dataesr/scientific-paragraphs-categorization huggingface dataset:
RNA-seq dataset collection and preprocessing The Illumina sequencing data (raw reads) were downloaded from the FTP server at the Duke University facility and verified for files integrity with MD5 checksum. A total of 22 to 32 million reads was obtained per each replicate sample of adult worms and 11 to 13 million reads per each replicate sample of schistosomula. Quality check of reads was with FastQC (www. bioinformatics. babraham. ac. uk/projects/fastqc/), and Trimmomatic  [36]  was used to trim Illumina adapters and to filter out reads with low quality values using the following parameters: MAXINFO with parameters 50:0. 05, HEADCROP of 28 nucleotides, a LEADING and TRAIL-ING value of 5, and minimum read length of 30 nucleotides.
usp. br. Read counting was done with cuffquant using the Tophat2 BAM files as input, and a metagenes transcriptome  [39]  as reference; this metagenes transcriptome reference gtf file is available at http://verjolab. usp. br. Statistical significance analysis of differential expression was obtained by using cuffdiff  [40]  with cuffquant counting as input and the default parameters, which imply the pooled dispersion method and the geometric library normalization method. A q-value � 0. 05 was used as significance threshold. The metagenes transcriptome reference takes into account the evidence from public RNAseq data either that two or more genomic neighbor Smp_nnnnnn predicted genes do encode fragments of the same protein and should be merged, or that in a given genomic locus a novel transcript was assembled from the public RNA-seq data  [39].
In the two cases the corresponding transcript was named "SmVG_xxxxxx", where xxxxxx stands for the XLOC_xxxxxx identifier number generated for that locus during the assembly  [39]. In the case that one or more Smp genes comprise the SmVG_xxxxxx metagene, it was further annotated as SmVG_xxxxxx: Smp_nnnnnn to indicate the corresponding Smp_nnnnnn genes that comprise that SmVG_xxxxxx; the expression value of that metagene was assigned to all SmVG_xxxxxx: Smp_nnnnnn genes belonging to the same SmVG_xxxxxx metagene. Sequence and genomic coordinates information for all SmVG_xxxxxx genes is available at the metagenes transcriptome reference gtf file mentioned above. The second pipeline employed Kallisto  [41] , which uses a pseudo-alignment approach to map the reads against the genome. The metagenes transcriptome was again used as reference.
RT-qPCR validation of DEGs For quantitative RT-PCR, complementary DNAs were obtained by reverse transcription (RT) of 100 ng schistosomula or adult worms total RNA using SuperScript III Reverse Transcriptase (Invitrogen) and random hexamer primers in a 20 μL volume, according to the manufacturer's recommendations. The resulting cDNA was diluted 8-fold in water and qPCR amplification was done with 2. 5 μL of diluted cDNA in a total volume of 10 μL using SYBR Green Master Mix (Life Technologies) and specific primer pairs (S1 Table) designed for S. mansoni genes by Primer3 online software. The Light cycle 480 II (Roche) qPCR was used. The results were analyzed by comparative Ct method and the statistical significance was calculated with the t-test. To find adequate normalizer genes for qPCR, we looked for evidence of genes with nondetectable changes in expression upon GSK343 treatment in the RNA-Seq data.
Protein database searches and analyses Raw data were processed using MaxQuant software version 1. 5. 2. 8 and the embedded database search engine Andromeda  [46]. A custom reference Proteins Database was used (http:// verjolab. usp. br); this fasta file contains the >Smp_nnnnnn protein sequences  [37]  from Ensembl (http://metazoa. ensembl. org/Schistosoma_mansoni/Info/Index) plus the 212 novel protein sequences (>cnnnn-gn-in) described by Anderson et al. [15]  and the micro-exon genes (>MEGnnnnnn and >GUnnnnnn sequences) described by DeMarco et al. [47]. The MS/MS spectra were searched against this custom reference database with the addition of common contaminants, with an MS accuracy of 4. 5 ppm and 0. 5 Da for MS/MS. Cysteine carbamidomethylation (57. 021 Da) was set as the fixed modification, and two missed cleavages for trypsin.
Methionine oxidation (15. 994 Da) and protein N-terminal acetylation (42. 010 Da) were set as variable modifications. Proteins and peptides were accepted at FDR less than 1%. All raw data have been submitted to the PRIDE archive  [48, 49]. Label-free quantitation (LFQ) was performed using the MaxQuant software with the "match between runs" feature activated. Protein LFQ intensity of each of the three biological replicates of treated and untreated samples were used for further statistical analyses. Proteins with valid values in at least two replicates of each biological condition were kept in the analyses. Exclusive proteins were identified in at least two biological replicates of one condition and in none of the other. Significantly regulated proteins were determined using the Welch's t-test using the Perseus v.
Considering that the oviposition pathways in S. mansoni are not annotated in the GO database, and that correct eggshell formation is essential for embryonic cell differentiation and development, we searched for genes described in the literature as related to egg formation  [15, 57]. Fig  13C  shows the expression levels of genes encoding four eggshell proteins, two tyrosinases, one serine/threonine kinase, all involved in egg production, and nanos-1 and -2, related to egg production and cell differentiation  [58, 59] ; the list of these genes with Smp ID biological replicates (columns) of female (A) and male (B) adult worm samples, either for controls or for treated parasites, as indicated at the top of the heatmaps. Parasites were exposed for 48 h in vitro to vehicle (control) or to 20 μM GSK343.
Acknowledgments We thank  Dr. Karina Saraiva ,  FIOCRUZ ,  Recife , and  Beatriz Mauricio  and  Dr. Carlos Jared ,  Instituto Butantan ,  São Paulo , for access to the scanning electron microscopy facilities in their laboratories. We acknowledge  Dr. Eliana Nakano  and  Patricia Aoki Miyasato ,  Instituto Butantan ,  São Paulo , and  Dr. Pedro Luiz Silva Pinto ,  Instituto Adolfo Lutz ,  São Paulo , for maintaining the parasite life cycle.
This work was supported in part by a grant from the  European Union 's  Seventh Framework Programme  under grant agreement no. 602080  to SVA and in part by the  Coordenacão de Aperfeicoamento de Pessoal de Nı ´vel Superior (CAPES) ,  Brasil  ( Finance Code 001 ). Fellowships from  Fundacão de Amparo à Pesquisa do Estado de São Paulo (FAPESP)  have supported EJRV and  ASAP  ( FAPESP 2014/24560-8  and  2016/10046-6 , respectively). LFdS and DAMV were supported by fellowships from  Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq). SVA was also supported by institutional funds from  Fundacão Butantan. SVA and JCS are recipients of established investigator fellowship awards from  CNPq, Brasil. GP is supported by  FAPESP  ( 2014/ 06863-3 ). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Acknowledgements. The authors would like to thank the farmers who accepted to participate in the study, the undergraduate students of the  Universidad San Francisco de Quito (USFQ)  for the collection of bovine blood in the  Galapagos Islands and the laboratory technicians from Agencia de Regulación y Control de la Bioseguridad y Cuarentena para Galápagos (ABG)  and  Centro de Transferencia y Desarrollo de Tecnologías (CTT)  from the  USFQ. Financial support. This work was funded by the  Universidad San Francisco de Quito (USFQ) ,  Quito , Ecuador and by the  Agence nationale de sécurité sanitaire de  l'alimentation, de l'environnement et du travail (ANSES), Maisons-Alfort, France.
farcinica and N. nova being the most frequent species  [5]. However, no data currently exists on the phylogenetic relationships between the indigenous N. brasiliensis strains of tropical origin and native strains isolated in France. Routine genus/species identification of Nocardia was based on macroscopic, microscopic, and biochemical characteristics. The methods described by Boiron et al. [6]  were used to determine the decomposition of adenine, casein, hypoxanthine, tyrosine, and xanthine. In addition to the phenotype-based methods, species-level identification is mainly genetically based, nowadays. Classically, 16S rRNA (rrs) gene sequencing is generally used for the specieslevel identification  [7, 8] , but it fails to discriminate among some species of Nocardia because it does not have enough polymorphism to differentiate them at the species level.
Databases of 8 different institutions based in different European countries (Austria, France, Italy, Netherlands, Portugal, Spain, Switzerland and United Kingdom) were retrospectively searched for consecutive cases of canine nodal lymphoma within a six year timeframe (2010-2015). Institutions enrolled were all referral centers for veterinary oncology, all located in academia, except one private referral center. Criteria for inclusion included a final diagnosis of lymphoma, based on results of clinical and laboratory data (variably including cytology, immunophenotyping or histopathology, depending on institution) and the availability of signalment data. As a control, the same institution provided a list of consecutive canine cases, from the same hospital databases with a diagnosis other than lymphoma, in the same timeframe.
These control groups were used to compare the prevalence for each breed in the lymphoma group, in order to correct for other possible sources of variation, such as high breed popularity in one area. The number of control cases varied among institutions but in all cases they exceeded the number of lymphoma cases (generally at least 10 fold higher). Data from dogs with lymphoma were analysed after matching with the appropriate control from the same geographic area in order to correct results for the breed prevalence among the whole canine population. When immunophenotype and lymphoma subtype were available these data were also recorded. Since diagnostic algorithms and classification schemes differ greatly among institutions, the subtypes recognized were grouped into 3 main groups: 1) B-cell lymphoma (all subtypes), 2) T-cell lymphoma-high grade, 3) T-zone lymphoma/T indolent lymphoma (identification based on histopathology, cytology or immunophenotyping).
Statistical analysis The 9 most represented breeds in the whole lymphoma database were considered for statistical purposes. The prevalence of different breeds in the databases from different countries varied but these 9 selected breeds were always among the 12 most common breeds for each country included in the study. We limited the analysis to these breeds in order to make comparisons between different institutions consistent. Using country-matched control groups obtained from internal databases of each institution, odds ratio (OR) analysis was performed to quantify the association, if any, between lymphoma predisposition and breed within each country. ORs were expressed with relative 95% confidence interval. The differences between control and lymphoma groups were evaluated using Chi-square test.
Golden retrievers were found to be mildly predisposed just in the UK (OR = 2. 16; confidence limit = 1. 34-3. 49) while no predisposition was recorded in other countries. For analysis of lymphoma subtypes, all countries were grouped together as the number of cases having a lymphoma subtype classification was too low to perform analysis by countries. Immunophenotype and cyto-histotype data were available in 1446 dogs and were used to categorize cases into the above mentioned main groups: B-cell lymphoma (n = 950; 65,7%), T-cell lymphoma-high grade (n = 396; 27,4%), and T-zone lymphoma/T indolent lymphoma (n = 100; 6,9%). No statistical differences were found in the prevalence of lymphoma subtypes between   2. From our results, it emerges that boxer and Labrador retriever were predisposed to develop high-grade T-cell lymphomas (respectively 10.
The lack of a common classification in different subtypes could affect the meaning of our results regarding possible breed predispositions to B cell lymphomas and T high grade lymphomas. However, it could be considered more valid for T zone lymphomas, as they represent a more homogenous lymphoma subtype with well-recognized biological behaviour. More specific studies could be performed by using a standard diagnostic approach (including cytology, histopathology, and immunophenotyping in all cases) and a common unique classification scheme in order to confirm the data derived from this retrospective analysis and to better identify breed-specific predilections that could be then used for possible genetic studies. The second limit is due to the choice of control cases. Non-lymphoma cases were selected from the same database used for the extraction of lymphoma cases, in order to correct results for the breed distribution, which is highly variable among countries.
These databases included diseased dogs presented at clinical examination or tissue samples sent for laboratory tests (cytology, flow cytometry). The breed prevalence in these databases is not necessarily representative of the whole canine population in each country. However, we considered it the most reliable control group available, since breed data on overall canine populations were not available for all countries, and are not consistent between European countries and areas. Bias could occur as all the institutions derive their database solely from diseased animals, and breed distribution may vary according to different breed predisposition to other diseases. However, due to the high number of control cases and the variety of possible diseases included, we considered this as a minor bias for the breed analyzed.
To quantify cellular proliferation, MTS assays (Promega, Fitchburg WI) were performed by adding 20 μL of MTS solution to each well and incubating at 37 °C for 1 to 2 h. The optical density of each well was acquired with a spectrophotometric plate reader (FLUOstar Omega, BMG Labtech, Germany) at a wavelength of 490 nm in accordance with the supplier's instructions. Experiments were performed in 6 replicates. The results for each treatment were reported as the mean of the percent surviving cells ± SEM (standard error of the mean). IC50 values were obtained using GraphPad Prism™ software, version 6. 1 (Sun Microsystems, Palo Alto, CA, USA).
Somatic mutations in candidate genes Genomic DNA sequencing was performed on six genes that frequently harbour recurrent somatic mutations in human melanoma subtypes: Braf, Nras, Gna11, Gnaq, Mitf and p53 (Additional file 2). The genes were sequenced in the canine tissue-derived genomic DNA isolated from the Dog_1 primitive tumor, the Dog_1 engrafted tumor and Ocr_OCMM1X cells, as well from the Dog_2 primitive tumor, and the Dog_2 engrafted tumor, and the primary derived and Ocr_OCMM2X cells. Each gene was sequenced from the genomic DNA, with the Sanger method, as previously described  [17]. Data were analyzed with DNA Sequencing Analysis software v5. 2 (Applied Biosystems). The presence of somatic mutations was assessed by comparing DNA sequences from the sample to the CanFam3 reference dog sequence using Seqscape software v2.
Chromosome alterations An oligo array comparative genomic hybridization (CGH) analysis was carried out on the DNA previously extracted from Dog_1 and Dog_2, using pan-genomic arrays of 60-mer oligonucleotides, comprising a total of 180,000 probes (Canine Genome 4 × 180 K SurePrint G3 Canine CGH Microarray 025522_D_F_20130822; Agilent Technologies, Santa Clara, CA). The arrays were scanned on an Agilent G2505C scanner, the images were quantified using Agilent Feature Extraction software (vA. 8. 5. 1. 1), and the acquired images were analyzed using Agilent Genomic Workbench software (V7. 0. 4. 0). The canine genome build CanFam3. 1 was used for data analysis. Copy number aberrations (CNA) were identified using aberration detection method 2 (ADM2) segmentation and the R script DNA library. A CNA was called as either a gain or deletion according to the log2 ratio distribution.
Probes on chromosomes X or Y were not analyzed because of sex mismatching. Regions of heterozygous gain (amplification) were defined as having a log2 ratio > + 0. 25, while regions suggestive of heterozygous loss (deletion) were defined as having a log2 ratio < -0. 25. (The threshold was fixed at 6. 0). The array data presented here are publicly accessible through the Gene Expression Omnibus (GEO) Series, accession number GSE88724.
Statistical analysis Results are expressed as the mean ± SEM, and statistical analyses were performed using GraphPad Prism® and StatView® 5. 0 software (SAS, Cary, NC). Data were analyzed using ANOVA followed by Fisher's PLSD post hoc test with a significance level of P < 0. 05 (*p < 0. 05; **p < 0. 01; ***p < 0. 005; ****p < 0. 001).
Acknowledgements We thank  Jean-Pierre Decavel  and  Thierry Chassat  from  PLETHA , the  Institut Pasteur de Lille Animal Facility , and  Marie-Hélène Gevaert  from the histopathological facility core,  Henri Warembour School of Medicine , for technical assistance. We are also thankful to the pathologists who contributed to the diagnosis and analysis of the tumor samples ( Dr. Ingrid Bemelmans ,  Dr. Marine Carlus  and  Dr. Quentin Pascal ). We would also like to thank  Céline Villenet  ( Functional Genomic Platform, Univ Lille, F-59000 Lille France ) for the preparation and production of the microarrays.
RNA Seq Data Analyses The sequences were aligned to the L. interrogans serovar Manilae L495 obtained from http://www. genoscope. cns. fr. The reference genome was indexed using the bowtie2-index. The reads were pre-processed to remove the first and last base, and filtered for quality using scripts written in PERL. The reads were aligned to the reference genome using Tophat  (Trapnell et al. , 2009). The aligned bam files were processed using htseq-count  (Anders et al. , 2015) , and the raw counts were processed using DESeq2 package in R  (Love et al. , 2014). The downstream analysis and plotting was done using home brew scripts written in R (R Archive Network). R package pheatmap was employed for the heatmap where the values were scaled according to row to depict how the gene expression for the specific gene changed across the conditions.
Quantitative Reverse Transcription PCR (RT-qPCR) for Target Gene Identification and RNA Seq Data Validation Leptospira WT and lvr mutants were cultured till mid-log and late-log phases. RNA was extracted for two biological replicates using the TRIzol method (Invitrogen TM , Thermo Fisher Scientific, Waltham, MA, USA). For studying expression of lvr genes in vivo, total RNA was extracted from hamster blood samples (n = 2) stored in TRIzol, as per the manufacturer's instructions (Invitrogen TM , Thermo Fisher Scientific, Waltham, MA, USA). Ambion R TURBO DNA-free TM DNase treatment kit (Applied Biosystems Inc, Foster City, CA, USA) was employed to remove contaminating DNA from RNA preparations. The concentration of RNA was determined using a NanoDrop TM 2000 spectrophotometer system (Thermo Fisher Scientific, Waltham, MA, USA).
The High capacity cDNA reverse transcription kit (Applied Biosystems Inc, Foster City, CA, USA) was employed for conversion of total RNA to single-stranded cDNA. The primers designed for target gene identification and RNA-seq data validation are listed in Table  S2. The qPCR was carried out on 7500 fast real-time PCR (Applied Biosystems Inc, Foster City, CA, USA) using iQ TM SYBR R Green supermix (Bio-rad, Hercules, CA, USA) according to manufacturer's instructions. The thermal cycling conditions used in the qPCR were 95 • C for 3 min, followed by 40 cycles of 95 • C for 5 s and 60 • C for 1 min. The specificity of the SYBR green PCR signal was confirmed by melt curve analysis. In RT-qPCR experiments, flaA gene (flagellar apparatus gene) was used as an endogenous control and L. interrogans WT was employed as reference strain.
Molecular Evolution Analyses Multiple BLAST searches were performed against the NCBI database for homologs of Lvr in other bacterial genomes. Two Lvr homologs in Mycobacterium were employed to root the phylogeny. A set of 67 unique amino acid sequences was assembled and they were aligned using SATé-II  (Liu et al. , 2012)  with MAFFT as aligner, MUSCLE as merger, and RAxML as tree estimator under WAG model. The robustness of branching topologies was estimated with 1,000 maximum likelihood searches of bootstrapped sequence data using PhyML  (Guindon et al. , 2010)  under the WAG model. Robustness of the topology was further confirmed with Bayesian analyses using MrBayes 3. 2  (Ronquist et al. , 2012). Bayesian phylogenetic analyses were performed using the Metropolis-coupled Markov chain Monte Carlo method (MCMCMC) under a mixed amino acid model by running for chains with 10,000,000 generations.
Phosphotransfer Assays Purified Lvr proteins (1 mg/mL) in desalting buffer (25 mM Tris-HCl, 250 mM NaCl, 10 mM MgCl2, pH 8. 5) were incubated with 1 mM ATP and 10 mCi of [γ 33 P] ATP (3000 Ci/mmol, ARC) at room temperature for 30 mins. Phosphotransfer reactions were stopped by mixing the samples with Laemmli buffer. Samples were then subjected to gel electrophoresis (SDS-PAGE), and visualized by autoradiography (Hyperfilm ECL) after 1-3 days of exposure. Densitometry analysis was performed using the software ImageJ.
To validate these gene expression data, we performed quantitative RT-PCR (qRT-PCR) for 17 randomly selected genes from the panel of differentially expressed genes (log ≥ 2-fold; adjusted p-value ≤ 0. 05). There was a strong agreement between our RNA-Seq and qRT-PCR datasets with a correlation coefficient (R 2 ) of 0. 9119 across the entire panel (Figure  3B ). We employed hierarchical clustering of lvr gene expression profiles to uncover biologically relevant expression signatures (Figure  3C ). The effect of lvr gene inactivation on transcript levels indicated a positive role for Lvr in clusters 1, 4, and 5, and a negative role in clusters 2 and 3 (Figure  3D ). To evaluate the potential biological role of the differentially expressed genes we assessed the cluster of orthologous genes (COG) classification system (Figure  3E , Tables  S5A-F ).
Data Availability RNA-Seq reads are available in the NCBI Sequence Read Archive, under accession numbers L. interrogans Manilae wild type (I: GSM2085874, II: GSM2085875), lvrA/B mutant (I: GSM2085878, II: GSM2085879), lvrB mutant (I: GSM2085876, II: GSM2085877). The genome sequencing data for lvrA/B and lvrB mutants have been deposited in NCBI under accession numbers SRR5956150 and SRR5956154 respectively.
Biological Assessment of the Procedure and Statistical Procedures To evaluate the biological relevance of the GCM assay in African Grey Parrot droppings, the relationship between individual dropping GCM concentration and HLR was investigated using the samples collected during the second step. To assess the robustness of the method, the impact of sex and dropping masses on GCM levels were also considered. Data analysis was performed using SAS 9. 4 software Copyright © 2002-2012 by SAS Institute Inc. , Cary, NC, USA. The significance threshold was classically fixed at 5%. Data analysis was thus carried out using a Student t test with the help of proc t test procedure or Wilcoxon Two-Sample Test using npar1way procedure in SAS 9. 4 software depending on normality and variances (homogeneity of variances will be verified using Fisher test using t test procedure also).