Publication details
Mechanobiological distinction of focal and conductive arrhythmias by AFM
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| Year of publication | 2026 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | Background: Cardiac arrhythmias arise from either abnormal focal impulse formation or impaired action potential propagation. Current in vitro models and biosensors primarily focus on cellular electrophysiology, often neglecting the stochastic significance of events and the mechanobiological aspects of cardiac contractions. There is an unmet clinical need for sensitive platforms that can distinguish these distinct arrhythmic mechanisms through mechanical analysis. Purpose: This research aimed to develop a highly sensitive biosensor using human pluripotent stem cell (hPSC) derived dualbeating organoids combined with atomic force microscopy (AFM). The objective was to discriminate between focal and conductive arrhythmic contractions by monitoring the threedimensional contractile movement and stochastic fluctuations of cardiac tissue. Methods: Two conductively coupled hPSCderived beating organoids were monitored using an AFM triangular cantilever as a sensitive transducer. Contractile behaviour was assessed by measuring vertical (DFL) and lateral (LF) deflection data at 100 Hz. A novel analysis of regression residuals was employed to quantify stochastic fluctuations, distinguishing the vertical and lateral directions of movement. The system’s sensitivity was validated using pharmacological agents, including heptanol (gap junction uncoupler), lidocaine (sodium channel blocker), salbutamol (ß2agonist), and aminophylline (phosphodiesterase inhibitor). Results: Synchronised beating produced predominantly vertical deflection, whereas desynchronised clusters induced significant torsional bending and lateral signals. Analysis of the variance of regression residuals revealed significantly higher stochastic fluctuations in unsynchronised clusters (SD: 0.89) compared to controls (SD: 0.56). Heptanol increased residual variance to SD 0.87, effectively modelling conduction blockade. Conversely, salbutamol and aminophylline reduced residual variance (SD 0.43 and 0.32 respectively), indicating improved conduction stability. The AFMbased transducer successfully discriminated focal from conductive arrhythmias on a singlebeat basis. Conclusions: The dualorganoid AFM biosensor provides a robust platform for distinguishing arrhythmia mechanisms through mechanobiological analysis. By capturing stochastic, lowabundance arrhythmic events often missed by deterministic analyses, this approach enhances translational relevance for cardiotoxicity assessment and precision medicine in cardiovascular health. |
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