The influence of maternal factors on the concentration of vitamin A in mature breast milk

Background & aims: This study evaluated the relationship between vitamin A concentration in maternal milk and the characteristics of the donors of a Brazilian human milk bank. Material and methods: A total of 136 donors were selected in 2003-2004 for micronutrient determinations in breast milk and blood, anthropometric measurements and investigation of obstetric, socioeconomic-demographic factors, and life style. Maternal serum/milk samples were obtained for vitamin A, iron, copper, and zinc determinations. Vitamin A concentrations in breast milk and blood were assessed by high-performance liquid chromatography. Copper, zinc and iron concentrations in breast milk, and copper and zinc concentrations in blood were detected by atomic emission spectrophotometry. Serum ceruloplasmin and serum iron were determined, respectively, by nephelometry and colorimetry. A linear regression model assessed the associations between milk concentrations of vitamin A and maternal factors. Results: Vitamin A in milk presented positive associations with iron in milk (p < 0.001), serum retinol (p = 0.03), maternal work (p = 0.02), maternal age (p = 0.02). and oral contraceptive use (p = 0.01), and a negative association with % body fat (p = 0.01) (R(2) = 0.47). Conclusion: These results suggest that some nutritional, obstetric, and socioeconomic-demographic factors may have an effect on mature breast milk concentrations of vitamin A in apparently healthy Brazilian mothers. (C) 2009 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Effect of inbreeding on growth and reproductive traits of Nellore cattle in Brazil

The objective of this study was to identify and quantify the influence of F (inbreeding coefficient) on weaning weight (WW), weight gain from weaning to 18 months of age (WG345), finishing visual score (precocity) at 18 months of age, muscling visual score at 18 months of age (MUS), hip height (HH), scrotal circumference at 18 months of age (SC), heifer probability of pregnancy at 14 months of age (PP14), and stayability (STAY) in Brazilian Nellore cattle. The complete pedigree included 417,552 animals born between 1984 and 2007 on 12 farms located in the states of Mato Grosso do Sul, Sao Paulo and Bahia. Following the observation of a statistically significant effect (P<0.05) of the covariates individual inbreeding coefficient (F) and maternal inbreeding coefficient, regression analysis of each trait, adjusted for all other effects, was performed as a function of the linear and quadratic effect of F and maternal F (when significant). Inbreeding negatively affected all traits studied (P<0.05), except for muscling. A quadratic effect of individual F on WW, WG345, HH and PP14, and a quadratic effect of maternal F on WG345 and HH were observed. Levels of inbreeding higher than 7-11% affected negatively growth and reproductive performance of Nellore cattle. Therefore, inbreeding should be avoided, except for purposes of genetic breeding whose main objective is the fixation of certain alleles in the population. (C) 2010 Elsevier B.V. All rights reserved.

Non-stationary frequency analysis of extreme daily rainfall in Sao Paulo, Brazil

This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of Sao Paulo. Brazil, over the period 1933-2005, based on the peaks-over-threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually. a GPD model is fitted to a sample of POT Values Selected With a constant threshold. However. in this work we use time-dependent thresholds, composed of relatively large p quantities (for example p of 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several Values of p. Four different GPD models (GPD-1, GPD-2, GPD-3. and GDP-4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time-varying covariates were incorporated into scale parameter of GPD-2. GPD-3, and GPD-4, describing annual cycle in GPD-2. linear trend in GPD-3, and both annual cycle and linear trend in GPD-4. The GPD-1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models WC used rescaled Akaike Information Criterion (AIC) with second-order bias correction. This criterion isolates GPD-3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non-parametric Mann-Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds. with p-value being virtually zero. Therefore. there is strong evidence that high quantiles of daily rainfall in the city of Sao Paulo have been increasing in magnitude and frequency over time. For example. 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright (C) 2008 Royal Meteorological Society

Factors associated with health-related quality of life after successful kidney transplantation: a population-based study

Kidney transplantation improves the quality of life of end-stage renal disease patients. The quality of life benefits, however, pertain to patients on average, not to all transplant recipients. The aim of this study was to identify factors associated with health-related quality of life after kidney transplantation. Population-based study with a cross-sectional design was carried out and quality of life was assessed by SF-36 Health Survey Version 1. A multivariate linear regression model was constructed with sociodemographic, clinical and laboratory data as independent variables. Two hundred and seventy-two kidney recipients with a functioning graft were analyzed. Hypertension, diabetes, higher serum creatinine and lower hematocrit were independently and significantly associated with lower scores for the SF-36 oblique physical component summary (PCSc). The final regression model explained 11% of the PCSc variance. The scores of oblique mental component summary (MCSc) were worse for females, patients with a lower income, unemployed and patients with a higher serum creatinine. The regression model explained 9% of the MCSc variance. Among the studied variables, comorbidity and graft function were the main factors associated with the PCSc, and sociodemographic variables and graft function were the main determinants of MCSc. Despite comprehensive, the final regression models explained only a little part of the heath-related quality of life variance. Additional factors, such as personal, environmental and clinical ones might influence quality of life perceived by the patients after kidney transplantation.

Small-Sample Corrections for Score Tests in Birnbaum-Saunders Regressions

In this article, we deal with the issue of performing accurate small-sample inference in the Birnbaum-Saunders regression model, which can be useful for modeling lifetime or reliability data. We derive a Bartlett-type correction for the score test and numerically compare the corrected test with the usual score test and some other competitors.

Improved likelihood inference in Birnbaum-Saunders regressions

The Birnbaum-Saunders regression model is commonly used in reliability studies. We address the issue of performing inference in this class of models when the number of observations is small. Our simulation results suggest that the likelihood ratio test tends to be liberal when the sample size is small. We obtain a correction factor which reduces the size distortion of the test. Also, we consider a parametric bootstrap scheme to obtain improved critical values and improved p-values for the likelihood ratio test. The numerical results show that the modified tests are more reliable in finite samples than the usual likelihood ratio test. We also present an empirical application. (C) 2009 Elsevier B.V. All rights reserved.

Distribution of ABCB1 polymorphisms among Brazilians: impact of population admixture

Introduction: Interethnic admixture is a source of cryptic population structure that may lead to spurious genotype-phenotype associations in pharmacogenomic studies. We studied the impact of population stratification on the distribution of ABCB1 polymorphisms (1236C > T, 2677G > T/A and 3435C > T) among Brazilians, a highly admixed population with Amerindian, European and African ancestral roots. Methods: Individual DNA from 320 healthy adults was genotyped with a panel of ancestry informative markers, and the proportions of African component of ancestry (ACA) were estimated. ABCB1 genotypes were determined by the single base extension/termination method. We describe the association between ABCB1 polymorphisms and ACA by fitting a linear proportional odds logistic regression model to the data. Results: The distribution of the ABCB1 2677G > T/A and 3435C > T, but not the 1236C > T, SNPs displayed a significant trend for decreasing frequency of the T alleles and TT genotypes from White to Intermediate to Black individuals. The same trend was observed in the frequency of the T/nonG/T haplotype at the 1236, 2677 and 3435 loci. When the population sample was proportioned in quartiles, according to the individual ACA estimates, the frequency of the T allele and TT genotype at each locus declined progressively from the lowest (< 0.25 ACA) to the highest (> 0.75 ACA) quartile. Linear proportional odds logistic regression analysis confirmed that the odds of having the T allele at each locus decreases in a continuous manner with the increase of the ACA, throughout the ACA range (0.13-0.94) observed in the overall population sample. A significant association was also detected between the individual ACA estimates and the presence of the T/nonG/T haplotype in the overall population. Conclusion: Self-identification according to the racial/color categories proposed by the Brazilian Census is insufficient to properly control for population stratification in pharmacogenomic studies of ABCB1.

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).