http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Modelling the Short QT Syndrome Gene Mutations
And Their Role in Cardiac Arrhythmogenesis
XVII, 217 p. 102 illus., 38 illus. in color. online resource.
The Short QT Syndrome (SQTS) is characterized by abbreviated QT intervals on the electrocardiogram, increased risk of cardiac arrhythmias and sudden death. Although several gene mutations have been identified in SQT patients, the role of these mutations in promoting arrhythmogenesis is still not completely understood. Consequently, this thesis employs multidisciplinary approaches to develop a 3D virtual heart, which is then used to elucidate how the short QT syndrome facilitates and maintains ventricular arrhythmias and to determine its effects on ventricular mechanical contraction. The findings in this thesis provide a comprehensive and mechanistic explanation for a number of gene mutations associated with potassium channels in terms of susceptibility to arrhythmia. The multiphysics models developed provide a powerful platform for identifying the root causes of various arrhythmias and investigating therapeutic interventions for these diseases. The thesis was examined by Prof. Chris Huang of the University of Cambridge, the most authoritative figure in cardiac electrophysiology, who has described the work as “outstanding.”.
Ion Channels and the Action Potential -- Potassium Channels Implicated in the Short QT Syndrome -- The Short QT Syndrome -- Model Development -- Methods, Experimental Protocols and Mathematical Preliminaries -- Increased Vulnerability of the Human Ventricle to Re-entrant Excitation in HERG-linked SQT1 -- Mathematically Modelling the Functional Consequences of the SQT2 Mutation -- Proarrhythmia in KCNJ2-linked Short QT Syndrome: Insights from Modelling -- Relationship between Electrical and Mechanical Systole in the Short QT Syndrome: Insights from Modelling -- Discussion and Conclusion.
Statistical Physics, Dynamical Systems and Complexity
Springer Theses, Recognizing Outstanding Ph.D. Research