A infecção por Leishmania infantum chagasi altera o metabolismo lipídico do hospedeiro

American visceral leishmaniasis (AVL), caused by Leishmania infantum chagasi (L.i.chagasi), stands as a public health problem in Brazil, with human and canine cases related in all states..Lipid metabolism can be modified in several status of infection. For example, experimental studies show that the cholesterol is necessary to internalization and replication of L.i.chagasi in macrophages through caveolar domains. Patients with AVL present low levels of cholesterol and a visible triglycerides increase. This work aimed to evaluate the lipid metabolism in several post-infection status by L.i.chagasi, including individuals with symptomatic infection (AVL), and asymptomatic. The levels of cholesterol, triglycerides, HDL and reactive C protein, were measured. Individuals with AVL were compared with individuals with assymptomatic infection and presented low levels of total cholesterol (128 ± 6.180 mg/dL vs. 158 ±5.733 mg/dL, p=0.0001), HDL (29 ± 1.746 mg/dL vs. 37 ± 1.647 mg/dL, p=0.0001), increased levels of triglycerides (149.5 mg/dL ± 12.72 vs. 78.00 ± 10.43 mg/dL, p=0.0095) and higher levels of reactive C protein (1.750± 0.4939 mg/dL vs. 0.40 ± 0.1707 mg/dL; p=0.0001). The expression of genes related to lipid metabolism, such as LXR-a, LXR-b, PPAR-a, PPAR-d, PPAR-g and APOE was evaluated by real time PCR. A reduction in the expression of those genes was found in the group of AVL patients corroborating the serum levels of the metabolites earlier quantified. Our findings suggest a modulation of metabolism of lipids, in the chronic phase of AVL, this could facilitate the survival of leishmania, due to the known reduction on the ability of macrophages in presenting antigens efficiently to the T cells due to the reduction in the cholesterol available, it results in a subversion of the host immunity.

Medição e modelagem da resposta de um sensor de pig perfilométrico sob diferentes solicitações dinâmicas

Ensure the integrity of the pipeline network is an extremely important factor in the oil and gas industry. The engineering of pipelines uses sophisticated robotic inspection tools in-line known as instrumented pigs. Several relevant factors difficult the inspection of pipelines, especially in offshore field which uses pipelines with multi-diameters, radii of curvature accentuated, wall thickness of the pipe above the conventional, multi-phase flow and so on. Within this context, appeared a new instrumented Pig, called Feeler PIG, for detection and sizing of thickness loss in pipelines with internal damage. This tool was developed to overcome several limitations that other conventional instrumented pigs have during the inspection. Several factors influence the measurement errors of the pig affecting the reliability of the results. This work shows different operating conditions and provides a test rig for feeler sensors of an inspection pig under different dynamic loads. The results of measurements of the damage type of shoulder and holes in a cyclic flat surface are evaluated, as well as a mathematical model for the sensor response and their errors from the actual behavior

Análise das medidas de boa e má diversidade na construção de comitês de classificadores através de metaheurísticas de otimização multiobjetivo

Committees of classifiers may be used to improve the accuracy of classification systems, in other words, different classifiers used to solve the same problem can be combined for creating a system of greater accuracy, called committees of classifiers. To that this to succeed is necessary that the classifiers make mistakes on different objects of the problem so that the errors of a classifier are ignored by the others correct classifiers when applying the method of combination of the committee. The characteristic of classifiers of err on different objects is called diversity. However, most measures of diversity could not describe this importance. Recently, were proposed two measures of the diversity (good and bad diversity) with the aim of helping to generate more accurate committees. This paper performs an experimental analysis of these measures applied directly on the building of the committees of classifiers. The method of construction adopted is modeled as a search problem by the set of characteristics of the databases of the problem and the best set of committee members in order to find the committee of classifiers to produce the most accurate classification. This problem is solved by metaheuristic optimization techniques, in their mono and multi-objective versions. Analyzes are performed to verify if use or add the measures of good diversity and bad diversity in the optimization objectives creates more accurate committees. Thus, the contribution of this study is to determine whether the measures of good diversity and bad diversity can be used in mono-objective and multi-objective optimization techniques as optimization objectives for building committees of classifiers more accurate than those built by the same process, but using only the accuracy classification as objective of optimization

Avaliação da aplicabilidade de correlações matemáticas e redes neurais na predição de parâmetros de especificação do diesel

Diesel fuel is one of leading petroleum products marketed in Brazil, and has its quality monitored by specialized laboratories linked to the National Agency of Petroleum, Natural Gas and Biofuels - ANP. The main trial evaluating physicochemical properties of diesel are listed in the resolutions ANP Nº 65 of December 9th, 2011 and Nº 45 of December 20th, 2012 that determine the specification limits for each parameter and methodologies of analysis that should be adopted. However the methods used although quite consolidated, require dedicated equipment with high cost of acquisition and maintenance, as well as technical expertise for completion of these trials. Studies for development of more rapid alternative methods and lower cost have been the focus of many researchers. In this same perspective, this work conducted an assessment of the applicability of existing specialized literature on mathematical equations and artificial neural networks (ANN) for the determination of parameters of specification diesel fuel. 162 samples of diesel with a maximum sulfur content of 50, 500 and 1800 ppm, which were analyzed in a specialized laboratory using ASTM methods recommended by the ANP, with a total of 810 trials were used for this study. Experimental results atmospheric distillation (ASTM D86), and density (ASTM D4052) of diesel samples were used as basic input variables to the equations evaluated. The RNAs were applied to predict the flash point, cetane number and sulfur content (S50, S500, S1800), in which were tested network architectures feed-forward backpropagation and generalized regression varying the parameters of the matrix input in order to determine the set of variables and the best type of network for the prediction of variables of interest. The results obtained by the equations and RNAs were compared with experimental results using the nonparametric Wilcoxon test and Student's t test, at a significance level of 5%, as well as the coefficient of determination and percentage error, an error which was obtained 27, 61% for the flash point using a specific equation. The cetane number was obtained by three equations, and both showed good correlation coefficients, especially equation based on aniline point, with the lowest error of 0,816%. ANNs for predicting the flash point and the index cetane showed quite superior results to those observed with the mathematical equations, respectively, with errors of 2,55% and 0,23%. Among the samples with different sulfur contents, the RNAs were better able to predict the S1800 with error of 1,557%. Generally, networks of the type feedforward proved superior to generalized regression.

A infecção por Leishmania infantum chagasi altera o metabolismo lipídico do hospedeiro

American visceral leishmaniasis (AVL), caused by Leishmania infantum chagasi (L.i.chagasi), stands as a public health problem in Brazil, with human and canine cases related in all states..Lipid metabolism can be modified in several status of infection. For example, experimental studies show that the cholesterol is necessary to internalization and replication of L.i.chagasi in macrophages through caveolar domains. Patients with AVL present low levels of cholesterol and a visible triglycerides increase. This work aimed to evaluate the lipid metabolism in several post-infection status by L.i.chagasi, including individuals with symptomatic infection (AVL), and asymptomatic. The levels of cholesterol, triglycerides, HDL and reactive C protein, were measured. Individuals with AVL were compared with individuals with assymptomatic infection and presented low levels of total cholesterol (128 ± 6.180 mg/dL vs. 158 ±5.733 mg/dL, p=0.0001), HDL (29 ± 1.746 mg/dL vs. 37 ± 1.647 mg/dL, p=0.0001), increased levels of triglycerides (149.5 mg/dL ± 12.72 vs. 78.00 ± 10.43 mg/dL, p=0.0095) and higher levels of reactive C protein (1.750± 0.4939 mg/dL vs. 0.40 ± 0.1707 mg/dL; p=0.0001). The expression of genes related to lipid metabolism, such as LXR-a, LXR-b, PPAR-a, PPAR-d, PPAR-g and APOE was evaluated by real time PCR. A reduction in the expression of those genes was found in the group of AVL patients corroborating the serum levels of the metabolites earlier quantified. Our findings suggest a modulation of metabolism of lipids, in the chronic phase of AVL, this could facilitate the survival of leishmania, due to the known reduction on the ability of macrophages in presenting antigens efficiently to the T cells due to the reduction in the cholesterol available, it results in a subversion of the host immunity.