A porcine large animal model of radiofrequency ablation-induced left bundle branch block.

Background: Electrocardiographic (ECG) features of left bundle branch (LBB) block (LBBB) can be observed in up to 20%-30% of patients suffering from heart failure with reduced ejection fraction. However, predicting which LBBB patients will benefit from cardiac resynchronization therapy (CRT) or conduction system pacing remains challenging. This study aimed to establish a translational model of LBBB to enhance our understanding of its pathophysiology and improve therapeutic approaches. Methods: Fourteen male pigs underwent radiofrequency catheter ablation of the proximal LBB under fluoroscopy and ECG guidance. Comprehensive clinical assessments (12-lead ECG, bloodsampling, echocardiography, electroanatomical mapping) were conducted before LBBB induction, after 7, and 21 days. Three pigs received CRT pacemakers 7 days after LBB ablation to assess resynchronization feasibility. Results: Following proximal LBB ablation, ECGs displayed characteristic LBBB features, including QRS widening, slurring in left lateral leads, and QRS axis changes. QRS duration increased from 64.2 ± 4.2 ms to 86.6 ± 12.1 ms, and R wave peak time in V6 extended from 21.3 ± 3.6 ms to 45.7 ± 12.6 ms. Echocardiography confirmed cardiac electromechanical dyssynchrony, with septal flash appearance, prolonged septal-to-posterior-wall motion delay, and extended ventricular electromechanical delays. Electroanatomical mapping revealed a left ventricular breakthrough site shift and significantly prolonged left ventricular activation times. RF-induced LBBB persisted for 3 weeks. CRT reduced QRS duration to 75.9 ± 8.6 ms, demonstrating successful resynchronization. Conclusion: This porcine model accurately replicates the electrical and electromechanical characteristics of LBBB observed in patients. It provides a practical, cost-effective, and reproducible platform to investigate molecular and translational aspects of cardiac electromechanical dyssynchrony in a controlled and clinically relevant setting.

Acute antiarrhythmic effects of SGLT2 inhibitors-dapagliflozin lowers the excitability of atrial cardiomyocytes.

In recent years, SGLT2 inhibitors have become an integral part of heart failure therapy, and several mechanisms contributing to cardiorenal protection have been identified. In this study, we place special emphasis on the atria and investigate acute electrophysiological effects of dapagliflozin to assess the antiarrhythmic potential of SGLT2 inhibitors. Direct electrophysiological effects of dapagliflozin were investigated in patch clamp experiments on isolated atrial cardiomyocytes. Acute treatment with elevated-dose dapagliflozin caused a significant reduction of the action potential inducibility, the amplitude and maximum upstroke velocity. The inhibitory effects were reproduced in human induced pluripotent stem cell-derived cardiomyocytes, and were more pronounced in atrial compared to ventricular cells. Hypothesizing that dapagliflozin directly affects the depolarization phase of atrial action potentials, we examined fast inward sodium currents in human atrial cardiomyocytes and found a significant decrease of peak sodium current densities by dapagliflozin, accompanied by a moderate inhibition of the transient outward potassium current. Translating these findings into a porcine large animal model, acute elevated-dose dapagliflozin treatment caused an atrial-dominant reduction of myocardial conduction velocity in vivo. This could be utilized for both, acute cardioversion of paroxysmal atrial fibrillation episodes and rhythm control of persistent atrial fibrillation. In this study, we show that dapagliflozin alters the excitability of atrial cardiomyocytes by direct inhibition of peak sodium currents. In vivo, dapagliflozin exerts antiarrhythmic effects, revealing a potential new additional role of SGLT2 inhibitors in the treatment of atrial arrhythmias.

An Extended Modular Processing Pipeline for Event-Based Vision in Automatic Visual Inspection.

Dynamic Vision Sensors differ from conventional cameras in that only intensity changes of individual pixels are perceived and transmitted as an asynchronous stream instead of an entire frame. The technology promises, among other things, high temporal resolution and low latencies and data rates. While such sensors currently enjoy much scientific attention, there are only little publications on practical applications. One field of application that has hardly been considered so far, yet potentially fits well with the sensor principle due to its special properties, is automatic visual inspection. In this paper, we evaluate current state-of-the-art processing algorithms in this new application domain. We further propose an algorithmic approach for the identification of ideal time windows within an event stream for object classification. For the evaluation of our method, we acquire two novel datasets that contain typical visual inspection scenarios, i.e., the inspection of objects on a conveyor belt and during free fall. The success of our algorithmic extension for data processing is demonstrated on the basis of these new datasets by showing that classification accuracy of current algorithms is highly increased. By making our new datasets publicly available, we intend to stimulate further research on application of Dynamic Vision Sensors in machine vision applications.