (S4 File). A total of 29 feline feeding trials on wet food were also eligible for inclusion, and sufficient data were available from 24 of these to calculate ME by all methods (S5 File). Summary statistics of the guaranteed analyses of the canine and feline foods that were used in the feeding trials finally included in the study are given in Tables  1  and 2 , respectively.
In the current study, the NCR 2006 cf equation performed better when using measured GE rather than predicted GE; with predicted GE, performance of this equation was marginally better than the MA equation in terms of systematic bias, but there was still a marked proportional error, when predicting ME content of feline dry food especially. Using measured, rather than predicted, GE improved the accuracy of predictions better, with narrower 95% limits of agreement (especially for wet food) but did not totally resolve the issues with proportional bias. Hall et al. also generated new equations which performed better than both the MA and NRC 2006 cf equations  [16]. As highlighted above, a limitation was that the same dataset was used both to generate the predictive equations and test them. Therefore, the current study was an opportunity to assess the performance of the equations proposed by this study with an independent dataset.
Further sources of inaccuracy include methods used to measure food portions (e. g. the use of measuring cups  [27] ) and feeding extra food in the form of treats and table scraps  [28]. Therefore, to avoid overfeeding, owners should also be made aware of how to measure out food portions accurately (e. g. using electronic gram scales) and also about the potential impact of feeding additional food. The study has a number of limitations that should be considered. First, although the number of available studies was large, some datasets were incomplete limiting the number of available food trials for the final analyses. Secondly, only a limited number of feeding trials were conducted on wet food during the study period meaning that conclusions about such food should be made more cautiously. Third, the studies were undertaken over a five-year period and only small numbers of animals from a single research colony; therefore, actual availability of ME in a diverse population of pet cats and dogs might be different.
Acknowledgments The authors wish to thank all caregivers for participating in the study. This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Conflicts of interest are as follows: At the time the study all authors were either employees  Royal Canin , except JC (who was undertaking an internship at the  Royal Canin research campus ) and AJG (whose academic post at the  University of Liverpool  is supported by  Royal Canin ). AJG has also received financial remuneration for providing educational material, speaking at conferences, and consultancy work from this company; all such remuneration has been for projects unrelated to the work reported in this manuscript. Authors were involved in the study design, data collection, data analysis, or data interpretation, and also in both the writing of the manuscript and in the decision to submit it for publication.
Transcription Levels of lsr2 in M. abscessus R and S Strains Our initial comparative genomic analyses performed on three isogenic M. abscessus S/R pairs identified several mutations in the GPL biosynthesis/transport locus that are responsible for the S-to-R transition  (Pawlik et al. , 2013). Microarray data obtained from RNAseq highlighted the differential expression   S2 ). MAB_0545, encoding the Lsr2 protein, was found to be moderately more expressed in the R than in the S variants of the CIP104536 and ATCC19977 strains as well as in one clinical isolate, referred to as the CF R strain  (Catherinot et al. , 2009). To confirm these results, quantitative RT-PCR analysis was performed on lsr2 using mRNA isolated from both the S and R variants of all three strains. Figure  1  shows that transcription of lsr2 is increased in the R strains relative to their S counterparts, particularly in the two type strains, thus validating the microarray data.
| Statistical analysis All demographic data and results were recorded on Excel spreadsheets (Microsoft, Redmond, Washington). Descriptive statistics, Spearman correlations, Passing-Bablok agreement curves, and difference diagrams were obtained with Analyse-It (Leeds, United Kingdom). Reference intervals were determined with Reference Value Advisor 15 using the nonparametric method, except when n <40 in which case the robust method was adopted. The 90% confidence intervals (CIs) were calculated by the nonparametric method when n >120 and by a bootleg methods in other cases. Outliers were identified by visual inspection of the histograms and Tukey's test. Values for the deleted outliers are given in the table footnotes. All variables were tested for possible effects of the following co-variables by ANOVA using Systat 13 (Systat Software, San Jose, California): presence of urine ketones, type of production (beef versus dairy), stage of lactation (beginning versus middle versus dry), breeding farm (1-32), and age.
Study design and epidemiological data sources We retrospectively obtained quantitative data. Epidemiological data for Buruli ulcer in Benin were collected from the annual statement of the four Centres for Leprosy and Buruli Ulcer Treatment and Diagnosis (CDTLUBs), as part of the National Control Program for Leprosy and Buruli Ulcer in Benin. The widespread locations of the four centres makes it possible to do continuous active surveys, to establish disease burden, and to provide the most appropriate care for each patient. Furthermore, it makes it possible to collect high-quality epidemiological data, as highlighted by many published epidemiological studies. 17, 18 nformation about well drilling (dates and sites) was obtained from the Ministry of Energy, Water and Mines of Benin (Vouillamoz J-M, Institut de recherche pour le développement, personal communication).
Coordinates were obtained for each well drilled in the departments of Ouémé and Plateau, with a hand-held global positioning system receiver (GarminGPSMAP-62sc; Olake, KS, USA). Patient data were collected at the CDTLUB-Pobè, where all epidemiological records for the patients with Buruli ulcer from the Ouémé and Plateau departments (administrative areas approximately equivalent to a county) are archived. Data collection was approved by the institutional review board of the CDTLUB and the national Beninese Buruli ulcer control authorities (IRB00006860), as well as the ethics committee of the university hospital of Angers, France (Comite d'Ethique du CHU d'Angers). Buruli ulcer cases were defined on the basis of the WHO clinical definition, with a confirmation by PCR. Sociodemographic variables (ie, age, sex, village or city of residence) were also collected for the patients with Buruli ulcer.
Research in context Evidence before this study We searched PubMed, without language restrictions, for articles published from database inception up until Dec 30, 2018, using the search terms "Buruli ulcer" OR "Mycobacterium ulcerans" AND "Epidemiology". 415 studies were identified and around 20 reported an association with contact with unprotected water sources (rivers) as the main risk factor for Buruli ulcer. Surprisingly, effects of well drilling on Buruli ulcer epidemiology have not been investigated in areas in which this disease is endemic, and the factors accounting for variations of Buruli ulcer incidence have not been identified, despite the decrease in the number of new cases observed in most African countries (Côte d'Ivoire, Ghana, Benin) in which Buruli ulcer is endemic.
Implications of all the available evidence The present study provides rationale for firm yet affordable public policies to be implemented at large scales in the affected areas, encouraging the drilling of wells to reduce the incidence of the disease. Accumulation of feedback data for the intervention should provide increasingly more accurate information on the optimal location for the well drilling, and integrating parameters relative to various underlying social aspects. Such voluntary policies should, in return, also provide valuable information concerning the fundamental aspects of the epidemiology of the disease. controls were individually matched on the basis of age and sex. A door-to-door systematic procedure was implemented for control selection. For any given case, we took their house as a starting point; we then continued in a random direction.
The research team and the nurse then went to meet the patients with Buruli ulcer at their place of residence or work. A questionnaire, either in French or translated into one of the local languages (ie, Goun or Nago), was read aloud to participants and completed in front of them. In the field, geographical coordinates were collected for the sites of human contact with water. These coordinates were obtained with the aforementioned hand-held global positioning system receiver. We calculated the Euclidean distance (shortest point-to-point distance) between the drilling site, the main bodies of water at which contact between humans and water occurred, and the places of residence and work of the patients, with ArcGis version 10. The various maps were constructed from field surveys and from diverse data sources (OpenStreetMaps, Google Earth, Shuttle Radar Topography Mission, Institut National de la Statistique et de l'Analyse Economique du Bénin).
We enrolled 106 individuals with previously diagnosed Buruli ulcer (diagnosed by the CDTLUB-Pobè) and 212 controls in this case-control study. Most patients (69 [65%] patients) were younger than 15 years old with a median age of 10 years (IQR 6•0-29•5). The sex ratio of male to female participants was 0•77 at the time of Buruli ulcer diagnosis. Most of the patients were young, accounting for the large proportion of schoolchildren and students among the recruited cases (49 [46%] patients). As ascertained from the questionnaire, the main socioeconomic activity in adult Buruli ulcer cases was subsistence farming (data not shown). We first did a univariate analysis to investigate the association between Buruli ulcer incidence and independent variables, such as sociodemographic factors and activities involving contact with water (table).
Acknowledgments We thank all the staff working at the  Centre de Dépistage et de Traitement de la lèpre et de l'Ulcère de Buruli of Pobè (The Pobè Buruli Ulcer and Leprosy Screening and Treatment Centre). We thank all those at the  Health Centre of Assrossa-Bonou , in particular  Louis Hounkpatin , who helped with data collection. We sincerely acknowledge  Laurent Marsollier  for their constructive and critical reviews.
Animals and Experimental Design Data used in the present study were obtained from a backcross design in which 60 and 70 Large White (LW) dams in TEMP area (INRA-Génétique, Expérimentation et Systèmes Innovants, Poitou-Charentes, France; 46°N, 0. 45°W) and in TROP area (INRA-Plateforme Tropicale d'Expérimentation sur l'Animal, Guadeloupe, French West Indies; 16°N, 61°W), respectively, were inseminated with the same 10 F1 (LW × Créole) boars. Créole breed is a local tropical breed. Full details on the experimental design are given by  Rosé et al. (2017). Finally, 558 and 564 backcross pigs (castrated males and females) in 12 batches were produced in TEMP and TROP climates, respectively. The general animal management conditions were homogenized in both climates before starting the study. We ensured the consistency of this management by sending farm technicians from the farm in TEMP area to the farm on TROP area and technicians from the farm in TROP area to the farm on TEMP area.
The following abbreviations will be used in the current article: TEMP23, TROP23, and TEMP26 will refer to data collected at 23 wk of age on TEMP and TROP and at 26 wk of age on TEMP climate, respectively. The chronic HS will refer to the comparison between TEMP23 and TROP23. The acute HS will refer to the comparison between TEMP23 and TEMP26.
DNA Sequencing The DNA extraction was performed with the Zimo kit from 50 mg of feces sample according to a method previously described by  Verschuren et al. (2018). The V3-V4 region of the 16S rRNA gene has been amplified by PCR before sequencing on an Illumina MiSeq platform. The amplification used F460 and R460 primers (F460: CTTTCCCTACACG ACGCTCTTCCGATCTA CGGRAGGCAGCAG, R460: GGAGTTCAGA CGT GTGCTCTTCCGATCTTA CCAGGGTA TCTAATCCT) and 30 cycles of PCR with an annealing temperature of 65 °C. The resulted 2 × 250 bp paired-end sequences were cleaned internally for length, homopolymers, and undetermined nucleotides. Sequencing and sequence cleaning have been performed in the GeT-PlaGE platform (Toulouse, France). The VSEARCH software  (Rognes et al. , 2016 ) was used to remove chimeras from the sequences data set and then to de novo cluster the resulting sequences into operational taxonomic units (OTU) with a threshold of 0.
97 similarity. The abundance of each OTU in each sample was recorded. Rare OTU, representing less than 0. 01% of the sequences from all samples, were removed. The Usearch software (9. 2. 64_i86linux32 version) was then used for taxonomic assignation based on SILVA database. The PICRUSt pipeline was applied on the 16S rRNA sequencing data  (Langille et al. , 2013). The resulting abundance of KEGG (Kyoto Encyclopedia of Genes and Genomes) genes orthologues in each sample was further categorized into biological pathways.
, 2018). The proportions of the variance explained by the environment, the batch, the sex type, or the sire family were evaluated by a principal variance component analysis (PVCA) through the Bioconductor R pvca package  (Bushel, 2018). The effect of the environment (TEMP23, TROP23, and TEMP26) on the relative abundance of the bacteria at the phylum level was evaluated through Wilcoxon tests, using 2 × 2 comparisons. Generalized linear models (GLM) were then established using edgeR R package  (Robinson et al. , 2010)  to evaluate the impact of the environment on the abundance of each OTU and of each pathway. The fixed effect of the sex was included in the model. The effect of batch within each climate was considered as a random effect. The analyzed models compared TEMP23 vs. TEMP26, and TEMP23 vs.
TROP23 for the OTU, and also TEMP26 vs. TROP23 for the pathways. The P-values were adjusted for multiple tests with the Benjamini-Hochberg method. In addition, a threshold was fixed to 0. 5 log2 fold change to extract the most differentially represented pathways in the studied environments. To predict the environment in which the pigs were raised based on their microbial data, sparse partial least squares discriminant analyses (sPLS-DA) were performed by using MixOmics R package  (Lê Cao et al. , 2011). The sPLS-DA was performed on the OTU table previously normalized through a total sum scaling and centered log ratio transformation. This table was not rarefied and the counts varied between 7,000 and 75,234 sequences per sample. A M-fold cross-validation was performed to evaluate the error rate of the models with 10-folds and 10 times repetition.
PCR products were resolved on a capillary sequencer ABI 3730XL (Thermo Fisher Scientific) by the Genoscreen laboratory (Lille, France). The electropherograms obtained were analyzed using GENEMAPPER software (Applied Biosystems/Life Technologies) and read by two independent analysts to determine allele sizes for each individual and markers. This microsatellite panel is known to produce unambiguous genotypes and to be highly polymorphic, and has demonstrated its relevance in previous H. contortus genetic structure studies (e. g. ,  [68] ). Genotyping errors were tracked using MICROCHECKER v. 2. 2. 3 software  [78]. Using FSTAT v. 2. 9. 3. 2 software  [35, 36] , we determined genetic diversity indices (see Table  1 ) and tested for departures from Hardy-Weinberg (HW) equilibrium and linkage disequilibrium between pairs of loci (none detected, results not shown).