Humane endpoint in mice by Brazilian researchers in the vaccine sector / Ponto final humanitário em camundongos aplicado por pesquisadores brasileiros da área de vacinas

The application of a humane endpoint (HE) for mice in vaccine trials and further challenging tasks with lethal samples is necessary to reduce or prevent pain and suffering in these animals, and is a refinement of the 3R policy enforced for animal testing in both national and international scenarios. In order to investigate the application of HE in Brazil, researchers from the vaccine sector have answered a questionnaire about their research profile, their usage of HE and their knowledge of its defining criteria, monitoring of animals, staff training, and euthanasia methods employed. The main results revealed that researchers failed to recognise the very concept of HE as well as when to apply it. In addition, the Institutional Animal Care and Use Committees (IACUCs) failed upon giving their approval to the trials. HE is an important refinament of animal testing policy, and these results highlight the need for a clear pre-established definition of when and how it should be implemented in order to ensure more effective application. Furthermore, it is important to clarify the ethics involved and the commitment of both the research teams and IACUCs to animal welfare.(AU)

A aplicação de um ponto final humanitário (PFH) em experimentos com vacinação e posterior desafio com amostras letais em camundongos é necessária para diminuir ou impedir a dor e o sofrimento desses animais, constituindo refinamento de acordo com a política dos 3Rs, vigente em âmbito nacional e internacional, no cenário da experimentação animal. A fim de investigar a aplicação de PFH no Brasil, foi enviado um questionário para pesquisadores da área de vacinas, com perguntas sobre perfil do pesquisador, aplicação de PFH e critérios para sua definição, monitoramento dos animais, treinamento da equipe e métodos de eutanásia empregados. Os principais resultados revelaram que há falhas tanto em reconhecer o conceito quanto em aplicar o PFH, por parte dos pesquisadores, e que as CEUAs também falharam ao aprovar tais experimentos. Chama-se atenção para o fato de que o PFH é um importante refinamento e para a necessidade de definição prévia de PFH e sua aplicação, assim como para a importância do esclarecimento da questão ética envolvida e do necessário compromisso das equipes de pesquisa e das CEUAs com o bem-estar animal.(AU)

Genetic associations between carcass traits measured by real-time ultrasound and scrotal circumference and growth traits in Nelore cattle.

The aim of the present study was to evaluate the genetic correlations among real-time ultrasound carcass, BW, and scrotal circumference (SC) traits in Nelore cattle. Carcass traits, measured by real-time ultrasound of the live animal, were recorded from 2002 to 2004 on 10 farms across 6 Brazilian states on 2,590 males and females ranging in age from 450 to 599 d. Ultrasound records of LM area (LMA) and backfat thickness (BF) were obtained from cross-sectional images between the 12th and 13th ribs, and rump fat thickness (RF) was measured between the hook and pin bones over the junction between gluteus medius and biceps femoris muscles. Also, BW (n = 22,778) and SC (n = 5,695) were recorded on animals born between 1998 and 2003. The BW traits were 120, 210, 365, 450, and 550-d standardized BW (W120, W210, W365, W450, and W550), plus BW (WS) and hip height (HH) on the ultrasound scanning date. The SC traits were 365-, 450-, and 550-d standardized SC (SC365, SC450, and SC550). For the BW and SC traits, the database used was from the Nelore Breeding Program-Nelore Brazil. The genetic parameters were estimated with multivariate animal models and REML. Estimated genetic correlations between LMA and other traits were 0.06 (BF), -0.04 (RF), 0.05 (HH), 0.58 (WS), 0.53 (W120), 0.62 (W210), 0.67 (W365), 0.64 (W450 and W550), 0.28 (SC365), 0.24 (SC450), and 0.00 (SC550). Estimated genetic correlations between BF and with other traits were 0.74 (RF), -0.32 (HH), 0.19 (WS), -0.03 (W120), -0.10 (W210), 0.04 (W365), 0.01 (W450), 0.06 (W550), 0.17 (SC365 and SC450), and -0.19 (SC550). Estimated genetic correlations between RF and other traits were -0.41 (HH), -0.09 (WS), -0.13 (W120), -0.09 (W210), -0.01 (W365), 0.02 (W450), 0.03 (W550), 0.05 (SC365), 0.11 (SC450), and -0.18 (SC550). These estimates indicate that selection for carcass traits measured by real-time ultrasound should not cause antagonism in the genetic improvement of SC and BW traits. Also, selection to increase HH might decrease subcutaneous fat as correlated response. Therefore, to obtain animals suited to specific tropical production systems, carcass, BW, and SC traits should be considered in selection programs.

Parâmetros genéticos para características de carcaça avaliadas por ultrassonografia em bovinos da raça Guzerá / Genetic parameters for body weight and real-time ultra sound carcass traits of Guzera cattle

A partir das observações de 1.325 animais (90,4 por cento de machos e 9,6 por cento de fêmeas) e do pedigree de 6.642 animais da raça Guzerá foram estimados os parâmetros genéticos para o peso corporal e as características área de olho de lombo e espessura de gordura na costela e na garupa, avaliadas por meio da técnica de ultrassonografia. Os componentes de (co)variância foram estimados pelo método da máxima verossimilhança restrita, utilizando-se o aplicativo MTDFREML. Foram utilizados, para as estimativas de repetibilidade e herdabilidade, modelos unicaracterística e, para as correlações genéticas e fenotípicas entre as características, modelos bicaracterísticas. As estimativas de repetibilidade (erros-padrão) foram 0,44(0,10) para peso corporal, 0,39(0,10) para área de olho de lombo, 0,75(0,06) para espessura de gordura na costela e 0,49(0,08) para espessura de gordura na garupa. As estimativas de herdabilidade, respectivamente a partir de modelos uni e bicaracterísticas, foram 0,42(0,11) e 0,41(0,11) para peso corporal, 0,35(0,09) e 0,34(0,09) para área de olho de lombo, 0,20(0,08) e 0,32(0,02) para espessura de gordura na garupa e 0,05(0,06) e 0,10(0,08) para espessura de gordura na costela. As estimativas de correlações genéticas foram 0,79(0,09) entre o peso corporal e a área de olho de lombo; 0,20(0,08) entre o peso corporal e a espessura de gordura na garupa; 0,05(0,06) entre a área de olho de lombo e a espessura de gordura na costela; 0,02(0,27) entre a área de olho de lombo e a espessura de gordura na garupa; e 0,64(0,22) entre as duas medidas de espessura de gordura. Os resultados indicam que é uma mensuração suficiente para a adequada avaliação das características área de olho de lombo e espessura de gordura na carcaça e que a seleção direta para essas características pode resultar em carcaças mais musculosas e de melhor acabamento. Indica, ainda, ausência de antagonismo genético entre a seleção para peso corporal e características ...

Genetic parameters were estimated for body weight and real-time ultra-sound loin-eye area, rump fat thickness, and back fat thickness using data from 1,325 yearling Guzera cattle (90.4 percent bulls and 9.6 percent heifers) and pedigree structure with 6,642 animals. Variance and covariance components were estimated using REML methodology and MTDFREML software. Single trait animal models were used to estimate repeatability and heritability for the four traits. Multiple traits animal models were used to estimate genetic correlations among the traits. Repeatability estimates (standard errors) were 0.44(0.10) for body weight, 0.39(0.10) for loin-eye area, 0.75(0.06) for rump fat thickness, and 0.49(0.08) for back fat thickness. Heritability estimates were 0.42(0.11) and 0.41(0.11) for body weight, 0.35(0.09) and 0.34(0.09) for loin-eye area, 0.20(0.08) and 0.32(0.08) for back fat thickness, and 0.05(0.06) and 0.10(0.08) for rump fat thickness, respectively from single and multiple traits models. Genetic correlation estimates were 0.79(0.09) between body weight and loin-eye area, 0.20(0.08) between body weight and back fat thickness, 0.05(0.06) between loin-eye area and rump fat thickness, 0.02(0.27) between loin-eye area and back fat thickness and 0.64(0.22) between the two measurements of fat thickness. In order to evaluate carcass traits, results suggested that repeated real-time ultra-sound measurements are not needed and that direct selection for these traits might be effective. In addition, there is no genetic antagonism between selection for body weight and carcass traits.