Ensuring the statistical soundness of competitive gene set approaches: gene filtering and genome-scale coverage are essential

In this article, we focus on the analysis of competitive gene set methods for detecting the statistical significance of pathways from gene expression data. Our main result is to demonstrate that some of the most frequently used gene set methods, GSEA, GSEArot and GAGE, are severely influenced by the filtering of the data in a way that such an analysis is no longer reconcilable with the principles of statistical inference, rendering the obtained results in the worst case inexpressive. A possible consequence of this is that these methods can increase their power by the addition of unrelated data and noise. Our results are obtained within a bootstrapping framework that allows a rigorous assessment of the robustness of results and enables power estimates. Our results indicate that when using competitive gene set methods, it is imperative to apply a stringent gene filtering criterion. However, even when genes are filtered appropriately, for gene expression data from chips that do not provide a genome-scale coverage of the expression values of all mRNAs, this is not enough for GSEA, GSEArot and GAGE to ensure the statistical soundness of the applied procedure. For this reason, for biomedical and clinical studies, we strongly advice not to use GSEA, GSEArot and GAGE for such data sets.

Identifying appropriate sampling and modelling approaches for analysing distributional patterns of Antarctic terrestrial arthropods along the Victoria Land latitudinal gradient

Biotic communities in Antarctic terrestrial ecosystems are relatively simple and often lack higher trophic levels (e. g. predators); thus, it is often assumed that species' distributions are mainly affected by abiotic factors such as climatic conditions, which change with increasing latitude, altitude and/or distance from the coast. However, it is becoming increasingly apparent that factors other than geographical gradients affect the distribution of organisms with low dispersal capability such as the terrestrial arthropods. In Victoria Land (East Antarctica) the distribution of springtail (Collembola) and mite (Acari) species vary at scales that range from a few square centimetres to regional and continental. Different species show different scales of variation that relate to factors such as local geological and glaciological history, and biotic interactions, but only weakly with latitudinal/altitudinal gradients. Here, we review the relevant literature and outline more appropriate sampling designs as well as suitable modelling techniques (e. g. linear mixed models and eigenvector mapping), that will more adequately address and identify the range of factors responsible for the distribution of terrestrial arthropods in Antarctica.

High pressure CO2 absorption studies on imidazolium-based ionic liquids:Experimental and simulation approaches

A combined experimental-computational study on the CO absorption on 1-butyl-3-methylimidazolium hexafluophosphate, 1-ethyl-3-methylimidazolium bis[trifluoromethylsulfonyl]imide, and 1-butyl-3-methylimidazolium bis[trifluoromethylsulfonyl]imide ionic liquids is reported. The reported results allowed to infer a detailed nanoscopic vision of the absorption phenomena as a function of pressure and temperature. Absorption isotherms were measured at 318 and 338K for pressures up to 20MPa for ultrapure samples using a state-of-the-art magnetic suspension densimeter, for which measurement procedures are developed. A remarkable swelling effect upon CO absorption was observed for pressures higher than 10MPa, which was corrected using a method based on experimental volumetric data. The experimental data reported in this work are in good agreement with available literature isotherms. Soave-Redlich-Kwong and Peng-Robinson equations of state coupled with bi-parametric van der Waals mixing rule were used for successful correlations of experimental high pressure absorption data. Molecular dynamics results allowed to infer structural, energetic and dynamic properties of the studied CO+ionic liquids mixed fluids, showing the relevant role of the strength of anion-cation interactions on fluid volumetric properties and CO absorption. © 2012 Elsevier B.V.

Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications. © 2010 Elsevier Inc. All rights reserved.

Bystander Signalling: Exploring Clinical Relevance Through New Approaches and New Models

Classical radiation biology research has centred on nuclear DNA as the main target of radiation-induced damage. Over the past two decades, this has been challenged by a significant amount of scientific evidence clearly showing radiation-induced cell signalling effects to have important roles in mediating overall radiobiological response. These effects, generally termed radiation-induced bystander effects (RIBEs) have challenged the traditional DNA targeted theory in radiation biology and highlighted an important role for cells not directly traversed by radiation. The multiplicity of experimental systems and exposure conditions in which RIBEs have been observed has hindered precise definitions of these effects. However, RIBEs have recently been classified for different relevant human radiation exposure scenarios in an attempt to clarify their role in vivo. Despite significant research efforts in this area, there is little direct evidence for their role in clinically relevant exposure scenarios. In this review, we explore the clinical relevance of RIBEs from classical experimental approaches through to novel models that have been used to further determine their potential implications in the clinic. 

Treatment approaches for diabetes and dyslipidemia

Dyslipidemia is an important risk factor for cardiovascular complications in persons with diabetes. Low-density lipoprotein-cholesterol (LDL-C) is the 'cornerstone' for assessment of lipoprotein-associated risk. However, LDL-C levels do not reflect the classic 'diabetic dyslipidemia' of hypertriglyceridemia and low high-density lipoprotein-cholesterol (HDL-C). Measurements of plasma apolipoprotein B100 concentrations and non-HDL-C may improve the definition of dyslipidemia. Statins, nicotinic acid and fibrates have roles in treating dyslipidemia in diabetes. Residual risk (i.e. risk that persists after correction of 'conventional' plasma lipoprotein abnormalities) is a new concept in the role of dyslipidemia in the pathogenesis of diabetic vascular complications. For example, regardless of plasma levels, lipoprotein extravasation through a leaking retinal blood barrier and subsequent modification may be crucial in the development of diabetic retinopathy. The current approach to the management of dyslipidemia in diabetes is briefly summarized, followed by a discussion of new concepts of residual risk and emerging lipoprotein-related mechanisms for vascular disease in diabetes.

Identifying optimal feeding habitat and proposed Marine Protected Areas (pMPAs) for the black-legged kittiwake (Rissa tridactyla) suggests a need for complementary management approaches

Marine Protected Areas (MPAs) are an important conservation tool. For marine predators, recent research has focused on the use of Species Distribution Models (SDMs) to identify proposed sites. We used a maximum entropy modelling approach based on static and dynamic oceanographic parameters to determine optimal feeding habitat for black-legged kittiwakes (Rissa tridactyla) at two colonies during two consecutive breeding seasons (2009 and 2010). A combination of Geographic Positioning System (GPS) loggers and Time-Depth Recorders (TDRs) attributed feeding activity to specific locations. Feeding areas were <30 km from the colony, <40 km from land, in productive waters, 25–175m deep. The predicted extent of optimal habitat declined at both colonies between 2009 and 2010 coincident with declines in reproductive success. Whilst the area of predicted optimal habitat changed, its location was spatially stable between years. There was a close match between observed feeding locations and habitat predicted as optimal at one colony (Lambay Island, Republic of Ireland), but a notable mismatch at the other (Rathlin Island, Northern Ireland). Designation of an MPA at Rathlin may, therefore, be less effective than a similar designation at Lambay perhaps due to the inherent variability in currents and sea state in the North Channel compared to the comparatively stable conditions in the central Irish Sea. Current strategies for designating MPAs do not accommodate likely future redistribution of resources due to climate change. We advocate the development of new approaches including dynamic MPAs that track changes in optimal habitat and non-colony specific ecosystem management.

Analysis of Bayesian classification-based approaches for Android malware detection

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.

Autoecological Approaches to Resolve Subjective Taxonomic Divisions within Arcellacea

Arcellacea (testate lobose amoebae) are important lacustrine environmental indicators that have been used in paleoclimatic reconstructions, assessing the effectiveness of mine tailings pond reclamation projects and for studying the effects of land use change in rural, industrial and urban settings. Recognition of ecophenotypically significant infra-specific ‘strains’ within arcellacean assemblages has the potential to enhance the utility of the group in characterizing contemporary and paleoenvironments. We present a novel approach which employs statistical tools to investigate the environmental and taxonomic significance of proposed strains. We test this approach on two identified strains: Difflugia protaeiformis Lamarck strain ‘acuminata’ (DPA), characterized by fine grained agglutination, and Difflugia protaeiformis Lamarck strain ‘claviformis’ (DPC), characterized by coarse grained agglutination. Redundancy analysis indicated that both organisms are associated with similar environmental variables. No relationship was observed between substrate particle size and abundance of DPC, indicating that DPC has a size preference for xenosomes during test construction. Thus DPC should not be designated as a distinct strain but rather form a species complex with DPA. This study elucidates the need to justify the designation of strains based on their autecology in addition to morphological stability.