Elliot M Miller, Tat Chung D Chan, Carlos Montes-Matamoros, Omar Sharif, Laurent Pujo-Menjouet, Michael R Lindstrom
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引用次数: 0
Abstract
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.
许多神经退行性疾病(NDs)的特点是有毒蛋白质物种在大脑中缓慢的空间扩散。这些有毒蛋白质会诱发神经元应激,引发折叠蛋白反应(UPR),从而减缓或停止蛋白质翻译,间接减轻毒性负荷。然而,UPR 也可能触发导致细胞凋亡的过程,而且 UPR 与多种 ND 的进展有牵连。在本文中,我们建立了一个新的数学模型来描述朊病毒疾病 UPR 机制的时空动态。我们的模型以单个神经元为中心,代表蛋白 P(健康)和 S(有毒)以异二聚体动力学相互作用(S 与 P 相互作用形成两个 S)。该模型采用非线性反应-扩散方程耦合系统的形式,其中 P 具有延迟的非线性通量(来自 UPR 的延迟)。通过延迟,我们找到了在 P 蛋白和 S 蛋白水平上表现出振荡的参数区。我们发现,当 S 清除率和 S 扩散率分别小于 P 清除率和 P 扩散率时,振荡更为明显。随着启动 UPR 的延迟时间增加,振荡会变得更加明显。我们还考虑了准现实的临床参数,以了解可能的药物疗法如何改变朊病毒疾病的病程。我们发现,减少 P 的产生、降低招募率、增加 S 的扩散性、提高 UPR S 阈值和增加 S 清除率似乎是降低平均 UPR 强度并有可能缓和疾病进展的最有效方法。