Issue 9, 2025

Dual lateral flow assay using quantum nanobeads for quantitative detection of BDNF and TNF-α in tears

Abstract

Glaucoma is a group of neurodegenerative eye diseases characterized by progressive damage to the optic nerve which is typically asymptomatic until irreversible vision loss has occurred. Early screening is essential for timely treatment to prevent visual impairment. However, existing detection methods struggle to achieve a balance between accuracy, time efficiency, and portability. The lateral flow assay (LFA) is a well-established immunoanalytical tool for point-of-care (POC) analysis. Here, we have developed a unique dual-testing, quantum nanobeads-based fluorescence LFA, allowing for the simultaneous and quantitative detection of two glaucoma biomarkers: tumor necrosis factor-α (TNF-α) and brain-derived neurotrophic factor (BDNF). By coating quantum dots on the surface of a SiO2 core, the fluorescent intensity of the quantum nanobeads was enhanced enabling an accurate, efficient, and high-throughput bioanalytical performance, with low detection limits of 3.39 pg mL−1 for TNF-α and 4.13 pg mL−1 for BDNF. The LFA also demonstrated superior selectivity, reproducibility, and stability to the standard enzyme-linked immunosorbent assay (ELISA). Using a 3D-printed readout box, the analysis of the LFA requires only a readily accessible smartphone and image processing software, making it an ideal POC detection tool. This ultrasensitive, economical, and user-friendly LFA demonstrates significant potential as an alternative for glaucoma screening.

Graphical abstract: Dual lateral flow assay using quantum nanobeads for quantitative detection of BDNF and TNF-α in tears

Supplementary files

Article information

Article type
Paper
Submitted
09 Dec 2024
Accepted
02 Apr 2025
First published
15 Apr 2025
This article is Open Access
Creative Commons BY license

Lab Chip, 2025,25, 2291-2303

Dual lateral flow assay using quantum nanobeads for quantitative detection of BDNF and TNF-α in tears

Y. Wu, Y. Hu, N. Jiang, M. W. Georgi, A. K. Yetisen and M. F. Cordeiro, Lab Chip, 2025, 25, 2291 DOI: 10.1039/D4LC01045K

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