College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shaanxi, China.
Shaanxi Institute for Food and Drug Control, Xi'an 710065, Shaanxi, China.
Food Chem. 2021 Jun 15;347:129001. doi: 10.1016/j.foodchem.2021.129001. Epub 2021 Jan 11.
Conventional gold nanoparticles-based lateral flow immunoassays (AuNPs-LFIA) lack sensitivity. In this work, we developed a graphite-like carbon nitride-laden AuNPs (g-CN@Au) assisted LFIA to improve sensitivity for 17β-estradiol (E2) in foods. g-CN nanosheets were applied as carriers, because of their excellent chemical stability, large surface areas and low-cost, loading large numbers of AuNPs to amplify signals and improve the overall response of g-CN@Au-based LFIA (g-CN@Au-LFIA). The lowest visual limit of detection (vLOD) of E2 is 0.5 ng mL for g-CN@Au-LFIA, which exhibit a significantly three-fold improved analytical performance compared with that of AuNPs-LFIA. Additionally, this method was successfully used to the detection of E2 in four spiked food samples, offering a great potential of the g-CN@Au based LFIA for its application in food products.
基于传统金纳米颗粒的侧向流动免疫分析（AuNPs-LFIA）缺乏灵敏度。在这项工作中，我们开发了一种负载石墨相氮化碳的金纳米颗粒（g-CN@Au）辅助 LFIA，以提高食品中 17β-雌二醇（E2）的灵敏度。g-CN 纳米片因其优异的化学稳定性、大的比表面积和低成本而被用作载体，负载大量的 AuNPs 来放大信号，提高基于 g-CN@Au 的 LFIA（g-CN@Au-LFIA）的整体响应。g-CN@Au-LFIA 对 E2 的最低视觉检测限（vLOD）为 0.5ng mL，与 AuNPs-LFIA 相比，分析性能显著提高了三倍。此外，该方法成功用于四种加标食品样品中 E2 的检测，为 g-CN@Au 基于 LFIA 在食品中的应用提供了很大的潜力。
