Polimorfismos do gene MSX1 e a fenda labio e/ou palatina não-sindrômica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Polimorfismos de nucleotídeo único (SNPS) dos genes PPARy2, lipase lipoproteica, receptor de LDL, apolipoproteina C3, e adiponectina podem modular o perfil lipídico de pacientes com a síndrome de Berardinelli-Seip

A Síndrome de Berardinelli-Seip (SBS) é um distúrbio raro do metabolismo dos lipídios, caracterizada pela ausência quase total de tecido adiposo subcutâneo, hipertrigliceridemia, hipoleptinemia e diabetes insulino resistente ou lipoatrófico. Sua etiologia envolve implicações hipotalâmicas, alterações nos receptores de insulina e mutações nos genes AGPAT2, Gng3lg, CAV1 e PTRF. O tecido adiposo secreta diversas substâncias, tais como: leptina, resistina, adiponectina, esteróides, TNF , IL-6, PAI-1, angiotensinogênio, IGF-1. Muitas delas estão associadas ao diabetes mellitus tipo 2, obesidade e hipertensão. Os PPARs são fatores transcricionais pertencentes à superfamília de receptores nucleares ligantes ativados. Sabe-se que o PPAR , é importante para o metabolismo lipídico e glicídico e que o ligante natural do PPAR é derivado do ácido graxo. Nesse sentido, foram avaliados 24 pacientes portadores da SBS, provenientes do Estado do Rio Grande do Norte, com a mediana das idades de 18,5 anos (0,55 a 47 a), sendo 9 (37,5 %) do gênero masculino e 15 (62,5 %) do gênero feminino. Quanto ao grupo étnico, foram classificados em caucasóides (brancos) 21 (87,5 %) e negróides 3 (12,5 %) pacientes. Foram feitas avaliações clínico-endocrinológica, bioquímica, hormonal, molecular e o estudo dos polimorfismos Adiponectina ADIPOQ, PPARγ2 Pro12Ala, LPL-PvuII, APOC3-SstI e LDLR-AvaII em portadores da SBS. Nesta população nós não encontramos nenhuma associação de parâmetros lipídicos e glicídicos com os polimorfismos LPL-PvuII, APOC3-SstI e LDLR-AvaII. Porém, observamos associação entre Adiponectina ADIPOQ e PPARγ2 Pro12Ala e níveis lipídicos mais elevados, sugerindo um papel biológico para estes fatores, indicando estudos mais aprofundados

Avaliação do status antioxidante, expressão gênica e polimorfismos dos genes SOD1, SOD2 e GPx1 em crianças, adolescentes e adultos jovens com diabetes tipo 1

Studies report that the pathophysiological mechanism of diabetes complications is associated with increased production of Reactive Oxygen Species (ROS)-induced by hyperglycemia and changes in the capacity the antioxidant defense system. In this sense, the aim of this study was to evaluate changes in the capacity of antioxidant defense system, by evaluating antioxidant status, gene expression and polymorphisms in the genes of GPx1, SOD1 and SOD2 in children, adolescents and young adults with type 1 diabetes. We studied 101 individuals with type 1 diabetes (T1D) and 106 normoglycemic individuals (NG) aged between 6 and 20 years. Individuals with type 1 diabetes were evaluated as a whole group and subdivided according to glycemic control in DM1G good glycemic control and DM1P poor glycemic control. Glycemic and metabolic control was evaluate by serum glucose, glycated hemoglobin, triglycerides, total cholesterol and fractions (HDL and LDL). Renal function was assessed by measurement of serum urea and creatinine and albumin-to-creatinine ratio (ACR) in spot urine. Antioxidant status was evaluate by content of reduced glutathione (GSH) in whole blood and the activity of erythrocyte enzymes glutathione peroxidase (GPx) and superoxide dismutase (SOD). We also analyzed gene expression and gene polymorphisms of GPx1 (rs1050450), SOD1 (rs17881135) and SOD2 (rs4880) by the technique of real-time PCR (Taqman®). Most individuals with DM1 (70.3%) had poor glycemic control (glycated hemoglobin> 8%). Regarding the lipid profile, individuals with type 1 diabetes had significantly elevated total cholesterol (p <0.001) and LDL (p <0.000) compared to NG; for triglycerides only DM1NC group showed significant increase compared to NG. There was an increase in serum urea and RAC of individuals with DM1 compared to NG. Nine individuals with type 1 diabetes showed microalbuminuria (ACR> 30 mg / mg). There was a decrease in GSH content (p = 0.006) and increased erythrocyte GPx activity (p <0.001) and SOD (p <0.001) in DM1 group compared to NG. There was no significant difference in the expression of GPx1 (p = 0.305), SOD1 (.365) and SOD2 (0.385) between NG and DM1. The allele and genotype frequencies of the polymorphisms studied showed no statistically significant difference between the groups DM1 and NG. However, the GPx1 polymorphism showed the influence of erythrocyte enzyme activity. There was a decrease in GPx activity in individuals with type 1 diabetes who had a polymorphic variant T (p = 0.012). DM1 patients with the polymorphic variant G (AG + GG) for polymorphism of SOD2 (rs4880) showed an increase in the RAC (p <0.05). The combined data suggest that glucose control seems to be the predominant factor for the emergence of changes in lipid profile, renal function and antioxidant system, but the presence of the polymorphisms studied may partly contribute to the onset of complications

Uso sustentável da Copernicia prunifera (Miller) H. E Moore no semiárido potiguar: valorização de saberes e conservação dos recursos genéticos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Mecanismos sócio-genéticos da representação social de trabalho docente por grupos de licenciandos de física e de química da Universidade Federal do Rio Grande do Norte

This research aims to understand the social representations Teaching Work in groups of undergraduate students of Physics and Chemistry of the Federal University of Rio Grande do Norte. For this, the proposal was based on the three theoretical and methodological consensus Carvalho (2012) in the explanation of socio-genetic mechanisms constituents of dynamic consensus that has functionality to your organization. It Was used to achieve this goal, the theoretical-epistemological Serge Moscovici (1978, 2003), Jodelet (2011), Wagner (1998,( 2011) and Carvalho (2012). The corpus analyzed results from a qualitative and quantitative research, developed in three stages. The first two (2) questionnaires to fifty (50) of each undergraduate course, a questionnaire and another profile for collection of free associations concerning motes inductors "Give Lesson," "Student" and "Teacher". The second step in the procedure Multiple Classifications, Roazzi (1995), aimed for another thirty (30) undergraduate students for each course, as well as Document Analysis of Educational Projects Curriculum courses in Physics and Chemistry. The data analysis of the first stage focused on descriptive statistics and frequency and average order of the words associated with motes inductors. The results from the Multiple Classification Procedure submitted to multidimensional analysis (MSA multidimensional scalogram analysis) and SSA (Similarity Structure Analysis), were interpreted by the theoretical and methodological proposal of the three consensus, supported by analysis of the rhetorical nature of justifications classifications and categorizations of words, boosted in times of application of Procedure Multiple Classification. The data revealed that the groups surveyed were the same Social Representation with specific dynamic consensual. Thinking Teaching Work for these groups it is considered in three dimensions: the BE-DO-HAVE of teaching. In the group of Physics consensus was clear semantic, which expressed a dynamic in which the interpretations of "Teaching Work" peacefully coexist on perceptions of two concepts: An identity around the "BE" "Teacher" or "BE" "Educator" and the other, how they think about professional development. The type of group consensus Chemistry pointed to a consensual logic hierarchical order in which the gradual between the elements of BE-DO-HAVE attested conflicts and disagreements about the perceptual object "Teaching Work", around what value most, whether they are the attributes of personal or professional-technical dimension of teaching, in the course of professional development. The thesis to explain the mechanisms of socio-genetic Representation Social Teaching Work by theoretical and methodological proposal was confirmed

Determinação dos parâmetros do controlador preditivo generalizado com função de pesos variante no tempo através de algoritmos genéticos

The predictive control technique has gotten, on the last years, greater number of adepts in reason of the easiness of adjustment of its parameters, of the exceeding of its concepts for multi-input/multi-output (MIMO) systems, of nonlinear models of processes could be linearised around a operating point, so can clearly be used in the controller, and mainly, as being the only methodology that can take into consideration, during the project of the controller, the limitations of the control signals and output of the process. The time varying weighting generalized predictive control (TGPC), studied in this work, is one more an alternative to the several existing predictive controls, characterizing itself as an modification of the generalized predictive control (GPC), where it is used a reference model, calculated in accordance with parameters of project previously established by the designer, and the application of a new function criterion, that when minimized offers the best parameters to the controller. It is used technique of the genetic algorithms to minimize of the function criterion proposed and searches to demonstrate the robustness of the TGPC through the application of performance, stability and robustness criterions. To compare achieves results of the TGPC controller, the GCP and proportional, integral and derivative (PID) controllers are used, where whole the techniques applied to stable, unstable and of non-minimum phase plants. The simulated examples become fulfilled with the use of MATLAB tool. It is verified that, the alterations implemented in TGPC, allow the evidence of the efficiency of this algorithm

Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço

The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed

Algoritmos genéticos: uso de lógica nebulosa e análise de convergência por cadeia de Markov

In this work, the Markov chain will be the tool used in the modeling and analysis of convergence of the genetic algorithm, both the standard version as for the other versions that allows the genetic algorithm. In addition, we intend to compare the performance of the standard version with the fuzzy version, believing that this version gives the genetic algorithm a great ability to find a global optimum, own the global optimization algorithms. The choice of this algorithm is due to the fact that it has become, over the past thirty yares, one of the more importan tool used to find a solution of de optimization problem. This choice is due to its effectiveness in finding a good quality solution to the problem, considering that the knowledge of a good quality solution becomes acceptable given that there may not be another algorithm able to get the optimal solution for many of these problems. However, this algorithm can be set, taking into account, that it is not only dependent on how the problem is represented as but also some of the operators are defined, to the standard version of this, when the parameters are kept fixed, to their versions with variables parameters. Therefore to achieve good performance with the aforementioned algorithm is necessary that it has an adequate criterion in the choice of its parameters, especially the rate of mutation and crossover rate or even the size of the population. It is important to remember that those implementations in which parameters are kept fixed throughout the execution, the modeling algorithm by Markov chain results in a homogeneous chain and when it allows the variation of parameters during the execution, the Markov chain that models becomes be non - homogeneous. Therefore, in an attempt to improve the algorithm performance, few studies have tried to make the setting of the parameters through strategies that capture the intrinsic characteristics of the problem. These characteristics are extracted from the present state of execution, in order to identify and preserve a pattern related to a solution of good quality and at the same time that standard discarding of low quality. Strategies for feature extraction can either use precise techniques as fuzzy techniques, in the latter case being made through a fuzzy controller. A Markov chain is used for modeling and convergence analysis of the algorithm, both in its standard version as for the other. In order to evaluate the performance of a non-homogeneous algorithm tests will be applied to compare the standard fuzzy algorithm with the genetic algorithm, and the rate of change adjusted by a fuzzy controller. To do so, pick up optimization problems whose number of solutions varies exponentially with the number of variables

Algoritmos genéticos e processamento paralelo aplicados à definição e treinamento de redes neurais perceptron de múltiplas camadas

ln this work, it was deveIoped a parallel cooperative genetic algorithm with different evolution behaviors to train and to define architectures for MuItiIayer Perceptron neural networks. MuItiIayer Perceptron neural networks are very powerful tools and had their use extended vastIy due to their abiIity of providing great resuIts to a broad range of appIications. The combination of genetic algorithms and parallel processing can be very powerful when applied to the Iearning process of the neural network, as well as to the definition of its architecture since this procedure can be very slow, usually requiring a lot of computational time. AIso, research work combining and appIying evolutionary computation into the design of neural networks is very useful since most of the Iearning algorithms deveIoped to train neural networks only adjust their synaptic weights, not considering the design of the networks architecture. Furthermore, the use of cooperation in the genetic algorithm allows the interaction of different populations, avoiding local minima and helping in the search of a promising solution, acceIerating the evolutionary process. Finally, individuaIs and evolution behavior can be exclusive on each copy of the genetic algorithm running in each task enhancing the diversity of populations

Otimização de modelos de predição da perda de propagação aplicáveis em 3,5GHZ utilizando algoritmos genéticos

The telecommunications industry has experienced recent changes, due to increasing quest for access to digital services for data, video and multimedia, especially using the mobile phone networks. Recently in Brazil, mobile operators are upgrading their networks to third generations systems (3G) providing to users broadband services such as video conferencing, Internet, digital TV and more. These new networks that provides mobility and high data rates has allowed the development of new market concepts. Currently the market is focused on the expansion of WiMAX technology, which is gaining increasingly the market for mobile voice and data. In Brazil, the commercial interest for this technology appears to the first award of licenses in the 3.5 GHz band. In February 2003 ANATEL held the 003/2002/SPV-ANATEL bidding, where it offered blocks of frequencies in the range of 3.5 GHz. The enterprises who purchased blocks of frequency were: Embratel, Brazil Telecom (Vant), Grupo Sinos, Neovia and WKVE, each one with operations spread in some regions of Brazil. For this and other wireless communications systems are implemented effectively, many efforts have been invested in attempts to developing simulation methods for coverage prediction that is close to reality as much as possible so that they may become believers and indispensable tools to design wireless communications systems. In this work wasm developed a genetic algorithm (GA's) that is able to optimize the models for predicting propagation loss at applicable frequency range of 3.5 GHz, thus enabling an estimate of the signal closer to reality to avoid significant errors in planning and implementation a system of wireless communication

Otimização do controle eletrônico do diagrama de radiação de arranjos de antenas usando algoritmos genéticos com codificação real

Antenna arrays are able to provide high and controlled directivity, which are suitable for radiobase stations, radar systems, and point-to-point or satellite links. The optimization of an array design is usually a hard task because of the non-linear characteristic of multiobjective, requiring the application of numerical techniques, such as genetic algorithms. Therefore, in order to optimize the electronic control of the antenna array radiation pattem through genetic algorithms in real codification, it was developed a numerical tool which is able to positioning the array major lobe, reducing the side lobe levels, canceling interference signals in specific directions of arrival, and improving the antenna radiation performance. This was accomplished by using antenna theory concepts and optimization methods, mainly genetic algorithms ones, allowing to develop a numerical tool with creative genes codification and crossover rules, which is one of the most important contribution of this work. The efficiency of the developed genetic algorithm tool is tested and validated in several antenna and propagation applications. 11 was observed that the numerical results attend the specific requirements, showing the developed tool ability and capacity to handle the considered problems, as well as a great perspective for application in future works.

Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

Análise de polimorfismos dos genes da rota quinureniana em pacientes com meningite bacteriana.

Bacterial meningitis (BM) is still an important infectious disease causing death and disability. Invasive bacterial infections of the central nervous systems (CNS) generate some of the most powerful inflammatory responses known, which contributes to neuronal damage. The DNA microarray technology showed alterations in the kynurenine (KYN) pathway that is induced in BM and other diseases associated with inflammation, leading to brain injury. Our main aim was to search SNPs previously described in the KYN path enzymes to investigate a putative association of this SNPs with imbalanced in this pathway in patients with BM. The patients included in this study were 33 males and 24 females, with ages varying from 02 months to 68 years. SNPs were located inside of the domain conserved in KYNU, IDO, KATI and KATII. Primers were designed for analysis of SNPs already described by PIRA-PCR followed by RFLP. The analysis of KYNU+715G/A SNP found a heterozygous frequency of 0.033. We did not found the variant allele of SNP KYNU+693G/A, KATI+164T/C, KATII+650C/T and IDO+434T/G. Despite of previews studies showing the importance of KYN pathway we did not found one association of these SNPs analyzed with susceptibility or severity of MB in study population.

Associação entre polimorfismos em enzimas de reparo de DNA e ocorrência de meningite bacteriana.

Despite advances in vaccine development and therapy, bacterial meningitis (BM) remains a major cause of death and long-term neurological disabilities. As part of the host inflammatory response to the invading pathogen, factors such as reactive oxygen species are generated, which may damage DNA and trigger the overactivation of DNA repair mechanisms. It is conceivable that the individual susceptibility and outcome of BM may be in part determined by non synonymous polymorphisms that may alter the function of crucial BER DNA repair enzymes as PARP-1, OGG-1 and APE-1. These enzymes, in addition to their important DNA repair function, also perform role of inflammatory regulators. In this work was investigated the non synonymous SNPs APE-1 Asn148Glu, OGG-1 Ser326Cys,PARP-1 Val762Ala, PARP-1 Pro882Leu and PARP-1 Cys908Tyr in patients with bacterial meningitis (BM), chronic meningitis (CM), aseptic meningitis (AM) and not infected (controls). As results we found increased frequency of variant alleles of PARP-1 Val762Ala (P = 0.005) and APE-1 Asn148Glu (P=0.018) in BM patients, APE-1 Asn148Glu in AM patients (P = 0.012) and decrease in the frequency of the variant allele OGG-1 Ser326Cys in patients with CM (P = 0.013), regarding the allelic frequencies in the controls. A major incidence of individuals heterozygous and/ or polymorphic homozygous in BM for PARP-1 Val762Ala (P= 0.0399, OD 4.2, 95% IC 1.213 -14.545) and PARP-1 Val762Ala/ APE-1 Asn148Glu (P = 0.0238, OD 11.111, 95% IC 1.274 - 96.914) was observed related to what was expected in a not infected population. It was also observed a major incidence of combined SNPs in the BM patients compared with the control group (P=0.0281), giving evidences that SNPs can cause some susceptibility to the disease. This combined effect of SNPs seems to regulate the principal cytokines and other factors related to BM inflammatory response and point the importance of DNA repair not only to repair activity when DNA is damaged, but to others essential functions to human organism balance.

Algoritmos genéticos canônico e elitista: uma abordagem comparativa

Universidade Federal do Rio Grande do Norte