Application of response surface methodology and quantitative NMR for the optimum extraction, characterization, and quantitation of Antrodia cinnamomea triterpenoids.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
20 Nov 2023
20 Nov 2023
Historique:
received:
24
09
2023
accepted:
16
11
2023
medline:
27
11
2023
pubmed:
21
11
2023
entrez:
21
11
2023
Statut:
epublish
Résumé
Antrodia cinnamomea (AC) is a treasured Asian medicinal mushroom, which has attracted attention due to recent research on its effectiveness in targeting a variety of serious ailments such as cancer and liver diseases. Among different A. cinnamomea constituents, triterpenoids are regarded as the most therapeutically attractive components because of their anti-inflammatory and cytotoxic activities. In the present study, we proposed a mathematical and statistical extraction protocol to evaluate the concentrations of total ergostane and lanostane triterpenoid derivatives from the ethanolic extract of the wild fruiting bodies of A. cinnamomea (EEAC) by utilizing response surface methodology (RSM) and quantitative NMR (qNMR) approaches. The optimum response surface model showed that the variations of the investigated response variables reached more than 90%, suggesting that the developed model is accurate in explaining response variability. Furthermore, the EEAC major characteristic triterpenoids were quantified through the comparison of the HPLC-tandem MS results with those of the qNMR results. The precision of the used techniques was also evaluated. The experimental design of the EEAC optimum extraction procedure obtained by using RSM and qNMR enabled accurate characterization and quantitation of A. cinnamomea triterpenoids.
Identifiants
pubmed: 37985810
doi: 10.1038/s41598-023-47615-6
pii: 10.1038/s41598-023-47615-6
pmc: PMC10661979
doi:
Substances chimiques
Triterpenes
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
20265Subventions
Organisme : Ministry of Science and Technology, Taiwan
ID : MOST 109-2320-B-276-001-MY2
Informations de copyright
© 2023. The Author(s).
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