Artificial intelligence (AI) algorithms are being applied across a large spectrum of everyday life activities. The implementation of AI algorithms in clinical practice has been met with some skepticism and concern, mainly because of the uneasiness that stems, in part, from a lack of understanding of how AI operates, together with the role of physicians and patients in the decision-making process; uncertainties regarding the reliability of the data and the outcomes; as well as concerns regarding the transparency, accountability, liability, handling of personal data, and monitoring and system upgrades. In this viewpoint, we take these issues into consideration and offer an integrated regulatory framework to AI developers, clinicians, researchers, and regulators, aiming to facilitate the adoption of AI that rests within the FDA’s pathway, in research, development, and clinical medicine.

Mitochondrial networks in cardiac myocytes under oxidative stress show collective (cluster) behavior through synchronization of their inner membrane potentials (ΔΨ _m ). However, it is unclear whether the oscillation frequency and coupling strength between individual mitochondria affect the size of the cluster and vice versa. We used the wavelet transform and developed advanced signal processing tools that allowed us to capture individual mitochondrial ΔΨ _m oscillations in cardiac myocytes and examine their dynamic spatio-temporal properties. Heterogeneous frequency behavior prompted us to sort mitochondria according to their frequencies. Signal analysis of the mitochondrial network showed an inverse relationship between cluster size and cluster frequency as well as between cluster amplitude and cluster size. High cross-correlation coefficients between neighboring mitochondria clustered longitudinally along the myocyte striations, indicated anisotropic communication between mitochondria. Isochronal mapping of the onset of myocyte-wide ΔΨ _m depolarization further exemplified heterogeneous ΔΨ _m among mitochondria. Taken together, the results suggest that frequency and amplitude modulation of clusters of synchronized mitochondria arises by means of strong changes in local coupling between neighboring mitochondria.

Vagus nerve stimulation (VNS) has been found to exert anti‐inflammatory effects in different clinical settings and has been associated with improvement of clinical outcomes. However, evidence on the mechanistic link between the potential association of inflammatory status with clinical outcomes following VNS is scarce. This review aims to summarize the existing knowledge linking VNS with inflammation and its potential link with major outcomes in cardiovascular diseases, in both preclinical and clinical studies. Existing data show that in the setting of myocardial ischemia and reperfusion, VNS seems to reduce inflammation resulting in reduced infarct size and reduced incidence of ventricular arrhythmias during reperfusion. Furthermore, VNS has a protective role in vascular function following myocardial ischemia and reperfusion. Atrial fibrillation burden has also been reduced by VNS, whereas suppression of inflammation may be a potential mechanism for this effect. In the setting of heart failure, VNS was found to improve systolic function and reverse cardiac remodeling. In summary, existing experimental data show a reduction in inflammatory markers by VNS, which may cause improved clinical outcomes in cardiovascular diseases. However, more data are needed to evaluate the association between the inflammatory status with the clinical outcomes following VNS.

An increasing number of studies have shown the impact of social determinants of health (SDoHs) on different cardiovascular outcomes. SDoHs influence the regional incidence of heart failure, heart failure outcomes, and heart failure readmission rates; can prevent use of advanced heart failure therapies in minorities with an indication for their use; can influence the incidence of coronary artery disease and peripheral artery disease outcomes; and can also prevent providing equal quality of care to all patients with myocardial infarction. In the setting of arrhythmias, specific SDoHs can increase the incidence of atrial fibrillation and adversely affect major outcomes in these patients. In congenital heart diseases, SDoHs can affect major outcomes, as well. In conclusion, SDoHs significantly impact cardiovascular morbidity and death and specific outcomes of patients with cardiovascular disease. Policy measures that aim to improve those SDoHs that negatively affect health outcomes hold promise for improving cardiovascular outcomes at individual and population levels.