Published We extend our congratulations to Assoc. Prof. Dr. Sakda Khoomrung of the Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, on his latest research publication in the Computational and Structural Biotechnology Journal on July 8, 2025.
Read the full article here: https://www.sciencedirect.com/science/article/pii/S2001037025002739
This study introduces a unique LC-QTOF-MSE method for targeted quantification, post-targeted screening, and untargeted metabolomics profiling in human urine. The technique, which utilizes MS1-based quantification, demonstrated excellent performance in terms of linearity (R² > 0.99), accuracy (84–131%), and precision (1–17% RSD).
Although less sensitive than traditional LC-triple quadrupole MS, this approach proves especially valuable for analyzing metabolites with weak fragmentation, making it highly suitable for the analysis of urinary metabolites.
A key advancement in the study is the integration of the Siriraj Metabolomics Data Warehouse (SiMD), which significantly enhances the accuracy and speed of metabolite identification. The SiMD platform is accessible at https://si-simd.com.
The method was successfully applied to urine samples from 100 healthy individuals, revealing distinct sex-related differences in metabolite profiles. These findings underscore the practicality and relevance of LC-QTOF-MSE with SiMD as a robust and efficient tool for clinical metabolomics research.
