RESUMO
The dairy cow experiences the most significant impact from negative energy balance during this period, which adversely affects reproductive health. Consequently, most pathologies affect dairy cows during this time frame. Thus, with the primary objective of reducing the incidence of these pathologies on dairy farms, we questioned whether supplemental zeolite administration in cattle feed would affect metabolism and reproductive health. Therefore, we proposed introducing an antepartum and postpartum supplementation of 400 g of zeolite in the basal diet. The control group received only the basal diet without zeolite supplementation. Monitoring the results stemmed from the consideration that reproductive health can only be present based on an unaltered energy metabolism. Hence, we deemed it necessary to analyze several metabolic markers in light of the expected outcomes concerning reproductive health. Cows treated with zeolite exhibited a calving to first service interval 12.78 days earlier than those in the control group. Moreover, the average number of services per conception used for future gestation was 0.44 lower in the zeolite-treated group compared to the control group (p<0.05). Additionally, the treatment group showed a lower presence of pathogens in the uterus and displayed a more favorable average uterine score. Observations following the completion of the research point towards an improvement in the health of transition dairy cows, opening a new path for dairy farms in terms of preventing postpartum pathologies. Indeed, the benefits from this study primarily impact the animals rather than directly influencing milk production. Therefore, further research is necessary in this regard.
RESUMO
The dynamics of HIV-1 infection consist of three distinct phases starting with primary infection, then latency and finally AIDS or drug therapy. In this paper we model the dynamics of primary infection and the beginning of latency. We show that allowing for time delays in the model better predicts viral load data when compared to models with no time delays. We also find that our model of primary infection predicts the turnover rates for productively infected T cells and viral totals to be much longer than compared to data from patients receiving anti-viral drug therapy. Hence the dynamics of the infection can change dramatically from one stage to the next. However, we also show that with the data available the results are highly sensitive to the chosen model. We compare the results using analysis and Monte Carlo techniques for three different models and show how each predicts rather dramatic differences between the fitted parameters. We show, using a chi(2) test, that these differences between models are statistically significant and using a jackknifing method, we find the confidence intervals for the parameters. These differences in parameter estimations lead to widely varying conclusions about HIV pathogenesis. For instance, we find in our model with time delays the existence of a Hopf bifurcation that leads to sustained oscillations and that these oscillations could simulate the rapid turnover between viral strains and the appropriate CTL response necessary to control the virus, similar to that of a predator-prey type system.