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Tailoring Mathematical Models to Stem-Cell Derived Cardiomyocyte Lines Can Improve Predictions of Drug-Induced Changes to Their Electrophysiology

Overview of attention for article published in Frontiers in Physiology, December 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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Title
Tailoring Mathematical Models to Stem-Cell Derived Cardiomyocyte Lines Can Improve Predictions of Drug-Induced Changes to Their Electrophysiology
Published in
Frontiers in Physiology, December 2017
DOI 10.3389/fphys.2017.00986
Pubmed ID
Authors

Chon Lok Lei, Ken Wang, Michael Clerx, Ross H. Johnstone, Maria P. Hortigon-Vinagre, Victor Zamora, Andrew Allan, Godfrey L. Smith, David J. Gavaghan, Gary R. Mirams, Liudmila Polonchuk

Abstract

Human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) have applications in disease modeling, cell therapy, drug screening and personalized medicine. Computational models can be used to interpret experimental findings in iPSC-CMs, provide mechanistic insights, and translate these findings to adult cardiomyocyte (CM) electrophysiology. However, different cell lines display different expression of ion channels, pumps and receptors, and show differences in electrophysiology. In this exploratory study, we use a mathematical model based on iPSC-CMs from Cellular Dynamic International (CDI, iCell), and compare its predictions to novel experimental recordings made with the Axiogenesis Cor.4U line. We show that tailoring this model to the specific cell line, even using limited data and a relatively simple approach, leads to improved predictions of baseline behavior and response to drugs. This demonstrates the need and the feasibility to tailor models to individual cell lines, although a more refined approach will be needed to characterize individual currents, address differences in ion current kinetics, and further improve these results.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 26%
Student > Ph. D. Student 9 21%
Student > Bachelor 5 12%
Student > Doctoral Student 4 10%
Lecturer 3 7%
Other 3 7%
Unknown 7 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 14%
Engineering 6 14%
Agricultural and Biological Sciences 5 12%
Computer Science 4 10%
Mathematics 4 10%
Other 7 17%
Unknown 10 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 23 January 2018.
All research outputs
#4,864,668
of 23,592,647 outputs
Outputs from Frontiers in Physiology
#2,470
of 14,312 outputs
Outputs of similar age
#102,395
of 441,667 outputs
Outputs of similar age from Frontiers in Physiology
#64
of 321 outputs
Altmetric has tracked 23,592,647 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,312 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done well, scoring higher than 82% 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 441,667 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 76% of its contemporaries.
We're also able to compare this research output to 321 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.