朊病毒疾病的延迟随机和确定性模型的理论与模拟。

IF 2.3 4区 数学 Q2 BIOLOGY
Gangadhara Boregowda, Omar Sharif, Daniel Gutierrez Iii, Allegra Simmons, Laurent Pujo-Menjouet, Tamer Oraby, Michael R Lindstrom
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引用次数: 0

摘要

神经退行性疾病(NDs),如阿尔茨海默病、帕金森病和朊病毒疾病,其特征是有毒蛋白质在大脑中的动态传播。在朊病毒疾病中,由神经元产生的细胞朊病毒蛋白(PrP C)错误折叠成一种有毒的形式,即痒病朊病毒蛋白(PrP Sc)。PrP Sc诱导神经元应激,最终导致细胞死亡。在本文中,我们建立了朊病毒疾病进展的数学模型,其中包括细胞防御机制,该机制引入了影响蛋白质翻译的延迟项和影响系统的未解释的生物因素的波动项。我们还扩展了该模型,以捕捉有毒蛋白质在大脑连接体上的空间扩散。我们的第一个目标是建立一个全球性的正解的存在性和唯一性的朊病毒疾病模型。然后,我们分析了模型的渐近行为,通过识别持久性和消除有毒蛋白质的制度。对于确定性时滞系统,我们进行了持久性的稳定性分析,并证明了系统存在Hopf分岔。我们还研究了随机模型平衡态的波动强度。此外,我们提出了数值模拟来说明使用生物学相关参数的模型动力学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Theory and simulations of delayed stochastic and deterministic models of prion diseases.

Neurodegenerative diseases (NDs), such as Alzheimer's, Parkinson's, and prion diseases, are characterized by the dynamical spread of toxic proteins through the brain. In prion diseases, cellular prion protein ( PrP C ), produced by neurons, misfolds into a toxic form, known as scrapie prion protein ( PrP Sc ). PrP Sc induces neuronal stress which ultimately leads to cell death. In this paper, we develop mathematical models for the progression of prion diseases, incorporating a cellular defense mechanism that introduces a delay term affecting protein translation and a volatility term accounting for unaccounted biological factors influencing the system. We also extend the model to capture the spatial spread of toxic proteins over the brain connectome. Our first objective is to establish the existence and uniqueness of a global positive solution to the prion disease models. Afterwards, we analyze the asymptotic behavior of the models by identifying regimes of persistence and extinction of toxic proteins. For the deterministic delayed systems, we perform a stability analysis for the persistence and demonstrate that the system undergoes a Hopf bifurcation. We also study the intensity of fluctuations of the equilibrium state of the stochastic model. Additionally, we present numerical simulations to illustrate the model dynamics using biologically relevant parameters.

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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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