Radiation dose-rate effects on gene expression for human biodosimetry

Background: The effects of dose-rate and its implications on radiation biodosimetry methods are not well studied in the context of large-scale radiological scenarios. There are significant health risks to individuals exposed to an acute dose, but a realistic scenario would include exposure to both high and low dose-rates, from both external and internal radioactivity. It is important therefore, to understand the biological response to prolonged exposure; and further, discover biomarkers that can be used to estimate damage from low-dose rate exposures and propose appropriate clinical treatment. Methods: We irradiated human whole blood ex vivo to three doses, 0.56 Gy, 2.23 Gy and 4.45 Gy, using two dose rates: acute, 1.03 Gy/min and a low dose-rate, 3.1 mGy/min. After 24 h, we isolated RNA from blood cells and these were hybridized to Agilent Whole Human genome microarrays. We validated the microarray results using qRT-PCR. Results: Microarray results showed that there were 454 significantly differentially expressed genes after prolonged exposure to all doses. After acute exposure, 598 genes were differentially expressed in response to all doses. Gene ontology terms enriched in both sets of genes were related to immune processes and B-cell mediated immunity. Genes responding to acute exposure were also enriched in functions related to natural killer cell activation and cell-to-cell signaling. As expected, the p53 pathway was found to be significantly enriched at all doses and by both dose-rates of radiation. A support vectors machine classifier was able to distinguish between dose-rates with 100% accuracy using leave-one-out cross-validation. Conclusions: In this study we found that low dose-rate exposure can result in distinctive gene expression patterns compared with acute exposures. We were able to successfully distinguish low dose-rate exposed samples from acute dose exposed samples at 24 h, using a gene expression-based classifier. These genes are candidates for further testing as markers to classify exposure based on dose-rate

Nonequilibrium relaxation study of the anisotropic antiferromagnetic Heisenberg model on the triangular lattice

Effect of exchange anisotropy on the relaxation time of spin and vector chirality is studied for the antiferromagnetic classical Heisenberg model on the triangular lattice by using the nonequilibrium relaxation Monte Carlo method. We identify the Berezinskii-Kosterlitz-Thouless (BKT) transition and the chiral transition in a wide range of the anisotropy, even for very small anisotropy of $\sim$ 0.01%. As the anisotropy decreases, both the critical temperatures steeply decrease, while the BKT critical region becomes divergently wide. We elucidate a sharp "V shape" of the phase diagram around the isotropic Heisenberg point, which suggests that the isotropic case is exceptionally singular and the associated Z vortex transition will be isolated from the BKT and chiral transitions. We discuss the relevance of our results to peculiar behavior of the spin relaxation time observed experimentally in triangular antiferromagnets.Comment: 5 pages, 4 figures, accepted for publication in J. Phys. Soc. Jp

Comparative Transcriptional Network Modeling of Three PPAR-α/γ Co-Agonists Reveals Distinct Metabolic Gene Signatures in Primary Human Hepatocytes

Aims: To compare the molecular and biologic signatures of a balanced dual peroxisome proliferator-activated receptor (PPAR)-α/γ agonist, aleglitazar, with tesaglitazar (a dual PPAR-α/γ agonist) or a combination of pioglitazone (Pio; PPAR-γ agonist) and fenofibrate (Feno; PPAR-α agonist) in human hepatocytes. Methods and Results: Gene expression microarray profiles were obtained from primary human hepatocytes treated with EC50-aligned low, medium and high concentrations of the three treatments. A systems biology approach, Causal Network Modeling, was used to model the data to infer upstream molecular mechanisms that may explain the observed changes in gene expression. Aleglitazar, tesaglitazar and Pio/Feno each induced unique transcriptional signatures, despite comparable core PPAR signaling. Although all treatments inferred qualitatively similar PPAR-α signaling, aleglitazar was inferred to have greater effects on high- and low-density lipoprotein cholesterol levels than tesaglitazar and Pio/Feno, due to a greater number of gene expression changes in pathways related to high-density and low-density lipoprotein metabolism. Distinct transcriptional and biologic signatures were also inferred for stress responses, which appeared to be less affected by aleglitazar than the comparators. In particular, Pio/Feno was inferred to increase NFE2L2 activity, a key component of the stress response pathway, while aleglitazar had no significant effect. All treatments were inferred to decrease proliferative signaling. Conclusions: Aleglitazar induces transcriptional signatures related to lipid parameters and stress responses that are unique from other dual PPAR-α/γ treatments. This may underlie observed favorable changes in lipid profiles in animal and clinical studies with aleglitazar and suggests a differentiated gene profile compared with other dual PPAR-α/γ agonist treatments

The structural basis for Z α1-antitrypsin polymerization in the liver

The serpinopathies are among a diverse set of conformational diseases that involve the aberrant self-association of proteins into ordered aggregates. α1-Antitrypsin deficiency is the archetypal serpinopathy and results from the formation and deposition of mutant forms of α1-antitrypsin as “polymer” chains in liver tissue. No detailed structural analysis has been performed of this material. Moreover, there is little information on the relevance of well-studied artificially induced polymers to these disease-associated molecules. We have isolated polymers from the liver tissue of Z α1-antitrypsin homozygotes (E342K) who have undergone transplantation, labeled them using a Fab fragment, and performed single-particle analysis of negative-stain electron micrographs. The data show structural equivalence between heat-induced and ex vivo polymers and that the intersubunit linkage is best explained by a carboxyl-terminal domain swap between molecules of α1-antitrypsin

Towards an Observational Appraisal of String Cosmology

We review the current observational status of string cosmology when confronted with experimental datasets. We begin by defining common observational parameters and discuss how they are determined for a given model. Then we review the observable footprints of several string theoretic models, discussing the significance of various potential signals. Throughout we comment on present and future prospects of finding evidence for string theory in cosmology, and on significant issues for the future.Comment: Review accepted for publication in the CQG focus issue on string cosmology. Minor clarifications and references adde

Multi-field inflation with random potentials: field dimension, feature scale and non-Gaussianity

We explore the super-horizon evolution of the two-point and three-point correlation functions of the primordial density perturbation in randomly-generated multi-field potentials. We use the Transport method to evolve perturbations and give full evolutionary histories for observables. Identifying the separate universe assumption as being analogous to a geometrical description of light rays, we give an expression for the width of the bundle, thereby allowing us to monitor evolution towards the adiabatic limit, as well as providing a useful means of understanding the behaviour in $f_NL$. Finally, viewing our random potential as a toy model of inflation in the string landscape, we build distributions for observables by evolving trajectories for a large number of realisations of the potential and comment on the prospects for testing such models. We find the distributions for observables to be insensitive to the number of fields over the range 2 to 6, but that these distributions are highly sensitive to the scale of features in the potential. Most sensitive to the scale of features is the spectral index, with more than an order of magnitude increase in the dispersion of predictions over the range of feature scales investigated. Least sensitive was the non-Gaussianity parameter $f_NL$, which was consistently small; we found no examples of realisations whose non-Gaussianity is capable of being observed by any planned experiment.Comment: 22 pages, 9 figure

Regional and cellular gene expression changes in human Huntington's disease brain

Huntington's disease (HD) pathology is well understood at a histological level but a comprehensive molecular analysis of the effect of the disease in the human brain has not previously been available. To elucidate the molecular phenotype of HD on a genome-wide scale, we compared mRNA profiles from 44 human HD brains with those from 36 unaffected controls using microarray analysis. Four brain regions were analyzed: caudate nucleus, cerebellum, prefrontal association cortex [Brodmann's area 9 (BA9)] and motor cortex [Brodmann's area 4 (BA4)]. The greatest number and magnitude of differentially expressed mRNAs were detected in the caudate nucleus, followed by motor cortex, then cerebellum. Thus, the molecular phenotype of HD generally parallels established neuropathology. Surprisingly, no mRNA changes were detected in prefrontal association cortex, thereby revealing subtleties of pathology not previously disclosed by histological methods. To establish that the observed changes were not simply the result of cell loss, we examined mRNA levels in laser-capture microdissected neurons from Grade 1 HD caudate compared to control. These analyses confirmed changes in expression seen in tissue homogenates; we thus conclude that mRNA changes are not attributable to cell loss alone. These data from bona fide HD brains comprise an important reference for hypotheses related to HD and other neurodegenerative disease