Temperature induced rotation in a [4.4]cyclophane

The synthesis, the X-ray, NMR and molecular modeling structure determination of a new orthopara[4.4]cyclophane are reported. The similarity of the π(CO)-π(Ar) driven conformational equilibrium of this compound to the work of an amusement ride machinery is also revealed.     

Recent developments in chromatographic fingerprints from herbal products: set-up and data analysis

The use of chromatographic fingerprints from herbal products where the whole chromatographic profile is applied to evaluate the quality of the investigated product. In this paper, recent developments in the set-up and data analysis of chromatographic fingerprints for herbal products are discussed. First different set-ups for fingerprint development are reviewed. Prior to fingerprint development, a suitable sample preparation, e.g. extraction, should be considered. In a second instance, this review focuses on the data analysis with regards to the different applications of fingerprints. Usually, chemometric data pretreatment is necessary. This is discussed first, followed by a short overview of the data handling techniques used in the two main application areas of herbal fingerprints, i.e. quality assurance and classification or calibration. The quality assurance, which involves the identification and quality control of the herbal products, is reviewed, followed by the use of fingerprints in classification or modelling. The different application areas are illustrated and discussed with several case studies.     

Identification of poliovirions and subviral particles by capillary electrophoresis

Poliovirions, purified from infected cell extracts with anion-exchange chromatography, can be analyzed and identified by CE in untreated fused silica capillaries using UV detection. Other subviral particles can be eluted as well from the same infected cell extract using a higher salt concentration buffer on the ion-exchange chromatography. Virions can be identified because of their conversion into empty capsids upon heating at 56°C. As a result of heating, the viral genome is released from the capsid. Here, we show that during this incubation some intermediate particles were found. The latter were identified by enzymatic peak shift analysis. The high salt concentration eluate subviral particles were analyzed with preincubation affinity CE together with their sensitivity for RNase and proteinase K treatment. Electropherograms of the higher salt concentration eluate display a mixture of at least four different subviral particles. One particle proved to have an [N1, H] antigenicity and was resistant to RNase and proteinase K digestion. The remaining particles were all sensitive to proteinase K treatment. This CE method proved to be valuable in the detection, identification and analysis of poliovirions and poliovirus particles offering an alternative powerful, cheap, fast and easy analysis method.     

Updating a chiral separation strategy for non-acidic drugs with capillary electrochromatography applicable for both chlorinated and non-chlorinated polysaccharide selectors

A generic strategy for the chiral separation of non-acidic pharmaceuticals was updated to complete an approach defined earlier. The selected chiral stationary phases are all polysaccharide selectors, chlorinated, and non-chlorinated, namely Lux(?) Amylose 2, Chiralcel(?) OD-RH, Lux(?) Cellulose 4, and Chiralpak(?) AD-RH. In this study, the screening step of a strategy defined earlier was updated and the optimization steps were re-evaluated for the applied chiral stationary phases. These screening and optimization conditions were studied by analyzing 20 pharmaceuticals at different organic modifier contents, temperatures, or applied voltages. The proposed chiral separation strategy was then evaluated with a test set of 19 non-acidic drugs. Seventeen compounds (89.5%) of the latter set could be resolved of which eight (42%) were baseline separated. The strategy thus proved to be applicable on compounds different from those used for its development.     

Enantioselectivity of monolithic silica stationary phases immobilized with different concentrations cellulose tris (3,5-dimethylphenylcarbamate), analyzed with different mobile phases in capillary electrochromatography

The 3,5-dimethylphenylcarbamate derivatives of cellulose bearing 3-(triethoxysilyl)propyl residues were immobilized in a capillary format onto a monolithic silica support by intermolecular polycondensation of the triethoxysilyl groups. The resulting columns were used for chiral separations using capillary electrochromatography. The effects of the synthesizing solvent, the selector coating procedure, the chiral selector concentration onto the silica monolith and the mobile phase pH value, on the separation of enantiomers were studied. The column-to-column reproducibility and stability also were evaluated. A test set of 14 chiral substances, including acidic, neutral, bifunctional and basic compounds, was used to investigate the effects of the factors mentioned above. Twelve pairs of enantiomers showed enantioselectivity at some of the different conditions tested. The column-to-column repeatability was satisfactory, and the prepared columns were stable under the adopted analysis conditions.     

Quality control of Citri reticulatae pericarpium: exploratory analysis and discrimination

Extracts of Citri reticulatae pericarpium (PCR) are commonly used in the Traditional Chinese Medicine. The quality control of PCR is currently performed by single marker analysis, which can hardly describe the complexity of such natural samples. In this study, a fingerprint methodology for PCR based on high-performance liquid chromatography (HPLC) was developed and validated. A total of 69 fingerprints of authenticated PCR samples, commercial PCR samples, mixed peel samples, and other Citrus peels were recorded. Exploratory data analysis allowed optimizing the extraction procedure and detecting mixed peel samples. Once the optimizations were performed and the method validated, discrimination between the authentic PCR samples and all other samples was performed by p-Discriminant Partial Least Squares. The established model was able to differentiate between classes with a high reliability for each sample. Furthermore, evaluation of the score and loading plots of the model indicated nobiletin, tangeretin, naringin and hesperidin as important markers for the quality control of PCR.     

Improved variable reduction in partial least squares modelling based on predictive-property-ranked variables and adaptation of partial least squares complexity

The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain significantly smaller numbers of informative variables than the existing SVR-PPRV, UVE-GA-PLS and UVE-iPLS methods without loss of prediction ability. Contrary to UVE-GA-PLS and UVE-iPLS, there is no variability in the number of retained variables in each PPRV(R) method. Renewed variable ranking, after deletion of a variable, followed by remodelling, combined with the possibility to decrease the PLS model complexity, is beneficial. A preferred PPRVR-CAM method is proposed.