{"title":"Spectrum-effect relationship between HPLC fingerprints and antioxidant activity of Qi-Fu-Yin based on multiple statistical correlation analysis.","authors":"Hengyu Li, Hongwei Zhao, Lingxiao Chen, Yong Yang, Shixue Wang, Rongyu Gao, Xiaorui Cheng","doi":"10.1002/pca.3396","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Qi-Fu-Yin has been used to treat Alzheimer's disease (AD) in China. Oxidative stress has been recognized as a factor in AD progress. To date, there is no quality control method to ensure batch-to-batch consistency of Qi-Fu-Yin, and the potential antioxidant compounds in Qi-Fu-Yin remain uncertain.</p><p><strong>Objectives: </strong>The aim of this study is to identify the potential antioxidant compounds of Qi-Fu-Yin and establish quality control standards for Qi-Fu-Yin.</p><p><strong>Methods: </strong>High-performance liquid chromatography was used to establish and quantify the fingerprints of Qi-Fu-Yin from various batches. Ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the common peaks. Bivariate correlation analysis, partial least squares regression analysis, and gray correlation analysis were used to establish the spectrum-effect relationship.</p><p><strong>Results: </strong>Forty-nine common peaks were determined through the establishment of fingerprints. Among them, 35 common peaks were preliminarily characterized. The multiple statistical correlation analysis methods identified six compounds as potential antioxidant constituents of Qi-Fu-Yin, and their antioxidant activities were validated in vitro. All six antioxidant compounds derived from two herbs. Therefore, three chemical index compounds derived from other three herbs were added to the quantitative analysis, while for two herbs, no peaks could be included. Eventually, six antioxidant constituents and three index compounds were quantitatively determined to provide a relatively comprehensive quality control for Qi-Fu-Yin.</p><p><strong>Conclusions: </strong>The study elucidated the antioxidant substance basis of Qi-Fu-Yin and provided a relatively comprehensive approach for the assay of Qi-Fu-Yin, which is a promising advance in the quality control of Qi-Fu-Yin.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"1565-1576"},"PeriodicalIF":3.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Phytochemical Analysis","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/pca.3396","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/22 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Qi-Fu-Yin has been used to treat Alzheimer's disease (AD) in China. Oxidative stress has been recognized as a factor in AD progress. To date, there is no quality control method to ensure batch-to-batch consistency of Qi-Fu-Yin, and the potential antioxidant compounds in Qi-Fu-Yin remain uncertain.
Objectives: The aim of this study is to identify the potential antioxidant compounds of Qi-Fu-Yin and establish quality control standards for Qi-Fu-Yin.
Methods: High-performance liquid chromatography was used to establish and quantify the fingerprints of Qi-Fu-Yin from various batches. Ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the common peaks. Bivariate correlation analysis, partial least squares regression analysis, and gray correlation analysis were used to establish the spectrum-effect relationship.
Results: Forty-nine common peaks were determined through the establishment of fingerprints. Among them, 35 common peaks were preliminarily characterized. The multiple statistical correlation analysis methods identified six compounds as potential antioxidant constituents of Qi-Fu-Yin, and their antioxidant activities were validated in vitro. All six antioxidant compounds derived from two herbs. Therefore, three chemical index compounds derived from other three herbs were added to the quantitative analysis, while for two herbs, no peaks could be included. Eventually, six antioxidant constituents and three index compounds were quantitatively determined to provide a relatively comprehensive quality control for Qi-Fu-Yin.
Conclusions: The study elucidated the antioxidant substance basis of Qi-Fu-Yin and provided a relatively comprehensive approach for the assay of Qi-Fu-Yin, which is a promising advance in the quality control of Qi-Fu-Yin.
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.