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Raman spectroscopy combined with multivariate analysis techniques as a potential tool for semen investigation

机译:拉曼光谱结合多元分析技术作为精液研究的潜在工具

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Molecular characterization of semen that can be used to provide an objective diagnosis of semen quality is still lacking. Raman spectroscopy measures vibrational modes of molecules, thus can be utilized to characterize biological fluids. Here, we employed Raman spectroscopy to characterize and compare normal and abnormal semen samples in the fingerprint region (400-1800cm~(-1)). Multivariate analysis methods including principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were used for spectral analysis to differentiate between normal and abnormal semen samples. Compared with PCA-LDA analysis, PLS-DA improved the diagnostic results, showing a sensitivity of 77% and specificity of 73%. Furthermore, our preliminary quantitative analysis based on PLS algorithm demonstrated that spermatozoa concentration were relatively well predicted (R~2=0.825). In conclusion, this study demonstrated that micro-Raman spectroscopy combined with multivariate methods can provide as a new diagnostic technique for semen analysis and differentiation between normal and abnormal semen samples.
机译:仍然缺乏可用于提供精液质量客观诊断的精液分子表征。拉曼光谱法测量分子的振动模式,因此可用于表征生物流体。在这里,我们使用拉曼光谱法来表征和比较指纹区域(400-1800cm〜(-1))中正常和异常精液样本。多元分析方法包括主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)用于光谱分析,以区分正常精液样本和异常精液样本。与PCA-LDA分析相比,PLS-DA改善了诊断结果,灵敏度为77%,特异性为73%。此外,我们基于PLS算法的初步定量分析表明,精子浓度相对较好地预测(R〜2 = 0.825)。总之,这项研究表明,显微拉曼光谱技术与多变量方法相结合可以为精液分析和区分正常和异常精液样本提供一种新的诊断技术。

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