RPE65 and the Accumulation of Retinyl Esters in Mouse Retinal Pigment Epithelium

The RPE65 protein of the retinal pigment epithelium (RPE) enables the conversion of retinyl esters to the visual pigment chromophore 11‐cis retinal. Fresh 11‐cis retinal is generated from retinyl esters following photoisomerization of the visual pigment chromophore to all‐trans during light detection. Large amounts of esters accumulate in Rpe65^?/? mice, indicating their continuous formation when 11‐cis retinal generation is blocked. We hypothesized that absence of light, by limiting the conversion of esters to 11‐cis retinal, would also result in the build‐up of retinyl esters in the RPE of wild‐type mice. We used HPLC to quantify ester levels in organic extracts of the RPE from wild‐type and Rpe65^?/? mice. Retinyl ester levels in Sv/129 wild‐type mice that were dark adapted for various intervals over a 4‐week period were similar to those in mice raised in cyclic light. In C57BL/6 mice however, which contain less Rpe65 protein, dark adaptation was accompanied by an increase in ester levels compared to cyclic light controls. Retinyl ester levels were much higher in Rpe65^?/? mice compared to wild type and kept increasing with age. The results suggest that the RPE65 role in retinyl ester homeostasis extends beyond enabling the formation of 11‐cis retinal.     

High-resolution investigation of the excited electronic states of CaSH and SrSH by laser excitation spectroscopy – ARTICLE WITHDRAWN

WITHDRAWN TO APPEAR IN SPECIAL ISSUE IN 2007     

A feasibility study of X‐ray phase‐contrast mammographic tomography at the Imaging and Medical beamline of the Australian Synchrotron

Results are presented of a recent experiment at the Imaging and Medical beamline of the Australian Synchrotron intended to contribute to the implementation of low‐dose high‐sensitivity three‐dimensional mammographic phase‐contrast imaging, initially at synchrotrons and subsequently in hospitals and medical imaging clinics. The effect of such imaging parameters as X‐ray energy, source size, detector resolution, sample‐to‐detector distance, scanning and data processing strategies in the case of propagation‐based phase‐contrast computed tomography (CT) have been tested, quantified, evaluated and optimized using a plastic phantom simulating relevant breast‐tissue characteristics. Analysis of the data collected using a Hamamatsu CMOS Flat Panel Sensor, with a pixel size of 100 µm, revealed the presence of propagation‐based phase contrast and demonstrated significant improvement of the quality of phase‐contrast CT imaging compared with conventional (absorption‐based) CT, at medically acceptable radiation doses.     

Power-Spectral density estimate of the Bloor-Gerrard instability in flows around circular cylinders

There have been differences in the literature concerning the power law relationship between the Bloor-Gerrard instability frequency of the separated shear layer from the circular cylinder, the Bénard-von Kármán vortex shedding frequency and the Reynolds number. Most previous experiments have shown a significant degree of scatter in the measurement of the development of the shear layer vortices. Shear layers are known to be sensitive to external influences, which can provide a by-pass transition to saturated growth, thereby camouflaging the fastest growing linear modes. Here, the spatial amplification rates of the shear layer instabilities are calculated using power-spectral density estimates, allowing the fastest growing modes rather than necessarily the largest structures to be determined. This method is found to be robust in determining the fastest growing modes, producing results consistent with the low scatter results of previous experiments.     

Fourier transform microwave spectroscopy of LiCCH, NaCCH, and KCCH: Quadrupole hyperfine interactions in alkali monoacetylides

The alkali metal monoacetylides LiCCH, NaCCH, and KCCH and their deuterium isotopologues have been investigated using Fourier transform microwave (FTMW) spectroscopy in the frequency range 5-37 GHz. The molecules were synthesized in a supersonic expansion by the reaction of metal vapor, produced by laser ablation, with acetylene or DCCD. Use of target rods of the pure metal and a DC discharge immediately following the laser interaction region were significant factors in molecule production. Multiple rotational transitions were recorded for all species, except where only the J = 1 → 0 line was accessible (Li species). Quadrupole hyperfine interactions arising from the metal nuclei were resolved in each molecule, as well as those from the deuterium nucleus in the deuterated isotopologues. From a combined analysis with previous millimeter-wave data, refined rotational constants were determined for these species, as well as ⁷Li, ²³Na, ³⁹K, and D eQq parameters. The values of the metal quadrupole coupling constants are comparable to those of the alkali halides and hydroxides, indicating a similar degree of ionic character in the metal-ligand bond.     

The Effect of Temperature on GPC for the Separation of PCBs from Transformer Oil and Subsequent Analysis by GC-MSD

Abstract

The analysis of PCBs often involves lengthy and expensive cleanup procedures to remove interferences associated with environmental sample matrices. Gel permeation chromatography (GPC) has proven to be a useful tool in removing many of these interferences from environmental samples, especially from difficult matrices such as oils, lipids and sediments. This paper describes the effect of temperature upon the GPC column in separating PCBs from transformer oil and its implication on GC-MS analysis.     

A preferential attachment model with Poisson growth for scale-free networks

We propose a scale-free network model with a tunable power-law exponent. The Poisson growth model, as we call it, is an offshoot of the celebrated model of Barabási and Albert where a network is generated iteratively from a small seed network; at each step a node is added together with a number of incident edges preferentially attached to nodes already in the network. A key feature of our model is that the number of edges added at each step is a random variable with Poisson distribution, and, unlike the Barabási–Albert model where this quantity is fixed, it can generate any network. Our model is motivated by an application in Bayesian inference implemented as Markov chain Monte Carlo to estimate a network; for this purpose, we also give a formula for the probability of a network under our model.