Pharmacogenetics of Warfarin: Development of a Dosing Algorithm for Brazilian Patients

A dosing algorithm including genetic (VKORC1 and CYP2C9 genotypes) and nongenetic factors (age, weight, therapeutic indication, and cotreatment with amiodarone or simvastatin) explained 51% of the variance in stable weekly warfarin doses in 390 patients attending an anticoagulant clinic in a Brazilian public hospital. The VKORC1 3673G>A genotype was the most important predictor of warfarin dose, with a partial R(2) value of 23.9%. Replacing the VKORC1 3673G>A genotype with VKORC1 diplotype did not increase the algorithm`s predictive power. We suggest that three other single-nucleotide polymorphisms (SNPs) (5808T>G, 6853G>C, and 9041G>A) that are in strong linkage disequilibrium (LD) with 3673G>A would be equally good predictors of the warfarin dose requirement. The algorithm`s predictive power was similar across the self-identified ""race/color"" subsets. ""Race/color"" was not associated with stable warfarin dose in the multiple regression model, although the required warfarin dose was significantly lower (P = 0.006) in white (29 +/- 13 mg/week, n = 196) than in black patients (35 +/- 15 mg/week, n = 76).

Graphical constraints: a graphical user interface for constraint problems

A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embraces areas like resource allocation, scheduling, timetabling or vehicle routing. Constraint programming is a form of declarative programming in the sense that instead of specifying a sequence of steps to execute, it relies on properties of the solutions to be found, which are explicitly defined by constraints. The idea of constraint programming is to solve problems by stating constraints which must be satisfied by the solutions. Constraint programming is based on specialized constraint solvers that take advantage of constraints to search for solutions. The success and popularity of complex problem solving tools can be greatly enhanced by the availability of friendly user interfaces. User interfaces cover two fundamental areas: receiving information from the user and communicating it to the system; and getting information from the system and deliver it to the user. Despite its potential impact, adequate user interfaces are uncommon in constraint programming in general. The main goal of this project is to develop a graphical user interface that allows to, intuitively, represent constraint satisfaction problems. The idea is to visually represent the variables of the problem, their domains and the problem constraints and enable the user to interact with an adequate constraint solver to process the constraints and compute the solutions. Moreover, the graphical interface should be capable of configure the solver’s parameters and present solutions in an appealing interactive way. As a proof of concept, the developed application – GraphicalConstraints – focus on continuous constraint programming, which deals with real valued variables and numerical constraints (equations and inequalities). RealPaver, a state-of-the-art solver in continuous domains, was used in the application. The graphical interface supports all stages of constraint processing, from the design of the constraint network to the presentation of the end feasible space solutions as 2D or 3D boxes.

Detecting cell assemblies in large neuronal populations

Recent progress in the technology for single unit recordings has given the neuroscientific community theopportunity to record the spiking activity of large neuronal populations. At the same pace, statistical andmathematical tools were developed to deal with high-dimensional datasets typical of such recordings.A major line of research investigates the functional role of subsets of neurons with significant co-firingbehavior: the Hebbian cell assemblies. Here we review three linear methods for the detection of cellassemblies in large neuronal populations that rely on principal and independent component analysis.Based on their performance in spike train simulations, we propose a modified framework that incorpo-rates multiple features of these previous methods. We apply the new framework to actual single unitrecordings and show the existence of cell assemblies in the rat hippocampus, which typically oscillate attheta frequencies and couple to different phases of the underlying field rhythm

Estudo clínico e laboratorial da pneumonia de bezerros induzida pela inoculação intrabronquial de Mannheimia haemolytica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Alfabetização de crianças e jovens: superando desafios da inclusão escolar

This work has its genesis in the life of a teacher. It contemplates the report of a great story that expresses the political will of anonymous people who sought/seek to overcome challenges and prejudices, a joint effort to make real the right to literacy. The reported story was developed in the Pedagogic Clinic Teacher Heitor Carrilho, Natal-RN which, concerned about the sentence of 'unable to learn the written language' attributed to children and young public school students, decided to invest in overcoming prejudices and fight against school failure of these underprivileged. The problem that motivated the study was thus set up: What particularities characterize a pedagogical practice which aims to teach literacy to children and youth from public schools, considered not capable of learning the written language? What theoretical and methodological procedures are shown as a boost to literacy in the development of a pedagogical practice systematically targeted to reflect the perspective of educating those students in public schools? Aiming to answer these questions, we conducted a qualitative research having as methodology, Life Stories and Research/Formation. For the construction of the data, it was decided to use the participative observation, semi-structured interviews and document analysis. Guided by the principles of content analysis the data analysis was built, from which emerged two categories: theoretical and methodological procedures aligned to the major axes of literacy and Procedures of the specific theoretical and methodological fundamentals of literacy. As subsets of the transverse procedures others were seized: didactic-pedagogic procedures; social affective procedures. Regarding these ones, the research shows the importance of the teacher to build a relationship of listening to the students and their families in order to organize the pedagogical work, looking at multiple dimensions of the subject: the intellect, the creative, the affective, moral, noting that between the methodology and didactics or as part of it, the links built represent great opportunities to promote literacy. Regarding the specific procedures, others were built: procedures that emphasize oral communication, procedures that favor writing and procedures that privilege reading. Under these procedures, the results of research show that you can only promote literacy if the teacher provides the students effective conditions of understanding the principles of alphabetical notation from the use of various kinds of texts, leading them to comprehend and use them in different contexts. Therefore, instructors must meet the learners' prior knowledge, their language, and the learning real needs that will bring new challenges consistent with their possibilities. The research confirms the importance of the Educational Support extra school. However, it is essential to emphasize that it is a function of the school to promote literacy for all students in the early years of schooling. It is recorded, however, that for the implementation of this desire, we must break the school model characterized by a rigid tradition, in which there is only room for those who learn the content taught in a minimum time. Unfortunately, despite the discourse of inclusion and ensuring the right to education, the school remains exclusive and selective separating the school learning of interpersonal relations and social integration and performance. On the one hand, research showed the difficulties of conducting studies and/or strategies that address the particularities of children and young people believed not capable of learning. On the other hand, the political commitment and motivation have increased the perception that it is possible to mitigate the existing deficits in the educational context, beginning with the everyday teaching practice, in which new knowledge can be learned, methodologies can be improved and, despite everything, the educational success can be built

Use of direct and iterative solvers for estimation of SNP effects in genome-wide selection

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Influence of data structure on the estimation of the additive genetic direct and maternal covariance for early growth traits in Nellore cattle

The objective of the present study was to investigate the effect of data structure on estimated genetic parameters and predicted breeding values of direct and maternal genetic effects for weaning weight (WW) and weight gain from birth to weaning (BWG), including or not the genetic covariance between direct and maternal effects. Records of 97,490 Nellore animals born between 1993 and 2006, from the Jacarezinho cattle raising farm, were used. Two different data sets were analyzed: DI_all, which included all available progenies of dams without their own performance; DII_all, which included DI_all + 20% of recorded progenies with maternal phenotypes. Two subsets were obtained from each data set (DI_all and DII_all): DI_1 and DII_1, which included only dams with three or fewer progenies; DI_5 and DII_5, which included only dams with five or more progenies. (Co)variance components and heritabilities were estimated by Bayesian inference through Gibbs sampling using univariate animal models. In general, for the population and traits studied, the proportion of dams with known phenotypic information and the number of progenies per dam influenced direct and maternal heritabilities, as well as the contribution of maternal permanent environmental variance to phenotypic variance. Only small differences were observed in the genetic and environmental parameters when the genetic covariance between direct and maternal effects was set to zero in the data sets studied. Thus, the inclusion or not of the genetic covariance between direct and maternal effects had little effect on the ranking of animals according to their breeding values for WW and BWG. Accurate estimation of genetic correlations between direct and maternal genetic effects depends on the data structure. Thus, this covariance should be set to zero in Nellore data sets in which the proportion of dams with phenotypic information is low, the number of progenies per dam is small, and pedigree relationships are poorly known. (c) 2012 Elsevier B.V. All rights reserved.

Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte

The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

Influence of Th1/Th2 cytokines and nitric oxide in murine systemic infection induced by Sporothrix schenckii

In an attempt to elucidate the effects of Sporothrix schenckii infection on the immune response, our laboratory has developed a murine model of disseminated sporotrichosis. Helper T cells can be further subdivided into Th1 and Th2 phenotypes. The differentiation of two subsets of T lymphocytes is driven by IL-12 and IL-4 cytokines, respectively. Th1 cells produce IFN-gamma that activate macrophages and promote cell-mediated immunity. In addition, we found low levels of iNOS and NO production in the initial (1st and 2nd weeks) and final (9th and 10th weeks) periods of the infection, in contrast with the period of week 4 to 7 of elevated values. The determination of IFN-gamma and IL-12 are in agreement with NO/iNOS detection, showing the presence of cellular immune response throughout the infectious process. However, the production of IL-4 shows an increase in levels after the 5th and 6th weeks suggesting a participation of Th2 response in this period as well. Regarding these results, the study demonstrated that in experimental sporotrichosis infection the cellular immune response participated throughout the period analyzed as a nitric oxide dependent mechanism. In contrast, the presence of Th2 response began in the 5th week, suggesting the participation of humoral immune response in advanced stages of sporotrichosis.

Abnormalities in apolipoprotein and lipid levels in an HIV-infected Brazilian population under different treatment profiles: the relevance of apolipoprotein E genotypes and immunological status

HIV infection is associated with disturbances in lipid metabolism due to a host's response mechanism and the current antiretroviral therapy. The pathological appearance and progression of atherosclerosis is dependent on the presence of injurious agents in the vascular endothelium and variations in different subsets of candidate genes. Therefore, the Hha I polymorphism in the apolipoprotein E gene was evaluated in addition to triglycerides, total cholesterol, very low-density lipoprotein (VLDL), LDL, high-density lipoprotein (HDL), and apolipoprotein (apo) Al, B and E levels in 86 Brazilian HIV-infected patients and 29 healthy controls. The allele frequency for apoE in the HIV-infected group and controls was in agreement with data on the Brazilian population. Dyslipidemia was observed in the HIV group and verified by increased levels of triglycerides, VLDL and apoE, and decreased levels of HDL and apoAl. The greatest abnormalities in these biochemical variables were shown in the HIV-infected individuals whose immune function was more compromised. The effect of the genetic variation at the APOE gene on biochemical variables was more pronounced in the HIV-infected individuals who carried the apoE2/3 genotype. The highly active antiretroviral therapy (HAART)-receiving group presented increased levels of total cholesterol and apoE. Dyslipidemia was a predictable consequence of HIV infection and the protease inhibitors intensified the increase in apoE values.

Morphofunctional evaluation of thymus in hyperglycemic-hypoinsulinemic mice during dermatophytic infection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Otimização em comitês de classificadores: uma abordagem baseada em filtro para seleção de subconjuntos de atributos

Traditional applications of feature selection in areas such as data mining, machine learning and pattern recognition aim to improve the accuracy and to reduce the computational cost of the model. It is done through the removal of redundant, irrelevant or noisy data, finding a representative subset of data that reduces its dimensionality without loss of performance. With the development of research in ensemble of classifiers and the verification that this type of model has better performance than the individual models, if the base classifiers are diverse, comes a new field of application to the research of feature selection. In this new field, it is desired to find diverse subsets of features for the construction of base classifiers for the ensemble systems. This work proposes an approach that maximizes the diversity of the ensembles by selecting subsets of features using a model independent of the learning algorithm and with low computational cost. This is done using bio-inspired metaheuristics with evaluation filter-based criteria

Seleção de atributos em comitês de classificadores utilizando algoritmos genéticos

Classifier ensembles are systems composed of a set of individual classifiers and a combination module, which is responsible for providing the final output of the system. In the design of these systems, diversity is considered as one of the main aspects to be taken into account since there is no gain in combining identical classification methods. The ideal situation is a set of individual classifiers with uncorrelated errors. In other words, the individual classifiers should be diverse among themselves. One way of increasing diversity is to provide different datasets (patterns and/or attributes) for the individual classifiers. The diversity is increased because the individual classifiers will perform the same task (classification of the same input patterns) but they will be built using different subsets of patterns and/or attributes. The majority of the papers using feature selection for ensembles address the homogenous structures of ensemble, i.e., ensembles composed only of the same type of classifiers. In this investigation, two approaches of genetic algorithms (single and multi-objective) will be used to guide the distribution of the features among the classifiers in the context of homogenous and heterogeneous ensembles. The experiments will be divided into two phases that use a filter approach of feature selection guided by genetic algorithm

Increased production of hydrogen peroxide by peripheral blood monocytes associated with smoking exposure intensity in smokers

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Monitoramento de parâmetros laboratoriais em gatos sem raça definida durante o período neonatal

O objetivo do presente estudo foi à monitoração dos parâmetros laboratoriais como hemograma, enzimas hepáticas alanina aminotransferase (ALT) e gama-glutamiltransferase (GGT), glicemia e proteinograma sérico, e avaliar o efeito da idade em gatos sem raça definida durante a fase neonatal. Vinte gatos machos e fêmeas foram utilizados a partir do terceiro dia de vida até o 38º dia de idade. As amostras de sangue foram colhidas semanalmente e as análises laboratoriais (hemograma, enzimas hepáticas, glicemia e proteinograma sérico) realizadas no 3º, 10º, 17º, 24º, 31º e 38º dia de idade. Os resultados exibiram efeito significativo da idade sobre a contagem total de eritrócitos, concentração de hemoglobina, volume globular, volume corpuscular médio, concentração de hemoglobina corpuscular média, leucócitos totais, neutrófilos, eosinófilos e basófilos. Nenhum efeito foi observado em células como linfócitos, monócitos ou na concentração sérica de glicose. A análise das modificações ocorridas nos parâmetros laboratoriais durante a fase neonatal reflete o desenvolvimento fisiológico do filhote e contribui para o conhecimento do processo adaptativo em gatos neonatos durante o primeiro mês de vida, sendo útil para a avaliação clínica, diagnóstico e tratamento das doenças neonatais.