Data_Sheet_1_De novo Explorations of Sarcopenia via a Dynamic Model.docx

Background: The cause of sarcopenia has been observed over decades by clinical trials, which, however, are still insufficient to systematically unravel the enigma of how resistance exercise mediates skeletal muscle mass.
Materials and Methods: Here, we proposed a minimal regulatory network and developed a dynamic model to rigorously investigate the mechanism of sarcopenia. Our model is consisted of eight ordinary differential equations and incorporates linear and Hill-function terms to describe positive and negative feedbacks between protein species, respectively.
Results: A total of 720 samples with 10 scaled intensities were included in simulations, which revealed the expression level of AKT (maximum around 3.9-fold) and mTOR (maximum around 5.5-fold) at 3, 6, and 24 h at high intensity, and non-monotonic relation (ranging from 1.2-fold to 1.7-fold) between the graded intensities and skeletal muscle mass. Furthermore, continuous dynamics (within 24 h) of AKT, mTOR, and other proteins were obtained accordingly, and we also predicted the delaying effect with the median of maximized muscle mass shifting from 1.8-fold to 4.6-fold during a 4-fold increase of delay coefficient.
Conclusion: The de novo modeling framework sheds light on the interdisciplinary methodology integrating computational approaches with experimental results, which facilitates the deeper understandings of exercise training and sarcopenia.

研究背景：数十年来，临床试验已对肌肉减少症（sarcopenia）的致病机制开展了相关探索，但目前仍不足以系统阐明阻力运动介导骨骼肌质量变化的内在谜题。
材料与方法：本研究构建了一个极简调控网络，并开发了动力学模型以严谨解析肌肉减少症的发病机制。该模型包含8个常微分方程（ordinary differential equations），分别引入线性项与希尔函数（Hill-function）项来刻画蛋白质分子间的正反馈与负反馈调控关系。
研究结果：本模拟共纳入720个样本，包含10个标准化强度指标。分析结果显示，在高强度干预下，AKT与mTOR的表达水平在干预后3、6、24小时分别达到峰值（AKT峰值约为初始水平的3.9倍，mTOR峰值约为5.5倍）；分级运动强度与骨骼肌质量间呈现非单调相关关系，其变化幅度介于1.2倍至1.7倍之间。此外，本研究还获取了AKT、mTOR及其他蛋白质在24小时内的连续动态变化特征，并预测了延迟效应：当延迟系数提升4倍时，最大骨骼肌质量的中位数可从1.8倍升至4.6倍。
研究结论：本研究提出的全新建模框架为计算方法与实验结果相结合的跨学科研究范式提供了新的阐释视角，有助于更深入地理解运动训练与肌肉减少症的内在关联。