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Trovato, C.

Publications and source records attributed to Trovato, C..

2 recordsLinked to original sources

In Silico Optimisation of Regenerative Cell Therapy in the Infarcted Human Ventricles to Mitigate Arrhythmic Burden

Myocardial infarction remains a frequent cause of heart failure and mortality. Cell therapy has been shown promising in pre-clinical trials to regenerate the damaged tissue, but delivered cells may beat spontaneously and produce arrhythmias in the ventricles, particularly in the first weeks after delivery, which hinders clinical application. Previous studies have proposed ionic targets to supress the cells automaticity but, so far, the effects of such treatments on the cells calcium dynamics, as a key driver of contractile function, have been insufficiently evaluated. Furthermore, effective strategies are needed that can alleviate the injected cells pro-arrhythmic action potential phenotypes. The goal of our study was to identify mechanisms to mitigate arrhythmic pathways following cell delivery in the chronically infarcted human ventricles using multiscale modelling and simulation. First, we demonstrate credibility by simulating experimentally observed transient automaticity-induced ventricular tachycardia arrhythmias with a frequency of up to 140 beats per minute at two weeks post cell injection in three different infarct geometries. Next, our simulations show how the timeframe during which re-entry was inducible increases 1) from before to after cell delivery at day 0 from 0 to 640 ms, 60 to 100 ms, and 60 to 760 ms in the small, medium, and large scar, respectively, and 2) from day 0 to day 14 after virtual cell injection in the large scar by 175%. Finally, we show that a combination of blocking the funny current and upregulating the inward rectifier potassium current, the sodium potassium pump, and the rapid delayed outward rectifier potassium current can reduce both automaticity-induced and re-entrant arrhythmias while maximising calcium amplitudes. In conclusion, our simulations show that not only automaticity-induced but also re-entrant arrhythmias increase as injected cells mature in the ventricles and depend on the scar size. Furthermore, through modelling and simulation, we identify anti-arrhythmic strategies to improve therapy safety while maximising efficacy.

bioengineering↗

In Silico Evaluation of Cell Therapy in Acute versus Chronic Infarction: Role of Automaticity, Heterogeneity and Purkinje in Human

Human-based modelling and simulation offer an ideal testbed for novel medical therapies to guide experimental and clinical studies. Myocardial infarction (MI) is a common cause of heart failure and mortality, for which novel therapies are urgently needed. Although cell therapy offers promise, electrophysiological heterogeneity raises pro-arrhythmic safety concerns, where underlying complex spatio-temporal dynamics cannot be investigated experimentally. After demonstrating credibility of the modelling and simulation framework, we investigate cell therapy in acute versus chronic MI, and the role of cell heterogeneity, scar size and the Purkinje system. Simulations agreed with experimental and clinical recordings from ionic to ECG dynamics in acute and chronic infarction. Following cell delivery, spontaneous beats were facilitated by heterogeneity in cell populations, chronic MI due to tissue depolarisation, and slow sinus rhythm. Subsequent re-entrant arrhythmias occurred, in some instances with Purkinje involvement, and their susceptibility was enhanced by impaired Purkinje-myocardium coupling, large scars, and acute infarction. We conclude that homogeneity in injected cell populations minimises their spontaneous beating, which is enhanced by chronic MI, whereas a healthy Purkinje-myocardium coupling is key to prevent subsequent re-entrant arrhythmias, particularly for large scars.

bioengineering↗