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Updated: Jan 25, 2026

Author Spotlight: High-Quality Quantum Dot Nanobeads for Sensitive Fluorescent Lateral Flow Immunoassays
Published on: June 28, 2024
Light-addressable sandwich photoelectrochemical immunosensor array and lateral flow immunoassays with
Louqun Wang1, Jingge Niu1, Xiaoli Chen1
1School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning Province, 110016, PR China.
Abstract:
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid-beta (Aβ) plaques, making Aβ a crucial biomarker for early diagnosis. In this study, we developed a novel light-addressable sandwich photoelectrochemical (PEC) immunosensor array for the detection of Aβ42, aiming to enhance diagnostic methods for AD. The array utilized cadmium telluride quantum dot-sensitized UiO-66 (U@C) as the sensing matrix and PCN-224@ZnIn2S4 nanoflower heterojunctions (P@Z) as immunoprobes, enabling multiplexed detection through laser pen activation on a single FTO electrode with a self-calibration method to minimize background noise and baseline drift. The assay required 60 min for incubation steps before detection; however, with 11 simultaneous detection points, it significantly reduced batch processing time and enhanced practicality. For point-of-care applications, we also developed a PEC-lateral flow immunoassay (PEC-LFIA) test strip that allowed for real-time, quantitative detection of Aβ42 with only 15 min of incubation required for testing. Both platforms effectively detected Aβ42 in PBS, artificial cerebrospinal fluid (CSF), and human plasma at concentrations ranging from fg/mL to ng/mL. Notably, sensitivity in human plasma was five times greater than that in artificial CSF. The PEC array achieved detection limits of 19.5 fg/mL in CSF and 3.1 fg/mL in plasma, while the PEC-LFIA strip demonstrated limits of 17.8 fg/mL in CSF and 3.1 fg/mL in human plasma. These advancements significantly reduced patient burden and brought us closer to utilizing a single drop of blood for monitoring brain aging.
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