High accuracy precession measurement with an autometric gyro

High accuracy precession measurement with autometric gyroscope

Unfair competition governs the interaction of pCPI-17 with myosin phosphatase (PP1-MYPT1).

The small phosphoprotein pCPI-17 inhibits myosin light-chain phosphatase (MLCP). Current models postulate that during muscle relaxation, phosphatases other than MLCP dephosphorylate and inactivate pCPI-17 to restore MLCP activity. We show here that such hypotheses are insufficient to account for the observed rapidity of pCPI-17 inactivation in mammalian smooth muscles. Instead, MLCP itself is the critical enzyme for pCPI-17 dephosphorylation. We call the mutual sequestration mechanism through which pCPI-17 and MLCP interact inhibition by unfair competition: MLCP protects pCPI-17 from other phosphatases, while pCPI-17 blocks other substrates from MLCP\u27s active site. MLCP dephosphorylates pCPI-17 at a slow rate that is, nonetheless, both sufficient and necessary to explain the speed of pCPI-17 dephosphorylation and the consequent MLCP activation during muscle relaxation

Efficient computation of the first passage time distribution of the generalized master equation by steady-state relaxation

The generalized master equation or the equivalent continuous time random walk equations can be used to compute the macroscopic first passage time distribution (FPTD) of a complex stochastic system from short-term microscopic simulation data. The computation of the mean first passage time and additional low-order FPTD moments can be simplified by directly relating the FPTD moment generating function to the moments of the local FPTD matrix. This relationship can be physically interpreted in terms of steady-state relaxation, an extension of steady-state flow. Moreover, it is amenable to a statistical error analysis that can be used to significantly increase computational efficiency. The efficiency improvement can be extended to the FPTD itself by modelling it using a Gamma distribution or rational function approximation to its Laplace transform

Macrostate Data Clustering

We develop an effective nonhierarchical data clustering method using an analogy to the dynamic coarse graining of a stochastic system. Analyzing the eigensystem of an interitem transition matrix identifies fuzzy clusters corresponding to the metastable macroscopic states (macrostates) of a diffusive system. A "minimum uncertainty criterion" determines the linear transformation from eigenvectors to cluster-defining window functions. Eigenspectrum gap and cluster certainty conditions identify the proper number of clusters. The physically motivated fuzzy representation and associated uncertainty analysis distinguishes macrostate clustering from spectral partitioning methods. Macrostate data clustering solves a variety of test cases that challenge other methods.Comment: keywords: cluster analysis, clustering, pattern recognition, spectral graph theory, dynamic eigenvectors, machine learning, macrostates, classificatio

Sam68 exerts separable effects on cell cycle progression and apoptosis

BACKGROUND: The RNA-binding protein Sam68 has been implicated in a number of cellular processes, including transcription, RNA splicing and export, translation, signal transduction, cell cycle progression and replication of the human immunodeficiency virus and poliovirus. However, the precise impact it has on essential cellular functions remains largely obscure. RESULTS: In this report we show that conditional overexpression of Sam68 in fibroblasts results in both cell cycle arrest and apoptosis. Arrest in G1 phase of the cell cycle is associated with decreased levels of cyclins D1 and E RNA and protein, resulting in dramatically reduced Rb phosphorylation. Interestingly, cell cycle arrest does not require the specific RNA binding ability of Sam68. In marked contrast, induction of apoptosis by Sam68 absolutely requires a fully-functional RNA binding domain. Moreover, the anti-cancer agent trichostatin A potentiates Sam68-driven apoptosis. CONCLUSIONS: For the first time we have shown that Sam68, an RNA binding protein with multiple apparent functions, exerts functionally separable effects on cell proliferation and survival, dependent on its ability to bind specifically to RNA. These findings shed new light on the ability of signal transducing RNA binding proteins to influence essential cell function. Moreover, the ability of a class of anti-cancer therapeutics to modulate its ability to promote apoptosis suggests that Sam68 status may impact some cancer treatments

A flexible, extensible object oriented real-time near photorealistic visualization system:the system framework design

In this paper we describe a novel, extensible visualization system currently under development at Aston University. We introduce modern programming methods, such as the use of data driven programming, design patterns, and the careful definition of interfaces to allow easy extension using plug-ins, to 3D landscape visualization software. We combine this with modern developments in computer graphics, such as vertex and fragment shaders, to create an extremely flexible, extensible real-time near photorealistic visualization system. In this paper we show the design of the system and the main sub-components. We stress the role of modern programming practices and illustrate the benefits these bring to 3D visualization. © 2006 Springer-Verlag Berlin Heidelberg