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 & Context (language use). 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.

Characterization of 1H-[1,2,4]oxadiazolo[4,3-a]quinoxalin-1-one as a heme-site inhibitor of nitric oxide-sensitive guanylyl cyclase.

Abstract: Nitric oxide (NO) binds with high affinity to the heme of soluble guanylyl cyclase (sGC), resulting in accumulation of the second messenger cGMP in many biological systems. 1H-[1,2,4]Oxadiazolo[4,3-a]quinoxalin-1-one (ODQ) was recently described as potent and selective inhibitor of sGC, providing an invaluable tool with which to settle the function of the cGMP pathway in NO-mediated signal transduction [Mol. Pharmacol. 48:184-188 (1995)]. The present study investigated the mechanism of ODQ-induced inhibition of purified bovine lung sGC. The drug induced a rightward shift of the concentration-response curves recorded with two different NO donors and a reduction of maximal sGC activity, pointing to a mixed type of inhibition. The time course of NO-stimulated sGC activity determined in the presence of 0.3 microM ODQ showed that the inhibitory effect was time-dependent (half-time approximately 3 min) and virtually complete after about 10 min. The cyclase did not recover from ODQ-induced inhibition upon extensive dilution, pointing to an apparently irreversible inactivation of the enzyme by the quinoxalin. Light absorbance spectroscopy showed that ODQ (0.3 mM) induced a shift of the Soret band of the heme from 431 nm to 393 nm, indicating that ODQ oxidizes the ferrous form of the enzyme to the ferric species, which is though to exhibit only poor NO sensitivity. Together, our results suggest that inhibition of sGC by ODQ is NO-competitive and results in an apparently irreversible oxidation of the prosthetic heme group.

Mutations in SPTLC1 , encoding serine palmitoyltransferase, long chain base subunit-1, cause hereditary sensory neuropathy type I

Abstract: Hereditary sensory neuropathy type I (HSN1) is the most common hereditary disorder of peripheral sensory neurons. HSN1 is an autosomal dominant progressive degeneration of dorsal root ganglia and motor neurons with onset in the second or third decades. Initial symptoms are sensory loss in the feet followed by distal muscle wasting and weakness. Loss of pain sensation leads to chronic skin ulcers and distal amputations. The HSN1 locus has been mapped to chromosome 9q22.1-22.3 (refs. 3,4). Here we map the gene SPTLC1, encoding serine palmitoyltransferase, long chain base subunit-1, to this locus. Mutation screening revealed 3 different missense mutations resulting in changes to 2 amino acids in all affected members of 11 HSN1 families. We found two mutations to be located in exon 5 (C133Y and C133W) and one mutation to be located in exon 6 of SPTLC1 (V144D). All families showing definite or probable linkage to chromosome 9 had mutations in these two exons. These mutations are associated with increased de novo glucosyl ceramide synthesis in lymphoblast cell lines in affected individuals. Increased de novo ceramide synthesis triggers apoptosis and is associated with massive cell death during neural tube closure, raising the possibility that neural degeneration in HSN1 is due to ceramide-induced apoptotic cell death.

Epsilon-nets and simplex range queries

Abstract: We present a new technique for half-space and simplex range query using O(n) space and O(na) query time, where a 0. These bounds are better than those previously published for all d ≥ 2. The technique uses random sampling to build a partition-tree structure. We introduce the concept of an e-net for an abstract set of ranges to describe the desired result of this random sampling and give necessary and sufficient conditions that a random sample is an e-net with high probability. We illustrate the application of these ideas to other range query problems.