Evaluation of Adult Chronic Chagas` Heart Disease Diagnosis by Molecular and Serological Methods

Chagas` disease caused by Trypanosoma cruzi is endemic in Latin America. T. cruzi presents heterogeneous populations and comprises two main genetic lineages, named T. cruzi I and T. cruzi II. Diagnosis in the chronic phase is based on conventional serological tests, including indirect immunofluorescence (IIF) and enzyme-linked immunosorbent assay (ELISA), and diagnosis in the acute phase based on parasitological methods, including hemoculture. The objective of this study was to evaluate the diagnostic procedures of Chagas` disease in adult patients in the chronic phase by using a PCR assay and conventional serological tests, including TESA-blot as the gold standard. Samples were obtained from 240 clinical chronic chagasic patients. The sensitivities, compared to that of TESA-blot, were 70% for PCR using the kinetoplast region, 75% for PCR using the nuclear repetitive region, 99% for IIF, and 95% for ELISA. According to the serological tests results, we recommend that researchers assess the reliability and sensitivity of the commercial kit Chagatest ELISA recombinant, version 3.0 (Chagatest Rec v3.0; Wiener Lab, Rosario, Argentina), due to the lack of sensitivity. Based on our analysis, we concluded that PCR cannot be validated as a conventional diagnostic technique for Chagas` disease. These data have been corroborated by low levels of concordance with serology test results. It is recommended that PCR be used only for alternative diagnostic support. Using the nuclear repetitive region of T. cruzi, PCR could also be applicable for monitoring patients receiving etiologic treatment.

Evaluation of computational methods for the reconstruction of HLA haplotypes

Human leukocyte antigen (HLA) haplotypes are frequently evaluated for population history inferences and association studies. However, the available typing techniques for the main HLA loci usually do not allow the determination of the allele phase and the constitution of a haplotype, which may be obtained by a very time-consuming and expensive family-based segregation study. Without the family-based study, computational inference by probabilistic models is necessary to obtain haplotypes. Several authors have used the expectation-maximization (EM) algorithm to determine HLA haplotypes, but high levels of erroneous inferences are expected because of the genetic distance among the main HLA loci and the presence of several recombination hotspots. In order to evaluate the efficiency of computational inference methods, 763 unrelated individuals stratified into three different datasets had their haplotypes manually defined in a family-based study of HLA-A, -B, -DRB1 and -DQB1 segregation, and these haplotypes were compared with the data obtained by the following three methods: the Expectation-Maximization (EM) and Excoffier-Laval-Balding (ELB) algorithms using the arlequin 3.11 software, and the PHASE method. When comparing the methods, we observed that all algorithms showed a poor performance for haplotype reconstruction with distant loci, estimating incorrect haplotypes for 38%-57% of the samples considering all algorithms and datasets. We suggest that computational haplotype inferences involving low-resolution HLA-A, HLA-B, HLA-DRB1 and HLA-DQB1 haplotypes should be considered with caution.

Comparative analysis of two immunohistochemical methods for antigen retrieval in the optical lobe of the honeybee Apis mellifera: Myosin-v assay

The present study compared two heating methods currently used for antigen retrieval (AR) immunostaining: the microwave oven and the steam cooker. Myosin-V, a molecular motor involved in vesicle transport, was used as a neuronal marker in honeybee Apis mellifera brains fixed in formalin. Overall, the steam cooker showed the most satisfactory AR results. At 100 degrees C, tissue morphology was maintained and revealed epitope recovery, while evaporation of the AR solution was markedly reduced; this is important for stabilizing the sodium citrate molarity of the AR buffer and reducing background effects. Standardization of heat-mediated AR of formalin-fixed and paraffin-embedded tissue sections results in more reliable immunostaining of the honeybee brain.

Methods for exploring the morpho-functional relations of the aortic depressor nerve in experimental diabetes

The present study investigated morpho-functional relations of the aortic depressor nerve (ADN) 5, 15 and 120 days after the onset of streptozotocin-induced diabetes in rats. Time control animals received vehicle. Under pentobarbital anesthesia, ADN activity was recorded simultaneously with arterial pressure. After the recordings, nerves were prepared for light microscopy study and morphometry. ADN function was accessed by means of pressure-nerve activity curve (fitted by sigmoidal regression) and cross-spectral analysis between mean arterial pressure (MAP) and ADN activity. The relation between morphological (myelinated fibers number and density, total myelin area, total fiber area and percentage of occupancy) and functional (gain, signal/noise relation, frequency) parameters were accessed by linear regression analysis and correlation coefficient calculations. Functional parameters obtained by means of the sigmoidal regression curve as well as by cross-spectral analysis were similar in diabetic and control rats. Morphometric parameters of the ADN were similar between groups 5 days after the onset of diabetes. Average myelin area and myelinated fiber area were significantly smaller on diabetic rats 15 and 120 days after the onset of diabetes, being the myelinated fiber and respective axons area and diameter also smaller on 120 days group. Nevertheless, G ratio (ratio between axon and fiber diameter) was nearly 0.6 and not different between groups or experimental times. No significant relationship between morphological and functional parameters was detected in all experimental groups. The present study suggests that ADN diabetic neuropathy was time-dependent, with damage to myelinated fibers to be the primary event, not evidenced by physiological methods. (C) 2010 Elsevier B.V. All rights reserved.

Comparison of different nonlinear functions to describe Nelore cattle growth

This work aims to compare different nonlinear functions for describing the growth curves of Nelore females. The growth curve parameters, their (co) variance components, and environmental and genetic effects were estimated jointly through a Bayesian hierarchical model. In the first stage of the hierarchy, 4 nonlinear functions were compared: Brody, Von Bertalanffy, Gompertz, and logistic. The analyses were carried out using 3 different data sets to check goodness of fit while having animals with few records. Three different assumptions about SD of fitting errors were considered: constancy throughout the trajectory, linear increasing until 3 yr of age and constancy thereafter, and variation following the nonlinear function applied in the first stage of the hierarchy. Comparisons of the overall goodness of fit were based on Akaike information criterion, the Bayesian information criterion, and the deviance information criterion. Goodness of fit at different points of the growth curve was compared applying the Gelfand`s check function. The posterior means of adult BW ranged from 531.78 to 586.89 kg. Greater estimates of adult BW were observed when the fitting error variance was considered constant along the trajectory. The models were not suitable to describe the SD of fitting errors at the beginning of the growth curve. All functions provided less accurate predictions at the beginning of growth, and predictions were more accurate after 48 mo of age. The prediction of adult BW using nonlinear functions can be accurate when growth curve parameters and their (co) variance components are estimated jointly. The hierarchical model used in the present study can be applied to the prediction of mature BW in herds in which a portion of the animals are culled before adult age. Gompertz, Von Bertalanffy, and Brody functions were adequate to establish mean growth patterns and to predict the adult BW of Nelore females. The Brody model was more accurate in predicting the birth weight of these animals and presented the best overall goodness of fit.

A Comparison of Bayesian and Sampling Theory Inferences in a Probit Model

HE PROBIT MODEL IS A POPULAR DEVICE for explaining binary choice decisions in econometrics. It has been used to describe choices such as labor force participation, travel mode, home ownership, and type of education. These and many more examples can be found in papers by Amemiya (1981) and Maddala (1983). Given the contribution of economics towards explaining such choices, and given the nature of data that are collected, prior information on the relationship between a choice probability and several explanatory variables frequently exists. Bayesian inference is a convenient vehicle for including such prior information. Given the increasing popularity of Bayesian inference it is useful to ask whether inferences from a probit model are sensitive to a choice between Bayesian and sampling theory techniques. Of interest is the sensitivity of inference on coefficients, probabilities, and elasticities. We consider these issues in a model designed to explain choice between fixed and variable interest rate mortgages. Two Bayesian priors are employed: a uniform prior on the coefficients, designed to be noninformative for the coefficients, and an inequality restricted prior on the signs of the coefficients. We often know, a priori, whether increasing the value of a particular explanatory variable will have a positive or negative effect on a choice probability. This knowledge can be captured by using a prior probability density function (pdf) that is truncated to be positive or negative. Thus, three sets of results are compared:those from maximum likelihood (ML) estimation, those from Bayesian estimation with an unrestricted uniform prior on the coefficients, and those from Bayesian estimation with a uniform prior truncated to accommodate inequality restrictions on the coefficients.

Evaluation of lignin contents in tropical forages using different analytical methods and their correlations with degradation of insoluble fiber

We compared the lignin contents of tropical forages by different analytical methods and evaluated their correlations with parameters related to the degradation of neutral detergent fiber (NDF). The lignin content was evaluated by five methods: cellulose solubilization in sulfuric acid [Lignin (sa)], oxidation with potassium permanganate [Lignin (pm)], the Klason lignin method (KL), solubilization in acetyl bromide from acid detergent fiber (ABLadf) and solubilization in acetyl bromide from the cell wall (ABLcw). Samples from ten grasses and ten legumes were used. The lignin content values obtained by gravimetric methods were also corrected for protein contamination, and the corrected values were referred to as Lignin (sa)p, Lignin (pm)p and KLp. The indigestible fraction of NDF (iNDF), the discrete lag (LAG) and the fractional rate of degradation (kd) of NDF were estimated using an in vitro assay. Correcting for protein resulted in reductions (P < 0.05) in the lignin contents as measured by the Lignin (sa), Lignin (pm) and, especially, the KL methods. There was an interaction (P < 0.05) of analytical method and forage group for lignin content. In general, LKp method provided the higher (P < 0.05) lignin contents. The estimates of lignin content obtained by the Lignin (sa)p, Lignin (pm)p and LKp methods were associated (P > 0.05) with all of the NDF degradation parameters. However, the strongest correlation coefficients for all methods evaluated were obtained with Lignin (pm)p and KLp. The lignin content estimated by the ABLcw method did not correlate (P > 0.05) with any parameters of NDF degradation. There was a correlation (P < 0.05) between the lignin content estimated by the ABLadf method and iNDF content. Nonetheless, this correlation was weaker than those found with gravimetric methods. From these results, we concluded that the gravimetric methods produce residues that are contaminated by nitrogenous compounds. Adjustment for these contaminants is suggested, particularly for the KL method, to express lignin content with greater accuracy. The relationships between lignin content measurements and NDF degradation parameters can be better determined using KLp and Lignin (pm)p methods. (C) 2011 Elsevier B.V. All rights reserved.