Molecular mechanism of energy metabolism in astrocytes: a parametric model from FDG PET images

Lecca, Paola and Lecca, Michela (2007) Molecular mechanism of energy metabolism in astrocytes: a parametric model from FDG PET images. UNSPECIFIED.

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    The signals detected during physiological activation of the brain with F-deoxyglucose DG PET reflect predominantly uptake of this tracer into astrocytes. This notion provides a cellular and molecular basis for the FDG PET technique. Although in recent years the functional brain imaging has experienced enormous advances, the cellular and, in particular, the molecular mechanisms generating the signals detected by these techniques are not completely known. In this paper, we present a computational model that attempts to disentangle the intricate nature of the molecular interactions governing the brain energy metabolism. The model describes the glutamate-stimulated glucose uptake and use into astrocytes. It consists of a set of ordinary dif- ferential equations, each of which specifying the time-behavior of the main molecular species involved in the astrocytic glucose use (i. e. glutamate, glucose, Na+, beta-threohydroxyaspartate) and the dynam- ical rates of glutamate, glucose and Na+ uptake. The kinetic rates constants of the model have been identified on a set of dynamic PET images. As far as we know, a mathematical and computational model of the brain energy metabolism at the molecular level has been never proposed. The relevance of such a model to the PET functional brain imaging consists in providing an in silico framework, in which to experiment the molecular glucose dynamics and elucidate their still elusive aspects. This is the preliminary version of a paper that was published in Advances in Brain, Vision, and Artificial Intelligence, Lecture Notes in Computer Science, Springer. The original version of the publication is available at

    Item Type: Departmental Technical Report
    Department or Research center: CoSBi (Center for Computational and Systems Biology)
    Subjects: Q Science > QA Mathematics > QA076 Computer software > QA076.7 Programming Languages - Semantics
    Report Number: TR-07-2007
    Repository staff approval on: 01 Dec 2009

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