NDLI: Lateral Flow Immunoassay with Quantum-Dot-Embedded Silica Nanoparticles for Prostate-Specific Antigen Detection

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Lateral Flow Immunoassay with Quantum-Dot-Embedded Silica Nanoparticles for Prostate-Specific Antigen Detection

Content Provider	MDPI
Author	Bock, Sungje Kim, Hyung-Mo Kim, Jaehi An, Jaehyun Choi, Yun-Sik Pham, Xuan-Hung Jo, Ahla Ham, Kyeong-Min Song, Hobeom Kim, Jung-Won Hahm, Eunil Rho, Won-Yeop Lee, Sang Hun Park, Seung-Min Lee, Sangchul Jeong, Dae Hong Lee, Ho-Young Jun, Bong-Hyun
Copyright Year	2021
Description	Prostate cancer can be detected early by testing the presence of prostate-specific antigen (PSA) in the blood. Lateral flow immunoassay (LFIA) has been used because it is cost effective and easy to use and also has a rapid sample-to-answer process. Quantum dots (QDs) with very bright fluorescence have been previously used to improve the detection sensitivity of LFIAs. In the current study, a highly sensitive LFIA kit was devised using QD-embedded silica nanoparticles. In the present study, only a smartphone and a computer software program, ImageJ, were used, because the developed system had high sensitivity by using very bright nanoprobes. The limit of PSA detection of the developed LFIA system was 0.138 ng/mL. The area under the curve of this system was calculated as 0.852. The system did not show any false-negative result when 47 human serum samples were analyzed; it only detected PSA and did not detect alpha-fetoprotein and newborn calf serum in the samples. Additionally, fluorescence was maintained on the strip for 10 d after the test. With its high sensitivity and convenience, the devised LFIA kit can be used for the diagnosis of prostate cancer.
Starting Page	33
e-ISSN	20794991
DOI	10.3390/nano12010033
Journal	Nanomaterials
Issue Number	1
Volume Number	12
Language	English
Publisher	MDPI
Publisher Date	2021-12-23
Access Restriction	Open
Subject Keyword	Nanomaterials Prostate-specific Antigen Prostate Cancer Lateral Flow Immunoassay Quantum Dot Quantum-dot-embedded Silica Nanoparticles
Content Type	Text
Resource Type	Article

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