Statistical modelling coupled with LC-MS analysis to predict human upper intestinal absorption of phytochemical mixtures

被引:11
作者
Selby-Pham, Sophie N. B. [1 ,2 ]
Howell, Kate S. [1 ]
Dunshea, Frank R. [1 ]
Ludbey, Joel [3 ]
Lutz, Adrian [4 ]
Bennett, Louise [2 ]
机构
[1] Univ Melbourne, Fac Vet & Agr Sci, Parkville, Vic 3010, Australia
[2] CSIRO Agr & Food, Werribee, Vic 3030, Australia
[3] CSIRO Informat Management & Technol, Clayton, Vic 3169, Australia
[4] Univ Melbourne, Sch Biosci, Metab Australia, Parkville, Vic 3010, Australia
关键词
Untargeted profiling; LC-MS; Secondary metabolites; Log P; Molecular mass; T-max; Phytochemical absorption prediction model; DNA-DAMAGE; FRUIT; BIOAVAILABILITY; ANTHOCYANINS; CONSUMPTION; RISK; TEA; SUPPLEMENTATION; METABOLITES; VEGETABLES;
D O I
10.1016/j.foodchem.2017.10.102
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
A diet rich in phytochemicals confers benefits for health by reducing the risk of chronic diseases via regulation of oxidative stress and inflammation (OSI). For optimal protective bio-efficacy, the time required for phytochemicals and their metabolites to reach maximal plasma concentrations (T-max) should be synchronised with the time of increased OSI. A statistical model has been reported to predict Tmax of individual phytochemicals based on molecular mass and lipophilicity. We report the application of the model for predicting the absorption profile of an uncharacterised phytochemical mixture, herein referred to as the 'functional fingerprint'. First, chemical profiles of phytochemical extracts were acquired using liquid chromatography mass spectrometry (LC-MS), then the molecular features for respective components were used to predict their plasma absorption maximum, based on molecular mass and lipophilicity. This method of 'functional fingerprinting' of plant extracts represents a novel tool for understanding and optimising the health efficacy of plant extracts.
引用
收藏
页码:353 / 363
页数:11
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