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Arking et al. 2011 ; Jeyaraj et al. 2012 ). However, genes interact with each other and
a genetic network perspective of cardiac electrophysiology is far from known and
how to reveal and study the gene networks related to cardiac diseases is a great
challenge (Weiss et al. 2012 ).
Many signaling pathways and their roles in cardiac excitation-contraction cou-
pling and arrhythmias have been identified (Wang 2007 ; Swaminathan et al. 2012 ;
Grimm et al. 2011 ), such as the
-adrenergic signaling pathways, the MAPK
signaling pathways, the CaMKII signaling pathways, and the ROS activated sig-
naling pathways. These signaling pathways are interlinked, causing complex effects
that cannot be understood fully by experimental observations only. Mathematical
models have been developed to quantitatively analyze the effects of these signaling
pathways on cardiac diseases. Saucerman et al. (Saucerman et al. 2003 , 2004 )
developed the first model to quantitatively study the effects of
β
-adrenergic signal-
ing on cardiac contractility and excitation. In this model (Fig. 10.2 ),
β
-adrenergic
stimulation activates cyclic AMP, which then activates protein kinase A (PKA).
PKA phosphorylates L-type Ca 2+ channel (LCC) and phospholamban, which
increases the open probability of the LCC and the rate of sarcoplasmic reticulum
(SR) Ca 2+ uptake. The model was used to study the effects of isoproterenol on Ca 2+
cycling and action potential dynamics (Saucerman et al. 2003 , 2004 ). Other
modeling studies (Hund and Rudy 2004 ; Hund et al. 2008 ; Saucerman and Bers
2008 ; Hashambhoy et al. 2009 , 2010 ) have focused on the effects of CaMKII
singling pathways on intracellular Ca 2+
β
cycling and action potential dynamics.
The synergy between
-adrenergic and CaMKII signaling has also been studied
by computer modeling (Soltis and Saucerman 2010 ). These studies have provided
important insights into cardiac signaling and diseases.
Cell metabolism is regulated by hundreds of metabolites that form a highly
interconnected complex network (Feist et al. 2009 ). In cardiac myocytes, the
metabolic network not only provides the energy needed for cardiac contraction
but also affects cardiac electrophysiology. Mathematical models have been devel-
oped to study the dynamics of cardiac metabolism (Cortassa et al. 2003 , 2004 ;Wu
et al. 2007 ; Dash and Beard 2008 ; Zhou et al. 2005a , b ; Jafri and Kotulska 2006 ).
Emergent properties such as oscillations (Jafri and Kotulska 2006 ; Cortassa
et al. 2004 ; Yang et al. 2008 ), occur due to the interactions of the metabolites and
feedback loops in the metabolic networks. The metabolic oscillations result in ATP
oscillations, which then causes oscillations in action potential duration due to
opening of the ATP-sensitive potassium channels (O'Rourke et al. 1994 ; Yang
et al. 2008 ). The oscillations may be responsible for arrhythmogenesis in
postischemic hearts (Akar et al. 2005 ).
β
10.2.2 The CRU Network and Ca 2+ Cycling Dynamics
Besides the molecular networks, organelles form spatial networks in cardiac cells
(Fig. 10.3a ). CRU network is the primary network generating intracellular Ca 2+
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