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Tracing anti‐osteoporosis components from raw and salt‐processed semen of Cuscuta chinensis by employing a biochemometrics strategy that integrates ultrasonic‐assisted extraction, quantitation, efficacy assessment in zebrafish, and grey relationship analysis
- Source :
- Journal of Separation Science. 44:3229-3236
- Publication Year :
- 2021
- Publisher :
- Wiley, 2021.
-
Abstract
- Semen of Cuscuta chinensis has been reported to have an anti-osteoporosis effect, however, the components which account for the anti-osteoporosis effect have not been clarified. In this work we propose a biochemometrics strategy that integrates quantitation, anti-osteoporosis evaluation in zebrafish, and grey relationship analysis for the identification of anti-osteoporosis components from the semen of Cuscuta chinensis. In the beginning, a precise and accurate liquid chromatography-tandem mass spectrometry method was established for simultaneous quantitation of seven major components in crude and salt-processed Cuscuta chinensis. The mode of multiple reaction monitoring was used. Chloramphenicol was selected as the internal standard. The method showed good linearity and repeatability. The recovery rates of each component ranged from 95.4 to 103.9%. The precisions of intra-day and inter-day were all within 5.0%. The method was then applied for quantitation of the seven major components in 11 batches of crude and salt-processed Cuscuta chinensis. Subsequently, the anti-osteoporosis effects of crude and salt-processed Cuscuta chinensis were evaluated in zebrafish. Principle component analysis, grey relationship analysis, and partial least squares regression were applied for deciphering the relationship between the contents of seven major components and the anti-osteoporosis effects. Hyperin, p-hydroxycinnamic acid, and astragalin were found to be the major anti-osteoporosis components.
- Subjects :
- Chromatography
biology
Chemistry
Selected reaction monitoring
Extraction (chemistry)
Filtration and Separation
Semen
Repeatability
biology.organism_classification
Analytical Chemistry
chemistry.chemical_compound
Partial least squares regression
Principal component analysis
Astragalin
Cuscuta chinensis
Subjects
Details
- ISSN :
- 16159314 and 16159306
- Volume :
- 44
- Database :
- OpenAIRE
- Journal :
- Journal of Separation Science
- Accession number :
- edsair.doi...........0fdbc566f27bd99cc5de91ff46d07dcf
- Full Text :
- https://doi.org/10.1002/jssc.202100272