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ORIGINAL RESEARCH article
Front. Bioeng. Biotechnol.
Sec. Nanobiotechnology
Volume 13 - 2025 | doi: 10.3389/fbioe.2025.1568719
This article is part of the Research Topic Dendritic Nanoparticles Synthesis and Application View all articles
Enhancing Lateral Flow Immunoassay Performance for Cardiac Troponin I Detection with Pore-Size Tailored Silica Nanoparticles and Smartphone-Based "AdaptiScan" Analysis
Provisionally accepted- 1 Institute of Energy Materials Science, University of Shanghai for Science and Technology, Shanghai, China
- 2 College of Information and Electrical Engineering, China Agricultural University, Beijing, Beijing, China
- 3 Department of Nephrology, Gongli Hospital of Shanghai Pudong New Area, Shanghai, China
- 4 State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences (CAS), Shanghai, Shanghai Municipality, China
The accurate and rapid detection of cardiac troponin I (cTnI) at the point of care is crucial for the timely diagnosis of myocardial infarction (MI). This study introduces an advanced lateral flow immunoassay (LFIA) platform for cTnI detection. We employed small-sized, large-pore dendritic mesoporous silica nanoparticles (DMSN-2) to encapsulate quantum dots (QDs), achieving an enhanced QD loading capacity of 1.427 g QD/g silica, compared to 0.881 g QD/g silica for smaller pore counterparts (DMSN-1). This nano-LFIA was further integrated with "AdaptiScan", a smartphone-based detection system that uses adaptive detection algorithms to automatically extract and analyze fluorescence signals from LFIA strips. This integration of pore-size tailored DMSNs and "AdaptiScan" resulted in a limit of detection (LoD) for cTnI of 42.6 ng/L, which meets clinical diagnostic requirements. The platform offers a sensitive, cost-effective, and portable solution for rapid detection of MI, potentially transforming point-of-care testing (POCT) in resource-limited settings.
Keywords: mesoporous, pore size, Quantum dots, Lateral flow immunoassay, smartphone-based analysis
Received: 30 Jan 2025; Accepted: 06 Mar 2025.
Copyright: © 2025 Ye, Xu, Li, Feng, Wang and Gao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yan Wang, College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, Beijing, China
Fang Gao, Institute of Energy Materials Science, University of Shanghai for Science and Technology, Shanghai, China
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