Interaction of DBC1 with polyoma small T antigen promotes its degradation and negatively regulates tumorigenesis

Deleted in Breast Cancer 1 (DBC1) is an important metabolic sensor. Previous studies have implicated DBC1 in various cellular functions, notably cell proliferation, apoptosis, histone modification, and adipogenesis. However, current reports about the role of DBC1 in tumorigenesis are controversial and designate DBC1 alternatively as a tumor suppressor or a tumor promoter. In the present study, we report that polyoma small T antigen (PyST) associates with DBC1 in mammalian cells, and this interaction leads to the posttranslational downregulation of DBC1 protein levels. When coexpressed, DBC1 overcomes PyST-induced mitotic arrest and promotes the exit of cells from mitosis. Using both transient and stable modes of PyST expression, we also show that cellular DBC1 is subjected to degradation by LKB1, a tumor suppressor and cellular energy sensor kinase, in an AMP kinase-independent manner. Moreover, LKB1 negatively regulates the phosphorylation as well as activity of the prosurvival kinase AKT1 through DBC1 and its downstream pseudokinase substrate, Tribbles 3 (TRB3). Using both transient transfection and stable cell line approaches as well as soft agar assay, we demonstrate that DBC1 has oncogenic potential. In conclusion, our study provides insight into a novel signaling axis that connects LKB1, DBC1, TRB3, and AKT1. We propose that the LKB1–DBC1–AKT1 signaling paradigm may have an important role in the regulation of cell cycle and apoptosis and consequently tumorigenesis.     

Peroxynitrite resistance of sarco/endoplasmic reticulum Ca2+ pump in pig coronary artery endothelium and smooth muscle

We examined the effects of peroxynitrite pre-treatment on sarco/endoplasmic reticulum Ca(2+) (SERCA) pump in pig coronary artery smooth muscle and endothelium. In saponin-permeabilized cells, smooth muscle showed much greater rates of the SERCA Ca(2+) pump-dependent (45)Ca(2+) uptake/mg protein than did the endothelial cells. Peroxynitrite treatment of cells inhibited the SERCA pump more severely in smooth muscle cells than in endothelial cells. To determine implications of this observation, we next examined the effect of the SERCA pump inhibitor cyclopiazonic acid (CPA) on intracellular Ca(2+) concentration of intact cultured cells. CPA produced cytosolic Ca(2+) transients in cultured endothelial and smooth muscle cells. Pre-treatment with peroxynitrite (200 microM) inhibited the Ca(2+) transients in the smooth muscle but not in the endothelial cells. CPA contracts de-endothelialized artery rings and relaxes precontracted arteries with intact endothelium. Peroxynitrite (250 microM) pre-treatment inhibited contraction in the de-endothelialized artery rings, but not the endothelium-dependent relaxation. Thus, endothelial cells appear to be more resistant than smooth muscle to the effects of peroxynitrite at the levels of SERCA pump activity, CPA-induced Ca(2+) transients in cultured cells, and the effects of CPA on contractility. The greater resistance of endothelium to peroxynitrite may play a protective role in pathological conditions such as ischemia-reperfusion when excess free radicals are produced.     

(In search of) probabilistic P systems

The aim of this paper is to (preliminarily) discuss various ways of introducing probabilities in membrane systems. We briefly present both ideas already circulated in the literature and new proposals, trying to have a systematic overview of possibilities of associating probabilities with the ingredients of a membrane system: with (localization of) single objects, with multiplicities of objects (hence with the multisets), with the rules (depending or not on the previous applied rule), with the communication targets. For a certain mode of using the probabilities associated with the evolution rules (in string-object P systems) we obtain the computational universality.     

From cells to computers: computing with membranes (P systems)

The aim of this paper is to introduce to the reader the main ideas of computing with membranes, a recent branch of (theoretical) molecular computing. In short, in a cell-like system, multisets of objects evolve according to given rules in the compartments defined by a membrane structure and compute natural numbers as the result of halting sequences of transitions. The model is parallel, nondeterministic. Many variants have already been considered and many problems about them were investigated. We present here some of these variants, focusing on two central classes of results: (1) characterizations of the recursively enumerable sets of numbers and (2) possibilities to solve NP-complete problems in polynomial--even linear--time (of course, by making use of an exponential space). The results are given without proofs. An almost complete bibliography of the domain, at the middle of October 2000, is also provided.     

Proteus syndrome: clinical and surgical aspects

The authors report a new case of Proteus syndrome with delayed diagnosis and they discuss the place of surgery in this syndrome.     

Small universal spiking neural P systems

In search for small universal computing devices of various types, we consider here the case of spiking neural P systems (SN P systems), in two variants: as devices that compute functions and as devices that generate sets of numbers. We start with the first case and we produce a universal spiking neural P system with 84 neurons. If a slight generalization of the used rules is adopted, namely, we allow rules for producing simultaneously several spikes, then a considerable reduction, to 49 neurons, is obtained. For SN P systems used as generators of sets of numbers, we find a universal system with restricted rules having 76 neurons and one with extended rules having 50 neurons.     

Removal of chromium on Polyalthia longifolia leaves biomass

Adsorption is an environmental friendly process for removal and/or recovery of heavy metals from wastewater. In recent years, it has been substantiated as a popular technique to treat industrial waste effluents, with significant advantages. In this work, batchwise removal of chromium (III) ions from water by Polyalthia longifolia leaves was studied as a function of adsorbent dose, pH, contact time, and agitation speed. Surface characteristics of the leaves were evaluated by recording IR spectra. The Langmuir, Freundlich, and Temkin adsorption isotherms were employed to explain the sorption process. It was found that one gram of leaves can remove 1.87 mg of trivalent chromium when working at pH 3.0. It has been concluded that Polyalthia longifolia leaves can be used as cost-effective and benign adsorbents for removal of Cr(III) ions from wastewater.     

The multiple‐specificity landscape of modular peptide recognition domains

Modular protein interaction domains form the building blocks of eukaryotic signaling pathways. Many of them, known as peptide recognition domains, mediate protein interactions by recognizing short, linear amino acid stretches on the surface of their cognate partners with high specificity. Residues in these stretches are usually assumed to contribute independently to binding, which has led to a simplified understanding of protein interactions. Conversely, we observe in large binding peptide data sets that different residue positions display highly significant correlations for many domains in three distinct families (PDZ, SH3 and WW). These correlation patterns reveal a widespread occurrence of multiple binding specificities and give novel structural insights into protein interactions. For example, we predict a new binding mode of PDZ domains and structurally rationalize it for DLG1 PDZ1. We show that multiple specificity more accurately predicts protein interactions and experimentally validate some of the predictions for the human proteins DLG1 and SCRIB. Overall, our results reveal a rich specificity landscape in peptide recognition domains, suggesting new ways of encoding specificity in protein interaction networks.     

Three options for citation tracking: Google Scholar,Scopus and Web of Science

Background

Researchers turn to citation tracking to find the most influential articles for a particular topic and to see how often their own published papers are cited. For years researchers looking for this type of information had only one resource to consult: the Web of Science from Thomson Scientific. In 2004 two competitors emerged – Scopus from Elsevier and Google Scholar from Google. The research reported here uses citation analysis in an observational study examining these three databases; comparing citation counts for articles from two disciplines (oncology and condensed matter physics) and two years (1993 and 2003) to test the hypothesis that the different scholarly publication coverage provided by the three search tools will lead to different citation counts from each.

Methods

Eleven journal titles with varying impact factors were selected from each discipline (oncology and condensed matter physics) using the Journal Citation Reports (JCR). All articles published in the selected titles were retrieved for the years 1993 and 2003, and a stratified random sample of articles was chosen, resulting in four sets of articles. During the week of November 7–12, 2005, the citation counts for each research article were extracted from the three sources. The actual citing references for a subset of the articles published in 2003 were also gathered from each of the three sources.

Results

For oncology 1993 Web of Science returned the highest average number of citations, 45.3. Scopus returned the highest average number of citations (8.9) for oncology 2003. Web of Science returned the highest number of citations for condensed matter physics 1993 and 2003 (22.5 and 3.9 respectively). The data showed a significant difference in the mean citation rates between all pairs of resources except between Google Scholar and Scopus for condensed matter physics 2003. For articles published in 2003 Google Scholar returned the largest amount of unique citing material for oncology and Web of Science returned the most for condensed matter physics.

Conclusion

This study did not identify any one of these three resources as the answer to all citation tracking needs. Scopus showed strength in providing citing literature for current (2003) oncology articles, while Web of Science produced more citing material for 2003 and 1993 condensed matter physics, and 1993 oncology articles. All three tools returned some unique material. Our data indicate that the question of which tool provides the most complete set of citing literature may depend on the subject and publication year of a given article.