Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.

Computing Zeros of Analytic Functions in the Complex Plane without using Derivatives

A new approach to evaluating all multiple complex roots of analytical function f(z) confined to the specified rectangular domain of complex plane has been developed and implemented in Fortran code. Generally f (z), despite being holomorphic function, does not have a closed analytical form thereby inhibiting explicit evaluation of its derivatives. The latter constraint poses a major challenge to implementation of the robust numerical algorithm. This work is at the instrumental level and provides an enabling tool for solving a broad class of eigenvalue problems and polynomial approximations.

Natural three-qubit interactions in one-way quantum computing

We address the effects of natural three-qubit interactions on the computational power of one-way quantum computation. A benefit of using more sophisticated entanglement structures is the ability to construct compact and economic simulations of quantum algorithms with limited resources. We show that the features of our study are embodied by suitably prepared optical lattices, where effective three-spin interactions have been theoretically demonstrated. We use this to provide a compact construction for the Toffoli gate. Information flow and two-qubit interactions are also outlined, together with a brief analysis of relevant sources of imperfection.

Down-regulation of beta1,4-galactosyltransferase V is a critical part of etoposide-induced apoptotic process and could be mediated by decreasing Sp1 levels in human glioma cells.

beta1,4-Galactosyltransferase V (beta1,4GalT V; EC 2.4.1.38) is considered to be very important in glioma for expressing transformation-related highly branched N-glycans. Recently, we have characterized beta1,4GalT V as a positive growth regulator in several glioma cell lines. However, the role of beta1,4GalT V in glioma therapy has not been clearly reported. In this study, interfering with the expression of beta1,4GalT V by its antisense cDNA in SHG44 human glioma cells markedly promoted apoptosis induced by etoposide and the activation of caspases as well as processing of Bid and expression of Bax and Bak. Conversely, the ectopic expression of beta1,4GalT V attenuated the apoptotic effect of etoposide on SHG44 cells. In addition, both the beta1,4GalT V transcription and the binding of total or membrane glycoprotein with Ricinus communis agglutinin-I (RCA-I) were partially reduced in etoposide-treated SHG44 cells, correlated well with a decreased level of Sp1 that has been identified as an activator of beta1,4GalT V transcription. Collectively, our results suggest that the down-regulation of beta1,4GalT V expression plays an important role in etoposide-induced apoptosis and could be mediated by a decreasing level of Sp1 in SHG44 cells, indicating that inhibitors of beta1,4GalT V may enhance the therapeutic efficiency of etoposide for malignant glioma.

One-way quantum computing in a decoherence-free subspace

We introduce a novel scheme for one-way quantum computing (QC) based on the use of information encoded qubits in an effective cluster state resource. With the correct encoding structure, we show that it is possible to protect the entangled resource from phase damping decoherence, where the effective cluster state can be described as residing in a decoherence-free subspace (DFS) of its supporting quantum system. One-way QC then requires either single or two-qubit adaptive measurements. As an example where this proposal can be realized, we describe an optical lattice set-up where the scheme provides robust quantum information processing. We also outline how one can adapt the model to provide protection from other types of decoherence.

Learning soft computing control strategies in a modular neural network architecture

Modelling and control of nonlinear dynamical systems is a challenging problem since the dynamics of such systems change over their parameter space. Conventional methodologies for designing nonlinear control laws, such as gain scheduling, are effective because the designer partitions the overall complex control into a number of simpler sub-tasks. This paper describes a new genetic algorithm based method for the design of a modular neural network (MNN) control architecture that learns such partitions of an overall complex control task. Here a chromosome represents both the structure and parameters of an individual neural network in the MNN controller and a hierarchical fuzzy approach is used to select the chromosomes required to accomplish a given control task. This new strategy is applied to the end-point tracking of a single-link flexible manipulator modelled from experimental data. Results show that the MNN controller is simple to design and produces superior performance compared to a single neural network (SNN) controller which is theoretically capable of achieving the desired trajectory. (C) 2003 Elsevier Ltd. All rights reserved.