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Updated: Sep 23, 2026

Revealing Electromechanical Control of Tissue Homeostasis Using a Two-Layer Microfluidic Device
Published on: September 19, 2025
Accelerated immunostaining of thick biological tissues using bidirectional electric fields with reversible
Ziwen Zhou1, Xiao Xiao1,2,3, Lijuan Du3
1Department of Neurology of the Second Affiliated Hospital of Zhejiang University School of Medicine, State Key Laboratory of Extreme Photonics and Instrumentation & Liangzhu Laboratory, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Abstract:
Immunostaining of thick biological tissues is often limited by slow antibody transport, resulting in long processing times and depth-dependent labeling. We describe an automated immunostaining approach based on an alternating bidirectional electric field, termed ARDEI, that improves labeling performance in millimeter-scale tissues. Under the applied electric-field conditions, tissue samples undergo reversible cyclic deformation, which may contribute to antibody redistribution by transiently altering tissue geometry. Using ARDEI, 1000 μm-thick mouse brain sections were labeled within 2.5 h, with improved signal penetration and spatial uniformity compared with passive diffusion and unidirectional electric-field staining under time-matched conditions. The system operates at 40 V under temperature-controlled conditions, minimizing thermal and structural perturbation. ARDEI supports three-dimensional imaging of neuronal and glial structures and can be applied to SHANEL-pretreated human brain tissue, where improved labeling uniformity was observed in 1000 μm-thick sections within 4 h. Under the tested conditions, repeated deformation cycles did not produce detectable structural distortion or signal degradation. These results show that ARDEI improves thick-tissue immunostaining performance and are consistent with a contribution from coupled electric-field-assisted transport and reversible tissue deformation. ARDEI provides a practical approach that can be integrated with existing optical imaging workflows for volumetric tissue analysis.
