Genes for the majority of group A streptococcal virulence factors and extracellular surface proteins do not confer an increased propensity to cause invasive disease

Background. The factors behind the reemergence of severe, invasive group A streptococcal (GAS) diseases are unclear, but it could be caused by altered genetic endowment in these organisms. However, data from previous studies assessing the association between single genetic factors and invasive disease are often conflicting, suggesting that other, as-yet unidentified factors are necessary for the development of this class of disease. Methods. In this study, we used a targeted GAS virulence microarray containing 226 GAS genes to determine the virulence gene repertoires of 68 GAS isolates (42 associated with invasive disease and 28 associated with noninvasive disease) collected in a defined geographic location during a contiguous time period. We then employed 3 advanced machine learning methods (genetic algorithm neural network, support vector machines, and classification trees) to identify genes with an increased association with invasive disease. Results. Virulence gene profiles of individual GAS isolates varied extensively among these geographically and temporally related strains. Using genetic algorithm neural network analysis, we identified 3 genes with a marginal overrepresentation in invasive disease isolates. Significantly, 2 of these genes, ssa and mf4, encoded superantigens but were only present in a restricted set of GAS M-types. The third gene, spa, was found in variable distributions in all M-types in the study. Conclusions. Our comprehensive analysis of GAS virulence profiles provides strong evidence for the incongruent relationships among any of the 226 genes represented on the array and the overall propensity of GAS to cause invasive disease, underscoring the pathogenic complexity of these diseases, as well as the importance of multiple bacteria and/ or host factors.

Mechanics of cellular adhesion to artificial artery templates

We are using polymer templates to grow artificial artery grafts in vivo for the replacement of diseased blood vessels. We have previously shown that adhesion of macrophages to the template starts the graft formation. We present a study of the mechanics of macrophage adhesion to these templates on a single cell and single bond level with optical tweezers. For whole cells, in vitro cell adhesion densities decreased significantly from polymer templates polyethylene to silicone to Tygon (167, 135, and 65 cells/mm(2)). These cell densities were correlated with the graft formation success rate (50%, 25%, and 0%). Single-bond rupture forces at a loading rate of 450 pN/s were quantified by adhesion of trapped 2-mm spheres to macrophages. Rupture force distributions were dominated by nonspecific adhesion (forces, < 40 pN). On polystyrene, preadsorption of fibronectin or presence of serum proteins in the cell medium significantly enhanced adhesion strength from a mean rupture force of 20 pN to 28 pN or 33 pN, respectively. The enhancement of adhesion by fibronectin and serum is additive (mean rupture force of 43 pN). The fraction of specific binding forces in the presence of serum was similar for polystyrene and polymethyl-methacrylate, but specific binding forces were not observed for silica. Again, we found correlation to in vivo experiments, where the density of adherent cells is higher on polystyrene than on silica templates, and can be further enhanced by fibronectin adsorption. These findings show that in vitro adhesion testing can be used for template optimization and to substitute for in-vivo experiments.

Using circular statistics to analyse time patterns in crime incidence

A set of techniques referred to as circular statistics has been developed for the analysis of directional and orientational data. The unit of measure for such data is angular (usually in either degrees or radians), and the statistical distributions underlying the techniques are characterised by their cyclic nature-for example, angles of 359.9 degrees are considered close to angles of 0 degrees. In this paper, we assert that such approaches can be easily adapted to analyse time-of-day and time-of-week data, and in particular daily cycles in the numbers of incidents reported to the police. We begin the paper by describing circular statistics. We then discuss how these may be modified, and demonstrate the approach with some examples for reported incidents in the Cardiff area of Wales. (c) 2005 Elsevier Ltd. All rights reserved.

Using distributions as statistical evidence in well-structured and ill-structured problems

Research has suggested that understanding in well-structured settings often does not transfer to the everyday, less-structured problems encountered outside of school. Little is known, beyond anecdotal evidence, about how teachers' consideration of distributions as evidence in well-structured settings compares with their use in ill-structured problem contexts. A qualitative study of preservice secondary teachers examined their use of distributions as evidence in four tasks of varying complexity and ill-structuredness. Results suggest that teachers' incorporation of distributions in well-structured settings does not imply that they will be incorporated in less structured problems (and vice-versa). Implications for research and teaching are discussed.