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Updated: May 25, 2026
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Assessing Functional Metrics of Skeletal Muscle Health in Human Skeletal Muscle Microtissues
Published on: February 18, 2021
A framework for mapping between "living" muscle model parameters and systems biology data for muscle tissue
1Department of Biomedical Engineering, Marquette University, Milwaukee, WI 53233, USA. jack.winters@mu.edu
Summary
This study introduces adaptable "living" muscle models by integrating protein dynamics. This approach enhances understanding of muscle function and aids in interpreting biological data from muscle biopsies.
Area of Science:
- Biomedical Engineering
- Systems Biology
- Muscle Physiology
Background:
- Muscle models traditionally treat muscle as a static actuator, neglecting its adaptive biological nature.
- Existing models do not account for the dynamic changes in muscle tissue over time.
Purpose of the Study:
- To extend Hill-based muscle models by incorporating the adaptive properties of living muscle tissue.
- To establish a framework for dynamic muscle modeling using protein family functions.
- To provide a method for interpreting high-throughput systems biology data from muscle biopsies.
Main Methods:
- Conceptualizing muscle fascicles as well-mixed composite materials.
- Identifying three key protein families: excitation-activation, mechanical transmission, and energy supply.
- Developing a framework to map protein and transcript regulation to muscle property estimation.
Main Results:
- Identified three functional protein family classes crucial for muscle activity.
- Proposed a framework linking protein regulation to muscle model parameters.
- Demonstrated potential for interpreting systems biology data in muscle research.
Conclusions:
- The developed framework enables the creation of evolving "living" muscle models.
- This approach offers a novel method for analyzing muscle tissue biopsies and understanding myopathies.
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