Septic Arthritis Caused by Legionella dumoffii in a Patient with Systemic Lupus Erythematosus-Like Disease

We describe a patient with systemic lupus erythematosus (SLE)-like disease on immunosuppressive treatment who developed septic arthritis of the knee involving Legionella dumoffii. Cultures initially remained negative. A broad-range 16S PCR using synovial fluid revealed L. dumoffii rRNA genes, a finding that was subsequently confirmed by positive Legionella culture results

Stability of viscous long liquid filaments

We study the collapse of an axisymmetric liquid filament both analytically and by means of a numerical model. The liquid filament, also known as ligament, may either collapse stably into a single droplet or break up into multiple droplets. The dynamics of the filament are governed by the viscosity and the aspect ratio, and the initial perturbations of its surface. We find that the instability of long viscous filaments can be completely explained by the Rayleigh-Plateau instability, whereas a low viscous filament can also break up due to end pinching. We analytically derive the transition between stable collapse and breakup in the Ohnesorge number versus aspect ratio phase space. Our result is confirmed by numerical simulations based on the slender jet approximation and explains recent experimental findings by Castrejon-Pita et al., PRL 108, 074506 (2012).Comment: 7 page

Automatic Goal Discovery in Subgoal Monte Carlo Tree Search

Monte Carlo Tree Search (MCTS) is a heuristic search algorithm that can play a wide range of games without requiring any domain-specific knowledge. However, MCTS tends to struggle in very complicated games due to an exponentially increasing branching factor. A promising solution for this problem is to focus the search only on a small fraction of states. Subgoal Monte Carlo Tree Search (S-MCTS) achieves this by using a predefined subgoal-predicate that detects promising states called subgoals. However, not only does this make S-MCTS domaindependent, but also it is often difficult to define a good predicate. In this paper, we propose using quality diversity (QD) algorithms to detect subgoals in real-time. Furthermore, we show how integrating QD-algorithms into S-MCTS significantly improves its performance in the Physical Travelling Salesmen Problem without requiring any domain-specific knowledge

Susceptibility of Thymocytes for Infection by Chicken Anemia Virus is Related to Pre- and Posthatching Development

To investigate the age-dependent mechanism of susceptibility for chicken anemia virus (CAV) infection, we inoculated embryos and chickens of ages between day 9 of embryonic development and day 28 after hatching with CAV. Chicken embryos inoculated at days 9 and 11 of development showed no CAV-infected cells in the thymus, nor in other lymphoid organs. Many CAV-infected cells were detected in the thymic cortex of all chicken embryos inoculated at days 13 and 16 of development and of all chickens inoculated 1, 3, and 7 days after hatching. All embryos and chickens that contained CAV-infected cells in the thymus also contained CAV-infected cells in the bone marrow, but not in the bursa of Fabricius or the spleen. In chickens inoculated at days 14 and 21, only few CAV-infected cells were detected in the thymus, whereas these cells were not detected in thymi of 28-day-old inoculated chickens. Depletion of the thymic cortex was only detected in chickens inoculated from day 16 of embryonic development till day 21 after hatching. Only hematocrit values of the chickens inoculated 1 and 3 days after hatching were below normal. The rationale for the simultaneous susceptibility of cells of the T-cell lineage and cells of the erythrocyte lineage is discussed. As far as the thymus is concerned, the absence of clinical and microscopical signs of CAV infection in older chickens and the inability of CAV to infect embryos at days 9 and 11 of embryonic development may be caused by a lack of susceptible thymocytes. In view of the three waves of thymic precursor cells that populate the thymus during ontogeny, as described by Le Douarin and colleagues, we hypothesize that CAV only infects thymocytes derived from the second wave of precursor cells

Design and effects of outcome-based payment models in healthcare: a systematic review

Introduction: Outcome-based payment models (OBPMs) might solve the shortcomings of fee-for-service or diagnostic-related group (DRG) models using financial incentives based on outcome indicators of the provided care. This review provides an analysis of the characteristics and effectiveness of OBPMs, to determine which models lead to favourable effects. Methods: We first developed a definition for OBPMs. Next, we searched four data sources to identify the models: (1) scientific literature databases; (2) websites of relevant governmental and scientific agencies; (3) the reference lists of included articles; (4) experts in the field. We only selected studies that examined the impact of the payment model on quality and/or costs. A narrative evidence synthesis was used to link specific design features to effects on quality of care or healthcare costs. Results: We included 88 articles, describing 12 OBPMs. We identified two groups of models based on differences in design features: narrow OBPMs (financial incentives based on quality indicators) and broad OBPMs (combination of global budgets, risk sharing, and financial incentives based on quality indicators). Most (5 out of 9) of the narrow OBPMs showed positive effects on quality; the others had mixed (2) or negative (2) effects. The effects of narrow OBPMs on healthcare utilization or costs, however, were unfavourable (3) or unknown (6). All broad OBPMs (3) showed positive effects on quality of care, while reducing healthcare cost growth. Discussion: Although strong empirical evidence on the effects of OBPMs on healthcare quality, utilization, and costs is limited, our findings suggest that broad OBPMs may be preferred over narrow OBPMs

Fuzzy Fibers: Uncertainty in dMRI Tractography

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

Sticky bubbles

We discuss the physical forces that are required to remove an air bubble immersed in a liquid from a corner. This is relevant for inkjet printing technology, as the presence of air bubbles in the channels of a printhead perturbs the jetting of droplets. A simple strategy to remove the bubble is to ush the ink past the bubble by providing a high pressure pulse. In this report we rst compute the viscous drag forces that such a ow exerts on the bubble. Then, we compare this to the \sticking forces" on the bubble, due to the capillary interaction with the wall. From this we can estimate the required ow velocities for bubble removal, as a function of channel geometry, contact angle and ink properties. Finally, we investigate other ways to exert a force on a trapped bubble. In particular we focus on forces induced by electric elds which can alter the contact angle of the drop, or by locally applying thermal gradients. Once again, these forces are compared to the sticking forces to identify the parameters where the bubble can be removed