Uterine and luteal hemodynamic evaluation of the non pregnant mare

Background: Studies with Doppler ultrassonography started at the end of the 90s for the determination of physiological and pathological alterations in the reproductive tract of the mare. Uterine alterations caused by inflammation, response from seminal plasma infusion, hormonal variations during estrous and diestrus, pregnancy and action of various vasoactive factors influence on the vascular perfusion detected by Doppler ultrasound. The development of efficient methods for uterine quality evaluation is of big importance for field equine reproduction veterinarians, once uterine environment is responsible for pregnancy maintenance. Review: Nowadays, the most used methods of uterine evaluation are the mode B ultrassonography, cytology, culture and biopsy. Hemodynamic evaluation of the uterus can be done by spectral data collected from large vessels, as A. uterine and its ramifications, or from subjective or objective evaluations from endometrium, miometrium and mesometrium attachment, which provide data referent to local and specific alterations of the evaluated area. Alterations in uterine vascular perfusion has been detected during estrous cycle, during pregnancy and in cases of infusion of inflammatory substances. These alterations happen because of vasoactive substances that act in the uterus during these events, however, most of these vasoactive substances are probably not even known. Also, important hemodynamic alterations in old mares, as an increase in vascular resistance, have been described. This increase might result from fibrosis of the uterus and in women it is considered to be a cause of infertility. In mares, periglandular fibrosis of the endometrium is considered to be the major diagnosable cause of embryonic and fetal loss in older mares. For the CL, ovarian artery of the mare supplies the ovary as well as the oviduct and therefore can be used for evaluation of these areas. The CL evaluation can also be done by the percentage of luteum area with colored signals as an indicator of the extent of blood flow. The percentage of the CL area with colored signals is determined subjectively by images observations in real time and/or by a freezing Power Doppler cross-section image with the maximum number of color pixels taped and the total number of color pixels is assessed by a computer analysis system. Therefore, a high correlation between plasmatic progesterone and CL vascularization also allows the CL evalution by this technique. In a first report, CL circulation reached its maximum on D5, the progesterone concentration in peripheral blood increased until D7 and in a posterior report, maximum perfusion was achieved two days after the maximum progesterone concentration (D8). Blood flow reduced between D10-D14 some days before the plasma progesterone decrease and, during the luteolytic period (D15-D17), the decline in CL blood-flow area was greater than blood flow decrease. Conclusion: Doppler ultrassonography add knowledge about uterine viability and CL functionality can be easily used by veterinarians in the field. It is a noninvasive method that provides real time results. However, because of the short time studies in this area have been done, many other answers still need to be found until normal and pathological patterns will be established.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

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.

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Resgate da função luteal em bovinos após desafio com cloroprostenol sódico

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Efeito do flunixin meglumine na duração da fase luteal e na taxa de prenhez de receptoras de embriões bovinos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeito de tratamentos com progesterona e/ou estradiol na incidência de regressão prematura do corpo lúteo após a primeira ovulação em vacas nelore pós-parto

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

Função luteal e luteólise em cadelas: aspectos morfo-funcionais

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

Influência da gonadotrofina coriônica humana sobre a hemodinâmica de folículos pré-ovulatórios e desenvolvimento luteal em águas

Pós-graduação em Medicina Veterinária - FMVZ

Resposta luteal à PGF2α (Dinoprost Trometamina) durante as fases de luteogênese e manutenção do corpo lúteo em éguas

Pós-graduação em Medicina Veterinária - FMVZ

Genetic parameters for body weight in buffaloes (Bubalus bubalis) in Colombia using random regression models

The objective of this research was to estimate (co) variance functions and genetic parameters for body weight in Colombian buffalo populations using random regression models with Legendre polynomials. Data consisted of 34,738 weight records from birth to 900 days of age from 7815 buffaloes. Fixed effects in the model were contemporary group and parity order of the mother. Random effects were direct and maternal additive genetic, as well as animal and maternal permanent environmental effects. A cubic orthogonal Legendre polynomial was used to model the mean curve of the population. Eleven models with first to sixth order polynomials were used to describe additive genetic direct and maternal effects, and animal and maternal permanent environmental effects. The residual was modeled considering five variance classes. The best model included fourth and sixth order polynomials for direct additive genetic and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects. The direct heritability increased from birth until 120 days of age (0.32 +/- 0.05), decreasing thereafter until one year of age (0.18 +/- 0.04) and increased again, reaching 0.39 +/- 0.09, at the end of the evaluated period. The highest maternal heritability estimates (0.11 +/- 0.05), were obtained for weights around weaning age (weaning age range is between 8 and 9.5 months). Maternal genetic and maternal permanent environmental variances increased from birth until about one year of age, decreasing at later ages. Direct genetic correlations ranged from moderate (0.60 +/- 0.060) to high (0.99 +/- 0.001), maternal genetic correlations showed a similar range (0.41 +/- 0.401 and 0.99 +/- 0.003), and all of them decreased as time between weighings increased. Direct genetic correlations suggested that selecting buffalos for heavier weights at any age would increase weights from birth through 900 days of age. However, higher heritabilities for direct genetic weights effects after 600 days of age suggested that selection for these effects would be more effective if done during this age period. A greater response to selection for maternal ability would be expected if selection used maternal genetic predictions for weights near weaning. (C) 2013 Elsevier B.V. All rights reserved.

Manipulation of the periovulatory sex steroidal milieu affects endometrial but not luteal gene expression in early diestrus Nelore cows

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