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Identification and analysis of serum samples by surface-enhanced Raman spectroscopy combined with characteristic ratio method and PCA for gastric cancer detection by Liu Guo; Yuanpeng Li; Furong Huang; Jia Dong; Fucui Li; Xinhao Yang; Siqi Zhu; Maoxun Yang is a Engineering article available to read on EtoBox.
What is Identification and analysis of serum samples by surface-enhanced Raman spectroscopy combined with characteristic ratio method and PCA for gastric cancer detection about?
This study aimed to explore the application of surface-enhanced Raman scattering (SERS) in the rapid diagnosis of gastric cancer. The SERS spectra of 68 serum samples from gastric cancer patients and healthy volunteers were acquired. The characteristic ratio method (CRM) and principal component analysis (PCA) were used to differentiate gastric cancer serum from normal serum. Compared with healthy volunteers, the serum SERS intensity of gastric cancer patients was relatively high at 722[Formula: see text]cm[Formula: see text], while it was relatively low at 588, 644, 861, 1008, 1235, 1397, 1445 and 1586[Formula: see text]cm[Formula: see text]. These results indicated that the relative content of nucleic acids in the serum of gastric cancer patients rises while the relative content of amino acids and carbohydrates decreases. In PCA, the sensitivity and specificity of discriminating gastric cancer were 94.1% and 94.1%, respectively, with the accuracy of 94.1%. Based on the intensity ratios of four characteristic peaks at 722, 861, 1008 and 1397[Formula: see text]cm[Formula: see text], CRM presented the diagnostic sensitivity and specificity of 100% and 97.4%, respectively, and the acc
Who reads Identification and analysis of serum samples by surface-enhanced Raman spectroscopy combined with characteristic ratio method and PCA for gastric cancer detection?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Liu Guo; Yuanpeng Li; Furong Huang; Jia Dong; Fucui Li; Xinhao Yang; Siqi Zhu; Maoxun Yang
- Publisher
- World Scientific ; World Scientific Publishing Co; World Scientific Pub Co Pte Lt (ISSN 1793-5458)
- Published
- 2019
- Language
- EN
- Field
- Engineering (Physical Sciences)