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Updated: Jan 23, 2026

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微重力中的数字双胞胎建模:用于预测和个性化空间医学的框架
Ruqaiyyah Siddiqui1, Rizwan Qaisar2, Adel Elmoselhi2
1Institute of Biological Chemistry, Biophysics and Bioengineering, Heriot-Watt University Edinburgh, EH14 4AS UK; Microbiota Research Center, Istinye University, Istanbul, 34010, Turkey.
Life sciences in space research
|January 21, 2026
概括
数字双胞胎通过整合各种数据来预测健康变化和优化对策,提供个性化的宇航员健康管理. 这种方法将太空医学从反应性观察转变为主动预测.
科学领域:
- 太空医学 太空医学
- 生物医学工程 生物医学工程
- 计算生物学是一种计算生物学.
背景情况:
- 人类太空飞行呈现出复杂的生理压力因素,影响多个身体系统.
- 当前的生物医学监测产生了大量的,被追溯分析的碎片化数据.
- 现有的数据分析方法不能动态指导实时宇航员健康对策.
研究的目的:
- 引入数字双胞胎技术作为个性化宇航员健康管理的框架.
- 使用数字双胞胎概述了多omics,生理和环境数据的整合.
- 提出实施数字双胞胎在太空飞行健康监测中的路线图.
主要方法:
- 开发个性化的数字双胞胎作为宇航员的自适应计算复制品.
- 将多omics,生理和行为数据流集成到数字双胞胎模型中.
- 提出一个阶段性实施战略,从模拟研究到任务整合.
主要成果:
- 数字双胞胎可以动态整合异构的宇航员健康数据.
- 个性化的数字双胞胎可以预测生理学降低条件.
- 可以指导优化对策协议和飞行医疗决策.
结论:
- 数字双胞胎技术使我们能够向精确的太空医学转变范式.
- 预测性健康管理可以通过预测性建模实现.
- 这个框架将宇航员监测从反应性转变为主动性.
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