Up to 1 in 5 patients hospitalised by COVID-19 have evidence of heart muscle injury as measured from a blood test. This is associated with a high death rate. Using an MRI scan of the heart we aim to investigate how often, and in what way, the heart becomes damaged, and how the heart recovers 6 months later. We need to know how heart muscle damage and recovery is affected by age, sex, ethnicity and other medical conditions (such as diabetes, high blood pressure, heart disease and narrowing of blood vessels), as these are also known to be associated with high death rates. We also want to see if we can improve the diagnosis of viral heart damage from a simple ECG, which may save patients having invasive heart tests which can be uncomfortable, are expensive and carry a small risk of serious complications and may put healthcare staff at increased risk of exposure to COVID-19.

The growth of organisms, and organs such as the brain, fingers and toes, occur by cells dividing and changing from simple precursors into complex cells with specific functions through a series of carefully regulated processes. The cell cycle controls cell division by requiring the cell to pass multiple checkpoints to ensure only a healthy cell can divide. Another important ability for a cell is to be able to stop dividing. For example, when no more cells are required in the developing brain, cells exit the cycle resulting in no more cells being produced than are needed. Failure to exit the cell cycle can lead to excessive cell numbers, and so-called overgrowth disorders, whereby organs are too big and often do not have the correct structure. In the brain this results in the disorder megalencephaly. While brains generally stop growing once fully developed, the brains of people with overgrowth disorders continue to grow. This growth persists even after surgical intervention, resulting in further complications. Taken together, these observations tell us that precise management of the cell cycle is required for development of the brain as well as other cells and organs in the body. The aim of my research is to investigate a family of 3 proteins called D-type Cyclins (CyclinD), that act as a molecular switch for the cell cycle. This will help to understand the molecular processes that control the cell cycle and how these lead to disease when they don't work correctly. When CCND levels are high, cells continue to divide to create more cells, however when CyclinD is switched off the cells stop dividing. I am interested in disorders that occur which CyclinD's do not get switched off, meaning cells continue to divide even when they're not supposed to. In particular, I want to learn more about the molecules that control this switch, what happens in a cell when the switch cannot be turned off and to develop molecules that target CyclinD in order to stop the cells dividing. Using this information, I hope to learn how cells signal to stop cell division normally and therefore how they coordinate the development of complex structures such as the brain. Currently there are no cures or therapies available that can specifically target CCND accumulation. Through my research, we have gained a better understanding of how CyclinD is regulated. Using this new knowledge, I have developed CyclinD-inhibitors that can overcome the effects of CyclinD accumulation and have generated relevant cell-based disease models in which to test them in. This study will therefore test a panel of CyclinD-inhibitors I have developed on a range of relevant disease models in order to test their therapeutic potential for cancers and overgrowth disorders.

A Brand New Sense (BraNeS) aims to create a digital tool that makes movement fun and aids creative expression and intergenerational exchange within the user's home setting and/or community environments. Just like anyone else, when they exercise, old people experience important health benefits. They are able to move better, accomplish daily and routine tasks easier and experience a positive shift in their mood. However, a major challenge is how to get people to become active in a way that they enjoy. Research has shown that a combination of movement and music is enjoyable, and people are more likely to adhere to exercise programmes that involve music. Studies have also shown that the social dimension of physical activity is an important factor of enjoyment. BraNeS explores the use of movement sonification as a form of physical activity that combines creative expression and social interaction. Movement sonification is the synchronous production of sound and movement through a digital device. It is an emerging practice which, on the on hand, is spreading within youth and music subcultures through new products aimed at primarily young audiences. It is also being tested within health and clinical settings for the treatment of health conditions and/or the improvement of physical performance. Through developing an existing prototype, BraNeS capitalises on this trend, in order to develop an intuitive, affordable and accessible tool that can be used in the user's living environment and increase mobility, aid creative expression and encourage intergenerational social interaction.

We have developed a new imaging method that has the potential to increase the signal in a magnetic resonance (MR) image by up to 100,000 fold. This method can potentially be used on any hospital MR scanner. Our method works by magnetically labelling substances we seek to probe without affecting their molecular structure and is therefore non-toxic. With this method it is possible to label both drugs and substances that occur naturally in the body, making the method widely applicable. In previously and currently funded work, we are developing the technical aspects of this method and seek to test it in healthy subjects. As part of the current grant application, we will create the infrastructure needed to apply this method in patients within 5 years, focussing on patients with heart disease, cancer and joint disease. Our new method has the potential to speed up and improve MR imaging in a very wide range of diseases and help in the development of new drugs.

The use of artificial intelligence (AI) in biological discovery and digital healthcare is increasing at rate. Digital imaging provides large quantities of diagnostic data in formats amenable to widespread adoption and automated analysis. As a result, research and commercial opportunities are arising to enhance and adapt current technologies to improve efficiency and automation with AI. However, in order to ensure the safest and most reliable deployment of these technologies in the digital era, there is a core requirement to ensure that the data upon which automated analyses are performed are of the highest quality and validity to ensure reliably positive outcomes. Furthermore, to warrant the maximum benefits of automation are reached, analysis devices must perform at the highest throughput and efficiency - a process that can be self-fulfilling by the integration of AI-workflow and Industry 4.0 approaches. To augment biomedical AI the applicant proposes a Portfolio Fellowship that will enhance, integrate and optimise FFEI's past, present and future technologies in bio-imaging and digital analysis workflow. This ambitious project will develop four core technologies, each enhancing a stage of the AI imaging pipeline. Technologies will start from different stages of market-readiness to ensure commercial and grant deliverables are manageable and realised. The overlapping stages of development will lead to a sustainable balance of commercial and research activities, whilst incrementally priming AI imaging markets for the emergence of modular, end-to-end AI technology from FFEI that can provide solutions that are adaptable and integrative to most segments of the digital healthcare market. A long-term objective is to integrate all the core developments into an FFEI 'smart lab' product, in which a single, modular device can perform all essential activities of biomedical AI laboratories. The Fellow aims to develop FFEI's biomedical capabilities by establishing a research environment to collect baseline metrics of current technology as a starting point for enhancement. The project will prototype new and established FFEI technology with flexibility to integrate emerging concepts from a network of academic partners. Ultimately, the objective will be for the Fellow's team to be able to dynamically test biological, mechanical and computational concepts to better achieve end-to-end optimisation of image data for AI. A key objective is to prove augmentation validity in refining end-to-end medical AI efficiency and reliability. To medically validate these technologies beyond concept, the Fellow will collaborate with NHS partners in parallel to FFEI productisation, allowing for iterative optimisations and case-data for accreditation. Enhancement of workflow processes with AI will require practical assessment and expert consultation, therefore the Fellow will create and lead a consortium of academic and NHS collaborators with expertise in biomedical R&D, diagnostics and AI analysis, further raising awareness through dissemination of peer-reviewed data. An essential component of the project's success will be the creation of a new 'AI imaging' team under the Fellow's leadership. FFEI have a highly experienced and established R&D imaging team into which the Fellow will recruit new members to grow FFEI's Life Science business, to bolster this team and explore new concepts whilst learning the skills of blending innovative thinking with commercial application. In return, the new team will bring fresh talent to FFEI, with anticipated recruiting of AI software, advanced opto-mechanical and biological experts, developing a team to take FFEI into a new age of AI augmentation and commercial success. The project will benefit the Fellow with personal development opportunities in business management, team leadership and commercial collaborations, under the mentorship and support of the FFEI executive team.