Limitations in electrophysiological model development and validation caused by differences between simulations and experimental protocols

Carro, J. ; Rodríguez-Matas, J.F. (Universidad de Zaragoza) ; Monasterio, V. ; Pueyo, E. (Universidad de Zaragoza)

Resumen: Models of ion channel dynamics are usually built by fitting isolated cell experimental values of individual parameters while neglecting the interaction between them. Another shortcoming regards the estimation of ionic current conductances, which is often based on quantification of Action Potential (AP)-derived markers. Although this procedure reduces the uncertainty in the calculation of conductances, many studies evaluate electrophysiological AP-derived markers from single cell simulations, whereas experimental measurements are obtained from tissue preparations. In this work, we explore the limitations of these approaches to estimate ion channel dynamics and maximum current conductances and how they could be overcome by using multiscale simulations of experimental protocols. Four human ventricular cell models, namely ten Tusscher and Panfilov (2006), Grandi et al. (2010), O''Hara et al. (2011), and Carro et al. (2011), were used. Two problems involving scales from ion channels to tissue were investigated: 1) characterization of L-type calcium voltage-dependent inactivation ICa, L; 2) identification of major ionic conductance contributors to steady-state AP markers, including APD90, APD75, APD50, APD25, Triangulation and maximal and minimal values of V and dV/dt during the AP (Vmax, Vmin, dV/dtmax, dV/dtmin). Our results show that: 1) ICa, L inactivation characteristics differed significantly when calculated from model equations and from simulations reproducing the experimental protocols. 2) Large differences were found in the ionic currents contributors to APD25, Triangulation, Vmax, dV/dtmax and dV/dtmin between single cells and 1D-tissue. When proposing any new model formulation, or evaluating an existing model, consistency between simulated and experimental data should be verified considering all involved effects and scales.

Idioma: Inglés

DOI: 10.1016/j.pbiomolbio.2016.11.006

Año: 2017

Publicado en: PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY 129 (2017), 53-64
ISSN: 0079-6107

Factor impacto JCR: 3.427 (2017)

Categ. JCR: BIOPHYSICS rank: 21 / 72 = 0.292 (2017) - Q2 - T1
Categ. JCR: BIOCHEMISTRY & MOLECULAR BIOLOGY rank: 109 / 292 = 0.373 (2017) - Q2 - T2

Factor impacto SCIMAGO: 1.446 - Biophysics (Q1) - Molecular Biology (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T88
Financiación: info:eu-repo/grantAgreement/ES/DGA/T96
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2012-37546-C03-03
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2013-41998-R

Tipo y forma: Revisión (PrePrint)

Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)
Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)