Del Mistro Greta, Cervo Silvia, Mansutti Elena, Spizzo Riccardo, Colombatti Alfonso, Belmonte Pietro, Zucconelli Renzo, Steffan Agostino, Sergo Valter, Bonifacio Alois
Department of Engineering and Architecture, University of Trieste, Via Valerio 6a, 34127, Trieste, TS, Italy.
Anal Bioanal Chem. 2015 May;407(12):3271-5. doi: 10.1007/s00216-015-8610-9. Epub 2015 Mar 20.
Surface-enhanced Raman scattering (SERS) spectra were obtained from urine samples from subjects diagnosed with prostate cancer as well as from healthy controls, using Au nanoparticles as substrates. Principal component analysis (PCA) of the spectral data, followed by linear discriminant analysis (LDA), leads to a classification model with a sensitivity of 100 %, a specificity of 89 %, and an overall diagnostic accuracy of 95 %. Even considering the very limited number of samples involved in this report, preliminary results from this approach are extremely promising, encouraging further investigation.
使用金纳米颗粒作为底物,从被诊断患有前列腺癌的受试者以及健康对照者的尿液样本中获取了表面增强拉曼散射(SERS)光谱。对光谱数据进行主成分分析(PCA),然后进行线性判别分析(LDA),得到了一个分类模型,其灵敏度为100%,特异性为89%,总体诊断准确率为95%。即使考虑到本报告中涉及的样本数量非常有限,这种方法的初步结果也极有前景,有望鼓励进一步的研究。