Quantification of Polycyclic Aromatic Hydrocarbons in Avian Dried Blood Spots by Ultra-performance Liquid Chromatography with Simple Liquid Extraction and Phospholipid Solid-phase Extraction Preparation

Here, a simple, reliable method for the quantification of the 16 EPA priority polycyclic aromatic hydrocarbons in dried blood spots is outlined using liquid extraction and phospholipid solid-phase sample cleanup coupled with analysis by ultra-performance liquid chromatography with ultraviolet–visible detection. Whole blood spotted on Whatman FTA cards was efficiently quantified by extraction into acidified methanol and passed through a phospholipid solid-phase extraction well plate before injection into a liquid chromatography under reverse-phase conditions. The analyte recoveries in quality control samples ranged from 63.4 to 104.1%, with relative standard deviations from 0.48 to 2.04%. These figures of merit are comparable with measurements in whole blood or serum using similar techniques. The method detection limits were from 45.0?ng·g^?1 for benzo[g,h,i]perylene to 118.7?ng·g^?1 for chrysene, with matrix spike recoveries from 64.3 to 99.4%, demonstrating acceptable sensitivity and low matrix interference. With a simple liquid extraction approach and short 16-min liquid chromatography, the dried blood spots were effectively and rapidly analyzed.     

High resolution Dopplerimetry of correlated angular and quantum state-resolved CO(2) scattering dynamics at the gas-liquid interface

Full three dimensional (3D) translational distributions for quantum state-resolved scattering dynamics at the gas-liquid interface are presented for experimental and theoretical studies of CO(2) + perfluorinated surfaces. Experimentally, high resolution absorption profiles are measured as a function of incident (θ(inc)) and scattering (θ(scat)) angles for CO(2) that has been scattered from a 300 K perfluorinated polyether surface (PFPE) with an incident energy of E(inc) = 10.6(8) kcal mol(-1). Line shape analysis of the absorption profiles reveals non-equilibrium dynamics that are characterized by trapping-desorption (TD) and impulsive scattering (IS) components, with each channel simply characterized by an effective "temperature" that compares very well with previous results from rotational state analysis [Perkins and Nesbitt, J. Phys. Chem. A, 2008, 112, 9324]. From a theoretical perspective, molecular dynamics (MD) simulations of CO(2) + fluorinated self-assembled monolayer surface (F-SAMs) yield translational probability distributions that are also compared with experimental results. Trajectories are parsed by θ(scat) and J, with the results rigorously corrected by flux-to-density transformation and providing comparisons in near quantitative agreement with experiment. 3D flux and velocity distributions obtained from MD simulations are also presented to illustrate the role of in- and out-of-plane scattering.     

In silico identification of conserved microRNAs and their target transcripts from expressed sequence tags of three earthworm species

MicroRNAs are a recently identified class of small regulatory RNAs that target more than 30% protein-coding genes. Elevating evidence shows that miRNAs play a critical role in many biological processes, including developmental timing, tissue differentiation, and response to chemical exposure. In this study, we applied a computational approach to analyze expressed sequence tags, and identified 32 miRNAs belonging to 22 miRNA families, in three earthworm species Eisenia fetida, Eisenia andrei, and Lumbricus rubellus. These newly identified earthworm miRNAs possess a difference of 2-4 nucleotides from their homologous counterparts in Caenorhabditis elegans. They also share similar features with other known animal miRNAs, for instance, the nucleotide U being dominant in both mature and pre-miRNA sequences, particularly in the first position of mature miRNA sequences at the 5' end. The newly identified earthworm miRNAs putatively regulate mRNA genes that are involved in many important biological processes and pathways related to development, growth, locomotion, and reproduction as well as response to stresses, particularly oxidative stress. Future efforts will focus on experimental validation of their presence and target mRNA genes to further elucidate their biological functions in earthworms.     

Brownian motion on the Sierpinski gasket

Summary We construct a Brownian motion taking values in the Sierpinski gasket, a fractal subset of ², and study its properties. This is a diffusion process characterized by local isotropy and homogeneity properties. We show, for example, that the process has a continuous symmetric transition density, p _t(x,y), with respect to an appropriate Hausdorff measure and obtain estimates on p _t(x,y).Research partially supported by an NSERC of Canada operating grantResearch partially supported by an SERC (UK) Visiting Fellowship     

Chaotic Dynamics in an Electronic Model of a Genetic Network

We consider dynamics in a class of piecewise-linear ordinary differential equations and in an electronic circuit that model genetic networks. In these models, gene activity varies continuously in time. However, as in Boolean or discrete-time switching networks, gene activity is driven high or low based only on whether the activities of the regulating genes are high or low (i.e., above or below certain thresholds). Depending on the “regulatory logic”, these models can exhibit simple dynamics, like stable fixed points or oscillation, or chaotic dynamics. The observed qualitative and quantitative differences between the dynamics in the idealized equations and the dynamics in the electronic circuit lead us to focus attention on the analysis of the dynamics as a function of parameter values. We propose new techniques for solving the inverse problem – the problem of inferring the regulatory logic and parameters from time series data. We also give new symbolic and statistical methods for characterizing dynamics in these networks.     

Super-Tree Random Measures

We use supercritical branching processes with random walk steps of geometrically decreasing size to construct random measures. Special cases of our construction give close relatives of the super-(spherically symmetric stable) processes. However, other cases can produce measures with very smooth densities in any dimension.     

Cloud dispersion models

A new technique has been developed to compute mean and fluctuating concentrations in complex turbulent flows. An initial distribution of material is discretised into any small clouds which are advected by a combination of the mean flow and large scale turbulence. The turbulence can be simulated either by Kinematic Simulation or by a stochastic model for the motion of each cloud centroid. The clouds also diffuse relative to their centroids; the statistics for this are obtained from a separate calculation of the growth of individual clouds in small scale turbulence, generated by Kinematic Simulation. The ensemble of discrete clouds is periodically rediscretised, to limit the size of the small clouds and prevent overlapping. The model is illustrated with simulations of dispersion in uniform flow and in a coastal flow, and the results are compared with analytic, steady state solutions where available.     

Assessing the role of chemical components in cellular responses to atmospheric particle matter (PM) through chemical fractionation of PM extracts

In order to further our understanding of the influence of chemical components and ultimately specific sources of atmospheric particulate matter (PM) on pro-inflammatory and other adverse cellular responses, we promulgate and apply a suite of chemical fractionation tools to aqueous aerosol extracts of PM samples for analysis in toxicity assays. We illustrate the approach with a study that used water extracts of quasi-ultrafine PM (PM_0.25) collected in the Los Angeles Basin. Filtered PM extracts were fractionated using Chelex, a weak anion exchanger diethylaminoethyl (DEAE), a strong anion exchanger (SAX), and a hydrophobic C18 resin, as well as by desferrioxamine (DFO) complexation that binds iron. The fractionated extracts were then analyzed using high-resolution sector field inductively coupled plasma mass spectrometry (SF-ICPMS) to determine elemental composition. Cellular responses to the fractionated extracts were probed in an in vitro rat alveolar macrophages model with measurement of reactive oxygen species (ROS) production and the cytokine tumor necrosis factor-α (TNF-α). The DFO treatment that chelates iron was very effective at reducing the cellular ROS activity but had only a small impact on the TNF-α production. In contrast, the hydrophobic C18 resin treatment had a small impact on the cellular ROS activity but significantly reduced the TNF-α production. The use of statistical methods to integrate the results across all treatments led to the conclusion that sufficient iron must be present to participate in the chemistry needed for ROS activity, but the amount of ROS activity is not proportional to the iron solution concentration. ROS activity was found to be most related to cationic mono- and divalent metals (i.e., Mn and Ni) and oxyanions (i.e., Mo and V). Although the TNF-α production was not significantly affected by the chelexation of iron, it was greatly impacted by the removal of organics with the C18 resin and all other metal removal methods, suggesting that iron is not a critical pathway leading to TNF-α production, but a wide range of soluble metals and organic compounds in particulate matter play a role. Although the results are specific to the Los Angeles Basin, where the samples used in the study were collected, the method employed in the study can be widely employed to study the role of components of particulate matter in in vitro or in vivo assays.