INTEGRAL and New Classes of High-Mass X-ray Binaries

The gamma-ray observatory INTEGRAL, launched in October 2002, produces a wealth of discoveries and new results on compact high energy Galactic objects, nuclear gamma-ray line emission, diffuse line and continuum emission, cosmic background radiation, AGN and high energy transients. Two important serendipitous discoveries made by the INTEGRAL mission are new classes of X-ray binaries, namely the highly-obscured high-mass X-ray binaries, and the super-giant fast transients. In this paper I will review the current status of these discoveries.Comment: 3 pages, 1 figure, submitted; Proceedings "The nature and evolution of X-ray binaries in diverse environments", St Petersburg/FL, USA, 28 Oct - 02 Nov 200

The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects

Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p\u3c0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p\u3c0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of big data (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA\u27s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Understanding the errors of SHAPE-directed RNA structure modeling

Single-nucleotide-resolution chemical mapping for structured RNA is being rapidly advanced by new chemistries, faster readouts, and coupling to computational algorithms. Recent tests have shown that selective 2'-hydroxyl acylation by primer extension (SHAPE) can give near-zero error rates (0-2%) in modeling the helices of RNA secondary structure. Here, we benchmark the method using six molecules for which crystallographic data are available: tRNA(phe) and 5S rRNA from Escherichia coli, the P4-P6 domain of the Tetrahymena group I ribozyme, and ligand-bound domains from riboswitches for adenine, cyclic di-GMP, and glycine. SHAPE-directed modeling of these highly structured RNAs gave an overall false negative rate (FNR) of 17% and a false discovery rate (FDR) of 21%, with at least one helix prediction error in five of the six cases. Extensive variations of data processing, normalization, and modeling parameters did not significantly mitigate modeling errors. Only one varation, filtering out data collected with deoxyinosine triphosphate during primer extension, gave a modest improvement (FNR = 12%, and FDR = 14%). The residual structure modeling errors are explained by the insufficient information content of these RNAs' SHAPE data, as evaluated by a nonparametric bootstrapping analysis. Beyond these benchmark cases, bootstrapping suggests a low level of confidence (<50%) in the majority of helices in a previously proposed SHAPE-directed model for the HIV-1 RNA genome. Thus, SHAPE-directed RNA modeling is not always unambiguous, and helix-by-helix confidence estimates, as described herein, may be critical for interpreting results from this powerful methodology.Comment: Biochemistry, Article ASAP (Aug. 15, 2011

Tocotrienol Affects Oxidative Stress, Cholesterol Homeostasis and the Amyloidogenic Pathway in Neuroblastoma Cells: Consequences for Alzheimer’s Disease

One of the characteristics of Alzheimer´s disease (AD) is an increased amyloid load and an enhanced level of reactive oxidative species (ROS). Vitamin E has known beneficial neuroprotective effects, and previously, some studies suggested that vitamin E is associated with a reduced risk of AD due to its antioxidative properties. However, epidemiological studies and nutritional approaches of vitamin E treatment are controversial. Here, we investigate the effect of α-tocotrienol, which belongs to the group of vitamin E, on AD-relevant processes in neuronal cell lines. In line with the literature, α-tocotrienol reduced the ROS level in SH-SY5Y cells. In the presence of tocotrienols, cholesterol and cholesterol esters, which have been shown to be risk factors in AD, were decreased. Besides the unambiguous positive effects of tocotrienol, amyloid-β (Aβ) levels were increased accompanied by an increase in the activity of enzymes responsible for Aβ production. Proteins and gene expression of the secretases and their components remained unchanged, whereas tocotrienol accelerates enzyme activity in cell-free assays. Besides enhanced Aβ production, tocotrienols inhibited Aβ degradation in neuro 2a (N2a)-cells. Our results might help to understand the controversial findings of vitamin E studies and demonstrate that besides the known positive neuroprotective properties, tocotrienols also have negative characteristics with respect to AD

The status of GEO 600

The GEO 600 laser interferometer with 600m armlength is part of a worldwide network of gravitational wave detectors. GEO 600 is unique in having advanced multiple pendulum suspensions with a monolithic last stage and in employing a signal recycled optical design. This paper describes the recent commissioning of the interferometer and its operation in signal recycled mode

Ethnic Variation in Inflammatory Profile in Tuberculosis

PMCID: PMC3701709This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Integrated vehicle-based safety systems light-vehicle field operational test key findings report

This document presents key findings from the light-vehicle field operational test conducted as part of the Integrated Vehicle-Based Safety Systems program. These findings are the result of analyses performed by the University of Michigan Transportation Research Institute to examine the effects of a prototype integrated crash warning system on driving behavior and driver acceptance. The light-vehicle platform included four integrated crash-warning subsystems (forward-crash, lateral-drift, lane-change/merge crash, and curve-speed warnings) installed on a fleet of 16 passenger cars and operated by 108 randomly-sampled drivers for a period of six weeks each. Each car was instrumented to capture detailed data on the driving environment, driver behavior, warning system activity, and vehicle kinematics. Data on driver acceptance was collected through a post-drive survey, debriefings and focus groups. Key findings indicate that use of the integrated crash warning system resulted in improvements in lane-keeping, fewer lane departures, and increased turn-signal use. The research also indicated that drivers were slightly more likely to maintain shorter headways with the integrated system. No negative behavioral adaptation effects were observed as a result of drivers’ involvement in secondary task behaviors. Drivers generally accepted the integrated crash warning system and 72 percent of all drivers said they would like to have an integrated warning system in their personal vehicles. Drivers also reported that they found the blind-spot detection component of the lane-change/merge crash warning system to be the most useful and satisfying aspect of the integrated system.U.S. Department of Transportation Research and Innovative Technology Administration ITS Joint Program Officehttp://deepblue.lib.umich.edu/bitstream/2027.42/84379/1/102748.pd

Integrated vehicle-based safety systems heavy truck field operational test, methodology and results report

This document presents the methodology and results from the heavy-truck field operational test conducted as part of the Integrated Vehicle-Based Safety Systems program. These findings are the result of analyses performed by the University of Michigan Transportation Research Institute to examine the effect of a prototype integrated crash warning system on driving behavior and driver acceptance. The heavy-truck platform included three integrated crash-warning subsystems (forward crash, lateral drift, and lane-change/merge crash warnings) installed on a fleet of 10 Class 8 tractors and operated by18 commercial drivers for 10 months. Each truck was instrumented to capture detailed data on the driving environment, driver behavior, warning system activity, and vehicle kinematics. Data on driver acceptance was collected through a post-drive survey and debriefings. The results indicate that integrated crash warning systems not only offer benefits relative to improved driver performance (e.g., improved headway keeping), but that the majority of commercial drivers accepted the system and reported subjective benefits from the integrated system they used. Of the drivers who participated, 15 out of 18 stated that they preferred a truck with the integrated system, stating that they would also recommend that their company consider the purchase of vehicles with integrated safety systems installed. No negative behavioral adaptation effects from the drivers‘ 10-month use of the integrated system were observed.U.S. Department of Transportation Research and Innovative Technology Administration ITS Joint Program Officehttp://deepblue.lib.umich.edu/bitstream/2027.42/84380/1/102749.pd