Evidence map›Paper›PMID 31150383›Full record

ArticlePLoS computational biology2019

Properties of cardiac conduction in a cell-based computational model.

Karoline Horgmo Jæger, Andrew G Edwards, Andrew McCulloch, Aslak Tveito

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
5.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 60 citations in OpenAlex.

  1. Sometimes extracellular recordings fail for good reasons.NPJ systems biology and applications · 2026
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  10. Myocardial ischemia simulation based on a multi-scale heart electrophysiology model.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024
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  17. Localization of NaThe Journal of physiology · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Karoline Horgmo JægerSimula Research Laboratory, Oslo, Norway.ORCID 0000-0003-4234-9094
Andrew G EdwardsSimula Research Laboratory, Oslo, Norway.
Andrew McCullochDepartment of Bioengineering, University of California, San Diego, California, United States of America.
Aslak TveitoSimula Research Laboratory, Oslo, Norway.
Simula Research Laboratory · NOUniversity of California San Diego · US

Funding

National Biomedical Computation Resource - Competitive Revision SupplementP41GM103426 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI AMARO, ROMMIE E · 2012 to 2019
$14.0M
Predictive multiscale in silico cardio-pharmacologyU01HL126273 · NHLBI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CLANCY, COLLEEN E · 2015 to 2019
$3.8M
Analyzing the Cardiac Power Grid: Adaptive responses to fluctuating local demandU01HL122199 · NHLBI · UNIVERSITY OF WASHINGTON · PI BEARD, DANIEL A, DASH, RANJAN K · 2015 to 2019
$3.3M
Systems Biology of Hypertrophic Heart Disease from Molecular Pathways to Organ SystemR01HL137100 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCCULLOCH, ANDREW D. · 2017 to 2020
$2.0M
NHLBI NIH HHS R01 HL137100NHLBI NIH HHS U01 HL122199NHLBI NIH HHS U01 HL126273NIGMS NIH HHS P41 GM103426
6 · The paper itself

Abstract

The conduction of electrical signals through cardiac tissue is essential for maintaining the function of the heart, and conduction abnormalities are known to potentially lead to life-threatening arrhythmias. The properties of cardiac conduction have therefore been the topic of intense study for decades, but a number of questions related to the mechanisms of conduction still remain unresolved. In this paper, we demonstrate how the so-called EMI model may be used to study some of these open questions. In the EMI model, the extracellular space, the cell membrane, the intracellular space and the cell connections are all represented as separate parts of the computational domain, and the model therefore allows for study of local properties that are hard to represent in the classical homogenized bidomain or monodomain models commonly used to study cardiac conduction. We conclude that a non-uniform sodium channel distribution increases the conduction velocity and decreases the time delays over gap junctions of reduced coupling in the EMI model simulations. We also present a theoretical optimal cell length with respect to conduction velocity and consider the possibility of ephaptic coupling (i.e. cell-to-cell coupling through the extracellular potential) acting as an alternative or supporting mechanism to gap junction coupling. We conclude that for a non-uniform distribution of sodium channels and a sufficiently small intercellular distance, ephaptic coupling can influence the dynamics of the sodium channels and potentially provide cell-to-cell coupling when the gap junction connection is absent.

Indexed as

Models, CardiovascularAnimalsArrhythmias, CardiacCell MembraneComputational BiologyComputer SimulationElectrophysiological PhenomenaExtracellular SpaceGap JunctionsHeart Conduction SystemHumansIntracellular SpaceMyocardial ContractionMyocytes, CardiacSodium ChannelsSodium Channels

Identifiers

PMID31150383
PMCPMC6561587
OpenAlexW2947507329

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.