A novel olfactory pathway is essential for fast and efficient blood-feeding in mosquitoes

In mosquitoes, precise and efficient finding of a host animal is crucial for survival. One of the poorly understood aspects of mosquito blood-feeding behavior is how these insects target an optimal site in order to penetrate the skin and blood vessels without alerting the host animal. Here we provide new findings that a piercing structure of the mouthpart of the mosquitoes, the stylet, is an essential apparatus for the stage in blood feeding. Indeed, the stylet possesses a number of sensory hairs located at the tip of the stylet. These hairs house olfactory receptor neurons that express two conventional olfactory receptors of Aedes aegypti (AaOrs), AaOr8 and AaOr49, together with the odorant co-receptor (AaOrco). In vivo calcium imaging using transfected cell lines demonstrated that AaOr8 and AaOr49 were activated by volatile compounds present in blood. Inhibition of gene expression of these AaOrs delayed blood feeding behaviors of the mosquito. Taken together, we identified olfactory receptor neurons in the stylet involved in mosquito blood feeding behaviors, which in turn indicates that olfactory perception in the stylet is necessary and sufficient for mosquitoes to find host blood in order to rapidly acquire blood meals from a host animal

Mutator Dynamics on a Smooth Evolutionary Landscape

We investigate a model of evolutionary dynamics on a smooth landscape which features a ``mutator'' allele whose effect is to increase the mutation rate. We show that the expected proportion of mutators far from equilibrium, when the fitness is steadily increasing in time, is governed solely by the transition rates into and out of the mutator state. This results is a much faster rate of fitness increase than would be the case without the mutator allele. Near the fitness equilibrium, however, the mutators are severely suppressed, due to the detrimental effects of a large mutation rate near the fitness maximum. We discuss the results of a recent experiment on natural selection of E. coli in the light of our model.Comment: 4 pages, 3 figure

Pedestrian, Crowd, and Evacuation Dynamics

This contribution describes efforts to model the behavior of individual pedestrians and their interactions in crowds, which generate certain kinds of self-organized patterns of motion. Moreover, this article focusses on the dynamics of crowds in panic or evacuation situations, methods to optimize building designs for egress, and factors potentially causing the breakdown of orderly motion.Comment: This is a review paper. For related work see http://www.soms.ethz.c

Technical Design Report for the PANDA Solenoid and Dipole Spectrometer Magnets

This document is the Technical Design Report covering the two large spectrometer magnets of the PANDA detector set-up. It shows the conceptual design of the magnets and their anticipated performance. It precedes the tender and procurement of the magnets and, hence, is subject to possible modifications arising during this process.Comment: 10 pages, 14MB, accepted by FAIR STI in May 2009, editors: Inti Lehmann (chair), Andrea Bersani, Yuri Lobanov, Jost Luehning, Jerzy Smyrski, Technical Coordiantor: Lars Schmitt, Bernd Lewandowski (deputy), Spokespersons: Ulrich Wiedner, Paola Gianotti (deputy

W18O49 Nanowires as Ultraviolet Photodetector

Photodetectors in a configuration of field effect transistor were fabricated based on individual W18O49 nanowires. Evaluation of electrical transport behavior indicates that the W18O49 nanowires are n-type semiconductors. The photodetectors show high sensitivity, stability and reversibility to ultraviolet (UV) light. A high photoconductive gain of 104 was obtained, and the photoconductivity is up to 60 nS upon exposure to 312 nm UV light with an intensity of 1.6 mW/cm2. Absorption of oxygen on the surface of W18O49 nanowires has a significant influence on the dark conductivity, and the ambient gas can remarkably change the conductivity of W18O49 nanowire. The results imply that W18O49 nanowires will be promising candidates for fabricating UV photodetectors

[Introduction] Toward an anthropology of the just price: history, ethnography, critique

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Comparison of evolutionary algorithms in gene regulatory network model inference

Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very di±cult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insu±cient. Results: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and o®er a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. Conclusions: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identi¯ed and a platform for development of appropriate model formalisms is established

Neural Mechanisms of Human Perceptual Learning: Electrophysiological Evidence for a Two-Stage Process

Artículo de publicación ISIBackground: Humans and other animals change the way they perceive the world due to experience. This process has been labeled as perceptual learning, and implies that adult nervous systems can adaptively modify the way in which they process sensory stimulation. However, the mechanisms by which the brain modifies this capacity have not been sufficiently analyzed. Methodology/Principal Findings: We studied the neural mechanisms of human perceptual learning by combining electroencephalographic (EEG) recordings of brain activity and the assessment of psychophysical performance during training in a visual search task. All participants improved their perceptual performance as reflected by an increase in sensitivity (d') and a decrease in reaction time. The EEG signal was acquired throughout the entire experiment revealing amplitude increments, specific and unspecific to the trained stimulus, in event-related potential (ERP) components N2pc and P3 respectively. P3 unspecific modification can be related to context or task-based learning, while N2pc may be reflecting a more specific attentional-related boosting of target detection. Moreover, bell and U-shaped profiles of oscillatory brain activity in gamma (30-60 Hz) and alpha (8-14 Hz) frequency bands may suggest the existence of two phases for learning acquisition, which can be understood as distinctive optimization mechanisms in stimulus processing.This research was supported by CONICYT doctoral grant to C.M.H. and by an ECOS-Sud/CONICYT grant C08S02 and FONDECYT 1090612 grant to D.C. and F.A

Antifibrotic Effects of the Dual CCR2/CCR5 Antagonist Cenicriviroc in Animal Models of Liver and Kidney Fibrosis

Background & Aims Interactions between C-C chemokine receptor types 2 (CCR2) and 5 (CCR5) and their ligands, including CCL2 and CCL5, mediate fibrogenesis by promoting monocyte/macrophage recruitment and tissue infiltration, as well as hepatic stellate cell activation. Cenicriviroc (CVC) is an oral, dual CCR2/CCR5 antagonist with nanomolar potency against both receptors. CVC’s anti-inflammatory and antifibrotic effects were evaluated in a range of preclinical models of inflammation and fibrosis. Methods Monocyte/macrophage recruitment was assessed in vivo in a mouse model of thioglycollate-induced peritonitis. CCL2-induced chemotaxis was evaluated ex vivo on mouse monocytes. CVC’s antifibrotic effects were evaluated in a thioacetamide-induced rat model of liver fibrosis and mouse models of diet-induced non-alcoholic steatohepatitis (NASH) and renal fibrosis. Study assessments included body and liver/kidney weight, liver function test, liver/kidney morphology and collagen deposition, fibrogenic gene and protein expression, and pharmacokinetic analyses. Results CVC significantly reduced monocyte/macrophage recruitment in vivo at doses ≥20 mg/kg/day (p < 0.05). At these doses, CVC showed antifibrotic effects, with significant reductions in collagen deposition (p < 0.05), and collagen type 1 protein and mRNA expression across the three animal models of fibrosis. In the NASH model, CVC significantly reduced the non-alcoholic fatty liver disease activity score (p < 0.05 vs. controls). CVC treatment had no notable effect on body or liver/kidney weight. Conclusions CVC displayed potent anti-inflammatory and antifibrotic activity in a range of animal fibrosis models, supporting human testing for fibrotic diseases. Further experimental studies are needed to clarify the underlying mechanisms of CVC’s antifibrotic effects. A Phase 2b study in adults with NASH and liver fibrosis is fully enrolled (CENTAUR Study 652-2-203; NCT02217475)

PeptX: Using Genetic Algorithms to optimize peptides for MHC binding

<p>Abstract</p> <p>Background</p> <p>The binding between the major histocompatibility complex and the presented peptide is an indispensable prerequisite for the adaptive immune response. There is a plethora of different <it>in silico </it>techniques for the prediction of the peptide binding affinity to major histocompatibility complexes. Most studies screen a set of peptides for promising candidates to predict possible T cell epitopes. In this study we ask the question vice versa: Which peptides do have highest binding affinities to a given major histocompatibility complex according to certain <it>in silico </it>scoring functions?</p> <p>Results</p> <p>Since a full screening of all possible peptides is not feasible in reasonable runtime, we introduce a heuristic approach. We developed a framework for Genetic Algorithms to optimize peptides for the binding to major histocompatibility complexes. In an extensive benchmark we tested various operator combinations. We found that (1) selection operators have a strong influence on the convergence of the population while recombination operators have minor influence and (2) that five different binding prediction methods lead to five different sets of "optimal" peptides for the same major histocompatibility complex. The consensus peptides were experimentally verified as high affinity binders.</p> <p>Conclusion</p> <p>We provide a generalized framework to calculate sets of high affinity binders based on different previously published scoring functions in reasonable runtime. Furthermore we give insight into the different behaviours of operators and scoring functions of the Genetic Algorithm.</p