Physics, Astrophysics and Cosmology with Gravitational Waves

Gravitational wave detectors are already operating at interesting sensitivity levels, and they have an upgrade path that should result in secure detections by 2014. We review the physics of gravitational waves, how they interact with detectors (bars and interferometers), and how these detectors operate. We study the most likely sources of gravitational waves and review the data analysis methods that are used to extract their signals from detector noise. Then we consider the consequences of gravitational wave detections and observations for physics, astrophysics, and cosmology.Comment: 137 pages, 16 figures, Published version <http://www.livingreviews.org/lrr-2009-2

Carbohydrate-active enzymes from the zygomycete fungus Rhizopus oryzae: a highly specialized approach to carbohydrate degradation depicted at genome level

<p>Abstract</p> <p>Background</p> <p><it>Rhizopus oryzae </it>is a zygomycete filamentous fungus, well-known as a saprobe ubiquitous in soil and as a pathogenic/spoilage fungus, causing Rhizopus rot and mucomycoses.</p> <p>Results</p> <p>Carbohydrate Active enzyme (CAZy) annotation of the <it>R. oryzae </it>identified, in contrast to other filamentous fungi, a low number of glycoside hydrolases (GHs) and a high number of glycosyl transferases (GTs) and carbohydrate esterases (CEs). A detailed analysis of CAZy families, supported by growth data, demonstrates highly specialized plant and fungal cell wall degrading abilities distinct from ascomycetes and basidiomycetes. The specific genomic and growth features for degradation of easily digestible plant cell wall mono- and polysaccharides (starch, galactomannan, unbranched pectin, hexose sugars), chitin, chitosan, β-1,3-glucan and fungal cell wall fractions suggest specific adaptations of <it>R. oryzae </it>to its environment.</p> <p>Conclusions</p> <p>CAZy analyses of the genome of the zygomycete fungus <it>R. oryzae </it>and comparison to ascomycetes and basidiomycete species revealed how evolution has shaped its genetic content with respect to carbohydrate degradation, after divergence from the Ascomycota and Basidiomycota.</p

The Mnn2 Mannosyltransferase Family Modulates Mannoprotein Fibril Length, Immune Recognition and Virulence of Candida albicans

The fungal cell wall is the first point of interaction between an invading fungal pathogen and the host immune system. The outer layer of the cell wall is comprised of GPI anchored proteins, which are post-translationally modified by both N- and O-linked glycans. These glycans are important pathogen associated molecular patterns (PAMPs) recognised by the innate immune system. Glycan synthesis is mediated by a series of glycosyl transferases, located in the endoplasmic reticulum and Golgi apparatus. Mnn2 is responsible for the addition of the initial α1,2-mannose residue onto the α1,6-mannose backbone, forming the N-mannan outer chain branches. In Candida albicans, the MNN2 gene family is comprised of six members (MNN2, MNN21, MNN22, MNN23, MNN24 and MNN26). Using a series of single, double, triple, quintuple and sextuple mutants, we show, for the first time, that addition of α1,2-mannose is required for stabilisation of the α1,6-mannose backbone and hence regulates mannan fibril length. Sequential deletion of members of the MNN2 gene family resulted in the synthesis of lower molecular weight, less complex and more uniform N-glycans, with the sextuple mutant displaying only un-substituted α1,6-mannose. TEM images confirmed that the sextuple mutant was completely devoid of the outer mannan fibril layer, while deletion of two MNN2 orthologues resulted in short mannan fibrils. These changes in cell wall architecture correlated with decreased proinflammatory cytokine induction from monocytes and a decrease in fungal virulence in two animal models. Therefore, α1,2-mannose of N-mannan is important for both immune recognition and virulence of C. albicans

From Laplace to supernova SN 1987a: Bayesian Inference In Astrophysics

The Bayesian approach to probability theory is presented as an alternative to the currently used long-run relative frequency approach, which does not offer clear, compelling criteria for the design of statistical methods. Bayesian probability theory offers unique and demonstrably optimal solutions to well-posed statistical problems, and is historically the original approach to statistics. The reasons for earlier rejection of Bayesian methods are discussed, and it is noted that the work of Cox, Jaynes, and others answers earlier objections, giving Bayesian inference a firm logical and mathematical foundation as the correct mathematical language for quantifying uncertainty. The Bayesian approaches to parameter estimation and model comparison are outlined and illustrated by application to a simple problem based on the gaussian distribution. As further illustrations of the Bayesian paradigm, Bayesian solutions to two interesting astrophysical problems are outlined: the measurement of weak signals in a strong background, and the analysis of the neutrinos detected from supernova SN 1987A. A brief bibliography of astrophysically interestin