Preliminary Evidence on the Diagnostic and Molecular Role of Circulating Soluble EGFR in Non-Small Cell Lung Cancer

Assessment of biological diagnostic factors providing clinically-relevant information to guide physician decision-making are still needed for diseases with poor outcomes, such as non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) is a promising molecule in the clinical management of NSCLC. While the EGFR transmembrane form has been extensively investigated in large clinical trials, the soluble, circulating EGFR isoform (sEGFR), which may have a potential clinical use, has rarely been considered. This study investigates the use of sEGFR as a potential diagnostic biomarker for NSCLC and also characterizes the biological function of sEGFR to clarify the molecular mechanisms involved in the course of action of this protein. Plasma sEGFR levels from a heterogeneous cohort of 37 non-advanced NSCLC patients and 54 healthy subjects were analyzed by using an enzyme-linked immunosorbent assay. The biological function of sEGFR was analyzed in vitro using NSCLC cell lines, investigating effects on cell proliferation and migration. We found that plasma sEGFR was significantly decreased in the NSCLC patient group as compared to the control group (median value: 48.6 vs. 55.6 ng/mL respectively; p = 0.0002). Moreover, we demonstrated that sEGFR inhibits growth and migration of NSCLC cells in vitro through molecular mechanisms that included perturbation of EGF/EGFR cell signaling and holoreceptor internalization. These data show that sEGFR is a potential circulating biomarker with a physiological protective role, providing a first approach to the functional role of the soluble isoform of EGFR. However, the impact of these data on daily clinical practice needs to be further investigated in larger prospective studies.     

Modelling of effects of ultrastructural morphology on the hygroelastic properties of wood fibres

Wood fibres constitute the structural framework of e.g. wood, paper, board and composites, where stiffness and dimensional stability are of importance. An analytical modelling approach has been used for prediction of hygroelastic response, and assessment of the stresses in thick-walled cylinder models of wood fibres. A wood fibre was idealised as a multilayered hollow cylinder made of orthotropic material with helical orientation. The hygroelastic response of the layered assembly due to axisymmetric loading and moisture content changes was obtained by solving the corresponding boundary value problem of elasticity. A simple solution scheme based on the state space approach and the transfer matrix method was employed. This was combined with an analytical ultrastructural homogenisation method, used to link hygroelastic properties of constituent wood polymers to properties of each layer. Predicted hygroelastic response captured experimentally measured behaviour. Fibres that were constrained not to twist showed a stiffer response than fibres allowed twisting under uniaxial loading. It was also shown that the ultrastructure, i.e. the microfibril angle, will control the hygroexpansion in the same way as it controls the compliance of the cell wall. Qualitative failure trends comparable with experimental observations could be established with stress analysis and a simple plane-stress failure criterion.     

Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.     

A survey on approaches to gridification

The Grid shows itself as a globally distributed computing environment, in which hardware and software resources are virtualized to transparently provide applications with vast capabilities. Just like the electrical power grid, the Grid aims at offering a powerful yet easy‐to‐use computing infrastructure to which applications can be easily ‘plugged’ and efficiently executed. Unfortunately, it is still very difficult to Grid‐enable applications, since current tools force users to take into account many details when adapting applications to run on the Grid. In this paper, we survey some of the recent efforts in providing tools for easy gridification of applications and propose several taxonomies to identify approaches followed in the materialization of such tools. We conclude this paper by describing common features among the proposed approaches, and by pointing out open issues and future directions in the research and development of gridification methods. Copyright © 2007 John Wiley & Sons, Ltd.     

Electrochemical chlorination of azulene derivatives: Insight into the mechanism of anodic oxidative chlorination

The cyclic voltammetry behavior of a series of five 1-substituted azulenes has been investigated as well as the electrochemical chlorination of these compounds. In the case of azulene compounds containing electron withdrawing groups which have higher oxidation potentials than that of the chloride ion, the electrochemical chlorination led usually to 3-chloro derivatives. The electrochemical chlorination fails for azulenes with lower oxidation potentials. Additionally some polyhalogenated compounds were obtained by controlled potential electrolyses. The paper also discusses the reaction mechanism of the electrochemical halogenation of 1-substituted azulenes.     

Simple and accurate scheme for fluid velocity interpolation for Eulerian-Lagrangian computation of dispersed flows in 3D curvilinear grids

Particle tracking in turbulent flows in complex domains requires accurate interpolation of the fluid velocity field. If grids are non-orthogonal and curvilinear, the most accurate available interpolation methods fail. We propose an accurate interpolation scheme based on Taylor series expansion of the local fluid velocity about the grid point nearest to the desired location. The scheme is best suited for curvilinear grids with non-orthogonal computational cells. We present the scheme with second-order accuracy, yet the order of accuracy of the method can be adapted to that of the Navier-Stokes solver.An application to particle dispersion in a turbulent wavy channel is presented, for which the scheme is tested against standard linear interpolation. Results show that significant discrepancies can arise in the particle displacement produced by the two schemes, particularly in the near-wall region which is often discretized with highly-distorted computational cells.     

Query language-based inverses of schema mappings: semantics, computation, and closure properties

The inversion of schema mappings has been identified as one of the fundamental operators for the development of a general framework for metadata management. During the last few years, three alternative notions of inversion for schema mappings have been proposed (Fagin-inverse (Fagin, TODS 32(4), 25:1–25:53, 2007), quasi-inverse (Fagin et?al., TODS 33(2), 11:1–11:52, 2008), and maximum recovery (Arenas et?al., TODS 34(4), 22:1–22:48, 2009)). However, these notions lack some fundamental properties that limit their practical applicability: most of them are expressed in languages including features that are difficult to use in practice, some of these inverses are not guaranteed to exist for mappings specified with source-to-target tuple-generating dependencies (st-tgds), and it has been futile to search for a meaningful mapping language that is closed under any of these notions of inverse. In this paper, we develop a framework for the inversion of schema mappings that fulfills all of the above requirements. It is based on the notion of ${\mathcal{C}}$ -maximum recovery, for a query language ${\mathcal{C}}$ , a notion designed to generate inverse mappings that recover back only the information that can be retrieved with queries in ${\mathcal{C}}$ . By focusing on the language of conjunctive queries (CQ), we are able to find a mapping language that contains the class of st-tgds, is closed under CQ-maximum recovery, and for which the chase procedure can be used to exchange data efficiently. Furthermore, we show that our choices of inverse notion and mapping language are optimal, in the sense that choosing a more expressive inverse operator or mapping language causes the loss of these properties.