Rapid myocardial relaxation is essential in maintaining cardiac output, and impaired relaxation is an early indicator of diastolic dysfunction. While the biochemical modifiers of relaxation are well known to include calcium handling, thin filament activation, and myosin kinetics, biophysical and biomechanical modifiers can also alter relaxation. We have previously shown that the relaxation rate is increased by an increasing strain rate, not a reduction in afterload. The slope of the relaxation rate to strain rate relationship defines Mechanical Control of Relaxation (MCR). To investigate MCR further, we performed in vitro experiments and computational modeling of preload-adjustment using intact rat cardiac trabeculae. Trabeculae studies are often performed using isometric (fixed-end) muscles at optimal length (Lo, length producing maximal developed force). We determined that reducing muscle length from Lo increased MCR by 20%, meaning that reducing preload could substantially increase the sensitivity of the relaxation rate to the strain rate. We subsequently used computational modeling to predict mechanisms that might underlie this preload-dependence. Computational modeling was not able to fully replicate experimental data, but suggested that thin-filament properties are not sufficient to explain preload-dependence of MCR because the model required the thin-filament to become more activated at reduced preloads. The models suggested that myosin kinetics may underlie the increase in MCR at reduced preload, an effect that can be enhanced by force-dependence. Relaxation can be modified and enhanced by reduced preload. Computational modeling implicates myosin-based targets for treatment of diastolic dysfunction, but further model refinements are needed to fully replicate experimental data.

Cardiovascular diseases are among the leading causes of death, and their early detection and treatment is important for lowering their prevalence and mortality rate. Electrocardiograms (ECGs) record electrical activity of the heart to provide information used to diagnose and treat various cardiovascular diseases. Many approaches to computer-aided ECG analysis have been performed, including Fourier analysis, principal component analysis, analyzing morphological changes, and machine learning. Due to the high accuracy required of ECG-analysis software, there is no universally-agreed upon algorithm to identify P,Q,R,S, and T-waves and measure intervals of interest. Topological data analysis uses tools from algebraic topology to quantify hole-like shapes within data, and methods using persistence statistics and fractal dimension with machine learning have been applied to ECG signals in the context of detecting arrhythmias within recent years. To our knowledge, there does not exist a method of identifying P,Q,S, and T-waves and measuring intervals of interest which relies on topological features of the data, and we propose a novel topological method for performing these aspects of ECG analysis. Specifically, we establish criteria to identify cardinality-minimal and area-minimal 1-cycles with certain properties as P,Q,S, and T-waves. This yields a procedure for measuring the PR-interval, QT-interval, ST-segment, QRS-duration, P-wave duration, and T-wave duration in Lead II ECG data. We apply our procedure to 400 sets of simulated Lead II ECG signals and compare with the interval values set by the model. Additionally, the algorithm is used to identify cardinality-minimal and area-minimal 1-cycles as P,Q,S, and T-waves in two sets of 200 randomly sampled Lead II ECG signals of real patients with 11 common rhythms. Analysis of optimal 1-cycles identified as P,Q,S, and T-waves and comparison of interval measurements shows that 1-cycle reconstructions can provide useful information about the ECG signal and could hold utility in characterizing arrhythmias.

Impaired relaxation is a prevalent form of diastolic dysfunction, present in nearly all cases of heart failure and in many asymptomatic adults. To date, there are no accepted treatments for impaired relaxation, despite its biochemical control by calcium reuptake, thin filament deactivation, and crossbridge kinetics. Mechanical modification of relaxation was previously theorized to occur through afterload; we, however, have recently shown that relaxation was actually modified by the strain rate of myocardial lengthening. We termed this Mechanical Control of Relaxation, or the sensitivity of the relaxation rate to the strain rate. The mechanisms underlying Mechanical Control of Relaxation are unknown, but computational models and our preliminary data suggest a dependence on myosin detachment. The objective of this study was to evaluate whether myosin was a modifying factor of Mechanical Control of Relaxation. Intact cardiac trabeculae and cardiomyocytes were obtained from rats (Sprague Dawley both treated and untreated with propylthiouracil, Spontaneously Hypertensive, and Wistar Kyoto strains) and underwent load-clamp studies. Mechanical Control of Relaxation could be improved by reducing preload (length) 5%, increasing the sensitivity of the relaxation rate to strain rate by 28±16%. Treatment with 400μM Omecamtiv Mecarbil, a myosin-ATPase specific drug, induced similar increases. Myosin isoform differences were also studied. Collagenase treatment of intact trabeculae increased Mechanical Control by 21±3%; intact myocyte studies show no collagen-dependence. These data provide evidence that the properties of myosin’s response to strain rate are major factors that modify Mechanical Control of myocardial Relaxation.