Comparison of the Near-Threshold Production of eta- and K-Mesons in Proton-Proton Collisions

The pp -> pp eta and pp -> pLambda K^+ reactions near threshold are dominated by the first and second S_11 resonance respectively. It is shown that a one-pion-exchange model exciting these isobars reproduces well the ratio of the production cross sections. The consequences for this and other channels are discussed.Comment: 10 pages, LaTeX2e, 1 eps-figur

Ecological networks: Pursuing the shortest path, however narrow and crooked

International audienceRepresenting data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade that use shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point checklist to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies. The last two decades have witnessed an exponential increase in the use of graph analysis in ecological and conservation studies (see refs. 1,2 for recent introductions to network theory in ecology and evolution). Networks (graphs) represent agents as nodes linked by edges representing pairwise relationships. For instance, a food web can be represented as a network of species (nodes) and their feeding relationships (edges) 3. Similarly, the spatial dynamics of a metapopulation can be analyzed by connecting the patches of suitable habitat (nodes) with edges measuring dispersal between patches 4. Data might either simply report the presence/absence of an edge (binary, unweighted networks), or provide a strength for each edge (weighted networks). In turn, these weights can represent a variety of ecologically-relevant quantities, depending on the system being described. For instance, edge weights can quantify interaction frequency (e.g., visitation networks 5), interaction strength (e.g., per-capita effect of one species on the growth rate of another 3), carbon-flow between trophic levels 6 , genetic similarity 7 , niche overlap (e.g., number of shared resources between two species 8), affinity 9 , dispersal probabilities (e.g., the rate at which individuals of a population move between patches 10), cost of dispersal between patches (e.g., resistance 11), etc. Despite such large variety of ecological network representations, a common task is the identification of nodes of high importance, such as keystone species in a food web, patches acting as stepping stones in a dispersal network , or genes with pleiotropic effects. The identification of important nodes is typically accomplished through centrality measures 5,12. Many centrality measures has been proposed, each probing complementary aspects of node-to-node relationships 13. For instance, Closeness centrality 14,15 highlights nodes that are "near" to all othe

Measurement of W-pair production in e+e−e^+ e^- collisions at 189 GeV

The production of W-pairs is analysed in a data samplecollected by ALEPH at a mean centre-of-mass energy of 188.6 GeV,corresponding to an integrated luminosity of 174.2 pb^-1. Crosssections are given for different topologies of W decays intoleptons or hadrons. Combining all final states and assumingStandard Model branching fractions, the total W-pair cross sectionis measured to be 15.71 +- 0.34 (stat) +- 0.18 (syst) pb.Using also the W-pair data samples collected by ALEPH at lowercentre-of-mass energies, the decay branching fraction of the W bosoninto hadrons is measured to be BR (W hadrons) = 66.97+- 0.65 (stat) +- 0.32 (syst) %, allowing a determination of theCKM matrix element |V(cs)|= 0.951 +- 0.030 (stat) +- 0.015 (syst)

Searches for neutral Higgs bosons in e+e−e^{+}e^{-} collisions at centre-of-mass energies from 192 to 202 GeV

Searches for neutral Higgs bosons are performed with the 237 pb^-1 of data collected in 1999 by the ALEPH detector at LEP, for centre-of-mass energies between 191.6 and 201.6 GeV. These searches apply to Higgs bosons within the context of the Standard Model and its minimal supersymmetric extension (MSSM) as well as to invisibly decaying Higgs bosons. No evidence of a signal is seen. A lower limit on the mass of the Standard Model Higgs boson of 107.7 GeV/c^2 at 95% confidence level is set. In the MSSM, lower limits of 91.2 and 91.6 GeV/c^2 are derived for the masses of the neutral Higgs bosons h and A, respectively. For a Higgs boson decaying invisibly and produced with the Standard Model cross section, masses below 106.4 GeV/c^2 are excluded

Determination of sin2 θeff w using jet charge measurements in hadronic Z decays

The electroweak mixing angle is determined with high precision from measurements of the mean difference between forward and backward hemisphere charges in hadronic decays of the Z. A data sample of 2.5 million hadronic Z decays recorded over the period 1990 to 1994 in the ALEPH detector at LEP is used. The mean charge separation between event hemispheres containing the original quark and antiquark is measured for bb̄ and cc̄ events in subsamples selected by their long lifetimes or using fast D*'s. The corresponding average charge separation for light quarks is measured in an inclusive sample from the anticorrelation between charges of opposite hemispheres and agrees with predictions of hadronisation models with a precision of 2%. It is shown that differences between light quark charge separations and the measured average can be determined using hadronisation models, with systematic uncertainties constrained by measurements of inclusive production of kaons, protons and A's. The separations are used to measure the electroweak mixing angle precisely as sin2 θeff w = 0.2322 ± 0.0008(exp. stat.) ±0.0007(exp. syst.) ± 0.0008(sep.). The first two errors are due to purely experimental sources whereas the third stems from uncertainties in the quark charge separations

Measurement of the W mass by direct reconstruction in e+e−e^+ e^- collisions at 172 GeV

The mass of the W boson is obtained from reconstructed invariant mass distributions in W-pair events. The sample of W pairs is selected from 10.65~pb$^{-1}$ collected with the ALEPH detector at a mean centre-of-mass energy of 172.09 \GEV. The invariant mass distribution of simulated events are fitted to the experimental distributions and the following W masses are obtained: $WW \to q\overline{q}q\overline{q } m_W = 81.30 +- 0.47(stat.) +- 0.11(syst.) GeV/c^2$, $WW \to l\nu q\overline{q}(l=e,\mu) m_W = 80.54 +- 0.47(stat.) +- 0.11(syst.) GeV/c^2$, $WW \to \tau\nu q\overline{q} m_W = 79.56 +- 1.08(stat.) +- 0.23(syst.) GeV/C62$. The statistical errors are the expected errors for Monte Carlo samples of the same integrated luminosity as the data. The combination of these measurements gives: $m_W = 80.80 +- 0.11(syst.) +- 0.03(LEP energy) GeV/^2$

Kynurenine–3–monooxygenase inhibition prevents multiple organ failure in rodent models of acute pancreatitis

Acute pancreatitis (AP) is a common and devastating inflammatory condition of the pancreas that is considered to be a paradigm of sterile inflammation leading to systemic multiple organ dysfunction syndrome (MODS) and death1,2 Acute mortality from AP-MODS exceeds 20%3 and for those who survive the initial episode, their lifespan is typically shorter than the general population4. There are no specific therapies available that protect individuals against AP-MODS. Here, we show that kynurenine-3-monooxygenase (KMO), a key enzyme of tryptophan metabolism5, is central to the pathogenesis of AP-MODS. We created a mouse strain deficient for Kmo with a robust biochemical phenotype that protected against extrapancreatic tissue injury to lung, kidney and liver in experimental AP-MODS. A medicinal chemistry strategy based on modifications of the kynurenine substrate led to the discovery of GSK180 as a potent and specific inhibitor of KMO. The binding mode of the inhibitor in the active site was confirmed by X-ray co-crystallography at 3.2 Å resolution. Treatment with GSK180 resulted in rapid changes in levels of kynurenine pathway metabolites in vivo and afforded therapeutic protection against AP-MODS in a rat model of AP. Our findings establish KMO inhibition as a novel therapeutic strategy in the treatment of AP-MODS and open up a new area for drug discovery in critical illness

Image intensity normalisation by maximising the Siddon line integral in the joint intensity distribution space

This paper presents a novel data-driven method for image intensity normalisation, which is a prerequisite step for any kind of image comparison. The method involves a novel application of the Siddon algorithm that was developed initially for fast reconstruction of tomographic images and is based on a linear normalisation model with either one or two parameters. The latter are estimated by maximising the line integral, computed using the Siddon algorithm, in the 2D joint intensity distribution space of image pairs. The proposed normalisation method, referred to as Siddon Line Integral Maximisation (SLIM), was compared with three other methodologies, namely background ratio (BAR) scaling, linear fitting and proportional scaling, using a large number of synthesised datasets. SLIM was also compared with BAR normalisation when applied to phantom data and two clinical examples. The new method was found to be more accurate and less biased than its counterparts for the range of characteristics selected for the synthesised data. These findings were in agreement with the results from the analysis of the experimental and clinical data. (C) 2009 Elsevier B.V. All rights reserved