Comparison of the GEANT4 releases 8.2 and 9.2 in terms of a pCT reduced calibration curve

The GEANT4 simulations are essential for the development of medical tomography with proton beams pCT. In the case of thin absorbers the latest releases of GEANT4 generate very similar final spectra which agree well with the results of other popular Monte Carlo codes like TRIM/SRIM, or MCNPX. For thick absorbers, however, the disagreements became evident. In a part, these disagreements are due to the known contradictions in the NIST PSTAR and SRIM reference data. Therefore, it is interesting to compare the GEANT4 results with each other, with experiment, and with diverse code results in a reduced form, which is free from this kind of doubts. In this work such comparison is done within the Reduced Calibration Curve concept elaborated for the proton beam tomography. © 2010 IEEE.

Genetic parameters for test-day milk yield, 305-day milk yield, and lactation length in Guzerat cows

Milk production in tropical environments requires the use of crossbreeding systems including breeds well adapted to harsh conditions, but with lower productivities when compared to specialized breeds. Besides the genetic improvement for milk production, lactation lengths also need to be studied for most of these breeds. Accordingly, genetic parameters were estimated for 305-day cumulative milk yield (MY305), test-day milk yield (TDMY), and lactation length (LL) using information from the first lactations of 2816 Guzerat cows selected for milk production in 28 herds in Brazil. Contemporary groups were defined as herd, year and season of the test for TDMY, and as herd, year and season of calving for MY305 and LL. Variance components were estimated with the restricted maximum likelihood method under a multi-trait animal model. Heritabilities estimated for TDMY ranged from 0.16 to 0.24, and were 0.24 and 0.12 for MY305 and LL, respectively. Genetic correlations were high and positive, ranging from 0.51 to 0.99 among TDMY records, from 0.81 to 0.98 between each TDMY and MY305, and from 0.71 to 0.94 between each TDMY and LL. Genetic parameters obtained in this study indicated the possibility of using test-day records for the prediction of breeding values for milk yield in this population of the Guzerat breed. The use of TDMY as selection criteria would result in indirect gains in MY305 and LL. However, the highest response to selection for MY305 would be obtained by direct selection for this trait. © 2012 Elsevier B.V.

Evaluation of von willebrand factor during pregnancy, lactation and oestrous cycle in bitches affected and unaffected by von willebrand disease

Plasmatic concentrations of von Willebrand Factor (vWF) increase during pregnancy in humans and dogs; however the mechanism of such increase is still not well defined. The aims of this study were: (i) to evaluate changes in vWF concentration during pregnancy and during the subsequent oestrous cycle in bitches affected and unaffected by von Willebrand Disease (vWD); (ii) to correlate the vWF levels and cortisol levels in both groups. Seven vWD affected (GI) and nine unaffected (GII) bitches were used. The animals were assessed during pregnancy, parturition, lactation and non-gestational oestrous cycle in 11 moments (Pregnancy 1, Pregnancy 2, Parturition, Lactation 1, Lactation 2, Lactation 3, Anestrus, Proestrus, Oestrus, Diestrus 1, and Diestrus 2). The following tests were performed; measurement of von Willebrand factor antigen (vWF:Ag), albumin and cortisol. In both groups, vWF concentration remained stable during the non-gestational oestrous cycle, but increased during pregnancy, with the highest value observed at parturition. Increases of 70% and 124% in vWF were seen in GI and GII, respectively, compared to anestrus. No correlation was found between vWF and cortisol. Values of vWF:Ag changed during pregnancy, with a peak at parturition, both in vWD affected and unaffected animals. Values of vWF were not altered in the different phases of the oestrous cycle following pregnancy in both groups. Evaluation of vWF during pregnancy can cause false negative results for vWD, but assessment can be performed at any point in the oestrous cycle of non-pregnant bitches. © 2012 Blackwell Verlag GmbH.

Interval multivariate curve resolution in the dereplication of HPLC-DAD data from Jatropha gossypifolia

Introduction Jatropha gossypifolia has been used quite extensively by traditional medicine for the treatment of several diseases in South America and Africa. This medicinal plant has therapeutic potential as a phytomedicine and therefore the establishment of innovative analytical methods to characterise their active components is crucial to the future development of a quality product. Objective To enhance the chromatographic resolution of HPLC-UV-diode-array detector (DAD) experiments applying chemometric tools. Methods Crude leave extracts from J. gossypifolia were analysed by HPLC-DAD. A chromatographic band deconvolution method was designed and applied using interval multivariate curve resolution by alternating least squares (MCR-ALS). Results The MCR-ALS method allowed the deconvolution from up to 117% more bands, compared with the original HPLC-DAD experiments, even in regions where the UV spectra showed high similarity. The method assisted in the dereplication of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. Conclusion The MCR-ALS method is shown to be a powerful tool to solve problems of chromatographic band overlapping from complex mixtures such as natural crude samples. Copyright © 2013 John Wiley & Sons, Ltd. Extracts from J. gossypifolia were analyzed by HPLC-DAD and, dereplicated applying MCR-ALS. The method assisted in the detection of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. The application of MCR-ALS allowed solving problems of chromatographic band overlapping from complex mixtures such as natural crude samples. Copyright © 2013 John Wiley & Sons, Ltd.

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.

Genetic parameters for milk yield, lactation length and calving intervals of murrah buffaloes from brazil

The major objective of this study was to estimate heritability and genetic correlations between milk yield (MY) and calving interval (CI) and lactation length (LL) in Murrah buffaloes using Bayesian inference. The database used belongs to the genetic improvement program of four buffalo herds from Brazil. To obtain the estimates of variance and covariance, bivariate analyses were performed with the Gibbs sampler, using the program MTGSAM. The heritability coefficient estimates were 0.28, 0.03 and 0.15 for MY, CI and LL, respectively. The genetic correlations between MY and LL was moderate (0.48). However, the genetic correlation between MY and CI showed large HPD regions (highest posterior density interval). Milk yield was the only trait with clear potential for genetic improvement by direct mass selection. The genetic correlation between MY and LL indicates that indirect selection using milk yield is a potentially beneficialstrategy.Theinterpretation of the estimated genetic correlation between MY and CI is difficult and could be spurious. ©2013 Sociedade Brasileira de Zootecnia.

Nutrients balances and milk fatty acid profile of mid lactation dairy cows supplemented with unsaturated fatty acid

The objective was to evaluate the effect of unsaturated fatty acid sources supplementation on nutrients balances and milk fatty acid profile of mid lactation dairy cows. Twelve Brazilian Holstein cows in the mid lactation (mean of 128 days) and (580 ± 20kg of weight; mean ± SD) with milk yield of 25kg/d were assigned randomly into three 4 × 4 Latin square, fed the following diets: control (C); refined soybean oil; (SO); whole soybean raw (WS) and; calcium salts of unsaturated fatty acids (CSFA). Milk yield was 26.6; 26.4; 24.1 and 25.7 to the diets CO, SO, WS and CSFA respectively. Cows fed the WS treatment produced less milk (1.95kg/d of milk), fat and lactose than did cows fed the SO and CSFA. Cows fed the CSFA treatment showed less blood, urine (g/d) concentrations of N more energetic efficiency and intake of energy than did cows fed the SO treatment. Cows fed the unsaturated fatty acids sources showed more C18:2 cis-9, trans-11 CLA and trans-C18:1 FA concentration in milk than did cows fed the CO treatment. Diets with whole soybeans and soybeans oil provide more efficient digestive processes, and increase milk composition of unsaturated fatty acids.

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows

The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. © 2013 American Dairy Science Association.

Diferentes abordagens para modelar a produção de leite de bovinos da raça Guzerá

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Growth curve of female collared peccaries (Pecari tajacu) raised in captivity in the Brazilian Amazon Region

Com o objetivo de ajustar modelos não-lineares, foram utilizados registros mensais do peso de 10 fêmeas de cateto (Pecari tajacu) coletados durante dois anos, no criatório do campo experimental Álvaro Adolfo da Embrapa Amazônia Oriental, Belém, PA. Utilizaram-se os modelos de Von Bertalanffy, Brody, Gompertz e Logístico. Os parâmetros foram estimados usando o procedimento NLIN do aplicativo SAS. Os critérios utilizados para verificar o ajuste dos modelos foram: desvio padrão assintótico (ASD); coeficiente de determinação (R²); desvio médio absoluto dos resíduos (ARD) e o índice assintótico (AR). Os modelos Brody e Logístico estimaram, respectivamente, o maior (19,44kg) e o menor (19,18kg) peso assintótico (A), caracterizando a menor (0,0064kg/dia) e a maior (0,0113kg/dia) taxa de maturação (K), haja vista a natureza antagônica entre estes parâmetros, comprovada pela correlação fenotípica variando entre -0,75 à -0,47. O modelo Brody estimou o menor valor para o ARD, fator limitante para caracterizar o menor valor para o AR por este modelo. Considerando o AR, o modelo Brody apresentou o melhor ajuste, contudo, pelos valores encontrados, os demais modelos também apresentaram ajuste adequando aos dados ponderais da referida espécie/sexo. Com base no AR adotado neste trabalho, recomenda-se o modelo Brody para ajustar a curva de crescimento de fêmeas de cateto (Pecari tajacu). Em razão dos valores estimados, sobretudo, para a K, essa característica pode ser incluída em um índice de seleção. Contudo, estudos com grupos mais representativos e criados em outras condições se faz oportuno.

Multivariate curve resolution analysis applied to time-resolved synchrotron X-ray Absorption Spectroscopy monitoring of the activation of copper alumina catalyst

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Exposure to lard-based high-fat diet during fetal and lactation periods modifies breast cancer susceptibility in adulthood in rats

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

Genetic Parameters for Milk Yield and Lactation Length of Crossbred Buffaloes from Brazil by Bayesian Inference

The objective of the study was to estimate heritability and repeatability for milk yield (MY) and lactation length (LL) in buffaloes using Bayesian inference. The Brazilian genetic improvement program of buffalo provided the data that included 628 females, from four herds, born between 1980 and 2003. In order to obtain the estimates of variance, univariate analyses were performed with the Gibbs sampler, using the MTGSAM software. The model for MY and LL included direct genetic additive and permanent environment as random effects, and contemporary groups, milking frequency and calving number as fixed effects. The convergence diagnosis was performed with the Geweke method using an algorithm implemented in R software through the package Bayesian Output Analysis. Average for milk yield and lactation length was 1,546.1 +/- 483.8 kg and 252.3 +/- 42.5 days, respectively. The heritability coefficients were 0.31 (mode), 0.35 (mean) and 0.34 (median) for MY and 0.11 (mode), 0.10 (mean) and 0.10 (median) for LL. The repeatability coefficient (mode) were 0.50 and 0.15 for MY and LL, respectively. Milk yield is the only trait with clear potential for genetic improvement by direct genetic selection. The repeatability for MY indicates that selection based on the first lactation could contribute for an improvement in this trait.

Genetic Parameter Estimates for Milk Yield and Lactation Length in Buffalo

The objective of this study was to estimate genetic parameters for milk yield at 244 days and lactation length in graded buffalo cows at the El Cangre Cattle Genetic Enterprise. Data were gathered from 2575 lactations, 1377 buffalo cows, 37 milking units and between 2002-2009 calving years. It was employed the Restricted Maximum Likelihood method (REML) for estimating (co) variance components with multi trait model. Average of milk yield at 244 days and lactation length were 864 kg and 240 days, respectively. Heritability was 0.15 for milk yield and 0.13 for lactation length. Genetic correlation between these traits was 0.63. It was concluded that it is necessary to intensify selection and to increase control of the information of the genetic herds to obtain high precision in the estimates and therefore, obtain bigger genetic progress in of this species in our country.