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A model of beta-adrenergic modulation of IKs in the guinea-pig ventricle (Severi et al. 2009)
Accession: 120835
Detailed understanding of IKs gating complexity may provide clues on the mechanisms of cardiac repolarization instability and the resulting arrhythmias. We developed and tested a kinetic Markov model to interpret physiologically relevant IKs properties, including pause-dependency and modulation by beta-adrenergic receptors (beta-AR). The model was developed from the Silva & Rudy formulation. Parameters were optimized on control and ISO experimental data, respectively.
Reference: Severi S, Corsi C, Rocchetti M, Zaza A (2009) Mechanisms of beta-adrenergic modulation of I(Ks) in the guinea-pig ventricle: insights from experimental and model-based analysis. Biophys J 96:3862-72 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type:  
Brain Region(s)/Organism:  
Cell Type(s):   Cardiac ventricular cell;
Channel(s):  I_Ks;  
Gap Junctions:  
Receptor(s):  
Gene(s):  
Transmitter(s):  
Simulation Environment:  Simulink;
Model Concept(s):  Ion Channel Kinetics;
Implementer(s):  Severi, Stefano [stefano.severi at unibo.it];
Search NeuronDB for information about:  I_Ks;
\
SeveriEtAl2009
readme.html
IKs.jpg
screenshot1.jpg
parottimiCTRL.mat
parottimiISO.mat
IKs.mdl
parametersIKs.m
                            
This is the readme for the model associated with the paper

Severi S, Corsi C, Rocchetti M, Zaza A (2009) Mechanisms of
beta-adrenergic modulation of I(Ks) in the guinea-pig ventricle:
insights from experimental and model-based analysis.
Biophys J 96:3862-72

This simulink code is provided in an as-is state by Stefano Severi.
Parameters are set to reproduce the current response to a single
voltage step in control conditions.

Usage:
Start matlab and type

parametersIKs
Iks

on the command line to load initial conditions and the simulink model:

simulink picture displays here (when works)

Select Simulation->Run in simulink, and then create a figure to see
the result:

plot(t,IKs)



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