Report from the Wellcome Trust/EBA “Perspectives in Clinical Proteomics” retreat--a strategy to implement next-generation proteomic analyses to the clinic for patient benefit: pathway to translation

Proteomics has long been thought to hold the promise of producing results of clinical utility which will influence patient treatment and outcomes. A recent Wellcome Trust/EBI meeting and retreat--“Perspectives in Clinical Proteomics”--brought together experts from a broad range of stakeholder groups with an interest in ensuring proteomics achieves this aim. This viewpoint presents views derived from these forums, proposing a pathway for the development of next-generation proteomic analyses in the clinical setting from selection of candidates through to their validation and ultimate demonstration of utility through health technology assessments. Although not meant to be all encompassing, important elements for proteomics researchers to consider are presented.     

Viewing 3D TV over two months produces no discernible effects on balance,coordination or eyesight

With the rise in stereoscopic 3D media, there has been concern that viewing stereoscopic 3D (S3D) content could have long-term adverse effects, but little data are available. In the first study to address this, 28 households who did not currently own a 3D TV were given a new TV set, either S3D or 2D. The 116 members of these households all underwent tests of balance, coordination and eyesight, both before they received their new TV set, and after they had owned it for 2 months. We did not detect any changes which appeared to be associated with viewing 3D TV. We conclude that viewing 3D TV does not produce detectable effects on balance, coordination or eyesight over the timescale studied.

Practitioner Summary: Concern has been expressed over possible long-term effects of stereoscopic 3D (S3D). We looked for any changes in vision, balance and coordination associated with normal home S3D TV viewing in the 2 months after first acquiring a 3D TV. We find no evidence of any changes over this timescale.     

A graph-based approach for assessing storm-induced coastal changes

Hurricanes and tropical storms are severe threats to coastal properties, settlements, and infrastructure. Airborne light detection and ranging (lidar) surveys conducted before and after storm events allow detailed analysis of coastal geomorphologic and sediment volumetric changes and have been proved very useful in the study of coastal changes. Traditionally, most studies use the pixel-based differencing method to quantify the spatial extent and magnitude of coastal changes based on sequential lidar surveys. This research presents a graph theory-based approach and associated software tools for representing and quantifying storm-induced damages to buildings, beaches and sand dunes, coastal vegetation canopy, and infrastructure. Generation of elevation difference grids, construction of local contour trees, and derivation of semantic properties are key components of the new algorithm for change object detection and extraction. An ontology and taxonomy are proposed to classify change objects into different types of coastal damages in terms of their semantic properties. This method has been successfully applied to assess damages of Hurricane Ike to the Bolivar Peninsula on the Texas Gulf Coast based on pre- and post-storm airborne lidar data and colour infrared aerial photographs.     

New statistical methods for investigating submarine pockmarks

We investigate the applicability of some novel spatial analysis techniques, developed for studies of astrophysical datasets, to the analysis of spatial point data in sedimentary basins. The techniques are evaluated and compared with standard methods using two test areas that contain large numbers of submarine pockmarks developed in distributed arrays. The familiar Ripley K and Voronoi tesselation techniques are used, and the results are then compared with those obtained using more novel techniques, the correlation length and minimal spanning tree. The correlation length technique is found to identify the precise distances at which clustering occurs more accurately, making a physical interpretation more clear than is possible using the Ripley K. The minimal spanning tree is found to be powerful at identifying the space-filling nature of the pockmark distribution, and has the advantage of being immune to edge effects. The use of these two novel techniques permits more information to be extracted from the datasets, and demonstrates clear statistically significant differences between them, which are not detectable using standard techniques.     

Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions

We propose a robust Poisson geometric process model with heavy-tailed distributions to cope with the problem of outliers as it may lead to an overestimation of mean and variance resulting in inaccurate interpretations of the situations. Two heavy-tailed distributions namely Student’s t and exponential power distributions with different tailednesses and kurtoses are used and they are represented in scale mixture of normal and scale mixture of uniform respectively. The proposed model is capable of describing the trend and meanwhile the mixing parameters in the scale mixture representations can detect the outlying observations. Simulations and real data analysis are performed to investigate the properties of the models.     

Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures

This paper studies a heavy-tailed stochastic volatility (SV) model with leverage effect, where a bivariate Student-t distribution is used to model the error innovations of the return and volatility equations. Choy et al. (2008) studied this model by expressing the bivariate Student-t distribution as a scale mixture of bivariate normal distributions. We propose an alternative formulation by first deriving a conditional Student-t distribution for the return and a marginal Student-t distribution for the log-volatility and then express these two Student-t distributions as a scale mixture of normal (SMN) distributions. Our approach separates the sources of outliers and allows for distinguishing between outliers generated by the return process or by the volatility process, and hence is an improvement over the approach of Choy et al. (2008). In addition, it allows an efficient model implementation using the WinBUGS software. A simulation study is conducted to assess the performance of the proposed approach and its comparison with the approach by Choy et al. (2008). In the empirical study, daily exchange rate returns of the Australian dollar to various currencies and daily stock market index returns of various international stock markets are analysed. Model comparison relies on the Deviance Information Criterion and convergence diagnostic is monitored by Geweke’s convergence test.     

Cerebral: visualizing multiple experimental conditions on a graph with biological context

Systems biologists use interaction graphs to model the behavior of biological systems at the molecular level. In an iterative process, such biologists obser ve the reactions of living cells under various experimental conditions, view the results in the context of the interaction graph, and then propose changes to the graph model. These graphs ser ve as a form of dynamic knowledge representation of the biological system being studied and evolve as new insight is gained from the experimental data. While numerous graph layout and drawing packages are available, these tools did not fully meet the needs of our immunologist collaborators. In this paper, we describe the data information display needs of these immunologists and translate them into design decisions. These decisions led us to create Cerebral, a system that uses a biologically guided graph layout and incor porates experimental data directly into the graph display. Small multiple views of different experimental conditions and a data-driven parallel coordinates view enable correlations between experimental conditions to be analyzed at the same time that the data is viewed in the graph context. This combination of coordinated views allows the biologist to view the data from many different perspectives simultaneously. To illustrate the typical analysis tasks performed, we analyze two datasets using Cerebral. Based on feedback from our collaboratorsweconcludethat Cerebral is a valuable tool for analyzing experimental data in the context of an interaction graph model.      

Mitochondria: A mirror into cellular dysfunction in heart disease

Cardiovascular (CV) disease is the single most significant cause of morbidity and mortality worldwide. The emerging global impact of CV disease means that the goals of early diagnosis and a wider range of treatment options are now increasingly pertinent. As such, there is a greater need to understand the molecular mechanisms involved and potential targets for intervention. Mitochondrial function is important for physiological maintenance of the cell, and when this function is altered, the cell can begin to suffer. Given the broad range and significant impacts of the cellular processes regulated by the mitochondria, it becomes important to understand the roles of the proteins associated with this organelle. Proteomic investigations of the mitochondria are hampered by the intrinsic properties of the organelle, including hydrophobic mitochondrial membranes; high proportion of basic proteins (pI greater than 8.0); and the relative dynamic range issues of the mitochondria. For these reasons, many proteomic studies investigate the mitochondria as a discrete subproteome. Once this has been achieved, the alterations that result in functional changes with CV disease can be observed. Those alterations that lead to changes in mitochondrial function, signaling and morphology, which have significant implications for the cardiomyocyte in the development of CV disease, are discussed.     

An exploratory study of the accessibility of state government Web sites

This paper focuses on Web accessibility. Relevant legislation and judicial decisions are reviewed, and prior empirical research is presented. This study presents the results from the Web accessibility analysis of the home pages of the 50 states and the District of Columbia. It found that twenty-nine percent of the home pages do not meet the requirements for Conformance Level A Web accessibility. Only one state meets Conformance Level AA standards, which are the minimum standards recommended for Web accessibility, and no state meets Conformance Level AAA standards. This paper also discusses how to address common accessibility problems.