Discrimination and classification techniques applied on Mallotus and Phyllanthus high performance liquid chromatography fingerprints.

Mallotus and Phyllanthus genera, both containing several species commonly used as traditional medicines around the world, are the subjects of this discrimination and classification study. The objective of this study was to compare different discrimination and classification techniques to distinguish the two genera (Mallotus and Phyllanthus) on the one hand, and the six species (Mallotus apelta, Mallotus paniculatus, Phyllanthus emblica, Phyllanthus reticulatus, Phyllanthus urinaria L. and Phyllanthus amarus), on the other. Fingerprints of 36 samples from the 6 species were developed using reversed-phase high-performance liquid chromatography with ultraviolet detection (RP-HPLC-UV). After fingerprint data pretreatment, first an exploratory data analysis was performed using Principal Component Analysis (PCA), revealing two outlying samples, which were excluded from the calibration set used to develop the discrimination and classification models. Models were built by means of Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Classification and Regression Trees (CART) and Soft Independent Modeling of Class Analogy (SIMCA). Application of the models on the total data set (outliers included) confirmed a possible labeling issue for the outliers. LDA, QDA and CART, independently of the pretreatment, or SIMCA after "normalization and column centering (N_CC)" or after "Standard Normal Variate transformation and column centering (SNV_CC)" were found best to discriminate the two genera, while LDA after column centering (CC), N_CC or SNV_CC; QDA after SNV_CC; and SIMCA after N_CC or after SNV_CC best distinguished between the 6 species. As classification technique, SIMCA after N_CC or after SNV_CC results in the best overall sensitivity and specificity.

Multivariate data analysis to evaluate the fingerprint peaks responsible for the cytotoxic activity of Mallotus species.

The Mallotus genus comprises numerous species used as traditional medicines in oriental countries and provides scientists a broad basis in the search for pharmacologically active constituents. In this paper, the cytotoxicity of 39 Mallotus extracts, different in species, part of the plant used, origin, and harvest season, is evaluated combining cytotoxicity assays with fingerprint technology and data handling tools. At first, the antiproliferative activity of the plant extracts is analyzed both on a non-cancerous cell line (WI-38--human lung fibroblast) and on a cancerous cell line (HeLa human cervix carcinoma). The results are linked to a data set of high-performance liquid chromatographic fingerprint profiles of the samples using multivariate calibration techniques. The regression coefficients of the multivariate model are then evaluated to indicate those peaks potentially responsible for the cytotoxic activity of the Mallotus extracts. In a final step, the cytotoxic extracts are analyzed by HPLC-MS and the indicated peaks identified.

Potentially antioxidant compounds indicated from Mallotus and Phyllanthus species fingerprints.

The genera of Mallotus and Phyllanthus contain several species that are commonly used as traditional medicines in oriental countries. Some species show interesting pharmaceutical activities, such as an antioxidant activity. To produce clinically useful medicines or food supplements (nutraceuticals) from these herbs, the species should be identified and a thorough quality control should be implemented. Nowadays, the integration of chromatographic and chemometric approaches allows a high-throughput identification and activity prediction of medicinal plants. In this study, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were applied and compared to distinguish Mallotus and Phyllanthus species. Moreover, peaks from their chromatographic fingerprints, which were responsible for their antioxidant activity were assigned. For the latter purpose, the relevant information was extracted from the chromatographic fingerprints using linear multivariate calibration techniques, i.e., Partial Least Squares (PLS) and Orthogonal Projections to Latent Structures (O-PLS). Results reveal that exploratory analysis using PCA shows somewhat diverging clustering tendencies between Mallotus and Phyllanthus samples than HCA. However, both approaches mainly confirm each other. Concerning the multivariate calibration techniques, both PLS and O-PLS models demonstrate good predictive abilities. By comparing the regression coefficients of the models with the chromatographic fingerprints, the peaks that are potentially responsible for the antioxidant activity of the extracts could be confirmed.

Potential antioxidant compounds in Mallotus species fingerprints. Part II: fingerprint alignment, data analysis and peak identification.

Some Mallotus species are commonly used as traditional medicine (TM) ingredients in Vietnam and China, but only a few are studied for their activities. In Part I, high-performance liquid chromatography (HPLC) fingerprints of 39 Mallotus samples (17 species) were developed and, because of the complexity of and the large differences between the samples, it was chosen to analyse the unaligned fingerprints. The peaks, potentially responsible for the antioxidant activity in given Mallotus species, were indicated by the regression coefficients from an orthogonal projections to latent structures (O-PLS) model. In the present study, an in depth discussion on the need for alignment of the Mallotus fingerprints for the indication of the potentially active compounds is made, as well as an experimental analysis and identification of the previously indicated peaks by HPLC-mass spectrometry (HPLC-MS). Additionally, to thoroughly study and discuss the alignment problem, the modelling and prediction of the antioxidant activity of green tea samples based on HPLC fingerprints were also considered.

Pressurized capillary electrochromatography in a screening for possible antioxidant molecules in Mallotus fingerprints: challenges, potentials and prospects.

Because of its eminent high resolution potential and minimal solvent consumption, pressurized capillary electrochromatography (pCEC) may offer an interesting alternative to HPLC for screening applications that need to resolve complex samples. In this paper, its potential was assessed in a screening of plant extracts from Mallotus species to indicate compounds with possible antioxidant activities by means of a PLS model built from their pCEC fingerprints. The main aim of this research was to find out whether pCEC can have an added value for this application. To get a complete overview of the techniques potential for this application, it was also assessed whether the technique can meet the requirements in terms of precision, sensitivity and column robustness. Encountered benefits and downsides were reported. Fingerprints with satisfactory sensitivity and precision could be obtained by concentrating the sample 5-fold and using optimized rinsing procedures, respectively. From the generated pCEC fingerprints of 39 Mallotus samples and their respective DPPH radical scavenging activity test results, a three-component PLS model was being built. The model proved good predictive abilities and easily allowed the indication of possible antioxidant compounds in the fingerprints. Despite its much higher peak capacity, the performance of pCEC to fingerprint the majority of the Mallotus extracts did not surpass that of a custom HPLC method. This was also reflected in its comparable power to indicate possible antioxidant compounds in the fingerprints after modeling. Because of its low detection sensitivity and modest column robustness, the benefit of the lower solvent consumption was partly paid-off by the current need for more system maintenance, also limiting the sample throughput. For the considered screening application, pCEC may suit as a viable but no preferred alternative technique.

Dissimilar chromatographic systems to indicate and identify antioxidants from Mallotus species.

The genus of Mallotus contains several species commonly used as traditional medicines in oriental countries. A data set containing 39 Mallotus samples, differing in species, cultivation conditions, harvest season and/or part of the plant was used to develop fingerprints on two dissimilar chromatographic systems. An exploratory analysis with principal component analysis (PCA) was performed on both data sets individually. The results were also combined to obtain additional information on the unknown samples included in the data set. Furthermore, the antioxidant activity of the samples was measured and modelled as a function of the fingerprints using the orthogonal projections to latent structures (O-PLS) technique. The regression coefficients of the models were studied to indicate the peaks potentially responsible for the antioxidant activity. The indicated peaks were analyzed and identified by HPLC coupled to mass spectrometry (HPLC-MS). Because of the complexity of biological samples, it was aspired to separate co-eluting components based on the significant difference in chromatographic selectivity on the dissimilar systems and consequently obtain additional, complementary information on the contribution of the individual components to the antioxidant activity. The results illustrate the potential use of dissimilar chromatographic systems. Several initially co-eluting compounds could be separated on the dissimilar system. The corresponding regression coefficients provided complementary information on the potential antioxidant activity of the separated compounds.

Potential antioxidant compounds in Mallotus species fingerprints. Part I: Indication, using linear multivariate calibration techniques.

Some Mallotus species are used in traditional medicine in Vietnam and China. Some also show interesting activities, such as antioxidant and cytotoxic ones. Combining fingerprint technology with data-handling techniques allows indicating the peaks potentially responsible for given activities. In this study it is aspired to indicate from chromatographic fingerprints the peaks potentially responsible for the antioxidant activity of several Mallotus species. Relevant information was extracted using linear multivariate calibration techniques, both before and after alignment of the fingerprints with correlation optimized warping (COW). From the studied techniques, stepwise multiple linear regression is least recommended as it made an inadequate variable selection. Principal component regression theoretically can take largely varying variables uncorrelated to the antioxidant activity into account. However, in practice in the actual case study this problem was limited. These problems in principle do not occur using partial least squares (PLS) models. Of the tested PLS methods, orthogonal projections to latent structures was preferred because of its simplicity, reproducibility, reduced model complexity and improved interpretability of the regression coefficients, yielding a clearer view on the individual contribution of the compounds. Furthermore, reducing analysis times from 60min to 35 and 22.5min resulted in the same main compounds, indicated responsible for the antioxidant activity. Models built after alignment by COW did not result in additional information.

Potential antioxidant compounds in Mallotus species fingerprints. Part I: indication, using linear multivariate calibration techniques.

Some Mallotus species are used in traditional medicine in Vietnam and China. Some also show interesting activities, such as antioxidant and cytotoxic ones. Combining fingerprint technology with data-handling techniques allows indicating the peaks potentially responsible for given activities. In this study it is aspired to indicate from chromatographic fingerprints the peaks potentially responsible for the antioxidant activity of several Mallotus species. Relevant information was extracted using linear multivariate calibration techniques, both before and after alignment of the fingerprints with correlation optimized warping (COW). From the studied techniques, Stepwise Multiple Linear Regression is least recommended as it made an inadequate variable selection. Principal Component Regression theoretically can take largely varying variables uncorrelated to the antioxidant activity into account. However, in practice in the actual case study this problem was limited. These problems in principle do not occur using Partial Least Squares (PLS) models. Of the tested PLS methods, Orthogonal Projections to Latent Structures was preferred because of its simplicity, reproducibility, reduced model complexity and improved interpretability of the regression coefficients, yielding a clearer view on the individual contribution of the compounds. Furthermore, reducing analysis times from 60 min to 35 and 22.5 min resulted in the same main compounds, indicated responsible for the antioxidant activity. Models built after alignment by COW did not result in additional information.

Development of HPLC fingerprints for Mallotus species extracts and evaluation of the peaks responsible for their antioxidant activity.

Some Mallotus species are used in traditional medicine in Vietnam. To use certain species in Western medicines or as food supplements, they should be identified and quality control should be more strict, for instance, to avoid the erroneous switching of species. In species with interesting activities, the compounds responsible for them should be identified. For these identifications, HPLC fingerprint methodology can be used. In this paper, HPLC fingerprints of different lengths were developed for a number of Mallotus species. Secondly, a multivariate regression model was constructed to model the antioxidant activity of the Mallotus samples from the HPLC fingerprints with the aim to indicate peaks possibly responsible for this activity. For this purpose, after data pretreatment, the calibration technique partial least squares (PLS) was applied.