Tyrosine phosphorylation of G protein alpha subunits by pp60c-src.

A number of lines of evidence suggest that cross-talk exists between the cellular signal transduction pathways involving tyrosine phosphorylation catalyzed by members of the pp60c-src kinase family and those mediated by guanine nucleotide regulatory proteins (G proteins). In this study, we explore the possibility that direct interactions between pp60c-src and G proteins may occur with functional consequences. Preparations of pp60c-src isolated by immunoprecipitation phosphorylate on tyrosine residues the purified G-protein alpha subunits (G alpha) of several heterotrimeric G proteins. Phosphorylation is highly dependent on G-protein conformation, and G alpha(GDP) uncomplexed by beta gamma subunits appears to be the preferred substrate. In functional studies, phosphorylation of stimulatory G alpha (G alpha s) modestly increases the rate of binding of guanosine 5'-[gamma-[35S]thio]triphosphate to Gs as well as the receptor-stimulated steady-state rate of GTP hydrolysis by Gs. Heterotrimeric G proteins may represent a previously unappreciated class of potential substrates for pp60c-src.

G-protein-coupled receptor genes as protooncogenes: constitutively activating mutation of the alpha 1B-adrenergic receptor enhances mitogenesis and tumorigenicity.

The alpha 1B-adrenergic receptor (alpha 1B-ADR) is a member of the G-protein-coupled family of transmembrane receptors. When transfected into Rat-1 and NIH 3T3 fibroblasts, this receptor induces focus formation in an agonist-dependent manner. Focus-derived, transformed fibroblasts exhibit high levels of functional alpha 1B-ADR expression, demonstrate a catecholamine-induced enhancement in the rate of cellular proliferation, and are tumorigenic when injected into nude mice. Induction of neoplastic transformation by the alpha 1B-ADR, therefore, identifies this normal cellular gene as a protooncogene. Mutational alteration of this receptor can lead to activation of this protooncogene, resulting in an enhanced ability of agonist to induce focus formation with a decreased latency and quantitative increase in transformed foci. In contrast to cells expressing the wild-type alpha 1B-ADR, focus formation in "oncomutant"-expressing cell lines appears constitutively activated with the generation of foci in unstimulated cells. Further, these cell lines exhibit near-maximal rates of proliferation even in the absence of catecholamine supplementation. They also demonstrate an enhanced ability for tumor generation in nude mice with a decreased period of latency compared with cells expressing the wild-type receptor. Thus, the alpha 1B-ADR gene can, when overexpressed and activated, function as an oncogene inducing neoplastic transformation. Mutational alteration of this receptor gene can result in the activation of this protooncogene, enhancing its oncogenic potential. These findings suggest that analogous spontaneously occurring mutations in this class of receptor proteins could play a key role in the induction or progression of neoplastic transformation and atherosclerosis.

Heat-labile enterotoxin: beyond G(m1) binding.

Enterotoxigenic Escherichia coli (ETEC) is a significant source of morbidity and mortality worldwide. One major virulence factor released by ETEC is the heat-labile enterotoxin LT, which is structurally and functionally similar to cholera toxin. LT consists of five B subunits carrying a single catalytically active A subunit. LTB binds the monosialoganglioside G(M1), the toxin's host receptor, but interactions with A-type blood sugars and E. coli lipopolysaccharide have also been identified within the past decade. Here, we review the regulation, assembly, and binding properties of the LT B-subunit pentamer and discuss the possible roles of its numerous molecular interactions.

HBHA and ESAT-6 induced IFN-g responses in M. tuberculosis infected subjects from a low incidence country

info:eu-repo/semantics/nonPublished

Exploitation of symbolic information in interprocedural dependence analysis

The requirement for a very accurate dependence analysis to underpin software tools to aid the generation of efficient parallel implementations of scalar code is argued. The current status of dependence analysis is shown to be inadequate for the generation of efficient parallel code, causing too many conservative assumptions to be made. This paper summarises the limitations of conventional dependence analysis techniques, and then describes a series of extensions which enable the production of a much more accurate dependence graph. The extensions include analysis of symbolic variables, the development of a symbolic inequality disproof algorithm and its exploitation in a symbolic Banerjee inequality test; the use of inference engine proofs; the exploitation of exact dependence and dependence pre-domination attributes; interprocedural array analysis; conditional variable definition tracing; integer array tracing and division calculations. Analysis case studies on typical numerical code is shown to reduce the total dependencies estimated from conventional analysis by up to 50%. The techniques described in this paper have been embedded within a suite of tools, CAPTools, which combines analysis with user knowledge to produce efficient parallel implementations of numerical mesh based codes.

Exact colorations of graphs and digraphs

A coloration is an exact regular coloration if whenever two vertices are colored the same they have identically colored neighborhoods. For example, if one of the two vertices that are colored the same is connected to three yellow vertices, two white and red, then the other vertex is as well. Exact regular colorations have been discussed informally in the social network literature. However they have been part of the mathematical literature for some time, though in a different format. We explore this concept in terms of social networks and illustrate some important results taken from the mathematical literature. In addition we show how the concept can be extended to ecological and perfect colorations, and discuss how the CATREGE algorithm can be extended to find the maximal exact regular coloration of a graph.

A multilevel algorithm for force-directed graph drawing

We describe a heuristic method for drawing graphs which uses a multilevel technique combined with a force-directed placement algorithm. The multilevel process groups vertices to form clusters, uses the clusters to define a new graph and is repeated until the graph size falls below some threshold. The coarsest graph is then given an initial layout and the layout is successively refined on all the graphs starting with the coarsest and ending with the original. In this way the multilevel algorithm both accelerates and gives a more global quality to the force- directed placement. The algorithm can compute both 2 & 3 dimensional layouts and we demonstrate it on a number of examples ranging from 500 to 225,000 vertices. It is also very fast and can compute a 2D layout of a sparse graph in around 30 seconds for a 10,000 vertex graph to around 10 minutes for the largest graph. This is an order of magnitude faster than recent implementations of force-directed placement algorithms.

A framework for historical case-based reasoning

This paper presents a framework for Historical Case-Based Reasoning (HCBR) which allows the expression of both relative and absolute temporal knowledge, representing case histories in the real world. The formalism is founded on a general temporal theory that accommodates both points and intervals as primitive time elements. A case history is formally defined as a collection of (time-independent) elemental cases, together with its corresponding temporal reference. Case history matching is two-fold, i.e., there are two similarity values need to be computed: the non-temporal similarity degree and the temporal similarity degree. On the one hand, based on elemental case matching, the non-temporal similarity degree between case histories is defined by means of computing the unions and intersections of the involved elemental cases. On the other hand, by means of the graphical presentation of temporal references, the temporal similarity degree in case history matching is transformed into conventional graph similarity measurement.

A multilevel algorithm for force-directed graph-drawing

We describe a heuristic method for drawing graphs which uses a multilevel framework combined with a force-directed placement algorithm. The multilevel technique matches and coalesces pairs of adjacent vertices to define a new graph and is repeated recursively to create a hierarchy of increasingly coarse graphs, G0, G1, …, GL. The coarsest graph, GL, is then given an initial layout and the layout is refined and extended to all the graphs starting with the coarsest and ending with the original. At each successive change of level, l, the initial layout for Gl is taken from its coarser and smaller child graph, Gl+1, and refined using force-directed placement. In this way the multilevel framework both accelerates and appears to give a more global quality to the drawing. The algorithm can compute both 2 & 3 dimensional layouts and we demonstrate it on examples ranging in size from 10 to 225,000 vertices. It is also very fast and can compute a 2D layout of a sparse graph in around 12 seconds for a 10,000 vertex graph to around 5-7 minutes for the largest graphs. This is an order of magnitude faster than recent implementations of force-directed placement algorithms.

A combined evolutionary search and multilevel optimisation approach to graph-partitioning

The graph-partitioning problem is to divide a graph into several pieces so that the number of vertices in each piece is the same within some defined tolerance and the number of cut edges is minimised. Important applications of the problem arise, for example, in parallel processing where data sets need to be distributed across the memory of a parallel machine. Very effective heuristic algorithms have been developed for this problem which run in real-time, but it is not known how good the partitions are since the problem is, in general, NP-complete. This paper reports an evolutionary search algorithm for finding benchmark partitions. A distinctive feature is the use of a multilevel heuristic algorithm to provide an effective crossover. The technique is tested on several example graphs and it is demonstrated that our method can achieve extremely high quality partitions significantly better than those found by the state-of-the-art graph-partitioning packages.