基于化学指纹图谱和抗血小板聚集效价的丹参质量评价

通过化学分析和生物活性评价考察丹参药材的品质差异,探讨丹参抗血小板聚集生物活性的主要贡献成分.采用高效液相色谱(HPLC)技术建立丹参药材HPLC指纹图谱,以抗血小板聚集相对效价作为指标,评价不同产地不同批次丹参药材的品质差异,构建基于化学表征及生物效价测定的评价模式.结果表明,不同批次丹参药材的HPLC指纹图谱相似度很高(相似度0.930~0.998),而其抗血小板聚集相对效价相差10倍,提示化学指纹图谱难以反映丹参的活性和质量差异.通过化学指纹图谱与抗血小板聚集生物效价进行谱效相关分析,筛选出与生物活性相关系数大于0.5的6个色谱峰:二氢丹参酮Ⅰ、隐丹参酮、丹参酮Ⅰ、丹参酮ⅡA及2个未知化合物.对上述4种已知化合物单体进行活性验证发现,隐丹参酮的抗血小板聚集活性最强,而其它3种丹参酮类化合物几乎没有体外抗血小板聚集活性.进一步比较丹参中高含量成分丹酚酸B与低含量成分隐丹参酮的活性贡献,结果表明,两者的活性贡献基本相当,说明隐丹参酮是丹参中低含量高活性成分,对评价丹参质量具有重要贡献度.     

超高效液相色谱指纹图谱结合化学计量学优选掌叶大黄饮片炮制工艺

优选掌叶大黄饮片的炮制工艺.建立基于UPLC(超高效液相色谱)的掌叶大黄饮片主要指标成分指纹图谱测定方法,结合相似度评价、聚类分析、主成分分析和方差分析等化学计量学方法,对不同润制时间、不同干燥方式、不同烘干温度及时间掌叶大黄饮片的指纹图谱信息进行分析.不同润制时间掌叶大黄饮片的指纹图谱之间存在明显差异;聚类分析可将不...     

基于挥发性组分的气相色谱指纹图谱评价沉香化气片质量

建立了沉香化气片的气相色谱指纹图谱,并结合化学模式识别评价20批沉香化气片的质量。乙醇超声提取20批沉香化气片的挥发性成分,以正十八烷为内标,分析了3个主要组分的含量,且以内标计算其他各组分的相对峰面积,建立了沉香化气片的气相色谱指纹图谱,确定了11个共有峰,得到了各批次样品的相似度,并通过气相色谱-质谱法和对照品比对对10个共有峰进行了指认。将获得的峰面积指纹图谱采用系统聚类分析和主成分分析进行化学模式识别研究,实现了不同批次沉香化气片的区分,发现了造成不同批次样品差异的主要标记物。该方法有效且综合性强,为科学评价与有效控制沉香化气片的质量提供了可靠的参考。     

基于牛舌草指纹图谱的多指标成分相对定量与鉴别方法

色谱指纹图谱法在中草药产地鉴别或中成药鉴别中发挥着重要作用,然而色谱峰强度和位置易受目标物提取和分离条件的影响,发展更加准确的指纹图谱具有重要意义。该文以色谱峰中某一个常见组分（芦丁）作为内标,分析其他组分的相对含量,以相对含量作为指纹图谱信息,结合化学模式识别可以精确给出产地的相似度。以牛舌草的液相色谱指纹图谱指纹峰为例,以其中芦丁的组分峰作为基准峰,其他指纹峰以芦丁为参照,计算每个指纹峰以芦丁计的含量,建立了牛舌草的指纹图谱。将获得的相对含量指纹图谱采用系统聚类分析和主成分分析进行化学模式识别研究,实现了不同产地牛舌草的区分。该方法建立了牛舌草多指标成分的相对定量与鉴别方法,既节省资源,又具有可操作性,对于其他中药或中成药的质量控制具有一定的借鉴意义。     

UV–化学模式识别不同产地的丹参

建立由UV–化学模式识别法评价丹参质量的方法。分别用正己烷、乙酸乙酯、水、乙醇提取不同产地的丹参,并测绘其紫外光谱。取紫外光谱各波长的吸光度为特征数据,进行主成分分析、聚类分析,对不同产地丹参质量的差异进行了评价。不同溶剂提取液的光谱聚类结果有所差异,可将不同产地丹参聚为3类。UV–化学模式识别技术可以从整体上反应丹参所含成分的差异,可为丹参质量控制与评价提供依据。     

连花清瘟颗粒有效成分提取及高效液相色谱指纹图谱分析北大核心CSCD

建立连花清瘟颗粒的高效液相色谱(HPLC)指纹图谱,确认其化学成分并结合化学模式识别技术对其进行系统、科学的质量评价。使用化学对照品比对分析和超高效液相色谱-飞行时间质谱(UPLC-Q-TOF-MS)进行定性鉴定;Swell Chromplus TM-C18色谱柱(150 mm×4.6 mm,5μm);以0.1%磷酸-乙腈流动相,梯度洗脱;检测波长278 nm,进行高效液相色谱(HPLC)。采用中药色谱指纹图谱相似度评价系统及聚类分析、主成分分析分析软件进行化学模式识别方法分析。结果表明,通过指纹图谱相似度计算发现,10批样品的HPLC指纹图谱中发现16个共有峰,相似度达到0.967。确认了9个化学成分,包括新绿原酸、绿原酸、隐绿原酸、异绿原酸A、苦杏仁苷、连翘苷、连翘酯苷A、大黄素、大黄酚、大黄酸。该方法简单、稳定、重复性好,可用于该药物的质量评价。     

红外指纹图谱与双指标模型结合用于白芷品质分析

利用共有峰率和变异峰率两个指标,鉴别了不同品质的白芷的红外指纹图谱,白芷样品按厂家各自聚为一类。并应用化学计量学中模式识别方法,即主成分分析和系统聚类分析法,对白芷样品共有特征高效液相色谱峰数据进行处理。主成分分析和系统聚类分析结果与双指标模型一致,川白芷与祁白芷共有峰率最高,达到83. 3%。运用红外指纹图谱与双指标模型结合的方法,可以对白芷进行简单快速准确鉴别,为白芷品质的评价提供了另一种思路。     

不同产地金银花药材HPLC指纹图谱的研究

研究并建立不同产地的金银花药材的指纹图谱,并应用系统聚类分析和主成分分析建立金银花药材的化学模式识别方法,以期为金银花药材品质评价与质量控制提供参考。CP-C_(18)色谱柱(5μm,4.6mm×150mm),以乙腈-0.2%磷酸水溶液为流动相进行梯度洗脱,流速为1.0 mL·min~(-1),柱温25℃,检测波长为254nm。16批不同产地的金银花药材有13个共有峰,相似度在0.916~0.990。聚类分析能对不同产地的金银花药材进行有效识别,主成分分析结果与聚类分析结果类似。建立的方法能够成功应用于金银花药材的质量控制与评价及产地识别,可为制定金银花药材质量控制与评价模式提供新的参考依据。     

基于多元统计学的青稞HPLC指纹图谱研究

为了筛选品质良好的青稞,选择不同产地的10批青稞样品,建立了青稞的高效液相指纹图谱,并进行了聚类分析和主成分分析,测定了儿茶素、表儿茶素和芦丁3种指标成分的含量。首先采用高效液相色谱法测得了10批青稞的色谱图,建立其共有模式,确定了11个共有峰,蓝青稞指标成分含量均高于白青稞。对共有峰数据进行聚类分析和主成分分析,10批青稞被分为两类,主成分分析得到了3个主成分,方差累积达82.266%,综合得分最高的三个样品分别为S4、S3、S1,均为西藏地区的蓝青稞,与指标成分含量测定的结果一致。指纹图谱、聚类分析结合主成分分析为青稞的指标筛选和综合评价提供了新的方法。     

基于化学识别模式的蒲公英指纹图谱的研究

建立蒲公英药材的指纹图谱,以中药色谱指纹图谱相似度评价软件(2012年版)确定共有峰及其归属,采用化学模式识别初步筛选其质量控制的4个指标性成分。结果表明,蒲公英药材的HPLC指纹图谱共标定出27个共有峰,并指认出其中14个色谱峰,15批蒲公英药材的相似度均0.93,且化学模式识别的结果具有相似性。本文建立的方法可应用于蒲公英药材的质量评价和其产地识别,为蒲公英药材质量控制与资源开发提供参考。     

Approaches to bioresponse-linked instrumental analysis in water analysis

A new concept based on hyphenation of biotests, for biological selection, and chemical analysis is introduced for water analysis. Biomolecular recognition components such as receptors, enzymes, and nucleic acids integrated in biological reaction chains are used for binding and selective enrichment of known and unknown biologically active substances in water samples; this is followed by identification and quantitation. The coupling of biomolecular recognition and binding to chemical analysis can be achieved either in discrete analytical steps, e.g. binding and elution of bioactive ligands from affinity columns followed by chemical analysis, or by methods capable of monitoring the binding of the ligand and simultaneous verification of its identity. This analytical strategy, denoted bioresponse-linked instrumental analysis (BLIA), enables detection of potential biological effects and identification of the analyte causing these effects. Several examples are presented.     

Chemometrics for the analysis of chromatographic data in metabolomics investigations

Metabolomics aims to better understand biological systems through the chemical analysis of an organism's metabolic profile. One common method of analysis is mass spectrometry preceded by chromatographic separations. Samples produced by metabolomics investigations can contain hundreds to thousands of compounds, which can put great strain on the instrumental analysis. In order to improve these analyses, the data analysis must not be overlooked. The ever‐evolving field of chemometrics provides many useful tools for the analysis of chromatographic data. These include methods for preprocessing data to extract a maximum amount of information from the data as well as pattern recognition in order to find the compounds that vary the most in relation to the perturbation to the biological system under study. This article aims to highlight and provide future outlooks on current chemometric methods for chromatographic‐based metabolomics investigations. Copyright © 2014 John Wiley & Sons, Ltd.     

Treatment of a class-in-class modelling problem in chemical pattern recognition

A supervised learning procedure is described for the detection and characterization of classes which overlap or are located within other classes. The UNEQ classifier proposed by Derde and Massart is extended by applying tests for multivariate homogeneity and homoscedasticity, principal components analysis of each class box, and Boolean-type decision rules. The extended algorithm is suitable for class-in-class modelling. The procedure is applied to chemical data for an environmental problem involving an industrial source of emission and its immission effects.     

基于核酸分子识别的电化学分析方法与应用

核酸作为生物体遗传信息的载体以及分子生物学和生物分析化学中重要的功能分子,近年来在电化学分析中受到了越来越多的重视。本文以作者所在研究组的工作为实例,对核酸分子识别的电化学分析方法作出简要的评述,内容涉及核酸序列和基因变异的电化学分析以及核酸作为功能分子进行识别检测的电化学分析等等。     

Microimaging FT-IR spectroscopy on pathological breast tissues

Microimaging Fourier transform infrared spectroscopy is able to monitor differentiation between normal and malignant tissues. All the specimens, previously submitted to histological analysis, displayed abnormal spectra compared with the corresponding normal tissues with changes in many diagnostic bands like those arising from phosphate, C–O and CH stretching vibrational modes. The comparison between cancer (K) and connective (C) spectra evidenced the following differences: in the vCH region 3000–2800 cm⁻¹ no hypomethylation effect was evident in K; the convolution of the bands of connective indicated an expected higher membrane fluidity; in the neoplastic zone, Amide I and II modes showed convoluted bands with maxima at 1651 and 1547 cm⁻¹, respectively, indicating an α-helix conformation of proteins due to changes in the secondary structure proteins upon carcinogenesis. Other signature bands, such as the deformation O–P–O phosphate band at 965 cm⁻¹, suggested DNA conformational changes in solid cancer, infiltrating cancer and neoplasia in the region 1350–800 cm⁻¹. These characteristic bands have been monitored as a function of the degree of cancer progression. Chemometric methods, such as principal component analysis (PCA) and hierarchical clustering analysis (HCA) have been used in order to distinguish spectra of neoplastic and normal zones.     

环糊精用于分子识别分析的新进展

本文概述了环糊精用于分子识别分析的新进展，讨论了单体、修饰、交联环糊精在分子识别分析中的具体应用与展望。     

A multi-evaluating strategy for raw and processed Veratrum nigrum L.: Fingerprinting combined with quantitative analysis based on multivariate chemometric methods

Veratrum nigrum L. (VN) is a well-known herbal medicine and rich in chemical components with multiple pharmacological activities including antihypertensive, anticancer, and antifungal effects. In the current experiment, the quality of VN from different habitats was evaluated based on combinative method of fingerprint, multi-component quantification and chemical pattern recognition. Fifteen batches of VN were collected, and intrinsic chemical composition were identified using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry, which is a method for analyzing the similarity between samples, coupled with fingerprint of traditional Chinese medicine. The fingerprint similarity model show that 22 common peaks were selected covering 15 batches of and the similarity > 0.963. The total of 22 joint components were tentatively identified by comparison with standard substances or literature. A ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry method for simultaneous determination of 8 compounds was established to evaluate the contents of raw and processed Veratrum nigrum L. Multivariate analysis was then applied to compare different batches of herbs based on ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry data. All raw and processed samples were classified by partial least squares discriminant analysis based on the 8 analyzed compounds. The findings suggested that veratramine and polydatin with a variable importance for the project (VIP) > 1 were identified as significant constituents, the presence of which can be used to differentiate between raw and processed Veratrum nigrum L. samples. These results indicate that processing methods show important effects on the composition of Veratrum nigrum L..     

迭代目标转换因子分析光度法用于地质样品中15个稀土元素同时测定的研究

本文以三溴偶氮氯膦(TB-CPA)为显色剂,采用迭代目标转换因子分析(ITTFA)法,对地质样品中15个稀土元素进行同时测定,分析结果的相对误差小于15％;标准偏差为3.8×10~(-4)～5.5×10~(-2);相对标准偏差为0.22～3.5％;各元素的检测下限为(1.0～3.0)×10~(-8)。本文采用模式识别方法,用欧氏距离和方差作为分类特征,进行未知样品分析结果的可靠性判别。初步证明因子分析光度法用于解决复杂地质样品分析是可行的。还对目标向量的构成,最佳主因子数的确定对计算结果的影响等问题作了讨论。     

药物分子设计和核酸的分子识别分析

分子识别分析理论应用于药物分子设计是新药开发的要求，也是分析化学一个极具潜力的发展方向，分子识别分析不仅为药物分子设计提供了生物大分子的组成，结构基基本信息，还为了解药物分子与生物大分子相互作用位点及作用方式提供了模型，本文评述了与药物分子设计中有关的核酸物质的分子识别分析，它们是设计好的抗癌药物的基础。