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Joo, Jinmyoung
Laboratory for Advanced Biomaterials and Translational Medicine
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Diagnosis in a Preclinical Model of Bladder Pain Syndrome Using a Au/ZnO Nanorod-based SERS Substrate

Author(s)
Lee, SanghwaNamgoong, Jung-ManYu, Hwan YeulJue, MiyeonKim, GwanhoJeon, SangminShin, Dong-MyungChoo, Myung-SooJoo, JinmyoungPack, Chan-GiKim, Jun Ki
Issued Date
2019-02
DOI
10.3390/nano9020224
URI
https://scholarworks.unist.ac.kr/handle/201301/30424
Fulltext
https://www.mdpi.com/2079-4991/9/2/224
Citation
NANOMATERIALS, v.9, no.2, pp.224
Abstract
To evaluate the feasibility of ZnO nanorod-based surface enhanced Raman scattering (SERS) diagnostics for disease models, particularly for interstitial cystitis/bladder pain syndrome (IC/BPS), ZnO-based SERS sensing chips were developed and applied to an animal disease model. ZnO nanorods were grown to form nano-sized porous structures and coated with gold to facilitate size-selective biomarker detection. Raman spectra were acquired on a surface enhanced Raman substrate from the urine in a rat model of IC/BPS and analyzed using a statistical analysis method called principal component analysis (PCA). The nanorods grown after the ZnO seed deposition were 30 to 50 nm in diameter and 500 to 600 nm in length. A volume of gold corresponding to a thin film thickness of 100 nm was deposited on the grown nanorod structure. Raman spectroscopic signals were measured in the scattered region for nanometer biomarker detection to indicate IC/BPS. The Raman peaks for the control group and IC/BPS group are observed at 641, 683, 723, 873, 1002, 1030, and 1355 cm(-1),which corresponded to various bonding types and compounds. The PCA results are plotted in 2D and 3D. The Raman signals and statistical analyses obtained from the nano-sized biomarkers of intractable inflammatory diseases demonstrate the possibility of an early diagnosis.
Publisher
MDPI
ISSN
2079-4991
Keyword (Author)
interstitial cystitis/bladder pain syndrome (IC/BPS)ZnO nanorodssurface enhancement Raman spectroscopy (SERS)principal component analysis (PCA)
Keyword
MICRO-RAMAN SPECTROSCOPYZNO NANORODSCYSTITISEXOSOMESGROWTHCANCER

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