秦岭龙胆的化学成分

从秦岭龙胆(Gentiana apiata N.E.Br.)全草的乙醇提取物中分离得到4个化合物,通过波谱分析分别鉴定为异荭草甙(isoorientin),龙胆苦甙(gentiopicroside),asystasioside A和蔗糖(D-sucrose).采用二维NMR分析,确定了asystasioside A的立体结构.以上化合物均为首次从该植物中发现.     

石墨炉原子吸收光谱法测定不同地区秦艽花中铅和镉的含量

选用硝酸和高氯酸(4∶1)的混合消解液对样品进行微波消解,利用微波消解-石墨炉原子吸收光谱法测定不同地区秦艽花药材中铅、镉的含量。该方法铅、镉加标回收率分别为96.5%、94.0%,相对标准偏差(RSD)分别为2.7%、4.3%,具有良好的准确度和精密度。结果显示,不同地区的秦艽花中Pb的含量介于1.266—3.429mg·kg-1之间,Cd的含量均小于等于0.167mg·kg-1,不同地区秦艽花中Pb、Cd的含量均有一定差异。该测定结果为秦艽花药材的质量控制与开发利用提供可靠依据。     

电感耦合等离子体-原子发射光谱法测定滇龙胆中的镉和铅

利用电感耦合等离子体-原子发射光谱法(ICP-AES)测定滇龙胆中重金属元素Cd和Pb,比较了干灰化法和湿化法2种样品处理方法对分析结果的影响,并测定了云南一些地区滇龙胆中的Cd和Pb含量。结果表明:采用电感耦合等离子体原子发射光谱法检测滇龙胆中的Cd和Pb,最低检出限(DL)分别为1.43ng·mL-1和1.16ng·mL-1;相对标准偏差(RSD)分别为4.37%和4.05%;回收率分别为96.25%和92.25%。利用湿法消解样品,精密度好,回收率高,优于干灰化法。干灰化法适合测定滇龙胆中Pb,但不适合测定Cd,其回收率仅为0.2%。用湿法消解样品,测定不同产地滇龙胆的Cd和Pb含量,结果表明:所测地区滇龙胆的Cd,Pb含量大大低于《中华人民共和国药典》(2005)规定的中药材重金属含量标准,符合GAP生产的要求。     

Determination of gentisin, isogentisin, and amarogentin in Gentiana lutea L. by capillary electrophoresis

A novel, fast, and simple capillary electrophoresis method has been developed for the analysis of gentisin, isogentisin, and amarogentin in roots of Gentiana lutea (yellow gentian), an herb traditionally used as gastric stimulant. Gentisin and isogentisin are xanthones showing potent inhibition of monoamine oxidase type A and B, amarogentin represents one of the bitter principles of Gentiana, responsible for its gastric-roborant effects. Optimal CE-separation conditions comprise a 100 mM sodium tetraborate buffer of pH 9.3, containing 10 mM beta-cyclodextrin as additive; optimum temperature and applied voltage were found to be 30 degrees C and 25 kV, respectively. Direct diode array detection at 260 nm (gentisin, isogentisin) and 242 nm (amarogentin) was performed, and the required analysis time was only 11 min. The developed method was validated for linearity, sensitivity, precision, and accuracy, and utilized to assay several commercially available G. lutea samples. Quantitative data obtained with the developed CE method are compared with HPLC results, and the advantages of each approach are discussed.     

藏药材白花龙胆花中微量元素的分析

对藏药材白花龙胆花中17种微量元素（Cu、Zn、Fe、Mn、Co、Ni、Se、Cr、Mg、Ca、K、Na、P、As、Hg、Pb、Cd）的含量作了测定。结果表明,白花龙胆花中含有较高的人体必需微量元素和常量元素,其中常量元素K、Ca、Na、Mg和微量元素Zn、Fe、Mn的含量均较高。     

不同采收期滇龙胆的红外光谱鉴别研究

采收是中药生产的重要环节,采收时间直接影响中药质量和产量,是中医临床安全有效用药的前提,开展中药适时采收期的研究具有重要意义和应用价值。采用傅里叶变换红外光谱法对72份不同采收期的滇龙胆进行鉴别研究,用TQ8.0软件对原始光谱进行一阶导数(first derivative,FD)、二阶导数(second derivative,SD)、标准正态变量(standard normal variate,SNV)、多元散射校正(multiplicative scatter correction,MSC)和平滑(savitaky-golay filter,SG)预处理,样品按3∶1分为校正集和预测集,同时建立主成分分析(principal component analysis,PCA)和偏最小二乘判别分析(partial least square discriminant analysis,PLS-DA)模型。结果显示,选取1 800~600cm~(-1)波段范围的光谱,去除光谱噪音;SNV结合二阶导数光谱和SG(15,3)平滑,预处理结果满意。主成分分析表明,前三个主成分方差贡献率为92.47%,5月、9月和10月份采收的样品差异较小。偏最小二乘判别分析建立判别模型,决定系数R2和校正均方根误差(RMSEE)分别为0.967 8和0.086 0,可对18个预测集样品进行准确分类。红外光谱法结合主成分分析、偏最小二乘判别分析对不同采收期滇龙胆的分类和判别效果较好,为不同采收期的中药鉴别提供理论依据。     

藏药材麻花艽中铜锌铁锰含量分析

采用ICP-AES法对青海省内采集的麻花艽中的铜、锌、铁、锰的含量进行了测定。结果表明,麻花艽中四种元素含量丰富,各部位含量差异较大,其中基部茎部含量较高,入药部位根部次之,为以后的开发利用提供了基础数据。     

基于FTIR技术和稀疏线性判别分析的秦艽种类鉴别

傅里叶变换红外光谱通常包含有大量的波长变量点,对其进行定性分析需要建立稳健的、可解释性的分类模型。稀疏线性判别分析(SLDA)是一种较为新颖和有效的机器学习算法,常用于高维度、小样本数据的变量筛选和判别分析,SLDA通过在线性判别分析中引入正则项,使分类器训练过程和变量选择过程同时完成,不同判别方向上载荷系数的稀疏性则增强了模型的可解释性。采集甘肃不同产地的秦艽样本94个,其中麻花秦艽(Gentiana straminea Maxim)30个,黄管秦艽(Gentiana officinalis)28个,大叶秦艽(Gentiana macrophylla Pall)36个,利用傅里叶变换红外光谱法获得所有样本的光谱图。取其中70个样本构成训练集,剩余24个为测试集。使用训练集建立SLDA模型,对2个判别方向上不为0的载荷系数个数进行网格化寻优,得到了最优的参数空间。利用建立的SLDA模型对测试样本进行预测,其分类准确率达到100%,实现了对三种秦艽的快速、准确鉴别。实验结果表明,与PLS-DA方法相比,SLDA模型在分类准确率、稀疏性及可解释性方面均具有一定优势,是一种新颖、有效的光谱定性分析方法。     

Geographical Authentication of Gentiana Rigescens by High-Performance Liquid Chromatography and Infrared Spectroscopy

The chemical characteristics of Gentiana rigescens are extremely variable due to their geographical origins which should be determined to evaluate the quality of this species. Different with other herbs with official tissue for classification materials, the geographical characterization of raw herbal materials on the basis of nonmedicinal parts is rarely discussed. Chromatographic active components were used as references to characterize the chemical profiles of samples from various geographical origins. Based on spectra data matrix of different botanical parts, the chemometric methods of partial least square discrimination analysis and support vector machine discrimination analysis were used to develop mathematical models to classify samples from different geographical origins. In terms of six active components, we found that significant differences were present in the tissue of G. rigescens based on geographical origins. In addition, the region with higher content of gentiopicroside was selected to be the optimal cultivated location. Chemometric results indicated that leaves were the optimal material for geographical characterization of G. rigescens with 100% accuracy by support vector machine while the accuracies of roots, stems, and flowers were 90.91, 96.10, and 97.01%, respectively. Partial least square discrimination analysis showed that accuracy values for roots, stems, leaves, and flowers were 35.65, 67.53, 76.62, and 50.75%, respectively, which also indicated that leaves are the optimal material. In conclusion, northwest Yunnan Province with higher content of gentiopicroside was selected to be the optimal cultivation location. Furthermore, leaves should be used for the most accurate geographical authentication.