Recognition, assessment and treatment of social anxiety disorder: summary of NICE guidance

Social anxiety disorder is one of the most persistent and common of the anxiety disorders, with lifetime prevalence rates in Europe of 6.7% (range 3.9-13.7%).1 It often coexists with depression, substance use disorder, generalised anxiety disorder, panic disorder, and post-traumatic stress disorder.2 It can severely impair a person’s daily functioning by impeding the formation of relationships, reducing quality of life, and negatively affecting performance at work or school. Despite this, and the fact that effective treatments exist, only about half of people with this condition seek treatment, many after waiting 10-15 years.3 Although about 40% of those who develop the condition in childhood or adolescence recover before adulthood,4 for many the disorder persists into adulthood, with the chance of spontaneous recovery then limited compared with other mental health problems. This article summarises the most recent recommendations from the National Institute for Health and Care Excellence (NICE) on recognising, assessing, and treating social anxiety disorder in children, young people, and adults.

Bioinformatics on the Cloud Computing Platform Azure

We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development. © 2014 Shanahan et al

NFATc1 controls the cytotoxicity of CD8+ T cells

NFAT nuclear translocation has been shown to be required for CD8+ T cell cytokine production in response to viral infection. Here the authors show NFATc1 controls the cytotoxicity and metabolic switching of activated CD8+ T cells required for optimal response to bacteria and tumor cells

Dynamics of mitochondrial heteroplasmy in three families investigated via a repeatable re-sequencing study

Background: Originally believed to be a rare phenomenon, heteroplasmy - the presence of more than one mitochondrial DNA (mtDNA) variant within a cell, tissue, or individual - is emerging as an important component of eukaryotic genetic diversity. Heteroplasmies can be used as genetic markers in applications ranging from forensics to cancer diagnostics. Yet the frequency of heteroplasmic alleles may vary from generation to generation due to the bottleneck occurring during oogenesis. Therefore, to understand the alterations in allele frequencies at heteroplasmic sites, it is of critical importance to investigate the dynamics of maternal mtDNA transmission. Results: Here we sequenced, at high coverage, mtDNA from blood and buccal tissues of nine individuals from three families with a total of six maternal transmission events. Using simulations and re-sequencing of clonal DNA, we devised a set of criteria for detecting polymorphic sites in heterogeneous genetic samples that is resistant to the noise originating from massively parallel sequencing technologies. Application of these criteria to nine human mtDNA samples revealed four heteroplasmic sites. Conclusions: Our results suggest that the incidence of heteroplasmy may be lower than estimated in some other recent re-sequencing studies, and that mtDNA allelic frequencies differ significantly both between tissues of the same individual and between a mother and her offspring. We designed our study in such a way that the complete analysis described here can be repeated by anyone either at our site or directly on the Amazon Cloud. Our computational pipeline can be easily modified to accommodate other applications, such as viral re-sequencing

Deletion of transketolase triggers a stringent metabolic response in promastigotes and loss of virulence in amastigotes of Leishmania mexicana

Transketolase (TKT) is part of the non-oxidative branch of the pentose phosphate pathway (PPP). Here we describe the impact of removing this enzyme from the pathogenic protozoan Leishmania mexicana. Whereas the deletion had no obvious effect on cultured promastigote forms of the parasite, the Δtkt cells were not infective to mice. Δtkt promastigotes were more susceptible to oxidative stress and various leishmanicidal drugs than wild-type, and metabolomics analysis revealed profound changes to metabolism in these cells. In addition to changes consistent with those directly related to the role of TKT in the PPP, central carbon metabolism was substantially decreased, the cells consumed significantly less glucose, flux through glycolysis diminished, and production of the main end products of metabolism was decreased. Only minor changes in RNA abundance from genes encoding enzymes in central carbon metabolism, however, were detected although fructose-1,6-bisphosphate aldolase activity was decreased two-fold in the knock-out cell line. We also showed that the dual localisation of TKT between cytosol and glycosomes is determined by the C-terminus of the enzyme and by engineering different variants of the enzyme we could alter its sub-cellular localisation. However, no effect on the overall flux of glucose was noted irrespective of whether the enzyme was found uniquely in either compartment, or in both

Phenotypic characterisation of regulatory T cells in dogs reveals signature transcripts conserved in humans and mice

Regulatory T cells (Tregs) are a double-edged regulator of the immune system. Aberrations of Tregs correlate with pathogenesis of inflammatory, autoimmune and neoplastic disorders. Phenotypically and functionally distinct subsets of Tregs have been identified in humans and mice on the basis of their extensive portfolios of monoclonal antibodies (mAb) against Treg surface antigens. As an important veterinary species, dogs are increasingly recognised as an excellent model for many human diseases. However, insightful study of canine Tregs has been restrained by the limited availability of mAb. We therefore set out to characterise CD4+CD25high T cells isolated ex vivo from healthy dogs and showed that they possess a regulatory phenotype, function, and transcriptomic signature that resembles those of human and murine Tregs. By launching a cross-species comparison, we unveiled a conserved transcriptomic signature of Tregs and identified that transcript hip1 may have implications in Treg function

CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.https://doi.org/10.1186/1471-2105-12-35