Evidence map›Paper›PMID 39960312›Full record

ArticleThe Journal of experimental biology2025

Using physiologically based models to predict in vivo skeletal muscle energetics.

Ryan N Konno, Glen A Lichtwark, Taylor J M Dick

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Soft, Flexible, and Stretchable Platforms for Tissue-Interfaced Bioelectronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ryan N KonnoSchool of Biomedical Sciences, The University of Queensland, St Lucia, QLD 4072, Australia.ORCID 0000-0003-1761-5266
Glen A LichtwarkSchool of Exercise and Nutrition Sciences, Queensland University of Technology, Brisbane, QLD 4000, Australia.ORCID 0000-0001-7366-3348
Taylor J M DickSchool of Biomedical Sciences, The University of Queensland, St Lucia, QLD 4072, Australia.ORCID 0000-0002-7662-9716

Funding

Australian Research Council DP230101886Australian Research Council FTFT190100129Natural Science and Engineering Council of CanadaThe University of QueenslandUniversity of Queensland
6 · The paper itself

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.

Indexed as

Energy MetabolismModels, BiologicalMuscle, SkeletalAnimalsBiomechanical PhenomenaMaleMuscle ContractionBiomechanicsMathematical modellingMetabolic costMuscle–tendon mechanics

Identifiers

PMID39960312
PMCPMC11993265

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.