Data mining of gene arrays for biomarkers of survival in ovarian cancer

The expected five-year survival rate from a stage III ovarian cancer diagnosis is a mere 22%; this applies to the 7000 new cases diagnosed yearly in the UK. Stratification of patients with this heterogeneous disease, based on active molecular pathways, would aid a targeted treatment improving the prognosis for many cases. While hundreds of genes have been associated with ovarian cancer, few have yet been verified by peer research for clinical significance. Here, a meta-analysis approach was applied to two care fully selected gene expression microarray datasets. Artificial neural networks, Cox univariate survival analyses and T-tests identified genes whose expression was consistently and significantly associated with patient survival. The rigor of this experimental design increases confidence in the genes found to be of interest. A list of 56 genes were distilled from a potential 37,000 to be significantly related to survival in both datasets with a FDR of 1.39859 × 10−11, the identities of which both verify genes already implicated with this disease and provide novel genes and pathways to pursue. Further investigation and validation of these may lead to clinical insights and have potential to predict a patient’s response to treatment or be used as a novel target for therapy

A Similarity Measure for GPU Kernel Subgraph Matching

Accelerator architectures specialize in executing SIMD (single instruction, multiple data) in lockstep. Because the majority of CUDA applications are parallelized loops, control flow information can provide an in-depth characterization of a kernel. CUDAflow is a tool that statically separates CUDA binaries into basic block regions and dynamically measures instruction and basic block frequencies. CUDAflow captures this information in a control flow graph (CFG) and performs subgraph matching across various kernel's CFGs to gain insights to an application's resource requirements, based on the shape and traversal of the graph, instruction operations executed and registers allocated, among other information. The utility of CUDAflow is demonstrated with SHOC and Rodinia application case studies on a variety of GPU architectures, revealing novel thread divergence characteristics that facilitates end users, autotuners and compilers in generating high performing code

An intelligent multi-agent memory assistant

World population is ageing and increasingly scarce resources are required to cover the needs of everyone adequately. Medical conditions, especially memory problems, restrict the daily life of a broad slice of the elderly population, affect their independence. To prevent this, providing the right care and assistance while having in mind the costs implicated is essential. One possible path is to work with resources that we already have today and create innovative solutions to achieve the required level of support. There are not many solution either technological or not to prevent memory loss. In this work we present a possible solution aimed at restoring or maintaining the independence of elderly people, through the use of so-called Memory Assistants. We thus present an Intelligent Multi-Agent Memory Assistant designed to help people with memory problems remember their events and activities. The implementation of an event manager, free time manger, medication remainder and a sensory system, to manage and monitor the user, we aim to improve their quality of life and increase their independence

Cross-species gene expression analysis of species specific differences in the preclinical assessment of pharmaceutical compounds

Animals are frequently used as model systems for determination of safety and efficacy in pharmaceutical research and development. However, significant quantitative and qualitative differences exist between humans and the animal models used in research. This is as a result of genetic variation between human and the laboratory animal. Therefore the development of a system that would allow the assessment of all molecular differences between species after drug exposure would have a significant impact on drug evaluation for toxicity and efficacy. Here we describe a cross-species microarray methodology that identifies and selects orthologous probes after cross-species sequence comparison to develop an orthologous cross-species gene expression analysis tool. The assumptions made by the use of this orthologous gene expression strategy for cross-species extrapolation is that; conserved changes in gene expression equate to conserved pharmacodynamic endpoints. This assumption is supported by the fact that evolution and selection have maintained the structure and function of many biochemical pathways over time, resulting in the conservation of many important processes. We demonstrate this cross-species methodology by investigating species specific differences of the peroxisome proliferatoractivator receptor (PPAR) a response in rat and human

Mechanical Properties of End-crosslinked Entangled Polymer Networks using Sliplink Brownian Dynamics Simulations

The mechanical properties of a polymeric network containing both crosslinks and sliplinks (entanglements) are studied using a multi-chain Brownian dynamics simulation. We coarse-grain at the level of chain segments connecting consecutive nodes (cross- or sliplinks), with particular attention to the Gaussian statistics of the network. Affine displacement of nodes is not imposed: their displacement as well as sliding of monomers through sliplinks is governed by force balances. The simulation results of stress in uniaxial extension and the full stress tensor in simple shear including the (non-zero) second normal stress difference are presented for monodisperse chains with up to 18 entanglements between two crosslinks. The cases of two different force laws of the subchains (Gaussian chains and chains with finite extensibility) for two different numbers of monomers in a subchain (no = 50 and no = 100) are examined. It is shown that the additivity assumption of slip- and crosslink contribution holds for sufficiently long chains with two or more entanglements, and that it can be used to construct the strain response of a network of infinitely long chains. An important consequence is that the contribution of sliplinks to the small-strain shear modulus is about ⅔ of the contribution of a crosslink

Structural subnetwork evolution across the life-span: rich-club, feeder, seeder

The impact of developmental and aging processes on brain connectivity and the connectome has been widely studied. Network theoretical measures and certain topological principles are computed from the entire brain, however there is a need to separate and understand the underlying subnetworks which contribute towards these observed holistic connectomic alterations. One organizational principle is the rich-club - a core subnetwork of brain regions that are strongly connected, forming a high-cost, high-capacity backbone that is critical for effective communication in the network. Investigations primarily focus on its alterations with disease and age. Here, we present a systematic analysis of not only the rich-club, but also other subnetworks derived from this backbone - namely feeder and seeder subnetworks. Our analysis is applied to structural connectomes in a normal cohort from a large, publicly available lifespan study. We demonstrate changes in rich-club membership with age alongside a shift in importance from 'peripheral' seeder to feeder subnetworks. Our results show a refinement within the rich-club structure (increase in transitivity and betweenness centrality), as well as increased efficiency in the feeder subnetwork and decreased measures of network integration and segregation in the seeder subnetwork. These results demonstrate the different developmental patterns when analyzing the connectome stratified according to its rich-club and the potential of utilizing this subnetwork analysis to reveal the evolution of brain architectural alterations across the life-span

Sources of Relativistic Jets in the Galaxy

Black holes of stellar mass and neutron stars in binary systems are first detected as hard X-ray sources using high-energy space telescopes. Relativistic jets in some of these compact sources are found by means of multiwavelength observations with ground-based telescopes. The X-ray emission probes the inner accretion disk and immediate surroundings of the compact object, whereas the synchrotron emission from the jets is observed in the radio and infrared bands, and in the future could be detected at even shorter wavelengths. Black-hole X-ray binaries with relativistic jets mimic, on a much smaller scale, many of the phenomena seen in quasars and are thus called microquasars. Because of their proximity, their study opens the way for a better understanding of the relativistic jets seen elsewhere in the Universe. From the observation of two-sided moving jets it is inferred that the ejecta in microquasars move with relativistic speeds similar to those believed to be present in quasars. The simultaneous multiwavelength approach to microquasars reveals in short timescales the close connection between instabilities in the accretion disk seen in the X-rays, and the ejection of relativistic clouds of plasma observed as synchrotron emission at longer wavelengths. Besides contributing to a deeper comprehension of accretion disks and jets, microquasars may serve in the future to determine the distances of jet sources using constraints from special relativity, and the spin of black holes using general relativity.Comment: 39 pages, Tex, 8 figures, to appear in vol. 37 (1999) of Annual Reviews of Astronomy and Astrophysic