Prediction of Radix Astragali Immunomodulatory Effect of CD80 Expression from Chromatograms by Quantitative Pattern-Activity Relationship.

The current use of a single chemical component as the representative quality control marker of herbal food supplement is inadequate. In this CD80-Quantitative-Pattern-Activity-Relationship (QPAR) study, we built a bioactivity predictive model that can be applicable for complex mixtures. Through integrating the chemical fingerprinting profiles of the immunomodulating herb Radix Astragali (RA) extracts, and their related biological data of immunological marker CD80 expression on dendritic cells, a chemometric model using the Elastic Net Partial Least Square (EN-PLS) algorithm was established. The EN-PLS algorithm increased the biological predictive capability with lower value of RMSEP (11.66) and higher values of Rp2 (0.55) when compared to the standard PLS model. This CD80-QPAR platform provides a useful predictive model for unknown RA extract's bioactivities using the chemical fingerprint inputs. Furthermore, this bioactivity prediction platform facilitates identification of key bioactivity-related chemical components within complex mixtures for future drug discovery and understanding of the batch-to-batch consistency for quality clinical trials.

Identifying bioactive components in natural products through chromatographic fingerprint.

Bioactive component identification is a crucial issue in search for new drug leads. We provide a new strategy to search for bioactive components based on Sure Independence Screening (SIS) and interval PLS (iPLS). The method, which is termed as SIS-iPLS, is not only able to find out the chief bioactive components, but also able to judge how many components should be there responsible for the total bioactivity. The method is totally "data-driven" with no need for prior knowledge about the unknown mixture analyzed, therefore especially suitable for effect-directed work like bioassay-guided fractionation. Two data sets, a synthetic mixture system of twelve components and a suite of Radix Puerariae Lobatae extracts samples, are used to test the identification ability of the SIS-iPLS method.

Rapid simultaneous determination of major isoflavones of Pueraria lobata and discriminative analysis of its geographical origins by principal component analysis.

INTRODUCTION: Isoflavones are main bioactive components of Pueraria lobata (Willd.) Ohwi. Puerarin has been used as the marker compound in herb quality evaluation in the Chinese Pharmacopoiea. However, it is also important to include the other isoflavones present in the herb, such as daidzin, daidzein, genistin and genistein, in the evaluation as they also contribute to the overall bioactivity of the herb. OBJECTIVE: To develop a rapid and reliable method for simultaneous quantitation of isoflavones for P. lobata herb quality evluation. METHODOLOGY: The chromatographic separation was performed on an Agilent rapid resolution liquid chromatographic system through gradient elution. The developed method for the quantification of puerarin, daidzin, daidzein, genistin and genistein was fully validated. When it was applied to analyse the extracts of P. lobata, baseline separation was obtained within 10 min. RESULTS: The amounts of puerarin, daidzin, daidzein and genistin varied greatly among the samples although their chromatographic fingerprints were similar to each other. The 19 samples studied were classified into three clusters (I-III) by principal component analysis based on the amounts of puerarin, daidzin, daidzein and genistin. CONCLUSION: The classification result can be related to herbal origins, but the classification outcome from the chromatographic fingerprinting similarity approach did not provide any geographical origin information. This shows that bioactive constituents can reflect the intrinsic quality of P. lobata more accurately.

Recipe for uncovering the bioactive components in herbal medicine.

Using whole chromatographic profiles and measurements of total bioactivity as input, a quantitative pattern-activity relationship (QPAR) approach is proposed as a general method for providing two pieces of crucial information about complex bioactive mixtures available: (i) a model for predicting total bioactivity from the chromatographic fingerprint and (ii) the features in the chromatographic profile responsible for the bioactivity. While the first piece of information is already available through existing approaches, the second one results from our ability to remove dominant features in the chromatographic fingerprints which mask the components specifically related to pharmacological activity. Our targeted approach makes information about bioactivity available at the molecular level and provides possibilities for assessment of herbal medicine (HM) possible beyond just authentication and total bioactivity. As an example, the antioxidant property of the HM Radix Puerariae lobatae is measured through its reducing power toward a ferric ion complex. A partial least-squares (PLS) model is created to predict the antioxidant activity from the chromatographic fingerprint. Using the antioxidant activity as a target, the most discriminatory projection in the multivariate space spanned by the chromatographic profiles is revealed. From this target-projected component, the chromatographic regions most strongly connected to antioxidant activity are identified using the so-called selectivity ratio (SR) plot. The results are validated by prediction of samples not included in the modeling step.

Comparative analysis of essential oils from eight herbal medicines with pungent flavor and cool nature by GC-MS and chemometric resolution methods.

Systematic comparative research was conducted on essential oils from eight traditional Chinese medicines (TCM) of pungent flavor and cool nature because the essential oils are the main active ingredients of herbs of this kind. The work was based on their component analysis by gas chromatography-mass spectrometry (GC-MS), on their retention indices, as well as on chemometric resolution methods. A total of 144 compounds were tentatively identified, accounting for 69.0% to 91.8% of the total essential oils. It is worth noting that there are 67 compounds in at least three of these eight essential oils. Moreover, many biologically active compounds, such as hexanal, alpha-pinene, camphene, beta-pinene, p-cymene, limonene, eucalyptol, (Z)-ocimene, gamma-terpinene, camphor, p-menthone, 4-terpineol, alpha-terpineol, carvone, eugenol, caryophyllene, beta-farnesene, alpha-curcumene, beta-selinene, delta-cadinene, caryophyllene oxide, cedrol, n-hexadecanoic acid, benzaldehyde, benzeneacetaldehyde, phthalic acid diisobutyl ester, linoleic acid, tetradecanoic acid, (Z,Z,Z)-9,12,15-octadecatrienoic acid, eucalyptol, pentadecanoic acid, hexadecanoic acid methyl ester, linoleic acid methyl ester, exist in at least four of the eight essential oils. These results might help us to understand why the eight herbs are all of pungent flavor and cool nature according to the theory of TCM, and may provide a useful chemical basis for future research on herbs of this kind.

Rapid analysis of Radix puerariae by near-infrared spectroscopy.

A new, rapid analytical method using near-infrared spectroscopy (NIRS) was developed to differentiate two species of Radix puerariae (GG), Pueraria lobata (YG) and Pueraria thomsonii (FG), and to determine the contents of puerarin, daidzin and total isoflavonoid in the samples. Five isoflavonoids, puerarin, daidzin, daidzein, genistin and genistein were analyzed simultaneously by high-performance liquid chromatography-diode array detection (HPLC-DAD). The total isoflavonoid content was exploited as critical parameter for successful discrimination of the two species. Scattering effect and baseline shift in the NIR spectra were corrected and the spectral features were enhanced by several pre-processing methods. By using linear discriminant analysis (LDA) and soft independent modeling class analogy (SIMCA), samples were separated successfully into two different clusters corresponding to the two GG species. Furthermore, sensitivity and specificity of the classification models were determined to evaluate the performance. Finally, partial least squares (PLS) regression was used to build the correlation models. The results showed that the correlation coefficients of the prediction models are R=0.970 for the puerarin, R=0.939 for daidzin and R=0.969 for total isoflavonoid. The outcome showed that NIRS can serve as routine screening in the quality control of Chinese herbal medicine (CHM).

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.

Quantification of target components in complex mixtures using alternative moving window factor analysis and two-step iterative constraint method.

Alternative moving window factor analysis (AMWFA) has shown the powerfulness for comprehensive comparison and individual identification of chemical components among different but related mixture systems. However, quantification of these components can only be attained after extraction of all spectra of pure components in samples with least square technique. In this study, a novel two-step iterative constraint method (TICM) is developed for independent quantification of the interested target analytes. The pure chromatographic profiles of the components can be mined out from mixtures with high complexity using a two-step iterative operation and stepwise purification of the targets from interferers. Some effective constraints of chromatographic profiles, such as non-negative and single-peaked properties, as well as zero-concentration outside of elution windows of components, are employed to further improve the efficiency of the method. One of the strong advantages of TICM is simplification of complex mixtures to several sub-systems for processing easily with the help of AMWFA, as well as bi-linear property of data sets obtained from coupled chromatographic instruments. It meets the urgent requirements and challenges of qualitative and quantitative analysis of complicated systems with multi-component in the investigation of herbal medicines (HMs), metabonomics and systems biology. From the results of simulated LC-DAD data, GC-MS data of volatile chemical components in three kinds of ginseng with different growth conditions, and four different medicinal parts of the same herb, good performance of the proposed method is achieved.

Analytical comparison of different parts of Radix Angelicae Sinensis by gas chromatography coupled with mass spectrometry.

The three parts of Radix Angelicae Sinensis (Danggui) were reported to have different therapeutic effects. In order to investigate their chemical compositions of different parts of Danggui, gas chromatography-mass spectrometry (GC-MS) combined with chemometrics data analysis was applied to provide a more detailed study. Subwindow factor analysis (SFA) and a modified augmented evolving window orthogonal projection (AEWOP) method were used to resolve the batch GC-MS data sets from the Danggui samples. Then, t-test, Wilcoxon rank sum test, and principal component analysis (PCA) were applied to carry out the comparison job. The results indicate which components are found to have significant differences among the three parts. These findings may be helpful for further research of the pharmacological activities of Danggui.

Mass spectral profiling: an effective tool for quality control of herbal medicines.

Quality control of herbal medicines (HMs) is a big big headache because of the high complexity and unknown mechanism on disease treatment. In this work, mass spectral profiling, a new tool for data processing is proposed to help a lot in solving this problem as gas chromatography-mass spectroscopy (GC-MS) is used to detect both the active and non-active ingredients buried in HMs. The main idea of mass spectral profiling is employment of target m/z points of GC-MS data on the extraction of chromatographic profiles of pure and/or mixed compositions concerned. Further, the absolute or relative abundance at these m/z points can be utilized for results interpretation. With the help of this tool, the qualitative and quantitative information of chemical components within complicated HMs will be mined out effectively. It can then be recommended as reference indices to assess the importance of target compositions in HMs, such as efficacy evaluation on disease treatment of the active constituents. Mass spectral profiling with less data points significantly improves the possibility to get the rich information with no strong requirements of data preprocessing procedures, like alignment of shift of retention times among different chromatographic profiles. It is powerful for quality control of HMs coupled with pattern recognition techniques on high-throughput data sets. In this study, a commonly used herbal medicine, Houttuynia cordata Thunb and its finished injection products, were used to deliver the strategies. Absolutely, the working principles can be extended to the investigation of metabonomics with gas chromatography-time-of-flight-mass spectrometry (GC-MS-TOF). The good performance of mass spectral profiling shows that it can be a promising tool in the future studies of complex mixture systems.

Analysis of berberine and total alkaloid content in cortex phellodendri by near infrared spectroscopy (NIRS) compared with high-performance liquid chromatography coupled with ultra-visible spectrometric detection.

This paper developed a rapid method using near infrared spectroscopy (NIRS) to differentiate two species of cortex phellodendri (CP), cortex phellodendri chinensis (PCS) and cortex phellodendri amurensis (PAR), and to predict quantitatively the content of berberine and total alkaloid content in all cortex phellodendri samples. Three alkaloids, berberine, jatrorrhizine and palmatine were analyzed simultaneously with a Thermo ODS Hypersil column by gradient elution with a new mobile phase under high-performance liquid chromatography-diode array detection (HPLC-DAD). Berberine content determined by HPLC-DAD was exploited as a critical parameter for successful discrimination between them. Multiplicative scatter correction (MSC), second derivative and Savitsky-Golay (S.G.) were utilized together to correct the scattering effect and eliminate the baseline shift in all near infrared diffuse reflectance spectra as well as to enhance spectral features in order to give a better correlation with the results obtained by HPLC-DAD. With the use of principal component analysis (PCA), samples datasets were separated successfully into two different clusters corresponding to two species. Furthermore, a partial least squares (PLS) regression method was built on the correlation model. The results showed that the correlation coefficients of the prediction models were R=0.996 for the berberine and R=0.994 for total alkaloid content. The influences of water absorption bands present in the NIR spectra on the models were also investigated in order to explore the practicability of NIRS in routine use. The outcome showed that NIRS possibly acts as routine screening in the quality control of Chinese herbal medicine.

Pretreatments of chromatographic fingerprints for quality control of herbal medicines.

Pretreatments of chromatographic fingerprints are important for quality control of herbal medicines and they include data correction and data transformation. The data correction can reduce the variations of experimental procedures, and data transformation can put different weights on the different parts of the fingerprints. In this paper, a new target peak alignment (TPA) procedure has been proposed to correct the retention time shifts, multiplicative scattering correction (MSC) has been introduced for response correction. Then the similarity of the fingerprints with mean and median fingerprints is used to evaluate the quality of herbal medicines (HMs). Furthermore, different data transformation methods with kernel principal component analysis (PCA) have been applied to the data and their effects were discussed. The proposed approaches have been demonstrated by the essential oils data set of a herbal medicine, named Houttuynia cordata (HC), containing samples from different geographic origins. The experimental results indicate that the proposed approaches may be helpful in the quality control of herbal medicines by fingerprints.

Orthogonal projection (OP) technique applied to pattern recognition of fingerprints of the herbal medicine houttuynia cordata Thunb. and its final injection products.

It is a crucial issue to determine the origins of herbal medicinal materials and identify the quality grades and fakes of their final products collected from different pharmaceutical corporations. Pattern recognition technique may assist the manufacturers to achieve this purpose and effectively control the quality of their products. In this work, a widely used method in chemometrics, orthogonal projection (OP) technique, was applied to discrimination analysis and identification of fingerprints of the herbal medicine houttuynia cordata Thunb. (HCT) and its final injection products. The advantages of the OP technique are clearly shown after comparing with the conventional methods such as principal component analysis (PCA), Mahalanobis distance (MD), and similarity comparison method (SCM). Three different sources of medicinal material HCT and its final injection products from six different manufacturers were studied under 'sixfold', 'threefold' and 'threefold-bis' cross-validation procedures. The good performance of the proposed method in determination and identification of unknown samples shows it could be a powerful tool for quality control in herbal medicine production and other related research fields.

Alternative moving window factor analysis for comparison analysis between complex chromatographic data.

In this investigation, a novel chemometric method is developed for the analysis of five possible relationships of components or spectral features between two correlative but different hyphenated chromatographic systems. It is very helpful for comparison study of components present in different complex systems in both chemistry and systems biology. The proposed method, named alternative moving window factor analysis (AMWFA), could be utilized to determine the number of common components between different samples and then to identify their corresponding spectra half-automatically. AMWFA can alternatively be employed to mind for the selective information hiding in anyone of the two compared data X and Y, and to self-verify the resolution results by changing the extracted target matrices in analysis. From the results of comparison of simulated hyphenated chromatographic data, volatile chemical components in drug pair rhizoma ligustici chuanxiong-radix paeoniae rubra (RLC-RPR) and its single herbal medicines, and analysis of Angelica oral solution and its plasma sample after oral intake to rabbit, powerful ability of the proposed method is shown.

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.

Identification of essential components of Houttuynia cordata by gas chromatography/mass spectrometry and the integrated chemometric approach.

Starting with Biller-Biemann's work [J.E. Biller, K. Biemann, Anal. Lett. 7 (1974) 515], various kinds of approaches have been proposed to extract GC/MS data to obtain pure components responses. In this paper, an integrated chemometric approach is proposed, which combine four sequential steps, data pretreatment, component perception, resolution and component identification, and then the proposed approach is manipulated to analyze the essential oils of a herbal medicine named Houttuynia cordata (HC). On the basis of the selective information obtained from both chromatograms and mass spectra, the proposed integrated chemometric approach can resolve the two-way GC/MS responses matrix into pure chromatograms and mass spectra without any model assumption on the peak shape. The resolution results obtained from HC samples demonstrate the performance of the proposed approach and indicate that it may be a promising one for analyzing complex chromatograms.

Correction of retention time shifts for chromatographic fingerprints of herbal medicines.

In this study, the combination of chemometric resolution and cubic spline data interpolation was investigated as a method to correct the retention time shifts for chromatographic fingerprints of herbal medicines obtained by high-performance liquid chromatography-diode array detection (HPLC-DAD). With the help of the resolution approaches in chemometrics, it was easy to identify the purity of chromatographic peak clusters and then resolve the two-dimensional response matrix into chromatograms and spectra of pure chemical components so as to select multiple mark compounds involved in chromatographic fingerprints. With these mark components determined, the retention time shifts of chromatographic fingerprints might be then corrected effectively. After this correction, the cubic spline interpolation technique was then used to reconstruct new chromatographic fingerprints. The results in this work showed that, the purity identification of the chromatographic peak clusters together with the resolution of overlapping peaks into pure chromatograms and spectra by means of chemometric approaches could provide the sufficient chromatographic and spectral information for selecting multiple mark compounds to correct the retention time shifts. The cubic spline data interpolation technique was user-friendly to the reconstruction of new chromatographic fingerprints with correction. The successful application to the simulated and real chromatographic fingerprints of two Cortex cinnamomi, fifty Rhizoma chuanxiong, ten Radix angelicae and seventeen Herba menthae samples from different sources demonstrated the reliability and applicability of the approach investigated in this work. Pattern recognition based on principal component analysis for identifying inhomogenity in chromatographic fingerprints from real herbal medicines could further interpret it.

Information theory applied to chromatographic fingerprint of herbal medicine for quality control.

At present, the construction of chromatographic fingerprints plays an important role in the quality control of complex herbal medicines. In this work, information theory was applied to obtain chromatographic fingerprints with good performance. Moreover, according to the characteristics of the chromatographic fingerprints obtained, some modifications of the calculation of the information content were conducted. In comparison with the information content from several chromatographic fingerprints obtained, reliable chromatographic fingerprints with a high separation degree and uniform concentration distribution of chemical components could be determined. The successful application of information theory with modification to simulated chromatographic fingerprints together with real herbal medicines such as Rhizoma chuanxiong and Ginkgo biloba from different sources demonstrated clearly that the proposed method to determine chromatographic fingerprints was reasonable and reliable and it was user-friendly. Chromatographic fingerprints determined with high separation degrees and uniform concentration distribution of chemical ingredients might also chemically represent characteristic components of herbal medicines for quality control.

Analysis of volatile fractions of Schisandra chinensis (Turcz.) Baill. using GC-MS and chemometric resolution.

The two-dimensional data obtained from GC-MS has been used qualitatively and quantitatively to determine the components of the volatile fractions of Schisandra chinensis obtained by six different extraction methods. Sub-window factor analysis (SFA) was employed to confirm the identities of components determined in different samples. With the help of SFA, and other chemometric techniques, peak purity in the chromatograms was determined, and overlapping peaks were resolved to yield a pure chromatographic profile and mass spectrum for each component. It is demonstrated that the accuracy of qualitative and quantitative analysis may be greatly enhanced using chemometric resolution methods, such methods being particularly valuable with respect to the analysis of complex samples such as traditional Chinese medicines. It is further demonstrated that different extraction methods give rise to volatile fractions of S. chinensis which differ qualitatively and quantitatively in their composition.

Pien Tze Huang protects the liver against carbon tetrachloride-induced damage.

Pien Tze Huang, a traditional Chinese medicine, has been extensively used as a therapeutic drug in the treatment of liver diseases. In this study, we have examined its ability to protect the liver from carbon tetrachloride (CCl4)-induced damage in the mouse. Histological observations revealed that CCl4 treatment induced extensive degenerative changes in the hepatocytes surrounding the central veins of the liver. However, these changes were much reduced by more than 28% in mice fed with 0.5 mg of Pien Tze Huang/g body weight/dose (3 doses over 36 hr) prior to CCl4 treatment. The effects of Pien Tze Huang were then further investigated in a hepatoma cell line. Flow analysis showed that it had no significant effects on cell proliferation. When the ability of Pien Tze Huang to influence various response elements of important signal transduction pathways was examined in the hepatoma cell line, it was found that Pien Tze Huang stimulated an increase in the response of AP1, CRE and NFkappaB responsive elements. The transcriptional factors of these responsive elements are known to play important roles in regulating cell death and survival. We thus postulate that the ability of Pien Tze Huang to protect the liver from damage is attained through its ability to modulate the activity of these important signal transduction pathways.