Pharmaceutical Sciences Research Division, King's College London, London, UK.
J Sep Sci. 2011 May;34(10):1111-5. doi: 10.1002/jssc.201000905. Epub 2011 Apr 1.
Aristolochic acids are known to contribute to various renal disorders; therefore, expanding the availability of analytical methodology to detect these compounds is important in order to assess the quality of Chinese herbal medicines in which they can be found. Twelve medicinal herbal samples were procured from various sources and extracted in duplicate prior to a "fingerprint" analysis using conventional HPLC-DAD. Multivariate analysis was performed on the entire chromatographed fingerprints. The resulting output was a partial least-square discriminant analysis model, which was able to evaluate the potential presence of aristolochic acids I and II as well as providing an individual herbal "fingerprint". The results of this study provide evidence that the presence of aristolochic acids contained within certain herbal extractions could be detected using a simple method, although some limitations apply to this method for quality control, since newly detected samples for aristolochic acid (positives) will need further confirmation with purity checks or MS hyphenation.
已知马兜铃酸会导致各种肾脏疾病;因此,扩大分析方法的可用性以检测这些化合物非常重要,以便评估其中可能含有这些化合物的中草药的质量。从各种来源采购了 12 种药用草药样本,并在使用常规 HPLC-DAD 进行“指纹”分析之前进行了双重提取。对整个色谱指纹图谱进行了多变量分析。得到的输出是偏最小二乘判别分析模型,该模型能够评估马兜铃酸 I 和 II 的潜在存在情况,以及提供单个草药“指纹”。本研究结果表明,虽然该方法在质量控制方面存在一些局限性,但可以使用简单的方法检测某些草药提取物中所含的马兜铃酸,因为需要进一步用纯度检查或 MS 串联检查来确认新检测到的马兜铃酸(阳性)样本。