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    Severe periodontitis affects nearly 1 billion individuals worldwide, highlighting the need for early diagnosis. Here, an integrated system consisting of a microfluidic chip and a portable point-of-care (POC) diagnostic device is developed using a polymethyl methacrylate (PMMA) chip fabrication and a three-dimensional printing technique, which is automatically controlled by a custom-designed smartphone application to routinely assess the presence of a specific periodontitis biomarker, odontogenic ameloblast-associated protein (ODAM). A sandwich-type fluorescence aptasensor is developed on a microfluidic chip, utilizing aptamer pair (MB@OD64 and OD35@FAM) selectively binding to target ODAM. Then this microfluidic chip is integrated into an automated Internet of Things (IoT)-based POC device, where fluorescence intensity, as a signal, from the secondary aptamer binding to ODAM in a sandwich-type binding reaction on the microfluidic chip is measured by a complementary metal oxide semiconductor (CMOS) camera with a 488 nm light-emitting diode (LED) excitation source. Obtained signals are processed by a microprocessor and visualized on a wirelessly connected smartphone application. This integrated biosensor system allows the rapid and accurate detection of ODAM within 30 min with a remarkable limit of detection (LOD) of 0.011 nM under buffer conditions. Clinical application is demonstrated by successfully distinguishing between low-risk and high-risk individuals with 100 % specificity. A strong potential in the translation of this fluorescence-based microfluidic aptasensor integrated with an IoT-based POC system is expected to be employed for non-invasive, on-site, rapid, and accurate ODAM detection, facilitating periodontitis diagnosis. Copyright © 2024 Elsevier B.V. All rights reserved.

    Citation

    Thi Thanh-Qui Nguyen, Eun-Mi Lee, Thi Thanh-Thao Dang, Eun Ryung Kim, Youngkyung Ko, Man Bock Gu. An IoT-based aptasensor biochip for the diagnosis of periodontal disease. Biosensors & bioelectronics. 2024 May 01;251:116097

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    PMID: 38330774

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