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在神经退行性疾病中传播的病态蛋白质的基于Connectome的生物物理模型

Peng Ren^1,2, Xuehua Cui^1,3, Xia Liang^1,3

¹Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology, Harbin, China.

PLoS computational biology

|January 21, 2025

概括

本综述探讨了模拟神经退行性疾病中类蛋白传播的计算模型. 这些模型有助于了解疾病的进展,并开发新的治疗方法.

科学领域:

神经科学是一个神经科学.
计算生物学计算生物学
生物物理学的生物物理.

背景情况:

神经退行性疾病涉及渐进的神经元损失,患病率越来越高,治疗方法有限.
致病机制尚不清楚,但涉及子样蛋白质的错误折叠和传播.
通过神经网络传播的异常蛋白质会导致神经元死亡.

研究的目的:

审查和比较三种基于连接体的生物物理模型,以模拟病态蛋白质在体内传播.
阐明这些模型的基本原则和应用.
提出模型优化的方向和统一的评估框架.

主要方法:

网络扩散模型网络扩散模型
流行病传播模型
基于代理的易受感染-移除 (SIR) 模型.

主要成果:

审查的模型为疾病进展提供了有希望的预测能力.
提供了对每个模型的优点和弱点的比较.
引入了优化模型和统一评估框架的新方向.

结论:

基于Connectome的生物物理模型是了解神经退行性疾病动态的宝贵工具.
本次审查旨在促进研究,加快这些模型的临床转化.
优化模型可以推进神经退行性疾病的治疗策略.

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