Microfluidic platform for rapid passive preparation of complex biological matrices in point-of-care testing.

Authors

Deniz Sadighbayan, Alireza Norouziazad, Fatemeh Rahimi, Jean-Paul Paluzzi, Razieh Salahandish

Published in

Scientific reports. Volume 16. Pages 34428. Epub Jul 28, 2026.

Abstract

Efficient whole blood processing at the point-of-care (POC) remains challenging due to interference from cellular components, risk of hemolysis, as well as reliance on external equipment and skilled operators. Here, we present a passive, low-cost microfluidic platform for rapid separation of cellular components from diluted samples of whole blood without the need for external pumps. The device features a circular maze-shaped microchannel incorporating 18 sequential wells, enabling effective cell retention through purely passive hydrodynamic mechanisms. Fabricated from hydrophilic polymer sheets and pressure-sensitive adhesive (PSA) layers, the platform is scalable, disposable, and enables very low-cost production (< $1 per unit). The blood-separation performance of the standalone microfluidic chip was validated using HEK-293 and AtT-20 cell suspensions, mixed cell suspensions, and diluted human blood. Efficient retention of cellular components in the early wells generated a cell-free filtrate suitable for downstream analytical applications. Building on this validated separation capability, the platform was integrated with a lateral flow immunoassay (LFIA) module as a proof-of-concept in a POC application by testing for hepatitis B surface antigen (HBsAg). The integrated system enabled detection of HBsAg at concentrations as low as 10 ng/mL within 10 min. In addition, deep learning-assisted convolutional neural networks were employed for automated assessment of filtration efficiency and test-line intensity. Overall, this work demonstrates a robust and accessible microfluidic sample-preparation platform with potential for decentralized diagnostic applications, particularly critical for resource-limited settings.

PMID:
43019135
Bibliographic data and abstract were imported from PubMed on 13 Nov 2026.

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