Zhilin Qu Phd

qu

Associate Professor
Department of Medicine

615 BA
310-794-6050

Education

  • BS, Beijing Normal University, 1987
  • MS, Beijing Normal University, 1990
  • PhD, Beijing Normal University, 1994

Awards and Honors

  • Third Place Award, UCLA Department of Medicine Research Day 2005
  • First Place Science and Technology Award, National Educational Council of China, 1999
  • Third Place Science Award, National Science Foundation of China, 1999
  • Postdoctoral Research Fellowship Award, American Heart Association, Western States Affiliate, 1997-1999

Research Interests

Dr. Qu’s general research
interest is to apply dynamical theories to biological systems at the systems
level. The specific research areas are:

  1. Multi-scale modeling
    of cardiac excitation-contraction coupling and arrhythmias. Ventricular
    fibrillation (VF) is the leading cause of sudden cardiac death and the only
    effective therapy is implantable cardioverter-defibrillators but expensive and
    limited in availability worldwide. Developing new effective and economic
    anti-arrhythmic drugs and improving the efficacy of defibrillators are
    apparently attractive therapeutic strategies, which need a better understanding
    of the mechanisms of VF. The cardiac system is extremely complex with nonlinear
    interactions, involving many levels of regulation: ion channel à sub-cellular compartment à whole cell à multi-cellular tissue à anatomical heart. Combined with experiments, computer
    modeling at all different levels and theories developed according to nonlinear
    dynamics are critically useful for the understanding of the mechanisms of VF
    and thus for the development of novel therapeutics. My goal is to develop an
    integrated computational system with multiple scales of regulation to
    understand the excitation-contraction coupling and arrhythmogenesis in the
    heart.
  2. Dynamics of cardiac
    metabolism. Cell metabolism is regulated by a complex network which not only
    controls the energy demand for the cell but can also generate dynamics to
    trigger cell death and arrhythmias. The initial research goal is to understand
    the dynamics due to the coupling between the glycolytic cycle, the mitochondria
    TCA cycle, and the SR/glycogenic cycle and their spatiotemporal dynamics
    through mathematical modeling and computer simulation, and to provide
    theoretical bases for how cardiac metabolism affects cardiac arrhythmogenesis
    and cardioprotection against ischemic injury. The ultimate goal is to develop a
    computational model system that will eventually include the interaction
    networks of genes, proteins, and metabolites and link the dynamics of the
    interactions to cardiac arrhythmogensis and mitochondria-related cell death. 
  3. Cell cycle control
    and biological signal transduction. Biological processes are regulated by
    complex networks of genes, proteins, and metabolites. Although understanding
    the functions of individual genes or proteins provides critical detailed
    information, this reductionist approach normally favored by biologists has
    limitations and it is far from understanding the whole system, since the
    interactions between the building blocks are complex and nonlinear. Due to the
    complexity, intuition has limited capability for synthesizing all of the
    information gathered from the biological experiments into a cohesive holistic
    understanding of the system behavior. Computer modeling and complex system
    theory become more and more important for understanding the behaviors of signal
    transduction networks in biology. I will use cell cycle control as a specific
    working example but I am also interested in generic dynamics arising from
    biological signal transduction network.

Recent Papers

  1. Nivala M., Korge P., Nivala M., Weiss J.N., Qu Z., “Linking flickering to waves and whole-cell oscillations in a mitochondrial network model,” Biophys J. 2011 Nov 2;1010(9):2102-22. Epub 2011 Nov 1.
  2. Madhavni R.V., Xie Y., Pantazis A., Garfinkel A., Qu Z., Weiss J.N., Olcese R., “Shaping a new Ca2+ conductance to suppress early afterdepolarizations in cardiac myocytes,” J Physiol. 2011 Dec 15;589(Pt 24):6081-92. Epub 2011 Oct 24.
  3. Korge P., Yang L., Yang J.H., Wang Y. Qu Z., Weiss J.N., “Protective role of transient pore openings in calcium handling by cardiac mitochondria,” J Biol Chem. 2011 Oct 7;286(40):34851-7. Epub 2011 Aug 22.
  4. Chang M.G., Sato D., de Lange E., Lee J.H., Karagueuzian H.S., Garfinkel A., Weiss J.N., Qu Z., “Bi-stable wave propagation and early afterdepolarization-mediated cardiac arrhythmias,” Heart Rhythm. 2012 Jan;9(1):115-22. Epub 2011 Aug 17.
  5. Qu Z., Garfinkel A., Weiss J.N., Nivala M., “Multi-scale modeling in biology: how to bridge the gaps between scales?” Prog Biophys Mol Biol. 2011 Oct;107(1):21-31. Epub 2011 Jun 23.
  6. Qu Z., Xie Y., Garfinkel A., Weiss J.N., “T-wave alternans and arrhythmogenesis in cardiac diseases,” Front Physiol. 2010;1:154.
  7. Morita N., Lee J.H., Xie Y., Sovari A., Qu Z., Weiss J.N., karagueuzian H.S., “Suppression of re-entrant and multifocal ventricular fibrillation by the late sodium current blocker ranolazine,” J Am Coll Cardiol. 2011 Jan 18;57(3):366-75.
  8. Weiss J.N., Nivala M., Garfinkel A. Qu Z., “Alternans and arrhythmias: from cell to heart,” Circ Res. 2011 Jan 7;108(1):98-112. Review.
  9. Baher A.A., Uy M., Xie F., Garfinkel A., Qu Z., Weiss J.N., “Bidirectional ventricular tachycardia: ping pong in the His-Purkinje system,” Heart Rhythm. 2011 Apr;8(4)599-605. Epub 2010 Nov 29.
  10. Qu Z., “Chaos in the genesis and maintenance of cardiac arrhythmias,” Prog Biophys Mol Biol. 2011 May;105(3):247-57. Epub 2010 Nov 13. Review.