Label‐free optical detection of type II diabetes based on surface‐enhanced Raman spectroscopy and multivariate analysis. (25th August 2014) - Lin, Jinyong; Huang, Zufang; Feng, Shangyuan; Lin, Juqiang; Liu, Nenrong; Wang, Jing; Li, Ling; Zeng, Yongyi; Li, Buhong; Zeng, Haishan; Chen, Rong
<x xml:space="preserve">Abstract</x> Surface‐enhanced Raman scattering (SERS) spectroscopy was first employed to detect oxyhemoglobin (OxyHb, the common type of hemoglobin) variation in type II diabetic development without using exogenous reagents. Using silver nanoparticles as SERS‐active substrate, high‐quality SERS spectra are obtained from blood OxyHb samples of 49 diabetic patients and 40 healthy volunteers. Tentative assignment of the observed SERS bands indicates specific structural changes of OxyHb molecule in diabetes, including heme transformation and globin variation. Furthermore, partial least squares and principal component analysis combined with linear discriminate analysis diagnostic algorithms are employed to analyze and classify the SERS spectra acquired from diabetic and healthy OxyHb, yielding the diagnostic accuracies of 90.0% and 95.5%, respectively. This exploratory work suggests that the silver nanoparticles‐based OxyHb SERS method in combination with multivariate statistical analysis has great potential for the label‐free detection of type II diabetes. Copyright © 2014 John Wiley & Sons, Ltd.