Cecum lymph node dendritic cells harbor slow-growing bacteria phenotypically tolerant to antibiotic treatment.

In vivo, antibiotics are often much less efficient than ex vivo and relapses can occur. The reasons for poor in vivo activity are still not completely understood. We have studied the fluoroquinolone antibiotic ciprofloxacin in an animal model for complicated Salmonellosis. High-dose ciprofloxacin treatment efficiently reduced pathogen loads in feces and most organs. However, the cecum draining lymph node (cLN), the gut tissue, and the spleen retained surviving bacteria. In cLN, approximately 10%-20% of the bacteria remained viable. These phenotypically tolerant bacteria lodged mostly within CD103⁺CX₃CR1⁻CD11c⁺ dendritic cells, remained genetically susceptible to ciprofloxacin, were sufficient to reinitiate infection after the end of the therapy, and displayed an extremely slow growth rate, as shown by mathematical analysis of infections with mixed inocula and segregative plasmid experiments. The slow growth was sufficient to explain recalcitrance to antibiotics treatment. Therefore, slow-growing antibiotic-tolerant bacteria lodged within dendritic cells can explain poor in vivo antibiotic activity and relapse. Administration of LPS or CpG, known elicitors of innate immune defense, reduced the loads of tolerant bacteria. Thus, manipulating innate immunity may augment the in vivo activity of antibiotics.

On kinematic relaxation and deposition of water droplets in the last stages of low pressure steam turbines

In the first part of the paper steady two-phase flow predictions have been performed for the last stage of a model steam turbine to examine the influence of drag between condensed fog droplets and the continuous vapour phase. In general, droplets due to homogeneous condensation are small and thus kinematic relaxation provides only a minor contribution to the wetness losses. Different droplet size distributions have been investigated to estimate at which size inter-phase friction becomes more important. The second part of the paper deals with the deposition of fog droplets on stator blades. Results from several references are repeated to introduce the two main deposition mechanisms which are inertia and turbulent diffusion. Extensive postprocessing routines have been programmed to calculate droplet deposition due to these effects for a last stage stator blade in three-dimensions. In principle the method to determine droplet deposition by turbulent diffusion equates to that of Yau and Young [1] and the advantages and disadvantages of this relatively simple method are discussed. The investigation includes the influence of different droplet sizes on droplet deposition rates and shows that for small fog droplets turbulent diffusion is the main deposition mechanism. If the droplets size is increased inertial effects become more and more important and for droplets around 1 μm inertial deposition dominates. Assuming realistic droplet sizes the overall deposition equates to about 1% to 3% of the incoming wetness for the investigated guide vane at normal operating conditions. Copyright © 2013 by Solar Turbines Incorporated.

An extension of slow feature analysis for nonlinear blind source separation

We present and test an extension of slow feature analysis as a novel approach to nonlinear blind source separation. The algorithm relies on temporal correlations and iteratively reconstructs a set of statistically independent sources from arbitrary nonlinear instantaneous mixtures. Simulations show that it is able to invert a complicated nonlinear mixture of two audio signals with a high reliability. The algorithm is based on a mathematical analysis of slow feature analysis for the case of input data that are generated from statistically independent sources. © 2014 Henning Sprekeler, Tiziano Zito and Laurenz Wiskott.