Loading...
Langevin, population density and moment-based modeling of local and global aspects of intercellular calcium signaling
Wang, Xiao
Wang, Xiao
Abstract
Markov chain models of the coupled gating of intracellular calcium (Ca 2+) channels are often used to study the stochastic dynamic of local Ca2+ release events and whole cell Ca2+ homeostasis. However, the runtime of the Markov chain description of Ca2+ channel gating is exponential in the number of Ca2+ channel states and may thus result in a combinatorial state space explosion when the number of channel states is large. This dissertation presents several novel stochastic modeling approaches that capture important aspects of Ca 2+ signaling while improving computational efficiency. This dissertation presents several novel stochastic modeling approaches that capture important aspects of calcium Ca2+ signaling. First, we present a Ca 2+ release site modeling approach based on a Langevin description of stochastic Ca2+ release. This Langevin model facilitates our investigation of correlations between successive puff/spark amplitudes, durations and inter-spark intervals, and how such puff/spark statistics depend on the number of channels per release site and the kinetics of Ca2+ -mediated inactivation of open channels. Second, we show that when the Ca2+ channel model is minimal, Langevin equations in a whole cell model involving a large number of release sites may be replaced by a single Fokker-Planck equation. This yields an extremely compact and efficient local/global whole cell model that reproduces and helps interpret recent experiments investigating Ca2+ homeostasis in permeabilized ventricular myocytes. Last but not least, we present a population density and moment-based approach to modeling L-type Ca2+ channels. Our approaches account for the effect of heterogeneity of local Ca2+ signals on whole cell Ca currents. Moreover, they facilitate the study of domain Ca-mediated inactivation of L-type Ca channels.
Description
Date
2015-01-01
Journal Title
Journal ISSN
Volume Title
Publisher
Collections
Download Dataset
Files
Loading...
10002161.pdf
Adobe PDF, 5.72 MB
Rights Holder
Usage License
Embargo
Research Projects
Organizational Units
Journal Issue
Keywords
Citation
Advisor
Department
Applied Science
DOI
https://dx.doi.org/doi:10.21220/s2-rpt4-tz50
