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神经退行性疾病建模:模型系统复合物的“逐步”和“网络”组织。

Modeling of Neurodegenerative Diseases: 'Step by Step' and 'Network' Organization of the Complexes of Model Systems.

机构信息

Biological Faculty, Lomonosov Moscow State University, 1-12, Leninskye Gory, 119992 Moscow, Russia.

Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 1-73, Leninskye Gory, 119992 Moscow, Russia.

出版信息

Int J Mol Sci. 2022 Dec 29;24(1):604. doi: 10.3390/ijms24010604.

Abstract

Neurodegenerative diseases have acquired the status of one of the leading causes of death in developed countries, which requires creating new model systems capable of accurately reproducing the mechanisms underlying these pathologies. Here we analyzed modern model systems and their contribution to the solution of unexplored manifestations of neuropathological processes. Each model has unique properties that make it the optimal tool for modeling certain aspects of neurodegenerative disorders. We concluded that to optimize research, it is necessary to combine models into complexes that include organisms and artificial systems of different organizational levels. Such complexes can be organized in two ways. The first method can be described as "step by step", where each model for studying a certain characteristic is a separate step that allows using the information obtained in the modeling process for the gradual study of increasingly complex processes in subsequent models. The second way is a 'network' approach. Studies are carried out with several types of models simultaneously, and experiments with each specific type are adjusted in conformity with the data obtained from other models. In our opinion, the 'network' approach to combining individual model systems seems more promising for fundamental biology as well as diagnostics and therapy.

摘要

神经退行性疾病已成为发达国家的主要死亡原因之一,这就需要创建新的模型系统,以能够准确再现这些病理的潜在机制。在这里,我们分析了现代模型系统及其对解决神经病理过程中未被探索表现的贡献。每个模型都具有独特的特性,使其成为模拟神经退行性疾病某些方面的最佳工具。我们得出的结论是,为了优化研究,有必要将模型组合成包含不同组织层次的生物体和人工系统的综合体。这种综合体可以通过两种方式来组织。第一种方法可以描述为“逐步”,其中用于研究特定特征的每个模型都是一个单独的步骤,允许将建模过程中获得的信息用于后续模型中对越来越复杂的过程的逐步研究。第二种方法是“网络”方法。同时对几种类型的模型进行研究,并且针对每种特定类型的实验都根据从其他模型获得的数据进行调整。在我们看来,对于基础生物学以及诊断和治疗,将单个模型系统组合成“网络”方法似乎更有前途。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac14/9820769/d5530b78c093/ijms-24-00604-g001.jpg

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