Relative involvement of protein kinase C and of the estrogen receptor in the cytotoxic action of a population of triphenylethylenes on MCF7 cells as revealed by correspondence factorial (CF) analysis

A multivariate statistical method, correspondence factorial (CF) analysis, was used to examine the correlations among the protein binding and cell proliferation effects of a series of 36 di- and triphenylethylenes (DPEs and TPEs). The analysis was applied to a study which measured their competition for estradiol binding to cytosol estrogen receptor (ER), their influence on protein kinase C (PKC) activity under different conditions of enzyme activation, their ability to promote the growth of a breast cancer cell line and to inhibit growth at high concentrations (cytotoxicity). The CF analysis revealed several levels of correlation. First, it distinguished those molecules within the population that stimulated rather than inhibited PKC activity. Second, it made apparent a strong correlation between cytotoxicity and inhibition of Ca++ and phosphatidylserine-dependent PKC activity, which was most marked when the enzyme had been activated by diacylglycerol indicating that PKC inhibition under physiological conditions might contribute to the overall cytotoxicity of these compounds. Third, a lower level of correlation was established between competition for ER binding and cytotoxicity. Taken together, the results suggest that MCF7 cells might be most sensitive to a cytotoxic effect of TPEs (via PKC and other targets) when they at the same time decrease estrogen-stimulated proliferation via an ER-mediated antiestrogenic effect.     

Introducing fuzziness in object models and database interfaces through aspects

Imperfection in information can be considered a crosscutting concern that manifests itself in diverse kinds of imprecision, uncertainty, or inconsistency in the data models of a software system. The extension of existing programming and querying interfaces for the different aspects of information imperfection requires a proper modularization of the different concerns of numerical imprecision handling, so that the extensions do not interfere with existing programming practices and do not obscure the original design. Aspect‐oriented design (AOD) enables such a form of nonintrusive extensions to be added to existing software libraries, clearly separating fuzziness or other imperfections in data as a differentiated concern that can be considered from the early phases of development. In this article, a general framework for aspect‐based extension of data models and fuzzy databases is described, and some design and implementation issues of such AOD‐based extensions on OJB database libraries are described as a case study. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 1199–1216, 2006.     

An expert PID controller uses refined ziegler and nichols rules and fuzzy logic ideas

This article proposes a scheme for the on-line adjustment of three mode controller settings based on experimental measurements of closed-loop performance. It uses a recently developed heuristic tuning procedure to identify estimated process parameters. This method may give rise to conflicting estimates. Fuzzy Set theory is applied to manage the situation in terms of a fuzzy conjunction to combine the various estimates. PID control was chosen because of its wide use in the industrial environment due to driving simplicity and robustness. The article shows design, development, and computer simulation aspects.     

Isomerization of n-hexane over mono- and bimetallic Pd–Pt catalysts supported on ZrO2–Al2O3–WOx prepared by sol–gel

The catalytic performance of mono- and bimetallic Pd (0.6, 1.0 wt.%)–Pt (0.3 wt.%) catalysts supported on ZrO₂ (70, 85 wt.%)–Al₂O₃ (15, 0 wt.%)–WO_x (15 wt.%) prepared by sol–gel was studied in the hydroisomerization of n-hexane. The catalysts were characterized by N₂ physisorption, XRD, TPR, XPS, Raman, NMR, and FT-IR of adsorbed pyridine. The preparation of ZrW and ZrAlW mixed oxides by sol–gel favored the high dispersion of WO_x and the stabilization of zirconia in the tetragonal phase. The Al incorporation avoided the formation of monoclinic-WO₃ bulk phase. The catalysts increased their S_BET for about 15% promoted by Al₂O₃ addition. Various oxidation states of WO_x species coexist on the surface of the catalysts after calcination. The structure of the highly dispersed surface WO_x species is constituted mainly of isolated monotungstate and two-dimensional mono-oxotungstate species in tetrahedral coordination. The activity of Pd/ZrW catalysts in the hydroisomerization of n-hexane is promoted both with the addition of Al to the ZrW mixed oxide and the addition of Pt to Pd/ZrAlW catalysts. The improvement in the activity of Pd/ZrAlW catalysts is ascribed to a moderated acid strength and acidity, which can be correlated to the coexistence of W⁶⁺ and reduced-state WO_x species (either W⁴⁺ or W⁰). The addition of Pt to the Pd/ZrAlW catalyst does not modify significantly its acidic character. Selectivity results showed that the catalyst produced 2MP, 3MP and the high octane 2,3-dimethylbutane (2,3-DMB) and 2,2-dimethylbutane (2,2-DMB) isomers.     

Effects of allelochemicals on plant respiration and oxygen isotope fractionation by the alternative oxidase

The goal of this investigation was to determine the effects of allelochemicals on plant respiration that thereby may be responsible for their role in growth inhibition. We have tested the effects of juglone, quercetin, cinnamic acid, and-pinene on respiration rates, and electron partitioning through the cytochrome and alternative respiratory pathways, by measuring on-line oxygen consumption and oxygen isotope fractionation in soybean cotyledon tissue. Cinnamic acid and-pinene decreased the oxygen consumption rate and increased the relative partitioning of electron transport to the alternative pathway. Possible biochemical mechanisms of these effects are discussed.     

Discovering social structures of local influence by using tweetStimuli

Information diffusion in large-scale networks has been studied to identify the users influence. The influence has been targeted as a key feature either to reach large populations or influencing public opinion. Through the use of micro-blogs, such as Twitter, global influencers have been identified and ranked based on message propagation (retweets). In this paper, a new application is presented, which allows to find first and classify then the local influence on Twitter: who have influenced you and who have been influenced by you. Until now, social structures of tweets’ original authors that have been either retweeted or marked as favourites are unobservable. Throughout this application, these structures can be discovered and they reveal the existence of communities formed by users of similar profile (that are connected among them) interrelated with other similar profile users’ communities.     

Synthesis of UHMW-PE by a Highly Active Homogeneous System: η5-(C5H5)2Ti(η1-OC(O)C6H5)2/MAO

Summary The complex ⁵-(C₅H₅)₂Ti (¹-OC(O)C₆H₅)₂ was synthesized and activated with MA0 for ethylene polymerization. The resultant polymer is UHMW-PE with a viscosimetric molecular weight of Mv = 6.8 x 10⁶ to 0.7 x 10⁶ g/mol dependent on the temperature of the reaction. The effects of the Al/Ti molar ratio and temperature of the reaction on the catalytic activity and polymer properties were studied.     

Dense subgraph maintenance under streaming edge weight updates for real-time story identification

Recent years have witnessed an unprecedented proliferation of social media. People around the globe author, everyday, millions of blog posts, social network status updates, etc. This rich stream of information can be used to identify, on an ongoing basis, emerging stories, and events that capture popular attention. Stories can be identified via groups of tightly coupled real-world entities, namely the people, locations, products, etc, that are involved in the story. The sheer scale and rapid evolution of the data involved necessitate highly efficient techniques for identifying important stories at every point of time. The main challenge in real-time story identification is the maintenance of dense subgraphs (corresponding to groups of tightly coupled entities) under streaming edge weight updates (resulting from a stream of user-generated content). This is the first work to study the efficient maintenance of dense subgraphs under such streaming edge weight updates. For a wide range of definitions of density, we derive theoretical results regarding the magnitude of change that a single edge weight update can cause. Based on these, we propose a novel algorithm, DynDens, which outperforms adaptations of existing techniques to this setting and yields meaningful, intuitive results. Our approach is validated by a thorough experimental evaluation on large-scale real and synthetic datasets.