Distribution of CCR2-64I and SDF1-3 ' A alleles and HIV status in 7 ethnic populations of Cameroon

Limited information is available on the prevalence among rural Africans of host genetic polymorphisms conferring resistance to HIV-1 infection or slowing HIV disease progression.We report the allelic frequencies of the AIDS-related polymorphisms CCR2-64I, SDF1-3#A, and CCR5-D32 in 321 volunteers from 7 ethnic groups in Cameroon. Allelic frequencies differed among the 7 ethnic groups, ranging from 10.8% to 31.3% for CCR2-64I and 0.0% to 7.1% for SDF1-3#A. No CCR5-D32 alleles were found. HIV seroprevalence was 6.9% in the total population and peaked at younger ages in girls and women than in boys and men. Among 15- to 54-year-olds, HIV seroprevalence varied from 2.0% to 11.1% among the village populations. Conditional logistic regression analysis using data from boys and men aged 15 to 54 years showed the number of CCR2-64I alleles to be a significant risk factor for HIV seropositivity (odds ratio per allele adjusted for age and matched on ethnic group = 6.3, 95% confidence interval: 1.3–30.3); this association was not found in women. The findings are consistent with the hypothesis that CCR2-64I alleles may delay HIV disease progression without affecting susceptibility to infection among men. We did not observe this relation among women, and other factors, such as multiple pregnancies or maternal stressors (eg, breastfeeding), may have masked any protective effect of CCR2-64I alleles. Further study of this issue among women is warranted. SDF1-3#A did not differ between HIV-seropositive and HIV-seronegative individuals but wasassociated with increasing age among HIV-seronegative women, suggesting a protective effect against HIV-1 infection.

Selection for variables in quantitative structure-activity/property relationship studies - Comparison between methods of orthogonal descriptors and leaps-and-bounds regression analysis

In this paper, the comparison of orthogonal descriptors and Leaps-and-Bounds regression analysis is performed. The results obtained by using orthogonal descriptors are better than that obtained by using Leaps-and-Bounds regression for the data set of nitrobenzenes used in this study. Leaps-and-Bounds regression can be used effectively for selection of variables in quantitative structure-activity/property relationship(QSAR/QSPR) studies. Consequently, orthogonalisation of descriptors is also a good method for variable selection for studies on QSAR/QSPR.

Prediction of molar absorptivities of color reagents during their color reactions with cerium using multiple regression analysis and neural network

A quantitative structure-property study has been made on the relationship between molar absorptivities (epsilon) of asymmetrical phosphone bisazo derivatives of chromotropic acid and their color reactions with cerium by multiple regression analysis and neural network. The new topological indices A(x1) - A(x3) suggested in our laboratory and molecular connectivity indices of 43 compounds have been calculated. The results obtained from the two methods are compared. The neural network model is superior to the regression analysis technique and gave a prediction which was sufficiently accurate to estimate the molar absorptivities of color reagents during their color reactions with cerium.

Quantitative structure-property relationships for colour reagents and their colour reactions with ytterbium using regression analysis and computational neural networks

In this paper, the new topological indices A(x1)-A(x3) suggested in our laboratory and molecular connectivity indices have been applied to multivariate analysis in structure-property studies. The topological indices of twenty asymmetrical phosphono bisazo derivatives of chromotropic acid have been calculated. The structure-property relationships between colour reagents and their colour reactions with ytterbium have been studied by A(x1)-A(x3) indices and molecular connectivity indices with satisfactory results. Multiple regression analysis and neural networks were employed simultaneously in this study.

QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS FOR TOXICITY OF PHENOLS USING REGRESSION-ANALYSIS AND COMPUTATIONAL NEURAL NETWORKS

Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor