Gas chromatography-mass spectrometry and chemometric resolution applied to the determination of essential oils in Cortex cinnamomi

Authentication and identification of Lamiaceae family with cyclic voltammetry fingerprint-PCA-LDA and determination of the used phenolic contents for classification using chromatographic analyses

Todays, it is essential to evaluate and check the quality of herbal medicines in to protect the public health. As medicinal plants, the extracts of labiate herbs are used directly or indirectly to treat a variety of diseases. Increase in their consumption has led to the fraud in herbal medicines. Hence, modern accurate diagnostic methods must be introduced to differentiate and authenticate these samples. Electrochemical fingerprints have not been evaluated for their capacity to distinguish and classify various genera within a family. Since it is essential to classify, identify, and distinguish between these closely related plants in order to guarantee the quality of the raw materials, the authenticity and quality of 48 dried and fresh Lamiaceae samples, which include Mint, Thyme, Oregano, Satureja, Basil, and Lavender with various geographic origins, were examined. The present study focused on (a) classification and authentication Labiate herbs extracts and (b) identification of active compounds in samples by Gas chromatography and HPLC methods. This was accomplished using principal component analysis (PCA) and PCA-linear discriminate analysis (PCA-LDA). The results of the clustering revealed that PCA-LDA categorized mint species more accurately than PCA. In addition to certain flavonoids including ferulic acid, apigenin, luteolin, and quercetin, HPLC and GC analysis of the ethanolic extract revealed the presence of phenolic acids such as rosmarenic acid, methyl rosmarenate, caffeic acid, cinnamic acid, and chlorogenic acid. Comparing results of PCA-LDA with chromatographic analysis show that the authentication and detection of fraud samples were correctly performed using chemometyrics technique based on CV fingerprints. Even, there was no need to completely identify components of the mint samples.

A review on phytochemistry, pharmacology and toxicology studies of Aconitum

Objectives

A number of species belonging to herbal genus Aconitum are well-known and popular for their medicinal benefits in Indian, Vietnamese, Korean, Japanese, Tibetan and Chinese systems of medicine. It is a valuable drug as well as an unpredictable toxic material. It is therefore imperative to understand and control the toxic potential of herbs from this genus. In this review, the ethnomedicinal, phytochemistry, pharmacology, structure activity relationship and toxicology studies of Aconitum were presented to add to knowledge for their safe application.

Key findings

A total of about 76 of all aconite species growing in China and surrounding far-east and Asian countries are used for various medical purposes. The main ingredients of aconite species are alkaloids, flavonoids, free fatty acids and polysaccharides. The tuberous roots of genus Aconitum are commonly applied for various diseases such as rheumatic fever, painful joints and some endocrinal disorders. It stimulates the tip of sensory nerve fibres. These tubers of Aconitum are used in the herbal medicines only after processing. There remain high toxicological risks of the improper medicinal applications of Aconitum. The cardio and neurotoxicities of this herb are potentially lethal. Many analytical methods have been reported for quantitatively and qualitatively characterization of Aconitum.

Summary

Aconitum is a plant of great importance both in traditional medicine in general and in TCM in particular. Much attention should be put on Aconitum because of its narrow therapeutic range. However, Aconitum's toxicity can be reduced using different techniques and then benefit from its pharmacological activities. New methods, approaches and techniques should be developed for chemical and toxicological analysis to improve its quality and safety.

Metabolite profiling and fingerprinting of Suillus species (Basidiomycetes) by electrospray mass spectrometry

The genus Suillus is known for the occurrence of a series of prenylated phenols and boviquinones. The extracts of four different Suillus species [S. bovinus, S. granulatus, S. tridentinus and S.variegatus) were investigated by using rapid ultra-performance Liquid chromatography/electrospray ionization mass spectrometry (UPLC/ESI-MS) and direct infusion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS). While direct infusion ESI-FT-ICR mass spectra give a fast overview concerning the elemental compositions of the compounds and, therefore, hints to the main metabolites, UPLC/ESI-tandem mass spectrometry is shown to be a useful tool for their identification. A principal component analysis (PCA) and hierarchical cluster analysis (HCA) based on the UPLC/ESI-MS clearly showed that the metabolite profiles can be used not only for the identification and classification of such fungi but also as a sophisticated and powerful tool for the chemotaxonomy of fungi. Furthermore, a clear discrimination of various types of biological samples (fruiting bodies versus mycelial cultures) is also possible. The orthogonal partial least squares (OPLS) two-class models of both UPLC/ESI-MS and ESI-FT-ICR-MS possess a clear differentiation of two compared Suillus species representing the between class variation and the within class variation. Based on generated S-plots and Loading plots, statistically significant metabolites could be identified as potential biomarker for one species.

Expression Of Selected Pathway-Marker Genes In Human Urothelial Cells Exposed Chronically To A Non-Cytotoxic Concentration Of Monomethylarsonous Acid

Bladder cancer has been associated with chronic arsenic exposure. Monomethylarsonous acid [MMA(III)] is a metabolite of inorganic arsenic and has been shown to transform an immortalized urothelial cell line (UROtsa) at concentrations 20-fold less than arsenite. MMA(III) was used as a model arsenical to examine the mechanisms of arsenical-induced transformation of urothelium. A previous microarray analysis revealed only minor changes in gene expression at one and two months of chronic exposure to MMA(III), contrasting with substantial changes observed at three months of exposure. To address the lack of information between two and three months of exposure (the critical period of transformation), the expression of select pathway marker genes was measured by PCR array analysis on a weekly basis. Cell proliferation rate, anchorage-independent growth, and tumorigenicity in SCID mice were also assessed to determine the early, persistent phenotypic changes and their association with the changes in expression of these selected marker genes. A very similar pattern of alterations in these genes was observed when compared to the microarray results, and suggested that early perturbations in cell signaling cascades, immunological pathways, cytokine expression, and MAPK pathway are particularly important in driving malignant transformation. These results showed a strong association between the acquired phenotypic changes that occurred as early as one to two months of chronic MMA(III) exposure, and the observed gene expression pattern that is indicative of the earliest stages in carcinogenesis.

Application of chemometrics in authentication of herbal medicines: a review

INTRODUCTION

Herbal medicines (HM) and their preparations have been widely used for hundreds of years all over the world. However, they have not been officially recognised due to a lack of adequate or accepted research methodology for their evaluation.

OBJECTIVE

To present a concise overview of the recent applications of chemometrics in solving the ambiguity of herbal medicine authentication during the last two decades.

METHODOLOGY

Studies involving the applications of chemometric analysis in combination with different analytical methods were classified according to the method of analysis used including chromatographic (HPLC, GC and CE), spectroscopic (NMR, IR, UV and ICP) and genetic analysis (RAPD). The purpose of each of these studies was classified into one of three main categories: taxonomic discrimination, quality assessment or classification between plants of different geographic origins.

RESULTS

This review comprises over 150 studies, covering the past two decades, emphasising the significance of chemometric methods in the discrimination of many herbs from closely related species and from adulterants, based on the principal bioactive components and phytochemical diversity. Furthermore, the differentiation between varieties and hybrids was achieved in addition to the prediction of the active components by quantitative methods of analysis. Discrimination according to geographical origin and localities, processing methods, DNA profiling and metabolomics were also efficiently investigated.

CONCLUSION

Chemometric methods have provided an efficient and powerful tool for the quality control and authentication of different herbs.

A metabolic profiling strategy for biomarker screening by GC-MS combined with multivariate resolution method and Monte Carlo

A GC-MS based metabolic profiling method via a multivariate resolution method and Monte Carlo PLS-DA is proposed for screening potential biomarkers, and applied to Type 2 diabetes mellitus. The metabolic profiles of plasma samples from healthy control and Type 2 diabetes mellitus patient groups were obtained by GC-MS, and 25 compounds considered as endogenous metabolites excluding glucose were identified. With the help of a multivariate resolution method, qualitative and quantitative results of the metabolic profiles were extracted for subsequent multivariate statistical analysis. In order to select potential biomarkers, responsible for the classification of the two groups, Monte Carlo PLS-DA was introduced. The distribution of the regression coefficients of PLS-DA models corresponding to the metabolites was obtained. The levels of metabolites with all positive coefficients were considered as decreased from healthy controls to patients, and all negative coefficients were considered as increased. Univariate t-test was employed to check for metabolites whose levels changed significantly. Metabolites identified as potential biomarkers of Type 2 diabetes mellitus were ten in total, namely lactate, alanine, α-hydroxyisobutyric acid, phosphate, serine, pyroglutamic acid, palmitic acid, stearic acid, 1-monopalmitin and cholesterol. Finally, canonical correlation analysis was used to explore the correlation between the selected ten metabolites and blood glucose, which was considered to be a routine parameter reflecting the disease state. The results showed that the ten selected metabolites correlated well with blood glucose (r = 0.81, p = 0.03), and may be considered as possible biomarkers of Type 2 diabetes mellitus. The results demonstrated that the proposed method may be a useful tool to discover potential biomarkers of diseases.

Determination of essential oil composition from Osmanthus fragrans tea by GC-MS combined with a chemometric resolution method

The essential oils of the Osmanthus fragrans tea (OFT), Osmanthus fragrans (OF) and green tea (GT) had been extracted by steam distillation and analyzed by gas chromatography-mass spectrometry (GC-MS) with the help of heuristic evolving latent projections (HELP), an effective chemometric resolution method (CRM). The overlapping peak clusters were resolved into pure chromatograms and pure mass spectra with HELP. The qualitative analysis was performed by similarity searches in the National Institute of Standards and Technology (NIST) mass spectra database with the obtained pure mass spectrum of each component. Identification of some compounds was also assisted by comparison of temperature-programmed retention indices (PTRI) with authentic standards included in our own laboratory database under construction. The quantitative results were obtained by overall volume integration (OVI) method. A total of 67, 73 and 53 components in essential oils of the OFT, OF and GT were identified, accounting for 90.83%, 93.65% and 89.97% total contents of the essential oil of OFT, OF and GT, respectively.

Chromatographic fingerprinting and related chemometric techniques for quality control of traditional Chinese medicines

Development of chromatographic fingerprint (CF) and related chemometric methods and their applications to quality control of traditional Chinese medicines (TCMs) were discussed. CF is essentially a kind of quality control method for TCMs (or Chinese herbal medicines). Also, it is a quality-relevant-data high-throughput and integral tool to explore chemically the complexity of TCMs. With the help of chemometrics, some difficulties in evaluation and analysis of CFs, such as calculation of information content, peak alignment, pattern analysis, deconvolution of overlapping peaks, etc. could be well solved. To further explore TCMs synergic quality, intensive study of CF coupled with chemometrics will create the possibility to achieve the aim to reveal the working mechanisms of TCMs and to further control and strengthen TCMs' intrinsic quality in a comprehensive manner.

Extraction of pure components from overlapped signals in gas chromatography-mass spectrometry (GC-MS)

Gas chromatography-mass spectrometry (GC-MS) is a widely used analytical technique for the identification and quantification of trace chemicals in complex mixtures. When complex samples are analyzed by GC-MS it is common to observe co-elution of two or more components, resulting in an overlap of signal peaks observed in the total ion chromatogram. In such situations manual signal analysis is often the most reliable means for the extraction of pure component signals; however, a systematic manual analysis over a number of samples is both tedious and prone to error. In the past 30 years a number of computational approaches were proposed to assist in the process of the extraction of pure signals from co-eluting GC-MS components. This includes empirical methods, comparison with library spectra, eigenvalue analysis, regression and others. However, to date no approach has been recognized as best, nor accepted as standard. This situation hampers general GC-MS capabilities, and in particular has implications for the development of robust, high-throughput GC-MS analytical protocols required in metabolic profiling and biomarker discovery. Here we first discuss the nature of GC-MS data, and then review some of the approaches proposed for the extraction of pure signals from co-eluting components. We summarize and classify different approaches to this problem, and examine why so many approaches proposed in the past have failed to live up to their full promise. Finally, we give some thoughts on the future developments in this field, and suggest that the progress in general computing capabilities attained in the past two decades has opened new horizons for tackling this important problem.

Traditional Chinese medicine and separation science

Traditional Chinese medicines (TCMs) are getting more and more popular nowadays in the whole world for improving health condition of human beings as well as preventing and healing diseases. TCM is a multi-component system with components mostly unknown, and only a few compounds are responsible for the pharmaceutical and/or toxic effects. The large numbers of other components in the TCM make the screening and analysis of the bioactive components extremely difficult. So, separation and analysis of the desired chemical components in TCM are very important subjects for modernization research of TCM. Thus, many novel separation techniques with significant advantages over conventional methods were introduced and applied to separation and analysis of the chemical constituents in TCM. This review presents just a brief outline of the applications of different separation methods for the isolation and analysis of TCM constituents.

Recent advances in the compound-oriented and pattern-oriented approaches to the quality control of herbal medicines

The current approaches to the quality control of herbal medicines are either compound-oriented or pattern-oriented, the former targeting specific components with some known chemical properties and the latter targeting all detectable components. The marker approach uses specific chemical compounds with known molecular structures, while the multi-compound approach uses both chemical compounds with known structures and those with partial chemical information e.g. retention times, mass spectra and ultraviolet spectra. Apart from chromatographic techniques, new techniques such as oscillating and electrochemistry fingerprints have been developed for quality control. Chemometric resolution methods are widely used for component deconvolution and data comparison. Pattern recognition techniques are used for authentication of herbal medicines.

Qualitative and quantitative analysis in quality control of traditional Chinese medicines

Separation techniques with high efficiency and sensitive detection have been widely used for quality control of traditional Chinese medicines (TCMs). High-performance liquid chromatography, gas chromatography, and capillary electrophoresis are commonly used to separate various components in TCMs. Ultraviolet detection, fluorescence detection, evaporative light-scattering detection, mass spectrometry and nuclear magnetic resonance can be applied to separation techniques for qualitative and quantitative analysis of TCMs. The development of quality control for TCMs based on quantitative and qualitative analysis from 2000 to 2007 are reviewed; the fingerprint technique is also discussed due to its broad application in the quality control of TCMs. Prospects for further research based on our primary results are also discussed.

Development of a method for analysis of Iranian damask rose oil: combination of gas chromatography-mass spectrometry with Chemometric techniques

Gas chromatography-mass spectrometry (GC-MS) combined with Chemometric resolution techniques were proposed as a method for the analysis of volatile components of Iranian damask rose oil. The essential oil of damask rose was extracted using hydrodistillation method and analyzed with GC-MS in optimized conditions. A total of 70 components were identified using similarity searches between mass spectra and MS database. This number was extended to 95 components with concentrations higher than 0.01% accounting for 94.75% of the total relative content using Chemometric techniques. For the first time in this work, an approach based upon subspace comparison is used for determination of the chemical rank of GC-MS data. The peak clusters were resolved using heuristic evolving latent projection (HELP) and multivariate curve resolution-alternating least square (MCR-ALS) by applying proper constraints, and the combination of both methods for some cases. It is concluded that a thorough analysis of the complex mixtures such as Iranian damask rose requires sophisticated GC-MS coupled with the Chemometric techniques.

Using mean field approach independent component analysis to fatty acid characterization with overlapped GC–MS signals

In this paper, mean field independent component analysis (MF-ICA) was applied as a deconvolution method to separate complex gas chromatographic-mass spectrometric (GC-MS) signals obtained from fatty acid analysis of fish oil. The separation which is a blind operation was used as a complementary method in identification of the unknown components of a mixture and in quantification purposes, as well. In MF-ICA, the sources (mass spectra) are recovered from the mean of their posterior distributions and mixing matrix (chromatograms) and noise level are estimated through the maximum a posterior (MAP) solution. The number of independent components (ICs) in the overlapping signals can be estimated by the difference between the reconstructed and original GC-MS data. It was found that the chromatographic profiles and the mass spectra of the components in overlapping multicomponent GC-MS data can be accurately recovered with and without previously background correction. The resolved mass spectral sources satisfactory are identified using mass spectral search system. The recovered chromatographic area and the relative content of each analyte considering selected number of ICs are calculated and the results are compared with the ones obtained previously by using heuristic evolving latent projections (HELP) method.

Quality assessment of Cortex cinnamomi by HPLC chemical fingerprint, principle component analysis and cluster analysis

HPLC fingerprint analysis, principle component analysis (PCA), and cluster analysis were introduced for quality assessment of Cortex cinnamomi (CC). The fingerprint of CC was developed and validated by analyzing 30 samples of CC from different species and geographic locations. Seventeen chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression of the HPLC fingerprints. The correlation coefficients of similarity in chromatograms were higher than 0.95 for the same species while much lower than 0.6 for different species. Besides, two principal components (PCs) have been extracted by PCA. PC1 separated Cinnamomum cassia from other species, capturing 56.75% of variance while PC2 contributed for their further separation, capturing 19.08% variance. The scores of the samples showed that the samples could be clustered reasonably into different groups corresponding to different species and different regions. The scores and loading plots together revealed different chemical properties of each group clearly. The cluster analysis confirmed the results of PCA analysis. Therefore, HPLC fingerprint in combination with chemometric techniques provide a very flexible and reliable method for quality assessment of traditional Chinese medicines.

The study on the chromatographic fingerprint of Fructus xanthii by microwave assisted extraction coupled with GC–MS

The chromatographic fingerprint of Fructus xanthii, a kind of Traditional Chinese Medicines (TCMs), was studied by microwave assisted extraction (MAE) coupled with gas chromatography-mass spectrometry (GC-MS). The optimized conditions of MAE were examined. The method of MAE was evaluated in contrast to heat reflux extraction (HRE) method and by the validation tests of precision and repeatability. The relative standard deviations (RSDs) of retention time and peak area of each component were less than 0.2% and 6%, respectively. Twenty-five different batches of samples collected from different producing areas and the toasting process of F. xanthii were studied. The characteristic differences in the producing areas and the chemical variances in the toasting process were obtained and studied by principal components analysis (PCA) and similarity analysis. The trends of main varying components were attempted to be described in order to specify the related pharmacology and toxicology in crude and toasted samples. The results suggest that the chromatographic fingerprint developed by MAE coupled with GC-MS provides useful information to reveal the quality of F. xanthii and evaluate the quality changes in the producing process.

Use of gas chromatography–mass spectrometry combined with resolution methods to characterize the essential oil components of Iranian cumin and caraway

Gas chromatography-mass spectrometry combined with iterative and non-iterative resolution methods was used to characterize the essential oil components of Iranian cumin and caraway. Orthogonal projection resolution (OPR) as a non-iterative and distance-selection-multivariate curve resolution-alternative least squares (DS-MCR-ALS) as an iterative method were used as auxiliary means to the analysis in the case of overlapping peaks. A total of 19 and 39 components were identified by direct similarity searches for cumin and caraway oils, respectively. These numbers were extended to 49 and 98 components, respectively with the help of chemometric techniques. Major constituents in cumin are gamma-terpinene (15.82%), 2-methyl-3-phenyl-propanal (32.27%) and myrtenal (11.64%) and in caraway are gamma-terpinene (24.40%), 2-methyl-3-phenyl-propanal (13.20%) and 2, 4(10)-thujadien (14.02%). In spite of different cultivation conditions, there are 28 components which are common between the two seeds.

Variable selection for discriminating herbal medicines with chromatographic fingerprints

When discriminating herbal medicines with pattern recognition based on chromatographic fingerprints, typically, the majority of variables/data points contain no discrimination information. In this paper, chemometric approaches concerning forward selection and key set factor analysis using principal component analysis (PCA), unweighted and weighted methods based on the inner- and outer-variances, Fisher coefficient from the between- and within-class variations were investigated to extract representative variables. The number of variables retained was determined based on the cumulative variance percent of principal components, the ratio of observations to variables and the factor indicative function (IND). In order to assess the methods for variable selection and criteria levels to determine the number of variables retained, the original and reduced datasets were compared with Procrustes analysis and a weighted measure of similarity. Moreover, the tri-variate plots of the first three PCA scores were used to visually examine the reduced datasets in low dimensional space. Herbal samples were finally discriminated by use of Bayes discrimination analysis with the reduced subsets. The case study for 79 herbal samples showed that, the methods of forward selection associating the variables with the loadings closest to 0 and key set factor analysis were preferable to determine the representative variables. Procrustes analysis and the weighted measure were not indicative to extract representative variables. High matching between the original and reduced datasets did not suggest high prediction accuracy. Visually examining the PC1-PC2-PC3 scores projection plots with the reduced subsets, not all the herb samples could be separated due to the complexity of chromatographic fingerprints.

Characterization of essential oil components of Iranian geranium oil using gas chromatography–mass spectrometry combined with chemometric resolution techniques

The essential oil components of geranium oil cultivated in center of Iran were identified and determined using gas chromatography-mass spectrometry data combined with the chemometric resolution techniques. A total of 61 components accounting for 91.51% were identified using similarity searches between the mass spectra and MS database. This number was extended to 85 components using chemometric techniques. Various chemometric methods such as morphological scores, simplified Borgen method (SBM) and fixed size moving window evolving factor analysis (FSMWEFA) were used for determining the number of components, pure variables, zero concentration and selective regions. Then the overlapping peak clusters were resolved into pure chromatograms and pure mass spectra using heuristic evolving latent projections (HELP) method. A characteristic feature of the Iranian geranium oil is the absence of 10-epi-gamma-eudesmol in its constituents compared with the oil from northern and southern parts of India. The results of this work show that combination of hyphenated chromatographic methods and resolution techniques provide a complementary method for accurate analysis of essential oils.

Separation Methods for Toxic Components in Traditional Chinese Medicines

Traditional Chinese medicines (TCMs) with many unique functions for treating diseases have attracted the interest of people worldwide. They have been popularly utilized for therapy and health promotion in most Asian countries and even in many European and North American countries. However, it should be clearly noted that TCMs are mixtures with complicated composition usually containing hundreds, even thousands of chemically different constituents, and it is the multiple constituents that work synthetically to determine the ultimate effect of a formula of TCM. Meanwhile, some components with toxicity in some TCMs, having various negative effects on different parts of body, may do serious harm to people's health; such harm in particular requires our attention. In this article, applications of different chromatographic and electrophoretic techniques in the analysis of toxic components in TCMs in recent decades have been comprehensively reviewed and some hyphenated procedures (combinations of two kinds of measurement) applied in this field are also summarized.

Analysis of volatile components from Cortex cinnamomi with hyphenated chromatography and chemometric resolution

In this paper, the combination of hyphenated chromatography and chemometric resolution was investigated as a method to qualitatively and quantitatively determine volatile components in Cortex cinnamomi from four main producing areas. With the help of chemometric resolution approaches, whether the chromatographic elution of chemical components is featured by "first-in-first-out" or embedded peaks could be determined. Upon this useful information obtained, the matrix data generated by hyphenated chromatography could be uniquely resolved into pure chromatogram and spectrum of each chemical component involved followed by qualitative and quantitative analysis. The results obtained in this work showed that, 94, 88, 93 and 89 volatile components were separated and 63, 60, 60 and 58 of them qualitatively and quantitatively determined representing about 93.39, 93.62, 92.03 and 92.59% of the total relative content, respectively. The combination of hyphenated chromatography with chemometric resolution could greatly enhance the chromatographic separation and spectral qualitatively determination ability so as to qualitatively and quantitatively detect many more volatile components and improve the analysis accuracy.