000099444 001__ 99444
000099444 005__ 20231006143304.0
000099444 0247_ $$2doi$$a10.22489/CinC.2020.303
000099444 0248_ $$2sideral$$a123039
000099444 037__ $$aART-2020-123039
000099444 041__ $$aeng
000099444 100__ $$aCelotto, Chiara$$uUniversidad de Zaragoza
000099444 245__ $$aRelationship between Atrial Oscillatory Acetylcholine Release Pattern and f-wave Frequency Modulation: a Computational and Experimental Study
000099444 260__ $$c2020
000099444 5060_ $$aAccess copy available to the general public$$fUnrestricted
000099444 5203_ $$aThe frequency of fibrillatory waves (f-waves), F f , exhibits significant variation over time, and previous studies suggest that some of this variation is related to respiratory modulation through the autonomic nervous system. In this study, we tested the hypothesis that this variation (ΔF f ) could be related to acetylcholine concentration ([ACh]) release pattern. Electrocardiograms were recorded from seven patients during controlled respiration before and after full vagal blockade, from which f-wave frequency modulation was characterized. Computational simulations in human atrial tissues were performed to assess the effects of [ACh] release pattern on F f and compared to experimental results in humans. A cross-stimulation protocol was applied onto the tissue to initiate a rotor while cyclically varying [ACh] following a sinusoidal waveform of frequency equal to 0.125 Hz. Different mean levels (0.05, 0.075μM/l) and peak-to-peak ranges (0.1, 0.05, 0.025 μM/l) of [ACh] variation were tested. In all patients, an f-wave frequency modulation could be observed. In 57% of the patients, this modulation was significantly reduced after vagal blockade. Simulations confirmed that rotor frequency variations followed the induced [ACh] patterns. Mean F f was dependent on mean [ACh] level, whileΔF f was dependent on [ACh] variation range.
000099444 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/PID2019-105674RB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-104881RB-I00$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 766082-MY-ATRIA$$9info:eu-repo/grantAgreement/EC/H2020/766082/EU/MultidisciplinarY training network for ATrial fibRillation monItoring, treAtment and progression/MY-ATRIA$$9info:eu-repo/grantAgreement/EUR/ERC-2014-StG-638284$$9info:eu-repo/grantAgreement/ES/DGA/LMP124-18$$9info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group
000099444 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000099444 592__ $$a0.257$$b2020
000099444 593__ $$aComputer Science (miscellaneous)$$c2020
000099444 593__ $$aCardiology and Cardiovascular Medicine$$c2020
000099444 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000099444 700__ $$0(orcid)0000-0003-4273-5403$$aSánchez Tapia, Carlos
000099444 700__ $$0(orcid)0000-0003-2946-3044$$aMountris, Konstantinos
000099444 700__ $$aAbdollahpur, Mostafa
000099444 700__ $$aSandberg, Frida
000099444 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna Lasaosa, Pablo$$uUniversidad de Zaragoza
000099444 700__ $$0(orcid)0000-0002-1960-407X$$aPueyo Paúles, Esther$$uUniversidad de Zaragoza
000099444 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000099444 773__ $$g47, ID303 (2020), [4 pp.]$$pComput. cardiol.$$tComputing in Cardiology$$x2325-8861
000099444 8564_ $$s1373303$$uhttps://zaguan.unizar.es/record/99444/files/texto_completo.pdf$$yVersión publicada
000099444 8564_ $$s2654366$$uhttps://zaguan.unizar.es/record/99444/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000099444 909CO $$ooai:zaguan.unizar.es:99444$$particulos$$pdriver
000099444 951__ $$a2023-10-06-14:07:16
000099444 980__ $$aARTICLE