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[摘要]
目的 采用UPLC-Q-TOF-MSE技术建立注射用益气复脉(冻干)(YQFM)的指纹图谱,为直观、简便、全面地评价其质量提供依据。方法 采用Waters Acquity UPLC HSS T3(100 mm×2.1 mm,1.8 μm)色谱柱,以乙腈-0.1%甲酸水体系梯度洗脱,体积流量0.3 mL/min,柱温30℃,进样量5μL;质谱检测采用负离子ESI模式,电压2.5 kV,离子源温度100℃,雾化气温度400℃,雾化气流量800 L/h。选择基峰离子流色谱图(BPC)进行指纹图谱研究,并计算相似度。同时将指纹图谱共有峰的数据以预处理后的离子响应强度为变量,导入SPSS 19.0软件,进行聚类分析(HCA)和主成分分析(PCA),并由分析软件Simca-P 12.0作图。结果 首次建立了YQFM的UPLC-Q-TOF-MSE指纹图谱,并确定了18个共有峰,其中15个来自红参,3个来自麦冬;根据对照品和参考文献定性指认了其中16个色谱峰;28批YQFM的相似度均在0.970以上。聚类分析结果为当欧氏距离平方和为5~10时,28批YQFM样品可以聚为4类;主成分降维提取了7个主成分,反映了原变量84.989%的信息,通过拟合归纳第1主成分的载荷因子模型,筛选出对样品质量影响较大的10种标记物。结合主成分得分构建了不同批次YQFM综合评价函数:Y=0.420 3 PC1+0.133 8 PC2+0.084 2 PC3+0.064 4 PC4+0.061 1 PC5+0.046 1 PC6+0.040 0 PC7,并对各批次综合得分进行了排序,28批供试样品中,S28综合得分最高,其次为S22、S11和S9,S14和S13的综合得分最低。结论 UPLC-Q-TOF-MSE指纹图谱结合化学模式识别可以对YQFM的质量进行客观、有效地评价,为其质量控制提供科学依据。
[Key word]
[Abstract]
Objective To establish a UPLC-Q-TOF-MSE fingerprint of Yiqi Fumai Injection (YQFM) for providing reference for visual, easy and overall control of its quality.Methods The chromatographic separation was performed on a Waters Acquity UPLC HSS T3 (100 mm×2.1 mm, 1.8 μm) column with the mobile phase consisting of acetonitrile and 0.1% formic acid for gradient elution. The flow rate was 0.3 mL/min, and the column temperature was 30℃. The capillary voltage was set at 2.5 kV. The nebulization gas was set to 800 L/h at 400℃, and the source temperature was 100℃. The BPC obtained with negative ion ESI mass spectra were selected for the fingerprint analysis. Similarity evaluation was used to evaluate the quality of YQFM from different batches. Based on the intensities of the ions for common peaks, HCA and PCA were performed using SPSS 19.0 and Simca-P software.Results The UPLC-Q-TOF-MSE fingerprint of YQFM was established by using 28 batches of sample and 18 common peaks were found, of which 15 mutual peaks from Ginseng Radix et Rhizoma rubra, three mutual peaks from Ophiopogonis Radix. Compared with the reference substances and references, 16 of the common peaks were identified and the similarity of 28 batches samples were over 0.970. 28 batches of YQFM could be divided into four grades when the sum of squared Euclidean distance is 5-10 in the result of HCA; PCA got seven principal components through dimension reduction and accumulative contribution rate reached 84.989%. By fitting the load factor model of the first principal component, ten markers greatly impacting on the quality were found. The comprehensive evaluation function of YQFM in different batches was constructed according to the principal component score. Among 28 batches of YQFM, the comprehensive score of S28 was the best, closely followed by S22, S11 and S9, while S14 and S13 was the worst.Conclusion The utilization of UPLC-Q-TOF-MSE fingerprint coupled with chemical pattern recognition could objectively and effectively assess the quality of YQFM, can provide a more comprehensive reference for the quality control of YQFM.
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[基金项目]
"重大新药创制"科技重大专项(2013ZX09402202);天津市中药注射剂关键技术校企协同创新实验室建设项目(17PTSYJC00090)