Analysis of nine rhubarb anthraquinones and bianthrones by micellar electrokinetic chromatography using experimental design

An efficient micellar electrokinetic chromatography (MEKC) method has been developed for the analysis of nine anthraquinones and bianthrones in rhubarb. A chemometric approach was used to search for the optimum conditions of separation. Those factors which were found to be significant with a screening design were further optimized with a central composite face-centered (CCF) design. Acetonitrile concentration was found to be the most influential, not only in resolution, but also in analysis time and peak asymmetry. With the optimized conditions: 15 mM sodium tetraborate/15 mM sodium dihydrogenphosphate buffer, 30 mM sodium deoxycholate, pH 8.6, 17 vol.% acetonitrile and 28 kV, nine tested analytes were baseline-separated within 14 min. The method was validated to analyze the rhubarb material. Solid-phase extraction (SPE) was manipulated to remove interfering substances. Five anthraquinones and two glycosidic bianthrones were detected and quantificated. The method should be suitable for determining these major active principles in rhubarb crude drugs.     

区带毛细管电泳分离测定大黄提取液中游离蒽醌化合物

采用区带毛细管电泳法分离和同时测定大黄提取液中五种蒽醌化合物的含量。毛细管电泳的分离条件为:50 cm×75μm i.d.未涂层石英分光毛细管,分离电压20kV,0.05 mol/L KH2PO4-Na2HPO4(pH=8.2)缓冲溶液,紫外检测波长为254 nm,以氨基苯磺酸为内标。该法简便,快速,分辨率高,重现性好。     

Discrimination of crude and processed rhubarb products using a chemometric approach based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry

Crude rhubarb subjected to different processing procedures will produce different therapeutic effects that are possibly due to processing‐induced variation in chemical composition. In this study, a chemometric approach based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry was established to systematically investigate the chemical variations of rhubarb induced by different processing methods. The approach was validated based on pooled quality‐control samples from two perspectives: the individual properties of variables and the bulk properties of samples. Orthogonal partial least squares discriminant analysis was introduced to compare the differences between crude and processed rhubarb products. A total of 20 significantly different markers were screened out and unambiguously/tentatively characterized. This research proved that a chemometric method based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry can comprehensively analyze the chemical variation of herbal medicine and provide evidence for a deeper understanding of the pharmacological activities of processed rhubarb products.     

Determination of 19 rhubarb constituents by high-performance liquid chromatography-ultraviolet-mass spectrometry

Rhubarb (Rhei rhizoma), a commonly used Chinese herb, contains anthraquinones, anthrones, galloylglucoses, stilbenes, and flavan-3-ols compounds, etc. as major constituents. Using 19 of these compounds as markers, an HPLC-UV-MS method was developed to estimate the quality of rhubarb samples within a period of 70 min. Extracts were analyzed with a Cosmosil 5C18-MS column and eluted with a gradient comprising an aqueous solution of acetic acid and methanol at a flow rate of 0.9 mL/min. Peaks were detected by absorbance measurements at 254 nm (6 and 8-19) and 280 nm (1-5 and 7), and the peaks of the marker substances were identified from their UV spectra and MS fragmentation patterns. The proposed method yielded a peak-area ratio RSD value with an intraday SD falling within 0.71-1.78% and an interday SD within 0.78-1.98% at a detection limit of 0.2-3.2 microg/mL. The ESI negative ion mode was used to collect data (molecular weight, CID fragments from MS and MS/MS spectra) for 19 compounds from four types of structure categories: anthraquinones, dianthrone glycosides, stilbenes, and galloylglucosides. The information gathered can be used to identify the structures of various peaks appearing in the LC chromatograms of rhubarb samples.     

微乳电动毛细管色谱在掌叶大黄指纹图谱上的应用

采用微乳电动毛细管色谱法(MEEKC)建立不同来源掌叶大黄的指纹图谱,为其质量控制提供依据。使用未涂层石英毛细管柱(75μm×65 cm,有效长度55 cm),采用的缓冲液为w(SDS)∶w(正丁醇)∶w(正辛烷)∶w(10 mmol/L硼砂溶液)=3.3∶6.6∶0.8∶89.3并通过添加10%的乙腈组成的O/W型微乳体系,分离电压18 kV,检测波长280 nm。结果通过聚类分析和相似度分析处理,14个掌叶大黄样品初步分为三类:道地药材,市售一般品和次品。本方法可用于掌叶大黄质量评价的有效手段,为MEEKC在中药指纹图谱研究中开辟了新的应用途径。     

HPLC–TOF‐MS and HPLC–MS/MS combined with multivariate analysis for the characterization and discrimination of phenolic profiles in nonfumigated and sulfur‐fumigated rhubarb

Sulfur fumigation has recently been used during the postharvest handling of rhubarb to reduce the drying duration and control pests. However, a few reports question the effect of sulfur fumigation on the bioactive components of rhubarb, which is crucial for the quality evaluation of the herbal medicine. The bottleneck limiting the study comes from the complex compounds that exist in herb samples with diverse structural features, wide concentration range and the difficulty to obtain all the reference standards. In this study, an integrated strategy based on the highly effective separation and analysis by liquid chromatography coupled with diode‐array detection and time‐of‐flight/triple‐quadruple tandem mass spectrometry combined with multivariate analysis was established. 68 phenolic compounds that exist in nonfumigated and sulfur‐fumigated herb samples of rhubarb were tentatively assigned based on their retention behavior, UV spectra, accurate molecular weight, and mass spectral fragments. Qualitative and semiquantitative comparison revealed a serious reduction of the majority of phenolic compounds in sulfur‐fumigated rhubarb. Furthermore, multivariate analysis was applied to holistically discriminate nonfumigated from sulfur‐fumigated rhubarb and explore the characteristic chemical markers. The established approach was specific and rapid for characterizing and screening sulfur‐fumigated rhubarb among commercial samples and could be applied for the quality assessment of other sulfur‐fumigated herbs.     

流动注射双光束光度法测定大黄中黄素含量

用改进的流动注射光度法测定大黄中黄素含量。大黄素在碱性介质中生成稳定红色络合物的特性,最大吸收波长为λ=530nm,一次进样同时产生一正一负两拐点的响应曲线。利用△A（A1—A2）的微分光度值进行定量分析,进样频率为130次·h^-1,线性范围为1.5-350μg·mL^-1,相关系数r=0.9997,相对标准偏差RSD=0.97%（n=9）。方法操作简单,快速可靠,平均回收率为99.6%。     

近红外光谱法最小二乘双胞胎支持向量机的应用研究

依据中药大黄的近红外光谱信息,采用最小二乘双胞胎支持向量机( LSTSVM)算法,通过MATLAB软件编程,建立参数可优化识别模型,实现了对中药大黄的真伪鉴别.将实验材料98个大黄样品随机划分为训练集和测试集,对于训练集60个样品采用留1/5法交叉验证优化模型参数,以所选最优化参数结合训练集样品的近红外光谱建立最优识别模型,对测试集的38个样品的真伪迸行识别,识别率可达97.4％.结果表明,LSTSVM算法是一种有效的识别方法,可依据中药大黄的近红外光谱对其真伪进行快速识别.同时,本研究将大黄样品6次随机划分为训练集和测试集,建模预测平均识别率为93.4％,表明采用LSTSVM算法建立识别模型具有较好的稳健性.     

支持向量机(SVM)在傅里叶变换近红外光谱分析中的应用研究

支持向量机(SVM)用于两类问题的识别研究,它是统计学习理论中最年轻的分支,所建分析模型有严格的数学基础。同时介绍了SVM学习的基本原理和方法,并将该方法引入化学计量学,以103个中药大黄样品为实验材料,通过SVM近红外光谱法建立了大黄样品真伪识别模型。对学习集中33个样品模型识别准确率为100％;对70个预测样品的识别准确率为96.77％, 为中药大黄的快速识别提供了参考。研究结果表明了SVM近红外光谱法建立生物样品识别模型的可行性。通过旨在介绍SVM学习方法的基本思想,以引起化学计量学工作者的进一步关注。     

基于大黄的红外光谱的人工神经网络鉴别研究

将傅里叶变换红外光谱法和人工神经网络用于鉴别正品和非正品大黄样品。在对神经网络训练前用小波变换对测量的红外光谱进行压缩,将原700个数据点的光谱压缩到44个变量,因此加速了神经网络的训练速度。52个大黄样品被用于网络模型的建立,其中包括25个正品大黄和27个非正品大黄的样品。文章还对隐含层神经元数目和动量参数的影响做了考察。结果表明,在优化的条件下用该方法对大黄样品的鉴别正确率达到98％。这种方法可被用于含大黄中药生产的质量控制。