Differential localization and regulation of death and decoy receptors for TNF-related apoptosis-inducing ligand (TRAIL) in human melanoma cells

Induction of apoptosis in cells by TNF-related apoptosis-inducing ligand (TRAIL), a member of the TNF family, is believed to be regulated by expression of two death-inducing and two inhibitory (decoy) receptors on the cell surface. In previous studies we found no correlation between expression of decoy receptors and susceptibility of human melanoma cells to TRAIL-induced apoptosis, In view of this, we studied the localization of the receptors in melanoma cells by confocal microscopy to better understand their function. We show that the death receptors TRAIL-R1 and R2 are located in the trans-Golgi network, whereas the inhibitory receptors TRAIL-R3 and -R4 are located in the nucleus. After exposure to TRAIL, TRAIL-R1 and -R2 are internalized into endosomes, whereas TRAIL-R3 and -R4 undergo relocation from the nucleus to the cytoplasm and cell membranes. This movement of decoy receptors was dependent on signals from TRAIL-R1 and -R2, as shown by blocking experiments with Abs to TRAIL-R1 and -R2, The location of TRAIL-R1, -R3, and -R4 in melanoma cells transfected with cDNA for these receptors was similar to that in nontransfected cells, Transfection of TRAIL-R3 and -R4 increased resistance of the melanoma lines to TRAIL-induced apoptosis even in melanoma lines that naturally expressed these receptors. These results indicate that abnormalities in decoy receptor location or function may contribute to sensitivity of melanoma to TRAIL-induced apoptosis and suggest that further studies are needed on the functional significance of their nuclear location and TRAIL-induced movement within cell.

Disagreement between correlations of quantum mechanics and stochastic electrodynamics in the damped parametric oscillator

Intracavity and external third order correlations in the damped nondegenerate parametric oscillator are calculated for quantum mechanics and stochastic electrodynamics (SED), a semiclassical theory. The two theories yield greatly different results, with the correlations of quantum mechanics being cubic in the system's nonlinear coupling constant and those of SED being linear in the same constant. In particular, differences between the two theories are present in at least a mesoscopic regime. They also exist when realistic damping is included. Such differences illustrate distinctions between quantum mechanics and a hidden variable theory for continuous variables.

Kinematic and non-linear analysis of foldable barrel vaults

Kinematic analysis is conducted to derive the geometric constraints for the geometric design of foldable barrel vaults (FBV) composed of polar or angulated scissor units. Non-linear structural analysis is followed to determine the structural response of FBVs in the fully deployed configuration under static loading. Two load cases are considered: cross wind and longitudinal wind. The effect of varying member sizes, depth-to-span ratio and geometric imperfections is examined. (C) 2000 Elsevier Science Ltd. All rights reserved.

The psychophysiology of anticipation

The current research explored the processes that predominate during the anticipation of an emotionally salient event. Experiment 1 (N536), employed three different conditional stimuli followed by pictorial pleasant, unpleasant or neutral unconditioned stimuli. Half the participants were trained with visual CSs, the other half with tactile CSs. In the group trained with visual CSs, startle eyeblinks were larger and faster during CSs that were paired with unpleasant pictures than CSs paired with neutral or pleasant pictures respectively, indicating an affect startle pattern. This linear trend was not found in the group trained with tactile CSs. Experiment 2 (N564) aimed to investigate whether the affective pattern found in the startle data in Experiment 1 could also be found using a behavioural measure of emotion. This time participants’ reaction time during a post-experimental affective priming taskwas used as dependantmeasure to assess the presence of emotional learning. Instead of a simple differential conditioning task, an occasion setting paradigm was employed and participants were trained using either a feature positive or feature negative design with pleasant or unpleasant picture USs. For participants trained with unpleasant USs, valence ratings collected before and after conditioning training suggested the presence of emotional learning, whereas no such pattern was found for participants trained with pleasant USs. These findings were not confirmed in the priming data.

Utilizing encoding in scalable linear optics quantum computing

We present a scheme which offers a significant reduction in the resources required to implement linear optics quantum computing. The scheme is a variation of the proposal of Knill, Laflamme and Milburn, and makes use of an incremental approach to the error encoding to boost probability of success.

High-breakdown linear discriminant analysis

The classification rules of linear discriminant analysis are defined by the true mean vectors and the common covariance matrix of the populations from which the data come. Because these true parameters are generally unknown, they are commonly estimated by the sample mean vector and covariance matrix of the data in a training sample randomly drawn from each population. However, these sample statistics are notoriously susceptible to contamination by outliers, a problem compounded by the fact that the outliers may be invisible to conventional diagnostics. High-breakdown estimation is a procedure designed to remove this cause for concern by producing estimates that are immune to serious distortion by a minority of outliers, regardless of their severity. In this article we motivate and develop a high-breakdown criterion for linear discriminant analysis and give an algorithm for its implementation. The procedure is intended to supplement rather than replace the usual sample-moment methodology of discriminant analysis either by providing indications that the dataset is not seriously affected by outliers (supporting the usual analysis) or by identifying apparently aberrant points and giving resistant estimators that are not affected by them.

Robust algorithms for solving stochastic partial differential equations

A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.

Differential disease reactions on lucerne genotypes inoculated with Phytophthora medicaginis isolates from lucerne and chickpea

Stem inoculation of clonally propagated lucerne genotypes was used to assess levels of host species and genotype specialisation in Phytophthora medicaginis. A quantitative assessment of pathogenic aggressiveness of 29 P. medicaginis isolates (from lucerne and chickpea) on 9 different clonally propagated lucerne genotypes revealed no significant difference in aggressiveness between isolates from lucerne and those from chickpea on all of the lucerne genotypes. This supported previous studies which showed that P. medicaginis isolates from lucerne and chickpea were indistinguishable using random amplified polymorphic DNA (RAPD) analysis. Analysis of pathogenic aggressiveness towards individual lucerne genotypes revealed, for the first time, specificity of individual P. medicaginis isolates. This has implications for breeding for resistance to P. medicaginis in lucerne, where screening should be done using the widest range of pathogen specificity obtainable.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.