Solid phase synthesis of peptides and proteins

A strategy for the total chemical synthesis and purification of proteins has been investigated and applied to the 85 residue methylated DNA binding domain (MBD) from the chromosomal protein MeCP2, the 66 residue Restriction Alleviation (Ral) protein from bacteriophage λ, and the 76 residue ß-chemokine Monocyte Chemotactic protein (MCP-1). The hydrophobicity of the Nᵃ protecting group tetrabenzo[a, c ,g, i]fluorenyl- 17- methoxycarbonyl (Tbfmoc) has been exploited to simplify the rapid purification of the 85 amino acid MBD protein by Hplc. Initial structural studies on the synthetic protein are also reported. In addition a comparative study of semi -permanent, temporary and enzyme cleavable thiol protection has resulted in the extension of this Tbfmoc methodology to the synthesis of cysteine containing proteins such as Ral and MCP -1.A general route to C- terminal α- hydroxyglycine extended peptides via Fmoc/t-Bu based solid phase peptide synthesis is also described. Such peptides are the biosynthetic precursors of peptide amides in which the C-terminal carboxamide functionality is required for biological activity in a number of important hormones

Trajectory optimization for high-altitude long endurance UAV maritime radar surveillance

For an unmanned aerial vehicle (UAV) carrying out a maritime radar surveillance mission, there is a tradeoff between maximizing information obtained from the search area and minimizing fuel consumption. This paper presents an approach for the optimization of a UAV's trajectory for maritime radar wide area persistent surveillance to simultaneously minimize fuel consumption, maximize mean probability of detection, and minimize mean revisit time. Quintic polynomials are used to generate UAV trajectories due to their ability to provide complete and complex solutions while requiring few inputs. Furthermore, the UAV dynamics and surveillance mission requirements are used to ensure a trajectory is realistic and mission compatible. A wide area search radar model is used within this paper in conjunction with a discretized grid in order to determine the search area's mean probability of detection and mean revisit time. The trajectory generation method is then used in conjunction with a multi-objective particle swarm optimization (MOPSO) algorithm to obtain a global optimum in terms of path, airspeed (and thus time), and altitude. The performance of the approach is then tested over two common maritime surveillance scenarios and compared to an industry recommended baseline

Computational modeling of the effects of auditory nerve dysmyelination

Our previous study showed that exposure to loud sound leading to hearing loss elongated the auditory nerve (AN) nodes of Ranvier and triggered notable morphological changes at paranodes and juxtaparanodes. Here we used computational modeling to examine how theoretical redistribution of voltage gated Na+, Kv3.1, and Kv1.1 channels along the AN may be responsible for the alterations of conduction property following acoustic over-exposure. Our modeling study infers that changes related to Na+ channel density (rather than the redistribution of voltage gated Na+, Kv3.1, and Kv1.1 channels) is the likely cause of the decreased conduction velocity and the conduction block observed after acoustic overexposure (AOE)

Response article to commentary on our article titled ‘Volvulus of the gastrointestinal tract’

Peer reviewe

Modelling the effect of the El Nino-Southern Oscillation on extreme spatial temperature events over Australia

When assessing the risk posed by high temperatures, it is necessary to consider not only the temperature at separate sites but also how many sites are expected to be hot at the same time. Hot events that cover a large area have the potential to put a great strain on health services and cause devastation to agriculture, leading to high death tolls and much economic damage. South-eastern Australia experienced a severe heatwave in early 2009; 374 people died in the state of Victoria and Melbourne recorded its highest temperature since records began in 1859 (Nairn and Fawcett, 2013). One area of particular interest in climate science is the effect of large scale climatic phenomena, such as the El Nino-Southern Oscillation (ENSO), on extreme temperatures. Here, we develop a framework based upon extreme value theory to estimate the effect of ENSO on extreme temperatures across Australia. This approach permits us to estimate the change in temperatures with ENSO at important sites, such as Melbourne, and also whether we are more likely to observe hot temperatures over a larger spatial extent during a particular phase of ENSO. To this end, we design a set of measures that can be used to effectively summarise many important spatial aspects of an extreme temperature event. These measures are estimated using our extreme value framework and we validate whether we can accurately replicate the 2009 Australian heatwave, before using the model to estimate the probability of having a more severe event than has been observed

Characterising the changing behaviour of heatwaves with climate change

Understanding the impact of future heatwaves and the development of effective adaptation strategies requires knowledge of both the changes in heatwave temperatures and their durations. We develop a framework, utilising extreme value theory, which allows for the effect of a covariate on both the marginal quantiles and the temporal dependence structure of daily maximum temperatures enabling the changes in heatwave temperatures (marginal effects) to be identified separately from duration changes (dependence effects). To characterise future heatwave changes we use global mean temperature anomalies as a covariate to provide the metric for climate change. Future daily maximum temperatures and global mean temperature changes are provided by 13 general circulation models (GCMs) from the CMIP5 archive forced with predicted future emissions of radiative forcing agents from the RCP8.5 scenario. For Orleans, central France, we find that for all GCMs temporal dependence is unaffected by greenhouse gas induced climate change indicating that durations of heatwaves that exceed time varying high thresholds (i.e., the 1 year level) will not change in the future. However, all GCMs project significant changes in the temperature margins with events similar to the 2003 European heatwave increasing by 1.3C to 2.7C and (8.0C to 18.7C) for a 1C (5C) increase in global temperature. Collectively our results indicate there could be a significant increase in heatwave risk as the world warms with heatwaves increasing in temperature significantly faster than the global mean and local average temperatures