Astroglial pentose phosphate pathway rates in response to high-glucose environments

ROS (reactive oxygen species) play an essential role in the pathophysiology of diabetes, stroke and neurodegenerative disorders. Hyperglycaemia associated with diabetes enhances ROS production and causes oxidative stress in vascular endothelial cells, but adverse effects of either acute or chronic high-glucose environments on brain parenchymal cells remain unclear. The PPP (pentose phosphate pathway) and GSH participate in a major defence mechanism against ROS in brain, and we explored the role and regulation of the astroglial PPP in response to acute and chronic high-glucose environments. PPP activity was measured in cultured neurons and astroglia by determining the difference in rate of 14CO2 production from [1-14C]glucose and [6-14C]glucose. ROS production, mainly H2O2, and GSH were also assessed. Acutely elevated glucose concentrations in the culture media increased PPP activity and GSH level in astroglia, decreasing ROS production. Chronically elevated glucose environments also induced PPP activation. Immunohistochemical analyses revealed that chronic high-glucose environments induced ER (endoplasmic reticulum) stress (presumably through increased hexosamine biosynthetic pathway flux). Nuclear translocation of Nrf2 (nuclear factor-erythroid 2 p45 subunit-related factor 2), which regulates G6PDH (glyceraldehyde-6-phosphate dehydrogenase) by enhancing transcription, was also observed in association with BiP (immunoglobulin heavy-chain-binding protein) expression. Acute and chronic high-glucose environments activated the PPP in astroglia, preventing ROS elevation. Therefore a rapid decrease in glucose level seems to enhance ROS toxicity, perhaps contributing to neural damage when insulin levels given to diabetic patients are not properly calibrated and plasma glucose levels are not adequately maintained. These findings may also explain the lack of evidence for clinical benefits from strict glycaemic control during the acute phase of stroke

Observation of contemporaneous optical radiation from a gamma-ray burst

The origin of gamma-ray bursts (GRBs) has been enigmatic since their discovery. The situation improved dramatically in 1997, when the rapid availability of precise coordinates for the bursts allowed the detection of faint optical and radio afterglows - optical spectra thus obtained have demonstrated conclusively that the bursts occur at cosmological distances. But, despite efforts by several groups, optical detection has not hitherto been achieved during the brief duration of a burst. Here we report the detection of bright optical emission from GRB990123 while the burst was still in progress. Our observations begin 22 seconds after the onset of the burst and show an increase in brightness by a factor of 14 during the first 25 seconds; the brightness then declines by a factor of 100, at which point (700 seconds after the burst onset) it falls below our detection threshold. The redshift of this burst, approximately 1.6, implies a peak optical luminosity of 5 times 10^{49} erg per second. Optical emission from gamma-ray bursts has been generally thought to take place at the shock fronts generated by interaction of the primary energy source with the surrounding medium, where the gamma-rays might also be produced. The lack of a significant change in the gamma-ray light curve when the optical emission develops suggests that the gamma-rays are not produced at the shock front, but closer to the site of the original explosion.Comment: 10 pages, 2 figures. Accepted for publication in Nature. For additional information see http://www.umich.edu/~rotse

Differential expression analysis for sequence count data

*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.

*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. 

*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from "http://www-huber.embl.de/users/anders/DESeq":http://www-huber.embl.de/users/anders/DESeq

Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution

Mechanism of Chemical Activation of Nrf2

NF-E2 related factor-2 (Nrf2) promotes the transcription of many cytoprotective genes and is a major drug target for prevention of cancer and other diseases. Indeed, the cancer-preventive activities of several well-known chemical agents were shown to depend on Nrf2 activation. It is well known that chemopreventive Nrf2 activators stabilize Nrf2 by blocking its ubiquitination, but previous studies have indicated that this process occurs exclusively in the cytoplasm. Kelch-like ECH-associated protein 1 (Keap1) binds to Nrf2 and orchestrates Nrf2 ubiquitination, and it has been a widely-held view that inhibition of Nrf2 ubiquitination by chemopreventive agents results from the dissociation of Nrf2 from its repressor Keap1. Here, we show that while the activation of Nrf2 by prototypical chemical activators, including 5,6-dihydrocyclopenta-1,2-dithiole-3-thione (CPDT) and sulforaphane (SF), results solely from inhibition of its ubiquitination, such inhibition occurs predominantly in the nucleus. Moreover, the Nrf2 activators promote Nrf2 association with Keap1, rather than disassociation, which appears to result from inhibition of Nrf2 phosphorylation at Ser40. Available evidence suggests the Nrf2 activators may block Nrf2 ubiquitination by altering Keap1 conformation via reaction with the thiols of specific Keap1 cysteines. We further show that while the inhibitory effects of CPDT and SF on Nrf2 ubiquitination depend entirely on Keap1, Nrf2 is also degraded by a Keap1-independent mechanism. These findings provide significant new insight about Nrf2 activation and suggest that exogenous chemical activators of Nrf2 enter the nucleus to exert most of their inhibitory impact on Nrf2 ubiquitination and degradation

Optical Magnetometry

Some of the most sensitive methods of measuring magnetic fields utilize interactions of resonant light with atomic vapor. Recent developments in this vibrant field are improving magnetometers in many traditional areas such as measurement of geomagnetic anomalies and magnetic fields in space, and are opening the door to new ones, including, dynamical measurements of bio-magnetic fields, detection of nuclear magnetic resonance (NMR), magnetic-resonance imaging (MRI), inertial-rotation sensing, magnetic microscopy with cold atoms, and tests of fundamental symmetries of Nature.Comment: 11 pages; 4 figures; submitted to Nature Physic

Mechanisms for the Evolution of a Derived Function in the Ancestral Glucocorticoid Receptor

Understanding the genetic, structural, and biophysical mechanisms that caused protein functions to evolve is a central goal of molecular evolutionary studies. Ancestral sequence reconstruction (ASR) offers an experimental approach to these questions. Here we use ASR to shed light on the earliest functions and evolution of the glucocorticoid receptor (GR), a steroid-activated transcription factor that plays a key role in the regulation of vertebrate physiology. Prior work showed that GR and its paralog, the mineralocorticoid receptor (MR), duplicated from a common ancestor roughly 450 million years ago; the ancestral functions were largely conserved in the MR lineage, but the functions of GRs—reduced sensitivity to all hormones and increased selectivity for glucocorticoids—are derived. Although the mechanisms for the evolution of glucocorticoid specificity have been identified, how reduced sensitivity evolved has not yet been studied. Here we report on the reconstruction of the deepest ancestor in the GR lineage (AncGR1) and demonstrate that GR's reduced sensitivity evolved before the acquisition of restricted hormone specificity, shortly after the GR–MR split. Using site-directed mutagenesis, X-ray crystallography, and computational analyses of protein stability to recapitulate and determine the effects of historical mutations, we show that AncGR1's reduced ligand sensitivity evolved primarily due to three key substitutions. Two large-effect mutations weakened hydrogen bonds and van der Waals interactions within the ancestral protein, reducing its stability. The degenerative effect of these two mutations is extremely strong, but a third permissive substitution, which has no apparent effect on function in the ancestral background and is likely to have occurred first, buffered the effects of the destabilizing mutations. Taken together, our results highlight the potentially creative role of substitutions that partially degrade protein structure and function and reinforce the importance of permissive mutations in protein evolution

Political and social determinants of life expectancy in less developed countries: a longitudinal study

<p>Abstract</p> <p>Background</p> <p>This study aimed to examine the longitudinal contributions of four political and socioeconomic factors to the increase in life expectancy in less developed countries (LDCs) between 1970 and 2004.</p> <p>Methods</p> <p>We collected 35 years of annual data for 119 LDCs on life expectancy at birth and on four key socioeconomic indicators: economy, measured by log10 gross domestic product per capita at purchasing power parity; educational environment, measured by the literacy rate of the adult population aged 15 years and over; nutritional status, measured by the proportion of undernourished people in the population; and political regime, measured by the regime score from the Polity IV database. Using linear mixed models, we analyzed the longitudinal effects of these multiple factors on life expectancy at birth with a lag of 0-10 years, adjusting for both time and regional correlations.</p> <p>Results</p> <p>The LDCs' increases in life expectancy over time were associated with all four factors. Political regime had the least influence on increased life expectancy to begin with, but became significant starting in the 3rd year and continued to increase, while the impact of the other socioeconomic factors began strong but continually decreased over time. The combined effects of these four socioeconomic and political determinants contributed 54.74% - 98.16% of the life expectancy gains throughout the lag periods of 0-10 years.</p> <p>Conclusions</p> <p>Though the effect of democratic politics on increasing life expectancy was relatively small in the short term when compared to the effects of the other socioeconomic factors, the long-term impact of democracy should not be underestimated.</p

Nomenclature and heterogeneity : consequences for the use of mesenchymal stem cells in regenerative medicine

Mesenchymal stem cells (MSCs) are in development for many clinical indications, based both on “stem” properties (tissue repair or regeneration) and on signalling repertoire (immunomodulatory and anti-inflammatory effects). Potential conflation of MSC properties with those of tissue-derived stromal cells presents difficulties in comparing study outcomes and represents a source of confusion in cell therapy development. Cultured MSCs demonstrate significant heterogeneity in clonogenicity and multi-lineage differentiation potential. However in vivo biology of MSCs includes native functions unrelated to regenerative medicine applications, so do nomenclature and heterogeneity matter? In this perspective we examine some consequences of the nomenclature debate and heterogeneity of MSCs. Regulatory expectations are considered, emphasising that product development should prioritise detailed characterisation of therapeutic cell populations for specific indications