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首页> 外文期刊>Journal of separation science. >Non-targeted metabolite fingerprinting of oriental folk medicine Angelica acutiloba roots by ultra performance liquid chromatography time-of-flight mass spectrometry
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Non-targeted metabolite fingerprinting of oriental folk medicine Angelica acutiloba roots by ultra performance liquid chromatography time-of-flight mass spectrometry

机译:超高效液相色谱飞行时间质谱对东方民间药当归根的非目标代谢物指纹图谱

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摘要

The potential of ultra-performance (UP)LC-TOF-MS based metabolite Fingerprinting was explored in the attempt to establish a standard methodology for the quality control of dried angelica roots (Angelica acutiloba) in commercial markets. Accurate, mass chromatographic fingerprints of positive and negative ion modes were collected simultaneously at a high-throughput manner with high resolution and sensitivity, where analysis of hydrophobic, low molecular weight compounds, which includes secondary metabolites, could be achieved. The comparison of various metabolite profiles was performed through the use of chemometric technique, ill which distinct partitioning of root samples was effectively achieved by principal component analysis. The discrimination was illustrated to have been subjective to cultivation area and was reported to be all important influential Factor for quality determination. Further insights to the chemical constituents in relation to quality were attained where some ion markers significantly linked to dissociation of angelica roots were tentatively identified as some secondary metabolites. Reliable classification models by partial least square discriminant analysis gave (rood capability in categorizing test set samples. Overall, through the utilization of UPLC-TOF-MS, analysis Could be attained with great sufficiency and accuracy for angelica root discrimination.
机译:探索了基于超高性能(UP)LC-TOF-MS的代谢物指纹图谱的潜力,以试图建立用于商业市场中干燥当归根(Angelica acutiloba)质量控制的标准方法。同时以高通量,高分辨率和高灵敏度收集正离子和负离子模式的准确的质谱指纹图谱,从而可以分析包括次生代谢物的疏水性,低分子量化合物。通过使用化学计量学技术比较了各种代谢物谱,这是通过主成分分析有效地实现了根样品的明显分配。说明了该歧视是受耕地主观因素的影响,据报告是所有影响质量确定的重要因素。通过初步鉴定一些与当归根解离密切相关的离子标记物,获得了与质量有关的化学成分的进一步见解。通过偏最小二乘判别分析得到的可靠分类模型具有(对测试集样本进行分类的能力。总体而言,通过使用UPLC-TOF-MS,可以对当归根进行充分,准确的分析。

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