Abstract:
Electron microscopy and immunocytochemistry were used to examine the sensory epithelium of the nasal cavity of the American alligator. Almost the entire nasal cavity is lined with olfactory (sensory) epithelium. Two types of olfactory sensory neurons are present. Both types bear cilia as well as microvilli at their apical endings and express the typical markers for olfactory neurons. The density of these olfactory neurons varies along the nasal cavity. In addition, solitary chemosensory cells innervated by trigeminal nerve fibres, are intermingled with olfactory sensory neurons. Solitary chemosensory cells express components of the PLC-transduction cascade found in solitary chemosensory cells in rodents.The nasal cavity of the American alligator contains two different chemosensory systems incorporated in the same sensory epithelium: the olfactory system proper and solitary chemosensory cells. The olfactory system contains two morphological distinct types of ciliated olfactory receptor neurons.The nasal cavity of all vertebrates houses multiple chemosensors. The olfactory and the vomeronasal receptors detect a variety of odours including food-related and social signals. In addition, chemically-sensitive free nerve endings of the trigeminal nerve and trigeminally innervated chemosensors that respond to irritants have been reported for some vertebrate species. The chemosensors are expressed in various cell types. In mammals, the olfactory system contains ciliated and microvillous olfactory receptor neurons (OSNs). In many mammals these neurons are segregated in two compartments: ciliated OSNs are housed in the main olfactory epithelium detecting chemicals related mostly to food and microvillous OSNs in the so-called vomeronasal organ (VNO) detecting mostly (but not limited to) social cues [1]. Fish olfactory epithelium also contains ciliated and microvillous OSNs [2], but here both cell types are intermingled in one olfactory epithelium since fish do not have a VNO. In

Abstract:
In this paper, we consider \emph{comparison-based} adaptive stochastic algorithms for solving numerical optimisation problems. We consider a specific subclass of algorithms called comparison-based step-size adaptive randomized search (CB-SARS), where the state variables at a given iteration are a vector of the search space and a positive parameter, the step-size, typically controlling the overall standard deviation of the underlying search distribution. We investigate the linear convergence of CB-SARS on \emph{scaling-invariant} objective functions. Scaling-invariant functions preserve the ordering of points with respect to their function value when the points are scaled with the same positive parameter (the scaling is done w.r.t. a fixed reference point). This class of functions includes norms composed with strictly increasing functions as well as \emph{non quasi-convex} and \emph{non-continuous} functions. On scaling-invariant functions, we show the existence of a homogeneous Markov chain, as a consequence of natural invariance properties of CB-SARS (essentially scale-invariance and invariance to strictly increasing transformation of the objective function). We then derive sufficient conditions for asymptotic \emph{global linear convergence} of CB-SARS, expressed in terms of different stability conditions of the normalised homogeneous Markov chain (irreducibility, positivity, Harris recurrence, geometric ergodicity) and thus define a general methodology for proving global linear convergence of CB-SARS algorithms on scaling-invariant functions.

Abstract:
In the context of unconstraint numerical optimization, this paper investigates the global linear convergence of a simple probabilistic derivative-free optimization algorithm (DFO). The algorithm samples a candidate solution from a standard multivariate normal distribution scaled by a step-size and centered in the current solution. This solution is accepted if it has a better objective function value than the current one. Crucial to the algorithm is the adaptation of the step-size that is done in order to maintain a certain probability of success. The algorithm, already proposed in the 60's, is a generalization of the well-known Rechenberg's $(1+1)$ Evolution Strategy (ES) with one-fifth success rule which was also proposed by Devroye under the name compound random search or by Schumer and Steiglitz under the name step-size adaptive random search. In addition to be derivative-free, the algorithm is function-value-free: it exploits the objective function only through comparisons. It belongs to the class of comparison-based step-size adaptive randomized search (CB-SARS). For the convergence analysis, we follow the methodology developed in a companion paper for investigating linear convergence of CB-SARS: by exploiting invariance properties of the algorithm, we turn the study of global linear convergence on scaling-invariant functions into the study of the stability of an underlying normalized Markov chain (MC). We hence prove global linear convergence by studying the stability (irreducibility, recurrence, positivity, geometric ergodicity) of the normalized MC associated to the $(1+1)$-ES. More precisely, we prove that starting from any initial solution and any step-size, linear convergence with probability one and in expectation occurs. Our proof holds on unimodal functions that are the composite of strictly increasing functions by positively homogeneous functions with degree $\alpha$ (assumed also to be continuously differentiable). This function class includes composite of norm functions but also non-quasi convex functions. Because of the composition by a strictly increasing function, it includes non continuous functions. We find that a sufficient condition for global linear convergence is the step-size increase on linear functions, a condition typically satisfied for standard parameter choices. While introduced more than 40 years ago, we provide here the first proof of global linear convergence for the $(1+1)$-ES with generalized one-fifth success rule and the first proof of linear convergence for a CB-SARS on such a class of functions that includes

Abstract:
We investigated the main olfactory epithelium of mice at the light and electron microscopic level and describe several subpopulations of microvillous cells. The ultrastructure of the microvillous cells reveals at least three morphologically different types two of which express the TrpM5 channel. None of these cells have an axon that projects to the olfactory bulb. Tests with a large panel of cell markers indicate that the TrpM5-positive cells are not sensory since they express neither neuronal markers nor are contacted by trigeminal nerve fibers.We conclude that TrpM5 is not a reliable marker for chemosensory cells. The TrpM5-positive cells of the olfactory epithelium are microvillous and may be chemoresponsive albeit not part of the sensory apparatus. Activity of these microvillous cells may however influence functionality of local elements of the olfactory system.Traditionally, the main olfactory epithelium (MOE) of mammals was said to contain only basal cells, supporting cells, and ciliated olfactory receptor neurons (ORNs) that utilize OR-type receptor molecules and the canonical G-protein-coupled transduction pathway via Gαolf, adenylyl cyclase III (ACIII), and cAMP [1]. However, a review of the literature suggests that this conventional view is too simplistic, e.g. microvillous ORNs are present in the olfactory epithelium of fishes and in the vomeronasal organ of mammals. Also, microvillous cells have been reported for the MOE of some mammals including humans [2-5]. A study by Rowley et al. utilizing HRP tracing claimed that at least some microvillous cells project directly to the olfactory bulb [6]. Braun and Zimmermann [4], utilizing ecto-5'-nucleotidase as a marker, detected microvillous cells in the MOE and suggested a mechanosensory function for these elements. Carr et al. reported microvillous cells in rats and concluded that these cells were non-sensory cells [7]. Functional studies revealed that mice with a disrupted cAMP pathway of ciliated ORNs are s

Abstract:
Esben H jlund Carlsen er fakta-chef for TV2 og st r for indk b af fremmed- produktioner, etablering af co-produktionsaftaler med udlandet, samt indk b og bestilling af danske programmer inden for faktaomr det. Faktaomr det d kker alt lige fra undervisningsstof, wild life, hobby, erotik, udland, de sm dyr til halvdelen af b rneprogrammerne. I dette interview fort ller Esben H jlund Carlsen om hvad man g r n r man skal udfylde det store hul, som en ny TV-kanal er, for det har v ret n d- vendigt at indg pakke-aftaler med nogle f store danske producenter. Han kommer ogs ind p sine erfaringer fra TV-Syd med dramaproduktioner med amat rskuespillere, og g r sig nogle tanker om hvordan TV-2 kan skabe sig sit eget image i forhold til Danmarks Radio. Esben H jlund Carlsen startede TV-2 for kun godt et r siden, og der har v ret nok at se til for at TV-2 kan g i luften som planlagt den 1. oktober 1988.

Abstract:
The calpains, calcium-activated neutral proteases, play important roles in calcium-regulated intra-cellular signal transduction cascades. Here we report the isolation and initial characterization of a cDNA encoding a calpain 9, digestive tract specific calpain, from catfish taste epithelium. This calpain 9 (Ip-CAPN9a) shares 61% identity with human calpain 9. Phylogenetic analysis provides evidence that catfish calpain 9 and the related enzymes from Oncorhynchus mykiss, Danio rerio, Xenopus laevis, Mus musculus, Rattus norvegicus and Homo sapiens make up a distinct clade within the tissue-specific calpain family. Northern blot analysis reveals that Ip-CAPN9a is predominantly expressed in barbell and digestive tract, but not expressed in brain. An antibody against the N-terminal segment of Ip-CAPN9a recognizes cells within the taste buds in catfish barbells.

Abstract:
Background Enterohemorrhagic Escherichia coli (EHEC) colonizes the intestinal epithelium and causes attaching and effacing (A/E) lesions. Expression of virulence genes, particularly those from the locus of the enterocyte effacement (LEE) pathogenicity island is required for the formation of a type three secretion system, which induces A/E lesion formation. Like other horizontally acquired genetic elements, expression of the LEE is negatively regulated by H-NS. In the non-pathogenic Escherichia coli K-12 strain the stringent starvation protein A (SspA) inhibits accumulation of H-NS, and thereby allows de-repression of the H-NS regulon during the stationary phase of growth. However, the effect of SspA on the expression of H-NS-controlled virulence genes in EHEC is unknown. Results Here we assess the effect of SspA on virulence gene expression in EHEC. We show that transcription of virulence genes including those of the LEE is decreased in an sspA mutant, rendering the mutant strain defective in forming A/E lesions. A surface exposed pocket of SspA is functionally important for the regulation of the LEE and for the A/E phenotype. Increased expression of ler alleviates LEE expression in an sspA mutant, suggesting that the level of Ler in the mutant is insufficient to counteract H-NS-mediated repression. We demonstrate that the H-NS level is two-fold higher in an sspA mutant compared to wild type, and that the defects of the sspA mutant are suppressed by an hns null mutation, indicating that hns is epistatic to sspA in regulating H-NS repressed virulence genes. Conclusions SspA positively regulates the expression of EHEC virulence factors by restricting the intracellular level of H-NS. Since SspA is conserved in many bacterial pathogens containing horizontally acquired pathogenicity islands controlled by H-NS, our study suggests a common mechanism whereby SspA potentially regulates the expression of virulence genes in these pathogens.

Abstract:
Recently, full sky maps from Planck have been made publicly available. In this paper, we do consistency tests for the three Planck CMB sky maps. We assume that the difference between two maps represents the contributions from systematics, noise, foregrounds and other sources, and that a precise representation of the Cosmic Microwave Background should be uncorrelated with it. We investigate the cross correlation in pixel space between the difference maps and the various Planck maps and find no significant correlations, in comparison to 10000 random Gaussian simulated maps. Additionally we investigate the difference map between the WMAP ILC 9 year map and the ILC 7 year map. We perform cross correlations between this difference map, and the ILC9 and ILC7, and find significant correlations only for the ILC9, at more than the 99.99% level. Likewise, a comparison between the Planck NILC map and the WMAP ILC9 map, shows a strong correlation for the ILC9 map with the difference map, also at more than the 99.99% level. Thus the ILC9 appears to be more contaminated than the ILC7, which should be taken into consideration when using WMAP maps for cosmological analyses.

Abstract:
This paper analyzes a (1, $\lambda$)-Evolution Strategy, a randomized comparison-based adaptive search algorithm, optimizing a linear function with a linear constraint. The algorithm uses resampling to handle the constraint. Two cases are investigated: first the case where the step-size is constant, and second the case where the step-size is adapted using cumulative step-size adaptation. We exhibit for each case a Markov chain describing the behaviour of the algorithm. Stability of the chain implies, by applying a law of large numbers, either convergence or divergence of the algorithm. Divergence is the desired behaviour. In the constant step-size case, we show stability of the Markov chain and prove the divergence of the algorithm. In the cumulative step-size adaptation case, we prove stability of the Markov chain in the simplified case where the cumulation parameter equals 1, and discuss steps to obtain similar results for the full (default) algorithm where the cumulation parameter is smaller than 1. The stability of the Markov chain allows us to deduce geometric divergence or convergence , depending on the dimension, constraint angle, population size and damping parameter, at a rate that we estimate. Our results complement previous studies where stability was assumed.

Abstract:
This paper analyses a $(1,\lambda)$-Evolution Strategy, a randomised comparison-based adaptive search algorithm, on a simple constraint optimisation problem. The algorithm uses resampling to handle the constraint and optimizes a linear function with a linear constraint. Two cases are investigated: first the case where the step-size is constant, and second the case where the step-size is adapted using path length control. We exhibit for each case a Markov chain whose stability analysis would allow us to deduce the divergence of the algorithm depending on its internal parameters. We show divergence at a constant rate when the step-size is constant. We sketch that with step-size adaptation geometric divergence takes place. Our results complement previous studies where stability was assumed.