Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania; Faculty of Physics, Babeş-Bolyai University, Cluj-Napoca, Romania.
Nanomedicine. 2019 Aug;20:102012. doi: 10.1016/j.nano.2019.04.015. Epub 2019 May 11.
In this preliminary study on synovial fluid (SF), knee osteoarthritis (OA) grading of n = 23 patients was accomplished by combining two methods: resonant Raman spectroscopy, and surface-enhanced Raman scattering (SERS) of native proteins acquired with iodide-modified silver nanoparticles and a laser emitting at 633 nm. Based on principal component analysis-linear discriminant analysis (PCA-LDA), the SERS spectra of proteins enabled the classification of low-grade and high-grade OA groups with an accuracy of 91%. Resonant Raman spectra of SF, recorded with laser excitation at 532 nm, exhibited carotenoid-associated bands that were less intense in the case of high-grade knee OA patients. Based on the resonant Raman spectra, the grading of OA patients was accomplished with an accuracy of 74%. Concatenating SERS and Raman spectral information increased the classification accuracy between the two groups to 100%. These results demonstrate the potential of Raman and SERS as a point-of-care method for aiding OA grading.
在这项关于滑液（SF）的初步研究中，通过结合两种方法对 23 名患者的膝关节骨关节炎（OA）进行分级：共振拉曼光谱法和利用碘化物修饰的银纳米粒子和发射波长为 633nm 的激光获得的天然蛋白质的表面增强拉曼散射（SERS）。基于主成分分析-线性判别分析（PCA-LDA），蛋白质的 SERS 光谱能够以 91%的准确率对低级别和高级别 OA 组进行分类。用 532nm 激光激发 SF 的共振拉曼光谱显示，在高级别膝 OA 患者中，类胡萝卜素相关带的强度较低。基于共振拉曼光谱，OA 患者的分级准确率达到 74%。串联 SERS 和 Raman 光谱信息将两组之间的分类准确率提高到 100%。这些结果表明 Raman 和 SERS 作为一种辅助 OA 分级的即时护理方法具有潜力。
