Artículos, conferencias, monografías
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Esta colección está formada por artículos, conferencias, comunicaciones y otras publicaciones elaborados por miembros de la Universitat Politècnica de València.
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Browsing Artículos, conferencias, monografías by Author "721877"
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- PublicationFibrotic Remodeling during Persistent Atrial Fibrillation: In Silico Investigation of the Role of Calcium for Human Atrial Myofibroblast Electrophysiology(MDPI, 2021-11) Sánchez, Jorge; Trénor Gomis, Beatriz Ana; Saiz Rodríguez, Francisco Javier; Dossel, Olaf; Loewe, Axel; Dpto. de Ingeniería Electrónica; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Industrial; Centro de Investigación e Innovación en Bioingeniería; European Commission; Research Council of Norway; Deutsche Forschungsgemeinschaft; Karlsruhe Institute of Technology; Agence Nationale de la Recherche, Francia; Bundesministerium für Bildung und Forschung, Alemania[EN] During atrial fibrillation, cardiac tissue undergoes different remodeling processes at different scales from the molecular level to the tissue level. One central player that contributes to both electrical and structural remodeling is the myofibroblast. Based on recent experimental evidence on myofibroblasts' ability to contract, we extended a biophysical myofibroblast model with Ca2+ handling components and studied the effect on cellular and tissue electrophysiology. Using genetic algorithms, we fitted the myofibroblast model parameters to the existing in vitro data. In silico experiments showed that Ca2+ currents can explain the experimentally observed variability regarding the myofibroblast resting membrane potential. The presence of an L-type Ca2+ current can trigger automaticity in the myofibroblast with a cycle length of 799.9 ms. Myocyte action potentials were prolonged when coupled to myofibroblasts with Ca2+ handling machinery. Different spatial myofibroblast distribution patterns increased the vulnerable window to induce arrhythmia from 12 ms in non-fibrotic tissue to 22 & PLUSMN; 2.5 ms and altered the reentry dynamics. Our findings suggest that Ca2+ handling can considerably affect myofibroblast electrophysiology and alter the electrical propagation in atrial tissue composed of myocytes coupled with myofibroblasts. These findings can inform experimental validation experiments to further elucidate the role of myofibroblast Ca2+ handling in atrial arrhythmogenesis.
- PublicationHeterogeneous Effects of Fibroblast-Myocyte Coupling in Different Regions of the Human Atria Under Conditions of Atrial Fibrillation(Frontiers Media SA, 2019-07-04) Sánchez-Arciniegas, Jorge Patricio; Gomez, Juan F; Martínez-Mateu, Laura; Romero Pérez, Lucia; Saiz Rodríguez, Francisco Javier; Trénor Gomis, Beatriz Ana; Dpto. de Ingeniería Electrónica; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Industrial; Centro de Investigación e Innovación en Bioingeniería; Generalitat Valenciana; Ministerio de Economía y Competitividad[EN] Background: Atrial fibrillation (AF), the most common cardiac arrhythmia, is characterized by alteration of the action potential (AP) propagation. Under persistent AF, myocytes undergo electrophysiological and structural remodeling, which involves fibroblast proliferation and differentiation, modifying the substrate for AP propagation. The aim of this study was to analyze the effects on the AP of fibroblast-myocyte coupling during AF and its propagation in different regions of the atria. Methods: Isolated myocytes were coupled to different numbers of fibroblasts using the established AP models and tissue simulations were performed by randomly distributing fibroblasts. Fibroblast formulations were updated to match recent experimental data. Major ion current conductances of the myocyte model were modified to simulate AP heterogeneity in four different atrial regions (right atrium posterior wall, crista terminalis, left atrium posterior wall, and pulmonary vein) according to experimental and computational studies. Results: The results of the coupled myocyte-fibroblast simulations suggest that a more depolarized membrane potential and higher fibroblast membrane capacitance have a greater impact on AP duration and myocyte maximum depolarization velocity. The number of coupled fibroblasts and the stimulation frequency are determining factors in altering myocyte AP. Strand simulations show that conduction velocity tends to homogenize in all regions, while the left atrium is more likely to be affected by fibroblast and AP propagation block is more likely to occur. The pulmonary vein is the most affected region, even at low fibroblast densities. In 2D sheets with randomly placed fibroblasts, wavebreaks are observed in the low density (10%) central fibrotic zone and when fibroblast density increases (40%) propagation in the fibrotic region is practically blocked. At densities of 10 and 20% the width of the vulnerable window increases with respect to control but is decreased at 40%. Conclusion: Myocyte-fibroblast coupling characteristics heterogeneously affect AP propagation and features in the different atrial zones, and myocytes from the left atria are more sensitive to fibroblast coupling.
- PublicationInfluence of Fibrotic Tissue Arrangement on Intracardiac Electrograms During Persistent Atrial Fibrillation(IEEE, 2019-09-11) Sánchez, Jorge; Nothstein Mark; Unger, Laura; Saiz Rodríguez, Francisco Javier; Trénor Gomis, Beatriz Ana; Dossel, Olaf; Loewe, Axel; Dpto. de Ingeniería Electrónica; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Industrial; Centro de Investigación e Innovación en Bioingeniería; Deutsche Forschungsgemeinschaft[EN] Under persistent atrial fibrillation (peAF), cardiac tissue experiences electrophysiological and structural remodeling. Fibrosis in the atrial tissue has an important impact on the myocyte action potential and its propagation. The objective of this work is to explore the effect of heterogeneities present in the fibrotic tissue and their impact on the intracardiac electrogram (EGM). Human atrial myocyte and fibroblast electrophysiology was simulated using mathematical models proposed by Koivumäki et al. to represent electrical remodeling under peAF and the paracrine effect of the transforming grow factor ¿1 (TGF-¿1). 2D tissue simulations were computed varying the density of fibrosis (10%, 20% and 40%), myofibroblasts and collagen were randomly distributed with different ratios (0%-100%, 50%-50% and 100%- 0%). Results show that increasing the fibrosis density changes the re-entry dynamics from functional to anatomical due to a block in conduction in regions with high fibrosis density (40%). EGM morphology was affected by different ratios of myofibroblasts-collagen. For low myofibroblast densities (below 50%) the duration of active segments was shorter compared to higher myofibroblasts densities (above 50%). Our results show that fibrosis heterogeneities can alter the dynamics of the re-entry and the morphology of the EGM.
- PublicationUsing Machine Learning to Characterize Atrial Fibrotic Substrate from Intracardiac Signals with a Hybrid in silico and in vivo Dataset(Frontiers Media SA, 2021-07-05) Sánchez Arciniegas, Jorge Patricio; Luongo, Giorgio; Nothstein, Mark; Unger, Laura A.; Saiz Rodríguez, Francisco Javier; Trénor Gomis, Beatriz Ana; Luik, Armin; Doessel, Olaf; Loewe, Axel; Dpto. de Ingeniería Electrónica; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Industrial; Centro de Investigación e Innovación en Bioingeniería; European Commission; Deutsche Forschungsgemeinschaft; AGENCIA ESTATAL DE INVESTIGACION[EN] In patients with atrial fibrillation, intracardiac electrogram signal amplitude is known to decrease with increased structural tissue remodeling, referred to as fibrosis. In addition to the isolation of the pulmonary veins, fibrotic sites are considered a suitable target for catheter ablation. However, it remains an open challenge to find fibrotic areas and to differentiate their density and transmurality. This study aims to identify the volume fraction and transmurality of fibrosis in the atrial substrate. Simulated cardiac electrograms, combined with a generalized model of clinical noise, reproduce clinically measured signals. Our hybrid dataset approach combines in silico and clinical electrograms to train a decision tree classifier to characterize the fibrotic atrial substrate. This approach captures different in vivo dynamics of the electrical propagation reflected on healthy electrogram morphology and synergistically combines it with synthetic fibrotic electrograms from in silico experiments. The machine learning algorithm was tested on five patients and compared against clinical voltage maps as a proof of concept, distinguishing non-fibrotic from fibrotic tissue and characterizing the patient's fibrotic tissue in terms of density and transmurality. The proposed approach can be used to overcome a single voltage cut-off value to identify fibrotic tissue and guide ablation targeting fibrotic areas.