RESUMO
Q fever infection in dairy herds is introduced through the transmission of the bacterium Coxiella burnetii, resulting in multiple detrimental effects such as reduction of lactation, abortions and chronic infection. Particularly in the UK, recent evidence suggests that the infection is endemic in dairy cattle. In this work, we investigate the dynamics of the disease with the aim to disentangle the relationship between the heterogeneity in the shedding routes and their effect on the environmental contamination. We develop a mathematical model for the transmission of Q fever within UK cattle herds by coupling the within-herd infection cycle of the disease with farm demographics and environmental effects, introduced by either the indoor or outdoor environment. Special focus is given on the mechanism of transmission in nulliparous heifers and multiparous cattle. We calibrate the model based on available knowledge on various epidemiological aspects of the disease and on data regarding farm demographics available in the UK DEFRA. The resulting model is able to reproduce the reported prevalence levels by field and in silico studies, as well as their evolution in time. In addition, it is built in an manner that allows the investigation of different housing techniques, farm management styles and a variety of interventions. Sensitivity analysis further reveals the parameters having the major effect in maintaining high prevalence levels of seropositive and shedding cattle. The present analysis aims also to indicate the gaps in the available data required to optimise the proposed model or future models that will developed on the basis of the one proposed herein. Finally, the developed model can serve as mathematical proof for the assessment of various interventions for controlling the dynamics of Q fever infection.
RESUMO
Lactate in the brain is considered an important fuel and signalling molecule for neuronal activity, especially during neuronal activation. Whether lactate is shuttled from astrocytes to neurons or from neurons to astrocytes leads to the contradictory Astrocyte to Neuron Lactate Shuttle (ANLS) or Neuron to Astrocyte Lactate Shuttle (NALS) hypotheses, both of which are supported by extensive, but indirect, experimental evidence. This work explores the conditions favouring development of ANLS or NALS phenomenon on the basis of a model that can simulate both by employing the two parameter sets proposed by Simpson et al. (J Cereb. Blood Flow Metab., 27:1766, 2007) and Mangia et al. (J of Neurochemistry, 109:55, 2009). As most mathematical models governing brain metabolism processes, this model is multi-scale in character due to the wide range of time scales characterizing its dynamics. Therefore, we utilize the Computational Singular Perturbation (CSP) algorithm, which has been used extensively in multi-scale systems of reactive flows and biological systems, to identify components of the system that (i) generate the characteristic time scale and the fast/slow dynamics, (ii) participate to the expressions that approximate the surfaces of equilibria that develop in phase space and (iii) control the evolution of the process within the established surfaces of equilibria. It is shown that a decisive factor on whether the ANLS or NALS configuration will develop during neuronal activation is whether the lactate transport between astrocytes and interstitium contributes to the fast dynamics or not. When it does, lactate is mainly generated in astrocytes and the ANLS hypothesis is realised, while when it doesn't, lactate is mainly generated in neurons and the NALS hypothesis is realised. This scenario was tested in exercise conditions.