Using lactation curves as a tool for breeding, nutrition and health management decisions in pasture-based dairy systems

Milk yield and reproductive efficiency are crucial to profitable dairying. Although, genetic improvement in the last few decades has led to substantial increases in milk yield/cow, fertility and reproductive health have declined (Dematawewa and Berger, 1998). In a pasture-based system, a 365 day calving interval is crucial for optimum profit. Hence the need to increase milk yield by improving persistence of lactation rather than peak lactation which puts increased stress on the cows at the time when they should be rebreeding. Peak milk yield, persistency and lactation length are the key components of the lactation profile. Dairy cows with high peak yields are more prone to metabolic and physiological disorders (Terkeli et al 1999). Although estimated breeding values (EBV) in dairy cows in Australia incorporates indices of economic value, such as survival and milking speed, the impact of the current breeding approach and management on the shape of the lactation profile is not clear. Mathematical functions such as those previously used to describe a series of milk test day records (Wood, 1967, Wilmink, 1987), have the advantage of minimizing random variation while simultaneously summarising the lactation profile into biologically interpretable parameters

Comparative effects of ASI and APR sire breeding values on the lactation profile of pasture-based Holstein-Friesian cows

Estimated Breeding Values (EBVs) of bulls are useful indicators of the genetic transmission ability of an animal of desirable traits to their progeny. Lactation profile differs between different merit cows but for pasture-based production systems, the impact of emerging EBV evaluation methods remains largely unpublished. In this study, Wood’s incomplete gamma model (Y(t) = atbe−ct ) was utilised to compare the effects of the Australian Selection Index (ASI) and Australian Profit Ranking (APR) EBVs on the shape of the lactation profile of first-parity, pasture-based Holstein-Friesian cows. Initial yield and the rate of increase to peak were significantly influenced by EBV choice, although peak yield was not. It was concluded that Wood’s incomplete gamma function adequately modelled the lactation profile of pasture-based cows explaining over 90% of the observed variation irrespective of using ASI or APR sire breeding values

Modelling the effect of stocking rate on the lactation profiles of grazing Holstein-Friesian dairy cows using cubic splines

The primary purpose of modeling lactation is to predict the dairy cow’s average daily milk yield with minimal error, after adjusting for various environmental factors. While empirical and mechanistic models have been commonly utilised to model the lactation profile of dairy cows, random regression procedures of Legendre polynomials and cubic splines are increasingly being used. The objectives of this study were to compare the lactation profiles and performance of dairy cows on dryland versus irrigated pastures at different stocking rates with or without grain supplementation using cubic splines model. Cubic splines adequately modelled the bi-weekly milk yield data with low residuals and uncorrelated coefficients attributable to the great flexibility of the model. Without supplementation, mean milk yield did not differ, but was slightly higher in cows grazing at 2.5-3.5 cows/ha stocking rate (SR) compared to cows stocked below at 2.0 c/ha and above at 4.0 c/ha (Figure 1). Irrespective of SR, cows on irrigated pasture had higher peaks except those stocked at 4.0 c/ha. Pasture allocation significantly (p<0.05) increased the rise to peak milk yield in cows stocked at lower stocking rates (2.4-2.5 c/ha) compared to those on 2.8-3.5 c/ha but the latter were more persistent and had higher predicted total milk yields. The results demonstrated the accuracy of cubic splines in modeling lactation and that higher stocking rates can improve the efficiency of pasture utilisation when coupled with adequate grain supplementation

Genetic and phenotypic factors inuencing milk, protein and fat yields of dairy cows in Tasmania, Australia

The Australian State of Tasmania enjoys a cool, temperate climate that remains the backbone of its pasture-based dairy production system. In this study, 330,366 lactation records from 428 Tasmanian dairy herds collected between 2000 and 2005 were analysed. The objective was to determine the inuence of genetic and non-genetic factors on milk, protein and fat yields of pasture-based dairy cows. The data were statistically subjected to analyses of variance using general linear mixed model procedures with repeated measures. State-wide average milk yield per lactation over a standard 305-day lactation length was 5200.7 ± 1239.7 litres (ranging from 1107 to 13256 litres), while fat and protein yields averaged 205.5 ± 47.0 kg (ranging from 53 to 385 kg) and 166.2 ± 41.5 kg (ranging from 47 to 297 kg), respectively. Highly signicant (P<0.001) effects on milk, protein and fat yields attributable to variation in herd size, cow’s parity, breed, season and year of calving were detected. Milk yield increased linearly with increase in parity (means of 3482.4, 4019.5, 4615.4, 4826.1 and 5018.8 litres per lactation for parities 1, 2, 3, 4 and >4, respectively). Milk, fat and protein yields were highest in cows calving during the spring season (4769.8 litres, 215.2kg and 168 kg respectively), Holstein-Friesian genotypes produced the most milk (5211 litres), protein (171 kg) and fat (210kg) yields per lactation. Herd sizes of more than 1110 cows produced the most milk, fat and protein. Productivity per cow increased with calving year except in 2003 when total milk yield was lower than in 2002. We conclude that herd size, breed, parity, season and year of calving were among the main factors driving production of dairy cows in Tasmania and adjustments for these factors would be mandatory for any unbiased comparison of lactation performance within and between pasture-based dairy production systems

Social distancing with chronic pain during COVID-19: A cross-sectional correlational analysis

Background Understanding of the role social factors play in chronic pain is growing, with more adaptive and satisfying social relationships helping pain management. During the COVID-19 pandemic, social distancing measures facilitated a naturalistic study of how changes to social interaction affected chronic pain intensity. Methods In a cross-sectional correlational design, questionnaire data was collected over a 38-day period during the March 2020 COVID-19 lockdown, individuals with chronic pain were asked about their current pain experience as well as notable social factors which might relate to pain. Results Multiple regression analysis revealed social satisfaction significantly predicted pain experience, with a reduction in social participation during COVID-19 lockdowns increasing pain disability, and increased social satisfaction associated with decreasing pain intensity. Conclusions While pain management often focuses on the functional aspects of pain alleviation, these findings suggest psychological aspects of socialising satisfaction also impact pain experience. Pain management strategies should consider ways to increase social satisfaction in individuals with chronic pain, perhaps by facilitating socialisation in the home using remote communication methods similar to those which became popular during the COVID-19 lockdown

Predictive characteristics of lactation models for pasture-based Holstein-Friesian dairy cows

Mathematical functions to describe a series of milk test day records have the advantage of minimizing random variation, while simultaneously summarizing the lactation profile. Five empirical functions and two mechanistic models were used to model herd and individual milk yield profiles of multiparous Holstein-Friesian cows on 113, 290 milk yield records (8438 lactations) collected from 1994-2005. The models tested were the incomplete gamma (IG), a modified gamma (MG), an exponential (EXP), a polynomial regression (PR), a mixed log (ML), the bi-compartmental (BC), and Dijkstra (DJ) functions, the latter two being mechanistic models. Each model was fitted using the non-linear (NLIN) function of SAS. Model accuracy was evaluated based on residual mean square (RMS), the magnitude and distribution of residuals, and the correlation between the observed and predicted values. All the models, except MG, did equally well in portraying the lactation profile. Parameter estimates were significant (P<0.05), with large serial correlations indicating biased predictions, especially during mid-lactation. Correlations of residuals and observed herd average lactations ranged between -0.13 (MG) to 0.19 (IG), while that between observed and predicted was between 0.76 and 0.99 for the same models. Lactation curves of individual cow milk yields were more varied, exhibited the tendency for a second peak which were not accurately modeled. Mechanistic models performed best with herd data, the PR model fitted overall best, while the MG model fitted the profile least accurately in this study

Plants Modify Biological Processes to Ensure Survival following Carbon Depletion: A Lolium perenne Model

BACKGROUND: Plants, due to their immobility, have evolved mechanisms allowing them to adapt to multiple environmental and management conditions. Short-term undesirable conditions (e.g. moisture deficit, cold temperatures) generally reduce photosynthetic carbon supply while increasing soluble carbohydrate accumulation. It is not known, however, what strategies plants may use in the long-term to adapt to situations resulting in net carbon depletion (i.e. reduced photosynthetic carbon supply and carbohydrate accumulation). In addition, many transcriptomic experiments have typically been undertaken under laboratory conditions; therefore, long-term acclimation strategies that plants use in natural environments are not well understood. METHODOLOGY/PRINCIPAL FINDINGS: Perennial ryegrass (Lolium perenne L.) was used as a model plant to define whether plants adapt to repetitive carbon depletion and to further elucidate their long-term acclimation mechanisms. Transcriptome changes in both lamina and stubble tissues of field-grown plants with depleted carbon reserves were characterised using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The RT-qPCR data for select key genes indicated that plants reduced fructan degradation, and increased photosynthesis and fructan synthesis capacities following carbon depletion. This acclimatory response was not sufficient to prevent a reduction (P<0.001) in net biomass accumulation, but ensured that the plant survived. CONCLUSIONS: Adaptations of plants with depleted carbon reserves resulted in reduced post-defoliation carbon mobilization and earlier replenishment of carbon reserves, thereby ensuring survival and continued growth. These findings will help pave the way to improve plant biomass production, for either grazing livestock or biofuel purposes

Neuromuscular abnormality and autonomic dysfunction in patients with cerebrotendinous xanthomatosis

<p>Abstract</p> <p>Background</p> <p>Cerebrotendinous xanthomatosis (CTX) is a rare lipid-storage disease. Neuromuscular abnormality and autonomic system (ANS) dysfuction in CTX are rarely examined in large-scale studies in the literature. We studied the peripheral nervous system, myopathology, and autonomic system of four CTX patients and performed a literature review of the reported CTX patients with peripheral neuropathy.</p> <p>Methods</p> <p>Four biochemically and genetically confirmed CTX patients, belonging to two families, were included for study and all received nerve conduction study (NCS), muscle biopsy for histopathologic and ultrastructural study, skin biopsy for intraepidermal nerve fiber (INEF) density measurement, autonomic testings including sympathetic skin response, R-R interval variation and head-up tilt test using an automated tilt table to record the changes of blood pressure and heart rate in different postures. The Q-Sweat test was also applied for the detection of sweat amount and onset time of response. The clinical characteristics, study methods and results of 13 studies of peripheral neuropathy in CTX patients in the literature were also recorded for analysis.</p> <p>Results</p> <p>The results of NCS study showed axonal sensory-motor polyneuropathy in three CTX cases and mixed axonal and demyelinating sensor-motor polyneuropathy in one. The myopathological and histopathologic studies revealed mild denervation characteristics, but the ultrastructural study revealed changes of mitochondria and the membranous system, and increased amounts of glycogen, lipofuscin and lipid deposition. The ANS study revealed different degrees of abnormalities in the applied tests and the INEF density measurement showed small fiber neuropathy in three of the four CTX patients. The literature review of peripheral neuropathy in CTX revealed different types of peripheral neuropathy, of which axonal peripheral neuropathy was the most common.</p> <p>Conclusions</p> <p>Peripheral neuropathy, especially the subtype of axonal sensori-motor neuropathy, is common in patients with CTX. Evidence of lipid metabolic derangement in CTX can be reflected in ultrastructural studies of muscles. With an adequate multi-parametric evaluation, a high incidence of ANS abnormalities can be seen in this rare lipid-storage disease, and a high incidence of small fiber involvement is also reflected in the IENF density measurement of skin biopsies.</p

Early Myeloid Dendritic Cell Dysregulation is Predictive of Disease Progression in Simian Immunodeficiency Virus Infection

Myeloid dendritic cells (mDC) are lost from blood in individuals with human immunodeficiency virus (HIV) infection but the mechanism for this loss and its relationship to disease progression are not known. We studied the mDC response in blood and lymph nodes of simian immunodeficiency virus (SIV)-infected rhesus macaques with different disease outcomes. Early changes in blood mDC number were inversely correlated with virus load and reflective of eventual disease outcome, as animals with stable infection that remained disease-free for more than one year had average increases in blood mDC of 200% over preinfection levels at virus set-point, whereas animals that progressed rapidly to AIDS had significant loss of mDC at this time. Short term antiretroviral therapy (ART) transiently reversed mDC loss in progressor animals, whereas discontinuation of ART resulted in a 3.5-fold increase in mDC over preinfection levels only in stable animals, approaching 10-fold in some cases. Progressive SIV infection was associated with increased CCR7 expression on blood mDC and an 8-fold increase in expression of CCL19 mRNA in lymph nodes, consistent with increased mDC recruitment. Paradoxically, lymph node mDC did not accumulate in progressive infection but rather died from caspase-8-dependent apoptosis that was reduced by ART, indicating that increased recruitment is offset by increased death. Lymph node mDC from both stable and progressor animals remained responsive to exogenous stimulation with a TLR7/8 agonist. These data suggest that mDC are mobilized in SIV infection but that an increase in the CCR7-CCL19 chemokine axis associated with high virus burden in progressive infection promotes exodus of activated mDC from blood into lymph nodes where they die from apoptosis. We suggest that inflamed lymph nodes serve as a sink for mDC through recruitment, activation and death that contributes to AIDS pathogenesis