Self-potential signatures associated with an injection experiment at an in situ biological permeable reactive barrier

Strategies available to evaluate the performance of in situ permeable reactive barriers are currently not well developed and often rely on fluid and media sampling directly from the permeable reactive barrier (PRB). Here, we investigate the utility of the self-potential (SP) method as a technique to monitor in situ PRB performance. Our field study was conducted at in situ biological PRB in Portadown, Northern Ireland, UK, which was emplaced to assist in the remediation of groundwater contamination (e.g., hydrocarbons, ammonia) that resulted from the operations and waste disposal practices of a former gasworks. Borehole SP measurements were collected during the injection of contaminant groundwater slugs in an attempt to monitor/detect the response of the microbial activity associated with the breakdown of the added contaminants into the PRB. In addition, an uncontaminated groundwater slug was injected into a different portion of the PRB as a ‘control’ and SP measurements were collected for comparison to the SP response of the contaminant slugs. The results of the SP signals due to the contaminant injections show that the magnitude of the response was relatively small (<10 mV) yet showed a consistent decrease during both contaminant injections. The net decrease in SP recorded during the contaminant injections slowly rebounded to near background values through ~44 hours post-injection. The SP response during the uncontaminated injection showed a slight, albeit negligible (within the margin of error), 1 mV increase in the measured SP signals, in contrast to the contaminant injections. The results of the SP signals recorded from the uncontaminated groundwater injection also persisted through a period of ~47 hours after injection but show a net increase in SP relative to pre-injection values. Based on the difference in SP response between the contaminated and uncontaminated injections, we suggest that the responses are likely to be the result of differences in the chemistry of the injection types (contaminated versus uncontaminated) and in situ groundwater. We argue that the SP signals associated with the contaminated injections are dominated by diffusion (electrochemical) potential, possibly enhanced by a microbial effect. While the results of our investigation show a consistent SP response associated with the contaminant injections that is dominated by diffusional effects, further studies are required in order to better understand the effect of microbial activity on SP signals and the potential utility for the SP method to detect/monitor changes that may be indicative of biological PRB performance.

Evaluating signatures of glacial refugia for North Atlantic benthic marine taxa

A goal of phylogeography is to relate patterns of genetic differentiation to potential historical geographic isolating events. Quaternary glaciations, particularly the one culminating in the Last Glacial Maximum ~21 ka (thousands of years ago), greatly affected the distributions and population sizes of temperate marine species as their ranges retreated southward to escape ice sheets. Traditional genetic models of glacial refugia and routes of recolonization include these predictions: low genetic diversity in formerly glaciated areas, with a small number of alleles/haplotypes dominating disproportionately large areas, and high diversity including "private" alleles in glacial refugia. In the Northern Hemisphere, low diversity in the north and high diversity in the south are expected. This simple model does not account for the possibility of populations surviving in relatively small northern periglacial refugia. If these periglacial populations experienced extreme bottlenecks, they could have the low genetic diversity expected in recolonized areas with no refugia, but should have more endemic diversity (private alleles) than recently recolonized areas. This review examines evidence of putative glacial refugia for eight benthic marine taxa in the temperate North Atlantic. All data sets were reanalyzed to allow direct comparisons between geographic patterns of genetic diversity and distribution of particular clades and haplotypes including private alleles. We contend that for marine organisms the genetic signatures of northern periglacial and southern refugia can be distinguished from one another. There is evidence for several periglacial refugia in northern latitudes, giving credence to recent climatic reconstructions with less extensive glaciation.

Signatures of delayed detonation, asymmetry, and electron capture in the mid-infrared spectra of supernovae 2003hv and 2005df

We present mid-infrared (5.2-15.2 mu m) spectra of the Type Ia supernovae (SNe Ia) 2003hv and 2005df observed with the Spitzer Space Telescope. These are the first observed mid-infrared spectra of thermonuclear supernovae, and show strong emission from fine-structure lines of Ni, Co, S, and Ar. The detection of Ni emission in SN 2005df 135 days after the explosion provides direct observational evidence of high-density nuclear burning forming a significant amount of stable Ni in a SN Ia. The SN 2005df Ar lines also exhibit a two-pronged emission profile, implying that the Ar emission deviates significantly from spherical symmetry. The spectrum of SN 2003hv also shows signs of asymmetry, exhibiting blueshifted [Co (III)], which matches the blueshift of [Fe (II)] lines in nearly coeval near-infrared spectra. Finally, local thermodynamic equilibrium abundance estimates for the yield of radioactive Ni-56 give M-56Ni approximate to 0.5 M-circle dot, for SN 2003hv, but only M-56Ni approximate to 0.13-0.22 M-circle dot for the apparently subluminous SN 2005df, supporting the notion that the luminosity of SNe Ia is primarily a function of the radioactive 56Ni yield. The observed emission-line profiles in the SN 2005df spectrum indicate a chemically stratified ejecta structure, which matches the predictions of delayed detonation (DD) models, but is entirely incompatible with current three-dimensional deflagration models. Furthermore, the degree that this layering persists to the innermost regions of the supernova is difficult to explain even in a DD scenario, where the innermost ejecta are still the product of deflagration burning. Thus, while these results are roughly consistent with a delayed detonation, it is clear that a key piece of physics is still missing from our understanding of the earliest phases of SN Ia explosions.

The Unification of Asymmetry Signatures of Type Ia Supernovae

We present a compilation of the geometry measures acquired using optical and IR spectroscopy and optical spectropolarimetry to probe the explosion geometry of Type Ia supernovae (SNe Ia). Polarization measurements are sensitive to asymmetries in the plane of the sky, whereas line profiles in nebular phase spectra are expected to trace asymmetries perpendicular to the plane of the sky. The combination of these two measures can overcome their respective projection effects, completely probing the structures of these events. For nine normal SNe Ia, we find that the polarization of Si II ?6355 at 5 days before maximum (p Si II ) is well correlated with its velocity evolution (\dot{v}_Si II), implying that \dot{v}_Si II is predominantly due to the asymmetry of the SNe. We find only a weak correlation between the polarization of Si II and the reported velocities (v neb) for peak emission of optical Fe II and Ni II lines in nebular spectra. Our sample is biased, with polarization measurements being only available for normal SNe that subsequently exhibited positive (i.e., redshifted) v neb. In unison these indicators are consistent with an explosion in which the outer layers are dominated by a spherical oxygen layer, mixed with an asymmetric distribution of intermediate-mass elements. The combination of spectroscopic and spectropolarimetric indicators suggests a single geometric configuration for normal SNe Ia, with some of the diversity of observed properties arising from orientation effects.

RADIATIVE SIGNATURES OF RELATIVISTIC SHOCKS

Particle-in-cell simulations of relativistic, weakly magnetized collisionless shocks show that particles can gain energy by repeatedly crossing the shock front. This requires scattering off self-generated small length-scale magnetic fluctuations. The radiative signature of this first-order Fermi acceleration mechanism is important for models of both the prompt and afterglow emission in gamma-ray bursts and depends on the strength parameter a = lambda e/delta B/mc(2) of the fluctuations (lambda is the length scale and vertical bar delta B vertical bar is the magnitude of the fluctuations). For electrons (and positrons), acceleration saturates when the radiative losses produced by the scattering cannot be compensated by the energy gained on crossing the shock. We show that this sets an upper limit on both the electron Lorentz factor gamma <10(6) (n/1 cm(-3))(-1/6)(-1/6) and on the energy of the photons radiated during the scattering process h omega(max) <40Max(a, 1)(n/1 cm(-3))(1/6)(-1/6) eV, where n is the number density of the plasma and (gamma) over bar is the thermal Lorentz factor of the downstream plasma, provided a <a(crit) similar to 10(6). This rules out "jitter" radiation on self-excited fluctuations with a <I as a source of gamma rays, although high-energy photons might still be produced when the jitter photons are upscattered in an analog of the synchrotron self-Compton process. In fluctuations with a > 1, radiation is generated by the standard synchrotron mechanism, and the maximum photon energy rises linearly with a, until saturating at 70 MeV, when a = a(crit).

Metabolic signatures of human Alzheimer's disease (AD): H-1 NMR analysis of the polar metabolome of post-mortem brain tissue

Brain tissue from so-called Alzheimer's disease (AD) mouse models has previously been examined using H-1 NMR-metabolomics, but comparable information concerning human AD is negligible. Since no animal model recapitulates all the features of human AD we undertook the first H-1 NMR-metabolomics investigation of human AD brain tissue. Human post-mortem tissue from 15 AD subjects and 15 age-matched controls was prepared for analysis through a series of lyophilised, milling, extraction and randomisation steps and samples were analysed using H-1 NMR. Using partial least squares discriminant analysis, a model was built using data obtained from brain extracts. Analysis of brain extracts led to the elucidation of 24 metabolites. Significant elevations in brain alanine (15.4 %) and taurine (18.9 %) were observed in AD patients (p ≤ 0.05). Pathway topology analysis implicated either dysregulation of taurine and hypotaurine metabolism or alanine, aspartate and glutamate metabolism. Furthermore, screening of metabolites for AD biomarkers demonstrated that individual metabolites weakly discriminated cases of AD [receiver operating characteristic (ROC) AUC <0.67; p < 0.05]. However, paired metabolites ratios (e.g. alanine/carnitine) were more powerful discriminating tools (ROC AUC = 0.76; p < 0.01). This study further demonstrates the potential of metabolomics for elucidating the underlying biochemistry and to help identify AD in patients attending the memory clinic

Integrative analysis of chemo-transcriptomic profiles for drug-feature specific gene expression signatures

One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.