Quantitative proteome analysis in cardiovascular physiology and pathology. I. Data processing

Methodological evaluation of the proteomic analysis of cardiovascular-tissue material has been performed with a special emphasis on establishing examinations that allow reliable quantitative analysis of silver-stained readouts. Reliability, reproducibility, robustness and linearity were addressed and clarified. In addition, several types of normalization procedures were evaluated and new approaches are proposed. It has been found that the silver-stained readout offers a convenient approach for quantitation if a linear range for gel loading is defined. In addition, a broad range of a 10-fold input (loading 20-200 microg per gel) fulfills the linearity criteria, although at the lowest input (20 microg) a portion of protein species will remain undetected. The method is reliable and reproducible within a range of 65-200 microg input. The normalization procedure using the sum of all spot intensities from a silver-stained 2D pattern has been shown to be less reliable than other approaches, namely, normalization through median or through involvement of interquartile range. A special refinement of the normalization through virtual segmentation of pattern, and calculation of normalization factor for each stratum provides highly satisfactory results. The presented results not only provide evidence for the usefulness of silver-stained gels for quantitative evaluation, but they are directly applicable to the research endeavor of monitoring alterations in cardiovascular pathophysiology.

DNA-based identification of novel bovine casein gene variants

In cattle, at least 39 variants of the 4 casein proteins (α(S1)-, β-, α(S2)- and κ-casein) have been described to date. Many of these variants are known to affect milk-production traits, cheese-processing properties, and the nutritive value of milk. They also provide valuable information for phylogenetic studies. So far, the majority of studies exploring the genetic variability of bovine caseins considered European taurine cattle breeds and were carried out at the protein level by electrophoretic techniques. This only allows the identification of variants that, due to amino acid exchanges, differ in their electric charge, molecular weight, or isoelectric point. In this study, the open reading frames of the casein genes CSN1S1, CSN2, CSN1S2, and CSN3 of 356 animals belonging to 14 taurine and 3 indicine cattle breeds were sequenced. With this approach, we identified 23 alleles, including 5 new DNA sequence variants, with a predicted effect on the protein sequence. The new variants were only found in indicine breeds and in one local Iranian breed, which has been phenotypically classified as a taurine breed. A multidimensional scaling approach based on available SNP chip data, however, revealed an admixture of taurine and indicine populations in this breed as well as in the local Iranian breed Golpayegani. Specific indicine casein alleles were also identified in a few European taurine breeds, indicating the introgression of indicine breeds into these populations. This study shows the existence of substantial undiscovered genetic variability of bovine casein loci, especially in indicine cattle breeds. The identification of new variants is a valuable tool for phylogenetic studies and investigations into the evolution of the milk protein genes.

Granular computing as a tool of human data interaction - a cognitive cities use case

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

Doppler Orbit Determination of Deep Space Probes by the Bernese GNSS Software: First Results of the Combined Orbit Determination from DSN and Inter-Satellite Ka-Band Data from the Grail Mission

Navigation of deep space probes is most commonly operated using the spacecraft Doppler tracking technique. Orbital parameters are determined from a series of repeated measurements of the frequency shift of a microwave carrier over a given integration time. Currently, both ESA and NASA operate antennas at several sites around the world to ensure the tracking of deep space probes. Just a small number of software packages are nowadays used to process Doppler observations. The Astronomical Institute of the University of Bern (AIUB) has recently started the development of Doppler data processing capabilities within the Bernese GNSS Software. This software has been extensively used for Precise Orbit Determination of Earth orbiting satellites using GPS data collected by on-board receivers and for subsequent determination of the Earth gravity field. In this paper, we present the currently achieved status of the Doppler data modeling and orbit determination capabilities in the Bernese GNSS Software using GRAIL data. In particular we will focus on the implemented orbit determination procedure used for the combined analysis of Doppler and intersatellite Ka-band data. We show that even at this earlier stage of the development we can achieve an accuracy of few mHz on two-way S-band Doppler observation and of 2 µm/s on KBRR data from the GRAIL primary mission phase.