23 resultados para Maternal mortality


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Postnatal myofibre characteristics and muscle mass are largely determined during fetal development and may be significantly affected by epigenetic parent-of-origin effects. However, data on such effects in prenatal muscle development that could help understand unexplained variation in postnatal muscle traits are lacking. In a bovine model we studied effects of distinct maternal and paternal genomes, fetal sex, and non-genetic maternal effects on fetal myofibre characteristics and muscle mass. Data from 73 fetuses (Day153, 54% term) of four genetic groups with purebred and reciprocal cross Angus and Brahman genetics were analyzed using general linear models. Parental genomes explained the greatest proportion of variation in myofibre size of Musculus semitendinosus (80-96%) and in absolute and relative weights of M. supraspinatus, M. longissimus dorsi, M. quadriceps femoris and M. semimembranosus (82-89% and 56-93%, respectively). Paternal genome in interaction with maternal genome (P<0.05) explained most genetic variation in cross sectional area (CSA) of fast myotubes (68%), while maternal genome alone explained most genetic variation in CSA of fast myofibres (93%, P<0.01). Furthermore, maternal genome independently (M. semimembranosus, 88%, P<0.0001) or in combination (M. supraspinatus, 82%; M. longissimus dorsi, 93%; M. quadriceps femoris, 86%) with nested maternal weight effect (5-6%, P<0.05), was the predominant source of variation for absolute muscle weights. Effects of paternal genome on muscle mass decreased from thoracic to pelvic limb and accounted for all (M. supraspinatus, 97%, P<0.0001) or most (M. longissimus dorsi, 69%, P<0.0001; M. quadriceps femoris, 54%, P<0.001) genetic variation in relative weights. An interaction between maternal and paternal genomes (P<0.01) and effects of maternal weight (P<0.05) on expression of H19, a master regulator of an imprinted gene network, and negative correlations between H19 expression and fetal muscle mass (P<0.001), suggested imprinted genes and miRNA interference as mechanisms for differential effects of maternal and paternal genomes on fetal muscle.

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In current simulation packages for the management of extensive beef-cattle enterprises, the relationships for the key biological rates (namely conception and mortality) are quite rudimentary. To better estimate these relationships, cohort-level data covering 17 100 cow-years from six sites across northern Australia were collated and analysed. Further validation data, from 7200 cow-years, were then used to test these relationships. Analytical problems included incomplete and non-standardised data, considerable levels of correlation among the 'independent' variables, and the close similarity of alternate possible models. In addition to formal statistical analyses of these data, the theoretical equations for predicting mortality and conception rates in the current simulation models were reviewed, and then reparameterised and recalibrated where appropriate. The final models explained up to 80% of the variation in the data. These are now proposed as more accurate and useful models to be used in the prediction of biological rates in simulation studies for northern Australia. © The State of Queensland (through the Department of Agriculture, Fisheries and Forestry) 2012. © CSIRO.

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Data from 9296 calves born to 2078 dams over 9 years across five sites were used to investigate factors associated with calf mortality for tropically adapted breeds (Brahman and Tropical Composite) recorded in extensive production systems, using multivariate logistic regression. The average calf mortality pre-weaning was 9.5% of calves born, varying from 1.5% to 41% across all sites and years. In total, 67% of calves that died did so within a week of their birth, with cause of death most frequently recorded as unknown. The major factors significantly (P < 0.05) associated with mortality for potentially large numbers of calves included the specific production environment represented by site-year, low calf birthweight (more so than high birthweight) and horn status at branding. Almost all calf deaths post-branding (assessed from n = 8348 calves) occurred in calves that were dehorned, totalling 2.1% of dehorned calves and 15.9% of all calf deaths recorded. Breed effects on calf mortality were primarily the result of breed differences in calf birthweight and, to a lesser extent, large teat size of cows; however, differences in other breed characteristics could be important. Twin births and calves assisted at birth had a very high risk of mortality, but <1% of calves were twins and few calves were assisted at birth. Conversely, it could not be established how many calves would have benefitted from assistance at birth. Cow age group and outcome from the previous season were also associated with current calf mortality; maiden or young cows (<4 years old) had increased calf losses overall. More mature cows with a previous outcome of calf loss were also more likely to have another calf loss in the subsequent year, and this should be considered for culling decisions. Closer attention to the management of younger cows is warranted to improve calf survival.

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Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment. This fraction is result of undesirable genotype-by-environment interactions (GxE) and measured by the genetic correlation (rg) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of GxE over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels.

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This is a retrospective study of 38 cases of infection by Babesia macropus, associated with a syndrome of anaemia and debility in hand-reared or free-ranging juvenile eastern grey kangaroos (Macropus giganteus) from coastal New South Wales and south-eastern Queensland between 1995 and 2013. Infection with B. macropus is recorded for the first time in agile wallabies (Macropus agilis) from far north Queensland. Animals in which B. macropus infection was considered to be the primary cause of morbidity had marked anaemia, lethargy and neurological signs, and often died. In these cases, parasitised erythrocytes were few or undetectable in peripheral blood samples but were sequestered in large numbers within small vessels of visceral organs, particularly in the kidney and brain, associated with distinctive clusters of extraerythrocytic organisms. Initial identification of this piroplasm in peripheral blood smears and in tissue impression smears and histological sections was confirmed using transmission electron microscopy and molecular analysis. Samples of kidney, brain or blood were tested using PCR and DNA sequencing of the 18S ribosomal RNA and heat shock protein 70 gene using primers specific for piroplasms. The piroplasm detected in these samples had 100 sequence identity in the 18S rRNA region with the recently described Babesia macropus in two eastern grey kangaroos from New South Wales and Queensland, and a high degree of similarity to an unnamed Babesia sp. recently detected in three woylies (Bettongia penicillata ogilbyi) in Western Australia.

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Fetal flavor conditioning during the perinatal stage could be essential at the time of the weaning to reduce the stress and improve the feed intake in pigs. The transfer of flavor compounds from maternal diet to amniotic fluid and milk has been shown in behavioral experiments, but not through analytical procedures such as gas chromatography–mass spectrometry (GC–MS). The aim of the experiment was to trace the principal essential oils compounds supplied in the diet in maternal fluids. Twenty Large White sows around their 104th gestational day were allocated to individual farrowing crates. Two groups of 10 sows were fed either a standard gestation diet or the same diet supplemented with a mix of 8 essential oils at a rate of 1kg/ton during the last 10 days of gestation. At approximately the 113th gestational day, animals were individually treated with 10mg of Lutalyse IM was to induce farrowing. Fresh amniotic fluid was collected during the farrowing in 100-mL glass bottles and immediately stored at −20 °C freezer. During the second lactation day, 10–20 IU of Oxytocin IM was administered to each sow to facilitate collection of milk samples in 20-mL glass bottles. The samples were stored at −20 °C until analyzed by GC–MS. The presence of significant amounts of principal components of all the essential oils except one were found in the milk and amniotic fluid samples of the treated sows relative to the control sows. Our data prove the transfer of selected dietary flavors to maternal fluids and sets the scenario for further trials to manipulate postweaning behavior in piglets.

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Fisheries management agencies around the world collect age data for the purpose of assessing the status of natural resources in their jurisdiction. Estimates of mortality rates represent a key information to assess the sustainability of fish stocks exploitation. Contrary to medical research or manufacturing where survival analysis is routinely applied to estimate failure rates, survival analysis has seldom been applied in fisheries stock assessment despite similar purposes between these fields of applied statistics. In this paper, we developed hazard functions to model the dynamic of an exploited fish population. These functions were used to estimate all parameters necessary for stock assessment (including natural and fishing mortality rates as well as gear selectivity) by maximum likelihood using age data from a sample of catch. This novel application of survival analysis to fisheries stock assessment was tested by Monte Carlo simulations to assert that it provided unbiased estimations of relevant quantities. The method was applied to the data from the Queensland (Australia) sea mullet (Mugil cephalus) commercial fishery collected between 2007 and 2014. It provided, for the first time, an estimate of natural mortality affecting this stock: 0.22±0.08 year −1 .

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It is common to model the dynamics of fisheries using natural and fishing mortality rates estimated independently using two separate analyses. Fishing mortality is routinely estimated from widely available logbook data, whereas natural mortality estimations have often required more specific, less frequently available, data. However, in the case of the fishery for brown tiger prawn (Penaeus esculentus) in Moreton Bay, both fishing and natural mortality rates have been estimated from logbook data. The present work extended the fishing mortality model to incorporate an eco-physiological response of tiger prawn to temperature, and allowed recruitment timing to vary from year to year. These ecological characteristics of the dynamics of this fishery were ignored in the separate model that estimated natural mortality. Therefore, we propose to estimate both natural and fishing mortality rates within a single model using a consistent set of hypotheses. This approach was applied to Moreton Bay brown tiger prawn data collected between 1990 and 2010. Natural mortality was estimated by maximum likelihood to be equal to 0.032 ± 0.002 week−1, approximately 30% lower than the fixed value used in previous models of this fishery (0.045 week−1).