Near-Infrared Long-Lived Luminescent Nanoparticle-Based Time-Gated Imaging for Background-Free Detection of Avian Influenza Virus

IF 9.1 1区 化学 Q1 CHEMISTRY, ANALYTICAL ACS Sensors Pub Date : 2025-02-15 DOI:10.1021/acssensors.4c03202
Jiwoo Han, Suyeon Kim, Dongkyu Kang, Sun-Hak Lee, Andrew Y. Cho, Heesu Lee, Jung-Hoon Kwon, Yong Shin, Young-Pil Kim, Joonseok Lee
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Abstract

Near-infrared (NIR)-to-NIR upconversion nanoparticles (UCNPs) are promising materials for biomedical imaging and sensing applications. However, UCNPs with long lifetimes continue to face the limitation that they are usually accompanied by weak luminescence intensity, resulting in difficulties in achieving high-resolution and sensitive time-gated imaging. To overcome this limitation, we have developed NIR long-lifetime luminescent nanoparticles (NLL NPs) with strong 800 nm emission by adding a photosensitizing shell and with a prolonged lifetime by lowering the activator concentration. NLL NP-based time-gated imaging overcomes the inherent limitations of steady-state imaging by providing higher signal-to-noise ratios and more robust signal intensities. When integrated into a lateral flow immunoassay (LFA) for the detection of avian influenza viruses, NLL NP-based time-gated imaging demonstrates a 32-fold lower limit of detection compared to conventional optimal 800 nm emitting nanoparticles. Furthermore, the high accuracy of the NLL NP-based LFA is confirmed through clinical validations using 65 samples, achieving a sensitivity and specificity of 100% and an area under the curve of 1.000. These results demonstrate the potential of NLL NP-based time-gated imaging as a powerful tool for the highly sensitive and accurate detection of avian influenza viruses in complex clinical samples.

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基于近红外长寿命发光纳米粒子的时间门控成像无背景检测禽流感病毒
近红外(NIR)到近红外(NIR)上转换纳米粒子(UCNPs)是生物医学成像和传感应用的有前途的材料。然而,长寿命的UCNPs仍然面临着通常伴随弱发光强度的限制,导致难以实现高分辨率和灵敏的时间门控成像。为了克服这一限制,我们通过添加光敏壳开发了具有800 nm强发射的近红外长寿命发光纳米粒子(NLL NPs),并通过降低活化剂浓度延长了寿命。基于NLL np的时门控成像通过提供更高的信噪比和更强的信号强度,克服了稳态成像的固有局限性。当整合到用于检测禽流感病毒的横向流动免疫分析(LFA)中时,基于NLL np的时间门控成像显示,与传统的最佳800 nm发射纳米颗粒相比,检测下限为32倍。此外,通过65个样本的临床验证,证实了基于NLL np的LFA具有较高的准确性,灵敏度和特异性为100%,曲线下面积为1.000。这些结果表明,基于NLL np的时间门控成像技术有潜力成为在复杂临床样本中高度敏感和准确检测禽流感病毒的有力工具。
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来源期刊
ACS Sensors
ACS Sensors Chemical Engineering-Bioengineering
CiteScore
14.50
自引率
3.40%
发文量
372
期刊介绍: ACS Sensors is a peer-reviewed research journal that focuses on the dissemination of new and original knowledge in the field of sensor science, particularly those that selectively sense chemical or biological species or processes. The journal covers a broad range of topics, including but not limited to biosensors, chemical sensors, gas sensors, intracellular sensors, single molecule sensors, cell chips, and microfluidic devices. It aims to publish articles that address conceptual advances in sensing technology applicable to various types of analytes or application papers that report on the use of existing sensing concepts in new ways or for new analytes.
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