基础科学和病原发生学
Parissa Fereydouni-Forouzandeh1,2, Nicolas Doyon1,2,3, Simon Duchesne1,2,3
1Laval University, Quebec City, QC, Canada.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 23, 2025
概括
人类大脑新陈代谢的数学模型显示出有希望的结果,但需要对外部有效性进行调整. 目前的模型捕捉短期过程,但需要增强以评估终身大脑代谢轨迹.
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
- 系统生物学 系统生物学
背景情况:
- 阿尔茨海默病的特点是,尽管能量需求增加,但大脑新陈代谢的调节下降.
- 了解这种代谢功能障碍需要一个多因素的因果框架.
- 数学建模为研究这些复杂的关系提供了一个有前途的方法.
研究的目的:
- 进行对人类大脑新陈代谢现有数学模型的范围审查.
- 确定适合未来在阿尔茨海默病研究中实施的模型.
- 引导开发用于研究大脑新陈代谢的计算框架.
主要方法:
- 按照PRISMA 2020指南进行系统范围审查.
- 使用关键词进行PubMed数据库搜索:"数学"",模型"",大脑"",葡萄糖".
- 对299项研究进行了选,其中14项根据纳入标准被选中进行定性分析.
主要成果:
- 选择的模型证明了足够的内部有效性 (提供方程,参数),但忽视了外部有效性.
- 只有50%的模型使用人类测量进行参数化;没有使用真实数据进行定量验证.
- 大多数模型使用普通微分方程,专注于短时间 (≤12小时),并探索各种代谢途径.
结论:
- 现有的计算模型可以捕捉基本的短期大脑新陈代谢组件.
- 模型具有很高的内部有效性,但外部有效性很差,限制了它们对现实场景的应用.
- 调整是必要的,以改善外部有效性和评估终身大脑代谢轨迹.
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