Biomedical subjects

Uwe Thissen

Publications and source records attributed to Uwe Thissen.

2 recordsLinked to original sources

PubMed2006

Effects of growth conditions and processing on Rehmannia glutinosa using fingerprint strategy.

Metabolite profiling in combination with multivariate statistics is a sophisticated method for quality assessment of natural products. For the development of a quality control strategy in Traditional Chinese Medicine (TCM), we have measured the metabolite fingerprints of Rehmannia glutinosa by GC-MS. Plants were grown under different climate and soil conditions in a phytotron and were processed by a variable number of repetitive steps to investigate the effects on both growth conditions and processing for material medica of R. glutinosa. The GC-MS data have been analyzed by principal component analysis (PCA) and the new approach of the ANOVA-simultaneous component analysis (ASCA) which can combine the information from a structured data design with multivariate analysis. The results clearly show the effect of the different factors and indicate directions for process improvement. When plants were grown under various temperatures, humidity and light intensities for a short period (3 weeks), no significant changes on studied metabolites were observed. However, significant changes were found between different processing cycles. The present data clearly indicate the importance of strictly controlling processing in R. glutinosa and illustrate the impact of growth conditions. This is the first report on the metabolite profile of R. glutinosa that provides a base for the establishment of a quality control strategy.

Climate↗

PubMed2004

Multivariate calibration with least-squares support vector machines.

This paper proposes the use of least-squares support vector machines (LS-SVMs) as a relatively new nonlinear multivariate calibration method, capable of dealing with ill-posed problems. LS-SVMs are an extension of "traditional" SVMs that have been introduced recently in the field of chemistry and chemometrics. The advantages of SVM-based methods over many other methods are that these lead to global models that are often unique, and nonlinear regression can be performed easily as an extension to linear regression. An additional advantage of LS-SVM (compared to SVM) is that model calculation and optimization can be performed relatively fast. As a test case to study the use of LS-SVM, the well-known and important chemical problem is considered in which spectra are affected by nonlinear interferences. As one specific example, a commonly used case is studied in which near-infrared spectra are affected by temperature-induced spectral variation. Using this test case, model optimization, pruning, and model interpretation of the LS-SVM have been demonstrated. Furthermore, excellent performance of the LS-SVM, compared to other approaches, has been presented on the specific example. Therefore, it can be concluded that LS-SVMs can be seen as very promising techniques to solve ill-posed problems. Furthermore, these have been shown to lead to robust models in cases of spectral variations due to nonlinear interferences.

Journal Article↗