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Cardiac Modeling of Steady-State Transients in the Ventricular Myocyte

This project focuses on studying the behavior of steady-state transients in the ventricular myocyte using the Nimrod toolkit to analyze data from the expanded Shannon et al. computational cardiac model. The aim is to search for steady-state transients in action potential, intracellular calcium, sodium concentration, and potassium concentration. Achievements include completing optimization experiments and identifying parameters influencing intracellular potassium behavior. Future work involves optimizing experiments for additional potassium channels to achieve steady-state behavior. Acknowledgements to the University of California, San Diego and the University of Queensland for their support in this research project.

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Cardiac Modeling of Steady-State Transients in the Ventricular Myocyte

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  1. Cardiac Modeling of Steady-State Transients in the Ventricular Myocyte Raymond Tran University of Queensland August 24 2013 UCSD PRIME

  2. Project Overview: Steady-State • Steady-state describes the behavior of a specific transient when it continues to operate in the same repetitive stimulation over time; this state does not change unless the cellular environment is altered. • This project focuses on using the Nimrod toolkit to perform multiple parameter sweeps on the expanded Shannon et al computational cardiac model. The data will then be analyzed to search for steady-state transients in AP, [Ca]i, [Na]i, [K]i.

  3. Accomplishments • Completed all optimization experiments of the applied current and Na/K pump on Nimrod/O. • Concluded that these sets of parameters could not influence a steady-state intracellular potassium behavior.

  4. Future Work • The problem that persisted throughout the project was achieving a steady-state behavior for Ki in the expanded Shannon et al model. However, there are six additional potassium channels that may influence potassium stability. • Discuss and share project results with Dr. Michailova, then devise optimization experiments to test the remaining channels.

  5. Culture

  6. Acknowledgements University of California, San Diego • Dr. Anushka Michailova, Department of Bioengineering. • UCSD PRIME – Dr. Gabriele Wienhausen, Dr. Peter Arzberger, Ms. Teri Simas. University of Queensland • Dr. David Abramson, Centre for Research Computing. • Dr. Timos Kipouros, Cambridge Engineering Design Center. • Blair Bethwaite, Monash eScience and Grid Engineering Lab. • Hoang Nguyen, Monash eScience and Grid Engineering Lab.

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