Evidence for gliadin antibodies as causative agents in schizophrenia.

Antibodies to gliadin, a component of gluten, have frequently been reported in schizophrenia. Highly immunogenic B cell epitopes along its length are homologous to numerous proteins relevant to schizophrenia, including members of the DISC1 interactome, glutamate, dopamine and neuregulin signaling networks, and plasticity or myelination pathways. Antibodies to gliadin may cross react with these key proteins, as has already been observed with synapsin 1 and calreticulin. Gliadin may thus be a causative agent in schizophrenia, under certain genetic and immunological conditions, producing its effects via antibody mediated knockdown of multiple proteins relevant to the disease process. Because of such homology, an autoimmune response may be sustained by the human antigens that resemble gliadin itself, a scenario supported by many reports of immune activation both in the brain and in lymphocytes in schizophrenia. Gluten free diets and removal of such antibodies may be of therapeutic benefit in certain cases of schizophrenia

The Impact of Professional Sports on Cities’ Economic Performance

The purpose of this paper is to estimate the impact of professional sports on cities’ economic performance as measured by real per capita income growth and changes in the unemployment rate. We use a panel model across 43 cities over eight years. Explanatory variables include the number of professional sports franchises in a city and the performance of those franchises. We find no statistically significant evidence suggesting that professional sports franchises impact cities’ real per capita income growth. We do, however, find that professional sports franchises have a statistically significant impact on unemployment rates

Efficient Bayesian inference for multivariate factor stochastic volatility models with leverage

This paper discusses the efficient Bayesian estimation of a multivariate factor stochastic volatility (Factor MSV) model with leverage. We propose a novel approach to construct the sampling schemes that converges to the posterior distribution of the latent volatilities and the parameters of interest of the Factor MSV model based on recent advances in Particle Markov chain Monte Carlo (PMCMC). As opposed to the approach of Chib et al. (2006} and Omori et al. (2007}, our approach does not require approximating the joint distribution of outcome and volatility innovations by a mixture of bivariate normal distributions. To sample the free elements of the loading matrix we employ the interweaving method used in Kastner et al. (2017} in the Particle Metropolis within Gibbs (PMwG) step. The proposed method is illustrated empirically using a simulated dataset and a sample of daily US stock returns.Comment: 4 figures and 9 table

On Scalable Particle Markov Chain Monte Carlo

Particle Markov Chain Monte Carlo (PMCMC) is a general approach to carry out Bayesian inference in non-linear and non-Gaussian state space models. Our article shows how to scale up PMCMC in terms of the number of observations and parameters by expressing the target density of the PMCMC in terms of the basic uniform or standard normal random numbers, instead of the particles, used in the sequential Monte Carlo algorithm. Parameters that can be drawn efficiently conditional on the particles are generated by particle Gibbs. All the other parameters are drawn by conditioning on the basic uniform or standard normal random variables; e.g. parameters that are highly correlated with the states, or parameters whose generation is expensive when conditioning on the states. The performance of this hybrid sampler is investigated empirically by applying it to univariate and multivariate stochastic volatility models having both a large number of parameters and a large number of latent states and shows that it is much more efficient than competing PMCMC methods. We also show that the proposed hybrid sampler is ergodic

Power spectrum multipoles on the curved sky: an application to the 6-degree Field Galaxy Survey

The peculiar velocities of galaxies cause their redshift-space clustering to depend on the angle to the line-of-sight, providing a key test of gravitational physics on cosmological scales. These effects may be described using a multipole expansion of the clustering measurements. Focussing on Fourier-space statistics, we present a new analysis of the effect of the survey window function, and the variation of the line-of-sight across a survey, on the modelling of power spectrum multipoles. We determine the joint covariance of the Fourier-space multipoles in a Gaussian approximation, and indicate how these techniques may be extended to studies of overlapping galaxy populations via multipole cross-power spectra. We apply our methodology to one of the widest-area galaxy redshift surveys currently available, the 6-degree Field Galaxy Survey, deducing a normalized growth rate f*sigma_8(z=0.06) = 0.38 +/- 0.12 in the low-redshift Universe, in agreement with previous analyses of this dataset using different techniques. Our framework should be useful for processing future wide-angle galaxy redshift surveys.Comment: 17 pages, 7 figures, version accepted by MNRA

Alzheimer's Disease: APP, Gamma Secretase, APOE, CLU, CR1, PICALM, ABCA7, BIN1, CD2AP, CD33, EPHA1, and MS4A2, and Their Relationships with Herpes Simplex, C. Pneumoniae, Other Suspect Pathogens, and the Immune System

Alzheimer's disease susceptibility genes, APP and gamma-secretase, are involved in the herpes simplex life cycle, and that of other suspect pathogens (C. pneumoniae, H. pylori, C. neoformans, B. burgdorferri, P. gingivalis) or immune defence. Such pathogens promote beta-amyloid deposition and tau phosphorylation and may thus be causative agents, whose effects are conditioned by genes. The antimicrobial effects of beta-amyloid, the localisation of APP/gamma-secretase in immunocompetent dendritic cells, and gamma secretase cleavage of numerous pathogen receptors suggest that this network is concerned with pathogen disposal, effects which may be abrogated by the presence of beta-amyloid autoantibodies in the elderly. These autoantibodies, as well as those to nerve growth factor and tau, also observed in Alzheimer's disease, may well be antibodies to pathogens, due to homology between human autoantigens and pathogen proteins. NGF or tau antibodies promote beta-amyloid deposition, neurofibrillary tangles, or cholinergic neuronal loss, and, with other autoantibodies, such as anti-ATPase, are potential agents of destruction, whose formation is dictated by sequence homology between pathogen and human proteins, and thus by pathogen strain and human genes. Pathogen elimination in the ageing population and removal of culpable autoantibodies might reduce the incidence and offer hope for a cure in this affliction