Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
An analytical assay based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) technique for absolute quantification of vancomycin in complexed biological matrix was developed in this study. Reversed phase column with gradient elution was chosen for chromatographic separation of vancomycin and internal standard (IS) norancomycin. Sample pretreatment was performed by micro-solid phase extraction (μ-SPE) with Oasis® MAX μElution Plate (I.D., 30 μm). Multiple reaction monitoring (MRM) transition was chosen for monitoring of the analytes. For vancomycin, mass-to-charge ratio (m/z) of the MRM transition was 725.3→144.1; For norvancomycin, m/z of the MRM transition was 718.3→144.2. The running time was 3 minutes for each sample. The UHPLC-MS/MS method showed a good linear relationship (R≥0.995) in the concentration range of 0.5-100 μg/mL. The intra- and inter-day accuracies (relative error, RE) are within the range of -3.44 %-1.50 % and precisions are between 3.48 % and 10.19 %. μ-SPE could enrich the analytes and decrease the endogenous interferences, thereby improving the selectivity and sensitivity of the method. The analytical assay is selective, accurate and reproducible. The assay was successfully applied to therapeutic drug monitoring of vancomycin in clinical application.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jpba.2025.116729 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The barriers for uptake of artificial intelligence in hepatology and how to overcome them.
J Hepatol
July 2025
Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany; Department of Medicine I, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, 01307 Dresden, Germany; Medical Oncology, National Center for Tumor Disease
Artificial intelligence (AI) methods in hepatology have proliferated since the mid-2010s, with numerous publications and some regulatory approvals. Yet, adoption of AI methods in real-world clinical practice and clinical research remains limited. Despite clear benefits of using AI to analyze complex data types in hepatology, such as histopathology, radiology images, multi-omics and more recently, natural language patient data, there are still substantial barriers and challenges to its integration into routine clinical workflows.
View Article and Find Full Text PDFDiscrimination of isomeric dihydroflavone and chalcone by the boosting optimal collision energy-liquid chromatography-tandem mass spectrometry: A case study of pharmacokinetics in honey-fried licorice.
J Chromatogr B Analyt Technol Biomed Life Sci
September 2025
Research Center for Chinese Medicine Analysis and Transformation, Beijing University of Chinese Medicine, Beijing 100029, China; Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China. Electronic address:
The occurrence of isomeric dihydroflavone and chalcone, two important subfamilies of flavonoid class, extensively happens in herbal medicines. However, identical MS/MS spectra make the identity confirmation a tough job, the complexity will be further boosted in biological samples. Inspired by that isomers possess distinct inherent physicochemical parameters, optimal collision energy (OCE), which is positively correlated with the bond dissociation energies (BDEs), was evaluated towards differentiating isomeric dihydroflavone and chalcone.
View Article and Find Full Text PDFMRMAssayDB: a comprehensive integrated resource for targeted proteomics assays.
Expert Rev Proteomics
September 2025
Gerald Bronfman Department of Oncology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada.
Introduction: Targeted quantitative proteomics is vital for accurate protein measurement in biological samples. Techniques like Multiple Reaction Monitoring (MRM or SRM) and Parallel Reaction Monitoring (PRM), often used with isotopically-labeled internal standards, provide absolute quantification and represent the current gold standard. However, developing and validating assays for individual proteins remains labor-intensive.
View Article and Find Full Text PDFCLAW-MRM: omprehensive ipidomics utomation orkflow for ultiple eaction onitoring Using Large Language Models.
Anal Chem
September 2025
Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, Indiana 47907, United States.
Lipidomic profiling generates vast datasets, making manual annotation and trend interpretation complex and time-intensive. The structural and chemical diversity of the lipidome further complicates the analysis. While existing tools support targeted lipid identification, they often lack automated workflows and seamless integration with statistical and bioinformatics tools.
View Article and Find Full Text PDFPredictive signal modeling and multi-rate filtering in accelerated cardiac MRI.
Magn Reson Med
August 2025
The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada.
Purpose: True real-time cardiac MRI (CMR), necessary for capturing live cardiac dynamics and imaging irregular cardiac rhythms, remains challenging. In this article, we move toward real-time CMR in multiple reconstruction frameworks via strategies to predict cardiac motion, improve computational efficiency, reduce artifacts, and preserve spatial resolution.
Theory And Methods: A published predictive signal model (PMOT) for imaging irregular cardiac dynamics was modified (mPMOT) to enable efficient computation of state-transition matrices for predicting cardiac motion, as training PMOT is computationally expensive.