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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Zhang, Yufeng Wang, Xiaoan Wo, Siukwan Ho, Hingman Han, Quanbin Fan, Xiaohui Zuo, Zhong |
| Description | Country affiliation: China Author Affiliation: Zhang Y ( School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.); Wang X ( School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.); Wo S ( School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.); Ho H ( School of Chinese Medicine, Hong Kong Baptist University, 7 Baptist University Road, Kowloon Tong, Hong Kong, China.); Han Q ( School of Chinese Medicine, Hong Kong Baptist University, 7 Baptist University Road, Kowloon Tong, Hong Kong, China.); Fan X ( College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, PR China.); Zuo Z ( School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China. Electronic address: joanzuo@cuhk.edu.hk.) |
| Abstract | Resolving components and determining their pseudo-molecular ions (PMIs) are crucial steps in identifying complex herbal mixtures by liquid chromatography-mass spectrometry. To tackle such labor-intensive steps, we present here a novel algorithm for simultaneous detection of components and their PMIs. Our method consists of three steps: (1) obtaining a simplified dataset containing only mono-isotopic masses by removal of background noise and isotopic cluster ions based on the isotopic distribution model derived from all the reported natural compounds in dictionary of natural products; (2) stepwise resolving and removing all features of the highest abundant component from current simplified dataset and calculating PMI of each component according to an adduct-ion model, in which all non-fragment ions in a mass spectrum are considered as PMI plus one or several neutral species; (3) visual classification of detected components by principal component analysis (PCA) to exclude possible non-natural compounds (such as pharmaceutical excipients). This algorithm has been successfully applied to a standard mixture and three herbal extract/preparations. It indicated that our algorithm could detect components' features as a whole and report their PMI with an accuracy of more than 98%. Furthermore, components originated from excipients/contaminants could be easily separated from those natural components in the bi-plots of PCA. |
| File Format | HTM / HTML |
| ISSN | 00032670 |
| Volume Number | 853 |
| e-ISSN | 18734324 |
| Journal | Analytica Chimica Acta |
| Language | English |
| Publisher | Elsevier |
| Publisher Date | 2015-01-01 |
| Publisher Place | Netherlands |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Discipline Analytical Discipline Chemistry Algorithms Chromatography, Liquid Methods Mass Spectrometry Statistics As Topic Drugs, Chinese Herbal Chemistry Molecular Weight Principal Component Analysis Time Factors Journal Article Research Support, Non-u.s. Gov't |
| Content Type | Text |
| Resource Type | Article |
| Subject | Spectroscopy Environmental Chemistry Analytical Chemistry Biochemistry |
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