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Discrete and Continuum Approximations for Collective Cell Migration in a Scratch Assay with Cell Size Dynamics

Overview of attention for article published in Bulletin of Mathematical Biology, January 2018
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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Title
Discrete and Continuum Approximations for Collective Cell Migration in a Scratch Assay with Cell Size Dynamics
Published in
Bulletin of Mathematical Biology, January 2018
DOI 10.1007/s11538-018-0398-2
Pubmed ID
Authors

Oleksii M. Matsiaka, Catherine J Penington, Ruth E. Baker, Matthew J. Simpson

Abstract

Scratch assays are routinely used to study the collective spreading of cell populations. In general, the rate at which a population of cells spreads is driven by the combined effects of cell migration and proliferation. To examine the effects of cell migration separately from the effects of cell proliferation, scratch assays are often performed after treating the cells with a drug that inhibits proliferation. Mitomycin-C is a drug that is commonly used to suppress cell proliferation in this context. However, in addition to suppressing cell proliferation, mitomycin-C also causes cells to change size during the experiment, as each cell in the population approximately doubles in size as a result of treatment. Therefore, to describe a scratch assay that incorporates the effects of cell-to-cell crowding, cell-to-cell adhesion, and dynamic changes in cell size, we present a new stochastic model that incorporates these mechanisms. Our agent-based stochastic model takes the form of a system of Langevin equations that is the system of stochastic differential equations governing the evolution of the population of agents. We incorporate a time-dependent interaction force that is used to mimic the dynamic increase in size of the agents. To provide a mathematical description of the average behaviour of the stochastic model we present continuum limit descriptions using both a standard mean-field approximation and a more sophisticated moment dynamics approximation that accounts for the density of agents and density of pairs of agents in the stochastic model. Comparing the accuracy of the two continuum descriptions for a typical scratch assay geometry shows that the incorporation of agent growth in the system is associated with a decrease in accuracy of the standard mean-field description. In contrast, the moment dynamics description provides a more accurate prediction of the evolution of the scratch assay when the increase in size of individual agents is included in the model.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 27%
Researcher 4 13%
Student > Bachelor 3 10%
Student > Master 3 10%
Student > Doctoral Student 2 7%
Other 3 10%
Unknown 7 23%
Readers by discipline Count As %
Engineering 4 13%
Biochemistry, Genetics and Molecular Biology 4 13%
Mathematics 3 10%
Agricultural and Biological Sciences 3 10%
Medicine and Dentistry 2 7%
Other 4 13%
Unknown 10 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 20 July 2019.
All research outputs
#13,016,439
of 23,045,021 outputs
Outputs from Bulletin of Mathematical Biology
#480
of 1,104 outputs
Outputs of similar age
#205,730
of 441,168 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#11
of 30 outputs
Altmetric has tracked 23,045,021 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,104 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 56% 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 441,168 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.