Iron is a very important micronutrient and unsurprisingly low levels within the body are associated with iron deficiency and anaemia. However, conversely there is also evidence that consuming too much iron is similarly detrimental to health and in particularly the health of your gut. Recent studies have shown that in the majority of adults we consume an excess of iron in our diets and the vast majority of this iron never gets absorbed by our bodies. Instead this pool of iron ends up in the large bowel where it can reside for between hours to days before it is then excreted. In particular recent studies have shown that this pool of iron is detrimental to gut health and this is likely mediated by altering the types of bacteria which normally colonise the large bowel. Thus our application is designed to create a unique formulation which could be used to mop up this pool of toxic iron which resides within the colon and thereby enhance intestinal health. This could be achieved by using experimental drugs with known iron neutralising properties but since these can be toxic we instead propose to identify natural agents which might be able to neutralise iron. One such molecule is alginate which is seaweed derived, used throughout the food industry and which has potent iron neutralising properties. Thus the aim of this study is to screen a large panel of natural food agents like alginate with the hope of identifying a molecule with the strongest iron neutralising properties. Once we identify such a molecule we wish to create a formulation which will ensure that when humans consume it the molecule will only become active in the large bowel where the excess iron resides. This formulation will be tested in an artificial model of the gut and if successful we will conduct a study with healthy volunteers to assess its bioactivity. If successful this could lead to the development of food products which could be used to enhance intestinal health.

This project proposes a new theoretical method to measure non-invasively the key characteristics of a two dimensional dynamically rough free surface of a turbulent open channel flow using airborne acoustic waves. The research of this project will cover both numerical simulation and analytical derivation of the approximated solutions based on extending the Kirchhoff approximation technique to the case of rough surface containing multiple scales. This will be used to develop a technique of recovering water surface profile based on the data recorded on array of microphones. The method will provide sub-millimetre accuracy required to identify various scales of gravity-capillary waves present on the surface of shallow water flow. This information can potentially be linked to underwater conditions and flow velocity profile. The project outcomes will provide a virtual environment to prove the concept of non-invasive measurements as well as a tool to interpret the collected data. The numerical simulations will be adapted to open source software (i.e. GNU Octave and Scilab). For dissemination of the results and further developments, the software will be realised to acoustic and hydraulic communities as open source. The key novelty of this project is that the proposed method will be able to work reliably with a broad range of flows typically found in rivers, estuaries and partially filled pipes (sewers), which are the key components of water infrastructure and are critical in the water circulation process. This work will enable the development of non-invasive instrumentation which can determine flow rates and sediment transport in natural and man-made channels. This will enhance our capability for flood risk assessment and pollution monitoring.

High blood pressure, or hypertension, is one of the most important causes of global morbidity and mortality in the developed world [1]. It has been shown that hypertensive people have a high risk of stroke, heart attack, heart failure and renal failure. The Health Survey for England in 2006 demonstrated that the prevalence of hypertension in the UK increased from 17% in the age group 40-49 years to 77% in those aged 70-79 years [2]. Hypertensive patients are usually identified by a threshold diagnosis of their systolic or diastolic pressures exceeding 140 or 90 mmHg respectively. However this diagnosis tends to misdiagnose the individuals in the large population in and around the threshold making the selection for appropriate therapy difficult. For example one important determinant of hypertension is the flexibility of the aorta (the first artery leading from the heart), which becomes stiffer with age and arteriosclerosis. However, such "stiffness" is only one among other geometrical and mechanical factors that influence the pressure pulse and thus hypertension. Therefore, non-invasive measurement of pulse pressure waveforms has been of interest for more than 100 years, and includes tonometry, Ultrasound and Magnetic Resonance Imaging (MRI). Although the non-invasive measurement of waveforms has become fast, the current analysis of the measured waveform data is relatively simplistic. In particular, the analysis of certain waveform features are performed in isolation and are impeded by a lack of understanding of the relative contributions from arterial stiffness/geometry, wave reflection and ventricular/arterial interaction to hypertensive pressure. Over the last two decades, computational modelling has been established as a new discipline to study the interaction of different parameters in the cardiovascular system. These models can help to separate the various contributions to the pressure waveform and elucidate complex interaction of parameters affecting hypertension. More recently, imaging data of the patient's anatomy and physiology has been introduced in numerical simulations to produce patient-specific models. Although, different models have been developed to investigate the influence of geometrical and mechanical factors, a model validation remains challenging since it would require large studies in animals and patients. This proposal aims at the identification of high-risk individuals by determining the mechanical factors which cause their pressure to be pathological. This approach would allow a better selection of appropriate treatments for the individual patient. For this, we propose the construction of a comprehensive experimental arterial model with which to determine and quantify main contributors to hypertensive pressure as well as to validate our existing computational arterial simulation frameworks (1D and 3D). Translation of these technologies towards the clinic will be facilitated with the construction of full-scale silicone arterial model, which will experimentally simulate haemodynamics of a hypertensive patient dataset. This will be followed by a clinical validation of a computational analysis tools in volunteers and a small patient cohort. References: [1] MacMahon, S., et al.: Blood-pressure-related disease is a global healthy priority. Lancet, 2006. 371: p. 1480-1482. [2] NHS, Health survey for england 2006 latest trends. 2008: Leeds.

Sciatica is a term used to describe painful symptoms affecting the hips, buttocks and legs. It is caused by injured or irritated nerves in the lower back. Sciatica pain can feel hot, sharp, or electrical in nature. Sciatica can also cause weakness and pins and needles. Sciatica is a complex condition and the pain may be caused by different mechanisms in different patients. We still do not fully understand the exact mechanisms of sciatica pain. Sciatica is a very common condition and can have a devastating effect on everyday life. For example, some patients lose their independence and need help with day-to-day tasks such as dressing. Sadly, approximately one in three patients with sciatica develop persistent sciatica pain. We currently do not understand why some patients develop persistent sciatica pain and why some recover. Previous research has demonstrated that usual clinical findings (e.g., presence of depression or changes on a standard MRI scan) cannot predict persistent sciatica pain. Therefore a different approach is required to identify patients who may develop persistent sciatica pain. This is the goal of the FORECAST study. Previous studies only included a short clinical examination. Our study is different. We will perform a detailed set of tests (see below). Our ambition is that the detailed tests can predict who will develop persistent sciatica pain. The questions we plan to answer in the FORECAST study are: 1. Can the detailed tests identify patients with similar mechanisms causing their sciatica pain? 2. Which of these detailed tests predict persistent sciatica pain? The FORECAST study is performed by a team of medical doctors, neuroscientists, statisticians and magnetic resonance imaging (MRI) specialists at Oxford University. The team also includes patient partners. They help us to make sure our study is useful for patients. We will invite 180 patients with recent onset of sciatica pain (<3 months) to participate in the FORECAST study. At their initial assessment, we will perform the detailed tests. This includes detailed sensory nerve testing (quantitative sensory testing). Quantitative sensory testing evaluates how well patients can feel different stimulations such as cold, warm or pressure. This tells us how well the nerve is working and how sensitive it has become. We will also include a precise set of questionnaires to evaluate the types of pain (e.g., burning or electric shock or achy) and emotional wellbeing. Emotional wellbeing can be affected when a patient has sciatica. For instance, some patients may be anxious or angry, and others may feel lonely and detach themselves from friends and family. We will also take a blood sample to look for signs of inflammation. In some patients we will use specialised MRI scans. These images are much more detailed and specialised than standard MRI scans. They allow us to evaluate the microscopic structure of the small nerves in the back, which is not possible with standard MRI scans. These detailed tests will provide us with a good picture of the starting point of a patient's experience of sciatica. We will then contact patients again three months and one year later, to ask whether they still have sciatica pain. We will use statistics to identify patients with similar mechanisms causing their sciatica pain. We will also examine which tests predict persistent sciatica pain. The results of the FORECAST study will help us better understand the complexity of sciatica and who will develop persistent pain. Our findings will also help future research. For example, future studies can examine whether we can prevent or reduce persistent pain by giving more specific treatment to patients who the FORECAST study shows are likely to develop persistent sciatica pain. We hope that the results of the FORECAST study will help reduce suffering and improve quality of life for patients with sciatica.

Severe malnutrition in early childhood is a major public health concern globally. This has serious consequences: - Short term: for children to survive: malnutrition in all its forms underlies some 45% of all under 5 child deaths worldwide. - Long term: for children to thrive: there is increasing realisation that early life malnutrition contributes to the fast-growing global epidemic of non-communicable diseases (NCDs). As more children now survive episodes of malnutrition in childhood there is increasing need to understand what causes the long term problems. Evidence on this would lead to: improved early treatment of child malnutrition; improved longer term treatment aiming to reduce long term adverse effects. In this project we have a unique opportunity to explore three groups of children/adults in: - Jamaica: children suffering from severe malnutrition in the 1980s have been followed up on several occasions already, with scope for further analysis from already collected data. - Malawi: We recently followed up a group of children admitted for severe malnutrition in 2005/6. We plan to both analyse existing data in more depth: also to possible collect new data in future. - Ethiopia: Individuals who were young children at the time of the great Ethiopia famine of 1983-85 are about to be followed up in a pilot study. Learning from the above two projects will inform and improve plans for the Ethiopia work. We aim to understand what are the long term problems following early child malnutrition and why they occur (the 'mechanisms' by which the two problems are linked) The work proposed in this applicaiton is background towards the above future project. There are two main activities planned A) Review of exisiting evidence: we will search the scientific literature to better understand what other have found to date re links between early life malnutrition and adult NCDs. Through this we will identify key knowledge gaps to target in future work. B) Collaborator meeting - we will bring together the teams working on the above three groups of children to: learn from each other and share experiences. Through this better future work will be possible and there is great potential to enhance the overall learning compared to following each group as a stand-alone. This meeting will be organised in Ethiopia in Autumn 2019: we will invite a number of key experts to make detailed plans for future work. The Ethiopia/Malawi/UK teams will also visit Jamaica (the most advanced/experienced group) to learn from their experience and thus help plan better future projects in Malawi and Ethiopia.