Genetic and Phenotypic Variability for Racing Performance of Trotter Horse in Serbia

Horse race results in studbooks are supposed to give information to manage the selection of trotters based on the analysis of genetic and phenotypic parameters. The objectives of this study was to estimate genetic and phenotypic variability of three racing traits (number of starts, race time and best racing time) of trotter horses in Serbia. The data were obtained from the Trotting Association of Serbia and consisted of 2252 observations. The model included effect of sex, year of birth, season, year of race, distance and race track as fixed effects and sire as random effect. The BLUP sire model was applied to the genetic evaluation of measured traits. Average mean of number of starts, race time and best racing time was 64, 83.15 and 79.28, respectively. Of all tested fixed effects only distance was not statistically significant for number of starts and season for best racing time. However, a statistically highly significant influence of all tested fixed effects on racing time was shown. Heritability estimates were 0.28 for number of starts, 0.19 for racing time and 0.35 for best racing time. The low heritability estimates for number of starts and racing time indicate that selection based on horse phenotypic value induces small genetic change in these traits while middle level of heritability for best racing time indicates that animal's phenotype is a good indicator of genetic merit or breeding value

Sources of Variation for Milk Traits in Regions of Vojvodina

The study aimed to investigate different sources of variation for milk traits in dairy cows, in first lactation from three breeding regions of Vojvodina (Srem, Banat and Backa). For research purposes a total of 2767 complete and 305 days records of milk yield (MY), fat yield (FY) and milk fat content (MFC) of Holstein-Friesian (HF, black and red) dairy cows was used. All cows were involved in the official milk recording program in 2013 in Vojvodina. Milk traits were analyzed using the mixed linear model in order to explain total variation with bull-sire as a random effect, region, year of birth and calving season as fixed effects and length of lactation as covariates. The average values of MY, MF and MFC in the first lactation of 305 days were 6053.4 kg of milk, 225.24 kg of milk fat and 3.74% milk fat content. The effects of the bull-sire, calving season, year of birth and breeding region on all investigated milk traits were highly significant (p>0.01) during 305 days, but year of birth for complete records had no significant effect on these parameters (P>0.05)

Toward higher-performance bionic limbs for wider clinical use

Funding Information: We were supported by the Academy of Finland (I.V.), Austrian Federal Ministry of Science (A.S. and O.C.A.), Bertarelli Foundation (S.M.), the European Union (A.S., D.F., K.-P.H., O.C.A., R.B. and S.M.), the European Research Council (A.S., D.F. and O.C.A.), German Federal Ministry of Education and Research BMBF (K.-P.H. and T.S.), the German National Research Foundation (T.S.), the Royal British Legion (A.M.J.B.), the Swedish Innovation Agency (VINNOVA) (R.B.), the Swedish Research Council (R.B.), the Swiss National Competence Center in Research (NCCR) in Robotics (S.M.), US Department of Defense (R.B. and H.H.), US Department of Veterans Affairs (D.T.), US Department of Veterans Affairs Rehabilitation Research and Development Service (R.F.ff.W.), US National Institute on Disability, Independent Living and Rehabilitation Research (H.H. and T.K.), US National Institutes of Health (D.T., H.H., L.J.H. and R.F.ff.W.), US National Institute on Neurological Disorders and Stroke (R.F.ff.W.), USNational Institute on Bioimaging and Bioengineering (R.F.ff.W.) and US National Science Foundation (H.H.). Publisher Copyright: © 2021, Springer Nature Limited.Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs.Peer reviewe