Modelling the MAPK signalling pathway using a two-stage identification algorithm

Signal transduction pathways describe the dynamics of cellular response to input signalling molecules at receptors on the cell membrane. The Mitogen-Activated Protein Kinase (MAPK) cascade is one of such pathways that are involved in many important cellular processes including cell growth and proliferation. This paper describes a black-box model of this pathway created using an advanced two-stage identification algorithm. Identification allows us to capture the unique features and dynamics of the pathway and also opens up the possibility of regulatory control design. In the approach described, an optimal model is obtained by performing model subset selection in two stages, where the terms are first determined by a forward selection method and then modified using a backward selection model refinement. The simulation results demonstrate that the model selected using the two-stage algorithm performs better than with the forward selection method alone.

Liquid structure of the ionic liquid, 1-methyl-4-cyanopyridinium bis{(trifluoromethyl)sulfonyl}imide determined from neutron scattering and molecular dynamics simulations

The liquid structure of 1-methyl-4-cyanopyridinium bis {(trifluoromethyl)sulfonyl}imide, a prototypical ionic liquid containing an electron-withdrawing group on the cation, has been investigated at 368 K. Experimental neutron scattering combined with empirical potential structure refinement analysis of the data and classical molecular dynamics simulations have been used to probe the liquid structure in detail. Both techniques generated highly consistent results that provide valuable validation of the force fields and refinement approaches. A significant degree of apparent charge ordering is found in the liquid structure, although the nonspherical shape of the ions results in interpenetration of cations into the first shell of adjacent cations, with much shorter closest contact distances than the averaged center-of-mass cation-cation and cation-anion separations.

Liquid structure of 1, 3-dimethylimidazolium salts

The structure of liquid 1, 3-dimethylimidazolium hexafluorophosphate is described in detail and compared with the structure of 1, 3-dimethylimidazolium chloride. In each case, the data were obtained from neutron diffraction experiments and analysed using an empirical potential structure refinement process. Overall, the structures are similar; however, significant differences arise from the variation in anion size.

Semi-formal Models to Support Program Development: Autonomic Management within Component Based Parallel and Distributed Programming

Functional and non-functional concerns require different programming effort, different techniques and different methodologies when attempting to program efficient parallel/distributed applications. In this work we present a "programmer oriented" methodology based on formal tools that permits reasoning about parallel/distributed program development and refinement. The proposed methodology is semi-formal in that it does not require the exploitation of highly formal tools and techniques, while providing a palatable and effective support to programmers developing parallel/distributed applications, in particular when handling non-functional concerns.

Mechanism of Activation of a G Protein-coupled Receptor, the Human Cholecystokinin-2 Receptor

G protein-coupled receptors (GPCRs) represent a major focus in functional genomics programs and drug development research, but their important potential as drug targets contrasts with the still limited data available concerning their activation mechanism. Here, we investigated the activation mechanism of the cholecystokinin-2 receptor (CCK2R). The three-dimensional structure of inactive CCK2R was homology-modeled on the basis of crystal coordinates of inactive rhodopsin. Starting from the inactive CCK2R modeled structure, active CCK2R (namely cholecystokinin-occupied CCK2R) was modeled by means of steered molecular dynamics in a lipid bilayer and by using available data from other GPCRs, including rhodopsin. By comparing the modeled structures of the inactive and active CCK2R, we identified changes in the relative position of helices and networks of interacting residues, which were expected to stabilize either the active or inactive states of CCK2R. Using targeted molecular dynamics simulations capable of converting CCK2R from the inactive to the active state, we delineated structural changes at the atomic level. The activation mechanism involved significant movements of helices VI and V, a slight movement of helices IV and VII, and changes in the position of critical residues within or near the binding site. The mutation of key amino acids yielded inactive or constitutively active CCK2R mutants, supporting this proposed mechanism. Such progress in the refinement of the CCK2R binding site structure and in knowledge of CCK2R activation mechanisms will enable target-based optimization of nonpeptide ligands.

A heuristic model for the simulation of the deformation of elastic and spongy material for virtual reality applications

This paper presents a practical algorithm for the simulation of interactive deformation in a 3D polygonal mesh model. The algorithm combines the conventional simulation of deformation using a spring-mass-damping model, solved by explicit numerical integration, with a set of heuristics to describe certain features of the transient behaviour, to increase the speed and stability of solution. In particular, this algorithm was designed to be used in the simulation of synthetic environments where it is necessary to model realistically, in real time, the effect on non-rigid surfaces being touched, pushed, pulled or squashed. Such objects can be solid or hollow, and have plastic, elastic or fabric-like properties. The algorithm is presented in an integrated form including collision detection and adaptive refinement so that it may be used in a self-contained way as part of a simulation loop to include human interface devices that capture data and render a realistic stereoscopic image in real time. The algorithm is designed to be used with polygonal mesh models representing complex topology, such as the human anatomy in a virtual-surgery training simulator. The paper evaluates the model behaviour qualitatively and then concludes with some examples of the use of the algorithm.

Network formation under mutual consent and costly communication

We consider two different approaches to describe the formation of social networks under mutual consent and costly communication. First, we consider a network-based approach; in particular Jackson–Wolinsky’s concept of pairwise stability. Next, we discuss a non-cooperative game-theoretic approach, through a refinement of the Nash equilibria of Myerson’s consent game. This refinement, denoted as monadic stability, describes myopically forward looking behavior of the players. We show through an equivalence that the class of monadically stable networks is a strict subset of the class of pairwise stable networks that can be characterized fully by modifications of the properties defining pairwise stability.

SoC memory hierarchy derivation from dataflow graphs

Hardware synthesis from dataflow graphs of signal processing systems is a growing research area as focus shifts to high level design methodologies. For data intensive systems, dataflow based synthesis can lead to an inefficient usage of memory due to the restrictive nature of synchronous dataflow and its inability to easily model data reuse. This paper explores how dataflow graph changes can be used to drive both the on-chip and off-chip memory organisation and how these memory architectures can be mapped to a hardware implementation. By exploiting the data reuse inherent to many image processing algorithms and by creating memory hierarchies, off-chip memory bandwidth can be reduced by a factor of a thousand from the original dataflow graph level specification of a motion estimation algorithm, with a minimal increase in memory size. This analysis is verified using results gathered from implementation of the motion estimation algorithm on a Xilinx Virtex-4 FPGA, where the delay between the memories and processing elements drops from 14.2 ns down to 1.878 ns through the refinement of the memory architecture. Care must be taken when modeling these algorithms however, as inefficiencies in these models can be easily translated into overuse of hardware resources.

Anisotropic seismic inversion using a multigrid Monte Carlo approach

We propose a new approach for the inversion of anisotropic P-wave data based on Monte Carlo methods combined with a multigrid approach. Simulated annealing facilitates objective minimization of the functional characterizing the misfit between observed and predicted traveltimes, as controlled by the Thomsen anisotropy parameters (epsilon, delta). Cycling between finer and coarser grids enhances the computational efficiency of the inversion process, thus accelerating the convergence of the solution while acting as a regularization technique of the inverse problem. Multigrid perturbation samples the probability density function without the requirements for the user to adjust tuning parameters. This increases the probability that the preferred global, rather than a poor local, minimum is attained. Undertaking multigrid refinement and Monte Carlo search in parallel produces more robust convergence than does the initially more intuitive approach of completing them sequentially. We demonstrate the usefulness of the new multigrid Monte Carlo (MGMC) scheme by applying it to (a) synthetic, noise-contaminated data reflecting an isotropic subsurface of constant slowness, horizontally layered geologic media and discrete subsurface anomalies; and (b) a crosshole seismic data set acquired by previous authors at the Reskajeage test site in Cornwall, UK. Inverted distributions of slowness (s) and the Thomson anisotropy parameters (epsilon, delta) compare favourably with those obtained previously using a popular matrix-based method. Reconstruction of the Thomsen epsilon parameter is particularly robust compared to that of slowness and the Thomsen delta parameter, even in the face of complex subsurface anomalies. The Thomsen epsilon and delta parameters have enhanced sensitivities to bulk-fabric and fracture-based anisotropies in the TI medium at Reskajeage. Because reconstruction of slowness (s) is intimately linked to that epsilon and delta in the MGMC scheme, inverted images of phase velocity reflect the integrated effects of these two modes of anisotropy. The new MGMC technique thus promises to facilitate rapid inversion of crosshole P-wave data for seismic slownesses and the Thomsen anisotropy parameters, with minimal user input in the inversion process.

Out-of-field cell survival following exposure to intensity-modulated radiation fields

PURPOSE:
To determine the in-field and out-of-field cell survival of cells irradiated with either primary field or scattered radiation in the presence and absence of intercellular communication.
METHODS AND MATERIALS:
Cell survival was determined by clonogenic assay in human prostate cancer (DU145) and primary fibroblast (AGO1552) cells following exposure to different field configurations delivered using a 6-MV photon beam produced with a Varian linear accelerator.
RESULTS:
Nonuniform dose distributions were delivered using a multileaf collimator (MLC) in which half of the cell population was shielded. Clonogenic survival in the shielded region was significantly lower than that predicted from the linear quadratic model. In both cell lines, the out-of-field responses appeared to saturate at 40%-50% survival at a scattered dose of 0.70 Gy in DU-145 cells and 0.24 Gy in AGO1522 cells. There was an approximately eightfold difference in the initial slopes of the out-of-field response compared with the a-component of the uniform field response. In contrast, cells in the exposed part of the field showed increased survival. These observations were abrogated by direct physical inhibition of cellular communication and by the addition of the inducible nitric oxide synthase inhibitor aminoguanidine known to inhibit intercellular bystander effects. Additional studies showed the proportion of cells irradiated and dose delivered to the shielded and exposed regions of the field to impact on response.
CONCLUSIONS:
These data demonstrate out-of-field effects as important determinants of cell survival following exposure to modulated irradiation fields with cellular communication between differentially irradiated cell populations playing an important role. Validation of these observations in additional cell models may facilitate the refinement of existing radiobiological models and the observations considered important determinants of cell survival.

New ruthenium(II) complexes of functionalized monoanionic aryldiamine N,C,N'-terdentate ligands: Syntheses of [Ru-II{2,6-(Me(2)NCH(2))(2)-4-R-C6H2}(terpy)]Cl+(-); X-ray structure of a dimeric organolithium compound,[Li{2,6-(Me(2)NCH(2))(2)-4-Ph-C6H2}](2)

The new anionic functionalized aryldiamine ligands [2,6-(Me(2)NCH(2))(2)-4-R-C6H2](-) (R = Me(3)SiC=C, C6H5, Me(3)Si), formally derived from [2,6-(Me(2)NCH(2))(2)C6H3](-), have been prepared as their lithium compounds. The compound [Li{2,6-(Me(2)NCH(2))(2)-4-Ph-C6H2}](2) crystallizes in the monoclinic space group C2/c (no. 15) with a = 13.1225(5), b = 13.5844(7), c = 15.9859(12) Angstrom, beta = 105.329(5)degrees, V = 3264.0(3)Angstrom(3), Z = 4. The structure refinement converged to R(1) = 0.0374 for 2037 observed reflections [F-o>4 sigma(F-o)] and wR(2) = 0.0922 for 2560 unique data. The organolithium compounds have been used in transmetalation reactions to give the corresponding functionalized organoruthenium(II) complexes [Ru-II{2,6-(Me(2)NCH(2))(2)-4-R-C6H2}(terpy)]Cl-+(-) (terpy = 2,2';6',2 ''-terpyridine). The Ru-II species with R = HC = C has also been synthesized.

Cell survival responses after exposure to modulated radiation fields.

In the present study survival responses were determined in cells with differing radiosensitivity, specifically primary fibroblast (AG0-1522B), human breast cancer (MDA-MB-231), human prostate cancer (DU-145) and human glioma (T98G) cells, after exposure to modulated radiation fields delivered by shielding 50% of the tissue culture flask. A significant decrease (P < 0.05) in cell survival was observed in the shielded area, outside the primary treatment field (out-of-field), that was lower than predicted when compared to uniform exposures fitted to the linear-quadratic model. Cellular radiosensitivity was demonstrated to be an important factor in the level of response for both the in- and out-of-field regions. These responses were shown to be dependent on secretion-mediated intercellular communication, because inhibition of cellular secreted factors between the in- and out-of-field regions abrogated the response. Out-of-field cell survival was shown to increase after pretreatment of cells with agents known to inhibit factors involved in mediating radiation-induced bystander signaling (aminoguanidine, DMSO or cPTIO). These data illustrate a significant decrease in survival out-of-field, dependent upon intercellular communication, in several cell lines with varying radiosensitivity after exposure to a modulated radiation field. This study provides further evidence for the importance of intercellular signaling in modulated exposures, where dose gradients are present, and may inform the refinement of established radiobiological models to facilitate the optimization of advanced radiotherapy treatment plans.

Improved structure optimization for fuzzy-neural networks

Fuzzy-neural-network-based inference systems are well-known universal approximators which can produce linguistically interpretable results. Unfortunately, their dimensionality can be extremely high due to an excessive number of inputs and rules, which raises the need for overall structure optimization. In the literature, various input selection methods are available, but they are applied separately from rule selection, often without considering the fuzzy structure. This paper proposes an integrated framework to optimize the number of inputs and the number of rules simultaneously. First, a method is developed to select the most significant rules, along with a refinement stage to remove unnecessary correlations. An improved information criterion is then proposed to find an appropriate number of inputs and rules to include in the model, leading to a balanced tradeoff between interpretability and accuracy. Simulation results confirm the efficacy of the proposed method.

Technology Assessment for a Complex Aircraft System using Technology Scenarios

Military decision makers need to understand and assess the benefits and consequences of their decisions in order to make cost efficient, timely, and successful choices. Technology selection is one such critical decision, especially when considering the design or retrofit of a complex system, such as an aircraft. An integrated and systematic methodology that will support decision-making between technology alternatives and options while assessing the consequences of such decisions is a key enabler. This paper presents and demonstrates, through application to a notional medium range short takeoff and landing (STOL) aircraft, one such enabler: the Technology Impact Forecasting (TIF) method. The goal of the TIF process is to explore both generic, undefined areas of technology, as well as specific technologies, and assess their potential impacts. This is actualized through the development and use of technology scenarios, and allows the designer to determine where to allocate resources for further technology definition and refinement, as well as provide useful design information. The paper particularly discusses the use of technology scenarios and demonstrates their use in the exploration of seven technologies of varying technology readiness levels.