Spread of Salmonella enterica in the body during systemic infection: unravelling host and pathogen determinants.

Salmonella enterica causes a range of life-threatening diseases in humans and animals worldwide. Current treatments for S. enterica infections are not sufficiently effective, and there is a need to develop new vaccines and therapeutics. An understanding of how S. enterica spreads in tissues has very important implications for targeting bacteria with vaccine-induced immune responses and antimicrobial drugs. Development of new control strategies would benefit from a more sophisticated evaluation of bacterial location, spatiotemporal patterns of spread and distribution in the tissues, and sites of microbial persistence. We review here recent studies of S. enterica serovar Typhimurium (S. Typhimurium) infections in mice, an established model of systemic typhoid fever in humans, which suggest that continuous bacterial spread to new infection foci and host phagocytes is an essential trait in the virulence of S. enterica during systemic infections. We further highlight how infections within host tissues are truly heterogeneous processes despite the fact that they are caused by the expansion of a genetically homogeneous microbial population. We conclude by discussing how understanding the within-host quantitative, spatial and temporal dynamics of S. enterica infections might aid the development of novel targeted preventative measures and drug regimens.

Effects of preferential transport in turbulent bluff-body-stabilized lean premixed CH 4/air flames

Preferential species diffusion is known to have important effects on local flame structure in turbulent premixed flames, and differential diffusion of heat and mass can have significant effects on both local flame structure and global flame parameters, such as turbulent flame speed. However, models for turbulent premixed combustion normally assume that atomic mass fractions are conserved from reactants to fully burnt products. Experiments reported here indicate that this basic assumption may be incorrect for an important class of turbulent flames. Measurements of major species and temperature in the near field of turbulent, bluff-body stabilized, lean premixed methane-air flames (Le=0.98) reveal significant departures from expected conditional mean compositional structure in the combustion products as well as within the flame. Net increases exceeding 10% in the equivalence ratio and the carbon-to-hydrogen atom ratio are observed across the turbulent flame brush. Corresponding measurements across an unstrained laminar flame at similar equivalence ratio are in close agreement with calculations performed using Chemkin with the GRI 3.0 mechanism and multi-component transport, confirming accuracy of experimental techniques. Results suggest that the large effects observed in the turbulent bluff-body burner are cause by preferential transport of H 2 and H 2O through the preheat zone ahead of CO 2 and CO, followed by convective transport downstream and away from the local flame brush. This preferential transport effect increases with increasing velocity of reactants past the bluff body and is apparently amplified by the presence of a strong recirculation zone where excess CO 2 is accumulated. © 2011 The Combustion Institute.

AI in the 21st century - With historical reflections

The discipline of Artificial Intelligence (AI) was born in the summer of 1956 at Dartmouth College in Hanover, New Hampshire. Half of a century has passed, and AI has turned into an important field whose influence on our daily lives can hardly be overestimated. The original view of intelligence as a computer program - a set of algorithms to process symbols - has led to many useful applications now found in internet search engines, voice recognition software, cars, home appliances, and consumer electronics, but it has not yet contributed significantly to our understanding of natural forms of intelligence. Since the 1980s, AI has expanded into a broader study of the interaction between the body, brain, and environment, and how intelligence emerges from such interaction. This advent of embodiment has provided an entirely new way of thinking that goes well beyond artificial intelligence proper, to include the study of intelligent action in agents other than organisms or robots. For example, it supplies powerful metaphors for viewing corporations, groups of agents, and networked embedded devices as intelligent and adaptive systems acting in highly uncertain and unpredictable environments. In addition to giving us a novel outlook on information technology in general, this broader view of AI also offers unexpected perspectives into how to think about ourselves and the world around us. In this chapter, we briefly review the turbulent history of AI research, point to some of its current trends, and to challenges that the AI of the 21st century will have to face. © Springer-Verlag Berlin Heidelberg 2007.