HPLC指纹图谱联合化学计量学及多组分含量测定用于黄麻酊质量评价与控制。

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Jing Qiu, Jie Li, Si-Yang Shang, Peng Zhou, Jing Leng
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引用次数: 0

摘要

黄麻酊(HMT)是一种具有60多年临床使用历史的中成药,广泛用于治疗糖尿病足溃疡等皮肤慢性溃疡。然而,HMT的整体质量评价和控制方法尚未得到研究。目的:建立基于高效液相色谱(HPLC)指纹图谱、化学计量学和多组分含量测定的药材药材质量综合评价与控制方法。方法:建立HMT化学指纹图谱,进行相似度分析,综合反映制剂在化学成分上的一致性。化学计量学分析包括层次聚类分析(HCA)、主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA),以确定影响质量差异的关键成分。测定五种潜在生物活性成分(马钱子碱、士的宁、麻风根碱、黄连碱和盐酸小檗碱)的含量作为补充质量控制措施。结果:建立了相似指数为> 0.990的HMT HPLC指纹图谱,其中鉴定出了马钱子碱、士的宁、麻黄碱、黄连碱、盐酸小檗碱5个常见化合物。通过200次排列试验验证的HCA、PCA和OPLS-DA结果基本一致。20批HMT样品中马钱子碱、士的宁、麻风根碱、黄连碱和盐酸小檗碱的含量分别为0.2088 ~ 0.5556、0.2599 ~ 0.9868、0.1358 ~ 0.2092、0.2634 ~ 0.6843和1.8301 ~ 2.7826 mg/mL。结论:高效液相色谱指纹图谱结合化学计量学和多组分含量测定,综合考虑药效和毒性,为药材药材的综合质量评价和控制提供了可靠的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HPLC Fingerprint Combined With Chemometrics and Multicomponent Content Determination for Quality Evaluation and Control of Huangma Tincture.

Introduction: Huangma Tincture (HMT) is a Chinese patent medicine with a history of clinical use for more than 60 years, widely used for treating dermal chronic ulcer such as diabetic foot ulcer. However, the overall quality evaluation and control method of HMT has not yet been researched.

Objective: The aim of this study is to establish a comprehensive quality evaluation and control method for HMT based on high-performance liquid chromatography (HPLC) fingerprint, chemometrics, and multicomponent content determination.

Methods: Establishing chemical fingerprint of HMT and carrying out similarity analysis comprehensively reflect the consistency of the formulation in terms of chemical composition. Chemometrics analyses, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA), were performed to identify components crucial to quality differences. The content of five potential bioactive ingredients (brucine, strychnine, jatrorrhizine, coptisine, and berberine hydrochloride) was determined as a supplementary quality control measure.

Results: HPLC fingerprint of HMT with similarity index > 0.990 was established, in which five common compounds (brucine, strychnine, jatrorrhizine, coptisine, and berberine hydrochloride) were identified. HCA, PCA, and OPLS-DA results, validated through 200 permutation tests, were basically consistent. The contents of brucine, strychnine, jatrorrhizine, coptisine, and berberine hydrochloride in 20 batches of HMT samples were 0.2088-0.5556, 0.2599-0.9868, 0.1358-0.2092, 0.2634-0.6843, and 1.8301-2.7826 mg/mL, respectively.

Conclusion: HPLC fingerprint combined with chemometrics and multicomponent content determination considering both effect and toxicity provides a robust method for the comprehensive quality evaluation and control of HMT.

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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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