Structural Motifs of Novel Metallothionein Proteins

Metallothioneins (MT) are a family of small cysteine rich proteins, which have been implicated in toxic metal detoxification, protection against oxidative stress, and as a metallochaperone. The most well studied member of the family is the mammalian MT, which consists of two domains: a β-domain with 9 cysteine residues, which sequesters 3 Cd2+/Zn2+, and an α-domain with 11 cysteine residues, which sequesters 4 Cd2+/Zn2+. The exact functions of MT are unknown but must relate to its metalation status. Several areas that could lead to the assignment of function include 1) the determination of the exact mechanism of metalation and the structural characterization of 2) submetalated and 3) supermetalated forms of MT. The following thesis presents electrospray ionization mass spectrometric (ESI MS) data showing that the mechanism of metalation of MT is noncooperative. That is metalation events occur independently of each other, allowing for partially metalated species to exist in vivo. Further metalation studies using the isolated domains of MT as metal ion competitors against the full MT protein have yielded evidence that a new Zn5-MT exists in which both domains ‘coalesce.’ In addition, NMR and CD spectroscopy, have shown the existence of a new ‘supermetalated’ Cd8-MT, which also results in a ‘coalescence’ of both domains. Taken together these results indicate that 1) partially metalated forms of the protein are stable and 2) the traditional structure of MT is in fact the exceptional case and that under conditions of metal ion deficiency and excess, both domains interact with each other

Assessment of mid-depth arrays of single beam acoustic doppler velocity sensors to characterise tidal energy sites

Accurate characterisation of fluid flow at tidal energy sites is critical for cost effective Tidal Energy Converter (TEC) design in terms of efficiency and survivability. The standard instrumentation in tidal site characterisation has been Diverging acoustic-Beam Doppler Profilers (DBDPs) which remotely measure the flow over a range of scales, resolving up to three velocity vectors. However, they are understood to have several drawbacks particularly in terms of characterising turbulent aspects of the flow. This characterisation is generally based upon a small number of key transient metrics, the accuracy of which directly impacts TEC designs. This work presents an optimisation and performance assessment of newly available Single Beam Doppler Profilers (SBDPs) mounted on a commercial-scale tidal turbine at mid-channel depth in a real operating environment. It was hypothesised that SBDPs would have advantages over DBDPs for site characterisation, in terms of reduced random error, reduced uncertainty in turbulence intensities and the ability to quantify the structure of the turbulent flow. The relationship between random error, sensor orientation and flow speed is quantified for both single and diverging beam sensor types. Random error was found to increase with increasing flow velocity as a power law, the slope of which varies for different sensor orientations. Quantification of noise offers a practical method to correct turbulence metrics. To enable the use of multiple acoustic sensors mounted in close proximity, interference was quantified and mitigation techniques examined. Cross-talk between sensors of the same type were generally shown to bias measurements towards zero. In the presence of alternate types of acoustic sensors, interference caused an increase in standard deviation of velocity results. Implementing a timing offset control mechanism was able to mitigate this effect. This work has achieved a greater understanding of the drivers (spatial separation, inclination angle, pulse power) and effects on measurements of interference along with ambient-noise for users of acoustic instruments. Lessons learned of value to the industry, as site characterisation work intensifies ahead of next generation commercial scale devices, are presented. Mid-channel depth mounted SBDPs were found to have advantages over seabed mounted DBDPs in resolving the key turbulent flow metrics. SBDPs were able to resolve integral length-scales of turbulence that show an anisotropic ratio of scales as predicted from theory and in work at similar sites, while the DBDPs results were similar for all directions. Turbulence intensity measurements were found to be similar after noise correction, with the SBDPs more able to accurately capture the turbulence dissipation rate. This evidence suggests that SBDP arrays present a significant improvement over bottom mounted DBDPs in discerning information about the nature of the turbulent flow, and thus future site characterisation work should consider the use of SBDPs alongside bottom mounted DBDPs for this purpose

Detecting anthropogenic cloud perturbations with deep learning

One of the most pressing questions in climate science is that of the effect of anthropogenic aerosol on the Earth's energy balance. Aerosols provide the `seeds' on which cloud droplets form, and changes in the amount of aerosol available to a cloud can change its brightness and other physical properties such as optical thickness and spatial extent. Clouds play a critical role in moderating global temperatures and small perturbations can lead to significant amounts of cooling or warming. Uncertainty in this effect is so large it is not currently known if it is negligible, or provides a large enough cooling to largely negate present-day warming by CO2. This work uses deep convolutional neural networks to look for two particular perturbations in clouds due to anthropogenic aerosol and assess their properties and prevalence, providing valuable insights into their climatic effects.Comment: Awarded Best Paper and Spotlight Oral at Climate Change: How Can AI Help? (Workshop) at International Conference on Machine Learning (ICML), Long Beach, California, 201

Insulin independence following islet transplantation improves long-term metabolic outcomes

AIMS: Pancreatic islet allotransplantation is an effective therapy for type 1 diabetes mellitus, restoring glycaemic control and hypoglycaemic awareness in patients with recurrent severe hypoglycaemia. Insulin independence following transplant is being increasingly reported; however, this is not a primary endpoint in the UK. Having surpassed 10 years of islet transplantation in Scotland, we aimed to evaluate the impact of insulin independence following transplant on metabolic outcomes and graft survival.METHODS: We conducted a retrospective analysis on data collected prospectively between 2011 and 2022. Patients who underwent islet transplantation in Scotland up to the 31st January 2020 were included. Primary endpoint was graft survival (stimulated C-peptide &gt;50 pmol/L). Secondary endpoints included GOLD score, HbA1c, C-peptide and insulin requirement. Outcomes were compared between patients who achieved insulin independence at any point following transplant versus those who did not.RESULTS: 60 patients were included. 74.5% experienced &gt;50 severe hypoglycaemic episodes in the year preceding transplant. There was a 55.0% decrease in insulin requirement following transplant and 30.0% achieved insulin independence. Mean graft survival time was 9.0 years (95% CI 7.2-10.9) in patients who achieved insulin independence versus 4.4 years (95% CI 3.4-5.3) in patients who did not. Insulin independence was associated with significantly improved graft function, glycaemic control and hypoglycaemic awareness at 1 year.CONCLUSIONS: This is the largest UK single-centre study on islet transplant to date. Our findings demonstrate significantly improved outcomes in patients who achieved insulin independence following islet transplantation.</p