dataesr/scientific-paragraphs-categorization huggingface dataset:
5 (Figures  5A, B ). This retinoid reporter transgene exhibited low level of expression in both mandible and maxilla adjacent to the growing incisors and molars in E16. 5 untreated fetuses (Figure  5C  and data not shown). In E16. 5 fetuses following RA treatment from E12. 5 to 16. 5, domains of RARE-lacZ activity broadly extended into alveolar bone and surrounding mesenchyme, but appeared absent from enamel organ and dental ectomesenchyme (Figure  5D  and data not shown). Note that very low levels of RA signaling may not be detected by such a reporter transgene. Proper control of RA levels is necessary for early neural crest patterning, but RA deficiency does not alter first branchial arch formation  (Niederreither et al. , 2000). To explore why RA activity was absent from most tissues of the tooth buds, we examined expression of CYP26 family cytochrome P450 enzymes specifically involved in RA catabolism.
, 2004 )), a target reduced by ∼2-fold at E16. 5 in RA-treated samples (Table  2 ). A novel RA-inhibited target is the matricellular protein Smoc2, whose mutation in human produces oligodontia, microdontia, abnormal root development, dentin dyplasia, and reduced alveolar bone growth  (Bloch-Zupan et al. , 2011). Retinoids are known to drive uncommitted progenitor cells into neuronal lineages  (Maden, 2007). Consistently, DAVID (Database for Annotation, Visualization, and Integrated Discovery) analysis revealed a functional enrichment score of 1. 4 E -6 for neuronal differentiation pathways. Increased Neurogenin1 (Neurog1), Neurogenin2 (Neurog2), and the notch target Hes5, are typical of an RA-induced neuronal differentiation profile (Table  S2 ). At E16. 5, Enam was the most reduced target (Table  2 ), also markedly reduced by in situ hybridization analysis (Figure  S7 ).
050 will result in false positives. regulating crystal adsorption  (Addison and McKee, 2010) , and their mutations produce hypomineralized enamel phenotypes including altered prism patterning and increased cellular apoptosis in both patients and mouse models  (Fukumoto et al. , 2004; Bei, 2009; Hu et al. , 2014; Núñez et al. , 2015). Reductions in the SCPP cluster appeared specific to enamel expression. Other enamel-regulating targets included the kallikrein-related The binding site motifs of Runx2/3, Dlx3/5, and Smad2/3/4 were obtained from the JASPAR database (http://jaspar. genereg. net) and used to find potential binding sites in conserved regions using the rVISTA database (http://genome. lbl. gov/vista/index. shtml). peptidase 4, essential for removing enamel proteins and biomineralization (OMIM: 603767), the peroxisome proliferatoractivated receptor (PPAR) alpha, required to achieve normal enamel mineralization (OMIM: 170998)  (Sehic et al.
ACKNOWLEDGMENTS We wish to thank  Amandine Velt ,  Céline Keime ,  Bernard Jost ,  Christelle Thibault-Carpentier ,  Doulaye Dembelé ,  Antonio Nanci ,  Greg Pratt ,  Rena D'Souza ,  Sylvain Provot ,  Dominique Hotton ,  Valérie Fraulob ,  Carole Haushalter ,  Muriel Rhinn ,  Anna Niewiadomska-Cimicka , and  Claire Huber  for gift of reagents, technical assistance, and/or knowledgeable insight.
FUNDING This work was supported by a grant from the  University Hospital of Strasbourg (API ,  2009-2012 , "Development of the oral cavity: from gene to clinical phenotype in Human"), the  EUfunded projects (ERDF)   A27  " Oro-dental manifestations of rare diseases " in the framework of the  RMT-TMO Offensive Sciences initiative INTERREG IV and INTERREG V No. 1. 7 RARENET , the  Institut d'Etudes Avancées (Institute of Advanced Studies) de l'Université de Strasbourg  (USIAS Fellows 2015), and the grant  ANR-10-LABX-0030-INRT  managed by the  Agence Nationale de la Recherche  under the  frame program Investissements d'Avenir   ANR-10-IDEX-0002-02. Sequencing was performed by the  IGBMC Microarray and Sequencing platform , supported by the  France Genomics National Infrastructure , funded as part of the  Investissements d'Avenir program  ( ANR-10-INB S-0009 ).
Animals and Baseline Variables Although a minimum of 80 dogs was planned in the protocol, recruitment was slow and inclusion was stopped by the sponsor after 49 dogs were recruited in the 29 months from March 1997 to July 2000. The number of cases screened was not recorded, but 49 dogs enrolled into the study were included in the database; 24 received benazepril and 25 received placebo. All 49 cases were included in the statistical analyses, which can therefore be considered an "all-randomized animal" or "intent-to-treat" analysis. No separate "perprotocol" analysis was made. Baseline data are shown in Table  1. There were no significant differences between groups for any variable. In the benazepril and placebo groups, respectively, 17 and 17 dogs had a reported recent history of any clinical sign, 8 and 16 had decreased appetite, 2 and 1 had diarrhea, and 4 and 4 had vomiting.
A total of 12 dogs were in International Renal Interest Society (IRIS) stage 2 (plasma creatinine ≤180 lmol/L), 29 were in IRIS stage 3 (plasma creatinine >180 and ≤440 lmol/ L), and 8 in IRIS stage 4 (plasma creatinine >440 lmol/ L). 14  Presence of Leishmania or other systemic parasite infections was not recorded, but only 1 dog was noted to have been treated previously for Leishmania infection. Some dogs included into the study did not fulfill the inclusion criteria. Although plasma creatinine and USG values from the investigators' laboratories were in all cases in compliance with the defined criteria, the final values used in the data analysis were derived from a separate central laboratory. At day 0, a total of 8 dogs had plasma creatinine concentrations (range 88. 4-141. 4 lmol/L) lower than the value of 142 lmol/L defined as the inclusion criterion.
One dog had a USG value of 1. 022 at day 0, versus the inclusion criterion of ≤1. 020. In accordance with the intention-to-treat approach, all cases were included in the analysis. The neutered status of 1 male dog in the benazepril group was not recorded. P values were calculated with the Mann-Whitney U, Kruskal-Wallis, or Fisher's exact tests. There were also no significant differences between the 2 groups at baseline for the subgroups of dogs with UPC >0. 5 or UPC >0. 5 and plasma creatinine ≤440 lmol/L (data not shown).
Therefore, additional analyses were conducted with stratification for baseline plasma creatinine and UPC, and by CPH analysis. The database contained a total of 53 variables from 49 cases. In order to reduce the risk of overparameterization, variables were selected for the CPH analyses as follows. First, correlations between clinical chemistry and hematology variables were assessed via Spearman q and P values, and only one of highly correlated variables was selected. Hematocrit, hemoglobin concentration, and red blood cell (RBC) count were highly correlated (q > 0. 95); therefore, RBC count was used. Second, presence or absence of bad breath, buccal cavity lesions, decreased appetite, diarrhea, dullness, neurological signs, vomiting, and weakness were summarized into a single category, the presence or absence of CKD clinical signs.
Time from inclusion in study (days) 0 Dogs with UPC >0. 5 and plasma creatinine ≤440 lmol/L (n = 27). In the univariate analysis, only plasma phosphate concentration was significant (P <. 05) and was associated with an HR >1 (Table  7 ). For the treatment effect (benazepril versus placebo), the HR (95% CI) was 0. 38 (0. 12-1. 19) with P =. 080 in the log-rank test. In the multivariate analysis, plasma phosphate and plasma protein concentration were significant (P <. 05) and were associated with HRs >1 (Table  5 ). Secondary Efficacy Endpoints. Mean (SD) data for UPC and plasma creatinine are shown up to day 180 in Figs  4  and 5. Data became increasingly unreliable after day 180 due to the loss of cases from the study. Proteinuria was assessed from the UPC. Data were log-transformed as this improved the normality distribution of the data, although in all dogs and the 2 subgroups the distributions remained significantly different (P <.
Calculations indicate that the original target of 80 dogs (40 in each group) should provide 80% power to demonstrate a significant benefit of benazepril on prolonging renal survival time with the treatment effect sizes observed in the subgroups of dogs with UPC > 0. 5 or UPC > 0. 5 and plasma creatinine ≤440 lmol/L. These subgroups are the optimal target for therapy with ACEIs, that is, mild to moderate CKD with proteinuria. 14 Although it would be ideal to conduct a new study with a larger number of dogs, a new placebo-controlled survival study with ACEIs in dogs with CKD might be difficult because ACEIs have become standard of care in proteinuric dogs with CKD. 14  Second, blood pressure was not measured routinely, resulting in data that were too sparse to analyze. As a consequence, we could not evaluate the possible antihypertensive effect of benazepril or study the association between blood pressure and outcomes.
Acknowledgments The clinical work was conducted in France,  Italy, Spain , and  United Kingdom , and the data were analyzed in Switzerland. The study was supported by  Novartis Animal Health , now owned by  Elanco Animal Health , a division of  Eli-Lilly company. We thank the other investigators including  Roberto Santilli  (Italy) and  Sarah Stonton  ( United Kingdom ) for managing clinical cases, and the following colleagues from former  Novartis Animal Health  for assistance managing or monitoring the study:  Laure Baduel ,  Fabienne Brovedani , and  Philippe Gruet (France)  and  Debbie Alexander ,  Cathy Brockman , and  Karen Quine  ( United Kingdom ). Preliminary results from the study were presented at the 1999 European College of Veterinary Internal Medicine meeting.
Read Mapping and SNP/Large Deletion Detection Read mapping and SNP detection were performed using the Snippy v2. 6 pipeline  (Seemann 2015). The Burrows-Wheeler Aligner (BWA) v0. 7. 12  (Li and Durbin 2009)  was used with default parameters to map clipped read-pairs to two M. ulcerans Agy99 reference genomes: the M. ulcerans Agy99 bacterial chromosome (Genbank: CP000325) and the M. ulcerans pMUM001 plasmid (Genbank: BX649209). Due to the unreliability of read mapping in mobile repetitive regions all ISE elements (IS2404 and IS2606) and all (plasmid-encoded) polyketide synthase genes were masked in these reference genomes (397 kb/5. 63 Mb-7% of Agy99, 118 kb/174 kb-67% of pMUM001). After read mapping to M. ulcerans Agy99 and pMUM001, average read depths were determined with SAMtools v1. 2  (Li et al.
Because the algorithm is stochastic, the analysis was run in 20 replicates for each value of K as to increase the probability of finding the posterior optimal clustering with that specific value of K. QGIS v. 2. 10 (Quantum_GIS 2012) was used to generate the figures on the geographical distribution of African M. ulcerans. The residence of BU patients at the time of their clinical visit was represented as points. In the case where residence information was missing, we used the location of the hospital supplying the sample. The administrative borders of countries were obtained from the Global Administrative Unit Layers dataset of FAO.
Discrete Phylogeographic Analysis To assess the geospatial distribution of African M. ulcerans through time, an additional BEAST2 analysis was performed. In this analysis, the posterior probability distribution of the location state (geographic region) of each node in the tree was inferred, in addition to the parameters described above (tree topology, evolutionary, and demographic model). Sampled isolates were associated with fixed discrete location states and a discrete BSSVS geospatial model  (Lemey et al. 2009 ) was subsequently used to reconstruct the ancestral location states of internal nodes in the tree from these isolate regions. To prevent loss of the signal in the data by considering too many discrete regions compared with the number of isolates, we limited the amount of discrete regions by merging neighboring countries (similarly as carried out in  Comas et al.
Acknowledgments K. V. was supported by a PhD-grant of the  Flemish Interuniversity Council-University Development Cooperation (Belgium). B. d. J. and C. M. were supported by the  European Research Council-INTERRUPTB  starting grant (no. 311725 ). T. P. S. was supported by a fellowship from the  National Health and Medical Research Council of Australia  ( 1105525 ). Funding for this work was provided by the  Department of Economy, Science and Innovation of the Flemish Government , the  Stop Buruli Consortium  supported by the  UBS Optimus Foundation , and the  Fund for Scientific Research Flanders (Belgium)  ( FWO  grant  no. G. 0321. 07N ). The computational resources used in this work were provided by the  HPC core facility CalcUA  and  VSC  ( Flemish Supercomputer Center) , funded by the  University of Antwerp , the  Hercules Foundation  and the  Flemish Government-department EWI.
HEV prevalence in farmed pigs It is crucial to know the prevalence of HEV on pig farms so as to be able to assess the health situation of the pig population and thus the risk to public health. We counted 86 studies (from 43 different countries) addressing HEV prevalence in farmed pigs. These studies are summarised in Additional file 1  [5, 11-21, 24, 47, 57, 66, 70-73, 79-139]. Various methods were used for data collection: samples were collected from slaughterhouses, randomlyselected or specifically-selected farms, or from serum/ faeces/organ banks. Some studies were conducted at a given point in time, leading to an instantaneous prevalence estimate, whereas others were retrospective and estimated the prevalence from sera collected over a given period of time. The number of farms varied from 1 to 2 001; the number of samples from 40 to 6 565.
Quantitative data on HEV transmission The persistence of a virus on farms is linked to (1) the intrinsic ability of the virus to remain in the animals' environment, (2) the possibility of regular reintroductions of the virus onto farms and (3) the ability of the virus to survive and spread in the population. This last criterion can be studied through the basic reproduction number (R0) of the virus, which measures the number of secondary infections due to one infectious pig during its entire shedding period in a fully susceptible population. The higher the basic reproduction number, the easier it is for the virus to spread and the greater its ability to stay within the population. Using a large-scale seroprevalence survey dataset from Japanese pig farms, Satou and Nishiura estimated the HEV R0 between 4.
7 times higher in pigs co-infected with PRRSV (direct transmission rate = 0. 70 [1. 18. 10 -3 -3. 67]). Direct transmission therefore plays a more important role in HEV transmission when animals were co-infected and reflecting the increased quantity of virus particles shed  [36]. The indirect transmission rate, considered to be the average number of animals that could be infected by a single genome equivalent present in the pen environment, was estimated at 6. 59. 10 -6 g/ GE/day [1. 43. 10 -10 -1. 27. 10 -4 ], i. e. 3. 3 times higher with co-infection than without. In other words, 3. 3 times fewer virus particles were required to infect a co-infected animal than an HEV-only infected animal. The impact of maternally-derived antibodies on HEV transmission was also assessed by modelling field-based longitudinal data on HEV dynamics of infection  [32].
Bacteriological study Nocardia spp were cultured from clinical specimens and all strains were identified using 16 s rRNA PCR. The sequences obtained were compared with those stored in GenBank. Strains had to have >99% sequence similarity with one species only. Sequencing of the 65-kDa heat shock protein gene (hsp65) was also performed to separate similar species, as described previously. 17 ntibiotic susceptibility was tested by disk diffusion method. Only TMP-SMX and carbapenem susceptibility were recorded; these are the antibiotics most commonly used when nocardiosis is suspected. 7.
, 2017). Compared with controls, stressed individuals showed an increased level of microbial diversity, an Abbreviations: ANOSIM, Analysis of similarities; ANOVA, Analysis of the variance; COX-2, Cyclooxygenase 2; CSS, Cumulative sum scaling; DM, dry matter; HPA, hypothalamic pituitary adrenal axe; INRA, National Institute for Agricultural Research; IFGM, interferon-γ; KEGG, Kyoto Encyclopedia of Genes and Genomes; NMDS, Non-Parametric Multidimensional Scaling; OUT, Operational Taxonomic Unit; PCoA, Principal component analysis; QIIME, Quantitative insights into microbial ecology; qPCR, real time quantitative PCR; RDP, Ribosomal Database Project; SAM, sympato-adrenomedullary axe; SCFA, short chain fatty acids; sPLS-DA, sparse partial least squares discriminant analysis; 5-HT, 5-hydroxytryptamine.
Daily intake of hay per pen was measured and recorded as the total amount of fed provided each day minus the hay left, either in the hay net or on the floor of the stall. Similarly, the concentrate leftovers were measured and recorded daily from the feeders in each pen. However, because foals were housed in pairs within a pen, these data can only provide an estimation of the individually daily intake. Since preliminary studies conducted in animals infected by gastrointestinal helminth reported significant changes in the composition of the gut microbiota  (Walk et al. , 2010; Li et al. , 2012; Wu et al. , 2012; Osborne et al. , 2014) , fresh fecal samples for parasitic coprology analysis (performed on 5 g of feces diluted in 70 mL of NaCl solution with density of 1. 2; sensitivity of 50 eggs/g) were obtained at -30, 0, and 30 days post-weaning.
The single-copy gene was the interferon-γ (IFGM). The forward PCR primer for the IFGM was IFGMF [5 ′ -ACGCAAGAAACCCAGATGTAGG-3 ′ ], and the reverse primer was IFGMR [5 ′ -AGATATCCAGGAAAA GAGGCCC-3 ′ ]. These specific reverse and forward primers were used at a final concentration of 700 nM. All PCR primers were designed using ABI Primer Express software (PE Applied Biosystems, Courtaboeuf, France). The gDNA samples (2 µL of gDNA 10 ng/µL) were mixed with 1 × SYBR Green Master Mix (Roche, Mannhein, Germany) and 3 µL of the specific reverse and forward primers in a final volume of 10 µL. Tubes containing 20-10-5-2. 5-1. 2-0. 6-0. 3 ng/µL of a reference horse pooled DNA were included in each PCR run as a standard curve. The same standard curve was used for all PCR runs to evaluate the PCR efficiency of telomere and IFGM amplification.
All PCRs were carried out on a Roche Lightcycler 480 real-time PCR machine with 384-tube capacity (Roche Diagnostics Corporation, Indianapolis, IN). Cycling conditions were 95 • C for 10 min, then 40 cycles of 95 • C for 10 s and 60 • C for 6 s and 72 • C for 10 s. For each sample and each gene, qPCR runs were performed in triplicate (in accordance with the manufacturer's protocol). In order to quantify and normalize the expression data, we used the Ct method. Values reported correspond to Ct between Ct value of telomeric region (T) amplification and IFGM (S) amplification for each sample relative to a control sample, here the value at day -73 for each weaning method. T/S value was calculated with GenEx software (GenEx 6. 1, bioMCC, Germany). We used the amplification efficiency calculated by each standard curve on each plate.
py command in QIIME  (Navas-Molina et al. , 2013). We applied a default base call Phred threshold of 20, allowing maximum three low-quality base calls before truncating a read, including only reads with >75% consecutive high-quality base calls, and excluding reads with ambiguous (N) base calls  (Navas-Molina et al. , 2013). After the quality-filtering step, an average of 27,280 sequences per sample were obtained, with a mean length of 441 ± 15 bp. Subsequently, the sequences were clustered into OTUs against the GreenGenes database (release 2013-08: gg_13_8_otus; DeSantis et al. , 2006) by using the uclust  (Edgar, 2010)  method at a 97% similarity cutoff. The filtering of chimeric OTUs was performed by using Usearch  (Edgar et al. , 2011)  against the GreenGenes reference alignment  (DeSantis et al.
, 2006). A phylogenic tree was generated from the filtered alignment using FastTree  (Price et al. , 2010). Singletons were discarded from the dataset to minimize the effect of spurious, low abundance sequences using the "filter_otus_from_otu_table. py" script. To confirm the annotation, the resulting OTU representative sequences were then searched against the Ribosomal Database Project naïve Bayesian classifier (RDP 10 database, version 6,  Cole et al. , 2009)  database, using the online program SEQMATCH (http://rdp. cme. msu. edu/seqmatch/seqmatch_ intro. jsp). The sequences that were not assigned to the Bacteria kingdom were filtered out for the rest of the analysis. Finally, consensus taxonomy was provided for each OTU based on the taxonomic assignment of individual reads using GreenGenes and RDP.
Using OTU abundance and the corresponding taxonomic classifications, feature abundance matrices were calculated at different taxonomic levels, representing OTUs and taxa abundance per sample. The "Phyloseq" R package  (McMurdie and Holmes, 2013)  was used for the detailed downstream analysis on abundance matrix. OTU counts per sample and OTU taxonomical assignments are available in Table  S2. The 16S rRNA amplicon gene sequences described in the study were deposited into the NCBI database (http://www. ncbi. nlm. nih. gov/). under GenBank accession numbers KY662487 to KY670589. The bioproject described in this paper belongs to the BioProject PRJNA375964. The corresponding BioSamples accession numbers were SAMN06348792 to SAMN06348995. Species richness (Observed, Chao1;  Chao, 1984)  and αdiversity measurements  (Shannon, 1997)  were calculated using the "Phyloseq" R package  (McMurdie and Holmes, 2013 ).
Functional Metagenomic Predictions The functional prediction for the 16S rRNA marker gene sequences was done using PICRUSt  (Langille et al. , 2013). After excluding the OTU unknown from the GreenGenes reference database and normalizing by 16S rRNA gene copy number, functional metagenomes for each sample were predicted from the Kyoto Encyclopedia of Genes and Genomes (KEGG) catalog and collapsed to a specified KEGG level. We used Wilcoxon rank-sum test with Benjamini-Hochberg multiple test correction to evaluate pathway-level enrichments between groups. A q < 0. 05 was considered as significant.
Network Inference at the Genus Level Networks at the genus level were inferred at different time points. In order to prevent the compositional effects bias typical of the classical correlations methods  (Aitchison, 1982; Pawlowsky-Glahn and Buccianti, 2011) , we calculated the correlations among OTUs or genera using the REBECCA method  (Ban et al. , 2015) , which identifies significant co-occurrence patterns by finding sparse solutions to a system with a deficient rank. This method constructs the system using log ratios of count data and solves the system using the l 1 -norm shrinkage method. In the network, every node represents one genus, whereas every edge connecting two nodes represents a significant interaction. We used the "iGraph" R package to visualize the network. As defined by  Ramayo-Caldas et al.