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Model Identifier
BIOMD0000001101
Short description
Format
MATLAB (Octave)
Related Publication
  • Clinical phenotypes in acute and chronic infarction explained through human ventricular electromechanical modelling and simulations Click here to expand
  • Xin Zhou, Zhinuo Jenny Wang, Julia Camps, Jakub Tomek, Alfonso Santiago, Adria Quintanas, Mariano Vazquez, Marmar Vaseghi, Blanca Rodriguez
  • eLife , 10/ 2024 , DOI: 10.7554/eLife.93002.2
  • University of Oxford
  • Aims Sudden death after myocardial infarction (MI) is associated with electrophysiological heterogeneities and ionic remodelling, which are reflected as variable phenotypes. Low ejection fraction (EF) is used in risk stratification, but its mechanistic links with the post-MI pro-arrhythmic heterogeneities are unknown. We aim to provide a mechanistic explanation of clinical phenotypes in acute and chronic MI, from ionic remodeling to ECG and EF, using human electromechanical modelling and simulation to augment experimental and clinical investigations. Methods and Results A human ventricular electromechanical modelling and simulation framework is constructed and validated with rich experimental and clinical datasets. Abnormalities caused by scar and border zone ionic remodeling are introduced in varying degrees as reported in experimental data obtained in acute and chronic infarction. Simulations enabled reproducing and explaining clinical phenotypes post-MI, from ionic remodelling to ECGs and pressure-volume loops. In acute MI, T-wave inversion and Brugada phenocopy were explained by up to 57 ms of local APD prolongation and activation failure due to the inhibition of potassium, sodium and calcium channels in the border zone. In chronic MI, upright tall T-waves highlight large repolarisation dispersion caused by uneven potassium channel expression in border and remote zones, which promoted ectopic propagation at fast pacing. Post-MI ionic remodelling reduced EF by up to 10% through inhibition of calcium transient amplitude due to weaker calcium currents or SERCA activity, but the EF at resting heart rate was not sensitive to the extent of repolarisation heterogeneity and the risk of repolarisation abnormalities at fast pacing. Conclusions Multi-scale modelling and simulation coherently integrates experimental and clinical data at subcellular, tissue, and organ scales to unravel electromechanical disease mechanisms in MI. In acute post-MI, ionic remodelling and its effect on refractoriness and propagation failure in the BZ have a strong impact on phenotypic ECG variability, whereas in chronic post-MI, the repolarisation dispersion across the BZ is crucial. T-wave and QT abnormalities are better indicators of repolarisation heterogeneities than EF in post-MI.
Contributors
Submitter of the first revision: XIN ZHOU
Submitter of this revision: XIN ZHOU
Annotation Curator: XIN ZHOU
Modeller: XIN ZHOU

Metadata information

is (1 statement)
BioModels Database MODEL2402290004

isDescribedBy (1 statement)

Curation status
Non-curated


Connected external resources

Name Description Size Actions

Model files (1)

model_ToRORd_LandCaMKSKJrelpKinetics.m Main model file for electromechanics 26.43 KB Preview | Download

Additional files (12)

EndoAcuteBZ1.m script for generating acute infarction border zone 1 traces 1.71 KB Preview | Download
EndoAcuteBZ2.m script for generating acute infarction border zone 2 traces 1.70 KB Preview | Download
EndoAcuteBZ3.m script for generating acute infarction border zone 3 traces 1.82 KB Preview | Download
EndoChronicBZ.m script for generating chronic infarction border zone traces 1.85 KB Preview | Download
EndoChronicRZ1.m script for generating chronic infarction remote zone 1 traces 1.86 KB Preview | Download
EndoChronicRZ2.m script for generating chronic infarction remote zone 2 traces 1.87 KB Preview | Download
EndoNZ.m script for generating normal traces 1.53 KB Preview | Download
POM253.mat Parameter file for population of models 21.21 KB Preview | Download
PlotAPCaTTaAcuteAndChronic.m Script for the plot of results 3.08 KB Preview | Download
getCurrentsStructureCaMKSKJrelpKinetics.m calculation of currents 9.43 KB Preview | Download
getStartingState.m starting state 2.94 KB Preview | Download
modelRunnerCaMKSKJrelpKinetics1ms.m model simulation defitions 5.48 KB Preview | Download

  • Model originally submitted by : XIN ZHOU
  • Submitted: Feb 29, 2024 1:19:04 PM
  • Last Modified: Mar 4, 2025 12:13:17 PM
Revisions
  • Version: 4
    • Submitted on: Mar 4, 2025 12:13:17 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Updated model file reproducing results and also added annotation file
  • Version: 1
    • Submitted on: Feb 29, 2024 1:19:04 PM
    • Submitted by: XIN ZHOU
    • With comment: Import of Zhou2024PostInfarctionMyocyteElectromechanics

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Curator's comment:
(added: 04 Mar 2025, 12:15:01, updated: 04 Mar 2025, 12:15:01)
Model reproducing results of figure 2B and figure 3B of the cited paper.