PubMed · 14887186
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C MARTY. 1951-10-13. [Chromatography].. https://pubmed.ncbi.nlm.nih.gov/14887186/
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A theory is proposed for the dependence on saturation of the average minimum resolution R(*) in point-process statistical-overlap theory for two-dimensional separations. Peak maxima are modelled by clusters of overlapping circles in hexagonal arrangements similar to close-packed layers. Such clusters exist only for specific circle numbers, but equations are derived that facilitate prediction of equivalent cluster properties for any number of circles. A metric is proposed for the average minimum resolution that separates two such clusters into two maxima. From this metric, the average minimum resolution of the two nearest-neighbor single-component peaks (SCPs)--one in each cluster--is calculated. Its value varies with the number of SCPs in both clusters. These resolutions are weighted by the probability that the two clusters contain the postulated numbers of SCPs and summed to give R(*), which decreases with increasing saturation. The dependence of R(*) on saturation is combined with a theory correcting the probability of overlap in a reduced square for boundary effects. The numbers of maxima in simulations of 75, 150, and 300 randomly distributed bi-Gaussians having exponential heights and aspect ratios of 1, 30, and 60 are compared to predictions. Excellent agreement between maxima numbers and theory is found at low and high saturation. Good estimates of the numbers of bi-Gaussians in simulations are calculated by fitting theory to numbers of maxima using least-squares regression. The theory is applied to mimicked GC x GCs of 93 compounds having many correlated retention times, with predictions that agree fairly well with maxima numbers.
Ten newly isolated hop proanthocyanidin oligomers and flavan-3-ol monomers from 13 different hops have been identified as gallocatechin, gallocatechin-(4alpha-->8)-catechin, gallocatechin-(4alpha-->6)-catechin, catechin-(4alpha-->8)-gallocatechin, catechin-(4alpha-->6)-gallocatechin, afzelechin-(4alpha-->8)-catechin, catechin-(4alpha-->8)-catechin-(4alpha-->8)-catechin, epicatechin-(4beta-->8)-epicatechin-(4beta-->8)-catechin, catechin-(4alpha-->8)-gallocatechin-(4alpha-->8)-catechin, and gallocatechin-(4alpha-->8)-gallocatechin-(4alpha-->8)-catechin, together with seven previously isolated oligomers, namely, catechin, epicatechin, epicatechin-(4beta-->8)-catechin, epicatechin-(4beta-->8)-epicatechin, catechin-(4alpha-->8)-catechin, catechin-(4alpha-->8)-epicatechin, and epicatechin-(4beta-->8)-catechin-(4alpha-->8)-catechin. These compounds were subjected to acid-catalyzed degradation in the presence of phloroglucinol or by partial or complete acid-catalyzed degradation and reaction with benzyl mercaptan followed by desulfurization. The resultant adducts when compared to authentic samples by high-performance liquid chromatography-atmospheric pressure chemical ionization tandem mass spectrometry and high-performance liquid chromatography-electrospray ionization tandem mass spectrometry served to identify the precursors. The composition of proanthocyanidins from 13 different hops was similar, but the concentration of individual compounds showed some differences, which indicated that hop proanthocyanidin profiles are affected by geographic origin and are variable depending on the cultivars.
Particle size and the size distribution are known to be important factors in the overall behavior of nanoparticulate drug delivery systems and an exact determination of these parameters is highly important. Several techniques are applied in the size determination of nanoparticulates, particularly dynamic light scattering. Also other methods have been proposed, among them hydrodynamic chromatography (HDC). In order to characterize a HDC method for nanosized carriers, differently sized lipid nanocapsules having a diameter of 25-100 nm were analyzed and results were compared with measurements from photon correlation spectroscopy (PCS) and atomic force microscopy. Results from atomic force microscopy studies were generally not in line with determinations from the other techniques due to a particle shape loss by the drying step. PCS and HDC led to comparable results in simple size determination of lipid nanocapsules. However, slight differences were found during the characterization of more complex samples. HDC was able to detect micelles as a byproduct of nanocapsule preparation while in PCS the sample dilution turned micelles undetectable. HDC analysis was able to characterize mixed samples of particle batches differing in their average size similar to PCS. HDC was found to be an excellent tool for the determination of size and average size distribution of lipid nanocapsules.