Comparison and characterisation of ribozyme delivery in cultured glial and neuronal cells in vivo and in vitro

Ribozymes are short strands of RNA that possess a huge potential as biological tools for studying gene expression and as therapeutic agents to down-regulate undesirable gene expression. Successful application of ribozymes requires delivery to the target site in sufficient amounts for an adequate duration. However, due to their large size and polyanionic character ribozymes are not amenable to transport across biological membranes. In this study a chemically modified ribozyme with enhanced biological stability, targeted against the EGFR mRNA has been evaluated for cellular delivery to cultured glial and neuronal cells with a view to developing treatments for brain tumours. Cellular delivery of free ribozyme was characterised in cultured glial and neuronal cells from the human and rat. Delivery was very limited and time dependent with no consistent difference observed between glial and neuronal cells in both species. Cellular association was largely temperature and energy-dependent with a small component of non-energy dependent association. Further studies showed that ribozyme cellular association was inhibited with self and cross competition with nucleic and non-nucleic acid polyanions indicating the presence of cell surface ribozyme-binding molecules. Trypsin washing experiments further implied that the ribozyme binding surface molecules were protein by nature. Dependence of cellular association on pH indicated that interaction of ribozyme with cell surface molecules was based on ionic interactions. Fluoresence studies indicated that, post cell association, ribozymes were sequestered in sub-cellular vesicles. South-Western blots identified several cell surface proteins which bind to ribozymes and could facilitate cellular association. The limited cellular association observed with free ribozyme required the development and evaluation of polylactide-co-glycolide microspheres incorporating ribozyme for enhanced cellular delivery. Characterisation of microsphere mediated delivery of ribozyme in cultured glial and neuronal cells showed that association increased by 18 to 27-fold in all cell types with no differences observed between cell lines and species. Microsphere mediated delivery was temperature and energy dependent and independent of pH. In order to assess the potential of PLGA micro spheres for the CNS delivery of ribozyme the distribution of ribozyme entrapping microspheres was investigated in rat CNS after intracerebroventricular injection. Distribution studies demonstrated that after 24 hours there was no free ribozyme present in the brain parenchyma, however microsphere entrapped ribozyme was found in the CNS. Microspheres remained in the ventricular system after deposition and passed from the lateral ventricles to the third and fourth ventricle and in the subarachnoid space. Investigation of the influence of microsphere size on the distribution in CNS demonstrated that particles up to 2.5 and O.5f.lm remained in the ventricles around the choroid plexus and ependymal lining.

Effect of electron-phonon coupling on transmission through Luttinger liquid hybridized with resonant level

We show that electron-phonon coupling strongly affects transport properties of the Luttinger liquid hybridized with a resonant level. Namely, this coupling significantly modifies the effective energy-dependent width of the resonant level in two different geometries, corresponding to the resonant or antiresonant transmission in the Fermi gas. This leads to a rich phase diagram for a metal-insulator transition induced by the hybridization with the resonant level.

Quantum dot materials for terahertz generation applications

Compact and tunable semiconductor terahertz sources providing direct electrical control, efficient operation at room temperatures and device integration opportunities are of great interest at the present time. One of the most well-established techniques for terahertz generation utilises photoconductive antennas driven by ultrafast pulsed or dual wavelength continuous wave laser systems, though some limitations, such as confined optical wavelength pumping range and thermal breakdown, still exist. The use of quantum dot-based semiconductor materials, having unique carrier dynamics and material properties, can help to overcome limitations and enable efficient optical-to-terahertz signal conversion at room temperatures. Here we discuss the construction of novel and versatile terahertz transceiver systems based on quantum dot semiconductor devices. Configurable, energy-dependent optical and electronic characteristics of quantum-dot-based semiconductors are described, and the resonant response to optical pump wavelength is revealed. Terahertz signal generation and detection at energies that resonantly excite only the implanted quantum dots opens the potential for using compact quantum dot-based semiconductor lasers as pump sources. Proof-of-concept experiments are demonstrated here that show quantum dot-based samples to have higher optical pump damage thresholds and reduced carrier lifetime with increasing pump power.

Traffic based energy consumption optimisation to improve the lifetime and performance of ad hoc wireless sensor networks

Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.

Spatially extensive summation of contrast-energy is revealed by contrast detection of micro-pattern textures

Vision must analyze the retinal image over both small and large areas to represent fine-scale spatial details and extensive textures. The long-range neuronal convergence that this implies might lead us to expect that contrast sensitivity should improve markedly with the contrast area of the image. But this is at odds with the orthodox view that contrast sensitivity is determined merely by probability summation over local independent detectors. To address this puzzle, I aimed to assess the summation of luminance contrast without the confounding influence of area-dependent internal noise. I measured contrast detection thresholds for novel Battenberg stimuli that had identical overall dimensions (to clamp the aggregation of noise) but were constructed from either dense or sparse arrays of micro-patterns. The results unveiled a three-stage visual hierarchy of contrast summation involving (i) spatial filtering, (ii) long-range summation of coherent textures, and (iii) pooling across orthogonal textures. Linear summation over local energy detectors was spatially extensive (as much as 16 cycles) at Stage 2, but the resulting model is also consistent with earlier classical results of contrast summation (J. G. Robson & N. Graham, 1981), where co-aggregation of internal noise has obscured these long-range interactions.

L-carnosine affects the growth of Saccharomyces cerevisiae in a metabolism-dependent manner

The dipeptide L-carnosine (β-alanyl-L-histidine) has been described as enigmatic: it inhibits growth of cancer cells but delays senescence in cultured human fibroblasts and extends the lifespan of male fruit flies. In an attempt to understand these observations, the effects of L-carnosine on the model eukaryote, Saccharomyces cerevisiae, were examined on account of its unique metabolic properties; S. cerevisiae can respire aerobically, but like some tumor cells, it can also exhibit a metabolism in which aerobic respiration is down regulated. L-Carnosine exhibited both inhibitory and stimulatory effects on yeast cells, dependent upon the carbon source in the growth medium. When yeast cells were not reliant on oxidative phosphorylation for energy generation (e.g. when grown on a fermentable carbon source such as 2% glucose), 10-30 mM L-carnosine slowed growth rates in a dose-dependent manner and increased cell death by up to 17%. In contrast, in media containing a non-fermentable carbon source in which yeast are dependent on aerobic respiration (e.g. 2% glycerol), L-carnosine did not provoke cell death. This latter observation was confirmed in the respiratory yeast, Pichia pastoris. Moreover, when deletion strains in the yeast nutrient-sensing pathway were treated with L-carnosine, the cells showed resistance to its inhibitory effects. These findings suggest that L-carnosine affects cells in a metabolism-dependent manner and provide a rationale for its effects on different cell types. © 2012 Cartwright et al.

Pyrolysis of contaminated energy crops and the characterisation of the gained biochar

The simultaneous use of willow as a vegetation filter and an energy crop can respond both to the increasing energy demand and to the problem of the soil and water contamination. Its characteristics guarantee that the resources are used economically. As a vegetation filter, willow uptakes organic and inorganic contaminants. As a fast growing energy crop it meets the requirements of rural areas without the exploitation of existing forestry. The aim of the research was to gather knowledge on the thermal behaviour of willow, uptaking contaminants and then used as an energy crop. For this reason pyrolysis experiments were performed in two different scales. In analytical scale metal-contaminated wood was investigated and bench scale pyrolysis experiments were performed with nitrogen-enriched willow, originated from a wastewater treatment plant. Results of the pyrolysis showed that 51-81 % of the wastewater derived nitrogen of willow was captured in the char product. Char had low surface area (1.4 to 5.4 m2/g), low bulk density (0.15–0.18 g/cm3), high pH values (7.8–9.4) and high water-holding capacity (1.8 to 4.3 cm3/g) while the bioavailability of char nutrients was low. Links were also established between the pyrolysis temperature and the product properties for maximising the biochar provided benefits for soil applications. Results also showed that the metal binding capacity of wood varied from one metal ion to another, char yield increased and levoglucosan yield decreased in their presence. While char yield was mainly affected by the concentration of the metal ions, levoglucosan yield was more dependent on the type of the ionic species. Combustion experiments were also carried out with metal-enriched char. The burnout temperatures, estimated ignition indices and the conversion indicate that the metal ions type and not the amount were the determining factors during the combustion. Results presented in the Thesis provide better understanding on the thermal behaviour of nitrogen-enriched and metal contaminated biomass which is crucial to design effective pyrolysis units and combustors. These findings are relevant for pyrolysis experiments, where the goal is to yield char for energetic or soil applications.

Making energy service companies (ESCOS) future fit

Energy service companies (ESCOs) are faced with a range of challenges and opportunities associated with the rapidly changing and flexible requirements of energy customers (end users) and rapid improvements in technologies associated with energy and ICT. These opportunities for innovation include better prediction of energy demand, transparency of data to the end user, flexible and time dependent energy pricing and a range of novel finance models. The liberalisation of energy markets across the world has leads to a very small price differential between suppliers on the unit cost of energy. Energy companies are therefore looking to add additional layers of value using service models borrowed from the manufacturing industry. This opens a range of new product and service offerings to energy markets and consumers and has implications for the overall efficiency, utility and price of energy provision.

Energy-based damage and fracture framework for viscoelastic asphalt concrete

A framework based on the continuum damage mechanics and thermodynamics of irreversible processes using internal state variables is used to characterize the distributed damage in viscoelastic asphalt materials in the form of micro-crack initiation and accumulation. At low temperatures and high deformation rates, micro-cracking is considered as the source of nonlinearity and thus the cause of deviation from linear viscoelastic response. Using a non-associated damage evolution law, the proposed model shows the ability to describe the temperature-dependent processes of micro-crack initiation, evolution and macro-crack formation with good comparison to the material response in the Superpave indirect tensile (IDT) strength test.

Gain dependent pulse regimes transitions in a dissipative dispersion-managed fibre laser

For the first time, we demonstrate the possibility to switch between three distinct pulse regimes in a dissipative dispersion-managed (DM) fibre laser by solely controlling the gain saturation energy. Nonlinear Schrödinger equation based simulations show the transitions between hyper-Gaussian similaritons, parabolic similaritons, and dissipative solitons in the same laser cavity. It is also shown that such transitions exist in a wide dispersion range from all-normal to slightly net-normal dispersion. This work demonstrates that besides dispersion and filter managements gain saturation energy can be a new degree of freedom to manage pulse regimes in DM fibre lasers, which offers flexibility in designing ultrafast fibre lasers. Also, the result indicates that in contrast to conservative soliton lasers whose intensity profiles are unique, dissipative DM lasers show diversity in pulse shapes. The findings not only give a better understanding of pulse shaping mechanisms in mode-locked lasers, but also provide insight into dissipative systems.