Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

DNA repair gene excision repair cross complementing-group 1 (ERCC1) in head and neck squamous cell carcinoma: analysis of methylation and polymorphism (G19007A), protein expression and association with epidemiological and clinicopathological factors

Aims: To evaluate the associations of excision repair cross complementing-group 1 (ERCC1) (DNA repair protein) (G19007A) polymorphism, methylation and immunohistochemical expression with epidemiological and clinicopathological factors and with overall survival in head and neck squamous cell carcinoma (HNSCC) patients. Methods and results: The study group comprised 84 patients with HNSCC who underwent surgery and adjuvant radiotherapy without chemotherapy. Bivariate and multivariate analyses were used. The allele A genotype variant was observed in 79.8% of the samples, GG in 20.2%, GA in 28.6% and AA in 51.2%. Individuals aged more than 45 years had a higher prevalence of the allelic A variant and a high (83.3%) immunohistochemical expression of ERCC1 protein [odds ratio (OR) = 4.86, 95% confidence interval (CI): 1.2-19.7, P = 0.027], which was also high in patients with advanced stage (OR= 5.04, 95% CI: 1.07-23.7, P = 0.041). Methylated status was found in 51.2% of the samples, and was higher in patients who did not present distant metastasis (OR = 6.67, 95% CI: 1.40-33.33, P = 0.019) and in patients with advanced stage (OR = 5.04, 95% CI: 1.07-23.7, P = 0.041). At 2 and 5 years, overall survival was 55% and 36%, respectively (median = 30 months). Conclusion: Our findings may reflect a high rate of DNA repair due to frequent tissue injury during the lifetime of these individuals, and also more advanced disease presentation in this population with worse prognosis.

Longitudinal familial analysis of blood pressure involving parametric (co)variance functions

Abstract Background For analyzing longitudinal familial data we adopted a log-linear form to incorporate heterogeneity in genetic variance components over the time, and additionally a serial correlation term in the genetic effects at different levels of ages. Due to the availability of multiple measures on the same individual, we permitted environmental correlations that may change across time. Results Systolic blood pressure from family members from the first and second cohort was used in the current analysis. Measures of subjects receiving hypertension treatment were set as censored values and they were corrected. An initial check of the variance and covariance functions proposed for analyzing longitudinal familial data, using empirical semi-variogram plots, indicated that the observed trait dispersion pattern follows the assumptions adopted. Conclusion The corrections for censored phenotypes based on ordinary linear models may be an appropriate simple model to correct the data, ensuring that the original variability in the data was retained. In addition, empirical semi-variogram plots are useful for diagnosis of the (co)variance model adopted.

What drives the seasonality of photosynthesis across the Amazon basin? A cross-site analysis of eddy flux tower measurements from the Brasil flux network

We investigated the seasonal patterns of Amazonian forest photosynthetic activity, and the effects thereon of variations in climate and land-use, by integrating data from a network of ground-based eddy flux towers in Brazil established as part of the ‘Large-Scale Biosphere Atmosphere Experiment in Amazonia’ project. We found that degree of water limitation, as indicated by the seasonality of the ratio of sensible to latent heat flux (Bowen ratio) predicts seasonal patterns of photosynthesis. In equatorial Amazonian forests (5◦ N–5◦ S), water limitation is absent, and photosynthetic fluxes (or gross ecosystem productivity, GEP) exhibit high or increasing levels of photosynthetic activity as the dry season progresses, likely a consequence of allocation to growth of new leaves. In contrast, forests along the southern flank of the Amazon, pastures converted from forest, and mixed forest-grass savanna, exhibit dry-season declines in GEP, consistent with increasing degrees of water limitation. Although previous work showed tropical ecosystem evapotranspiration (ET) is driven by incoming radiation, GEP observations reported here surprisingly show no or negative relationships with photosynthetically active radiation (PAR). Instead, GEP fluxes largely followed the phenology of canopy photosynthetic capacity (Pc), with only deviations from this primary pattern driven by variations in PAR. Estimates of leaf flush at three