Spatial Changes in the Atrial Fibrillation Wave-Dynamics After Using Antiarrhythmic Drugs: A Computational Modeling Study

Hwang, Ilseon; Park, Je Wook; Kwon, Oh Seok; Lim, Byounghyun; Lee, Jisu; Jin, Ze; Yu, Hee Tae; Kim, Tae Hoon; Joung, Boyoung; Pak, Hui Nam

doi:10.3389/fphys.2021.733543

Cited by 3 publications

(1 citation statement)

References 46 publications

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“…The main population of AF in China is the elderly, and AF can cause cardiac insufficiency and vascular embolism, with high fatality and disability rates, and serious harm to human health [ 2 ]. With the arrival of an aging society in China, it is expected that the number of patients and the total prevalence will increase significantly in the future [ 3 – 5 ]. In addition, AF can also cause palpitations, fatigue, chest tightness, cognitive dysfunction, impaired exercise tolerance, and other common clinical symptoms, which affect the quality of life of patients [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Network Pharmacology and Pharmacological Mechanism of CV-3 in Atrial Fibrillation

Wang

Zeng

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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The high fatality and disability rate of atrial fibrillation (AF) strongly promote the development of pathogenesis and treatment of AF that is of great value. The present research attempted to clarify potential mechanisms of Mujiangzi oil (CV-3) in treating AF by constructing an AF cardiomyocytes model and using a network pharmacology approach. The experiment was divided into 4 groups: control, an AF model, AF + CV-3-treated, and the AF + verapamil group. Flow cytometry and the MTT assay were employed to detect cell apoptosis and cell viability, respectively. The main active components of CV-3 and predicted targets were obtained firstly, and molecular docking was performed. In the AF model, the cell apoptosis was aggravated, but inhibited in the CV-3-treated group. In addition, the cell viability was recovered after CV-3 treatment compared with the model group. Five potential active compounds of CV-3 were collected, including effective ingredients N-decanoic acid, spathulenol, copaene, β-panasinsene, and eucalyptol. Among them, N-decanoic acid and spathulenol was demonstrated to bind to PTGS2 with binding energy of −4.08 and −7.09 kcal/mol, respectively, and hydrogen bonds interaction were found. The present study indicated that CV-3 could alleviate AF cardiomyocytes apoptosis and improve cardiomyocytes viability, and N-decanoic acid and spathulenol may be the key components of CV-3 in treatment of AF by regulating PTGS2. This study provided the possible target PTGS2 and the understanding of molecular mechanisms of CV-3 in treating AF.

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Section: Introductionmentioning

confidence: 99%

Network Pharmacology and Pharmacological Mechanism of CV-3 in Atrial Fibrillation

Wang

Zeng

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

Trayanova,

Lyon,

Shade

et al. 2024

Physiological Reviews

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The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias. from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient clinical data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook towards potential future advances, including the combination of mechanistic modeling and machine learning / artificial intelligence, is provided. As the field of cardiology is embarking on a journey towards precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

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Clinical Usefulness of Virtual Ablation Guided Catheter Ablation of Atrial Fibrillation Targeting Restitution Parameter-Guided Catheter Ablation: CUVIA-REGAB Prospective Randomized Study

et al. 2022

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Effective ablation approach for persistent atrial fibrillation (PeAF) beyond pulmonary vein (PV) isolation is still controversial. We developed a real-time computational AF modeling technique to perform rapid rotor mapping reflecting the individual electrophysiology and AF mechanisms. In this study, we investigated whether extra-PV ablation targeting a high maximal slope of the action potential duration restitution curve (Smax) improves the outcome of PeAF ablation. However, virtual ablation-guided Smax modulation approach for PeAF did not result in an improved procedural outcome compared to the empirical ablation strategy. Further investigation is needed regarding a more effective patient-customized mechanism-based AF catheter ablation using the functional electrophysiology.

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Spatial Changes in the Atrial Fibrillation Wave-Dynamics After Using Antiarrhythmic Drugs: A Computational Modeling Study

Cited by 3 publications

References 46 publications

Network Pharmacology and Pharmacological Mechanism of CV-3 in Atrial Fibrillation

Network Pharmacology and Pharmacological Mechanism of CV-3 in Atrial Fibrillation

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

Clinical Usefulness of Virtual Ablation Guided Catheter Ablation of Atrial Fibrillation Targeting Restitution Parameter-Guided Catheter Ablation: CUVIA-REGAB Prospective Randomized Study

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