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非局部模型在分析脑神经退行性蛋白动力学中的应用,及其在阿尔茨海默病中的应用。

Nonlocal models in the analysis of brain neurodegenerative protein dynamics with application to Alzheimer's disease.

机构信息

MS2Discovery Interdisciplinary Research Institute, Wilfrid Laurier University, Waterloo, Canada.

BCAM-Basque Center for Applied Mathematics, Bilbao, Spain.

出版信息

Sci Rep. 2022 May 5;12(1):7328. doi: 10.1038/s41598-022-11242-4.

Abstract

It is well known that today nearly one in six of the world's population has to deal with neurodegenerative disorders. While a number of medical devices have been developed for the detection, prevention, and treatments of such disorders, some fundamentals of the progression of associated diseases are in urgent need of further clarification. In this paper, we focus on Alzheimer's disease, where it is believed that the concentration changes in amyloid-beta and tau proteins play a central role in its onset and development. A multiscale model is proposed to analyze the propagation of these concentrations in the brain connectome. In particular, we consider a modified heterodimer model for the protein-protein interactions. Higher toxic concentrations of amyloid-beta and tau proteins destroy the brain cell. We have studied these propagations for the primary and secondary and their mixed tauopathies. We model the damage of a brain cell by the nonlocal contributions of these toxic loads present in the brain cells. With the help of rigorous analysis, we check the stability behaviour of the stationary points corresponding to the homogeneous system. After integrating the brain connectome data into the developed model, we see that the spreading patterns of the toxic concentrations for the whole brain are the same, but their concentrations are different in different regions. Also, the time to propagate the damage in each region of the brain connectome is different.

摘要

众所周知,当今世界上有六分之一的人口患有神经退行性疾病。尽管已经开发出许多用于此类疾病的检测、预防和治疗的医疗设备,但相关疾病进展的一些基本原理仍迫切需要进一步阐明。在本文中,我们专注于阿尔茨海默病,据信淀粉样β和tau 蛋白的浓度变化在其发病和发展中起着核心作用。提出了一种多尺度模型来分析这些浓度在脑连接组中的传播。特别是,我们考虑了一种用于蛋白质-蛋白质相互作用的改进的杂二聚体模型。更高浓度的淀粉样β和 tau 蛋白毒性会破坏脑细胞。我们研究了这些原发性和继发性tau 病以及它们的混合传播。我们通过存在于脑细胞中的这些毒性负荷的非局部贡献来模拟脑细胞的损伤。通过严格的分析,我们检查了对应于均匀系统的稳定点的稳定性行为。将脑连接组数据整合到所开发的模型中后,我们发现整个大脑中有毒浓度的传播模式相同,但在不同区域的浓度不同。此外,在脑连接组的每个区域传播损伤所需的时间也不同。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0479/9072437/77a4ab293a88/41598_2022_11242_Fig1_HTML.jpg

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