Die Darstellung von β-Glykolen aus Aldolen durch Einwirkung magnesiumorganischer Verbindungen

Ohne Zusammenfassung     

Über eine neue Synthese von α-Alkyladipinsäuren

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Die Bestimmung der Trockensubstanz im Malz

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Improved particle-packed HPLC/MS microchips for proteomic analysis

The influence of packing process parameters (packing pressure, application of ultrasound) and the stationary phase particle size (3.5 and 5 μm) on the chromatographic performance of HPLC/MS chips was systematically investigated for proteomic samples. First, reproducibility and detection limits of the separation were evaluated with a low‐complexity sample of tryptic BSA peptides. The influence of adsorbent packing quality on protein identification was then tested with a typical proteomics sample of high complexity, a human plasma protein fraction (Cohn fraction IV‐4). All HPLC/MS chips provided highly reproducible separations of these proteomic samples, but improved packing conditions and smaller particle sizes resulted in chromatograms with narrower peaks and correspondingly higher signal intensities. Improved separation performance increased the peak capacity, the number of identified peptides, and thus the sequence coverage in the proteomic samples, particularly for low sample amounts.     

Application of displacement chromatography for the proteome analysis of a human plasma protein fraction

It was the aim of this study to compare the performance of displacement chromatography with gradient elution chromatography both applied as the cation-exchange separation step for a proteome analysis in a bottom-up approach using multidimensional chromatography for the separation of tryptic peptides prior to their mass spectrometric analysis. The tryptic digest of the human Cohn fraction IV-4 served as a sample. For both chromatography modes commonly used operating parameters were chosen thus ensuring optimal separation results of equal sample amounts for each mode. All resulting fractions were analyzed with an HPLC-chip–LC–MS system. The eluate of the HPLC-chip column was ionized by electrospray ionization (ESI) and analyzed with an ion-trap mass spectrometer. For guaranteeing high confidence concerning the identity of the peptides, the mass spectrometric data were processed by different bioinformatic tools applying stringent criteria. By the displacement approach the total amount of identified proteins (78) was significantly higher than in the gradient mode (58). The results showed that displacement chromatography is a well suited alternative in comparison to gradient elution separation for analysis of proteomes via the bottom-up approach applying multidimensional chromatography, especially in those cases when larger quantities of proteins are available.     

Classification of behavior using vocalizations of Pacific white-sided dolphins (Lagenorhynchus obliquidens)

Surface behavior and concurrent underwater vocalizations were recorded for Pacific white-sided dolphins in the Southern California Bight (SCB) over multiple field seasons spanning 3 years. Clicks, click trains, and pulsed calls were counted and classified based on acoustic measurements, leading to the identification of 19 key call features used for analysis. Kruskal-Wallis tests indicated that call features differ significantly across behavioral categories. Previous work had discovered two distinctive click Types (A and B), which may correspond to known subpopulations of Pacific white-side dolphins in the Southern California Bight; this study revealed that animals producing these different click types also differ in both their behavior and vocalization patterns. Click Type A groups were predominantly observed slow traveling and milling, with little daytime foraging, while click Type B groups were observed traveling and foraging. These behavioral differences may be characteristic of niche partitioning by overlapping populations; coupled with differences in vocalization patterns, they may signify that these subpopulations are cryptic species. Finally, random forest decision trees were used to classify behavior based on vocalization data, with rates of correct classification up to 86%, demonstrating the potential for the use of vocalization patterns to predict behavior.     

Hessian Potentials with Parallel Derivatives

Let ${U \subset \mathbb A^n}$ be an open subset of real affine space. We consider functions ${F: U \to \mathbb R}$ with non-degenerate Hessian such that the first or the third derivative of F is parallel with respect to the Levi-Civita connection defined by the Hessian metric ${F{^\prime{^\prime}}}$ . In the former case the solutions are given precisely by the logarithmically homogeneous functions, while the latter case is closely linked to metrised Jordan algebras. Both conditions together are related to unital metrised Jordan algebras. Both conditions combined with convexity provide a local characterization of canonical barriers on symmetric cones.