Combination of large-volume sample stacking with polarity switching and micelle electrokinetic chromatography for the analysis of anion compounds in Yangxinshi tablets.

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Phytochemical Analysis Pub Date : 2024-07-01 Epub Date: 2024-03-10 DOI:10.1002/pca.3347
Wenping Liu, Rui Zhou, Jin Li, Kunze Du, Jun He, Yaqi Yao, Yanxu Chang
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Abstract

Introduction: Yangxinshi tablet (YXST) is a traditional Chinese medicine preparation characterized by its high efficacy and safety for the treatment of cardiovascular diseases. Anionic compounds have been revealed as potential active components. However, there is currently limited research regarding its quality control.

Objective: We aimed to establish a strategy for the simultaneous separation and determination of five key anionic compounds in YXST.

Method: A sensitive and efficient analytical method was developed and applied for the simultaneous separation and determination of five key compounds in YXST using large-volume sample stacking with polarity switching and micelle electrokinetic chromatography (LVSS-PS-MEKC) coupled with diode array detection. Crucial parameters, including sample volume, applied voltage, composition and pH of the running buffer, concentration of organic modifier, and switching time of the polarity, were systematically evaluated and optimized using a single variable method to enhance separation performance. Furthermore, the impact of cyclodextrin and sodium dodecyl sulfate as electrolyte modifiers was also investigated.

Results: Under the optimal conditions, baseline separation of the five compounds (daidzein, puerarin, glycyrrhiztinic acid, chlorogenic acid, and salvianolic acid B) was achieved within 20 min. In comparison to the conventional MEKC mode, the constructed LVSS-PS-MEKC method exhibited a more than sixfold increase in the enrichment factor. The method was validated in terms of linearity, precision, accuracy, 24 h stability, and recovery and successfully applied to analyze YXST samples.

Conclusion: A sensitive strategy was developed for the simultaneous separation and determination of five key anionic components in YXST, offering a robust and efficient strategy for pharmaceutical analysis.

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将大容量样品堆积与极性切换和胶束电动色谱法相结合,用于分析养心氏片中的阴离子化合物。
简介养心氏片(YXST)是一种传统中药制剂,在治疗心血管疾病方面具有高效、安全的特点。阴离子化合物是其潜在的活性成分。然而,目前有关其质量控制的研究还很有限:我们旨在建立一种同时分离和测定 YXST 中五种主要阴离子化合物的策略:建立了一种灵敏、高效的分析方法,并将其应用于大体积样品叠加极性切换和胶束电动色谱法(LVSS-PS-MEKC)结合二极管阵列检测法同时分离和测定 YXST 中的五种关键化合物。采用单一变量法对关键参数进行了系统评估和优化,这些参数包括样品体积、外加电压、运行缓冲液的成分和 pH 值、有机改性剂的浓度以及极性切换时间,以提高分离性能。此外,还研究了环糊精和十二烷基硫酸钠作为电解质改性剂的影响:结果:在最佳条件下,五种化合物(麦冬苷、葛根素、甘草次酸、绿原酸和丹酚酸 B)在 20 分钟内实现了基线分离。与传统的MEKC模式相比,所构建的LVSS-PS-MEKC方法的富集因子提高了6倍以上。该方法在线性、精密度、准确度、24 h稳定性和回收率等方面都得到了验证,并成功应用于YXST样品的分析:结论:该方法灵敏度高,可同时分离和测定 YXST 中的五种关键阴离子成分,为药物分析提供了一种稳健高效的方法。
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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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