Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

The zero-inflated Conway-Maxwell-Poisson distribution: Bayesian inference, regression modeling and influence diagnostic

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Method validation using weighted linear regression models for quantification of UV filters in water samples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Two periods of total testicular regression are peculiar events of the annual reproductive cycle of the black Myotis bat, Myotis nigricans (Chiroptera: Vespertilionidae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A note on model uncertainty in linear regression

We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.

Random regression models using different functions to model milk flow in dairy cows

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Response of pullets to digestible lysine intake

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multicollinearity and financial constraint in investment decisions: a bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Comparação entre o Disease Activity Score-28 e o Juvenile Arthritis Disease Activity Score na artrite idiopática juvenil

Introduction: the assessment of the activity of rheumatoid arthritis and juvenile idiopathic arthritis is made by means of different tools, respectively DAS-28 and JADAS.Objective: To compare DAS-28 and JADAS with scores of 71, 27 and 10 joint counts in juvenile idiopathic arthritis.Method: A secondary analysis of a phase III placebo-controlled trial, testing safety and efficacy of abatacept was conducted in 8 patients with 178 assessment visits. Joint count scores for active and limited joints, physician's and parents'global assessment by 0-10 cm Visual Analog Scale, and erythrocyte sedimentation rate normalized to 0-10 scale, in all visits. The comparison among the activity indices in different observations was made through Anova or adjusted gamma model. The paired observations between DAS-28 and JADAS 71, 27 and 10, respectively, were analyzed by linear regression.Results: There were significant differences among individual measures, except for ESR, in the first four months of biological treatment, when five of the eight patients reached ACR-Pedi 30, with improvement. The indices of DAS-28, JADAS 71, 27 and 10 also showed significant difference during follow-up. Linear regression adjusted model between DAS-28 and JADAS resulted in mathematical formulas for conversion: [DAS-28 = 0.0709 (JADAS 71) + 1.267] (R-2 = 0.49); [DAS-28 = 0.084 (JADAS 27) + 1.7404] (R-2 = 0.47) and [DAS-28 = 0.1129 (JADAS-10) + 1.5748] (R-2 = 0.50).Conclusion: The conversion of scores of DAS-28 and JADAS 71, 27 and 10 for this mathematical model would allow equivalent application of both in adolescents with arthritis. (C) 2014 Elsevier Editora Ltda. All rights reserved.

Impact of the processes of testicular regression and recrudescence in the prostatic complex of the bat myotis nigricans (Chiroptera: Vespertilionidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Impact of the processes of total testicular regression and recrudescence on the epididymal physiology of the bat myotis nigricans (chiroptera: vespertilionidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Prevalence of Treponema Species Detected in Endodontic Infections: Systematic Review and Meta-regression Analysis

Introduction: This systematic review and meta-regression analysis aimed to calculate a combined prevalence estimate and evaluate the prevalence of different Treponema species in primary and secondary endodontic infections, including symptomatic and asymptomatic eases. Methods: The MEDLINE/PubMed, Embase, Scielo, Web of Knowledge, and Scopus data-bases were searched without starting date restriction up to and including March 2014. Only reports in English were included. The selected literature was reviewed by 2 authors and classified as suitable or not to be included in this review. Lists were compared, and, in case of disagreements, decisions were made after a discussion based on inclusion and exclusion criteria. A pooled prevalence of Treponema species in endodontic infections was estimated. Additionally, a meta-regression analysis was performed. Results: Among the 265 articles identified in the initial search, only 51 were included in the final analysis. The studies were classified into 2 different groups according to the type of endodontic infection and whether it was an exclusively primary/secondary study (n = 36) or a primary/secondary comparison (n = 15). The pooled prevalence of Treponema species was 41.5% (95% confidence interval, 35.9-47.0). In the multivariate model of meta-regression analysis, primary endodontic infections (P < .001), acute apical abscess, symptomatic apical periodontitis (P < .001), and concomitant presence of 2 or more species (P = .028) explained the heterogeneity regarding the prevalence rates of Treponema species. Conclusions: Our findings suggest that Treponema species are important pathogens involved in endodontic infections, particularly in cases of primary and acute infections.

Mathematical modeling of a continuous alcoholic fermentation process in a two-stage tower reactor cascade with flocculating yeast recycle

Experiments of continuous alcoholic fermentation of sugarcane juice with flocculating yeast recycle were conducted in a system of two 0.22-L tower bioreactors in series, operated at a range of dilution rates (D (1) = D (2) = 0.27-0.95 h(-1)), constant recycle ratio (alpha = F (R) /F = 4.0) and a sugar concentration in the feed stream (S (0)) around 150 g/L. The data obtained in these experimental conditions were used to adjust the parameters of a mathematical model previously developed for the single-stage process. This model considers each of the tower bioreactors as a perfectly mixed continuous reactor and the kinetics of cell growth and product formation takes into account the limitation by substrate and the inhibition by ethanol and biomass, as well as the substrate consumption for cellular maintenance. The model predictions agreed satisfactorily with the measurements taken in both stages of the cascade. The major differences with respect to the kinetic parameters previously estimated for a single-stage system were observed for the maximum specific growth rate, for the inhibition constants of cell growth and for the specific rate of substrate consumption for cell maintenance. Mathematical models were validated and used to simulate alternative operating conditions as well as to analyze the performance of the two-stage process against that of the single-stage process.

Random regression models for milk, fat and protein in Colombian Buffaloes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)