Stretchable Porous Membranes for Barrier Tissue Models with Electronic Real-time Measurement and Biomimetic Cyclic Strain

Published

November 13, 2025

Author(s)

Alexander Guttenplan, Darwin Reyes-Hernandez

Abstract

In recent years, microphysiological systems- microfabricated models of a functional organ or tissue- have been developed to study a variety of biological processes in vitro in a microenvironment that replicates the in vivo microenvironment more faithfully than a culture dish. In particular, models of barrier tissues, consisting of two compartments separated by a porous membrane, have been used to investigate the passage of drugs, toxins and cancer cells through these tissues and to measure their integrity. Some of these models include an elastomeric membrane which can be stretched to model processes such as breathing and gut peristalsis, or electrodes for real-time measurement of barrier tissue integrity. However, to date no system has been fabricated which includes microelectrodes on a porous elastomeric membrane. Here, we lithographically pattern gold electrodes on porous PDMS membranes, to enable electronic sensing capabilities in addition to mechanical manipulation. These membranes are incorporated into vacuum-actuated devices which impart cyclic mechanical strain, and are demonstrated to be usable for electrical impedance measurements even after 1000 stretching cycles. In future, these electrodes could be used both for dielectrophoretic trapping of cells in a region of interest for more rapid assembly of a model tissue, and for measurement of changes in barrier tissue function in real time.

Citation

Micromachines

Volume

16

Issue

11

Pub Type

Journals

Download Paper

https://doi.org/10.3390/mi16111282

Local Download

Keywords

Microphysiological systems, stretchable porous membranes, impedance measurements

Citation

Guttenplan, A. and Reyes-Hernandez, D. (2025), Stretchable Porous Membranes for Barrier Tissue Models with Electronic Real-time Measurement and Biomimetic Cyclic Strain, Micromachines, [online], https://doi.org/10.3390/mi16111282, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=960114 (Accessed January 9, 2026)