The Geometric Birnbaum-Saunders regression model with cure rate

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Bayesian outlier analysis in binary regression

We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the focus is mainly on accommodation of outliers, the proposed methodology is also able to detect them. Our approach consists of evaluating the posterior distribution of random effects included in the linear predictor. The evaluation of the posterior distributions of interest involves cumbersome integration, which is easily dealt with through stochastic simulation methods. We also discuss different specifications of prior distributions for the random effects. The potential of these strategies is compared in a real data set. The main finding is that the inclusion of extra variability accommodates the outliers, improving the adjustment of the model substantially, besides correctly indicating the possible outliers.

Expression of fibroblast growth factor receptors during development and regression of the bovine corpus luteum

There is evidence that fibroblast growth factors (FGFs) are involved in the regulation of growth and regression of the corpus luteum (CL). However, the expression pattern of most FGF receptors (FGFRs) during CL lifespan is still unknown. The objective of the present study was to determine the pattern of expression of 'B' and 'C' splice variants of FGFRs in the bovine CL. Bovine CL were collected from an abattoir and classed as corpora hemorrhagica (Stage I), developing (Stage II), developed (Stage III) or regressed (Stage IV) CL. Expression of FGFR mRNA was measured by semiquantitative reverse transcription-polymerase chain reaction and FGFR protein was localised by immunohistochemistry. Expression of mRNA encoding the 'B' and 'C' spliced forms of FGFR1 and FGFR2 was readily detectable in the bovine CL and was accompanied by protein localisation. FGFR1C and FGFR2C mRNA expression did not vary throughout CL lifespan, whereas FGFR1B was upregulated in the developed (Stage III) CL. FGFR3B, FGFR3C and FGFR4 expression was inconsistent in the bovine CL. The present data indicate that FGFR1 and FGFR2 splice variants are the main receptors for FGF action in the bovine CL.

Regression of the lateral oviducts during the larval-adult transformation of the reproductive system of Melipona quadrifasciata and Frieseomelitta varia

Toward the end of the larval phase (pre-pupa), the reproductive systems of Melipona quadrifasciata and Frieseomelitta varia workers are anatomically similar. Scanning electron microscopy showed that during this developmental phase the right and left ovaries are fused and form a heart-shaped structure located above the midgut. Each ovary is connected to the genital chamber by a long and slender lateral oviduct. During pupal development, the lateral oviducts of workers from both species become extremely reduced due to a drastic process of cell death, as shown by transmission electron microscopy. During the lateral oviduct shortening, their simple columnar epithelial cells show some signs of apoptosis in addition to necrosis. Cell death was characterized by cytoplasmic vesiculation, peculiar accumulation of glycogen, and dilation of cytoplasmic organelles such as mitochondria and rough endoplasmic reticulum. The nuclei, at first irregularly contoured, became swollen, with chromatin flocculation and various areas of condensed chromatin next to the nuclear envelope. At the end of the pupal phase, deep recesses marked the nuclei. At emergence, worker and queen reproductive systems showed marked differences, although reduction in the lateral oviducts was an event occurring in both castes. However, in queens the ovarioles increased in length and the spermatheca was larger than that of workers. At the external anatomical level, the reproductive system of workers and queens could be distinguished in the white- and pink-eyed pupal phase. The metamorphic function of the death of lateral oviduct cells, with consequent oviduct shortening, is discussed in terms of the anatomical reorganization of the reproductive system and of the ventrolateral positioning of adult worker bee ovaries. (C) 2000 Wiley-Liss, Inc.

Assessing relationships between genetic evaluations using robust regression with an application to holsteins in Uruguay

Globalization of dairy cattle breeding has created a need for international sire proofs. Some early methods for converting proofs from one population to another are based on simple linear regression. An alternative robust regression method based on the t-distribution is presented, and maximum likelihood and Bayesian techniques for analysis are described, including the situation in which some proofs are missing. Procedures were used to investigate the relationship between Holstein sire proofs obtained by two Uruguayan genetic evaluation programs. The results suggest that conversion equations developed from data including only sires having proofs in both populations can lead to distorted results, relative to estimates obtained using techniques for incomplete data. There was evidence of non-normality of regression residuals, which constitutes an additional source of bias. A robust estimator may not solve all problems, but can provide simple conversion equations that are less sensitive to outlying proofs and to departures from assumptions.

Morphometric evaluation of gingival overgrowth and regression caused by cyclosporin in rats

Cyclosporin A is a selective immunosuppressant, used in organ transplants to prevent graft rejection. Cyclosporin A can cause various side effects including gingival overgrowth. The aim of this work was to evaluate gingival overgrowth of rats treated daily with 10 mg/kg body weight of Cyclosporin A for 60 days, as well as the regression after the interruption of treatment. All rats treated with Cyclosporin A developed gingival overgrowth, with increased thickness of the epithelium, height and width of the connective tissue. The density of fibroblasts and collagen fibers also increased. Five to 90 days after the interruption of treatment with Cyclosporin A, there was a progressive reduction of the gingival volume and of collagen fibers and fibroblast densities. The reduction was more pronounced in the initial periods and after 90 days did not return to the normal values.

Antenatal corticosteroid use and clinical evolution of preterm newborn infants

Objectives: To describe the use of antenatal corticosteroid and clinical evolution of preterm babies. Methods: An observational prospective cohort study was carried out. All 463 pregnant women and their 514 newborn babies with gestational age ranging from 23 to 34 weeks, born at the Brazilian Neonatal Research Network units, were evaluated from August 1 to December 31, 2001. The data were obtained through maternal interview, analysis of medical records, and follow-up of the newborn infants. Data analysis was performed with the use of chi-square, t Student, Mann-Whitney, and ANOVA tests and multiple logistic regression, with level of significance set at 5%. Results: Treatment was directly associated with the number of prenatal visits, with maternal hypertension and with the antenatal use of tocolytic agents. Babies from treated pregnant women presented better Apgar scores at the 1st and 5th minute, reduced need for intervention in the delivery room and lower SNAPPE II. They were born with higher birth weight, longer gestational age and needed less surfactant use, ventilation, and oxygenation time. After multiple logistic regression, the use of antenatal corticosteroid independently improved birth conditions, decreased ventilation time, being related to increased occurrence of neonatal sepsis. Conclusions: The use of corticosteroid was associated with better prenatal care and birth conditions, better preterm evolution but higher risk of infection. Copyright © 2004 by Sociedade Brasileira de Pediatria.

Profile of cardiovascular risk factors and mortality in patients with symptomatic peripheral arterial disease

Introduction: The present study examines cardiovascular risk factor profiles and 24-month mortality in patients with symptomatic peripheral arterial disease. Design Study: Prospective observational study including 75 consecutive patients with PAD (67 ± 9.7 years of age; 52 men and 23 women) hospitalized for planned peripheral vascular reconstruction. Doppler echocardiograms were performed before surgery in 54 cases. Univariate analyses were performed using Student's t-test or Fisher's exact test. Survival analysis at 24-month follow-up was performed using the Cox regression model and Kaplan-Meier method including age and chronic use of aspirin as covariates. Survival curves were compared using the log-rank test. Results: Hypertension and smoking were the most frequent risk factors (52 cases and 51 cases, respectively), followed by diabetes (32 cases). Undertreated dyslipidemia was found in 26 cases. Fasting glycine levels (131 ± 69.1 mg/dl) were elevated in 29 cases. Myocardial hypertrophy was found in 18 out of 54 patients. Thirty-four patients had been treated with aspirin. Overall mortality over 24 months was 24% and was associated with age (HR: 0.064; CI95: 0.014-0.115; p=0.013) and lack of use of aspirin, as no deaths occurred among those using this drug (p<0.001). No association was found between cardiovascular death (11 cases) and the other risk factors. Conclusion: There is a high prevalence of uncontrolled (treated or untreated) cardiovascular risk factors in patients undergoing planned peripheral vascular reconstruction, and chronic use of aspirin is associated with reduced all-cause mortality in these patients.

Preprocessing data for short-term load forecasting with a general regression neural network and a moving average filter

This paper proposes a filter based on a general regression neural network and a moving average filter, for preprocessing half-hourly load data for short-term multinodal load forecasting, discussed in another paper. Tests made with half-hourly load data from nine New Zealand electrical substations demonstrate that this filter is able to handle noise, missing data and abnormal data. © 2011 IEEE.

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

Expression of opg, rank, and rankl proteins in tooth repair processes after immediate and delayed tooth

This study evaluated the immunohistochemical expression of OPG, RANK, and RANKL proteins in the repair after immediate and delayed replantation of rat teeth. Fifty-six Wistar rats (Rattus norvegicus albinus) had their maxillary right lateral incisor extracted and then replanted, according to the following conditions: group I (control; n = 8), teeth were not extracted; group II (n = 16), immediate replantation; group III (n = 16), delayed replantation without treatment; and group IV (n = 16), delayed replantation after root surface treatment (periodontal ligament removal and immersion in 2% acidulated-phosphate sodium fluoride) and calcium hydroxide intracanal dressing. Rats in group I were euthanized on the first day of the experiment, while the animals in the other groups were euthanized 10 and 60 days after replantation (n = 8/period). Hematoxylin and eosin-stained sections were obtained for histological analysis. The immunohistochemical analysis revealed expression of OPG and RANKL proteins in all groups and both postreplantation times, except for group II at 60 days. In the experimental groups, RANK expression was observed only at 10 days. In conclusion, there was strong immunostaining for the OPG-RANK-RANKL system at the earlier postreplantation time, suggesting a more effective participation of these proteins at the start of the healing process, as their expression decreased at 60 days. Copyright © 2013 by Mutaz B. Habal, MD.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.