Bratchenko Ivan, Bratchenko Lyudmila
Laser and Biotechnical Systems Department, Samara National Research University, Moskovskoe Shosse 34, 443086 Samara, Russia.
Int J Mol Sci. 2024 Dec 4;25(23):13030. doi: 10.3390/ijms252313030.
This comment discusses a recent research paper on the classification of saliva samples with SERS by Borsa et al. The authors suggested utilizing PCA-LDA to detect oral cancer and claimed to achieve an accuracy of up to 77%. Despite the high prediction capability of the proposed approach, the demonstrated findings could be treated as unclear due to possible overestimation of the proposed classification models. Data should be provided for both the training and the validation sets to make sure that there were no repeated data from the same sample in either set. Moreover, the authors proposed to measure opiorphin in saliva with SERS as a potential biomarker of oral cancer. However, opiorphin in saliva is contained in ng/mL concentrations, and the proposed technique is most likely not capable of recording the real concentration of opiorphin.
本评论讨论了博尔萨等人最近发表的一篇关于用表面增强拉曼光谱法（SERS）对唾液样本进行分类的研究论文。作者建议利用主成分分析-线性判别分析（PCA-LDA）来检测口腔癌，并声称准确率高达77%。尽管所提出的方法具有较高的预测能力，但由于所提出的分类模型可能存在高估，所展示的结果可能被视为不明确。应提供训练集和验证集的数据，以确保两组中都没有来自同一样本的重复数据。此外，作者建议用SERS测量唾液中的阿片样物质增强因子作为口腔癌的潜在生物标志物。然而，唾液中的阿片样物质增强因子浓度为纳克/毫升，所提出的技术很可能无法记录阿片样物质增强因子的实际浓度。
