Elosta Shaban, Gajdosová Dagmar, Havel Josef
Department of Analytical Chemistry, Masaryk University, Kotlárská, Brno, Czech Republic.
J Sep Sci. 2006 May;29(8):1174-9. doi: 10.1002/jssc.200500361.
Ginkgo biloba, traditional Chinese medicine is now generally accepted. Separation and determination of active components in G. biloba is important for the product quality control. Therefore, the development of an effective and reliable separation method is important. In this work, a new capillary electrophoretic (CZE) method for separation of the G. biloba leaf extracts components was developed and optimized by the use of experimental design and artificial neural network (ANN). Under best separation conditions, in gamma-CD-modified buffer, the separation was reached within 10 min (36 mM borate BGE, pH 9.2, 1 mM gamma-CD), while the hydrodynamic mode for sample injection (2 s) and UV detection at 270 nm were applied. The method developed was validated and applied for analysis of various extracts and G. biloba products.
银杏叶作为传统中药现已被广泛接受。银杏叶中活性成分的分离与测定对于产品质量控制至关重要。因此,开发一种有效且可靠的分离方法具有重要意义。在本研究中,通过实验设计和人工神经网络(ANN)开发并优化了一种用于分离银杏叶提取物成分的新型毛细管电泳(CZE)方法。在最佳分离条件下,即在γ-环糊精修饰的缓冲液中,10分钟内可实现分离(36 mM硼酸盐缓冲液,pH 9.2,1 mMγ-环糊精),同时采用流体动力学进样模式(2秒)并在270 nm处进行紫外检测。所开发的方法经过验证,并应用于各种提取物和银杏叶产品的分析。