High blood pressure causes an increase in the size of the heart (cardiac hypertrophy) and is a major risk factor for the development of heart failure. One in five people die from this condition. Angiotensin II is a hormone that stimulates cardiac hypertrophy and it functions by binding to the Angiotensin II type I (ATI) receptor. A complex programme of intracellular signalling is initiated to stimulate hypertrophy and a new protein called ATRAP has been recently identified that protects against the effects of Angiotensin II. ATRAP was discovered because it binds to the ATI receptor but how ATRAP suppresses cardiac hypertrophy is not known. We have made an unexpected connection between ATRAP and a lipid binding protein, RdgB-beta. We propose to define the connection between the two proteins, ATRAP and RdgB-beta in the context of lipid signalling via enzymes called phospholipases that produce the 'signalling lipid', phosphatidic acid (PA). We will establish how this protein-lipid network operates during Angiotensin II signalling. The activity of phospholipases is stimulated when Angiotensin II binds to the receptor. RdgB-beta is uncharacterised and we have discovered that it has unusual lipid binding properties - it binds PA. Our concept is that RdgB-beta sequesters the 'PA' signal and therefore restrains the signalling cascade resulting in inhibition of cardiac hypertrophy. We will examine how RdgB-beta binds 'PA' and disposes of it. Because ATRAP binds RdgB-beta we think that a 'bridge' between two membranes is formed. This allows the 'PA' to be removed from the plasma membrane where signalling occurs and sent to the compartment where lipids are re-used for making new lipids. To form the bridge, RdgB-beta has to interact with ATRAP on one membrane and other proteins on the opposite membrane. We will therefore identify these proteins by using RdgB-beta as bait to fish for new proteins. We will also study the importance of RdgB-beta and ATRAP by increasing or decreasing the protein levels in the cells. This will inform us on how Angiotensin II signalling is affected. If RdgB-beta reinforces the restraint put by ATRAP on Angiotensin II signalling, this will provide strong evidence that the molecular mechanism used by ATRAP is to participate in the removal of the signalling lipid, PA. To further test the model, we will delete the gene for RdgB-beta in a model organism (Drosophila) and examine the phenotype in collaboration with our project partner in Bangalore, India. To determine the importance of PA binding to RdgB-beta, we will make mutant proteins that cannot bind PA. These mutants will be examined for rescue of the fly defect. The interaction between RdgB-beta and ATRAP together with the binding of PA to RdgB-beta could provide the molecular explanation of how ATRAP is able to suppress the function of Angiotensin II signalling and could therefore offer a novel therapeutic target for intervention in cardiovascular diseases. In the clinic, inhibition of Angiotensin II signalling by ACE inhibitors that prevents the production of Angiotensin II or drugs that prevent binding of Angiotensin II to its receptor are used for treatment for hypertension. Since most drugs have side-effects, drug combination that targets different systems are often used. Therefore the proposed research could well lead to a different molecular target which could provide a more effective treatment. Understanding how the endogenous inhibitor of Angiotensin II signalling, ATRAP, functions, may provide new strategies for drug targeting. Because ATRAP interacts with RdgB-beta, the possibility that targeting RdgB-beta may provide a unique opportunity to generate a new class of drugs that could be based on binding small hydrophobic molecules in the lipid binding pocket of RdgB-beta. The benefit derived from such drugs is huge as high blood pressure is one of the most common diseases that afflict humans.

Laboratory analysis of a clinical sample such as blood serum is a powerful diagnostic tool. It establishes the presence and concentration of a specific biomolecule that correlates with the risk or progression of a particular disease, or with the susceptibility of the disease to a given treatment. Regular screening for a large number of such biomarkers, the discovery of which is a major biomedical research activity, would make the large-scale application of predictive, preventive and personalized medicine a reality. This emphasis on prevention and individualization of healthcare is highly desirable from a socio-economical perspective, but the required increase in the number of laboratory tests (already about a billion per annum in the UK) will be huge and cannot be met with the biochemical analysis methods that are currently employed.The aim of this Grand Challenge project is to develop silicon nanowire arrays, the only technology that has been shown to enable highly specific and ultrasensitive analysis of protein biomarkers with electronic rather than costly optical detection, into a robust user platform for the simultaneous analysis of a large number of biomarkers in the same clinical sample. We will optimize a unique method to fabricate extensive arrays of silicon nanowires with a cost-effective mass-production technology that is similar to that used by the microelectronics industry. The silicon nanowires will be incorporated in an advanced microfluidic matrix that will not only allow the sample volume to be very small (a blood droplet obtained with a simple finger prick could be sufficient), but will also provide the means to divide the nanowire array, which can consist of up to a thousand parallel nanowires, into many individually addressable sets of nanowires. Through appropriate functionalization chemistry, each nanowire set can be made to recognize and quantify a different biomarker, enabling a maximum amount of information to be extracted from a minimal amount of sample.The nanowire devices, including the microfluidics for sample handling, will be developed as a single disposable chip, suitable for the mass production of commercial diagnostic kits. Our industrial partners, one manufacturer and two different end-users, will provide a pronounced commercial perspective to the development of the nanowire platform. For clinically relevant pre-commercialization proof of principle, the project will focus on the analysis of six different protein markers of viral infection and treatment. The project will have unique access to clinical samples -serum and induced sputum- obtained from patients admitted to the Acute Medical Unit at the Southampton General Hospital suffering from acute asthma exacerbations. It will also have access to serum samples from asthmatic volunteers undergoing Phase I clinical trials using inhaled beta-interferon which is being developed for treatment of virus-induced asthma exacerbations.The silicon nanowire technology will enable routine and economical high-throughput biomarker analysis outside the clinical laboratory, providing the technological means for a transition to a healthcare system in which regular screening for complex diseases facilitates prevention and early intervention. Throughout the project we will explore practical questions of implementation during scientific and technological development rather than, as is more commonly the case, after scientific and technological phases have been completed. To achieve this we will engage with the public, healthcare professionals, healthcare managers and policy makers to explore key questions of risk and regulation as well as exploring how this technology might be brought into effective use within established systems of healthcare work and organization.

The ability to predict weather offers the potential to provide valuable information that can be used in planning health services. For example, imagine a hospital planning system that was able to predict fluctuations in demand for different services as a consequence of predictions of meteorological events such as the early February cold spell in 2009. Such a tool would result in a substantial benefit to both the NHS and health outcomes. Specifically, appropriate use of meteorological intelligence would help to:1. Improve health by reducing morbidity and mortality rates, and generally improving health outcomes.2. Improve access to services by better predicting hospital pressures due to weather events, thus allowing for hospital mangers to anticipate and better prepare for such fluctuations. This research will explore and quantify the relationship between weather patterns and extreme weather events, and their impact on various health conditions, such a heart attacks, stroke, asthma, and fractures. For example, it is thought that a sudden surge in cold temperature can cause blood to thicken slightly and blood pressure to increase, which can trigger a heart attack or stroke in vulnerable patients. There are many other reported (observed) trends such as thunderstorm-related asthma. A thunderstorm in South East England, for example, saw 640 patients presenting with severe asthma to hospital, ten times the usual number. By linking weather and health in this way, we can help save lives or minimise the risk of morbidity by creating an early warning system that can ensure at-risk patients are well informed and have sufficient medication and advice. Furthermore, this research will utilise computer simulation techniques and statistical models and apply their use to create a novel hospital operational capacity support tool (MetSim) that will utilise meteorological forecasts alongside NHS hospital data to provide information to hospitals on expected levels of emergency admissions and to alert them of sudden surges in demand and daily fluctuations. By forecasting demand in this manner, MetSim will allow hospital managers to understand more closely resulting resource needs over the short-term planning horizon and assist in planning decisions such as cancellation of elective admissions. Given that the provision of hospital resources is a matter of considerable public and political concern and has been the subject of widespread debate, this research will help the NHS more effectively and efficiently plan and manage their health services.A further benefit of MetSim is that it can act as a public health warning system. Health-weather correlations could be used by regional Strategic Health Authorities or Primary Care Trusts to alert at-risk populations. This could have significant public health benefits by ensuring such people are better informed about the forthcoming risks and have sufficient medication and appropriate medical advice. Treating patients for the health conditions evaluated in this research (to include heart disease, stroke, acute bronchitis, fractures and pneumonia) accounts for a significant proportion of the NHS budget. For example, stroke and heart disease incidence in the UK is amongst the highest in the world and these two conditions alone cost the NHS an estimated 18.3 billion annually. Using MetSim to prevent hospital admissions or improving health outcomes for even a small percentage of these patients could result in significant costs savings to NHS Trusts.This novel and valuable research involves a collaborative team of specialists in Operational Research and Statistics, with co-operation and support of the Met Office, Southampton University Hospital NHS Trust, and the Cardiff and Vale NHS Trust. The level of support, commitment and excitement about this research from these three organisations is such that between them they have pledged 60,000 towards the costs of the overall project.