Properties of Ellipticity Correlation with Atmospheric Structure from Gemini South

Cosmic shear holds great promise for a precision independent measurement of $\Omega\rm_m$, the mass density of the universe relative to the critical density. The signal is expected to be weak, so a thorough understanding of systematic effects is crucial. An important systematic effect is the atmosphere: shear power introduced by the atmosphere is larger than the expected signal. Algorithms exist to extract the cosmic shear from the atmospheric component, though a measure of their success applied to a range of seeing conditions is lacking. To gain insight into atmospheric shear, Gemini South imaging in conjunction with ground condition and satellite wind data were obtained. We find that under good seeing conditions Point-Spread-Function (PSF) correlations persist well beyond the separation typical of high-latitude stars. Under these conditions, ellipticity residuals based on a simple PSF interpolation can be reduced to within a factor of a few of the shot-noise induced ellipticity floor. We also find that the ellipticity residuals are highly correlated with wind direction. Finally, we correct stellar shapes using a more sophisticated procedure and generate shear statistics from stars. Under all seeing conditions in our data set the residual correlations lie everywhere below the target signal level. For good seeing we find that the systematic error attributable to atmospheric turbulence is comparable in magnitude to the statistical error (shape noise) over angular scales relevant to present lensing surveys.Comment: To appear in ApJ April 10, 2007, 659

Human liver glycogen phosphorylase inhibitors bind at a new allosteric site

AbstractBackground: Glycogen phosphorylases catalyze the breakdown of glycogen to glucose-1-phosphate for glycolysis. Maintaining control of blood glucose levels is critical in minimizing the debilitating effects of diabetes, making liver glycogen phosphorylase a potential therapeutic target.Results: The binding site in human liver glycogen phosphorylase (HLGP) for a class of promising antidiabetic agents was identified crystallographically. The site is novel and functions allosterically by stabilizing the inactive conformation of HLGP. The initial view of the complex revealed key structural information and inspired the design of a new class of inhibitors which bind with nanomolar affinity and whose crystal structure is also described.Conclusions: We have identified the binding site of a new class of allosteric HLGP inhibitors. The crystal structure revealed the details of inhibitor binding, led to the design of a new class of compounds, and should accelerate efforts to develop therapeutically relevant molecules for the treatment of diabetes

Quantum transport through a DNA wire in a dissipative environment

Electronic transport through DNA wires in the presence of a strong dissipative environment is investigated. We show that new bath-induced electronic states are formed within the bandgap. These states show up in the linear conductance spectrum as a temperature dependent background and lead to a crossover from tunneling to thermal activated behavior with increasing temperature. Depending on the strength of the electron-bath coupling, the conductance at the Fermi level can show a weak exponential or even an algebraic length dependence. Our results suggest a new environmental-induced transport mechanism. This might be relevant for the understanding of molecular conduction experiments in liquid solution, like those recently performed on poly(GC) oligomers in a water buffer (B. Xu et al., Nano Lett 4, 1105 (2004)).Comment: 5 pages, 3 figure

Bupropion Increases Selection of High Effort Activity in Rats Tested on a Progressive Ratio/Chow Feeding Choice Procedure: Implications for Treatment of Effort-Related Motivational Symptoms

Background: Depression and related disorders are characterized by deficits in behavioral activation, exertion of effort, and other psychomotor/motivational dysfunctions. Depressed patients show alterations in effort-related decision making and a bias towards selection of low effort activities. It has been suggested that animal tests of effort-related decision making could be useful as models of motivational dysfunctions seen in psychopathology. Methods: Because clinical studies have suggested that inhibition of catecholamine uptake may be a useful strategy for treatment of effort-related motivational symptoms, the present research assessed the ability of bupropion to increase work output in rats responding on a test of effort-related decision-making (ie, a progressive ratio/chow feeding choice task). With this task, rats can choose between working for a preferred food (high-carbohydrate pellets) by lever pressing on a progressive ratio schedule vs obtaining a less preferred laboratory chow that is freely available in the chamber. Results: Bupropion (10.0–40.0 mg/kg intraperitoneal) significantly increased all measures of progressive ratio lever pressing, but decreased chow intake. These effects were greatest in animals with low baseline levels of work output on the progressive ratio schedule. Because accumbens dopamine is implicated in effort-related processes, the effects of bupropion on markers of accumbens dopamine transmission were examined. Bupropion elevated extracellular dopamine levels in accumbens core as measured by microdialysis and increased phosphorylated dopamine and cyclic-AMP related phosphoprotein 32 kDaltons (pDARPP-32) immunoreactivity in a manner consistent with D1 and D2 receptor stimulation. Conclusion: The ability of bupropion to increase exertion of effort in instrumental behavior may have implications for the pathophysiology and treatment of effort-related motivational symptoms in humans

Modeling the Mechanism of Action of a DGAT1 Inhibitor Using a Causal Reasoning Platform

Triglyceride accumulation is associated with obesity and type 2 diabetes. Genetic disruption of diacylglycerol acyltransferase 1 (DGAT1), which catalyzes the final reaction of triglyceride synthesis, confers dramatic resistance to high-fat diet induced obesity. Hence, DGAT1 is considered a potential therapeutic target for treating obesity and related metabolic disorders. However, the molecular events shaping the mechanism of action of DGAT1 pharmacological inhibition have not been fully explored yet. Here, we investigate the metabolic molecular mechanisms induced in response to pharmacological inhibition of DGAT1 using a recently developed computational systems biology approach, the Causal Reasoning Engine (CRE). The CRE algorithm utilizes microarray transcriptomic data and causal statements derived from the biomedical literature to infer upstream molecular events driving these transcriptional changes. The inferred upstream events (also called hypotheses) are aggregated into biological models using a set of analytical tools that allow for evaluation and integration of the hypotheses in context of their supporting evidence. In comparison to gene ontology enrichment analysis which pointed to high-level changes in metabolic processes, the CRE results provide detailed molecular hypotheses to explain the measured transcriptional changes. CRE analysis of gene expression changes in high fat habituated rats treated with a potent and selective DGAT1 inhibitor demonstrate that the majority of transcriptomic changes support a metabolic network indicative of reversal of high fat diet effects that includes a number of molecular hypotheses such as PPARG, HNF4A and SREBPs. Finally, the CRE-generated molecular hypotheses from DGAT1 inhibitor treated rats were found to capture the major molecular characteristics of DGAT1 deficient mice, supporting a phenotype of decreased lipid and increased insulin sensitivity

Metabolic sensitivity of pancreatic tumour cell apoptosis to glycogen phosphorylase inhibitor treatment

Inhibitors of glycogen breakdown regulate glucose homeostasis by limiting glucose production in diabetes. Here we demonstrate that restrained glycogen breakdown also inhibits cancer cell proliferation and induces apoptosis through limiting glucose oxidation, as well as nucleic acid and de novo fatty acid synthesis. Increasing doses (50-100 microM) of the glycogen phosphorylase inhibitor CP-320626 inhibited [1,2-(13)C(2)]glucose stable isotope substrate re-distribution among glycolysis, pentose and de novo fatty acid synthesis in MIA pancreatic adenocarcinoma cells. Limited oxidative pentose-phosphate synthesis, glucose contribution to acetyl CoA and de novo fatty acid synthesis closely correlated with decreased cell proliferation. The stable isotope-based dynamic metabolic profile of MIA cells indicated a significant dose-dependent decrease in macromolecule synthesis, which was detected at lower drug doses and before the appearance of apoptosis markers. Normal fibroblasts (CRL-1501) did not show morphological or metabolic signs of apoptosis likely due to their slow rate of growth and metabolic activity. This indicates that limiting carbon re-cycling and rapid substrate mobilisation from glycogen may be an effective and selective target site for new drug development in rapidly dividing cancer cells. In conclusion, pancreatic cancer cell growth arrest and death are closely associated with a characteristic decrease in glycogen breakdown and glucose carbon re-distribution towards RNA/DNA and fatty acids during CP-320626 treatment

Step-Scan Fourier Transform Infrared Absorption Difference Time-Resolved Spectroscopy Studies of Excited State Decay Kinetics and Electronic Structure of Low-Spin d6 Transition Metal Polypyridine Complexes With 10 Nanosecond Time Resolution

Step-scan Fourier transform absorption difference time-resolved spectroscopy (S2FTIR ∆A TRS) has been used to collect mid-IR time-resolved infrared spectra of the transient electronic excited states of polypyridine transition metal complexes with 10 ns time resolution. The time-resolved data can be used for kinetic analysis or to generate “snapshots” of the lowest lying excited state. Shifts of vibrational bands in the excited state relative to the ground state can be used to infer significant details of the electronic structure of the excited state. The multiplex advantage of the FTIR technique allows a wide variety of vibrational bands to be analyzed for this purpose. In the example illustrated, the shift of the ester ν(CO) band in {Ru(bpy)[4,4′-(COOEt)2bpy]2}

Green function techniques in the treatment of quantum transport at the molecular scale

The theoretical investigation of charge (and spin) transport at nanometer length scales requires the use of advanced and powerful techniques able to deal with the dynamical properties of the relevant physical systems, to explicitly include out-of-equilibrium situations typical for electrical/heat transport as well as to take into account interaction effects in a systematic way. Equilibrium Green function techniques and their extension to non-equilibrium situations via the Keldysh formalism build one of the pillars of current state-of-the-art approaches to quantum transport which have been implemented in both model Hamiltonian formulations and first-principle methodologies. We offer a tutorial overview of the applications of Green functions to deal with some fundamental aspects of charge transport at the nanoscale, mainly focusing on applications to model Hamiltonian formulations.Comment: Tutorial review, LaTeX, 129 pages, 41 figures, 300 references, submitted to Springer series "Lecture Notes in Physics

Do regional brain volumes and major depressive disorder share genetic architecture?:A study of Generation Scotland (<i>n</i>=19,762), UK Biobank (<i>n</i>=24,048) and the English Longitudinal Study of Ageing (<i>n</i>=5,766)

Major depressive disorder (MDD) is a heritable and highly debilitating condition. It is commonly associated with subcortical volumetric abnormalities, the most replicated of these being reduced hippocampal volume. Using the most recent published data from Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium's genome-wide association study of regional brain volume, we sought to test whether there is shared genetic architecture between seven subcortical brain volumes and intracranial volume (ICV) and MDD. We explored this using linkage disequilibrium score regression, polygenic risk scoring (PRS) techniques, Mendelian randomisation (MR) analysis and BUHMBOX. Utilising summary statistics from ENIGMA and Psychiatric Genomics Consortium, we demonstrated that hippocampal volume was positively genetically correlated with MDD (rG=0.46, P=0.02), although this did not survive multiple comparison testing. None of the other six brain regions studied were genetically correlated and amygdala volume heritability was too low for analysis. Using PRS analysis, no regional volumetric PRS demonstrated a significant association with MDD or recurrent MDD. MR analysis in hippocampal volume and MDD identified no causal association, however, BUHMBOX analysis identified genetic subgrouping in GS:SFHS MDD cases only (P=0.00281). In this study, we provide some evidence that hippocampal volume and MDD may share genetic architecture in a subgroup of individuals, albeit the genetic correlation did not survive multiple testing correction and genetic subgroup heterogeneity was not replicated. In contrast, we found no evidence to support a shared genetic architecture between MDD and other regional subcortical volumes or ICV