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Trayanova NA, Lyon A, Shade J, Heijman J. Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation. Physiol Rev 2024; 104:1265-1333. [PMID: 38153307 DOI: 10.1152/physrev.00017.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 12/29/2023] Open
Abstract
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 data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward 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 toward 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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Affiliation(s)
- Natalia A Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Aurore Lyon
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of Heart and Lungs, Department of Medical Physiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Julie Shade
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Jordi Heijman
- Department of Cardiology, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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Epigenetics and Gut Microbiota Crosstalk: A potential Factor in Pathogenesis of Cardiovascular Disorders. BIOENGINEERING (BASEL, SWITZERLAND) 2022; 9:bioengineering9120798. [PMID: 36551003 PMCID: PMC9774431 DOI: 10.3390/bioengineering9120798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
Cardiovascular diseases (CVD) are the leading cause of mortality, morbidity, and "sudden death" globally. Environmental and lifestyle factors play important roles in CVD susceptibility, but the link between environmental factors and genetics is not fully established. Epigenetic influence during CVDs is becoming more evident as its direct involvement has been reported. The discovery of epigenetic mechanisms, such as DNA methylation and histone modification, suggested that external factors could alter gene expression to modulate human health. These external factors also influence our gut microbiota (GM), which participates in multiple metabolic processes in our body. Evidence suggests a high association of GM with CVDs. Although the exact mechanism remains unclear, the influence of GM over the epigenetic mechanisms could be one potential pathway in CVD etiology. Both epigenetics and GM are dynamic processes and vary with age and environment. Changes in the composition of GM have been found to underlie the pathogenesis of metabolic diseases via modulating epigenetic changes in the form of DNA methylation, histone modifications, and regulation of non-coding RNAs. Several metabolites produced by the GM, including short-chain fatty acids, folates, biotin, and trimethylamine-N-oxide, have the potential to regulate epigenetics, apart from playing a vital role in normal physiological processes. The role of GM and epigenetics in CVDs are promising areas of research, and important insights in the field of early diagnosis and therapeutic approaches might appear soon.
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Belletti R, Romero L, Martinez-Mateu L, Cherry EM, Fenton FH, Saiz J. Arrhythmogenic Effects of Genetic Mutations Affecting Potassium Channels in Human Atrial Fibrillation: A Simulation Study. Front Physiol 2021; 12:681943. [PMID: 34135774 PMCID: PMC8201780 DOI: 10.3389/fphys.2021.681943] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 05/05/2021] [Indexed: 11/16/2022] Open
Abstract
Genetic mutations in genes encoding for potassium channel protein structures have been recently associated with episodes of atrial fibrillation in asymptomatic patients. The aim of this study is to investigate the potential arrhythmogenicity of three gain-of-function mutations related to atrial fibrillation—namely, KCNH2 T895M, KCNH2 T436M, and KCNE3-V17M—using modeling and simulation of the electrophysiological activity of the heart. A genetic algorithm was used to tune the parameters’ value of the original ionic currents to reproduce the alterations experimentally observed caused by the mutations. The effects on action potentials, ionic currents, and restitution properties were analyzed using versions of the Courtemanche human atrial myocyte model in different tissues: pulmonary vein, right, and left atrium. Atrial susceptibility of the tissues to spiral wave generation was also investigated studying the temporal vulnerability. The presence of the three mutations resulted in an overall more arrhythmogenic substrate. Higher current density, action potential duration shortening, and flattening of the restitution curves were the major effects of the three mutations at the single-cell level. The genetic mutations at the tissue level induced a higher temporal vulnerability to the rotor’s initiation and progression, by sustaining spiral waves that perpetuate until the end of the simulation. The mutation with the highest pro-arrhythmic effects, exhibiting the widest sustained VW and the smallest meandering rotor’s tip areas, was KCNE3-V17M. Moreover, the increased susceptibility to arrhythmias and rotor’s stability was tissue-dependent. Pulmonary vein tissues were more prone to rotor’s initiation, while in left atrium tissues rotors were more easily sustained. Re-entries were also progressively more stable in pulmonary vein tissue, followed by the left atrium, and finally the right atrium. The presence of the genetic mutations increased the susceptibility to arrhythmias by promoting the rotor’s initiation and maintenance. The study provides useful insights into the mechanisms underlying fibrillatory events caused by KCNH2 T895M, KCNH2 T436M, and KCNE3-V17M and might aid the planning of patient-specific targeted therapies.
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Affiliation(s)
- Rebecca Belletti
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Lucia Romero
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Laura Martinez-Mateu
- Departamento de Teoría de la Señal y Comunicaciones y Sistemas Telemáticos y Computación, Universidad Rey Juan Carlos, Madrid, Spain
| | - Elizabeth M Cherry
- School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Flavio H Fenton
- School of Physics, Georgia Institute of Technology, Atlanta, GA, United States
| | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
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Heikhmakhtiar AK, Abrha AT, Jeong DU, Lim KM. Proarrhythmogenic Effect of the L532P and N588K KCNH2 Mutations in the Human Heart Using a 3D Electrophysiological Model. J Korean Med Sci 2020; 35:e238. [PMID: 32715669 PMCID: PMC7384902 DOI: 10.3346/jkms.2020.35.e238] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 06/01/2020] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Atrial arrhythmia is a cardiac disorder caused by abnormal electrical signaling and transmission, which can result in atrial fibrillation and eventual death. Genetic defects in ion channels can cause myocardial repolarization disorders. Arrhythmia-associated gene mutations, including KCNH2 gene mutations, which are one of the most common genetic disorders, have been reported. This mutation causes abnormal QT intervals by a gain of function in the rapid delayed rectifier potassium channel (IKr). In this study, we demonstrated that mutations in the KCNH2 gene cause atrial arrhythmia. METHODS The N588K and L532P mutations were induced in the Courtemanche-Ramirez-Nattel (CRN) cell model, which was subjected to two-dimensional and three-dimensional simulations to compare the electrical conduction patterns of the wild-type and mutant-type genes. RESULTS In contrast to the early self-termination of the wild-type conduction waveforms, the conduction waveform of the mutant-type retained the reentrant wave (N588K) and caused a spiral break-up, resulting in irregular wave generation (L532P). CONCLUSION The present study confirmed that the KCNH2 gene mutation increases the vulnerability of the atrial tissue for arrhythmia.
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Affiliation(s)
- Aulia Khamas Heikhmakhtiar
- School of Computing, Telkom University, Bandung, Jawa Barat, Indonesia
- Research Center of Human Centric Engineering (HUMIC), Telkom University, Bandung, Jawa Barat, Indonesia
| | - Abebe Tekle Abrha
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea
| | - Da Un Jeong
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea
| | - Ki Moo Lim
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea.
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Aronis KN, Ali RL, Liang JA, Zhou S, Trayanova NA. Understanding AF Mechanisms Through Computational Modelling and Simulations. Arrhythm Electrophysiol Rev 2019; 8:210-219. [PMID: 31463059 PMCID: PMC6702471 DOI: 10.15420/aer.2019.28.2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Accepted: 06/17/2019] [Indexed: 12/21/2022] Open
Abstract
AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The authors summarise recent advancements in development of multi-scale AF models and focus on the mechanistic links between alternations in atrial structure and electrophysiology with AF. Key AF mechanisms that have been explored using atrial modelling are pulmonary vein ectopy; atrial fibrosis and fibrosis distribution; atrial wall thickness heterogeneity; atrial adipose tissue infiltration; development of repolarisation alternans; cardiac ion channel mutations; and atrial stretch with mechano-electrical feedback. They review modelling approaches that capture variability at the cohort level and provide cohort-specific mechanistic insights. The authors conclude with a summary of future perspectives, as envisioned for the contributions of atrial modelling in the mechanistic understanding of AF.
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Affiliation(s)
- Konstantinos N Aronis
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
- Division of Cardiology, Johns Hopkins HospitalBaltimore, MD, US
| | - Rheeda L Ali
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
| | - Jialiu A Liang
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
| | - Shijie Zhou
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
| | - Natalia A Trayanova
- Department of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins UniversityBaltimore, MD, US
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Zhou X, Bueno-Orovio A, Schilling RJ, Kirkby C, Denning C, Rajamohan D, Burrage K, Tinker A, Rodriguez B, Harmer SC. Investigating the Complex Arrhythmic Phenotype Caused by the Gain-of-Function Mutation KCNQ1-G229D. Front Physiol 2019; 10:259. [PMID: 30967788 PMCID: PMC6430739 DOI: 10.3389/fphys.2019.00259] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 02/28/2019] [Indexed: 12/18/2022] Open
Abstract
The congenital long QT syndrome (LQTS) is a cardiac electrophysiological disorder that can cause sudden cardiac death. LQT1 is a subtype of LQTS caused by mutations in KCNQ1, affecting the slow delayed-rectifier potassium current (I Ks), which is essential for cardiac repolarization. Paradoxically, gain-of-function mutations in KCNQ1 have been reported to cause borderline QT prolongation, atrial fibrillation (AF), sinus bradycardia, and sudden death, however, the mechanisms are not well understood. The goal of the study is to investigate the ionic, cellular and tissue mechanisms underlying the complex phenotype of a gain-of-function mutation in KCNQ1, c.686G > A (p.G229D) using computer modeling and simulations informed by in vitro measurements. Previous studies have shown this mutation to cause AF and borderline QT prolongation. We report a clinical description of a family that carry this mutation and that a member of the family died suddenly during sleep at 21 years old. Using patch-clamp experiments, we confirm that KCNQ1-G229D causes a significant gain in channel function. We introduce the effect of the mutation in populations of atrial, ventricular and sinus node (SN) cell models to investigate mechanisms underlying phenotypic variability. In a population of human atrial and ventricular cell models and tissue, the presence of KCNQ1-G229D predominantly shortens atrial action potential duration (APD). However, in a subset of models, KCNQ1-G229D can act to prolong ventricular APD by up to 7% (19 ms) and underlie depolarization abnormalities, which could promote QT prolongation and conduction delays. Interestingly, APD prolongations were predominantly seen at slow pacing cycle lengths (CL > 1,000 ms), which suggests a greater arrhythmic risk during bradycardia, and is consistent with the observed sudden death during sleep. In a population of human SN cell models, the KCNQ1-G229D mutation results in slow/abnormal sinus rhythm, and we identify that a stronger L-type calcium current enables the SN to be more robust to the mutation. In conclusion, our computational modeling experiments provide novel mechanistic explanations for the observed borderline QT prolongation, and predict that KCNQ1-G229D could underlie SN dysfunction and conduction delays. The mechanisms revealed in the study can potentially inform management and treatment of KCNQ1 gain-of-function mutation carriers.
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Affiliation(s)
- Xin Zhou
- Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Alfonso Bueno-Orovio
- Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
| | | | | | - Chris Denning
- Department of Stem Cell Biology, Centre for Biomolecular Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Divya Rajamohan
- Department of Stem Cell Biology, Centre for Biomolecular Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Kevin Burrage
- Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
- Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Andrew Tinker
- The William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Blanca Rodriguez
- Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Stephen C. Harmer
- The William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
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Jeong DU, Lim KM. Influence of the KCNQ1 S140G Mutation on Human Ventricular Arrhythmogenesis and Pumping Performance: Simulation Study. Front Physiol 2018; 9:926. [PMID: 30108508 PMCID: PMC6080549 DOI: 10.3389/fphys.2018.00926] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Accepted: 06/25/2018] [Indexed: 11/14/2022] Open
Abstract
The KCNQ1 S140G mutation, which is involved in IKs current, affects atrial fibrillation. However, little is known about its effect on the mechanical behavior of the heart. Therefore, we assessed the influence of the KCNQ1 S140G mutation on ventricular electrophysiological stability and mechanical pumping performance using a multi-scale model of cardiac electromechanics. An image-based electromechanical model was used to assess the effect on electrical propagation and arrhythmogenesis of the KCNQ1 S140G mutation. In addition, it was used to compare the mechanical response under the wild-type (WT) and S140G mutation conditions. The intracellular calcium transient obtained from the electrophysiological model was applied as an input parameter to a mechanical model to implement excitation–contraction coupling. The IKs current equation was modified to account for expression of the KCNQ1 S140G mutation, and it included a scaling factor (ϕ) for mutant expressivity. The WT and S140G mutation conditions were compared at the single-cell and three-dimensional (3D) tissue levels. The action potential duration (APD) was reduced by 60% by the augmented IKs current under the S140G mutation condition, which resulted in shorter QT interval. This reduced the 3D sinus rhythm wavelength by 60% and the sustained re-entry by 56%. However, pumping efficiency of mutant ventricles was superior in sinus rhythm condition. In addition, the shortened wavelength in cardiac tissue allowed a re-entrant circuit to form and increased the probability of sustaining ventricular tachycardia and ventricular fibrillation. In contrast, under the WT condition, a normal wavelength (20.8 cm) was unlikely to initiate and sustain re-entry in the cardiac tissue. Subsequently, the S140G mutant ventricles developed a higher dominant frequency distribution range (2.0–5.3 Hz) than the WT condition (2.8–3.7 Hz). In addition, stroke volume of mutant ventricles was reduced by 65% in sustained re-entry compared to the WT condition. In conclusion, signs of the S140G mutation might be difficult to identify in sinus rhythm even though the mutant ventricles show shortened QT interval. This suggests that the KCNQ1 S140G mutation increases the risk of death by sudden cardiac arrest. In addition, the KCNQ1 S140G mutation can induce ventricular arrhythmia and lessen ventricular contractility under re-entrant conditions.
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Affiliation(s)
- Da Un Jeong
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Ki Moo Lim
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
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Yuniarti AR, Setianto F, Marcellinus A, Hwang HJ, Choi SW, Trayanova N, Lim KM. Effect of KCNQ1 G229D mutation on cardiac pumping efficacy and reentrant dynamics in ventricles: Computational study. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2018; 34:e2970. [PMID: 29488358 PMCID: PMC6556218 DOI: 10.1002/cnm.2970] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 02/09/2018] [Accepted: 02/12/2018] [Indexed: 05/12/2023]
Abstract
There is growing interest in genetic arrhythmia since mutations in gene which encodes the ion channel underlie numerous arrhythmias. Hasegawa et al reported that G229D mutation in KCNQ1 underlies atrial fibrillation due to significant shortening of action potential duration (APD) in atrial cells. Here, we predicted whether KCNQ1 G229D mutation affects ventricular fibrillation generation, although it shortens APD slightly compared with the atrial cell. We analyzed the effects of G229D mutation on electrical and mechanical ventricle behaviors (not considered in previous studies). We compared action potential shapes under wild-type and mutant conditions. Electrical wave propagations through ventricles were analyzed during sinus rhythm and reentrant conditions. IKs enhancement due to G229D mutation shortened the APD in the ventricular cells (6%, 0.3%, and 8% for endo, M, and epi-cells, respectively). The shortened APD contributed to 7% shortening of QT intervals, 29% shortening of wavelengths, 20% decrease in intraventricular pressure, and increase in end-systolic volume 17%, end-diastolic volume 7%, and end-diastolic pressure 11%, which further resulted in reduction in stroke volume as well as cardiac output (28%), ejection fraction 33% stroke work 44%, and ATP consumption 28%. In short, using computational model of the ventricle, we predicted that G229D mutation decreased cardiac pumping efficacy and increased the vulnerability of ventricular fibrillation.
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Affiliation(s)
- Ana Rahma Yuniarti
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Febrian Setianto
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Aroli Marcellinus
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Han Jeong Hwang
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Seong Wook Choi
- Department of Mechanical & Biomedical Engineering, Kangwon National University, Chuncheon, South Korea
| | - Natalia Trayanova
- Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Ki Moo Lim
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
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