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Gap-junction channels inhibit transverse propagation in cardiac muscle

Overview of attention for article published in BioMedical Engineering OnLine, January 2005
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Title
Gap-junction channels inhibit transverse propagation in cardiac muscle
Published in
BioMedical Engineering OnLine, January 2005
DOI 10.1186/1475-925x-4-7
Pubmed ID
Authors

Nicholas Sperelakis, Lakshminarayanan Ramasamy

Abstract

The effect of adding many gap-junctions (g-j) channels between contiguous cells in a linear chain on transverse propagation between parallel chains was examined in a 5 x 5 model (5 parallel chains of 5 cells each) for cardiac muscle. The action potential upstrokes were simulated using the PSpice program for circuit analysis. Either a single cell was stimulated (cell A1) or the entire chain was stimulated simultaneously (A-chain). Transverse velocity was calculated from the total propagation time (TPT) from when the first AP crossed a Vm of -20 mV and the last AP crossed -20 mV. The number of g-j channels per junction was varied from zero to 100, 1,000 and 10,000 (Rgj of infinity, 100 MOmega, 10 MOmega, 1.0 MOmega, respectively). The longitudinal resistance of the interstitial fluid (ISF) space between the parallel chains (Rol2) was varied between 200 KOmega (standard value) and 1.0, 5.0, and 10 MOmega. The higher the Rol2 value, the tighter the packing of the chains. It was found that adding many g-j channels inhibited transverse propagation by blocking activation of all 5 chains, unless Rol2 was greatly increased above the standard value of 200 KOmega. This was true for either method of stimulation. This was explained by, when there is strong longitudinal coupling between all 5 cells of a chain awaiting excitation, there must be more transfer energy (i.e., more current) to simultaneously excite all 5 cells of a chain.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 13%
Unknown 7 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 38%
Student > Doctoral Student 2 25%
Student > Bachelor 1 13%
Student > Master 1 13%
Student > Ph. D. Student 1 13%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 38%
Computer Science 2 25%
Medicine and Dentistry 2 25%
Engineering 1 13%
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 30 May 2016.
All research outputs
#7,451,942
of 22,783,848 outputs
Outputs from BioMedical Engineering OnLine
#207
of 824 outputs
Outputs of similar age
#36,552
of 141,336 outputs
Outputs of similar age from BioMedical Engineering OnLine
#1
of 1 outputs
Altmetric has tracked 22,783,848 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 824 research outputs from this source. They receive a mean Attention Score of 4.6. This one has gotten more attention than average, scoring higher than 62% 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 141,336 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them