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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Biomedical Chromatog...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Biomedical Chromatography
Article . 2020 . Peer-reviewed
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A strategy for qualitative and quantitative profiling of Angelicae Pubescentis Radix and detection of its analgesic and anti‐inflammatory components by spectrum–effect relationship and multivariate statistical analysis

Authors: Ajiao Hou; Liu Yang; Jiaxu Zhang; Song Wang; Wenjing Man; Xinyue Guo; Bingyou Yang; +4 Authors

A strategy for qualitative and quantitative profiling of Angelicae Pubescentis Radix and detection of its analgesic and anti‐inflammatory components by spectrum–effect relationship and multivariate statistical analysis

Abstract

AbstractThis study established a spectrum–effect relationship method for screening and quantifying the analgesic and anti‐inflammatory active ingredients in Angelicae Pubescentis Radix (AP) by ultra‐high‐performance liquid chromatography–quadrupole mass spectrometry detector analysis (UPLC–QDA). First, the fingerprint of AP was established to determine the common peaks. Next, six batches of AP samples, with significant differences, were selected for evaluation of pharmacological activity. Subsequently, the spectrum–effect relationship was used to screen the active ingredients. Finally, the screened ingredients were quantified using UPLC–QDA. In total, 21 common peaks were identified and four effective compounds (bergapten, columbianetin acetate, osthole and isoimperatorin) were selected using the gray relational analysis and partial least squares regression analysis. Quantitative analysis showed that the content of the four effective compounds was the highest in a randomly selected batch, S7 (Hubei). To our knowledge, this is the first attempt that evaluated the quality and spectrum–effect relationship of AP by quantitative analysis and chemometrics. This study identified the key pharmacologically active components of AP and thereby improved the quality evaluation system of AP. This method has broad application prospects for screening effective components and will be helpful in establishing more reliable, scientific and reasonable quality standards for AP and other traditional Chinese medicines.

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Keywords

Inflammation, Male, Analgesics, Behavior, Animal, Anti-Inflammatory Agents, Reproducibility of Results, Mass Spectrometry, Disease Models, Animal, Mice, Limit of Detection, Multivariate Analysis, Animals, Chromatography, High Pressure Liquid, Angelica, Drugs, Chinese Herbal

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
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