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Fiber Network Models Predict Enhanced Cell Mechanosensing on Fibrous Gels

Overview of attention for article published in Journal of Biomechanical Engineering, September 2016
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Article details
Title
Fiber Network Models Predict Enhanced Cell Mechanosensing on Fibrous Gels
Published in
Journal of Biomechanical Engineering, September 2016
DOI 10.1115/1.4034490
Pubmed ID
Authors
Abstract

The propagation of mechanical signals through non-linear fibrous tissues is much more extensive than through continuous synthetic hydrogels. Results from recent studies indicate that increased mechanical propagation arises from the fibrous nature of the material rather than the strain-stiffening property. The relative importance of different parameters of the fibrous network structure to this propagation, however, remain unclear. In this work, we directly compared the mechanical response of substrates of varying thickness subjected to a constant cell traction force using either a non-fibrous strain-stiffening continuum-based model or a volume-averaged fiber network model consisting of two different types of fiber network structures: one with low fiber connectivity (Growth Networks) and one with high fiber connectivity (Delaunay Networks). The Growth Network fiber models predicted a greater propagation of substrate displacements through the model and a greater sensitivity to gel thickness compared to the more connected Delaunay Networks and the nonlinear continuum model. Detailed analysis of the results indicates that rotational freedom of the fibers in a network with low fiber connectivity are critically important for enhanced, long-range mechanosensing. Our findings demonstrate the utility of multiscale models in predicting cells mechanosensing on fibrous gels, and they provide a more complete understanding of how cell traction forces propagate through fibrous tissues, which has implications for the design of engineered tissues and the stem cell niche.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Netherlands 1 2%
United Kingdom 1 2%
Unknown 52 96%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 14 26%
Student > Doctoral Student 4 7%
Student > Master 4 7%
Researcher 4 7%
Professor > Associate Professor 3 6%
Other 10 19%
Unknown 15 28%
Readers by discipline
Readers by discipline Count As %
Engineering 19 35%
Physics and Astronomy 4 7%
Chemistry 3 6%
Biochemistry, Genetics and Molecular Biology 2 4%
Agricultural and Biological Sciences 2 4%
Other 6 11%
Unknown 18 33%
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 09 January 2017.
All research outputs
#20,413,129
of 22,963,381 outputs
Outputs from Journal of Biomechanical Engineering
#1,054
of 1,174 outputs
Outputs of similar age
#294,966
of 337,897 outputs
Outputs of similar age from Journal of Biomechanical Engineering
#7
of 8 outputs
Altmetric has tracked 22,963,381 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,174 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 1st percentile – i.e., 1% 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 337,897 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one.