Identification and comparative oridonin metabolism in different species liver microsomes by using UPLC-Triple-TOF-MS/MS and PCA

Metabolite identification of ursolic acid in mouse plasma and urine after oral administration by ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry

“…10,11 Recently, liquid chromatography coupled with mass spectrometry (LC-MS) is an effective technique for qualitative and quantitative analysis of drug metabolites in various biological samples. [12][13][14] Among the various LC-MS instruments, UPLC-Q/ TOF-MS is a reliable and efficient technique for complex samples due to its high detection sensitivity and accuracy. [15][16][17][18] MS E (where E represents the collision energy) is a tandem mass spectrometry method that obtains highly accurate parent ion and fragment ion information.…”

Ultrahigh‐performance liquid chromatography coupled with triple quadrupole and time‐of‐flight mass spectrometry for the screening and identification of the main flavonoids and their metabolites in rats after oral administration of Cirsium japonicum DC. extract

“…In this study, the metabolite identification strategy was based on a Triple TOF™ instrument with on‐line data acquisition via MMDF, DBS‐dependent and multiple post‐acquisition data‐mining technologies. The detailed analytical strategy was as follows . (1) On‐line data were acquired using a full scan, and accurate MS/MS data were obtained using an effective MMDF and DBS‐dependent data acquisition method.…”

“…The detailed analytical strategy was as follows. 31 (1) On-line data were acquired using a full scan, and accurate MS/MS data were obtained using an effective MMDF and DBS-dependent data acquisition method.…”

Distinguishing Smilax glabra and Smilax china rhizomes by flow-injection mass spectrometry combined with principal component analysis

“…The MS data of each sample consisted of a matrix (ion counts versus mass-to-charge ratio over a range of 120-1500). The massive MS data obtained were handled with PCA (10,(20)(21)(22), placing the classification results on a sound statistical ground. Data of all samples were exported to Excel (Version 2013, 64-bit, Microsoft Corporation, USA) for pre-processing, and were then analyzed by statistical software SIMCA (Version 14.1.0.2047, 64-bit, MKS Umetrics, Umea, Sweden) for PCA and OPLS-DA.…”