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星点设计-效应面法优化青连宁心胶囊中黄连和青蒿的提取工艺

Optimal extraction of effective constituents from Rhizoma coptidis and Artemisia annua in Qinglian Ningxin Capsules based on central composite design-response surface methodology

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【作者】 牟大可马飞牟冉冉孙洪胜

【Author】 MU Dake;MA Fei;MU Ranran;SUN Hongsheng;The Affiliated Hospital of Shandong University of TCM;

【通讯作者】 孙洪胜;

【机构】 山东中医药大学附属医院

【摘要】 目的用星点设计-效应面法对黄连和青蒿的提取工艺进行优化。方法以小檗碱、巴马汀、黄连碱和表小檗碱为考察指标,采用星点设计考察乙醇浓度、乙醇用量、提取时间对黄连的提取工艺进行优化;以青蒿素得膏率为考察指标,采用星点设计考察乙醇用量、温浸时间、乙醇浓度对青蒿的提取工艺进行优化。结果优选的黄连提取工艺为10.5倍量含1%硫酸的70%的乙醇提取3次,每次90 min,小檗碱、巴马汀、黄连碱和表小檗碱的平均含量与预测值偏差-1.5%;优选的青蒿提取工艺为11.5倍量60%的乙醇提取2次,每次110 min,青蒿素的平均含量与预测值偏差-0.33%。结论星点设计-效应面法优选黄连和青蒿的提取工艺,方法简便,预测性良好。

【Abstract】 Objective To optimize the process of extracting effective constituents from Rhizoma coptidis and Artemisia annua by central composite design-response surface methodology.Methods The effects of optimization factors such as solvent fold,ethanol concentration and extract time on extraction rate of berberine,palmatine,hydrastis and epiberberine of Rhizoma coptidis were investigated by using box-behnken design and response surface method; The effects of optimization factors such as solvent fold,ethanol concentration and warm immersion time on extraction rate of coefficient of unguent of Artemisia annua were investigated by using box-behnken design and response surface method. Results The best extraction process of Rhizoma coptidis was 10.5 times of 70% ethanol with 1% H2 SO4 and extracting for three times,each time 90 min.Bias between the average content of berberine,palmatine,hydrastis,epiberberine and predicted values was less than-1.5%;The best extraction process of Rhizoma coptidis was 11.5 times of 60% ethanol with and extracting for two times,each time110 min.Bias between the average content of artemisinin and predicted values was less than-0.33%. Conclusion Optimized extraction technology of Rhizoma coptidis and Artemisia annua was convenient with high predictive.

【基金】 山东省重点研发计划(No.2014GGH219001)
  • 【文献出处】 药学研究 ,Journal of Pharmaceutical Research , 编辑部邮箱 ,2018年10期
  • 【分类号】R284.2
  • 【被引频次】3
  • 【下载频次】246
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