基于UHPLC-QTOF MSE技术和多层次智能平台的Tongqiao Huoxue中化学成分和代谢物的表征
Pengyi Chen1, Lincheng Bai1, Xinyue Zheng1
1College of Medicine, Heilongjiang University of Traditional Chinese Medicine, Harbin, China.
Journal of separation science
|February 14, 2026
概括
这项研究开发了一种综合质谱工作流程,以分析传统中医 (TCM) 配方,如Tongqiao Huoxue Decoction (THD). 该方法准确地确定了THD中的235种化合物和体内101种代谢物,推动了TCM研究.
科学领域:
- 药理学 药理学是指药理学的学科.
- 分析化学 分析化学
- 传统中国医药 传统中国医药
背景情况:
- 阐明传统中医药 (TCM) 配方复杂的物质基础仍然是一个重大挑战.
- 现有的TCM单一软件分析管道存在诸如不完整的光谱库和依赖平台的偏差等局限性.
研究的目的:
- 建立一个集成的,多平台的UHPLC-QTOF MS^E数据分析工作流程,用于Tongqiao Huoxue Decoction (THD).
- 通过结合多种分析工具来进行全面的数据处理,克服传统单一软件管道的局限性.
- 描述THD的化学成分及其体内代谢物,以了解其在脑梗塞中的治疗机制.
主要方法:
- 为了UHPLC-QTOF MS^E数据分析,建立了一个结合UNIFI,MS-DIAL,QI和FBMN的集成工作流.
- 采用多角度识别系统共同处理数据,减少分析盲点和干扰.
- 来自接受THD治疗的老鼠的血清和尿液样本被分析以确定体内代谢物.
主要成果:
- 在THD中实现了235个化学成分的高可靠性表征.
- 在大鼠血清和尿液样本中确定了101种体内代谢物.
- 发现了主要的代谢物类,可能与脑梗塞中THD的药理动力学机制有关.
结论:
- 开发的工作流提供了一个严格,准确,可复制和高效的解决方案,用于分析生物和药物样本.
- 这项研究加深了对THD治疗脑梗塞的治疗材料基础的理解.
- 为基于质谱的TCM处方及其体内转换提供了一个新的,可泛化的方法论范式.
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