Conjugative transfer of ICESde3396 between three β-hemolytic streptococcal species

Background: Integrative conjugative elements (ICEs) are mobile genetic elements (MGEs) that possess all genes necessary for excision, transfer and integration into recipient genome. They also carry accessory genes that impart new phenotypic features to recipient strains. ICEs therefore play an important role in genomic plasticity and population structure. We previously characterised ICESde 3396, the first ICE identified in the β-hemolytic Streptococcus dysgalactiae subsp equisimilis (SDSE) and demonstrated its transfer to single isolates of Streptococcus pyogenes (group A streptococcus, GAS) and Streptococcus agalactiae (group B streptococcus, GBS). While molecular studies found the ICE in multiple SDSE and GBS isolates, it was absent in all GAS isolates examined. Results: Here we demonstrate that ICESde 3396:km is transferable from SDSE to multiple SDSE, GAS and GBS isolates. However not all strains of these species were successful recipients under the same growth conditions. To address the role that host factors may have in conjugation we also undertook conjugation experiments in the presence of A549 epithelial cells and DMEM. While Horizontal Gene Transfer (HGT) occurred, conjugation efficiencies were no greater than when similar experiments were conducted in DMEM. Additionally transfer to GAS NS235 was successful in the presence of DMEM but not in Todd Hewitt Broth suggesting that nutritional factors may also influence HGT. The GAS and GBS transconjugants produced in this study are also able to act as donors of the ICE. Conclusion: We conclude that ICEs are major sources of interspecies HGT between β-hemolytic streptococci, and by introducing accessory genes imparting novel phenotypic characteristics, have the potential to alter the population structure of these species

Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models

We express the mean and variance terms in a double exponential regression model as additive functions of the predictors and use Bayesian variable selection to determine which predictors enter the model, and whether they enter linearly or flexibly. When the variance term is null we obtain a generalized additive model, which becomes a generalized linear model if the predictors enter the mean linearly. The model is estimated using Markov chain Monte Carlo simulation and the methodology is illustrated using real and simulated data sets.Comment: 8 graphs 35 page

Local ocean response to a multiphase westerly wind burst: 1. Dynamic response

The dynamic response to a westerly wind burst which occurred during the Coupled Ocean Atmosphere Response Experiment in the warm pool of the equatorial Pacific Ocean is described using velocity, hydrography, and microstructure measurements. Turbulent fluxes distributed momentum input from the wind over a near‐surface layer of variable thickness. Coriolis and pressure gradient terms combined to induce a wavelike response whose frequency was close to the local inertial frequency. Wind stress variations on near‐inertial timescales interfered both constructively and destructively with the wave response, exerting considerable influence on the observed currents

A new generation of intelligent trainable tools for analyzing large scientific image databases

The focus of this paper is on the detection of natural, as opposed to human-made, objects. The distinction is important because, in the context of image analysis, natural objects tend to possess much greater variability in appearance than human-made objects. Hence, we shall focus primarily on the use of algorithms that 'learn by example' as the basis for image exploration. The 'learn by example' approach is potentially more generally applicable compared to model-based vision methods since domain scientists find it relatively easier to provide examples of what they are searching for versus describing a model

Analysis of United Kingdom Off-Highway Construction Machinery Market and Its Consumers Using New-Sales Data

The off-highway construction machinery market and its consumers have attracted minimal previous research. This study addresses that void by analyzing annual United Kingdom (UK) (volume/portfolio) new-sales data for the 10 most popular products within that market, 1990–2010 inclusive. Graphical, descriptive statistical, Pearson-correlational, autocorrelational, and elementary modeling are employed to identify contrasts in sales regarding (1) high- and low-volume items; (2) growth trends and significant recessionary effects on volumes; (3) a demand change point circa 1997, since when annual product portfolio has changed little; and (4) product associations in consumer demand. Significant association is demonstrated between demand and construction output, especially with the value of new housing. Subsequently, consumption of wheeled loaders is modeled using construction volume, and demand for mini and crawler excavators is modeled using new-housing data. Time series trends for these machinery types are presented and forecast through 2015. The primary contribution of this study is a deeper understanding of the UK new-machinery market and the predilections of its consumers over the last two decades (to present)