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UPLC-Q-TOF/MS coupled with multivariate statistical analysis as a powerful technique for rapidly exploring potential chemical markers to differentiate between radix paeoniae alba and radix paeoniae rubra

机译:UPLC-Q-TOF / MS与多变量统计分析相结合,是一种快速探索潜在化学标记物以区分白and和白a的强大技术

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摘要

To explore rapidly the potential chemical markers for differentiating Radix Paeoniae Alba and Radix Paeoniae Rubra, a method is proposed based on ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) coupled with multivariate statistical analysis. Batches of commercial samples were analyzed by UPLC-Q-TOF/MS. The datasets of tR-m/z pair, ion intensities and sample codes were further processed with orthogonal partial least squared discriminant analysis (OPLS-DA) to compare holistically the difference between these two kinds of samples. Then statistics were used to generate an S-plot, in which the variables (tR-m/z pair) contributing most to the difference were clearly depicted as points at the two ends of "S", and the components correlated to these ions should be regarded as the chemical markers. The identities of the most changed markers can be identified by comparing the mass/UV spectra and retention times with those of reference compounds and/or tentatively assigned by matching empirical molecular formulae with those of known compounds published in the literature. Using this proposed approach, albflorin, paeoniflorin, oxypaeoniflorin, benzoylpaeoniflorin, galloylalbiflorin and paeoniflorigenone were found to be the differentiating components for discrimination of Radix Paeoniae Alba and Radix Paeoniae Rubra. Moreover, paeoniflorin sulfonate and its isomer, isomaltopaeoniflorin sulfonate, were found to be the characteristic markers for all Radix Paeoniae Alba samples that were processed by sulfurdioxide gas fumigation. The results suggested that this newly established approach could be used to explore rapidly the potential chemical markers for herbs with similar chemical characteristics.
机译:为了快速探索区分赤e和赤Pa的潜在化学标记,提出了一种基于超高效液相色谱-四极杆飞行时间质谱(UPLC-Q-TOF / MS)结合多元统计分析的方法。通过UPLC-Q-TOF / MS分析了一批商业样品。使用正交偏最小二乘判别分析(OPLS-DA)对tR-m / z对,离子强度和样品编码的数据集进行进一步处理,以全面比较这两种样品之间的差异。然后使用统计数据生成S图,其中将对差异影响最大的变量(tR-m / z对)清楚地描绘为“ S”两端的点,并且与这些离子相关的成分应被视为化学标记。可以通过将质量/ UV光谱和保留时间与参考化合物的质量/ UV光谱和保留时间进行比较,和/或通过将经验分子式与文献中公开的已知化合物进行匹配,初步确定变化最大的标志物的身份。使用这种提议的方法,发现白花丹,pa药花色素,羟pa药花色素,苯甲酰pa药花素,没食子醛双花药素和pa药花香酮是区分Pa药和Alba药的鉴别成分。此外,发现pa药花青素磺酸盐及其异构体异麦芽酮异花青素磺酸盐是所有通过二氧化硫气体熏蒸处理的Rad药丹参样品的特征标记。结果表明,这种新建立的方法可用于快速探索具有相似化学特征的草药的潜在化学标记。

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