ArticleThe Journal of experimental biology2025
Using physiologically based models to predict in vivo skeletal muscle energetics.
Article in The Journal of experimental biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Soft, Flexible, and Stretchable Platforms for Tissue-Interfaced Bioelectronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Propulsion without penalty: greater soleus force with stiffer footwear does not necessarily increase estimated soleus metabolic cost across walking speeds.Journal of applied physiology (Bethesda, Md. : 1985) · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
Understanding how muscles use energy is essential for elucidating the role of skeletal muscle in animal locomotion. Yet, experimental measures of in vivo muscle energetics are challenging to obtain, so physiologically based muscle models are often used to estimate energy use. These predictions of individual muscle energy expenditure are not often compared with indirect whole-body measures of energetic cost. Here, we examined and illustrated the capability of physiologically based muscle models to predict in vivo measures of energy use, which rely on fundamental relationships between muscle mechanical state and energy consumption. To improve model predictions and ensure a physiological basis for model parameters, we refined our model to include data from isolated muscle experiments and account for inefficiencies in ATP recovery processes. Simulations were performed to capture three different experimental protocols, which involved varying contraction frequency, duty cycle and muscle fascicle length. Our results demonstrated the ability of the model to capture the dependence of energetic cost on mechanical state across contractile conditions, but tended to underpredict the magnitude of energetic cost. Our analysis revealed that the model was most sensitive to the force-velocity parameters and the data informing the energetic parameters when predicting in vivo energetic rates. This work highlights that it is the mechanics of skeletal muscle contraction that govern muscle energy use, although the precise physiological parameters for human muscle likely require detailed investigation.
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