Using visual analytics to develop situation awareness in astrophysics

We present a novel collaborative visual analytics application for cognitively overloaded users in the astrophysics domain. The system was developed for scientists who need to analyze heterogeneous, complex data under time pressure, and make predictions and time-critical decisions rapidly and correctly under a constant influx of changing data. The Sunfall Data Taking system utilizes several novel visualization and analysis techniques to enable a team of geographically distributed domain specialists to effectively and remotely maneuver a custom-built instrument under challenging operational conditions. Sunfall Data Taking has been in production use for 2 years by a major international astrophysics collaboration (the largest data volume supernova search currently in operation), and has substantially improved the operational efficiency of its users. We describe the system design process by an interdisciplinary team, the system architecture and the results of an informal usability evaluation of the production system by domain experts in the context of Endsley's three levels of situation awareness

Harnessing Complexity in High Performance Computing Ecosystems: A Complex Adaptive Systems Framework

The use of high performance computing (HPC) has been generating influential scientific breakthroughs since the twentieth century. Yet there have been few studies of the complex socio-technical systems formed by these supercomputers and the humans who operate and use them. In this paper, we describe the first complex adaptive systems (CAS) analysis of the dynamics of HPC ecosystems. We conducted an 18-month ethnographic study that included scientific collaborations that use an HPC research center and examined the processes in HPC socio-technical systems via CAS theory to devise organizational designs and strategies that take advantage of system complexity. We uncovered several significant mismatches in the variation and adaptation processes within subsystems and conclude with three potential design directions for management and organization of HPC socio-technical ecosystems

Accuracy of methods for diagnosing atrial fibrillation using 12-lead ECG: a systematic review and meta-analysis

Background: Screening for atrial fibrillation (AF) using 12-lead-electrocardiograms (ECGs) has been recommended; however, the best method for interpreting ECGs to diagnose AF is not known. We compared accuracy of methods for diagnosing AF from ECGs. Methods: We searched MEDLINE, EMBASE, CINAHL and LILACS until March 24, 2014. Two reviewers identified eligible studies, extracted data and appraised quality using the QUADAS-2 instrument. Meta-analysis, using the bivariate hierarchical random effects method, determined average operating points for sensitivities, specificities, positive and negative likelihood ratios (PLR, NLR) and enabled construction of Summary Receiver Operating Characteristic (SROC) plots. Results: 10 studies investigated 16 methods for interpreting ECGs (n = 55,376 participant ECGs). The sensitivity and specificity of automated software (8 studies; 9 methods) were 0.89 (95% C.I. 0.82–0.93) and 0.99 (95% C.I. 0.99–0.99), respectively; PLR 96.6 (95% C.I. 64.2–145.6); NLR 0.11 (95% C.I. 0.07–0.18). Indirect comparisons with software found healthcare professionals (5 studies; 7 methods) had similar sensitivity for diagnosing AF but lower specificity [sensitivity 0.92 (95% C.I. 0.81–0.97), specificity 0.93 (95% C.I. 0.76–0.98), PLR 13.9 (95% C.I. 3.5–55.3), NLR 0.09 (95% C.I. 0.03–0.22)]. Sub-group analyses of primary care professionals found greater specificity for GPs than nurses [GPs: sensitivity 0.91 (95% C.I. 0.68–1.00); specificity 0.96 (95% C.I. 0.89–1.00). Nurses: sensitivity 0.88 (95% C.I. 0.63–1.00); specificity 0.85 (95% C.I. 0.83–0.87)]. Conclusions: Automated ECG-interpreting software most accurately excluded AF, although its ability to diagnose this was similar to all healthcare professionals. Within primary care, the specificity of AF diagnosis from ECG was greater for GPs than nurses

Increased therapeutic potential of an experimental anti-mitotic inhibitor SB715992 by genistein in PC-3 human prostate cancer cell line

BACKGROUND: Kinesin spindle proteins (KSP) are motor proteins that play an essential role in mitotic spindle formation. HsEg5, a KSP, is responsible for the formation of the bipolar spindle, which is critical for proper cell division during mitosis. The function of HsEg5 provides a novel target for the manipulation of the cell cycle and the induction of apoptosis. SB715992, an experimental KSP inhibitor, has been shown to perturb bipolar spindle formation, thus making it an excellent candidate for anti-cancer agent. Our major objective was a) to investigate the cell growth inhibitory effects of SB715992 on PC-3 human prostate cancer cell line, b) to investigate whether the growth inhibitory effects of SB715992 could be enhanced when combined with genistein, a naturally occurring isoflavone and, c) to determine gene expression profile to establish molecular mechanism of action of SB715992. METHODS: PC-3 cells were treated with varying concentration of SB715992, 30 μM of genistein, and SB715992 plus 30 μM of genistein. After treatments, PC-3 cells were assayed for cell proliferation, induction of apoptosis, and alteration in gene and protein expression using cell inhibition assay, apoptosis assay, microarray analysis, real-time RT-PCR, and Western Blot analysis. RESULTS: SB715992 inhibited cell proliferation and induced apoptosis in PC-3 cells. SB715992 was found to regulate the expression of genes related to the control of cell proliferation, cell cycle, cell signaling pathways, and apoptosis. In addition, our results showed that combination treatment with SB715992 and genistein caused significantly greater cell growth inhibition and induction of apoptosis compared to the effects of either agent alone. CONCLUSION: Our results clearly show that SB715992 is a potent anti-tumor agent whose therapeutic effects could be enhanced by genistein. Hence, we believe that SB715992 could be a novel agent for the treatment of prostate cancer with greater success when combined with a non-toxic natural agent like genistein

Depression of glutamate and GABA release by presynaptic GABAB receptors in the entorhinal cortex in normal and chronically epileptic rats

Presynaptic GABAB receptors (GABABR) control glutamate and GABA release at many synapses in the nervous system. In the present study we used whole-cell patch-clamp recordings of spontaneous excitatory and inhibitory synaptic currents in the presence of TTX to monitor glutamate and GABA release from synapses in layer II and V of the rat entorhinal cortex (EC)in vitro. In both layers the release of both transmitters was reduced by application of GABABR agonists. Quantitatively, the depression of GABA release in layer II and layer V, and of glutamate release in layer V was similar, but glutamate release in layer II was depressed to a greater extent. The data suggest that the same GABABR may be present on both GABA and glutamate terminals in the EC, but that the heteroreceptor may show a greater level of expression in layer II. Studies with GABABR antagonists suggested that neither the auto- nor the heteroreceptor was consistently tonically activated by ambient GABA in the presence of TTX. Studies in EC slices from rats made chronically epileptic using a pilocarpine model of temporal lobe epilepsy revealed a reduced effectiveness of both auto- and heteroreceptor function in both layers. This could suggest that enhanced glutamate and GABA release in the EC may be associated with the development of the epileptic condition. Copyright © 2006 S. Karger AG

Peripheral Delivery of a CNS Targeted, Metalo-Protease Reduces Aβ Toxicity in a Mouse Model of Alzheimer's Disease

Alzheimer's disease (AD), an incurable, progressive neurodegenerative disorder, is the most common form of dementia. Therapeutic options have been elusive due to the inability to deliver proteins across the blood-brain barrier (BBB). In order to improve the therapeutic potential for AD, we utilized a promising new approach for delivery of proteins across the BBB. We generated a lentivirus vector expressing the amyloid β-degrading enzyme, neprilysin, fused to the ApoB transport domain and delivered this by intra-peritoneal injection to amyloid protein precursor (APP) transgenic model of AD. Treated mice had reduced levels of Aβ, reduced plaques and increased synaptic density in the CNS. Furthermore, mice treated with the neprilysin targeting the CNS had a reversal of memory deficits. Thus, the addition of the ApoB transport domain to the secreted neprilysin generated a non-invasive therapeutic approach that may be a potential treatment in patients with AD

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development