Comparing chemical fingerprints of herbal medicines using modified window target-testing factor analysis.

College of Chemistry and Chemical Engineering, Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha, 410083, P. R. China.
Analytical and Bioanalytical Chemistry (Impact Factor: 3.66). 03/2005; 381(4):913-24. DOI: 10.1007/s00216-004-2987-1
Source: PubMed

ABSTRACT A "chromatographic fingerprint" of a herbal medicine is essentially its chromatographic spectrum: a characteristic representation of its chemical components, some of which are pharmacologically active. Since a wide variety of factors, such as the geographical location, the harvest season, and the part used can influence the chemical constituents (and therefore the pharmacological activity) of any particular herbal medicine and its products, these fingerprints provide a way to compare and contrast the compositions of different variants of the same herbal medicine. In particular, it is possible to ascertain whether particular components present in one herbal fingerprint are also present in another fingerprint. In this work we use a novel method-modified window target-testing factor analysis (MWTTFA), based on the use of target factor analysis (TFA), fixed-size moving window evolving factor analysis (FSMWEFA) and a Gaussian shape correction to the chromatographic profiles-to achieve this end. To demostrate the strategy, the fingerprints of samples from garlics produced in different geographical locations were compared, as well as the fingerprints of samples taken from above-ground and below-ground parts of Houttuynia cordata Thunb. The results from these comparisons clearly show that four chemical components present in Hunan common edible garlic are absent in Xingping base garlic, while seven components are present in Xingping base garlic but absent in Hunan common edible garlic. Also, eleven components are present in the sample from the above-ground part of Houttuynia cordata Thunb but not in the sample from the below-ground part, while seven components are present in the sample from the below-ground part of Houttuynia cordata Thunb that are not present in the sample from the above-ground part. These interesting conclusions should be very useful for future pharmacological and clinical research into these herbal medicines, and the novel MWTTFA technique can also be used for quality control purposes.

  • [Show abstract] [Hide abstract]
    ABSTRACT: This work is mainly oriented to give an overview of the progress of multivariate curve resolution methods in the last 5 years. Conceived as a review that combines theory and practice, it will present the basics needed to understand what is the use, prospects and limitations of this family of chemometric methods with the latest trends in theoretical contributions and in the field of analytical applications.
    Critical Reviews in Analytical Chemistry 01/2006; 36:163-176. · 2.89 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Essential oils (EOs) are valuable natural products that are popular nowadays in the world due to their effects on the health conditions of human beings and their role in preventing and curing diseases. In addition, EOs have a broad range of applications in foods, perfumes, cosmetics and human nutrition. Among different techniques for analysis of EOs, gas chromatography-mass spectrometry (GC-MS) is the most important one in recent years. However, there are some fundamental problems in GC-MS analysis including baseline drift, spectral background, noise, low S/N (signal to noise) ratio, changes in the peak shapes and co-elution. Multivariate curve resolution (MCR) approaches cope with ongoing challenges and are able to handle these problems. This review focuses on the application of MCR techniques for improving GC-MS analysis of EOs published between January 2000 and December 2010. In the first part, the importance of EOs in human life and their relevance in analytical chemistry is discussed. In the second part, an insight into some basics needed to understand prospects and limitations of the MCR techniques are given. In the third part, the significance of the combination of the MCR approaches with GC-MS analysis of EOs is highlighted. Furthermore, the commonly used algorithms for preprocessing, chemical rank determination, local rank analysis and multivariate resolution in the field of EOs analysis are reviewed.
    Talanta 08/2011; 85(2):835-49. · 3.50 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A total of 25 sugarcane spirit extracts of six different Brazilian woods and oak, commonly used by cooperage industries for aging cachaça, were analyzed for the presence of 14 phenolic compounds (ellagic acid, gallic acid, vanillin, syringaldehyde, synapaldehyde, coniferaldehyde, vanillic acid, syringic acid, quercetin, trans-resveratrol, catechin, epicatechin, eugenol, and myricetin) and two coumarins (scopoletin and coumarin) by HPLC-DAD-fluorescence and HPLC-ESI-MSn. Furthermore, an HPLC-DAD chromatographic fingerprint was build-up using chemometric analysis based on the chromatographic elution profiles of the extracts monitored at 280 nm. Major components identified and quantified in Brazilian wood extracts were coumarin, ellagic acid, and catechin, whereas oak extracts shown a major contribution of catechin, vanillic acid, and syringaldehyde. The main difference observed among oak and Brazilian woods remains in the concentration of coumarin, catechin, syringaldehyde, and coniferaldehyde. The chemometric analysis of the quantitative profile of the 14 phenolic compounds and two coumarins in the wood extracts provides a differentiation between the Brazilian wood and oak extracts. The chromatographic fingerprint treated by multivariate analysis revealed significant differences among Brazilian woods themselves and oak, clearly defining six groups of wood extracts: (i) oak extracts, (ii) jatobá extracts, (iii) cabreúva-parda extracts, (iv) amendoim extracts, (v) canela-sassafrás extracts and (vi) pequi extracts.
    Journal of Separation Science 12/2009; 32(21):3681 - 3691. · 2.59 Impact Factor