Histories of abuse predict stronger within-person covariation of ovarian steroids and mood symptoms in women with menstrually related mood disorder

Individual differences in sensitivity to cyclical changes in ovarian steroids estradiol (E2) and progesterone (P4) have been implicated in the pathophysiology of menstrually related mood disorder (MRMD). However, no prospective studies have investigated psychosocial risk factors for sensitivity to hormone effects on mood in MRMD. Using a repeated measures approach and multilevel models, we tested the hypothesis that a history of abuse provides a context in which within-person elevations of E2 and P4 prospectively predict daily symptoms

Toward the Reliable Diagnosis of DSM-5 Premenstrual Dysphoric Disorder: The Carolina Premenstrual Assessment Scoring System (C-PASS)

Despite evidence for the validity of premenstrual dysphoric disorder (PMDD) and its recent inclusion in DSM-5, variable diagnostic practices compromise the construct validity of the diagnosis and threaten the clarity of efforts to understand and treat its underlying pathophysiology. In an effort to hasten and streamline the translation of the new DSM-5 criteria for PMDD into terms compatible with existing research practices, we present the development and initial validation of the Carolina Premenstrual Assessment Scoring System (C-PASS). The C-PASS is a standardized scoring system for making DSM-5 PMDD diagnoses using 2 or more menstrual cycles of daily symptom ratings using the Daily Record of Severity of Problems (DRSP)

The TIGGE project and its achievements

TIGGE was a major component of the THORPEX (The Observing System Research and Predictability Experiment) research program, whose aim is to accelerate improvements in forecasting high-impact weather. By providing ensemble prediction data from leading operational forecast centers, TIGGE has enhanced collaboration between the research and operational meteorological communities and enabled research studies on a wide range of topics. The paper covers the objective evaluation of the TIGGE data. For a range of forecast parameters, it is shown to be beneficial to combine ensembles from several data providers in a Multi-model Grand Ensemble. Alternative methods to correct systematic errors, including the use of reforecast data, are also discussed. TIGGE data have been used for a range of research studies on predictability and dynamical processes. Tropical cyclones are the most destructive weather systems in the world, and are a focus of multi-model ensemble research. Their extra-tropical transition also has a major impact on skill of mid-latitude forecasts. We also review how TIGGE has added to our understanding of the dynamics of extra-tropical cyclones and storm tracks. Although TIGGE is a research project, it has proved invaluable for the development of products for future operational forecasting. Examples include the forecasting of tropical cyclone tracks, heavy rainfall, strong winds, and flood prediction through coupling hydrological models to ensembles. Finally the paper considers the legacy of TIGGE. We discuss the priorities and key issues in predictability and ensemble forecasting, including the new opportunities of convective-scale ensembles, links with ensemble data assimilation methods, and extension of the range of useful forecast skill

Discovery and Development of Toll-Like Receptor 4 (TLR4) Antagonists: A New Paradigm for Treating Sepsis and Other Diseases

Abstract. Sepsis remains the most common cause of death in intensive care units in the USA, with a current estimate of at least 750,000 cases per year, and 215,000 deaths annually. Despite extensive research still we do not quite understand the cellular and molecular mechanisms that are involved in triggering and propagation of septic injury. Endotoxin (lipopolysaccharide from Gram-negative bacteria, or LPS) has been implicated as a major cause of this syndrome. Inflammatory shock as a consequence of LPS release remains a serious clinical concern. In humans, inflammatory responses to LPS result in the release of cytokines and other cell mediators from monocytes and macrophages, which can cause fever, shock, organ failure and death. A number of different approaches have been investigated to try to treat and/or prevent the septic shock associated with infections caused by Gram-negative bacteria, including blockage of one or more of the cytokines induced by LPS. Recently several novel amphipathic compounds have been developed as direct LPS antagonists at the LPS receptor, TLR4. This review article will outline the current knowledge on the TLR4-LPS synthesis and discuss the signaling, in vitro pre-clinical and in vivo clinical evaluation of TLR4 antagonists and their potential use in sepsis and a variety of diseases such as atherosclerosis as well as hepatic and renal malfunction. KEY WORDS: drug discovery; LPS; sepsis; toll-like receptor antagonists

Visualizing Big Data with augmented and virtual reality: challenges and research agenda

This paper provides a multi-disciplinary overview of the research issues and achievements in the field of Big Data and its visualization techniques and tools. The main aim is to summarize challenges in visualization methods for existing Big Data, as well as to offer novel solutions for issues related to the current state of Big Data Visualization. This paper provides a classification of existing data types, analytical methods, visualization techniques and tools, with a particular emphasis placed on surveying the evolution of visualization methodology over the past years. Based on the results, we reveal disadvantages of existing visualization methods. Despite the technological development of the modern world, human involvement (interaction), judgment and logical thinking are necessary while working with Big Data. Therefore, the role of human perceptional limitations involving large amounts of information is evaluated. Based on the results, a non-traditional approach is proposed: we discuss how the capabilities of Augmented Reality and Virtual Reality could be applied to the field of Big Data Visualization. We discuss the promising utility of Mixed Reality technology integration with applications in Big Data Visualization. Placing the most essential data in the central area of the human visual field in Mixed Reality would allow one to obtain the presented information in a short period of time without significant data losses due to human perceptual issues. Furthermore, we discuss the impacts of new technologies, such as Virtual Reality displays and Augmented Reality helmets on the Big Data visualization as well as to the classification of the main challenges of integrating the technology.publishedVersionPeer reviewe

Ciliopathies: an expanding disease spectrum

Ciliopathies comprise a group of disorders associated with genetic mutations encoding defective proteins, which result in either abnormal formation or function of cilia. As cilia are a component of almost all vertebrate cells, cilia dysfunction can manifest as a constellation of features that include characteristically, retinal degeneration, renal disease and cerebral anomalies. Additional manifestations include congenital fibrocystic diseases of the liver, diabetes, obesity and skeletal dysplasias. Ciliopathic features have been associated with mutations in over 40 genes to date. However, with over 1,000 polypeptides currently identified within the ciliary proteome, several other disorders associated with this constellation of clinical features will likely be ascribed to mutations in other ciliary genes. The mechanisms underlying many of the disease phenotypes associated with ciliary dysfunction have yet to be fully elucidated. Several elegant studies have crucially demonstrated the dynamic ciliary localisation of components of the Hedgehog and Wnt signalling pathways during signal transduction. Given the critical role of the cilium in transducing “outside-in” signals, it is not surprising therefore, that the disease phenotypes consequent to ciliary dysfunction are a manifestation of aberrant signal transduction. Further investigation is now needed to explore the developmental and physiological roles of aberrant signal transduction in the manifestation of ciliopathy phenotypes. Utilisation of conditional and inducible murine models to delete or overexpress individual ciliary genes in a spatiotemporal and organ/cell-specific manner should help clarify some of the functional roles of ciliary proteins in the manifestation of phenotypic features

Activated T-cells inhibit neurogenesis by releasing granzyme B: Rescue by Kv1.3 blockers

There is a great need for pharmacological approaches to enhance neural progenitor cell (NPC) function particularly in neuroinflammatory diseases with failed neuroregeneration. In diseases such as multiple sclerosis and stroke, T-cell infiltration occurs in periventricular zones where NPCs are located and is associated with irreversible neuronal loss.We studied the effect of T-cellactivation on NPC functions. NPC proliferation and neuronal differentiation were impaired by granzyme B (GrB) released by the T-cells. GrB mediated its effects by the activation of a Gi-protein-coupled receptor leading to decreased intracellular levels of cAMP and subsequent expression of the voltagedependent potassium channel, Kv1.3. Importantly, blocking channel activity with margatoxin or blocking its expression reversed the inhibitory effects of GrB on NPCs. We have thus identified a novel pathway in neurogenesis. The increased expression of Kv1.3 in pathological conditions makes it a novel target for promoting neurorestoration. Copyright © 2010 the authors.Link_to_subscribed_fulltex