University of Graz

About: University of Graz is a education organization based out in Graz, Steiermark, Austria. It is known for research contribution in the topics: Population & Quantum chromodynamics. The organization has 17934 authors who have published 37489 publications receiving 1110980 citations. The organization is also known as: Carolo Franciscea Graecensis & Karl Franzens Universität.

Structural analysis of porcine brain nitric oxide synthase reveals a role for tetrahydrobiopterin and L-arginine in the formation of an SDS-resistant dimer.

Abstract: Nitric oxide synthases (NOSs), which catalyze the formation of the ubiquitous biological messenger molecule nitric oxide, represent unique cytochrome P-450s, containing reductase and mono-oxygenase domains within one polypeptide and requiring tetrahydrobiopterin as cofactor. To investigate whether tetrahydrobiopterin functions as an allosteric effector of NOS, we have analyzed the effect of the pteridine on the conformation of neuronal NOS purified from porcine brain by means of circular dichroism, velocity sedimentation, dynamic light scattering and SDS-polyacrylamide gel electrophoresis. We report for the first time the secondary structure of NOS, showing that the neuronal isozyme contains 30% alpha-helix, 14% antiparallel beta-sheet, 7% parallel beta-sheet, 19% turns and 31% other structures. The secondary structure of neuronal NOS was neither modulated nor stabilized by tetrahydrobiopterin, and the pteridine did not affect the quaternary structure of the protein, which appears to be an elongated homodimer with an axial ratio of approximately 20/1 under native conditions. Low temperature SDS-polyacrylamide gel electrophoresis revealed that tetrahydrobiopterin and L-arginine synergistically convert neuronal NOS into an exceptionally stable, non-covalently linked homodimer surviving in 2% SDS and 5% 2-mercaptoethanol. Ligand-induced formation of an SDS-resistant dimer is unprecedented and suggests a novel role for tetrahydrobiopterin and L-arginine in the allosteric regulation of protein subunit interactions.

Optical sensors for determination of heavy metal ions

Abstract: A review is given on optical means for single shot testing (“probing”) as well as continuous monitoring (“sensing”) of heavy metal ions (HMs). Following an introduction into indicator based approaches, we discuss the types of indicator dyes and polymeric supports used, as well as existing sensing schemes for HMs. The wealth of information is compiled in the form of tables and critically reviewed. Notwithstanding the tremendous work performed so far, it is obvious that still severe limitations do exist in terms of selectivity, limits of detection, dynamic ranges, applicability to specific problems, and reversibility. On the other hand, such sensors have found — and will find — their application whenever rapid and cost-effective testing is required, where personnel is scarce or unskilled, and in field tests. Despite their limitations, the number of such sensors (and of irreversible “probes”) for HMs is likely to increase in future.

On the use of neurophysiological tools in is research: developing a research agenda for neurois

Abstract: This article discusses the role of commonly used neurophysiological tools such as psychophysiological tools (e.g., EKG, eye tracking) and neuroimaging tools (e.g., fMRI, EEG) in Information Systems research. There is heated interest now in the social sciences in capturing presumably objective data directly from the human body, and this interest in neurophysiological tools has also been gaining momentum in IS research (termed NeuroIS). This article first reviews commonly used neurophysiological tools with regard to their major strengths and weaknesses. It then discusses several promising application areas and research questions where IS researchers can benefit from the use of neurophysiological data. The proposed research topics are presented within three thematic areas: (1) development and use of systems, (2) IS strategy and business outcomes, and (3) group work and decision support. The article concludes with recommendations on how to use neurophysiological tools in IS research along with a set of practical suggestions for developing a research agenda for NeuroIS and establishing NeuroIS as a viable subfield in the IS literature.