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目的:建立中药指纹图谱按特征成分簇定量的方法。方法:运用总量统计矩原理及中药特征成分簇特性与朗伯-比尔定律的关系,建立了中药特征成分簇与浓度的线性回归方程,并以大黄为模型药物,采用HPLC法,系统的适应性条件:色谱柱为Alltech Apollo C18柱(250 mm×4.6 mm,5μm);流动相:乙腈-1%醋酸水溶液由5∶95变为95∶5梯度洗脱;流速:1.0 mL/min;温度:40℃;检测波长:254 nm。结果:根据中药特征成分簇特性,大黄指纹图谱可以划分为14个特征成分簇,其谱量学线性回归方程为:CT=10.543-2.13×10-7AUCT1-4.16×10-7AUCT2-8.06×10-7AUCT3-4.98×10-6AUCT4+1.30×10-6AUCT5+3.10×10-9AUCT6+1.91×10-6AUCT7-3.08×10-7AUCT8+3.98×10-6AUCT9+9.77×10-7AUCT10+5.57×10-6AUCT11-3.00×10-6AUCT12+4.51×10-6AUCT13+6.98×10-6AUCT14(R2=1.000)。结论:中药指纹图谱可按特征成分簇分段,建立的线性回归方程可用于中药定量分析,构建中药谱量学数学模型。
Objective: To establish a method for quantification of fingerprints of traditional Chinese medicines by characteristic clusters. Methods: Using the principle of total statistical moments and the relationship between the characteristic clusters of traditional Chinese medicines and Lambert-Beer’s law, a linear regression equation was established for clusters and concentrations of traditional Chinese medicines. Rhubarb was used as a model drug, and HPLC was used to adapt the system. Conditions: Alltech Apollo C18 column (250 mm×4.6 mm, 5 μm); mobile phase: acetonitrile-1% aqueous acetic acid gradient from 5:95 to 95:5 gradient; flow rate: 1.0 mL/min; temperature : 40°C; detection wavelength: 254 nm. Results: According to the cluster characteristics of traditional Chinese medicine, rhubarb fingerprints can be divided into 14 clusters of features. The spectral regression equation is: CT=10.543-2.13×10-7AUCT1-4.16×10-7AUCT2-8.06×10- 7AUCT3-4.98*10-6AUCT4+1.30*10-6AUCT5+3.10*10-9AUCT6+1.91*10-6AUCT7-3.08*10-7AUCT8+3.98*10-6AUCT9+9.77*10-7AUCT10+5.57*10-6AUCT11- 3.00 x 10-6 AUCT12 + 4.51 x 10-6 AUCT13 + 6.98 x 10-6 AUCT14 (R2 = 1.000). Conclusion: The TCM fingerprints can be segmented by clusters of characteristic components. The established linear regression equations can be used for the quantitative analysis of traditional Chinese medicines and construct the mathematics model of Chinese herbal spectrums.