Coptis chinensis(Huanglian) is a commonly used traditional Chinese medicine(TCM) herb and alkaloids are the most important chemical constituents in it. In the present study, an isocratic reverse phase high performance...Coptis chinensis(Huanglian) is a commonly used traditional Chinese medicine(TCM) herb and alkaloids are the most important chemical constituents in it. In the present study, an isocratic reverse phase high performance liquid chromatography(RP-HPLC) method allowing the separation of six alkaloids in Huanglian was for the first time developed under the quality by design(Qb D) principles. First, five chromatographic parameters were identified to construct a Plackett-Burman experimental design. The critical resolution, analysis time, and peak width were responses modeled by multivariate linear regression. The results showed that the percentage of acetonitrile, concentration of sodium dodecyl sulfate, and concentration of potassium phosphate monobasic were statistically significant parameters(P < 0.05). Then, the Box-Behnken experimental design was applied to further evaluate the interactions between the three parameters on selected responses. Full quadratic models were built and used to establish the analytical design space. Moreover, the reliability of design space was estimated by the Bayesian posterior predictive distribution. The optimal separation was predicted at 40% acetonitrile, 1.7 g·m L-1of sodium dodecyl sulfate and 0.03 mol·m L-1 of potassium phosphate monobasic. Finally, the accuracy profile methodology was used to validate the established HPLC method. The results demonstrated that the Qb D concept could be efficiently used to develop a robust RP-HPLC analytical method for Huanglian.展开更多
It has been reported that hyperspectral data could be employed to qualitatively elucidate the spatial composition of tablets of Chinese medicinal plants.To gain more insights into this technology,a quantitative profil...It has been reported that hyperspectral data could be employed to qualitatively elucidate the spatial composition of tablets of Chinese medicinal plants.To gain more insights into this technology,a quantitative profile provided by near infrared(NIR)spectromicroscopy was further studied by determining the glycyrrhizic acid content in licorice,Glycyrrhiza uralensis.Thirty-nine samples from twenty-four different origins were analyzed using NIR spectromicroscopy.Partial least squares,interval partial least square(iPLS),and least squares support vector regression(LS-SVR) methods were used to develop linear and non-linear calibration models,with optimal calibration parameters(number of interval numbers,kernel parameter,etc.) being explored.The root mean square error of prediction(RMSEP) and the coefficient of determination(R^2) of the iPLS model were 0.717 7% and 0.936 1 in the prediction set,respectively.The RMSEP and R^2 of LS-SVR model were 0.515 5%and 0.951 4 in the prediction set,respectively.These results demonstrated that the glycyrrhizic acid content in licorice could barely be analyzed by NIR spectromicroscopy,suggesting that good quality quantitative data are difficult to obtain from microscopic NIR spectra for complicated Chinese medicinal plant materials.展开更多
基金supported by National Natural Science Foundation of China(No.81403112)Beijing Natural Science Foundation(No.7154217)+1 种基金Scientific Research Program of Beijing University of Chinese Medicine(No.2015-JYB-XS104)Special Program for Beijing Key Laboratory of Chinese Medicine Manufacturing Process Control and Quality Evaluation(No.Z151100001615065)
文摘Coptis chinensis(Huanglian) is a commonly used traditional Chinese medicine(TCM) herb and alkaloids are the most important chemical constituents in it. In the present study, an isocratic reverse phase high performance liquid chromatography(RP-HPLC) method allowing the separation of six alkaloids in Huanglian was for the first time developed under the quality by design(Qb D) principles. First, five chromatographic parameters were identified to construct a Plackett-Burman experimental design. The critical resolution, analysis time, and peak width were responses modeled by multivariate linear regression. The results showed that the percentage of acetonitrile, concentration of sodium dodecyl sulfate, and concentration of potassium phosphate monobasic were statistically significant parameters(P < 0.05). Then, the Box-Behnken experimental design was applied to further evaluate the interactions between the three parameters on selected responses. Full quadratic models were built and used to establish the analytical design space. Moreover, the reliability of design space was estimated by the Bayesian posterior predictive distribution. The optimal separation was predicted at 40% acetonitrile, 1.7 g·m L-1of sodium dodecyl sulfate and 0.03 mol·m L-1 of potassium phosphate monobasic. Finally, the accuracy profile methodology was used to validate the established HPLC method. The results demonstrated that the Qb D concept could be efficiently used to develop a robust RP-HPLC analytical method for Huanglian.
基金supported by the National Natural Science Foundation of China(No.81303218)the Doctoral Fund of the Ministry of Education of China(No.20130013120006)Beijing University of Chinese Medicine Special Subject of Outstanding Young Teachers and Innovation Team Foundation
文摘It has been reported that hyperspectral data could be employed to qualitatively elucidate the spatial composition of tablets of Chinese medicinal plants.To gain more insights into this technology,a quantitative profile provided by near infrared(NIR)spectromicroscopy was further studied by determining the glycyrrhizic acid content in licorice,Glycyrrhiza uralensis.Thirty-nine samples from twenty-four different origins were analyzed using NIR spectromicroscopy.Partial least squares,interval partial least square(iPLS),and least squares support vector regression(LS-SVR) methods were used to develop linear and non-linear calibration models,with optimal calibration parameters(number of interval numbers,kernel parameter,etc.) being explored.The root mean square error of prediction(RMSEP) and the coefficient of determination(R^2) of the iPLS model were 0.717 7% and 0.936 1 in the prediction set,respectively.The RMSEP and R^2 of LS-SVR model were 0.515 5%and 0.951 4 in the prediction set,respectively.These results demonstrated that the glycyrrhizic acid content in licorice could barely be analyzed by NIR spectromicroscopy,suggesting that good quality quantitative data are difficult to obtain from microscopic NIR spectra for complicated Chinese medicinal plant materials.
