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May 31st to June 2nd 2017
PPGBIOQPROGRAMA DE PÓS GRADUAÇÃO
EM BIOQUÍMICA (UFRN)
Founding:
ABSTRACTS
Contents
Program 02
Oral contribution 03
Poster presentation 07
Authors 18
PROGRAM
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14:00 MANYUAN LONG New Genes Drive Phenotypic Evolution by Changing Gene Expression Networks15:00 ADRIÃO NETO Artificial Neural Networks and Deep Learning
16:15 SANDRO SOUZA Genome-wide identification of putative tumor antigens 17:00 SEVERINE AFFELDT Causal analysis of the expansion of 'dangerous' gene families in vertebrates
09:30 CLOVIS REIS - 11.000 Synonyms! But not so much... LUCAS VISCARDI - Eukaryotic Evolutionary Network of Neurotransmitters 10:15 IGOR POLIKARPOV Structural Mol. Biol. and its Applications in Bioenergy, Enzymatic Catalysis and Synthetic Biol.11:00 RITA ALMEIDA Transcriptograms for genome wide gene expression analysis
14:00 HERVÉ ISAMBERT Learning causal networks from multivariate information in genomic data15:00 RODRIGO DALMOLIN Evolutionary rooting of biological systems
16:15 BENILTON CARVALHO Brazilian initiative on precision medicine: statistical perspectives17:00 POSTER SESSION
09:30 ADRIANO TORT New insights into the mechanisms of spatial coding by hippocampal neurons10:15 SIDARTA RIBEIRO REM sleep and plasticity11:00 LIMING LI Prion-mediated regulation in gene expression
PPGBIOQPROGRAMA DE PÓS GRADUAÇÃO
EM BIOQUÍMICA (UFRN)
Coffee Break
Coffee Break
Coffee Break
ORAL CONTRIBUTION
PPGBIOQPROGRAMA DE PÓS GRADUAÇÃO
EM BIOQUÍMICA (UFRN)
Coffee Break
4
Causal analysis of the expansion of 'dangerous' gene families in vertebrates
Severine Affeldt; Param Priya Singh; Giulia Malaguti; Herve Isambert
LIPADE Laboratory - University of Paris Descartes (France); Stanford University - Palo Alto(USA); AMOLF - Amsterdam (The Netherlands); CNRS - Institut Curie (France)
Vertebrate genomes present a striking expansion of gene families frequently implicated insevere genetic diseases such as cancer. We have found that this expansion of 'dangerous' genefamilies can be traced back to two rounds of whole genome duplication at the onset ofvertebrates about 500MY ago. Our analyses of the human protein coding genes reveal astrong correlation between the retention of duplicates from whole genome duplication (so-called 'ohnologs') and their susceptibility to dominant deleterious mutations. An alternativehypothesis frequently invoked to account for the biased retention of ohnologs is the 'dosage-balance' hypothesis, which posits that the ohnologs are retained as their interactions withprotein partners require to maintain balanced expression levels. Yet, we found that genesusceptibility to deleterious mutations is more relevant than dosage-balance for the retentionof ohnologs (Singh et al. 2012, 2014 & 2015). To go beyond correlations, we performedMediation analyses (Pearl 2001) to quantify the causal effects of many genomic properties(eg, essentiality, expression levels) on the retention of ohnologs. Our results confirm that theretention of human ohnologs is primarily caused by their susceptibility to deleteriousmutations. Yet, the Mediation analysis considers only three-variable models with a singlemediator Z, s.t. X --> Z --> Y & X --> Y. Hence, to quantify causal effects in more complexcausal models (Verny et al. 2017), we also extended the Mediation analysis to allow formultiple mediators. All in all, our results demonstrate that the retention of human ohnologs isa consequence of their susceptibility to deleterious mutations and the purifying selection inpost-whole-genome-duplication species. This work emphasizes the importance of advancestatistical approaches to quantify causal effects in multivariate analyses.
whole genome duplication, genetic disorders, mediation analysis, multivariate analysis
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11.000 Synonyms! But not so much...
Clovis Ferreira dos Reis, Andre Luis Fonseca Faustino, Rodrigo Juliani Siqueira Dalmolin,Sandro José de Souza
Federeal University of Rio Grande do Norte
Mutations and genetic recombination are the engine that allows an organism to adapt to anew and inhospitable environment. Molecular evolution studies tries to infer the mechanismsthrough which those mutations are selected or deleted from the populations over the time.Neutralism theory has divided research’s opinion since its proposal, having strong oppositionto the prevalent selectionism. All short-lived evolutionary experiments never had establish aconsensus, but now with the advent of Next-Generation Sequencing (NGS) and its massivesequencing possibility, long term experiments and resulting genome sequencing came to bepossible, giving another view over theme. Thus based on data from a long term evolutionexperiment (LTEE) made using 50,000 generations, among twelve populations of E. colibacteria, this work presents evidence that codon bias is another factor that must to beconsider when studing population fitness, natural selection and genome evolution over timein bacterial populations. Thereunto the relative adaptiveness index for a codon (w) wasremodeled to quantify how much the codon bias could induce positive selection oversynonymous mutation. Our findings suggests that synonyms mutations are correlated with theΔw, reducing fitness on negative values. This strategy show an alternative way to measurenot so clear influences over fitness, improving evolution background knowledge on LTEEexperiments.
Molecular Evolution, Codon Bias, long term evolution experiment, adaptiveness index,positive selection, synonymous mutation
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Eukaryotic Evolutionary Network of Neurotransmitters
Lucas Henriques Viscardi; Danilo Imparato; Maria Cátira Bortolini; Rodrigo JulianiDalmolin
Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do RioGrande do Sul, Departamento de genética; Programa de Pós-Graduação em Bioinformática,
Universidade Federal do Rio Grande do Norte, Centro de Biociências, Departamento deBioquímica
It has been proposed that the last common ancestor of all synapses, emerged right before theCnidarians. However, the presence of other neurotransmitters in a handful of taxonomieswithin eukaryotes rise the question of when the network of nervous system would be alreadyestablished in evolution. Here we searched for the origin of genes that orchestrate theevolution of human synapses and their interaction for five major neurotransmitters (GABA,Glutamate, Serotonin, Dopamine and Acetylcholine). Thereunto, we tracked down the originof each component of the gene/protein interaction network following the phylogenetic tree,searching for orthologues of species available in STRING database. Important correlationswere observed in respect to the origin of the orthologous and their bias to accumulatemutations, and the major peak events regarding gene arising through eukaryotic evolutionarytree. Many genes in our set were already present in the common ancestral of all eukaryotes,but only Glutamatergic system is represented by essential receptors that emerged before thePorifera. Importantly, genes which carry more deleterious polymorphisms according to ourpredictions arose in the branch of the Euglenozoa, indicating that associations with Calcium-voltage channel and psychiatric disorders are probably consequences of damages inprimordial systems established around 1,7 billion years ago. Our results also suggest that thebackground for human reward system, was probably stablished at the common ancestor ofCnidarians, corroborating previous studies. Still, genes emerging late in evolution ofsynapses are significantly more plastic and also expressed in derived brain tissues, likeprefrontal cortex. Curiously, plasticity correlates neither with conservation or number ofpolymorphisms in our data, therefore neurotransmitter genes probably did not pass throughrelaxation of selective constraint after duplication events during the evolution of eukaryotes.
Neurotransmitters, Evolution, Eukaryotes
POSTER PRESENTATION
PPGBIOQPROGRAMA DE PÓS GRADUAÇÃO
EM BIOQUÍMICA (UFRN)
Coffee Break
8
R-Peridot: A Dynamic, Expansible and User Friendly Tool For Differential ExpressionAnalysis of RNA-Seq and Gene Ontology
ALVES SOBRINHO, P. A.; MARTINS, D. L.; FAUSTINO, A. L. F.; SOUZA, S. J.;SOUZA, J. E. S.;
Universidade Federal do Rio Grande do Norte
Several software are available for the analysis of RNA-Seq data, each using several statisticalmethods, and analyzing differential expression under different conditions for each gene.However, they can generate different results and many researchers have presented difficultiesto use them because of high learning curve, requiring concepts of distinct areas such asstatistics and programming languages, mainly because these concepts are not present in thecurrent academic curriculum of most courses on life and health sciences. In light of thesedifficulties faced by many researchers, R-Peridot was developed. It is a tool that makes use ofdeployed packages developed in the Java and R programming languages, to allow theanalysis of RNA-Seq data using parallel processing, with an intuitive graphical user interface.R-Peridot makes an analysis of the input data given by the user through the R packagesDESeq, DESeq2, sSeq, EBSeq and edgeR for RNA-Seq analysis. Each one of these uses theirown statistical methods to generate a table with a subset of the genes in the input data, whichare differentially expressed. For each of these packages three graphs are generated M.A. plot,volcano plot and histogram graph. Then, R-Peridot makes: post-analysis generating a Venndiagram of the results of each package, the BoxPlot of the samples, a HeatMap, aDendrogram map, a PCA plot and a Gene Ontology chart made with the clusterProfilerpackage of R. And to find the genes which are always differentially expressed, despite thestatistical method used, R-Peridot makes a table with the intersection of the results found ineach package. The user can modify the analysis and post-analysis modules and even add hisown modules with more R packages using the Modules Manager inside R-Peridot. With thesefeatures, the project aim to help researchers, with or without previous knowledge ofprogramming, to do RNA-Seq analysis easily.
RNA-Seq analysis, Gene Expression, Graphical User Interface, Differential Expression, GeneOntology
9
RPEDIA: A R PACKAGE FOR S-SCORE TOOLS OVER THE PLATAFORM FORENHANCING DATA INTEGRATION AND ANALYSIS (PEDIA) API
Leonidas Da Silva Barbosa, Andre Fonseca, Sandro José
UFRN
The large volume of data generated by Next Generation Sequencing (NGS) platforms is oneof the major “Big Data” issues of this decade. How to store and which analysis techniques touse is the key in the whole process to acquire a quick and reliable result. One of thosetechniques is the S-score (De Souza, et al.), developed by us, which integrates different typesof genomic information and gives a score to identify and prioritize cancer genes. In thisapproach a set of parameters are used to calculate the potentiality of a gene as a tumorsuppressor or oncogene. Although the S-score calculation seems simple, the run time of thisapproach, depending of the number of tissues involved, genes or clinical samples, can takehours or even days depending on the implementation. With this in mind a series of strategieswere created to to speed up the generation of S-score processed data. Using areimplementation of the S-score strategy through a new approach using parallelism, wedeveloped a REST API platform to provide S-score tools, such as S-score itself, SDIFF andstratification data for further analyses (either clinical or expression). Through this prototypeplatform, which is underdevelopment, a R package was created for using within the PEDIA(Platform for Enhancing Data Integration and Analysis) API to provide data from the S-scoretools. In this work we present RPEDIA a R package for PEDIA tools API.
PEDIA, API REST, S-score, Data analyzes, R package, TCGA, Câncer
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Influence of SNPs on pharmacological interest genes expression regulation
Paulo Branco, Guilherme Suarez-Kurtz, Sandro de Souza
UFRN
Variations in the level of gene expression are one of the main causes of phenotypic variabilityin organisms, including drug responses in humans. A microRNA (miRNA) is a non-codingRNA that plays an important role in gene regulation acting in a post-transcriptional fashionleading to gene silencing. By mapping single nucleotide polymorphisms (SNPs) to miRNAbinding sites in mRNAs and to miRNAs themselves, this work identified variants that affectgene-miRNA interaction and influence gene expression regulation. Analysis of expressionQuantitative Trait Loci (eQTL) identified a series of genes whose expression is regulated bythe genotype of specific SNPs. This work provides a genome-wide mapping of eQTLslocated in miRNA binding sites and seeds of miRNA. Ongoing analysis are seeking therelationship between genes of pharmacological interest and the set of mapped SNPs.
SNPs, microRNA, gene regulation
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Transcriptional profile of induced and primary neurons reveals new candidate genes forlineage reprogramming
Diego M Coelho, Sandro José de Souza, Marcos R Costa
Bioinformatics Multidisciplinary Environment - IMD, NeuroCell - Brain Institute
Somatic cells can be directly reprogrammed into neurons through the expression of fewtranscription factors. However, the precise mechanisms involved in the lineage-conversionare poorly understood. Similarly, it remains unclear how similar lineage-reprogrammedinduced neurons (iNs) are to bona fide central nervous system neurons. In this work, we usedan unsupervised machine-learning approach to compare the transcriptional profiles oflineage-reprogrammed mouse embryonic fibroblasts (MEFs), mouse embryonictelencephalon neural progenitors and neurons, as well as mouse postnatal cerebral cortexneurons. We show that the transcriptional profile of a subpopulation of lineage-reprogrammed MEFs resembles that of primary neural progenitors and neurons, indicatingthat the intermediate steps enacted by reprogramming factors within MEFs during thetransition to iNs are similar to those observed during primary neuron differentiation. Finally,by comparing the transcriptional profiles of MEFs that undertook a neuronal pathway to thatof MEFs adopting a myogenic fate or retaining fibroblast features we identified potentialcandidates to improve the efficiency for lineage conversion of those cells into neurons.
Direct Lineage Reprogramming, Developmental Neurobiology, Primary Neurons
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Transcriptional Regulatory Network of Ewing’s Sarcoma
Marcel da Câmara Ribeiro Dantas, Marialva Sinigaglia, Caroline Brunetto de Farias, AndréTesainer Brunetto, Algemir Lunardi Brunetto, Rodrigo Juliani Siqueira Dalmolin
Programa de Pós-Graduação em Bioinformática, BioME, Universidade Federal do RioGrande do Norte; Instituto do Câncer Infantil, Porto Alegre, RS, Brasil; Laboratório de
Câncer e Neurobiologia, Centro de Pesquisa Experimental, Hospital de Clínicas de PortoAlegre (CPE-HCPA), Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brasil;
Departamento de Bioquímica, Universidade Federal do Rio Grande do Norte
Ewing's Sarcoma affects bones and soft tissues and is the second most frequent bone tumor inchildren. Ewing's Sarcoma is characterized by the presence of a translocation involving theEWS and another ETS-Family member, typically FLI-1. The oncoprotein EWS-FLI1 induceschromatin remodeling and changes gene expression, activating oncogenes and suppressingtumor suppressor genes, contributing to tumor differentiation and tumor survival. TheEwing’s Sarcoma regulatory network reconstruction is important to uncover the keytranscription factors mediators of tumor pathophysiology. The Ewing's Sarcoma regulatorynetwork was reconstructed and plotted using, respectively, RTN and RedeR packages for RStatistical Computing, available at Bioconductor. This analysis uses the mutual informationof the gene expression profile for inferring relevant pairwise interactions among genes.Regulatory networks were reconstructed from the Ewing's Sarcoma biopsies datasets presentin GEO database (GSE34620 and GSE17679), totalizing 149 samples. Human transcriptionfactors were gathered from Fletcher 2013. The complete regulatory network presented 783regulons. Among them, we identified 11 TFs known to be involved in Ewing’s Sarcoma:FLI1, TP53, FOXM1, MYC, ETV1, NR0B1, ETV4, MYCN, EWS, ERG, and FEV. FLI1,TP53, MYCN, MYC, and FOXM1 interact agonistically to each other. ETV1 and ETV4interact agonistically to each other and antagonistically with the formers. FOXM1 regulondraws attention by regulating a greater number of genes and by interacting with TP53 andMYCN. FOXM1 is expressed in proliferating cells but not in quiescent or terminallydifferentiated cells and has been implicated in cell migration, invasion, angiogenesis, andmetastasis. It has been demonstrated that EWS/FLI1 upregulates FOXM1 levels indirectlyand is expressed at high levels in Ewing's Sarcoma primary tumor. Drugs that physicallyinteract with FOXM1 are demonstrated to inhibit tumor growth in mouse xenograft models.These results suggest that FOXM1 may be a regulator in Ewing Sarcoma. This methodologyallowed us to identify the relationship among transcription factors involved in Ewing'sSarcoma that could provide new therapeutic targets.
Systems Biology, Pediatric Cancer, Cancer of Unknown Primary, RTN
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In silico analysis of miR-137 transcription inhibition in Homozygous (T/T)schizophrenic patients: a pilot study
Stephany C. Esmaile1, Jonas I. N. Oliveira1, Bruno G. Sousa2 and Carlos A. G. Blaha2
1Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte,Natal, RN, Brazil. 2Departamento de Biologia Celular e Molecular, Universidade Federal do
Rio Grande do Norte, Natal, RN, Brazil.
MicroRNA miR-137 single nucleotide polymorphism (rs1625579 SNP) is strongly associatedwith worsening of schizophrenia symptoms and is involved in miR-137 gene suppression.MicroRNA miR-137 regulates synaptogenesis, neural plasticity and suppresses a variety ofcancer types. Based on in silico predictions of the current MIR137 Host Gene with andwithout the SNP, it can be hypothesized that the mutation reversibly inhibits miR-137 genetranscription by steric hindrance due to localization and alterations on DNA conformation,stability, electrostatic potential and transcription factor binding sites.
MIR137HG; miR-137; in silico; Schizophrenia.
14
SurvSign: an interactive R package for cohort stratification and survival analysis
Andre Fonseca; Sandro J. de Souza
Ph.D Program in Bioinformatics, IMD, UFRN; Bioinformatics MultidisciplinaryEnvironment (BioME), IMD, UFRN; Brain Institute, UFRN
Prognosis analysis based on overall and disease-free survival is a traditional method inclinical research. Briefly, survival analysis can be defined as a set of statistical approachesthat measure the time based on an occurrence of an event of interest. In cancer research,survival methods, such as Kaplan-Meier, have been used to measure patient outcome andevaluate clinical trials and treatment strategies. The Cancer Genome Atlas (TCGA)consortium has used those methodologies to analyze a series of clinical and molecularfeatures, such as molecular subtypes, aggressivity and response to treatments. Althoughseveral applications have been created to perform survival analysis, such as survminer (Rpackage) and cBio Platform (web platform), most of them have limited features or requireextensive programming skills. Here, we introduce survSign, a new tool that allows thedownload and analysis of the TCGA data, using an interactive R Shiny interface. In addition,the tool covers other features, such as i) an intuitive platform for cohort analysis and samplestratification; ii) comparisons among multiple survival curves (Log-rank pairwise); iii)signature analysis based on gene combinations; iv) Kaplan-Meier plotting and customization.Additionally, survSign was also designed as a regular R package, for exhaustive analysis orintermediate users. Currently, survSign have been applied in our research to find potentialtargets associated with clinical features and prognosis status. In particular, survSign was usedto analyze two gene lists, the human surfaceome, and cancer testis genes (CTs) in a pan-cancer analysis. As result, we have proposed the impact of distinct genes or metabolicpathways in patient outcome. Furthermore, our findings have also shown an associationamong putative CTs expression, immunological response and prognosis status.
prognosis status, clinical features, log-rank test
15
Sex-biased gene expression on brain plasticity in common marmosets
Viviane Brito Nogueira, Sandro José de Souza, Maria Bernardete Cordeiro de Sousa
Federal University of Rio Grande do Norte, BioME, Brain Institute, Graduate Program inHealth Sciences
Common marmoset (Callithrix jacchus), a small New Work monkey has been widely used asa neuropsychiatric model not only elucidating brain dysfunctions in neuropsychiatricdisorders but also deciphering neural circuits involved in social behaviors in primates,including humans. In this study, public transcriptome data from marmosets’ frontal cortexwere analyzed to compare differential expression between males and females. RNA-seq readsfrom Cortez et al. 2014 were mapped with TopHat v2.1.0 (using Bowtie2 – 2.2.5, Langmeadet al. 2009) to the reference genome assembly. Cufflinks 2.2.1 (Trapnell et al. 2010) was usedto calculate the FPKM values. Sex-biased expression was defined as the normalizeddifference between expression in males and females: Δ = (m–f) / (m+ f) (Cheng &Kirkpatrick 2016). To identify GO categories enriched for male- and female-biased genes,hypergeometric test for overrepresentation was used (padjust < 0.01, enrichGO in R).Isoforms from 33 genes female-biased were enriched for regulation of synaptic plasticity(padjust 6e-9) as tested by Monte Carlo simulations (1,000 random sets). Some of these 33genes are involved with glutamatergic synapsis functioning and other with plastic eventsrelated to remodeling of synaptic circuits. Furthermore, some genes are involved in cAMP-CREB1 signaling cascade possibly related to stress modulation during social competitionamong females to achieve dominant status and reach the reproductive position into the socialgroup. Others genes are involved in the visual transduction cascade and are possiblyassociated to differences in the number of opsins once all males are dichromatic and femaleare di or trichromatic. In summary, we show that genes presenting a sex-biased expressionpattern in marmosets fall into ontology categories related to neural cells and behaviorprocesses.
sexual dimorphism, primate neuropsychiatric model, synaptic plasticity
16
Metabolic map of lead poisoning
Souza, I.D., Andrade, A.S., Dalmolin, R.J.S.
Postgraduate Program in Bioinformatics, UFRN, Natal, Brazil
Since antiquidy, lead was used by mankind as a tool for daily routine, due its uniqueproperties, like malleability, ductility, corrosion resistance, low melting point and lowelectrical conductivity. Nowadays, lead is one of the most studied heavy metals worldwideowing to its relation with occupational exposure on industry workers. Many effects of leadpoisoning were already been reported on literature, showing a compromising of whole bodyhealth, with symptoms related to cardiovascular, imune, skeletal, reproductive,heamatological, renal and gastrointestinal systems, even the most studied ones are relatedwith neurological system. Although there is evidence of how it affects homeostasis at thecellular level, the description of metabolic pathways affected in lead poisoning is not fullyestablished. To clarify the effects of lead poisoning, the aim of this study is to build ametabolic map of the cellular and biochemical pathways altered by the presence of lead, andto analise which proteins and cellular componentes this heavy metal has the hability to bindand interfere with its normal function. For this purpose, made a literature review in order toobtain information about lead interactions with biomolecules. We have found a total of 22proteins which can directly interact with lead, with many others that can be indirectlyaffected by this metal. We used KEGG pathways to search for the pathways each proteinparticipates. With those informations, we built the metabolic map of lead poisoning.
lead poisoning; heavy metals; lead intoxication; environmental toxicity; systems toxicology;environmental health
17
Genome-wide identification of cancer/testis genes and their association with prognosisin a pan-cancer analysis
V.L. da Silva1,2,3,#; A.F. Fonseca1,2,3#; M. Fonseca1; T.E. da Silva1; A.C. Coelho1,3; J.E.Kroll1,3,4; J.E.S. de Souza3,5; B. Stransky3,6; G.A. de Souza1,3 & S.J. de Souza1,3
1-Instituto do Cérebro; 2-Ph.D. Program in Bioinformatics; 3-BioinformaticsMultidisciplinary Environment (BioME); 4-Instituto de Bioinformática e Biotecnologia; 5-
Instituto Metrópole Digital; 6-Dep. de Engenharia Biomédica
Cancer/testis (CT) genes are excellent candidates for cancer immunotherapies because oftheir restrict expression in normal tissues and the capacity to elicit an immune response whenexpressed in tumor cells. In this study, we provide the largest screen for CT genes so far withthe identification of 698 putative CT genes. Comparison with a set of known CT genes showsthat we have identified 512 new CT genes. Integration of gene expression and clinical dataled us to identify dozens of CT genes associated with either good or poor prognosis. For theCT genes related to good prognosis, we show that there is a direct relationship between CTgene expression and a signal for CD8+ cells infiltration for lung adenocarcinoma andmelanoma.
Cancer/testis, antigens, biomarkers, prognosis, bioinformatics.
Authors index
Affeldt S, 04Alves Sobrinho PA, 08Andrade AS, 16Barbosa LS, 09Blaha CAG, 13Bortolini MC, 06Branco P, 10Brunetto AL, 12Brunetto AT, 12Coelho AC, 17Coelho DM, 11Costa MR, 11Dalmolin RJS, 05, 06, 12, 16Dantas MCR, 12Esmaile SC, 13Farias CB, 12Fonseca ALF, 05, 08, 09, 14, 17Fonseca M, 17Imparata D, 06Isambert H, 04Kroll JE, 17Malaguti G, 04Martins DL, 08Nogueira VB, 15Oliveira JIN, 13Reis CF, 05Silva TE, 17Singh PP, 04Sinigaglia M, 12Sousa BG, 13Sousa MBC, 15Souza SJ, 05, 06, 09, 10, 11, 14, 15, 17Souza GA, 17Souza ID, 16Souza JES, 04, 17Stransky B, 17Suerez-Kurtz G, 10Viscardi LH, 06
