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Record W4414758767 · doi:10.1113/jp289425

Mechanistic insights into sex differences in atrial electrophysiology and arrhythmia vulnerability through sex‐specific computational models

2025· article· en· W4414758767 on OpenAlexaff
Nathaniel T. Herrera, Haibo Ni, Charlotte Smith, Yixuan Wu, Dobromir Dobrev, Stefano Morotti, Eleonora Grandi

Bibliographic record

VenueThe Journal of Physiology · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Heart, Lung, and Blood InstituteDeutsche ForschungsgemeinschaftNational Institute on AgingNational Institutes of HealthEuropean CommissionAmerican Heart Association
KeywordsAtrial fibrillationCardiac electrophysiologyRepolarizationElectrophysiologyAfterdepolarizationAtrial action potentialEffective refractory periodRyanodine receptorSinus rhythmRefractory period

Abstract

fetched live from OpenAlex

Abstract Atrial fibrillation (AF), the most common cardiac arrhythmia, shows marked sex differences in clinical presentation, treatment response and outcomes. Although prevalence is similar, women often experience more severe symptoms, higher rates of adverse drug effects and reduced treatment efficacy. To investigate the underlying sex‐specific AF mechanisms, we developed and validated male and female human atrial cardiomyocyte models that integrate sex‐based differences in electrophysiology and calcium (Ca2+) handling under normal sinus rhythm (nSR) and chronic AF (cAF) conditions. Although the model parameterizations and assumptions (based on limited human data) may not capture the full spectrum of clinical variability, the models reproduced key reported sex‐dependent differences in human atrial cardiomyocyte action potential (AP) and Ca2+ transient (CaT) dynamics. Simulations revealed that both sexes exhibited shortened effective refractory periods and wavelengths in cAF vs. nSR. Females were more prone to delayed afterdepolarizations (DADs), whereas males were more susceptible to AP duration (APD) and CaT amplitude (CaTAmp) alternans. Population‐based modelling identified distinct parameter associations with arrhythmia mechanisms: DAD vulnerability was associated with enhanced ryanodine receptor Ca2+ sensitivity in females, and alternans in males correlated with reduced L‐type Ca2+ current maximal conductance. Pharmacological simulations revealed sex‐specific responses to antiarrhythmic therapies. In males, multiple drug combinations restored APD at 90% repolarization (APD90), CaTAmp and reduced alternans susceptibility, whereas females responded to only one combination improving APD90 and CaTAmp but with minimal impact on DAD risk. These findings underscore the need for sex‐specific therapeutic strategies and support use of computational modelling in guiding precision medicine against AF. image Key points Atrial fibrillation (AF) is a common heart rhythm disorder that presents differently in males and females, but how the underlying mechanisms differ in males and females is not fully understood. We developed and validated computer models of male and female human atrial cardiomyocytes that incorporate known sex differences in ion channels and calcium handling under normal sinus rhythm and AF conditions. Under normal rhythm, males and females showed distinct electrical activity, which became less pronounced in AF. In AF, both sexes showed reduced effective refractory period and wavelength and depressed calcium transients. Males were more susceptible to electrical alternans, whereas females showed a greater tendency for calcium‐driven delayed afterdepolarizations. Simulated drug treatments showed greater benefit in male models, particularly with combinations targeting multiple potassium channels, whereas female models showed limited response. These results highlight the need for sex‐specific approaches to treating AF and may help guide future drug development.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.275
Teacher spread0.258 · 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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