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A multiscale chemo-electro-mechanical skeletal muscle model to analyze muscle contraction and force generation for different muscle fiber arrangements

Overview of attention for article published in Frontiers in Physiology, December 2014
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Title
A multiscale chemo-electro-mechanical skeletal muscle model to analyze muscle contraction and force generation for different muscle fiber arrangements
Published in
Frontiers in Physiology, December 2014
DOI 10.3389/fphys.2014.00498
Pubmed ID
Authors

Thomas Heidlauf, Oliver Röhrle

Abstract

The presented chemo-electro-mechanical skeletal muscle model relies on a continuum-mechanical formulation describing the muscle's deformation and force generation on the macroscopic muscle level. Unlike other three-dimensional models, the description of the activation-induced behavior of the mechanical model is entirely based on chemo-electro-mechanical principles on the microscopic sarcomere level. Yet, the multiscale model reproduces key characteristics of skeletal muscles such as experimental force-length and force-velocity data on the macroscopic whole muscle level. The paper presents the methodological approaches required to obtain such a multiscale model, and demonstrates the feasibility of using such a model to analyze differences in the mechanical behavior of parallel-fibered muscles, in which the muscle fibers either span the entire length of the fascicles or terminate intrafascicularly. The presented results reveal that muscles, in which the fibers span the entire length of the fascicles, show lower peak forces, more dispersed twitches and fusion of twitches at lower stimulation frequencies. In detail, the model predicted twitch rise times of 38.2 and 17.2 ms for a 12 cm long muscle, in which the fibers span the entire length of the fascicles and with twelve fiber compartments in series, respectively. Further, the twelve-compartment model predicted peak twitch forces that were 19% higher than in the single-compartment model. The analysis of sarcomere lengths during fixed-end single twitch contractions at optimal length predicts rather small sarcomere length changes. The observed lengths range from 75 to 111% of the optimal sarcomere length, which corresponds to a region with maximum filament overlap. This result suggests that stability issues resulting from activation-induced stretches of non-activated sarcomeres are unlikely in muscles with passive forces appearing at short muscle length.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Germany 1 2%
Ireland 1 2%
Unknown 58 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 21%
Researcher 6 10%
Student > Master 6 10%
Student > Postgraduate 5 8%
Student > Doctoral Student 5 8%
Other 12 20%
Unknown 14 23%
Readers by discipline Count As %
Engineering 28 46%
Agricultural and Biological Sciences 6 10%
Biochemistry, Genetics and Molecular Biology 3 5%
Unspecified 1 2%
Mathematics 1 2%
Other 4 7%
Unknown 18 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 August 2022.
All research outputs
#18,009,288
of 23,130,383 outputs
Outputs from Frontiers in Physiology
#7,285
of 13,884 outputs
Outputs of similar age
#243,589
of 354,594 outputs
Outputs of similar age from Frontiers in Physiology
#55
of 111 outputs
Altmetric has tracked 23,130,383 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,884 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 354,594 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.