EFFECT OF DESTRUCTION OF NTS AND PVN ON NEIGUAN (PC6)- ELECTROACUPUNCTURE-I NDUCED IMPROVEMENT OF ISCHEMIC MYOCARDIAL CELLULAR MEMBRANE POTENTIALS IN RABBITS

Objective: To observe the influence of electrolytic destruction of nucleus soli tary tract (NTS) and hypothalamic paraventricular nucleus (PVN) on the effect of electroacupuncture (EA) in improving ischemic myocardia cellular transmembrane action potential (TMAP). Methods: 38 Japanese breed big-ear wh ite rabbits (ane sthetized with 20% Urethane, 4 mL/kg) were randomly divided into acute myocardia l ischemia (AMI) group (n=8), PVN destruction group ( n=12) and PVN+NTS destructio n group (n=18). AMI model was established by occlusion of the descending anterio r branch (DAB) of the coronary artery. TMAP of myocytes was recorded by using a glass microelectrode which was fixed to a suspending spring silver wire. Bilater al "Neiguan"(PC 6) in all the 3 groups were punctured and stimulated electri call y by using parameters of continuous waves, frequency of 7 Hz, intensity of 6 mA a nd duration of 30 minutes. Results: After AMI, ECG-ST elevated significantly whil e APA lowered, APD50 and APD90 shortened clearly in comparison with those of pre -AMI in the 3 groups. Compared with AMI group, ECG-ST values of PVN destructi on group and PVN+NTS destruction group were significantly higher (P <0.05～0.01), whi le APA, APD50 and APD90 all significantly lower in all the recording time course s(P<0.05). The facts displayed that electrolytic destru ction of PVN and PVN+NT S could produce ischemic myocardial injury and reduce the protective effect of E A on ischemic myocardial cells. Comparison between PVN destruction and PVN+NTS g roups showed that all the 4 indexes of the later group were evidently worse than those of the former group (P<0.05), suggesting after des truction of these two n uclei, the effect of EA was worsened further. Conclusion: Electrolytic destru ction of PVN and NTS weakens the protective effect of EA on ischemic myocardial cells, both NTS and PVN take part in the effect of EA of "Neiguan"(PC 6) Point i n improving ischemic myocardium.

A Convolutional Neural Network Model for Classifying Cardiac Membrane Potential Patterns

Investigation of the electrophysiological mechanisms that induce arrhythmias is one of the most important issues in scientific research.Since computational cardiology allows the systematic dissection of causal mechanisms of observed effects,simulations based on the ionic channel mathematical models have become one of the most widely used methods.To reduce themanual classification of different types of membrane potential patterns produced during simulations,a convolutional neural network is developed in this paper.The model includes 4convolution layers,4 pooling layers and a fully connected layer.An activation function of Re LU is used.Before machine learning,all the pattems are calibrated,cut,and normalized to a uniform format with a size of 256×256.The contour boundary of each pattern is extracted using the maximum between-class variance method.In the examination,the proposed learning algorithm shows a recognition accuracy of 97%on test data set after training.