通过数学模型揭示成人神经发生中的调节反馈机制。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Diana-Patricia Danciu, Filip Z Klawe, Alexey Kazarnikov, Laura Femmer, Ekaterina Kostina, Ana Martin-Villalba, Anna Marciniak-Czochra
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引用次数: 0

摘要

成人神经发生被定义为成人大脑中神经干细胞产生新神经元的过程。全面了解调节这一过程的机制对于开发有效的干预措施以减缓与衰老相关的成人神经发生的衰退至关重要。数学模型为研究神经干细胞及其谱系的动力学提供了一个有价值的工具,并揭示了这些过程在衰老过程中的变化。本研究利用实验数据,通过非线性微分方程模型研究神经群体之间的调节反馈机制,探索这些过程是如何被调节的。我们的观察表明,神经谱系的时间进化主要受神经干细胞的调节,而分化程度越高的神经群体对神经谱系的影响相对较弱。此外,我们阐明了不同亚种群支配这些规则的方式,并深入了解了特定扰动对系统的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unraveling regulatory feedback mechanisms in adult neurogenesis through mathematical modelling.

Adult neurogenesis is defined as the process by which new neurons are produced from neural stem cells in the adult brain. A comprehensive understanding of the mechanisms that regulate this process is essential for the development of effective interventions aimed at decelerating the decline of adult neurogenesis associated with ageing. Mathematical models provide a valuable tool for studying the dynamics of neural stem cells and their lineage, and have revealed alterations in these processes during the ageing process. The present study draws upon experimental data to explore how these processes are modulated by investigating regulatory feedback mechanisms among neural populations through the lens of nonlinear differential equations models. Our observations indicate that the time evolution of the neural lineage is predominantly regulated by neural stem cells, with more differentiated neural populations exerting a comparatively weaker influence. Furthermore, we shed light on the manner in which different subpopulations govern these regulations and gain insights into the impact of specific perturbations on the system.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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