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Record W4412505805 · doi:10.1113/jp288659

Computational modelling of the pro‐ and antiarrhythmic effects of atrial high rate‐dependent trafficking of small‐conductance calcium‐activated potassium channels

2025· article· en· W4412505805 on OpenAlexaff
Stefan Meier, Dobromir Dobrev, Paul G.A. Volders, Jordi Heijman

Bibliographic record

VenueThe Journal of Physiology · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Institutes of HealthNederlandse Organisatie voor Wetenschappelijk OnderzoekZonMwDeutsche ForschungsgemeinschaftNational Heart, Lung, and Blood InstituteHartstichtingEuropean Commission
KeywordsPotassiumCalcium-activated potassium channelPotassium channelCalciumConductanceChemistryBiophysicsPharmacologyCardiologyInternal medicineMedicineBiologyMathematics

Abstract

fetched live from OpenAlex

Abstract Small‐conductance calcium‐activated potassium (SK) channels are promising targets for atrial‐specific antiarrhythmic therapies, with evidence suggesting tachycardia‐dependent SK‐channel upregulation. However, the dynamics of SK‐channel gating and trafficking in human atrial electrophysiology remain unclear because of experimental limitations, including the availability of human cardiomyocytes and long patch clamp experiments. Although computational models help explore these mechanisms, none integrate SK‐channel trafficking. In the present study, we expanded our K v 11.1 trafficking model to simulate rate‐dependent SK‐channel trafficking in a human atrial cardiomyocyte model. Calibrated against experimental data, our model replicates time‐ and rate‐dependent SK‐channel function, allowing simulations of SK‐channel trafficking and its effects on action potentials. Tachypacing at 5 Hz increased SK‐channel density, enhancing SK current and shortening action potential duration, with or without calcium buffering. Two‐dimensional tissue simulations with physiological calcium handling showed that tachycardia increased re‐entry duration and ectopic activity. SK‐channel inhibition reduced re‐entry duration but promoted ectopic activity, suggesting a reduction in atrial fibrillation burden rather than complete elimination. Our novel computational model highlights SK channels’ role in re‐entry‐promoting effects of short atrial tachycardia episodes, offering insights into early atrial fibrillation progression and potential antiarrhythmic strategies. image Key points Small‐conductance calcium‐activated potassium (SK) channels have emerged as potential targets for atrial‐specific antiarrhythmic therapies, especially in atrial fibrillation (AF). Emerging evidence suggests that tachycardia‐induced SK‐channel trafficking can regulate cardiac cellular electrophysiology over minutes, but investigating its impact on arrhythmogenesis in humans is experimentally challenging. We adapted our recent in silico K v 11.1 trafficking model to simulate SK‐channel trafficking and incorporated it into a human atrial cardiomyocyte model, which was calibrated based on experimental results. Tachypacing at 5 Hz led to a substantial increase in SK channel‐density at the membrane, resulting in enhanced SK current and a reduction in action potential duration. 2‐D tissue simulations demonstrated that rapid pacing promoted both re‐entry and ectopic (triggered) activity. Blocking SK channels reduced re‐entry duration but increased ectopic activity, suggesting that SK channel inhibition could decrease AF burden, but may not eliminate AF per se .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.256
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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