首页> 外文期刊>Journal of Molecular Structure >Discrimination and chemical characterization of different Paeonia lactifloras (Radix Paeoniae Alba and Radix Paeoniae Rubra) by infrared macro-fingerprint analysis-through-separation
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Discrimination and chemical characterization of different Paeonia lactifloras (Radix Paeoniae Alba and Radix Paeoniae Rubra) by infrared macro-fingerprint analysis-through-separation

机译:红外宏指纹-分离指纹图谱鉴别和鉴别不同的Pa药((药)和e药(药材)

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Paeonia lactiflora, a commonly used herbal medicine (HM) in Traditional Chinese Medicine (TCM), mainly has two species, Radix Paeoniae Alba (RPA) and Radix Paeoniae Rubra (RPR), for different clinical applications in TCM. For expounding the chemical profile of RPA and RPR and ensuring the clinical efficacy and safety, an infrared macro-fingerprint analysis-through-separation method integrated with statistical pattern recognition was developed to analyze and discriminate the two Paeonia lactifloras. In IR spectra, the major difference between the two was in the range of 1200-900 cm(-1): the strongest peak of RPA was at 1024 cm(-1), while that of RPR was 1049 cm(-1). The difference was magnified in second derivative spectra. The findings were further verified by investigating the separation process of total glucosides, stepwisely monitored by both of IR and UPLC-MS/MS. Simultaneously, the aqueous extracts of RPA and RPR had been separated continuously to acquire the comprehensively hierarchical chemical characteristics for undoubtedly identification and subsequently discrimination of the two herbs. Moreover, 60 batches of the two HMs (30 for each) were objectively classified by principal component regression (PCR) model based on IR macro-fingerprints. (C) 2015 Elsevier B.V. All rights reserved.
机译:药(Paeonia lactiflora)是中药(TCM)中常用的草药(HM),主要有两种药材:Rad药白RP(RPA)和Rad药红柏(RPR),用于中药的不同临床应用。为了阐明RPA和RPR的化学特征并确保临床疗效和安全性,开发了一种结合统计模式识别的红外宏指纹-分离分离法来分析和区分这两种Pa药。在红外光谱中,两者之间的主要差异在1200-900 cm(-1)范围内:RPA的最强峰在1024 cm(-1),而RPR的最强峰在1049 cm(-1)。在二阶导数光谱中差异被放大。通过研究总糖苷的分离过程进一步证实了这些发现,并通过IR和UPLC-MS / MS进行了逐步监测。同时,RPA和RPR的水提物已连续分离,以获取全面分级的化学特性,从而无疑地鉴定和随后区分了两种草药。此外,通过基于IR宏指纹的主成分回归(PCR)模型,对60个批次的两个HM(每个30个)进行了客观分类。 (C)2015 Elsevier B.V.保留所有权利。

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