杨梅抗补体和抗氧化活性的UPLC-MS图谱化学识别及谱效关系

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Mengyao Zhang, Deji, Daofeng Chen, Yan Lu
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引用次数: 0

摘要

简介:杨梅(Myricariae Ramulus, MR)是一种传统的抗炎藏药,提取自杨梅属(Myricaria wardii Marquand)等多种杨梅属植物的枝叶。目的:对15批不同产地和药用部位的MR进行光谱效应分析,以确定其抗炎作用相关的质量标记。材料与方法:采用脂多糖感染小鼠模型,研究了不同部位的抗炎作用。利用UPLC-Q-TOF-MS/MS在负离子模式下进一步鉴定了弓形虫枝叶中乙酸乙酯(EA)组分的化合物组成。随后,通过溶血法和ABTS自由基清除法测定其抗补体和抗氧化活性,并建立了15批样品的UPLC色谱。最后,采用灰色关联分析和偏最小二乘回归进行光谱效应分析,确定质量标记。结果:EA部位通过调节IL-6和髓过氧化物酶,有效减轻炎症反应。共鉴定出华氏弓形虫46种化合物,主要包括没食子衍生物、酚类酰胺、黄酮类和萜类。活性测定表明,多叶小枝的两种活性显著强于树枝。此外,观察到两部分的化学成分有明显的区别。结合光谱效应分析结果,将枝条中提取的3,4-二羟基-5-甲氧基苯甲酸甲酯、杨梅素A、原儿茶醛、n -阿铁酰去甲肾上腺素和叶状细枝中提取的原儿茶酸作为质量标记。结论:本研究结果为提高磁共振成像的质量控制提供了参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chemical Recognition and Spectrum-Effect Relationship of UPLC-MS Chromatograms With Anti-Complementary and Antioxidant Activities of Myricariae Ramulus.

Introduction: Myricariae Ramulus (MR) is a traditional anti-inflammatory Tibetan medicine derived from the branches and leafy twigs of various Myricaria plants, such as Myricaria wardii Marquand.

Objective: This study performed spectrum-effect analyses on 15 batches of MR, sourced from various origins and medicinal parts, to identify quality markers associated with its anti-inflammatory effects.

Materials and methods: The anti-inflammatory effects of different extracts and fractions from M. wardii were evaluated in lipopolysaccharide-infected mice. Further analysis was conducted utilizing UPLC-Q-TOF-MS/MS in the negative ion mode to recognize the compound composition of ethyl acetate (EA) fractions from the branches and leafy twigs of M. wardii. Subsequently, anti-complementary and antioxidant activities were conducted via the hemolysis and ABTS radical scavenging methods, and UPLC chromatograms for 15 batches of samples were established. Finally, spectrum-effect analysis was performed by gray relational analysis and partial least squares regression to identify the quality markers.

Results: The EA fraction effectively alleviated inflammatory responses by regulating IL-6 and myeloperoxidase. A total of 46 compounds from M. wardii were recognized, which mainly encompass gallic derivatives, phenolic amides, flavonoids, and terpenoids. Activity assays demonstrated that the two activities of leafy twigs were significantly stronger than those of branches. Moreover, an obvious distinction in chemical composition between the two parts was observed. Combining the spectrum-effect analysis results, methyl 3,4-dihydroxy-5-methoxybenzoate, myricarin A, protocatechualdehyde, and N-feruloyl normetanephrine from the branches, and protocatechuic acid from the leafy twigs were considered quality markers.

Conclusion: These results provide insights into improving the quality control of MR.

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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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