Evidence map›Paper›PMID 30883540›Full record

ArticlePLoS computational biology2019

Self-organization of conducting pathways explains electrical wave propagation in cardiac tissues with high fraction of non-conducting cells.

Nina Kudryashova, Aygul Nizamieva, Valeriya Tsvelaya, Alexander V Panfilov, Konstantin I Agladze

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 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

12 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Smart Optogenetics for Real-Time Automated Control of Cardiac Electrical Activity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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  12. Optimizing the Use of iPSC-CMs for Cardiac Regeneration in Animal Models.Animals : an open access journal from MDPI · 2020
    Review
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

5 authors at 2 institutions in 2 countries.

Nina KudryashovaLaboratory of Biophysics of Excitable Systems, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.ORCID 0000-0001-8529-7250
Aygul NizamievaLaboratory of Biophysics of Excitable Systems, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Valeriya TsvelayaLaboratory of Biophysics of Excitable Systems, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Alexander V PanfilovDepartment of Physics and Astronomy, Ghent University, Ghent, Belgium.
Konstantin I AgladzeLaboratory of Biophysics of Excitable Systems, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.ORCID 0000-0002-9258-436X
Moscow Institute of Physics and Technology · RUUral Federal University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiac fibrosis occurs in many forms of heart disease and is considered to be one of the main arrhythmogenic factors. Regions with a high density of fibroblasts are likely to cause blocks of wave propagation that give rise to dangerous cardiac arrhythmias. Therefore, studies of the wave propagation through these regions are very important, yet the precise mechanisms leading to arrhythmia formation in fibrotic cardiac tissue remain poorly understood. Particularly, it is not clear how wave propagation is organized at the cellular level, as experiments show that the regions with a high percentage of fibroblasts (65-75%) are still conducting electrical signals, whereas geometric analysis of randomly distributed conducting and non-conducting cells predicts connectivity loss at 40% at the most (percolation threshold). To address this question, we used a joint in vitro-in silico approach, which combined experiments in neonatal rat cardiac monolayers with morphological and electrophysiological computer simulations. We have shown that the main reason for sustainable wave propagation in highly fibrotic samples is the formation of a branching network of cardiomyocytes. We have successfully reproduced the morphology of conductive pathways in computer modelling, assuming that cardiomyocytes align their cytoskeletons to fuse into cardiac syncytium. The electrophysiological properties of the monolayers, such as conduction velocity, conduction blocks and wave fractionation, were reproduced as well. In a virtual cardiac tissue, we have also examined the wave propagation at the subcellular level, detected wavebreaks formation and its relation to the structure of fibrosis and, thus, analysed the processes leading to the onset of arrhythmias.

Indexed as

AnimalsAnimals, NewbornArrhythmias, CardiacComputer SimulationHeartHeart Conduction SystemModels, CardiovascularRats

Identifiers

PMID30883540
PMCPMC6438583
OpenAlexW2922164723

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.