Coulomb Phase Gluon Scattering at Strong Coupling

We calculate corrections to gluon scattering amplitudes in a Coulomb phase using gauge/string duality. The Coulomb phase considered is a maximal rank breaking of $SU(n_1+n_2)\to SU(n_1)\times SU(n_2) \times U(1)$. This problem therefore has 3 scales involved: 1) the scale of the massive fields $M_W$ arising from the spontaneous breaking of the gauge group; 2) The scale of the scattering, characterized by the Mandelstam variables $s,t,u$; 3) The IR regulator $m_{IR}$. We find corrections in the hard scattering limit $|s|,|t|,|u|\gg m_{IR}^2 \gg M_W^2$, and also find below threshold corrections with $M_W^2 \gg |s|,|t|,|u|$. We find that the corrections in the second case are finite, and so are IR regulator independent.Comment: 17+17 pages, 3 figure

Computational Design of Metal Ion Sequestering Agents

Organic ligands that exhibit a high degree of metal ion recognition are essential precursors for developing separation processes and sensors for metal ions. Since the beginning of the nuclear era, much research has focused on discovering ligands that target specific radionuclides. Members of the Group 1A and 2A cations (e.g., Cs, Sr, Ra) and the f-block metals (actinides and lanthanides) are of primary concern to DOE. Although there has been some success in identifying ligand architectures that exhibit a degree of metal ion recognition, the ability to control binding affinity and selectivity remains a significant challenge. The traditional approach for discovering such ligands has involved lengthy programs of organic synthesis and testing that, in the absence of reliable methods for screening compounds before synthesis, have resulted in much wasted research effort. This project seeks to enhance and strengthen the traditional approach through computer-aided design of new and improved host molecules. Accurate electronic structure calculations are coupled with experimental data to provide fundamental information about ligand structure and the nature of metal-donor group interactions (design criteria). This fundamental information then is used in a molecular mechanics model (MM3) that helps us rapidly screen proposed ligand architectures and select the best members from a set of potential candidates. By using combinatorial methods, molecule building software has been developed that generates large numbers of candidate architectures for a given set of donor groups. The specific objectives of this project are: to further understand the structural and energetic aspects of individual donor group-metal ion interactions and incorporate this information within the framework of MM3; to further develop and evaluate approaches for correlating ligand structure with reactivity toward metal ions, in other words, screening capability; to use molecule structure building software to generate large numbers of candidate ligand architectures for given sets of donor groups; to screen candidates and identify ligand architectures that will exhibit enhanced metal ion recognition. These new capabilities are being applied to ligand systems identified under other DOE sponsored projects where studies have suggested that modifying existing architectures will lead to dramatic enhancements in metal ion binding affinity and selectivity. With this in mind, we are collaborating with Professors R. T. Paine (University of New Mexico) and K. N. Raymond (University of California, Berkeley) and Drs. B. A. Moyer and G. M. Brown (Oak Ridge National Laboratory) to obtain experimental validation of the predicted new ligand structures. 3 Successful completion of this study will yield molecular-level insight into the role that ligand architecture plays in controlling metal ion complexation and will provide a computational approach to ligand design

Computational Design of Metal Ion Sequestering Agents

Organic ligands that exhibit a high degree of metal ion recognition are essential precursors for developing separation processes and sensors for metal ions. Since the beginning of the nuclear era, much research has focused on discovering ligands that target specific radionuclides. Members of the Group 1A and 2A cations (e.g., Cs, Sr, Ra) and the f-block metals (actinides and lanthanides) are of primary concern to the U.S. Department of Energy (DOE). Although there has been some success in identifying ligand architectures that exhibit a degree of metal ion recognition, the ability to control binding affinity and selectivity remains a significant challenge. The traditional approach for discovering such ligands has involved lengthy programs of organic synthesis and testing that, in the absence of reliable methods for screening compounds before synthesis, have resulted in much wasted research effort. This project seeks to enhance and strengthen the traditional approach through computer-aided design of new and improved host molecules. Accurate electronic structure calculations are coupled with experimental data to provide fundamental information about ligand structure and the nature of metal-donor group interactions (design criteria). This fundamental information then is used in a molecular mechanics model (MM3) that helps us rapidly screen proposed ligand architectures and select the best members from a set of potential candidates. By using combinatorial methods, molecule building software has been developed that generates large numbers of candidate architectures for a given set of donor groups. The specific objectives of this project are as follows: (1) Further understand the structural and energetic aspects of individual donor group- metal ion interactions and incorporate this information within the framework of MM3. (2) Further develop and evaluate approaches for correlating ligand structure with reactivity toward metal ions, in other words, screening capability. (3) Use molecule structure building software to generate large numbers of candidate ligand architectures for given sets of donor groups. (4) Screen candidates and identify ligand architectures that will exhibit enhanced metal ion recognition. These new capabilities are being applied to ligand systems identified under other DOE sponsored projects in which studies have suggested that modifying existing architectures will lead to dramatic enhancements in metal ion binding affinity and selectivity. With this in mind, we are collaborating with researchers at the University of New Mexico, University of California at Berkeley, University of Oregon, and Oak Ridge National Laboratory to obtain experimental validation of the predicted new ligand structures. Successful completion of this study will yield molecular-level insight into the role that ligand architecture plays in controlling metal ion complexation and will provide a computational approach to ligand design

Interstellar Object Accessibility and Mission Design

Interstellar objects (ISOs) are fascinating and under-explored celestial objects, providing physical laboratories to understand the formation of our solar system and probe the composition and properties of material formed in exoplanetary systems. This paper will discuss the accessibility of and mission design to ISOs with varying characteristics, including a discussion of state covariance estimation over the course of a cruise, handoffs from traditional navigation approaches to novel autonomous navigation for fast flyby regimes, and overall recommendations about preparing for the future in situ exploration of these targets. The lessons learned also apply to the fast flyby of other small bodies including long-period comets and potentially hazardous asteroids, which also require a tactical response with similar characteristicsComment: Accepted at IEEE Aerospace Conferenc

Characterizing Transition Temperature Gas in the Galactic Corona

We present a study of the properties of the transition temperature (T~10^5 K) gas in the Milky Way corona, based on measurements of OVI, NV, CIV, SiIV and FeIII absorption lines seen in the far ultraviolet spectra of 58 sightlines to extragalactic targets, obtained with Far-Ultraviolet Spectroscopic Explorer (FUSE) and Space Telescope Imaging Spectrograph. In many sightlines the Galactic absorption profiles show multiple components, which are analyzed separately. We find that the highly-ionized atoms are distributed irregularly in a layer with a scaleheight of about 3 kpc, which rotates along with the gas in the disk, without an obvious gradient in the rotation velocity away from the Galactic plane. Within this layer the gas has randomly oriented velocities with a dispersion of 40-60 km/s. On average the integrated column densities are log N(OVI)=14.3, log N(NV)=13.5, log N(CIV)=14.2, log N(SiIV)=13.6 and log N(FeIII)=14.2, with a dispersion of just 0.2 dex in each case. In sightlines around the Galactic Center and Galactic North Pole all column densities are enhanced by a factor ~2, while at intermediate latitudes in the southern sky there is a deficit in N(OVI) of about a factor 2, but no deficit for the other ions. We compare the column densities and ionic ratios to a series of theoretical predictions: collisional ionization equilibrium, shock ionization, conductive interfaces, turbulent mixing, thick disk supernovae, static non-equilibrium ionization (NIE) radiative cooling and an NIE radiative cooling model in which the gas flows through the cooling zone. None of these models can fully reproduce the data, but it is clear that non-equilibrium ionization radiative cooling is important in generating the transition temperature gas.Comment: 99 pages, 11 figures, with appendix on Cooling Flow model; only a sample of 5 subfigures of figure 2 included - full set of 69 available through Ap

Early-life adversity selectively impairs α2-GABAA receptor expression in the mouse nucleus accumbens and influences the behavioral effects of cocaine

Haplotypes of the Gabra2 gene encoding the α2 subunit of the GABAA receptor (GABAAR) are associated with drug abuse, suggesting that α2-GABAARs may play an important role in the circuitry underlying drug misuse. The genetic association of Gabra2 haplotypes with cocaine addiction appears to be evident primarily in individuals who had experienced childhood trauma. Given this association of childhood trauma, cocaine abuse and the Gabra2 haplotypes, we have explored in a mouse model of early life adversity (ELA) whether such events influence the behavioral effects of cocaine and if, as suggested by the human studies, α2-GABAARs in the nucleus accumbens (NAc) are involved in these perturbed behaviors. In adult mice prior ELA caused a selective decrease of accumbal α2-subunit mRNA, resulting in a selective decrease in the number and size of the α2-subunit (but not the α1-subunit) immunoreactive clusters in NAc core medium spiny neurons (MSNs). Functionally, in adult MSNs ELA decreased the amplitude and frequency of GABAAR-mediated miniature inhibitory postsynaptic currents (mIPSCs), a profile similar to that of α2 "knock-out" (α2-/-) mice. Behaviorally, adult male ELA and α2-/- mice exhibited an enhanced locomotor response to acute cocaine and blunted sensitization upon repeated cocaine administration, when compared to their appropriate controls. Collectively, these findings reveal a neurobiological mechanism which may relate to the clinical observation that early trauma increases the risk for substance abuse disorder (SAD) in individuals harbouring haplotypic variations in the Gabra2 gene.</p

Characterization of cleavage events in the multifunctional cilium adhesin Mhp684 (P146) reveals a mechanism by which mycoplasma hyopneumoniae regulates surface topography

Mycoplasma hyopneumoniae causes enormous economic losses to swine production worldwide by colonizing the ciliated epithelium in the porcine respiratory tract, resulting in widespread damage to the mucociliary escalator, prolonged inflammation, reduced weight gain, and secondary infections. Protein Mhp684 (P146) comprises 1,317 amino acids, and while the N-terminal 400 residues display significant sequence identity to the archetype cilium adhesin P97, the remainder of the molecule is novel and displays unusual motifs. Proteome analysis shows that P146 preprotein is endogenously cleaved into three major fragments identified here as P50P146, P40P146, and P85P146 that reside on the cell surface. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) identified a semitryptic peptide that delineated a major cleavage site in Mhp684. Cleavage occurred at the phenylalanine residue within sequence 672ATEF2QQ677, consistent with a cleavage motif resembling S/T-X-F2XD/E recently identified in Mhp683 and other P97/P102 family members. Biotinylated surface proteins recovered by avidin chromatography and separated by two-dimensional gel electrophoresis (2-D GE) showed that more-extensive endoproteolytic cleavage of P146 occurs. Recombinant fragments F1P146-F3P146 that mimic P50P146, P40P146, and P85P146 were constructed and shown to bind porcine epithelial cilia and biotinylated heparin with physiologically relevant affinity. Recombinant versions of F3P146 generated from M. hyopneumoniae strain J and 232 sequences strongly bind porcine plasminogen, and the removal of their respective C-terminal lysine and arginine residues significantly reduces this interaction. These data reveal that P146 is an extensively processed, multifunctional adhesin of M. hyopneumoniae. Extensive cleavage coupled with variable cleavage efficiency provides a mechanism by which M. hyopneumoniae regulates protein topography

Gravitational field and equations of motion of spinning compact binaries to 2.5 post-Newtonian order

We derive spin-orbit coupling effects on the gravitational field and equations of motion of compact binaries in the 2.5 post-Newtonian approximation to general relativity, one PN order beyond where spin effects first appear. Our method is based on that of Blanchet, Faye, and Ponsot, who use a post-Newtonian metric valid for general (continuous) fluids and represent pointlike compact objects with a delta-function stress-energy tensor, regularizing divergent terms by taking the Hadamard finite part. To obtain post-Newtonian spin effects, we use a different delta-function stress-energy tensor introduced by Bailey and Israel. In a future paper we will use the 2.5PN equations of motion for spinning bodies to derive the gravitational-wave luminosity and phase evolution of binary inspirals, which will be useful in constructing matched filters for signal analysis. The gravitational field derived here may help in posing initial data for numerical evolutions of binary black hole mergers.Comment: 18 pages, no figur

Characterization of subsurface media from locations up- and down-gradient of a uranium-contaminated aquifer.

The processing of sediment to accurately characterize the spatially-resolved depth profiles of geophysical and geochemical properties along with signatures of microbial density and activity remains a challenge especially in complex contaminated areas. This study processed cores from two sediment boreholes from background and contaminated core sediments and surrounding groundwater. Fresh core sediments were compared by depth to capture the changes in sediment structure, sediment minerals, biomass, and pore water geochemistry in terms of major and trace elements including pollutants, cations, anions, and organic acids. Soil porewater samples were matched to groundwater level, flow rate, and preferential flows and compared to homogenized groundwater-only samples from neighboring monitoring wells. Groundwater analysis of nearby wells only revealed high sulfate and nitrate concentrations while the same analysis using sediment pore water samples with depth was able to suggest areas high in sulfate- and nitrate-reducing bacteria based on their decreased concentration and production of reduced by-products that could not be seen in the groundwater samples. Positive correlations among porewater content, total organic carbon, trace metals and clay minerals revealed a more complicated relationship among contaminant, sediment texture, groundwater table, and biomass. The fluctuating capillary interface had high concentrations of Fe and Mn-oxides combined with trace elements including U, Th, Sr, Ba, Cu, and Co. This suggests the mobility of potentially hazardous elements, sediment structure, and biogeochemical factors are all linked together to impact microbial communities, emphasizing that solid interfaces play an important role in determining the abundance of bacteria in the sediments

A graphical model approach for inferring large-scale networks integrating gene expression and genetic polymorphism

<p>Abstract</p> <p>Background</p> <p>Graphical models (e.g., Bayesian networks) have been used frequently to describe complex interaction patterns and dependent structures among genes and other phenotypes. Estimation of such networks has been a challenging problem when the genes considered greatly outnumber the samples, and the situation is exacerbated when one wishes to consider the impact of polymorphisms (SNPs) in genes.</p> <p>Results</p> <p>Here we describe a multistep approach to infer a gene-SNP network from gene expression and genotyped SNP data. Our approach is based on 1) construction of a graphical Gaussian model (GGM) based on small sample estimation of partial correlation and false-discovery rate multiple testing; 2) extraction of a subnetwork of genes directly linked to a target candidate gene of interest; 3) identification of cis-acting regulatory variants for the genes composing the subnetwork; and 4) evaluating the identified cis-acting variants for trans-acting regulatory effects of the target candidate gene. This approach identifies significant gene-gene and gene-SNP associations not solely on the basis of gene co-expression but rather through whole-network modeling. We demonstrate the method by building two complex gene-SNP networks around Interferon Receptor 12B2 (IL12RB2) and Interleukin 1B (IL1B), two biologic candidates in asthma pathogenesis, using 534,290 genotyped variants and gene expression data on 22,177 genes from total RNA derived from peripheral blood CD4+ lymphocytes from 154 asthmatics.</p> <p>Conclusion</p> <p>Our results suggest that graphical models based on integrative genomic data are computationally efficient, work well with small samples, and can describe complex interactions among genes and polymorphisms that could not be identified by pair-wise association testing.</p