Mierzejewski, M. | bioRxiv Science

bioRxiv2026

A scalable mesh microelectrode array platform for longitudinal electrophysiology in neural spheroids

Electrophysiological interfacing remains difficult in three-dimensional in vitro models, when using planar microelectrode arrays or optical methods. This challenge limits experimental progress using such models, despite their promise of better physiological relevance than monolayer cell culture. Mesh MEAs which can integrate conformally on or even within tissue offer a possible solution but are not yet widely accessible. Here, we present a mesh MEA device, designed as a simple, manufacturable platform for spheroid electrophysiology. In neural spheroids, the device enabled longitudinal electrophysiological recordings and pharmacological modulation of spontaneous electrical activity. On native polyimide meshes, spheroids maintained their shape while cells enveloped the mesh, embedding electrodes to a depth of 100 {micro}m after 2 weeks. In contrast, laminin biofunctionalization of the mesh promoted outgrowth and migration of cells. This device and associated methods should be adaptable to organoids, ex vivo tissue, or bioengineered in vitro models.

neuroscience↗

bioRxiv2026

Nanopore event detection in a simple and adaptive way

Nanopore read-out, that is the current signals measured across nanometer-sized openings in dielectric membranes or through natural protein channels, enables the detection, identification and sequencing of individual molecules. The detection can take place by analyzing the events of single biomolecules interacting with the pore. The accuracy in the detection of these single events is key for identification of physicochemical properties of analyte molecules. To this end, we further develop a very simple, fast, almost parameter-free, and adaptable cluster-based event detection (CBED) algorithm that clusters the nanopore signals prior to detecting nanopore events. The algorithm is validated against two other event detection schemes with respect to simplicity and efficiency. For this, nanopore data from four different experiments stemming from different laboratories that vary in the nanopore type, size, and analyte are considered. The comparison is made on the basis of the number of events detected, their quality, and the most important features extracted from nanopore events. Our results underline the higher efficiency and less noise of the CBED detected events for biological nanopore data and the need for an on-the-fly adaptivity of the baseline current for a class of solid-state nanopore data.

bioinformatics↗