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Microfluidic Paper-Based Device for Medicinal Diagnosis

微流控 检测点注意事项 计算机科学 纳米技术 制作 材料科学 医学 替代医学 病理 免疫学
作者
Atchara Lomae,Pattarachaya Preechakasedkit,Kanyapat Teekayupak,Yosita Panraksa,Jutiporn Yukird,Orawon Chailapakul,Nipapan Ruecha
出处
期刊:Current Topics in Medicinal Chemistry [Bentham Science]
卷期号:22 (27): 2282-2313 被引量:1
标识
DOI:10.2174/1568026623666221103103211
摘要

The demand for point-of-care testing (POCT) devices has rapidly grown since they offer immediate test results with ease of use, makingthem suitable for home self-testing patients and caretakers. However, the POCT development has faced the challenges of increased cost and limited resources. Therefore, the paper substrate as a low-cost material has been employed to develop a cost-effective POCT device, known as "Microfluidic paper-based analytical devices (μPADs)". This device is gaining attention as a promising tool for medicinal diagnostic applications owing to its unique features of simple fabrication, low cost, enabling manipulation flow (capillarydriven flow), the ability to store reagents, and accommodating multistep assay requirements.This review comprehensively examines the fabrication methods and device designs (2D/3D configuration) and their advantages and disadvantages, focusing on updated μPADs applications for motif identification.The evolution of paper-based devices, starting from the traditional devices of dipstick and lateral flow assay (LFA) with μPADs, has been described. Patterned structure fabrication of each technique has been compared among the equipment used, benefits, and drawbacks. Microfluidic device designs, including 2D and 3D configurations, have been introduced as well as their modifications. Various designs of μPADs have been integrated with many powerful detection methods such as colorimetry, electrochemistry, fluorescence, chemiluminescence, electrochemiluminescence, and SER-based sensors for medicinal diagnosis applications.The μPADs potential to deal with commercialization in terms of the state-of-the-art of μPADs in medicinal diagnosis has been discussed. A great prototype, which is currently in a reallife application breakthrough, has been updated.

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