Simultaneous determination of six index constituents and comparative analysis of four ethnomedicines from genus Gentiana using a UPLC‐UV‐MS method

Many species from genus Gentiana (Gentianaceae) have a long history of applications as folk medicines in the world. A simple rapid UPLC‐UV‐MS/MS method has been developed and validated for the simultaneous determination of six index constituents (gentiopicroside, swertiamarin, loganic acid, sweroside, mangiferin and ferulic acid) from the four ethnomedicines (G. rigescens Franch. ex Hemsl., G. rhodantha Franch. ex Hemsl., G. scabra Bunge and G. farreri Balf. f.). The UPLC analysis was performed on Shim‐Pack XR‐ODS III (150 × 2.0 mm, 2.2 µm). The mobile phase was consisted of acetonitrile–0.1% formic acid water using gradient elution. The wavelength 242 nm was chose for the four iridoids as well as mangiferin and 320 nm was set for ferulic acid. Mass spectrometry was applied for identification and quantification for analytes with low concentration. All the regression equations revealed a good linear relationship (R² > 0.9993). Accuracy and precision were all within the required limits. The chromatogram fingerprints analysis combined with principal component analysis showed the similarity values of the four species were <0.788 while the similarity values of G. scabra Bunge and G. rigescens Franch. ex Hemsl. were >0.993, which provided reasonable foundation for utilization and clinical application of the four ethnomedicines. This developed method appears to be a useful tool for quality control of the four ethnomedicines. Copyright © 2014 John Wiley & Sons, Ltd.     

Discrimination of Polygoni Multiflori radix and Cynanchi Auriculati radix using ultra‐high performance liquid chromatography fingerprints and chemical pattern recognition

In this work, a strategy was proposed to discriminate Polygoni Multiflori Radix (PMR) and its adulterant (Cynanchi Auriculati Radix, CAR). Ultra‐high performance liquid chromatography (UHPLC) fingerprints were established to analyze samples containing PMR, CAR and mixtures simultaneously. Multivariate classification methods were applied to analyze the obtained UHPLC fingerprints, including principal component analysis (PCA), partial least square discriminant analysis (PLS‐DA), soft independent modeling of class analogy (SIMCA), support vector machine discriminant analysis (SVMDA) and counter‐propagation artificial neural network (CP‐ANN). A plot of PCA score showed that PMR and CAR samples belonged to separate clusters (PMR class and CAR class), and samples of mixtures were located near PMR or CAR classes. Analysis by PLS‐DA, SVMDA and CP‐ANN performed well for recognition and prediction in terms of PMR and CAR samples. Moreover, the PLS‐DA method performed best in the detection of adulterated samples, even if the adulterant was about 25%.     

Applications of Carbon Dots (CDs) in Latent Fingerprints Imaging

Carbon dots (CDs), a new member of the carbon-based material family, possess unique properties, such as high fluorescence, non-toxicity, eco-friendliness, stability and cost-effectiveness. These properties helped CDs to receive tremendous attention in various fields, namely, biological, opto-electronic, bio-imaging and energy-related applications. Although CDs are widely explored in bio-imaging and bio-sensing applications, their effectiveness in forensic science and technology is comparatively new. In this review, applications of CDs pertaining to latent FPs recovery since 2015 to 2020 is summarized comprehensively.     

聚集诱导发光材料显现潜指纹应用研究的综合实验设计**

结合前期的科研成果,设计了一个以聚集诱导发光材料在潜指纹显现应用研究为主线的综合性化学实验。整个实验包含了聚集诱导发光性质研究、潜指纹显现应用和在自动指纹识别系统平台上匹配测试等3方面内容。本实验贴近学科前沿且联系公安工作实际,不仅可以促使学生了解聚集诱导发光材料的研究现状和刑事科学技术学科前沿知识,还可以解决公安教育与公安实践脱节的问题。     

Quantitative analysis of multicomponents by single marker combined with HPLC fingerprint qualitative analyses for comprehensive evaluation of Aurantii Fructus

The present study aimed to develop a strategy involving quantitative analysis of multicomponents by single marker in combination with high‐performance liquid chromatography fingerprint qualitative analysis for performing the quality control of Aurantii Fructus. The content of 12 components (eriocitrin, neoeriocitrin, narirutin, naringin, hesperidin, neohesperidin, meranzin, poncirin, naringenin, nobiletin, tangeretin, and auraptene) in samples was determined using reliable relative correction factors that were obtained using naringin as an internal reference standard. The new method demonstrated good applicability, and no significant differences were observed between the external standard method and the new method as determined by calculating standard method difference. Qualitative evaluation of samples was conducted using similarity analysis, hierarchical cluster analysis, and quality fluctuation analysis. Chromatographic fingerprint data were divided into three groups by similarity and hierarchical cluster analyses, and seven components may have a more significant impact on the quality of Aurantii Fructus in quality fluctuation analysis. Overall, the study suggests that the qualitative and quantitative analyses of multicomponents using quantitative analysis of multicomponents by single marker combined with chromatographic fingerprinting can be considered good quality criteria for performing quality control and providing technical support for the further pharmacological and pharmaceutical research of Aurantii Fructus.     

高效液相-四极杆飞行时间串联质谱分析黄蜀葵花中黄酮醇类化合物

以中药材黄蜀葵花为分析对象,采用高效液相-电喷雾/四极杆-飞行时间串联质谱,识别中药中黄酮醇类化合物.通过解析紫外光谱和二级质谱,识别了17个黄酮醇糖苷和2个黄酮醇苷元,用对照品对照及分析酸水解液的方法进行了验证;并探讨了黄酮醇类化合物的电喷雾/串联质谱(ESI/MS/MS)的裂解方式;在此分析基础上,研究了HPLC指纹图谱和多指标含量测定方法,方法学考察结果表明符合测定要求;采用金丝桃苷、杨梅素和槲皮素作参照,以折算分子量的方法计算相对含量,扩展中药质量控制多指标化的范畴.     

应用电化学指纹图谱优化黄连水提取工艺的研究

以黄连提取液中的总成分为定量指标,应用电化学振荡技术获取不同提取工艺的电化学指纹图谱.根据电化学指纹图谱特征参数诱导时间来考察其水溶性有效成分含量的高低,与高效液相色谱含量测定方法对照,验证了该方法的可靠性,确定黄连提取的最佳工艺为:采用12倍量的水,提取1.5 h,提取2次.结果表明利用电化学指纹图谱的诱导时间优化中药水溶性有效成分的提取工艺是可行的.     

磷光碳点粉末的合成及其在抗背景干扰的潜指纹成像中的应用

以乙二胺、磷酸和硼酸为反应物,采用水热法制备了荧光碳点(CDs)溶液,进一步加热水热反应溶液,获得了磷光CDs粉末。利用X射线衍射(XRD)、透射电子显微镜(TEM)、X射线光电子能谱(XPS)、紫外可见(UV-Vis)吸收光谱和光致发光光谱等对CDs的结构、形貌和尺寸、表面基团与化学组成以及光学特性进行了表征。结果表明,合成的CDs粉末为无定型碳,形貌为单分散的近球形,尺寸分布在 3.78~7.64 nm范围之内,其表面存在大量的 N、P和 B杂原子基团。CDs粉末在 365 nm紫外光照射下呈现明亮的蓝色荧光,关闭激发光后,呈现长达10 s的绿色室温磷光。该CDs粉末可作为指纹试剂应用于具有复杂背景图案且有强荧光发射基质表面的潜指纹(LFPs)显现。显现后的LFPs在激发光关闭后均呈现明亮完整的磷光指纹图谱,指纹细节特征清晰可辨,有效消除了背景图案与背景荧光干扰。同时,制备的CDs粉末对不同干扰背景客体表面老化7 d的LFPs也能够显现出清晰可识别的磷光指纹图谱。     

One- and two-dimensional gas chromatography–mass spectrometry and high performance liquid chromatography–diode-array detector fingerprints of complex substances: A comparison of classification performance of similar,complex Rhizoma Curcumae samples with the aid of chemometrics

Many complex natural or synthetic products are analysed either by the GC–MS (gas chromatography–mass spectrometry) or HPLC–DAD (high performance liquid chromatography–diode-array detector) technique, each of which produces a one-dimensional fingerprint for a given sample. This may be used for classification of different batches of a product. GC–MS and HPLC–DAD analyses of complex, similar substances represented by the three common types of the TCM (traditional Chinese medicine), Rhizoma Curcumae were analysed in the form of one- and two-dimensional matrices firstly with the use of PCA (Principal component analysis), which showed a reasonable separation of the samples for each technique. However, the separation patterns were rather different for each analytical method, and PCA of the combined data matrix showed improved discrimination of the three types of object; close associations between the GC–MS and HPLC–DAD variables were observed. LDA (linear discriminant analysis), BP-ANN (back propagation-artificial neural networks) and LS-SVM (least squares-support vector machine) chemometrics methods were then applied to classify the training and prediction sets. For one-dimensional matrices, all training models indicated that several samples would be misclassified; the same was observed for each prediction set. However, by comparison, in the analysis of the combined matrix, all models gave 100% classification with the training set, and the LS-SVM calibration also produced a 100% result for prediction, with the BP-ANN calibration closely behind. This has important implications for comparing complex substances such as the TCMs because clearly the one-dimensional data matrices alone produce inferior results for training and prediction as compared to the combined data matrix models. Thus, product samples may be misclassified with the use of the one-dimensional data because of insufficient information.     

Advances in fingerprint analysis

Fingerprints have been used in forensic investigations for the identification of individuals since the late 19th century. However, it is now clear that fingerprints can provide significantly more information about an individual. Here, we highlight the considerable advances in fingerprinting technology that can simultaneously provide chemical information regarding the drugs ingested and the explosives and drugs handled by a person as well as the identity of that individual.