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.