Definitely simultaneous determination of three lignans in rat using ultra-high performance liquid...

Herbal medicines (HMs) have been widely demonstrated to be extremely complicated chemical pools, notably the occurrences of isomers that usually possess similar chromatographic and spectrometric behaviors, and the complexity will be further boosted in HMs-treated biological samples. Hence, there is a technical barrier regarding identity confirmation towards the acquisition of reliable quantitative information for those compounds-of-interest in biological matrices, although tandem mass spectrometry (MS/MS) is a favored tool because of the advantages in terms of specificity and selectivity, in particular being hyphenated with ultra-high performance liquid chromatography (UHPLC). More structural information should be involved in addition to retention times and precursor-to-product ion transitions, to consolidate the identities of the captured signals. Attempts were made here to strengthen quantitation confidences via matching MS² spectra and relative response-collision energy curves (RRCECs) between each pair of suspect peak and the authentic signal, and UHPLC coupled to hybrid triple quadrupole-linear ion trap mass spectrometry (Qtrap-MS) that enabled simultaneous acquisition of qualitative and quantitative information acted as the analytical tool. Definitely simultaneous determination of a pair of regio-isomers namely 6‑hydroxy‑4‑(4‑hydroxy‑3‑methoxyphenyl)‑3‑hydroxymethyl‑7‑methoxy‑3,4‑dihydro‑2‑naphthaldehyde (VB-1) and vitedoin A (VB-2), together with another analogue namely detetrahydroconidendrin (VB-3), in rat plasma as well as tissues was conducted following oral administration of the extract of fruits of Vitex negundo var. cannabifolia. Diverse method validation assays in regard of selectivity, linearity, intra- and inter-day variations, matrix effect, and recovery were employed to demonstrate the newly developed method being able to fulfill the demands of rational quantitation. Overall, the current study offers a promising approach to accomplish confidence-enhanced quantitation in biological matrices.