Chinese Journal of Tissue Engineering Research ›› 2026, Vol. 30 ›› Issue (19): 5057-5065.doi: 10.12307/2026.790

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In vitro simulation of cellular exercise environments: advancements in methodology and signal simulation

Chen Bingao1, Chen Hongbao1, Xie Hao1, Ding Xinglei2, Yuan Yu1, Zhang Jiahao1, Ban Weikang1, Xu Shenghao1, Yuan Yang1   

  1. 1School of Physical Education, 2School of Life Sciences, Qufu Normal University, Qufu 273165, Shandong Province, China
  • Received:2025-10-15 Accepted:2025-12-09 Online:2026-07-08 Published:2026-02-24
  • Contact: Yuan Yang, PhD, Associate professor, School of Physical Education, Qufu Normal University, Qufu 273165, Shandong Province, China
  • About author:Chen Bingao, MS candidate, School of Physical Education, Qufu Normal University, Qufu 273165, Shandong Province, China
  • Supported by:
    Taishan Scholars Talent Project, No. tsqn202312181 (to YY); Shandong Provincial Youth Innovation Team Project, No. 2023RW102 (to YY)

Abstract: BACKGROUND: With an increasing understanding of the health benefits of exercise, research on the mechanisms of exercise intervention has become a focal point. Traditional studies rely on in vivo animal models or multi-omics techniques to indirectly infer exercise intervention mechanisms, but the research is not in-depth enough, and many disease models cannot achieve the prescribed exercise intensity. Therefore, in vitro cell-based exercise environment simulation techniques are of particular significance. Existing technologies primarily focus on the replication of single signals, failing to comprehensively simulate the interaction of multi-dimensional signals during exercise, which limits the understanding of exercise adaptation mechanisms.
OBJECTIVE: To explore the technological advancements in in vitro cell-based exercise environment simulation, analyze the advantages of existing signal simulation techniques, and propose a new framework integrating multi-dimensional signals to promote the precise replication of exercise mechanisms and application research in related fields.
METHODS: This study conducted a search in the PubMed and Web of Science databases using keywords such as Exercise, Physiology, Molecular Signals, Myokines, Exerkines, etc. Relevant original research and review articles were selected, and after the initial search and removal of duplicates, a total of 5 046 related articles were identified. After further screening, 99 articles were ultimately included in the study.
RESULTS AND CONCLUSION: Existing in vitro cell-based exercise simulation technologies have made progress in replicating certain specific attributes of exercise, such as mechanical stretch and electrical signals. However, these technologies have yet to fully replicate the multi-dimensional signal interactions that occur during exercise. By integrating mechanical forces, electrophysiological stimulation, and bioactive factors, future simulation technologies are expected to more accurately replicate the impact of exercise on cell metabolism, gene expression, and phenotypic shaping, providing a more precise experimental platform for studying exercise mechanisms. Moreover, innovations and optimizations in in vitro exercise simulation technologies will offer crucial support for exercise medicine, drug development, and regenerative medicine.

Key words: ">exercise, cellular exercise environment, in vitro cells, exercise simulation, mechanical stimulation, electrophysiological stimulation, exercise factors

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