Li Yuanpeng, Guo Liu, Li Li, Yang Chuanmei, Guang Peiwen, Huang Furong, Chen Zhenqiang, Wang Lihu, Hu Junhui
College of Physical Science and Technology, Guangxi Normal University, Guilin, China.
Guangxi Key Laboratory Nuclear Physics and Technology, Guangxi Normal University, Guilin, China.
Front Chem. 2020 Dec 7;8:580489. doi: 10.3389/fchem.2020.580489. eCollection 2020.
Early diagnosis is important to reduce the incidence and mortality rate of diabetes. The feasibility of early diagnosis of diabetes was studied via near-infrared spectra (NIRS) combined with a support vector machine (SVM) and aquaphotomics. Firstly, the NIRS of entire blood samples from the population of healthy, pre-diabetic, and diabetic patients were obtained. The spectral data of the entire spectra in the visible and near-infrared region (400-2,500 nm) were used as the research object of the qualitative analysis. Secondly, several preprocessing steps including multiple scattering correction, variable standardization, and first derivative and second derivative steps were performed and the best pretreatment method was selected. Finally, for the early diagnosis of diabetes, models were established using SVM. The first overtone of water (1,300-1,600 nm) was used as the research object for an aquaphotomics model, and the aquagram of the healthy group, pre-diabetes, and diabetes groups were drawn using 12 water absorption patterns for the early diagnosis of diabetes. The results of SVM showed that the highest accuracy was 97.22% and the specificity and sensitivity were 95.65 and 100%, respectively when the pretreatment method of the first derivative was used, and the best model parameters were c = 18.76 and g = 0.008583.The results of the aquaphotomics model showed clear differences in the 1,400-1,500 nm region, and the number of hydrogen bonds in water species (1,408, 1,416, 1,462, and 1,522 nm) was evidently correlated with the occurrence and development of diabetes. The number of hydrogen bonds was the smallest in the healthy group and the largest in the diabetes group. The suggested reason is that the water matrix of blood changes with the worsening of blood glucose metabolic dysfunction. The number of hydrogen bonds could be used as biomarkers for the early diagnosis of diabetes. The result show that it is effective and feasible to establish an accurate and rapid early diagnosis model of diabetes via NIRS combined with SVM and aquaphotomics.
早期诊断对于降低糖尿病的发病率和死亡率至关重要。通过近红外光谱（NIRS）结合支持向量机（SVM）和水相光代谢组学研究了糖尿病早期诊断的可行性。首先，获取了健康人群、糖尿病前期患者和糖尿病患者全血样本的近红外光谱。将可见和近红外区域（400 - 2500 nm）内全光谱的光谱数据用作定性分析的研究对象。其次，进行了包括多重散射校正、变量标准化以及一阶导数和二阶导数步骤等多个预处理步骤，并选择了最佳预处理方法。最后，为实现糖尿病的早期诊断，使用支持向量机建立模型。将水的第一泛音（1300 - 1600 nm）用作水相光代谢组学模型的研究对象，并利用12种吸水模式绘制了健康组、糖尿病前期组和糖尿病组的水相图，用于糖尿病的早期诊断。支持向量机的结果表明，当使用一阶导数预处理方法时，最高准确率为97.22%，特异性和敏感性分别为95.65和100%，最佳模型参数为c = 18.76和g = 0.008583。水相光代谢组学模型的结果显示在1400 - 1500 nm区域存在明显差异，水物种中的氢键数量（1408、1416、1462和1522 nm）与糖尿病的发生和发展明显相关。氢键数量在健康组中最少，在糖尿病组中最多。推测原因是血液的水基质随着血糖代谢功能障碍的加重而发生变化。氢键数量可作为糖尿病早期诊断的生物标志物。结果表明，通过近红外光谱结合支持向量机和水相光代谢组学建立准确、快速的糖尿病早期诊断模型是有效且可行的。
