Bayesian Computational Modeling: a new tool for understanding the reacti ve gliosis propagation

AUZMENDI J; MOFFATT L; RAMOS AJ

Buenos Aires

Congreso; Federation of Neurosciences Societies (FALAN); 2016

Federation of Neurosciences Societies (FALAN)

Ischemic brain injury promotes the acquisition of the reactive astrogliosis phenotype (RA) characterized by an increase of astrocyte volume and secretion of proinflammatory molecules. Initially focal, RA propagates to distal regions of the CNS but the underlying mechanism remains uncertain. Two major possibilities have been proposed. The DAMP hypothesis states that the simple diffusion of DAMPs from the necrotic core is determinant. The Soluble Mediators (SM) hypothesis argues that the subsequent signal carried out by SM secreted by the proximal astrocytes is essential for the RA propagation. We applied the Bayesian Computational Modeling (BCM) to distinguish between those mechanisms in the dynamics of the gliosis propagation. We developed a 1-D mathematical model that included a Markovian Model for the astrocytes activation coupled to a system of partial differential equations for the diffusion and binding of DAMPs and SM. Then we found the prior distribution for all the parameters of the system. We used GFAP-stained rat brain sections at 3 and 7 days post injury by cortical devascularization and we applied a morphological score to represent the observed RA gradient. Then we used the model to predict the proportion of astrocytes in each reactive state. We run a least square non linear fit to find the most probable combination of parameters and we compared the hypotheses with Thermodynamic Integration. We found a strong evidence for the mechanism that involve the secretion of SM.