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- W2078529892 abstract "NMR based metabolic profiling techniques are rapidly emerging as promising tools for the quality control of medicinal plants and plant derived products [1]. However, their use is often limited by sample complexity, which makes the identification of discriminating constituents a challenging task [2]. The use of hyphenated techniques such as LC-SPE-NMR has been proven to facilitate this process by separating selected analytes from the matrix and providing valuable 1H and 13C NMR data, which aids the identification process. In a previous work, we described the use of NMR based metabolic profiling for the differentiation of 15 different T. vulgaris lots [3]. In this study, we present the application of LC-SPE-NMR for the rapid dereplication of known secondary metabolites in T. vulgaris extracts and fractions obtained by ASE (Accelerated Solvent Extraction), liquid-liquid extraction and HSCCC (High Speed Counter Current Chromatography). Multiple peak trapping allowed the acquisition of 1D (1H) and 2D NMR spectra (COSY, ROESY, HSQC, HMBC) with excellent signal-to-noise ratio. This approach enabled the unambiguous identification of seven compounds, namely thymol, cirsimaritin, cirsilineol, xanthomicrol, 8-methoxycirsilineol, 3,4,3',4'-tetrahydroxy-5,5'-diisopropyl-2,2'-dimethylbiphenyl and rosmarinic acid. Based on the outcome of the previously reported PCA (Principal Component Analysis) [3], it was possible to identify thymol and rosmarinic acid as discriminating constituents. The identification process was carried out within three weeks using 8g of starting plant material. Thus, this report underlines the importance of LC-SPE-NMR as a fast and effective dereplication tool for the identification of discriminators in NMR based metabolic profiling." @default.
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- W2078529892 date "2009-07-01" @default.
- W2078529892 modified "2023-10-16" @default.
- W2078529892 title "Rapid dereplication of secondary metabolites from Thymus vulgaris L. using LC-SPE-NMR as discriminators identification tool in NMR based metabolic profiling" @default.
- W2078529892 doi "https://doi.org/10.1055/s-0029-1234674" @default.
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