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A Dynamic Simulation of Musculoskeletal Function in the Mouse Hindlimb During Trotting Locomotion

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, May 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Title
A Dynamic Simulation of Musculoskeletal Function in the Mouse Hindlimb During Trotting Locomotion
Published in
Frontiers in Bioengineering and Biotechnology, May 2018
DOI 10.3389/fbioe.2018.00061
Pubmed ID
Authors

James P. Charles, Ornella Cappellari, John R. Hutchinson

Abstract

Mice are often used as animal models of various human neuromuscular diseases, and analysis of these models often requires detailed gait analysis. However, little is known of the dynamics of the mouse musculoskeletal system during locomotion. In this study, we used computer optimization procedures to create a simulation of trotting in a mouse, using a previously developed mouse hindlimb musculoskeletal model in conjunction with new experimental data, allowing muscle forces, activation patterns, and levels of mechanical work to be estimated. Analyzing musculotendon unit (MTU) mechanical work throughout the stride allowed a deeper understanding of their respective functions, with the rectus femoris MTU dominating the generation of positive and negative mechanical work during the swing and stance phases. This analysis also tested previous functional inferences of the mouse hindlimb made from anatomical data alone, such as the existence of a proximo-distal gradient of muscle function, thought to reflect adaptations for energy-efficient locomotion. The results do not strongly support the presence of this gradient within the mouse musculoskeletal system, particularly given relatively high negative net work output from the ankle plantarflexor MTUs, although more detailed simulations could test this further. This modeling analysis lays a foundation for future studies of the control of vertebrate movement through the development of neuromechanical simulations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 72 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 26%
Student > Master 14 19%
Student > Doctoral Student 5 7%
Researcher 5 7%
Professor > Associate Professor 3 4%
Other 7 10%
Unknown 19 26%
Readers by discipline Count As %
Engineering 17 24%
Neuroscience 7 10%
Biochemistry, Genetics and Molecular Biology 4 6%
Agricultural and Biological Sciences 4 6%
Sports and Recreations 3 4%
Other 10 14%
Unknown 27 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 09 March 2023.
All research outputs
#2,032,408
of 25,457,297 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#240
of 8,542 outputs
Outputs of similar age
#41,888
of 342,313 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#11
of 55 outputs
Altmetric has tracked 25,457,297 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,542 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 97% of its peers.
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 342,313 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.