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定制贵金属纳米粒子设计以实现灵敏的侧向流动免疫分析。

Tailoring noble metal nanoparticle designs to enable sensitive lateral flow immunoassay.

机构信息

State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Nanchang University, Nanchang 330047, P. R. China.

Hypertension Research Institute of Jiangxi Province, Department of Cardiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, P. R. China.

出版信息

Theranostics. 2022 Jan 1;12(2):574-602. doi: 10.7150/thno.67184. eCollection 2022.

Abstract

Lateral flow immunoassay (LFIA) with gold nanoparticles (AuNPs) as signal reporters is a popular point-of-care diagnostic technique. However, given the weak absorbance of traditional 20-40 nm spherical AuNPs, their sensitivity is low, which greatly limits the wide application of AuNP-based LFIA. With the rapid advances in materials science and nanotechnology, the synthesis of noble metal nanoparticles (NMNPs) has enhanced physicochemical properties such as optical, plasmonic, catalytic, and multifunctional activity by simply engineering their physical parameters, including the size, shape, composition, and external structure. Using these engineered NMNPs as an alternative to traditional AuNPs, the sensitivity of LFIA has been significantly improved, thereby greatly expanding the working range and application scenarios of LFIA, particularly in trace analysis. Therefore, in this review, we will focus on the design of engineered NMNPs and their demonstration in improving LFIA. We highlight the strategies available for tailoring NMNP designs, the effect of NMNP engineering on their performance, and the working principle of each engineering design for enhancing LFIA. Finally, current challenges and future improvements in this field are briefly discussed.

摘要

基于金纳米粒子(AuNPs)作为信号报告物的侧向流动免疫分析(LFIA)是一种流行的即时诊断技术。然而,鉴于传统的 20-40nm 球形 AuNPs 吸收能力较弱,其灵敏度较低,这极大地限制了基于 AuNP 的 LFIA 的广泛应用。随着材料科学和纳米技术的快速发展,通过简单地设计其物理参数,包括尺寸、形状、组成和外部结构,合成贵金属纳米粒子(NMNPs)增强了其光学、等离子体、催化和多功能活性等物理化学性质。使用这些工程化的 NMNPs 替代传统的 AuNPs,可以显著提高 LFIA 的灵敏度,从而大大扩展 LFIA 的工作范围和应用场景,特别是在痕量分析中。因此,在这篇综述中,我们将重点介绍工程化 NMNPs 的设计及其在提高 LFIA 中的应用。我们强调了定制 NMNP 设计的策略、NMNP 工程对其性能的影响,以及每种工程设计增强 LFIA 的工作原理。最后,简要讨论了该领域当前的挑战和未来的改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d140/8692915/690b91175b5c/thnov12p0574g001.jpg

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