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Updated: May 29, 2026

Human iPSC-Derived Cardiomyocyte Networks on Multiwell Micro-electrode Arrays for Recurrent Action Potential Recordings
Published on: July 15, 2019
Rapid functional evaluation of beta-cells by extracellular recording of membrane potential oscillations with
Thomas Pfeiffer1, Udo Kraushaar, Martina Düfer
1NMI Natural and Medical Science Institute, Department of Electrophysiology, University of Tübingen, Markwiesenstraße 55, 72770 Reutlingen, Germany.
Abstract:
The membrane potential (V (m)) of beta-cells oscillates at glucose concentrations between ~6 and 25 mM, i.e. burst phases with action potentials alternate with silent interburst phases generating so-called slow waves. The slow waves drive oscillations of the cytosolic Ca(2+) concentration ([Ca(2+)](c)) and insulin secretion. The length of the bursts correlates with the amount of insulin release. Thus, the fraction of plateau phase (FOPP), i.e. the percentage of time with burst activity, is an excellent marker for beta-cell function and metabolic integrity. Extracellular voltage changes of mouse islets were measured using a microelectrode array (MEA) allowing the detection of burst and interburst phases. At a non-stimulating glucose concentration (3 mM) no electrical activity was detectable while bursting was continuous at 30 mM. The glucose concentration-response (determined as FOPP) curve revealed half-maximal stimulation at 12 ± 1 mM (Hill equation fit). The signal was sensitive to K(ATP) channel modulators, e.g. tolbutamide or diazoxide. Simultaneous recordings of electrical activity and [Ca(2+)](c) revealed congruent bursts and peaks, respectively. The extracellular recordings are in perfect agreement with more time-consuming intracellular electrical recordings. The results provide a 'proof-of-principle' for detection of beta-cell slow waves and determination of the FOPP using extracellular electrodes in a MEA-based system. The method is facile and provides the capability to study the effects of modulators of beta-cell function including possible anti-diabetic drugs in real time. Moreover, the method may be useful for checking the metabolic integrity of human donor islets prior to transplantation.
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