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An integrated mathematical epithelial cell model for airway surface liquid regulation by mechanical forces

Overview of attention for article published in Journal of Theoretical Biology, November 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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39 Mendeley
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Article details
Title
An integrated mathematical epithelial cell model for airway surface liquid regulation by mechanical forces
Published in
Journal of Theoretical Biology, November 2017
DOI 10.1016/j.jtbi.2017.11.010
Pubmed ID
Authors
Abstract

A robust method based on reverse engineering was utilized to construct the ion-channel conductance functions for airway epithelial sodium channels (ENaC), the cystic fibrosis transmembrane conductance regulator (CFTR), and calcium-activated chloride channels (CaCC). The ion-channel conductance models for both normal (NL) and cystic fibrosis (CF) airway epithelia were developed and then coupled to an adenosine triphosphate (ATP) metabolism model and a fluid transport model (collectively called the integrated cell model) to investigate airway surface liquid (ASL) volume regulation and hence mucus concentration, by mechanical forces in NL and CF human airways. The epithelial cell models for NL and CF required differences in Cl(-) secretion (decreased in CF) and Na(+) absorption (raised in CF) to reproduce behaviors similar to in vitro epithelial cells exposed to mechanical forces (cyclic shear stress, cyclic compressive pressure and cilial strain) and selected modulators of ion channels and ATP release. The epithelial cell models were then used to investigate the effects of mechanical forces and evaporative flux on ASL and mucus homeostasis in both NL and CF airway epithelia. Because of reduced CF ASL volumes, CF mucus concentrations increased and produced a greater dependence of ASL volume regulation on cilia-mucus-ATP release interactions in CF than NL epithelial nodules. Similarly, the CF model was less tolerant to evaporation induced ASL volume reduction at all ATP release rates than the NL model. Consequently, this reverse engineered model appears to provide a robust tool for investigating CF pathophysiology and novel therapies.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 39 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 %
Unknown 39 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 8 21%
Researcher 6 15%
Student > Bachelor 5 13%
Professor > Associate Professor 4 10%
Student > Doctoral Student 3 8%
Other 4 10%
Unknown 9 23%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 23%
Medicine and Dentistry 5 13%
Engineering 5 13%
Agricultural and Biological Sciences 2 5%
Chemical Engineering 1 3%
Other 6 15%
Unknown 11 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 01 January 2023.
All research outputs
#11,075,031
of 33,738,238 outputs
Outputs from Journal of Theoretical Biology
#1,332
of 4,477 outputs
Outputs of similar age
#132,204
of 367,213 outputs
Outputs of similar age from Journal of Theoretical Biology
#11
of 52 outputs
Altmetric has tracked 33,738,238 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 4,477 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has gotten more attention than average, scoring higher than 68% 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 367,213 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 62% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.