A meta-analysis of pharmacotherapy for social anxiety disorder: an examination of efficacy, moderators, and mediators

INTRODUCTION: Social anxiety disorder (SAD) is among the most prevalent mental disorders, associated with impaired functioning and poor quality of life. Pharmacotherapy is the most widely utilized treatment option. The current study provides an updated meta-analytic review of the efficacy of pharmacotherapy and examines moderators and mediators of treatment efficacy. Areas Covered: A comprehensive search of the current literature yielded 52 randomized, pill placebo-controlled trials of pharmacotherapy for adults diagnosed with SAD. Data on potential mediators of treatment outcome were collected, as well as data necessary to calculate pooled correlation matrices to compute indirect effects. Expert Opinion: The overall effect size of pharmacotherapy for SAD is small to medium (Hedges' g = 0.41). Effect sizes were not moderated by age, sex, length of treatment, initial severity, risk of study bias, or publication year. Furthermore, reductions in symptoms mediated pharmacotherapy's effect on quality of life. Support was found for reverse mediation. Future directions may include sustained efforts to examine treatment mechanisms of pharmacotherapy using rigorous longitudinal methodology to better establish temporal precedence

A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning

Light-cone-like spreading of correlations in a quantum many-body system

How fast can correlations spread in a quantum many-body system? Based on the seminal work by Lieb and Robinson, it has recently been shown that several interacting many-body systems exhibit an effective light cone that bounds the propagation speed of correlations. The existence of such a "speed of light" has profound implications for condensed matter physics and quantum information, but has never been observed experimentally. Here we report on the time-resolved detection of propagating correlations in an interacting quantum many-body system. By quenching a one-dimensional quantum gas in an optical lattice, we reveal how quasiparticle pairs transport correlations with a finite velocity across the system, resulting in an effective light cone for the quantum dynamics. Our results open important perspectives for understanding relaxation of closed quantum systems far from equilibrium as well as for engineering efficient quantum channels necessary for fast quantum computations.Comment: 7 pages, 5 figures, 2 table

Probabilistic Clustering of Time-Evolving Distance Data

We present a novel probabilistic clustering model for objects that are represented via pairwise distances and observed at different time points. The proposed method utilizes the information given by adjacent time points to find the underlying cluster structure and obtain a smooth cluster evolution. This approach allows the number of objects and clusters to differ at every time point, and no identification on the identities of the objects is needed. Further, the model does not require the number of clusters being specified in advance -- they are instead determined automatically using a Dirichlet process prior. We validate our model on synthetic data showing that the proposed method is more accurate than state-of-the-art clustering methods. Finally, we use our dynamic clustering model to analyze and illustrate the evolution of brain cancer patients over time

Rapidly Decaying Supernova 2010X: A Candidate ".Ia" Explosion

We present the discovery, photometric and spectroscopic follow-up observations of SN 2010X (PTF 10bhp). This supernova decays exponentially with tau_d=5 days, and rivals the current recordholder in speed, SN 2002bj. SN 2010X peaks at M_r=-17mag and has mean velocities of 10,000 km/s. Our light curve modeling suggests a radioactivity powered event and an ejecta mass of 0.16 Msun. If powered by Nickel, we show that the Nickel mass must be very small (0.02 Msun) and that the supernova quickly becomes optically thin to gamma-rays. Our spectral modeling suggests that SN 2010X and SN 2002bj have similar chemical compositions and that one of Aluminum or Helium is present. If Aluminum is present, we speculate that this may be an accretion induced collapse of an O-Ne-Mg white dwarf. If Helium is present, all observables of SN 2010X are consistent with being a thermonuclear Helium shell detonation on a white dwarf, a ".Ia" explosion. With the 1-day dynamic-cadence experiment on the Palomar Transient Factory, we expect to annually discover a few such events.Comment: 6 pages, 5 figures; Minor Changes; Note correction in Fig 4 caption; published by ApJ

A comprehensive evaluation of colonic mucosal isolates of Sutterella wadsworthensis from inflammatory bowel disease

Peer reviewedPublisher PD

Service provision and barriers to care for homeless people with mental health problems across 14 European capital cities

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Rapid Diagnostic Algorithms as a Screening Tool for Tuberculosis: An Assessor Blinded Cross-Sectional Study

Background: A major obstacle to effectively treat and control tuberculosis is the absence of an accurate, rapid, and low-cost diagnostic tool. A new approach for the screening of patients for tuberculosis is the use of rapid diagnostic classification algorithms. Methods: We tested a previously published diagnostic algorithm based on four biomarkers as a screening tool for tuberculosis in a Central European patient population using an assessor-blinded cross-sectional study design. In addition, we developed an improved diagnostic classification algorithm based on a study population at a tertiary hospital in Vienna, Austria, by supervised computational statistics. Results: The diagnostic accuracy of the previously published diagnostic algorithm for our patient population consisting of 206 patients was 54% (CI: 47%–61%). An improved model was constructed using inflammation parameters and clinical information. A diagnostic accuracy of 86% (CI: 80%–90%) was demonstrated by 10-fold cross validation. An alternative model relying solely on clinical parameters exhibited a diagnostic accuracy of 85% (CI: 79%–89%). Conclusion: Here we show that a rapid diagnostic algorithm based on clinical parameters is only slightly improved by inclusion of inflammation markers in our cohort. Our results also emphasize the need for validation of new diagnostic algorithms in different settings and patient populations