Literature DB >> 32474352

UHPLC-QqQ-MS/MS method development and validation with statistical analysis: Determination of raspberry ketone metabolites in mice plasma and brain.

Bo Yuan1, Danyue Zhao2, Dushyant Kshatriya3, Nicholas T Bello3, James E Simon4, Qingli Wu5.   

Abstract

Raspberry ketone (RK) (4-(4-hydroxyphenyl)-2-butanone) is the major compound responsible for the characteristic aroma of red raspberries, and has long been used commercially as a flavoring agent and recently as a weight loss supplement. A targeted UHPLC-QqQ-MS/MS method was developed and validated for analysis of RK and 25 associated metabolites in mouse plasma and brain. Dispersion and projection analysis and central composite design were used for method optimization. Random effect analysis of variance was applied for validation inference and variation partition. Within this framework, repeatability, a broader sense of precision, was calculated as fraction of accuracy variance, reflecting instrumental imprecision, compound degradation and carry-over effects. Multivariate correlation analysis and principle component analysis were conducted, revealing underlying association among the manifold of method traits. R programming was engaged in streamlined statistical analysis and data visualization. Two particular phenomena, the analytes' background existence in the enzyme solution used for phase II metabolites deconjugation, and the noted lability of analytes in pure solvent at 4 ℃ vs. elevated stability in biomatrices, were found critical to method development and validation. The approach for the method development and validation provided a foundation for experiments that examine RK metabolism and bioavailability.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Design of experiment; Metabolomics; Multivariate analysis; Random effects ANOVA; Surface response modelling

Mesh:

Substances:

Year:  2020        PMID: 32474352      PMCID: PMC7391222          DOI: 10.1016/j.jchromb.2020.122146

Source DB:  PubMed          Journal:  J Chromatogr B Analyt Technol Biomed Life Sci        ISSN: 1570-0232            Impact factor:   3.205


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10.  A highly sensitive ultra-high performance liquid chromatography/tandem mass spectrometry method with in-source fragmentation for rapid quantification of raspberry ketone.

Authors:  Bo Yuan; Danyue Zhao; Ruoyuan Du; Dushyant Kshatriya; Nicholas T Bello; James E Simon; Qingli Wu
Journal:  J Food Drug Anal       Date:  2018-08-14       Impact factor: 6.157

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