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Bull Math Biol ; 86(7): 82, 2024 Jun 05.
Artigo em Inglês | MEDLINE | ID: mdl-38837083

RESUMO

Many neurodegenerative diseases (NDs) are characterized by the slow spatial spread of toxic protein species in the brain. The toxic proteins can induce neuronal stress, triggering the Unfolded Protein Response (UPR), which slows or stops protein translation and can indirectly reduce the toxic load. However, the UPR may also trigger processes leading to apoptotic cell death and the UPR is implicated in the progression of several NDs. In this paper, we develop a novel mathematical model to describe the spatiotemporal dynamics of the UPR mechanism for prion diseases. Our model is centered around a single neuron, with representative proteins P (healthy) and S (toxic) interacting with heterodimer dynamics (S interacts with P to form two S's). The model takes the form of a coupled system of nonlinear reaction-diffusion equations with a delayed, nonlinear flux for P (delay from the UPR). Through the delay, we find parameter regimes that exhibit oscillations in the P- and S-protein levels. We find that oscillations are more pronounced when the S-clearance rate and S-diffusivity are small in comparison to the P-clearance rate and P-diffusivity, respectively. The oscillations become more pronounced as delays in initiating the UPR increase. We also consider quasi-realistic clinical parameters to understand how possible drug therapies can alter the course of a prion disease. We find that decreasing the production of P, decreasing the recruitment rate, increasing the diffusivity of S, increasing the UPR S-threshold, and increasing the S clearance rate appear to be the most powerful modifications to reduce the mean UPR intensity and potentially moderate the disease progression.


Assuntos
Conceitos Matemáticos , Modelos Neurológicos , Neurônios , Doenças Priônicas , Resposta a Proteínas não Dobradas , Resposta a Proteínas não Dobradas/fisiologia , Doenças Priônicas/metabolismo , Doenças Priônicas/patologia , Doenças Priônicas/fisiopatologia , Neurônios/metabolismo , Humanos , Animais , Dinâmica não Linear , Simulação por Computador , Príons/metabolismo , Análise Espaço-Temporal , Apoptose
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