Key result
Gradient-based parameter optimization fitting control and IKr-blocked waveforms successfully generates cell-specific hiPSC-CM models.
Why the study?
Fitting a single action potential record in parameter optimization methods was not always successful in providing a unique ionic current composition due to a shortage of information.
A gradient-based parameter optimization method using two different action potential waveforms improves the accuracy of cell-specific computational models of hiPSC-CMs.
Answers are grounded in this paper and cite their sources.
Preclinical optimization advances hiPSC-CM models; leaves open clinical translation for arrhythmia prediction.
Parameter optimization (PO) methods to determine the ionic current composition of experimental cardiac action potential (AP) waveform have been developed using a computer model of cardiac membrane excitation. However, it was suggested that fitting a single AP record in the PO method was not always successful in providing a unique answer because of a shortage of information. We found that the PO method worked perfectly if the PO method was applied to a pair of a control AP and a model output AP in which a single ionic current out of 11 current species, such as I Kr , I CaL , I Na , I Ks or I Kur , was partially blocked in silico . When the target was replaced by a pair of experimental control and I Kr -blocked records of APs generated spontaneously in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), the simultaneous fitting of the two waveforms by the PO method was hampered to some extent by the irregular slow fluctuations in the V m recording and/or sporadic alteration in AP configurations in the hiPSC-CMs. This technical problem was largely removed by selecting stable segments of the records for the PO method. Moreover, the PO method was made fail-proof by running iteratively in identifying the optimized parameter set to reconstruct both the control and the I Kr -blocked AP waveforms. In the lead potential analysis, the quantitative ionic mechanisms deduced from the optimized parameter set were totally consistent with the qualitative view of ionic mechanisms of AP so far described in physiological literature.
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Zhang et al. (2023) studied hiPSC-CMs action potential modeling. Gradient-based parameter optimization method fitting two AP waveforms vs. Single AP waveform fitting was evaluated on Mean square error (MSE) of the parameter optimization method. A gradient-based parameter optimization method fitting both control and IKr-blocked action potential waveforms successfully generated cell-specific models of hiPSC-CMs.
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