欢迎访问《中国临床药理学与治疗学》杂志官方网站,今天是 分享到:

中国临床药理学与治疗学 ›› 2011, Vol. 16 ›› Issue (7): 763-767.

• 定理药理学 • 上一篇    下一篇

麻黄汤不同配伍对大鼠发汗作用的定量评价

熊倩, 张密, 郑青山   

  1. 上海中医药大学药物临床研究中心,上海 201203
  • 收稿日期:2011-04-07 修回日期:2011-06-10 出版日期:2011-07-26 发布日期:2011-09-22
  • 通讯作者: 郑青山,男,教授,博士生导师,研究方向:药物相互作用动力学。Tel: 021-51322750 E-mail: zheng.zqs@gmail.com
  • 作者简介:熊倩,女,七年制研究生,研究方向:中药复方配伍规律。E-mail:xiongqian1986@yahoo.com.cn

Quantitative evaluation of pharmacodynamic interactions on diaphoretic effects among the components of Mao-to in rats

XIONG Qian, ZHANG Mi, ZHENG Qing-shan   

  1. Center for Drug of Clinical Research, Shanghai University of Chinese Medicine, Shanghai 201203, China
  • Received:2011-04-07 Revised:2011-06-10 Online:2011-07-26 Published:2011-09-22

摘要: 目的: 基于麻黄汤不同配伍对大鼠发汗影响的实验数据,采用模型化与模拟化方法进行再分析,提取更多信息,阐明其配伍规律,为优化组方提供参考。方法: 麻黄汤4个组分为L14(24+)正交设计,1水平为“使用”,0水平为“不使用”,药效指标为大鼠腋窝皮肤汗腺空泡发生率为作用指数。采用正交模拟法与非线性混合效应模型(NONMEM),分析各组分在复方背景下的重要程度和相互作用。模拟偏倚由4种视图及单组分实验结果综合评价。结果: 麻黄汤各组分对大鼠发汗作用的药效影响按重要程度排序依次是桂枝(B)、麻黄(A)、杏仁(C)和甘草(D),药效最佳组合为麻黄+桂枝,最弱组合为杏仁+甘草。结论: 麻黄汤发汗作用药效贡献最大的为麻黄、桂枝,且两者作用相当,发挥最佳发汗作用须两者联用。

关键词: 麻黄汤, 配伍, 模拟, 定量分析

Abstract: AIM: To analyze pharmacodynamic interaction on diaphoretic effects among the components from Mao-to for finding an optimal combination.METHODS: According to the four components that included in Mao-to, an orthogonal design with 1-level = used and 0-level = not used, was selected in L14(24) and a mathematical model was built up with the nonlinear mixed effect model (NONMEM) for rat experiment. Vacuole incidence of axillary sweat gland was determined to evaluate the diaphoretic effect. The importance and effectiveness of each component were analyzed in combinations and the bias was evaluated by some charts.RESULTS: The prediction model showed that it would be Cassia Twig (B), Ephedra (A), Apricot (C), and Liquorice (D) in order by the importance and the best combination is A plus B, while the worst is C combined with D.CONCLUSION: Ephedra and Cassia Twig in combination have significant diaphoretic effect in rats, and the combination will show better effect in comparison with any single component.

Key words: Mao-to, Compound, Simulation, Pharmacodynamic interactions

中图分类号: