Vo Thi Nhat Linh (한국재료연구원) | 한빛사논문 > 한빛사

한빛사논문

조회550

한국재료연구원

CV File 181 kb

Biosens. Bioelectron., 2023 Mar 15;224:115076 | https://doi.org/10.1016/j.bios.2023.115076 3D plasmonic coral nanoarchitecture paper for label-free human urine sensing and deep learning-assisted cancer screening

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

^aDepartment of Nano-Bio Convergence, Korea Institute of Materials Science (KIMS), Changwon, Gyeongnam, 51508, South Korea
^bBiomedical Engineering Research Center, Samsung Medical Center, Seoul, 06351, South Korea
^cDepartment of Mechanical Engineering, Pohang University of Science and Technology, Pohang, 37673, South Korea
^dDivision of Hepatobiliary-Pancreatic Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, South Korea
^eDepartment of Biomedical Engineering, College of Medicine, Kyung Hee University, Seoul, 02447, South Korea
^fPOSCO-POSTECH-RIST Convergence Research Center for Flat Optics and Metaphotonics, Pohang, 37673, South Korea

Corresponding authors: Samjin Choi, Dong-Ho Kim, Junsuk Rho, Ho Sang Jung

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.

논문정보

형식Research article
게재일2023년 03월 (BRIC 등록일 2023-03-07)
연구진국내 연구진
분야 바이오·의료융합 > 바이오센싱 및 나노바이오물질

댓글 작성 로그인

CV 열람하기

연락처 보기