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.

Ovarian function in Nelore (Bos taurus indicus) cows after post-ovulation hormonal treatments

Maternal recognition of pregnancy in the cow requires successful signaling by the conceptus to block luteolysis. Conceptus Growth and function depend on an optimal uterine environment, regulated by luteal progesterone. The objective of this study was to test strategies to optimize luteal function, as well as prevent a dominant follicle from initiating luteolysis. Nelore (Bos taurus indicus) beef cows (n = 40) were submitted to a GnRH/PGF(2 alpha)/GnRH protocol. Cows that ovulated from a dominant ovarian follicle (ovulation = Day 0) were allocated to receive: no additional treatment (Gc; n = 7); 3000 IU of hCG on Day 5 (G(hCG); n = 5); 5 mg of estradiol-17 beta on Day 12 (G(E2); n = 6); or 3000 IU of hCG on Day 5 and 5 mg of estradiol-17 beta on Day 12 (G(hCG/E2); n = 5). Ultrasonographic imaging of the ovaries, assessment of plasma progesterone concentration, and detection of estrus were done daily from Day 5 to the day of subsequent ovulation. Treatment with hCG induced an accessory CL, increased CL volume, and plasma progesterone concentration throughout the luteal phase (P < 0.01). Estradiol-17 beta induced atresia and recruitment of a new wave of follicular growth; it eliminated a potentially estrogen-active, growing ovarian follicle within the critical period for maternal recognition of pregnancy, but it also hastened luteolysis (Days 16 or 17 vs. Days 18 or 19 in non-treated cows). In conclusion, the approaches tested enhanced luteal function (hCG) and altered ovarian follicular dynamics (estradiol-17 beta), but were unable to extend the life-span of the CL in Nelore cows. (c) 2008 Elsevier Inc. All rights reserved.

Reproductive behavior, development and eye regression in the cave armored catfish, Ancistrus cryptophthalmus Reis, 1987 (Siluriformes: Loricariidae), breed in laboratory

The troglobitic armored catfish, Ancistrus cryptophthalmus (Loricariidae, Ancistrinae) is known from four caves in the São Domingos karst area, upper rio Tocantins basin, Central Brazil. These populations differ in general body shape and degree of reduction of eyes and of pigmentation. The small Passa Três population (around 1,000 individuals) presents the most reduced eyes, which are not externally visible in adults. A small group of Passa Três catfish, one male and three females, reproduced spontaneously thrice in laboratory, at the end of summertime in 2000, 2003 and 2004. Herein we describe the reproductive behavior during the 2003 event, as well as the early development of the 2003 and 2004 offsprings, with focus on body growth and ontogenetic regression of eyes. The parental care by the male, which includes defense of the rock shelter where the egg clutch is laid, cleaning and oxygenation of eggs, is typical of many loricariids. On the other hand, the slow development, including delayed eye degeneration, low body growth rates and high estimated longevity (15 years or more) are characteristic of precocial, or K-selected, life cycles. In the absence of comparable data for close epigean relatives (Ancistrus spp.), it is not possible to establish whether these features are an autapomorphic specialization of the troglobitic A. cryptophthalmus or a plesiomorphic trait already present in the epigean ancestor, possibly favoring the adoption of the life in the food-poor cave environment. We briefly discuss the current hypotheses on eye regression in troglobitic vertebrates.

Desenvolvimento morfológico dos ovários em fetos eqüinos sem raça definida

O objetivo deste trabalho foi caracterizar histologicamente o desenvolvimento ovariano pré-natal em fetos eqüinos sem raça definida (SRD) nos trópicos, ressaltando surgimento e quantificação de ovogônias e folículos. Foram obtidos 131 fetos em frigorífico, os quais foram mensurados quanto ao comprimento (cm) equivalente à distância cefalococcígea (CR), seguido de corte das gônadas e fixação das amostras em Bouin por 24 horas. As idades foram estimadas por regressão. Foram preparados cortes histológicos ovarianos de 7µm de espessura, os quais foram corados com hematoxilina-eosina. O surgimento de ovogônias, folículos primordiais, em crescimento e antrais foi verificado, respectivamente, em fetos com CR entre 4,1 e 6,5cm (40 a 49 dias de gestação (DG)); 9,1 e 12,0cm (60 a 69 DG); 23,1 e 29,0cm (116 a 135 DG) e 50,1 e 65,0cm (201 a 245 DG). A quantidade máxima de ovogônias, folículos primordiais, em crescimento e antrais foi observada em fetos com CR entre, 4,1 e 6,0cm (40 a 49 DG); 16,1 e 23,0cm (90 a 115 DG); 29,1 e 36,0cm (136 a 155 DG) e 50,1 e 97,0cm (201 a 320 DG), respectivamente. Os resultados sugerem que o desenvolvimento morfológico dos ovários fetais de eqüinos SRD nos trópicos é mais precoce que o observado nos relatos de literatura referentes a estudos de eqüinos de diversas raças em regiões temperadas.

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co) variances with age adequately and larger breeding value accuracies can be expected using this model.

A critical analysis of Doppler velocimetry in the differential diagnosis of malignant and benign ovarian masses

Objectives: To evaluate the intratumoral reliability of color Doppler parameters and the contribution of Doppler sonography to the gray-scale differential diagnosis of ovarian masses. Methods: An observational study was performed including 67 patients, 15 (22.4%) with malignant ovarian neoplasm and 52 (77.6%) with benign ovarian diseases. We performed the Doppler evaluation in two distinct vessels selected after decreasing the Doppler gain to sample only vessels with higher velocity flow. Doppler measurements were obtained from each identified vessel, and resistive index (RI), pulsatility index (PI), peak systolic velocity (PSV), and end-diastolic velocity (EDV) were measured. Intraclass coefficient of correlation (ICC), sensitivity, specificity, and potential improvement in gray-scale ultrasound performance were calculated. Results: The general ICC were 0.60 (95% CI 0.42- 0.73) for RI, 0.65 (95% CI 0.49- 0.77) for PI, 0.07 (95% CI- 0.17-0.30) for PSV, and 0.19 (95% CI -0.05-0.41) for EDV. The sensitivity and specificity were respectively 84.6% and 86.7% for RI, 69.2% and 93.3% for PI, 80.0% and 65.4% for gray-scale sonography, and 93.3% and 65.4% for gray-scale plus RI (p = 0.013). Conclusions: Gynecologists must be careful in interpreting results from Doppler evaluation of ovarian masses because PSV and EDV present poor intratumoral reliability. The lower RI value, evaluated in at least two distinct sites of the tumor, was able to improve the performance of gray-scale ultrasound in differential diagnosis of ovarian masses.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Ovarian function in cows submitted to acute stress during proestrus

Studies in which ACTH was administrated in heifers after the occurrence of luteolysis showed a delay in the onset of estrus and the estrus duration was shortened. This study evaluated the effect of acute stress by road transportation on estrous behavior and ovulation, monitored by serum progesterone and cortisol concentrations in cows at the periovulatory period, using a crossover design. Eleven crossbred cows, divided into Control and Transport groups had their estrus cycle synchronized with GnRH, an intravaginal progesterone device, and cloprostenol. Thirty hours after withdrawal of the device, the animals of the Transport group were transported for 60 min by truck and those from the Control group remained at pasture. Ovarian ultrasound examination was performed every 12 h from device withdrawal until ovulation in every cow. From the day after removal of the device until ovulation estrous behavior was monitored 24 h a day. Blood samples for serum cortisol and progesterone concentrations were taken at -90, -60, 0, 30, 60 and 180 min in relation to the end of transportation. Transportation during the estrous period induced stress in cows as reflected by changes in serum concentrations of progesterone and cortisol. However, we did not detect impairment in estrus expression, estrus duration or ovulation (P>0.05). (C) 2010 Elsevier B.V. All rights reserved.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.