NFSWI-DDA,使HRMSTQ-MS

Rongrong Li1, Xinyi Jiao1, Xiaolin Wu2

  • 1State Key Laboratory of Component-based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, PR China; Haihe Laboratory of Modern Chinese Medicine, Tianjin, 301617, PR China.

Talanta
|January 15, 2025
PubMed
概括

通过一种新的非固定细分窗口间隔数据依赖获取 (NFSWI-DDA) 方法,提高了非目标代谢物识别. 这种方法增强了MS2的覆盖范围,以准确识别代谢物和在生物样本中进行有针对性的分析.