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用于无标记人体尿液传感及深度学习辅助癌症筛查的3D等离子体珊瑚纳米结构纸

3D plasmonic coral nanoarchitecture paper for label-free human urine sensing and deep learning-assisted cancer screening.

作者信息

Linh Vo Thi Nhat, Lee Min-Young, Mun Jungho, Kim Yeseul, Kim Hongyoon, Han In Woong, Park Sung-Gyu, Choi Samjin, Kim Dong-Ho, Rho Junsuk, Jung Ho Sang

机构信息

Department of Nano-Bio Convergence, Korea Institute of Materials Science (KIMS), Changwon, Gyeongnam, 51508, South Korea.

Department of Nano-Bio Convergence, Korea Institute of Materials Science (KIMS), Changwon, Gyeongnam, 51508, South Korea; Biomedical Engineering Research Center, Samsung Medical Center, Seoul, 06351, South Korea.

出版信息

Biosens Bioelectron. 2023 Mar 15;224:115076. doi: 10.1016/j.bios.2023.115076. Epub 2023 Jan 9.

Abstract

Practical human biofluid sensing requires a sensor device to differentiate patients from the normal group with high sensitivity and specificity. Label-free molecular identification from human biofluids allows direct classification of abnormal samples, providing insights for disease diagnosis and finding of new biomarkers. Here, we introduce a label-free surface-enhanced Raman scattering sensor based on a three-dimensional plasmonic coral nanoarchitecture (3D-PCN), which has strong electromagnetic field enhancement through multiple hot spots. The 3D-PCN was synthesized on a paper substrate via direct one-step gold reduction, forming a coral-like nanoarchitecture with high absorption property for biofluids. This was fabricated as a urine test strip and then integrated with a handheld Raman system to develop an on-site urine diagnostic platform. The developed platform successfully classified the human prostate and pancreatic cancer urines in a label-free method supported by two types of deep learning networks, with high clinical sensitivity and specificity. Our technology has the potential to be utilized not only for urinary cancer diagnosis but also for various human biofluid sensing systems as a future point-of-care testing platform.

摘要

实际的人体生物流体传感需要一种传感器设备,能够以高灵敏度和特异性将患者与正常组区分开来。从人体生物流体中进行无标记分子识别可以直接对异常样本进行分类,为疾病诊断和发现新的生物标志物提供见解。在此,我们介绍一种基于三维等离子体珊瑚纳米结构(3D-PCN)的无标记表面增强拉曼散射传感器,该结构通过多个热点具有强大的电磁场增强作用。通过直接一步还原金在纸质基底上合成了3D-PCN,形成了对生物流体具有高吸收特性的珊瑚状纳米结构。将其制作成尿液试纸条,然后与手持式拉曼系统集成,开发出一种现场尿液诊断平台。所开发的平台在两种深度学习网络支持的无标记方法中成功地对人类前列腺癌和胰腺癌尿液进行了分类,具有高临床灵敏度和特异性。我们的技术不仅有潜力用于泌尿系统癌症诊断,还可作为未来的即时检测平台用于各种人体生物流体传感系统。

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