[One-dimensional time-dependent model of the cardiac pacemaker activity induced by the mechanoelectric feedback in a thermo-electro-mechanical background]

Discrimination of Patients with Varying Degrees of Coronary Artery Stenosis by ECG and PCG Signals Based on Entropy

Coronary heart disease (CHD) is the leading cause of cardiovascular death. This study aimed to propose an effective method for mining cardiac mechano-electric coupling information and to evaluate its ability to distinguish patients with varying degrees of coronary artery stenosis (VDCAS). Five minutes of electrocardiogram and phonocardiogram signals was collected synchronously from 191 VDCAS patients to construct heartbeat interval (RRI)-systolic time interval (STI), RRI-diastolic time interval (DTI), HR-corrected QT interval (QTcI)-STI, QTcI-DTI, Tpeak-Tend interval (TpeI)-STI, TpeI-DTI, Tpe/QT interval (Tpe/QTI)-STI, and Tpe/QTI-DTI series. Then, the cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), joint distribution entropy (JDistEn), magnitude-squared coherence function, cross power spectral density, and mutual information were applied to evaluate the coupling of the series. Subsequently, support vector machine recursive feature elimination and XGBoost were utilized for feature selection and classification, respectively. Results showed that the joint analysis of XSampEn, XFuzzyEn, and JDistEn had the best ability to distinguish patients with VDCAS. The classification accuracy of severe CHD-mild-to-moderate CHD group, severe CHD-chest pain and normal coronary angiography (CPNCA) group, and mild-to-moderate CHD-CPNCA group were 0.8043, 0.7659, and 0.7500, respectively. The study indicates that the joint analysis of XSampEn, XFuzzyEn, and JDistEn can effectively capture the cardiac mechano-electric coupling information of patients with VDCAS, which can provide valuable information for clinicians to diagnose CHD.

High-frequency sarcomeric auto-oscillations induced by heating in living neonatal cardiomyocytes of the rat

In the present study, we investigated the effects of infra-red laser irradiation on sarcomere dynamics in living neonatal cardiomyocytes of the rat. A rapid increase in temperature to >~38 °C induced [Ca(2+)]i-independent high-frequency (~5-10 Hz) sarcomeric auto-oscillations (Hyperthermal Sarcomeric Oscillations; HSOs). In myocytes with the intact sarcoplasmic reticular functions, HSOs coexisted with [Ca(2+)]i-dependent spontaneous beating in the same sarcomeres, with markedly varying frequencies (~10 and ~1 Hz for the former and latter, respectively). HSOs likewise occurred following blockade of the sarcoplasmic reticular functions, with the amplitude becoming larger and the frequency lower in a time-dependent manner. The present findings suggest that in the mammalian heart, sarcomeres spontaneously oscillate at higher frequencies than the sinus rhythm at temperatures slightly above the physiologically relevant levels.