Jesús Carro – DENIS Project

Jesús Carro was born in Oviedo (Asturias, Spain), in 1985. He received the M.Sc. degree in Telecommunication Engineering in 2009 at the Universtity of Oviedo, and the M.Sc. degree in Biomedical Engineering in 2010 at the University of Zaragoza. He is currently finishing his PhD Thesis in Biomedical Engineering at the University of Zaragoza.

His research interests are focused on the mathematical modeling of the electrical activity of the cardiac cells. In particular, he is working in a new electrophisiological model of the human ventricular cells. He has participated in several national research projects. Since 2011, he works as lecturer at the University San Jorge (Zaragoza, Spain).

In 2018, he was elected as a member of the CellML Editorial Boar for three years (2018-2021).

Contact info:

Jesús Carro Fernández
School of Architecture and Technology
University San Jorge
Autovía A-23 Zaragoza-Huesca Km. 299
50830 Villanueva de Gállego, Zaragoza (Spain)

Publications

Journal Articles

Monasterio, V; Castro, J; Carro, J

DENIS: Solving cardiac electrophysiological simulations with volunteer computing

PLoS One, 13 (10), pp. e0205568, 2018, ISSN: 1932-6203.

Links | BibTeX

Carro, J; Pueyo, E; Rodríguez Matas, J F

A response surface optimization approach to adjust ionic current conductances of cardiac electrophysiological models. Application to the study of potassium level changes

PLoS One, 13 (10), pp. e0204411, 2018, ISSN: 1932-6203.

Abstract | Links | BibTeX

@article{carro2018,
title = {A response surface optimization approach to adjust ionic current conductances of cardiac electrophysiological models. Application to the study of potassium level changes},
author = {Carro, J. and Pueyo, E. and Rodríguez Matas, J.F.},
url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0204411},
doi = {10.1371/journal.pone.0204411},
issn = {1932-6203},
year = {2018},
date = {2018-10-03},
journal = {PLoS One},
volume = {13},
number = {10},
pages = {e0204411},
abstract = {Cardiac electrophysiological computational models are often developed from previously published models. The new models may incorporate additional features to adapt the model to a different species or may upgrade a specific ionic formulation based on newly available experimental data. A relevant challenge in the development of a new model is the estimation of certain ionic current conductances that cannot be reliably identified from experiments. A common strategy to estimate those conductances is by means of constrained non-linear least-squares optimization. In this work, a novel methodology is proposed for estimation of ionic current conductances of cardiac electrophysiological models by using a response surface approximation-based constrained optimization with trust region management. Polynomial response surfaces of a number of electrophysiological markers were built using statistical sampling methods. These markers included action potential duration (APD), triangulation, diastolic and systolic intracellular calcium concentration, and time constants of APD rate adaptation. The proposed methodology was applied to update the Carro et al. human ventricular action potential model after incorporation of intracellular potassium ([K+]i) dynamics. While the Carro et al. model was well suited for investigation of arrhythmogenesis, it did not allow simulation of [K+]i changes. With the methodology proposed in this study, the updated Carro et al. human ventricular model could be used to simulate [K+]i changes in response to varying extracellular potassium ([K+]o) levels. Additionally, it rendered values of evaluated electrophysiological markers within physiologically plausible ranges. The optimal values of ionic current conductances in the updated model were found in a notably shorter time than with previously proposed methodologies. As a conclusion, the response surface optimization-based approach proposed in this study allows estimating ionic current conductances of cardiac electrophysiological computational models while guaranteeing replication of key electrophysiological features and with an important reduction in computational cost with respect to previously published approaches. The updated Carro et al. model developed in this study is thus suitable for the investigation of arrhythmic risk-related conditions, including those involving large changes in potassium concentration.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

Cardiac electrophysiological computational models are often developed from previously published models. The new models may incorporate additional features to adapt the model to a different species or may upgrade a specific ionic formulation based on newly available experimental data. A relevant challenge in the development of a new model is the estimation of certain ionic current conductances that cannot be reliably identified from experiments. A common strategy to estimate those conductances is by means of constrained non-linear least-squares optimization. In this work, a novel methodology is proposed for estimation of ionic current conductances of cardiac electrophysiological models by using a response surface approximation-based constrained optimization with trust region management. Polynomial response surfaces of a number of electrophysiological markers were built using statistical sampling methods. These markers included action potential duration (APD), triangulation, diastolic and systolic intracellular calcium concentration, and time constants of APD rate adaptation. The proposed methodology was applied to update the Carro et al. human ventricular action potential model after incorporation of intracellular potassium ([K+]i) dynamics. While the Carro et al. model was well suited for investigation of arrhythmogenesis, it did not allow simulation of [K+]i changes. With the methodology proposed in this study, the updated Carro et al. human ventricular model could be used to simulate [K+]i changes in response to varying extracellular potassium ([K+]o) levels. Additionally, it rendered values of evaluated electrophysiological markers within physiologically plausible ranges. The optimal values of ionic current conductances in the updated model were found in a notably shorter time than with previously proposed methodologies. As a conclusion, the response surface optimization-based approach proposed in this study allows estimating ionic current conductances of cardiac electrophysiological computational models while guaranteeing replication of key electrophysiological features and with an important reduction in computational cost with respect to previously published approaches. The updated Carro et al. model developed in this study is thus suitable for the investigation of arrhythmic risk-related conditions, including those involving large changes in potassium concentration.

Carro, J; Rodríguez Matas, J F; Monasterio, V; Pueyo, E

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

Progress in Biophysics and Molecular Biology, 129 , pp. 53-64, 2017, ISSN: 0079-6107.

Links | BibTeX

Carro, J; Rodríguez Matas, J F; Pueyo, E

A Methodology to Improve Human Ventricular Models for the Investigation of Cardiac Arrhythmias

Biophysical Journal, 112 (3, Supplement 1), pp. 403a, Published in abstract form, 2017, ISSN: 0006-3495.

Links | BibTeX

Rodríguez Matas, J F; Carro, J; Pueyo, E; Burrage, K; Rodríguez, B

Impact of Multiple Ionic Changes in Arrhythmic Risk Biomarkers in Human Ventricular Electrophysiology

Biophysical Journal, 102 (3), pp. 543-543, Published in abstract form, 2012.

Links | BibTeX

Carro, J; Rodríguez Matas, J F; Laguna, P; Pueyo, E

A human ventricular cell model for investigation of cardiac arrhythmias under hyperkalaemic conditions

Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 369 (1954), pp. 4205–4232, 2011.

Links | BibTeX

Inproceedings

Castro, J; Monasterio, V; Carro, J

Volunteer Computing Approach for the Collaborative Simulation of Electrophysiological Models

2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pp. 118-123, 2016.

Links | BibTeX

Marcén, A C; Carro, J; Monasterio, V

Wearable Monitoring for the Detection of Nocturnal Agitation in Dementia

Proceedings of the 6th International Joint Conference on Pervasive and Embedded Computing and Communication Systems, pp. 63-69, 2016, ISBN: 978-989-758-195-3.

Links | BibTeX