Quantitative and qualitative determination of LiuweiDihuang preparations by ultra high performance liquid chromatography in dual‐wavelength fingerprinting mode and random forest

Qiu, Yixing; Huang, Jianhua; Jiang, Xingming; Chen, Yang; Liu, Yang; Zeng, Rong; Shehla, Nuzhat; Liu, Qiang; Liao, Duan‐Fang; Guo, Dan; Liang, Yi‐Zeng; Wang, Wei

doi:10.1002/jssc.201500560

Cited by 20 publications

(10 citation statements)

References 19 publications

(13 reference statements)

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“…[2], has been used as a traditional Chinese medicine with treatment of blood related disorders for 2000 years [3]. CM is also widely used in Chinese Patent Medicines as one sub-material, such as in famous LiuweiDihuang preparations, GuizhiFuling tablet and Rhubarb Peony Decoction [4] [5] [6]. According to Chinese Pharmacopoeia, CM should originate from Paeonia Suffruticosa Andr.…”

Section: Introductionmentioning

confidence: 99%

Study on the Multi-Component Quantitation of Cortex Moutan and Its Intestinal Absorption Characteristics

Ge¹,

Hou²,

Li³

et al. 2019

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Cortex Moutan (Paeonia suffruticosa Andr.) is a common traditional Chinese medicine and has been widely used in clinic for 2000 years in China. As sources for this crude drug are always mixed with other species, many cultivars on herbal market may lead to quality instability. Multi-component quantitative analysis is an efficient method to reflect chemical profiles of herb medicine and is always taken as the main method for quality evaluation. So, the aim of this work is to develop analytical method to quantify paeonol, paeoniflorin, gallic acid, oxypaeoniflorin, benzoylpaeoniflorin and paeonolide in Cortex Moutan (CM) to evaluate the chemical qualities of CM from different species or cultivars. Besides, we also study the intestinal absorption characteristics of paeonol and paeoniflorin for further pharmacological evaluation. In the present study, all of the standard markers were performed on an Ecosil C 18 (250 mm × 4.6 mm, 5 μM, Lubex Co., Guangzhou, China) with linear gradient elution of 0.2% formic acid water and acetonitrile. The proposed method was applied to analyze 50 batches of samples with acceptable linearity (R 2 , 0.9995-0.9999), precisions (RSD, 0.47%-2.08%), repeatability (RSD, 039%-2.63%), stability (RSD, 0.52%-2.45%), and recovery (RSD, 0.72%-3.03%) of the six compounds. Furthermore, the Hierarchical Cluster Analysis was applied to classify the 50 samples based on contents of the six compound markers. The results obtained from multi-component quantification of CM clearly indicated that CM originated from P. suffruticosa and P. ostii presented different chemical properties, and that samples from the two materials could be gathered into one branch, respectively, while CM sourced from cultivars of P. suffruticosa showed great variety on chemical quality. The results from Hierarchical Cluster Analysis implied that the established method could be used as a powerful tool for the quality evaluation of CM.

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Section: Introductionmentioning

confidence: 99%

Study on the Multi-Component Quantitation of Cortex Moutan and Its Intestinal Absorption Characteristics

Ge¹,

Hou²,

Li³

et al. 2019

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“…Although clarification of compound composition opens up the possibility of determining structure–activity relationships (SARs) of TCM constituents, it is a time consuming and laborious but important task for researchers. Potentially active compounds need to be identified within the compound mixture when a significant SAR has been verified and pharmacological observation of the TCM need to be investigated . In many cases, this is accomplished by the application of mass detection techniques .…”

Section: Introductionmentioning

confidence: 99%

Five‐descriptor model to predict the chromatographic sequence of natural compounds

Hou

Wang

et al. 2016

J of Separation Science

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Despite the recent introduction of mass detection techniques, ultraviolet detection is still widely applied in the field of the chromatographic analysis of natural medicines. Here, a neural network cascade model consisting of nine small artificial neural network units was innovatively developed to predict the chromatographic sequence of natural compounds by integrating five molecular descriptors as the input. A total of 117 compounds of known structure were collected for model building. The order of appearance of each compound was determined in gradient chromatography. Strong linear correlation was found between the predicted and actual chromatographic position orders (Spearman's rho = 0.883, p < 0.0001). Application of the model to the external validation set of nine natural compounds was shown to dramatically increase the prediction accuracy of the real chromatographic order of multiple compounds. A case study shows that chromatographic sequence prediction based on a neural network cascade facilitated compound identification in the chromatographic fingerprint of Radix Salvia miltiorrhiza. For natural medicines of known compound composition, our method provides a feasible means for identifying the constituents of interest when only ultraviolet detection is available.

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“…Zhang et al [91] developed a UPLC-MS fingerprinting of SiJunZiTang with a Waters Acquity HSS Liu-Wei-Di-Huang-Wan (LWDHW), shown to have clinical efficacy for "nourishing kidney-yin" in TCMs, has been used for thousands of years in China. Wang et al [92] established an UHPLC method for the comprehensive quantitative determination of the major bioactive markers in LWDHW. In order to achieve efficient separation, several UPLC columns, including the Agilent Zorbax SB-C18 (100 mm × 2.1 mm, 1.8 m), the Agilent Zorbax Plus-C18 (100 mm × 2.1 mm, 1.8 m), and the Agilent Zorbax SB-Aq C18 (100 mm × 2.1 mm, 1.8 m), were evaluated.…”

Section: High-efficiency Stationary Phases For Tcmsmentioning

confidence: 99%

Recent development in liquid chromatography stationary phases for separation of Traditional Chinese Medicine components

Jin

Liu

Guo

et al. 2016

Journal of Pharmaceutical and Biomedical Analysis

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Traditional Chinese Medicine (TCM) is an ancient medical practice which has been used to prevent and cure diseases for thousands of years. TCMs are frequently multi-component systems with mainly unidentified constituents. The study of the chemical compositions of TCMs remains a hotspot of research. Different strategies have been developed to manage the significant complexity of TCMs, in an attempt to determine their constituents. Reversed-phase liquid chromatography (RPLC) is still the method of choice for the separation of TCMs, but has many problems related to limited selectivity. Recently, enormous efforts have been concentrated on the development of efficient liquid chromatography (LC) methods for TCMs, based on selective stationary phases. This can improve the resolution and peak capacity considerably. In addition, high-efficiency stationary phases have been applied in the analysis of TCMs since the invention of ultra high-performance liquid chromatography (UHPLC). This review describes the advances in LC methods in TCM research from 2010 to date, and focuses on novel stationary phases. Their potential in the separation of TCMs using relevant applications is also demonstrated.

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Quantitative and qualitative determination of LiuweiDihuang preparations by ultra high performance liquid chromatography in dual‐wavelength fingerprinting mode and random forest

Cited by 20 publications

References 19 publications

Study on the Multi-Component Quantitation of Cortex Moutan and Its Intestinal Absorption Characteristics

Study on the Multi-Component Quantitation of Cortex Moutan and Its Intestinal Absorption Characteristics

Five‐descriptor model to predict the chromatographic sequence of natural compounds

Recent development in liquid chromatography stationary phases for separation of Traditional Chinese Medicine components

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