应用于阿尔茨海默病的蛋白质扩散和组织萎缩的耦合数学和数值模型

IF 6.9 1区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Valentina Pederzoli , Mattia Corti , Davide Riccobelli , Paola F. Antonietti
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引用次数: 0

摘要

本文的目的是在实践中介绍、分析和测试一个新的数学模型,该模型描述了生物制剂扩散驱动的生物组织萎缩之间的相互作用,并应用于神经退行性疾病。本文提出了一种新的数学和计算模型,该模型包括用于物质扩散的Fisher-Kolmogorov方程和控制质量损失的弹性方程。这些方程通过一个逻辑定律交织在一起,决定了介质质量的减少。该模型适用于阿尔茨海默病的发病和发展。在这里,方程式描述了错误折叠τ-蛋白的繁殖和随后的脑萎缩的疾病特征。为了解决数值上继承的复杂性,我们提出了一种不连续Galerkin方法进行空间离散,而时间积分依赖于Crank-Nicolson方法。我们提出了数学模型,探讨了它的特点,并提出了离散化的建议。通过收敛结果验证了模型的实现,并对阿尔茨海默病发病的应用场景进行了仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A coupled mathematical and numerical model for protein spreading and tissue atrophy applied to Alzheimer’s disease
The aim of this paper is to introduce, analyze and test in practice a new mathematical model describing the interplay between biological tissue atrophy driven by the diffusion of a biological agent, with applications to neurodegenerative disorders. This study introduces a novel mathematical and computational model comprising a Fisher–Kolmogorov equation for species diffusion coupled with an elasticity equation governing mass loss. These equations intertwine through a logistic law dictating the reduction of the medium’s mass. This model is applied to the onset and development of Alzheimer’s disease. Here, the equations describe the propagation of misfolded τ-proteins and the ensuing brain atrophy characteristic of the disease. To address numerically the inherited complexities, we propose a Discontinuous Galerkin method for spatial discretization, while time integration relies on the Crank–Nicolson method. We present the mathematical model, explore its characteristics, and present the proposed discretization. Furthermore, convergence results are presented to verify the model’s implementation, accompanied by simulations illustrating the application scenario of the onset of Alzheimer’s disease.
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来源期刊
CiteScore
12.70
自引率
15.30%
发文量
719
审稿时长
44 days
期刊介绍: Computer Methods in Applied Mechanics and Engineering stands as a cornerstone in the realm of computational science and engineering. With a history spanning over five decades, the journal has been a key platform for disseminating papers on advanced mathematical modeling and numerical solutions. Interdisciplinary in nature, these contributions encompass mechanics, mathematics, computer science, and various scientific disciplines. The journal welcomes a broad range of computational methods addressing the simulation, analysis, and design of complex physical problems, making it a vital resource for researchers in the field.
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