UNIVERSITY OF EDINBURGH

UKRI Gateway to Research · FY 2025 · 2025-03

Human actions are having a staggering impact on all life on the planet, leading to the new geological epoch, the Anthropocene. One of the greatest hallmarks of the Anthropocene is biodiversity loss, including rapid population declines of vertebrate populations, which often lead to loss of genetic diversity. Host-associated microbiomes, collection of microorganisms that live in and on the host, are central to host survival, as they provide many essential biological functions, ranging from digestion to immunity to reproductions. Disruptions of microbial communities can have severe consequences, reducing host fitness and causing disease. Microbiomes are themselves impacted by host genetics and the environment. Recognising this intimate connection between the hosts and their microbiomes, this project asks a central question: How did human-driven population declines during the last two centuries impact host-associated microbiomes and what consequences does it have for the hosts? Surprisingly, despite the fundamental importance of microbiomes, their role has rarely been considered in the context of widespread population declines. The few existing studies suggest that small, isolated populations show reduced microbial diversity and altered community composition. Experiments confirm these observations and link the resulting microbiome changes to negative fitness consequences for the host. However, the cross-sectional approach applied to wild study systems so far suffers from the inability to distinguish the microbiome responses to recent change from long-term processes that are not related to population declines. Doing this requires microbiomes from the past that pre-date the population declines. These have been unattainable until very recently because most host-associated microbiomes decompose after host death. However, microbial 'time travel' is now possible via metagenomic analysis of dental calculus, a unique microbial fossil that persists virtually unchanged through time, is abundant on teeth of diverse mammals, and is readily available from museum specimens across the last 200 years, the period of greatest human impact. By applying ancient DNA techniques and jointly analysing host genomes and microbiomes from the same individual, this project will generate fundamental new knowledge about host-microbiome co-evolution during population declines. First, by comparing microbiomes from the same population from before and after population decline (and in non-declined control populations) in 12 mammalian species, this project will investigate if population declines lead to changes in host-associated microbiomes and evaluate the relative contribution of host genomics and the environment to this change. Second, through individual-level joint analyses of host genomics and the microbiomes, we will explore the association between host heterozygosity, inbreeding and genetic load - typical genomic markers of population decline - and microbiomes and how these translate into population-level changes. Finally, we will identify specific host genes and microbial species that change through time in a concerted fashion and are related to presence of oral disease in wild mammals. This project will provide fundamental insights into anthropogenic impacts on microbiomes of wild mammals, with implications for wildlife conservation, animal and human health.

UKRI Gateway to Research · FY 2025 · 2025-03

AI is rapidly reshaping the way we work and live. Tailoring state-of-the-art solutions was only possible for those companies with AI research labs or individuals with deep technical knowledge of how the technology works. However, there is a growing commoditisation of AI; for example, companies such as OpenAI have provided affordable mass access to Large Language Models, with ChatGPT currently having around 180.5 million users. This increased access to AI could, McKinsey estimates, deliver an additional economic output of approximately US$13 trillion by 2030, with generative AI contributing $3.5 trillion. This is equivalent to the GDP of the UK. Despite the clear advantages, corporate adoption has plateaued, with only 50-60% of companies utilising AI technologies consistently. This stagnation is largely due to a prevalent distrust of AI among leaders and the general public, compounded by a limited understanding of the technology. The key objective of this project is to work with one of the world’s largest insurance companies to undertake world-leading research to provide insurance services that indemnify organisations against damage caused by underperforming or unreliable AI solutions. Reduced insurance premiums create incentives to develop and deploy high-quality auditable AI systems that inspire trust. Clear understanding and management of risks allows organisations to innovate with confidence.  This will ultimately lead to better risk management practices and standards for AI. With insurance-backed performance guarantees, companies creating and using AI can offer compensation in case of underperformance, thus encouraging broader adoption of innovative AI solutions.  Moreover, the AI insurance market can complement policymakers and regulators in managing AI risks by providing scalable evaluation mechanisms through the financial markets. We have worked with AXA to co-create a transformational research programme that addressed the key interconnected challenges that need to be addressed to create a robust AI insurance model: Risk Assessment and Measurement: This involves evaluating the potential risks associated with AI systems. For AI insurance, this means understanding how AI algorithms perform under various conditions and scenarios and involves quantifying the likelihood of failure or underperformance of algorithmic pipelines. This will require the development of an implementable AI assurance framework to allow robust audit of algorithmic systems across appropriate metrics including model accuracy, bias, fairness, and privacy. Claims Likelihood and Size Estimation: Once risks are measured, insurers need to estimate the potential size of claims and the likelihood of the risk being realised. This involves calculating the possible financial losses that clients might incur if the AI system fails to perform as expected. This estimation is crucial for setting premiums and reserves. This requires precise evaluation of the likelihood and severity of algorithmic systems’ failure across all the key evaluation metrics using scenarios and statistical modelling. Dynamic Insurance Premium Adjustment: Insurance premiums should adjust to the evolving risk profile of AI systems and corresponding claims estimation. As new data emerges and AI systems update, the risk profile changes, necessitating premium adjustments. This strategy ensures insurance products are priced accurately to reflect the true risk while staying competitive in the market. This will require developing algorithms that seamlessly assimilate available data while maintaining appropriate transparency and regulatory compliance.

UKRI Gateway to Research · FY 2025 · 2025-03

In most mountain river catchments, upstream changes in land-use combined with changes in climate are generating increasingly intense floods that deposit large amounts of sand and gravel and scour new channel courses. The distribution of flood waters are much harder to predict in these scenarios, and so new computer models that integrate both water and sediment transport are required. We have run a series of extreme case flood scenarios that incorporate sediment transport for Kathmandu city in Nepal that were published in August 2024. The results indicated that if modeled as floods comprising just water, then the inundation was modest and embankments held back flood waves. In contrast, once sediment was incorporated, channels became choked and spilled into neighbouring floodplains, and new channel courses incised through floodplains. These were experimental models with highly extreme scenarios. However, on the 27th and 28th of September these hypothetical scenarios became a reality when unprecedented rainfall hit the city. The model forecasts described above appear to have under-estimated the impact of sedimentation and erosion during the floods, with embanked channels being filled with sand and gravel, and water breaking through embankments to form new channels through partially developed floodplain regions. This confirmation of the impact of erosion and sedimentation in this setting provides us with a unique opportunity to provide a world leading exemplar of these processes and an opportunity to test alternative hypotheses concerning the drivers of this event. We already have high resolution digital topography in a setting with a high density of meteorological and hydrological stations that recorded the event. We now also have the record of high water mark, sediment thicknesses and erosional scour and the grainsize of the sediment. This means we will be able to test the extent to which sediment was remobilised within the channel systems, or whether additional external inputs from processes such as upstream sand mining and landsliding were a necessary condition for this event. In addition to testing detailed forecasts of sediment-rich flood water impacts, we will have the opportunity to test for controls on the accumulation of sediment throughout the catchment linked to the geometry of river channel networks. For example, where a tributary converges with a main channel, how will the backwater effects in the tributary affect sedimentation, and similarly, areas where there are low gradient channels and gorges both appear to have been impacted by localised enhancement of flood inundation by sediment accumulation.

UKRI Gateway to Research · FY 2025 · 2025-03

Good Scientific Computing and Data Management skills are increasingly important in all disciplines of science, but are rarely taught at undergraduate level to environmental scientists, and students in related domains. This leads to a significant knowledge gap, limiting their ability to work effectively with both data and code which inevitably has a direct impact on the science outputs they are able to produce. It also leads to disparity between researchers in different domains, where these skills are often now taught as mandatory elements in physical science undergraduate degrees. We have significant collective experience in teaching good practices around programming, including testing data analysis, management, and visualisation, and knowledge across a wide spectrum of the NERC domain. We are therefore well placed to provide relevant and engaging courses to researchers who have no experience of programming, and to those who have had some previous exposure to scientific computing, and we will run courses that will appeal to both of these groups. Our plan to run both in-person and online courses, as well as providing appropriate funding, will help attract attendance from groups who traditionally find it difficult to attend multi-day in-person courses. The courses we provide will be fully interactive, with attendees working along with the instructor in real time for the taught components of the lessons. There will be regular exercises for the attendees to have time to consolidate the material, with a high ratio of demonstrators to attendees to ensure that there is sufficient support for those who find the concepts more difficult. Materials for the exercises is domain specific, helping to mitigate against the issue that many non-domain specific training courses have that content appears too abstract, and attendees find it difficult to learn both new concepts and how to align it to their own work. Increasing computing and numeracy literacy amongst PhD students and early-career researchers will not only help with their own research, but they are highly transferable skills and will be extremely valuable regardless of their long-term career ambitions. We hope that it will also lead to other students being encouraged to increase their own skills, thereby improving the overall levels of scientific computing skill within the environmental disciplines. From our own collaborations, we know that this type of training is in high demand in academic, NGO, and public sector institutions and so we will advertise these courses widely to ensure maximum visibility and take-up. We will use our own experiences and lessons learned from running previous courses (e.g. from those run under the ARCHER, Ed-DASH, and SSI grants, which have collectively taught in excess of 5000 students) to guide good practice, and take on board continual feedback to make sure the courses continue to be as useful as possible throughout the timeframe of the grant. From the courses we ran under our previous grants (Essential Scientific Computing for Environmental Scientists: NE/X009211/1 and Essential Scientific Computing for Environmental Scientists 2: NE/Y003799/1), we have received valuable feedback which has enabled us to enhance the content further for the intended audience. Following the success of the Bring Your Own Data day to three of the in-person courses, to provide more focussed support for a small number of attendees with their own research, we will continue to offer these.

UKRI Gateway to Research · FY 2025 · 2025-03

Quantum technology will revolutionise many aspects of life and bring enormous benefits to the economy and society. The Centre for Doctoral Training in Quantum Informatics (QI CDT) will provide advanced training in the structure, behaviour, and interaction of quantum hardware, software, and applications. The training programme spans computer sciences, mathematics, physics, and engineering, and will enable the use of quantum technology in a way that is integrable, interoperable, and impactful, rather than developing the hardware itself. The training programme targets three research challenges with a strong focus on end user impact: (i) quantum service architecture concerns how to design quantum networks and devices most usefully; (ii) scalable quantum software is about feasible application at scale of quantum technology and its integration with other software; and (iii) quantum application analysis investigates how quantum technology can be used most advantageously to solve end user problems. The QI CDT will offer 75+ PhD students an intensive 4-year training and research programme that equips them with the skills needed to tackle the research challenges of quantum informatics. This new generation will be able to integrate quantum hardware with high-performance computing, design effective quantum software, and apply this in a societally meaningful way. The QI CDT brings together a coalition with national reach including over 65 academic experts in quantum informatics from five universities - the University of Edinburgh, the University of Oxford, University College London, Heriot-Watt University, and the University of Strathclyde - and three public sector partners - the National Quantum Computing Centre, the National Physical Laboratory, and the Hartree Centre. A network of over 30 industry partners, diverse in size and domain expertise, and 9 leading international universities, give students the best basis for meaningful and collaborative research. A strong focus on cohort-based training will make QI CDT students into a diverse network of future leaders in Quantum Informatics in the UK.

UKRI Gateway to Research · FY 2025 · 2025-03

Adolescents with ADHD commonly experience difficulties with emotion regulation that negatively impact their mental health and daily functioning. However, there is a notable lack of widely accessible, effective and suitably tailored interventions aimed at improving emotion regulation specifically for this group. To address this need, we co-developed an initial smartphone-based digital health intervention (DHI) prototype for emotion regulation in collaboration with adolescents with ADHD, to help ensure it meets their specific needs. The DHI was informed by a review of the evidence, clinical input, and close collaboration with users. It was designed to address key challenges such as overcoming difficulties with sustained DHI engagement, which may be compounded in adolescents with ADHD. The purpose of the current project is to build our initial prototype into a full intervention prototype, provide an early evaluation of  its promise, identify further improvements, and support the development of a sustainability and scaling plan. The outcome of the project will be a full DHI that will be ready for larger-scale evaluation. The project will act as a critical stepping stone to a widely accessible intervention that can improve emotion regulation and, in turn, enhance mental health among adolescents with ADHD.

UKRI Gateway to Research · FY 2025 · 2025-03

ONS reports (2018-2022) show that, in the UK, workers aged 50-64 are most likely to be absent from work due to ill health, an average of 6.1 days per year per worker (highest of all age groups); collectively 56.3M working days are lost per year. In addition, nearly one quarter of workers aged over 50 who permanently withdraw from the labour market before State Pension Age do so because of health reasons. Another ONS report (November 2024) notes that the majority of people who are economically inactive because of long-term sickness are aged between 50-64, and that this number is growing. Given workers aged 50+ (henceforth referred to as mid-later life workers, MLLW) comprise a third of the UK workforce, with that proportion set to rise with continued demographic trends, interventions focused on supporting health needs in the workplace of this age group are urgently needed. The Supporting Healthy Ageing at Work (SHAW, ES/V016148/1) project carried out interviews with 144 MLLW and their employers in four case study settings, following up with 48 individuals over a year-long co-design process. The research identified that many MLLW felt there was lack of support from employers in relation to their health and well-being needs as they got older. Employers were seen to lack organisational systems, processes and culture through which MLLW felt able to disclose sensitive aspects of health and well-being.  There was a strong unmet need for workplace interventions to support personal and private reflection on own health needs, with sharing information with employers being optional.  On the employer side, frustration was expressed at the seemingly low awareness and take-up of the support they currently offer for health and well-being. The era App was therefore created to help bridge these gaps. era combines validated health measures with AI to help employees explore and reflect on the ways in which their health and work interact, and to take action by matching health needs with appropriate employer support. Employee data are entirely confidential at the individual level, while aggregate data can be used by the employer to target health and well-being support to their workforce (or sections thereof).   The current project aims to advance the path to commercialisation through the following activities: Conversion of existing web-based era App into a native app for mobiles to enhance its commercial potential, features and usability; Improve design specification via gamification – to encourage multiple visits so as individuals can build up a profile of their health and work over time in order to get the most benefit from the app; Widen market research, including emphasis on pricing, competitor analysis, honing distinctiveness etc. Explore different routes to commercialisation with a commercial partner era provides MLLW a way of seeking relevant organisational support without disclosing sensitive self-reported health and well-being information to Line Managers, HR or Occupational Health individuals and processes. It also offers significant benefits to employing organisations. era streamlines and curates access to existing employer health and wellbeing resources – making better use of these resources. Aggregated reports enable organisations to identify where employee health and well-being needs are not being met, allowing for focused workplace interventions to adapt structural barriers to employee needs.

UKRI Gateway to Research · FY 2025 · 2025-03

How can a huge-scale chemical process be managed to guarantee that the largest possible yield of a certain substance is produced? How can we ensure that buildings and other infrastructure are optimally designed? How can fluid dynamics processes be impacted so as to minimize turbulence or maximize flow in a particular region? These, and many other important questions from science, engineering, and industry, may be tackled through the optimization and control of problems involving partial differential equations (PDEs). PDEs are used to describe mathematically how real-world physical systems behave: they can model cell biology, chemical reactions, processes in mathematical finance, fluid flow, quantum mechanics, and a vast range of other processes. What we are particularly interested in is the optimization of such problems, where we apply some external forces on the dynamics so that the system will behave in the 'best' possible way. This motivates the main focus of this project: the study of PDE-constrained optimization, including particular problem formulations which are often referred to as infinite-horizon control or model-predictive control problems. The possibilities such formalisms offer is enormous, driving cutting-edge research in engineering, systems biology, chemical processes, imaging, and many other fields. Whereas many such problems can be clearly stated on paper, accurately resolving them on a computer is a very important, and difficult, challenge. Indeed, for many problems with information provided at a very fine level, in particular resulting from processes driven by vast quantities of data, the resulting systems of equations are of such enormous scale that producing accurate numerical solutions can be intractable. This work seeks to resolve this challenge, by bringing to bear modern technologies from the field of numerical linear algebra, in particular through the timely and exciting research area of randomized linear algebra. The exploitation of current methodologies can ensure the generation of robust solutions in real-time, while minimizing computer storage requirements, and often enabling the use of parallel computing. The usage of randomization within solvers for PDEs themselves has been well established, however the development of such solvers is so far an underexplored area for optimization and control problems where the PDEs act as constraints. We will meet this outstanding challenge through four ambitious work packages: (i) using randomization in eigenvalue iteration for parabolic PDEs, an important class of PDEs which describe diffusion-driven processes in particular; (ii) randomized features within iterative methods for modelling processes with nonlinear phenomena; (iii) randomization within model-order reduction for PDE-constrained optimization, where the computational complexity of the model itself is reduced to make feasible a range of numerical algorithms for the solution; (iv) the use of randomized solvers for problems which have uncertain inputs. The final package will bring together all of the previous work, devising an overarching framework for treating optimization problems with randomness built in. Our new algorithms will be analysed theoretically and validated numerically, on a wide variety of huge-scale problems. Interaction with industry and across academic disciplines is a key outcome. Industry impact will be generated in collaboration with project partners FESTO and Arup, with whom we will apply our methodology to optimization and control problems that have a key link to national economic challenges. We will release code libraries, and organise a workshop with academic and industrial invitees, to further enhance the scientific and commercial impact of these new developments.

UKRI Gateway to Research · FY 2025 · 2025-03

The low surface brightness peripheral regions of galaxies contain a gold mine of information about their assembly histories, reflecting how minor mergers and accretions have influenced their evolution over cosmic time. Enormous stellar envelopes and copious amounts of faint tidal debris are natural outcomes of the hierarchical assembly process - the quantitative study of these features, while extremely challenging, offers tremendous potential for gaining insight into the detailed histories of galaxies. I have played a leading role in groundbreaking work that helped to establish and develop this line of research but shortcomings in the previously available datasets (e.g. sample size, surface brightness depth), and the often-disjoint analyses of observations and numerical simulations, have thus far limited the conclusions that can be drawn. My exceptionally timely project MARGO will use state-of-the-art data from world-leading facilities and the forthcoming Euclid and LSST surveys to accurately determine the properties of the faint outskirts of galaxies throughout the local Universe and use them as a new tool to rigorously test the current galaxy formation paradigm. The approach of MARGO is three-pronged, combining precision analyses of the resolved stellar populations in the halos of the nearest systems beyond the Local Group with unbiased integrated light studies of tidal debris in large statistical samples. Fossil information about past accretion events in galaxy peripheries will be extracted and compared to cosmological simulations of structure formation to stress test their predictions on small scales. Critical to the success of the project is the development of a new methodology to detect faint tidal features in large galaxy samples using machine learning., MARGO will transform our understanding of low surface brightness galaxy outskirts and finally enable us to place the particular history of our own Milky Way in context.

UKRI Gateway to Research · FY 2025 · 2025-03

The Milky Way is currently the only galaxy resolvable on a star-by-star basis with large statistical samples, making it the perfect testbed for exploring the structure of galaxies. Some of the pivotal open questions that still remain unanswered regarding galactic structure are: how much mass and dark matter do galaxies contain, and how is it spatially distributed? Under the assumption of a simple and time-invariant potential, many galactic dynamics techniques (e.g., Jeans or Schwarzchild models) infer the Milky Way's mass and dark matter content and distribution from stellar kinematic observations. These methods typically rely on parameterised potential models of the Milky Way and must take into account non-trivial survey selection effects, because they are making use of the density of stars in phase space. Large-scale spectroscopic surveys now supply information beyond kinematics in the form of precise stellar label measurements (especially element abundances). These element abundances are known to correlate with orbital actions or other dynamical invariants, and in many cases can be measured without detailed knowledge of the stellar selection function, therefore making element abundance gradients less sensitive to selection function effects. This proposal aims to: 1) synergise the vast amount of spectro-astro-photometric Milky Way data from the Gaia satellite mission and large-scale spectroscopic surveys; 2) build on the Orbital Torus Imaging (OTI) framework that uses element abundance gradients in phase space, and construct a data-driven generative model to measure the spatial, orbital, and mass distribution in the Milky Way; 3) use OTI to measure the amount of dark matter across the Milky Way; 4) use OTI to measure the amount of disequilibrium in the Milky Way. The results from this research programme will place constraints on current galaxy formation models.

UKRI Gateway to Research · FY 2025 · 2025-03

Apicomplexans are a group of obligate intracellular parasites that place an enormous burden on human and animal health, causing diseases of global importance such as malaria, toxoplasmosis and cryptosporidiosis. Malaria is caused by Plasmodium spp and results in >600,000 deaths annually. Toxoplasma gondii, the causative agent of toxoplasmosis, causes fatal encephalitis in those with weakened immune systems and causes congenital toxoplasmosis, resulting in serious birth defects and stillbirth, with >200,000 cases recorded annually.  Frontline drugs have many drawbacks including severe side effects, evolution of resistance and incomplete clearance of chronic stages of the parasite, particularly in the case of Toxoplasma. New drugs and therapeutic interventions are urgently required. Many existing drugs target metabolic pathways in the parasite that are absent, or at least highly divergent, in the host. Therefore, understanding parasite metabolism, and the key areas it diverges from the host, is important for developing new and effective therapeutic strategies. Intracellular parasites must fulfil their metabolic needs by stealing nutrients from the host environment. A key nutrient class are sulfur-containing metabolites, which includes many vitamins, cofactors, amino acids and glutathione. Sulfur containing metabolites are essential for cell function, playing central roles in crucial life processes such as redox control, respiration, DNA metabolism, and protein translation. Acquiring sulfur metabolites from this host is essential for the parasite to perform all of the biochemical processes it needs to replicate and cause infection. Nutrients are taken up by the parasite by specialised transporter proteins. Transporters present in the host are often absent in the parasite, as they have evolved novel parasite-specific transporters. Transporters are particularly abundant hits in drug screens, and numerous medications target transporters, making parasite transporters of essential metabolites a potentially rich set of targets. Identifying and understanding how parasitic transporters work is therefore important, although to date few have been characterised in detail. Despite its importance for parasite survival how Toxoplasma acquires sulfur-compounds from the host cell environment has not been explored. Using Toxoplasma gondii as a tractable apicomplexan model, I will address two fundamental questions about parasite sulfur metabolism: how the parasite acquires sulfur nutrients from the host environment and how these resources are integrated and used during infection. To achieve this, I will identify parasitic transporters of sulfur metabolites through proteomic approaches and understand how they work through a series of cutting-edge biochemical and structural investigations. Then, using a diverse array of molecular parasitology and metabolomics approaches, including making mutants of key transporters, I will study how these transporters are used by the parasites and their importance for parasite fitness. I will then study key enzymes required for integrating sulfur into parasite metabolism, through the sulfur assimilation pathway. The biosynthesis of key sulfur metabolites, cysteine and glutathione, will be explored, with particular focus on their importance in the understudied chronic life-stage of the parasite. Together, this work will reveal how Toxoplasma obtains a key unstudied class of nutrients and advance our understanding of a major knowledge gap in parasite metabolism. The findings will uncover novel underlying biology of an important human pathogen, likely applicable to other apicomplexan parasites and infection models. The more we learn about how parasites scavenge and metabolise key nutrients, the better we are able to develop new and effective therapeutic strategies; therefore this work and has the potential to uncover attractive therapeutic drug targets.

UKRI Gateway to Research · FY 2025 · 2025-03

The goal of this proposal is to develop and apply cutting-edge RNA technologies to test new vaccine strategies against gastrointestinal nematodes, while advancing frontier bioscience on how these parasites use their own RNAs to modulate the host environment to increase survival and transmission. Vaccines are the most cost-effective method to combat infectious disease in humans and animals. Currently, there are no vaccines licensed for soil-transmitted helminths in humans, even though ~1.3 billion humans suffer morbidity due to infection. There are also no vaccines licensed for gastrointestinal nematodes that are suitable for scalable commercial production in livestock, despite the significant impact on food security and the huge economic losses associated with infections. Our approach addresses two potential causes of this gap: (i) the striking ability of gastrointestinal nematodes to manipulate and evade host immunity and (ii) the substantial effects of genetically and ecologically diverse host and parasite populations that exist outside of the lab on vaccine responsiveness. We discovered that gastrointestinal nematodes have evolved novel RNA interference and RNA export pathways that enable them to evade host immunity and survive in the host. Our data suggest that parasites use a diverse suite of RNAs to alter the host environment. We have developed a vaccine strategy to target an Argonaute protein (exWAGO) that is required for parasite RNAs function. Our preliminary data indicate that this is the Achilles heel of the RNA transport mechanism and we predict that targeting exWAGO in combination with extracellular vesicles will provide a robust strategy to block all nematode RNA transmission to the host. Our goal is to generate a bivalent vaccine with exWAGO and SID-2, a membrane protein expressed on the surfaces of extracellular vesicles, using RNA technologies that are amenable to multiplexing and future scale up in manufacturing. The proposed research will provide the first real-world test of an RNA vaccine against a helminth. We will test the immunogenicity of exWAGO and SID-2 RNA vaccine constructs in C57BL/6 mice (Aim 1) and their protective capacity when administered individually or in combination followed by parasite challenge (Aim 2). Once we have optimised the bivalent vaccine in the laboratory model, we will then move to testing vaccine efficacy and the consequence of blocking RNA transmission in real-world conditions of H. polygyrus infecting Apodemus sylvaticus (wood mice; Aim 3). This model allows us to address the second gap: the impact of host, parasite and environmental variation on vaccine responsiveness.  We hypothesise that parasites sense and respond with transmitted RNA to variable host/environmental conditions and that, by blocking all RNAs that the parasite transmit, this vaccine approach may prevent the parasite from modulating the host for its own adaptation/survival. We will employ both controlled laboratory and field studies and in parallel use small RNA sequencing analysis to directly test whether and how vaccination blocks parasite RNA trafficking to host cells  in vivo. This project integrates three BBSRC priority areas: we will develop and implement transformative RNA technologies to advance understanding of the rules of life using a unique animal model to understand the role of RNA communication in a natural ecological system. We use these advances in bioscience to develop new vaccine strategies for sustainable agriculture and food.  

UKRI Gateway to Research · FY 2025 · 2025-03

Food is essential to life. People have become increasingly aware of the environmental impact of producing and consuming food through, e.g., greenhouse gas emissions, use of land and water resources or chemical pollution. Current challenges include feeding a growing population without damaging the planet, tackling the rise of diet-related diseases, and providing a diverse range of safe, tasty, and nutritious foods. These challenges call for a worldwide food transition towards more sustainable food products and processes. Nowadays, a successful new food product must address several criteria to meet the consumers' demands and needs: having the expected sensory properties, being nutritious and healthy, and be sustainable. Healthy foods are often associated with clean label foods comprising a reduced number of natural ingredients, and no artificial ingredients or synthetic additives, and to foods less rich in lipids (especially saturated fat from animals), salt and sugars. Sustainability throughout the whole value chain of food systems is a global issue, covering notably food production, transport, processing, distribution, marketing and consumption (as acknowledged in the EU Green Deal and Farm to Fork strategy). Sustainable and healthy food implies notably a transition from a diet rich in animal-based ingredients towards a diet enriched in plant-based ingredients. This is the challenge behind the Edible Soft Matter (ESM) project. Understanding, designing and producing the innovative food of tomorrow requires a fundamental knowledge of the functional properties of novel raw food materials and ingredients, of the way these food ingredients interact, assemble and respond to chemical, physical, and mechanical processes to form complex multiscale, multicomponent materials, with targeted properties. Major advancements require going beyond trial and error approaches to formulate new foods and to gain a detailed knowledge of the multiscale/multicomponent interplay and the impact on the structure/functionality relationships using food science and soft matter science. The fundamental concepts, scientific approaches and technical tools developed in soft matter science are uniquely adapted to address these requirements. The main building block of foods, namely proteins, polysaccharides and lipids, present intriguing analogies with the main building blocks of any soft materials, namely colloids, polymers and surfactants. Furthermore, texture as well as human sensory perception can be understood as a complex interplay between the multiscale structural and mechanical properties of a product. Soft matter science is a key scientific field to unveil this interplay but also its link to sensory evaluation and to elucidate and tailor the intricate structure-function relationship in foods. The ambition of ESM is to bring upstream advancements in various aspects related to the needed transition towards plant-based food using food science in conjunction with fundamental soft matter science. Soft matter science has been tremendously successful in tackling several complex problems involving multicomponent materials with a wide range of length and time scales through statistical physics, scaling laws and multiscale description. It therefore provides unique perspectives for the interpretation of the complexity of foods and for a rational design of new foods. The ESM consortium believes that combining tools and concepts from a soft matter approach to those of food science is key to making major advances. This frontier science will deliver novel experimental and modelling tools for the food science community, uncover a mechanistic understanding of structural and functional diversity of edible soft materials and provide a paradigm shift in the design of innovative foods.

UKRI Gateway to Research · FY 2025 · 2025-03

Worldwide, the proportion of older people in human populations is growing rapidly: based on WHO estimates, between 2015 and 2050 the proportion of the global population over 60 will double. As age is the predominant risk factor for the majority of pathologies, this growth will be accompanied by widespread health challenges. I propose to widen the availability of tools to identify general drivers of enhanced risk - across vertebrates - by considering organisms and contexts that have previously been overlooked. I will achieve this by developing epigenetic ageing clocks for birds and leveraging on the numerous detailed long-term studies, from which biological samples and metadata are available, on the impact of environmental factors such as diet, infection, climate, urbanisation and industrial pollution.   Epigenetic clocks have revolutionised the fields of ageing and gerontology, and have opened new research avenues such as the area of epigenetic rejuvenation. These tools enable the measurement of biological ageing - the rate of physiological and molecular ageing of a tissue or a whole organism, by accurately quantifying age-related changes of chemical marks on DNA. The ticking rate of such clocks is not constant, as methylation is highly sensitive to environmental and life-style factors - infection, dietary factors, physical activity, reproductive measures and lifestyle stresses can cause age acceleration or deceleration. Yet there remains much to be learned about how the broad or direct environment affects the rates of ageing. Classical ageing research models such as the fruit fly, fish and rodents, pose limitations to the study of external environmental factors in the natural environment, as they are usually studied in a single context (the lab) and the results are not always translated to other vertebrates or contexts. Expanding methylation studies to other vertebrate systems will allow us to identify a much greater range of intersecting environments and stressors that impact ageing.   It has also been recently shown that mammals undergo an age reset very early in their embryonic development, which is likely a universal phenomenon, speculated upon since the development of Dolly the Sheep from aged cells. How the environment affects this reset is not yet studied, and mammals represent a challenging system to do so. Birds are a long-standing early development model system that can overcome these challenges. Epigenetic clocks, however, are not yet developed for any common bird model.   I propose to make epigenetic clocks for avian research to study the environmental effects on ageing, both during pre-natal development and adulthood. My objectives are:   to develop and benchmark epigenetic clocks for three common bird model species where experimental or environmental data is available to probe for drivers of accelerated age develop a pan-avian clock through further data harvesting for a diverse range of species as a general tool with broader use   This work will generate new knowledge to progress our understanding of the rules of life and the fundamental biological mechanisms responsible for early developmental age reset, age-related degenerative processes and the environmental factors that affect them. Epigenetic clocks will be also applicable in the context of infection, evolutionary biology, bird ecology, conservation, and agriculture. Given our ageing population, this knowledge is critical to progressing world-leading research that can be applied to wider societal and environmental benefit. The benefits of avian epigenetic clocks are thus far-reaching and extend beyond fundamental biology and ageing.

UKRI Gateway to Research · FY 2025 · 2025-03

Aging is associated with a decline in the ability of cells to degrade unwanted material. The build-up of undegraded material in cells can result in their dysfunction and is therefore associated with various aging-related diseases, including neurodegeneration and cancer. One of the major cellular hubs that mediate degradation processes is known as the lysosome. Lysosomes are specialised compartments that can degrade a wide range of substrates through the activities of specific enzymes. This localised activity of enzymes in lysosomes is essential to regulate their function. Therefore, cells have developed various mechanisms to deliver enzymes to lysosomes and ensure their restrained activity. In this proposal, we aim to understand how lipids are degraded in lysosomes. The degradation of lipids is mediated by a subset of enzymes known as lipases. We have identified a novel mechanism in cells that delivers lipases to lysosomes. We aim to understand the molecular bases of this mechanism and what happens in cells when it is disrupted. We will address whether enhancing this lipase delivery pathway can prolong longevity in order to confirm its relevance during aging. This proposal aims to understand mechanisms underlying aging and we predict that our findings may help us improve healthy aging in humans. Our goal is to uncover the molecular details of how our cells function and remain healthy in order to help us design methods to improve healthy aging and delay the onset of disorders in humans. The findings and tools generated during the course of this study will also have wider implications and utilities across multiple research areas.

UKRI Gateway to Research · FY 2025 · 2025-02

Influenza A virus (IAV) is a ubiquitous virus in wild birds that poses a constant infection threat to domesticated animals and humans. In the majority of cases, the avian strains of IAV do not replicate well in mammals and cause little to no disease. More rarely, they can infect and cause severe disease, but cannot efficiently spread from the initially infected animal or person. However, the virus can evolve to become fully transmissible in the new mammalian host and this poses the risk of provoking a global pandemic if the virus jumps into humans - as happened in 1918 and again in 2009. Surveillance can identify these dangerous strains of IAV at the earlier stages when they can only cause limited infections, but it is currently impossible to predict the risk of the virus evolving further to reach pandemic status, or to predict how virulent it might be if it did. This project aims to fill this knowledge gap by studying three strains of IAV that are currently causing concern: H5N1 highly pathogenic avian influenza, H3N8 low pathogenicity avian influenza and H1N1 G4 swine influenza. These viruses have already evolved to be capable of infecting humans and/or transmitting between other mammal species, so we will use a combination of molecular virology and computational biology approaches to understand how they have evolved to reach this threat level. We will determine the viral genome sequence features that set how the three key parameters of virus behaviour - ability to replicate, transmit and cause disease - are interlinked by creating mutant versions of them and studying these phenotypes. Importantly, because these strains of IAV have already evolved transmissibility, we can do these experiments safely by using "loss-of-function" approaches in which we aim to make the viruses less dangerous. State of the art computational approaches will quantify the results of the laboratory experiments and place them into the broader context of the global efforts to understand influenza, with the aim of producing computer models able to threat assess the likely behaviour of future strains of IAV as they appear.

UKRI Gateway to Research · FY 2025 · 2025-02

The proposed research addresses the urgent public health crisis of bacterial pathogens that are resistant to treatment with antibiotics. Currently, it is not well understood if and how bacteria and their resistance genes spread between humans, animals, and the environment. Using a well-structured sampling framework we will compare the diversity of bacteria and their resistance patterns in Scotland (UK) and Chongming Island (China) to identify the drivers that shape the observed distributions. By analysing their DNA sequences and tracing their evolutionary history, we can learn more about how they move between people, animals, and the environment. This knowledge will help us refine our understanding of how infections and antibiotic resistance spread.Our project also aims to develop new ways to estimate the risk of transmission of antibiotic-resistant bacteria. By using advanced mathematical models, we can identify the sources and transmission routes. These scientific findings will provide insights that are relevant to policymakers. By understanding how antibiotic-resistant bacteria spread, we can develop better policies and interventions to limit the spread of infections and reduce the threat of antibiotic resistance.

UKRI Gateway to Research · FY 2025 · 2025-02

Knowledge of causal processes is vital for all aspects of our lives, from mundane consumer choices to high-impact socio-political decision making. Much of our causal knowledge is acquired not from individual experience, but from cultural transmission via language. While theorists have amassed a large body of philosophical and psychological understanding about causation, surprisingly little research has been devoted to a theoretical understanding of the processes that underlie communication of causal information and the role of the linguistic signal in this transmission. The main objective of this project is to apply methods and tools from experimental pragmatics to shed light on a wide range of puzzles about causal language and cognition. We introduce a new pragmatic framework, the "CommuniCause" approach, which makes new and empirically testable predictions and offers a unified explanation for a number of disparate phenomena, both old and new. CommuniCause brings together two important strands of research that have been isolated until now, in a way that will benefit both communities. It draws on established philosophical theorizing and recent computational models of individual causal cognition, but is distinguished by its focus on linguistic factors: the speaker's choice among the variety of linguistic expressions available, and the impact that this choice has on a recipient's pragmatic interpretation. CommuniCause promises advances to linguistic pragmatics as well, by confronting theories and models with a range of intricate puzzles that have not previously been treated from a linguistic perspective. The project explores the extent to which this pragmatic approach can explain key features of causal inference. One is the problem of causal selection, how we identify one event as the cause of another. When two cars collide, why do we think that the driver that ran the red light was "the cause" of the accident, rather than the safe but unlucky driver? Another puzzle involves the interpretation of correlational evidence: Why do people interpret "Aspartame is linked to cancer" as implying that aspartame consumption causes cancer, and not the other way around? The CommuniCause perspective suggests treating these puzzles as traces of pragmatic reasoning: in interpreting what others have said, we can use what we know about how speakers make choices to infer what they are probably trying to convey. In a number of experiments, we explore the detailed predictions of the framework for how speakers make complex choices among various ways of expressing themselves, how causal and non-causal language is interpreted in context, and how linguistic framing influences causal reasoning processes. If these results validate our approach, we can conclude that language matters in causal thought and talk to a much greater extent than previously realized. A particularly interesting contribution of this project with important practical implications is the juxtaposition of causal and non-causal language. We investigate the conditions under which speakers choose non-causal expressions (e.g., "If A, then B" or "A is associated with B") to convey causal meaning, and the circumstances under which listeners infer causal information from expressions that are merely correlational. Contrary to widespread conception, we do not consider causal inference from non-causal language a fault or an irrationality. Rather, the CommuniCause approach is able to shed light on the efficiency and systematicity of this phenomenon, thereby providing a better grip on avoiding miscommunication between domain experts and lay audiences in important areas like health communication.

UKRI Gateway to Research · FY 2025 · 2025-02

Symbiotic microbiomes play a central role in many biological processes and are intrinsically linked to host health. The composition of host-associated microbiomes is mediated by host genetics, which is particularly relevant to wild systems in the face of global climate change and rapid population declines. It is thus crucial to understand how changes in genetic diversity impact host-microbiome interactions. Achieving this goal in wild populations requires samples that span decades to centuries of population declines, yet host-associated microbiomes often do not preserve after host death. To address this significant knowledge gap, we will utilise dental calculus, the calcified oral microbiome, from museum-preserved specimens of Scandinavian brown bears that experienced a dramatic population bottleneck over the course of the last 200 years. Preliminary research in our group found an inverse relationship between the prevalence of dental caries (cavities resulting from tooth decay) and population size. The main research objectives of MetaBear are to investigate i) the role of host population genomics in the prevalence of oral disease, ii) how population declines and host genetics shape oral microbiomes, and iii) the evolution of oral pathogens and emergence of virulence factors. In a world first, we will integrate state-of-the-art ancient DNA techniques with metagenomics, population genomics and phylogenomics to establish a new field of research - Temporal Hologenomics, the study of hosts and microbiomes over time. Insights from MetaBear are intrinsically interdisciplinary and will have direct applications to conservation and evolutionary biology, as well as EU Green Deal and UN Sustainable Development Goals strategies. The open-access Temporal Hologenomic bioinformatic pipelines developed in this project will be taught in dedicated workshops, enhancing the uptake of this approach in evolutionary, clinical and conservation biology.

UKRI Gateway to Research · FY 2025 · 2025-02

Context In a world where the number of forcibly displaced people is at an all-time high, reaching over 110 million people in 2023, there is a critical need to identify means to keep those people safe and healthy as well as empower them to maintain or return to their livelihoods. Given the increasing trends of global climate disasters and conflict this is likely to only increase in severity and so timely research and action is needed. The majority of refugees in Kenya come from a rural background yet livestock in refugee camps have been little researched, likely owing to a sense of urgency during crises which sees immediate life-saving initiatives prioritised. However, living in displacement has become a chronic situation for many and so investigation of such is overdue. By exploring and quantifying the nutritional impact of livestock-keeping in refugee camps, this project will shine a light on an under-researched area and potential avenue out of malnutrition and displacement. In a sector with no room for failure without costing human lives, and with tightening budgets from donors, it is crucial to optimise humanitarian planning. This is where excellent, rigorous research is needed to empirically demonstrate the potential positive or negative impacts. This aligns with the global and population health areas of scientific remit of the Medical Research Council (MRC). Aims of the research The overarching aim of this research is to investigate the benefits and risks of livestock keeping among refugees in East Africa. It will explore this through achieving five objectives: Evaluate critically the current literature on livestock’s role on refugee health, nutrition, and livelihoods. Measure the difference in child nutritional outcomes between refugee households who own livestock and those who do not. Explore refugee perceptions of livestock ownership in the refugee camp context. Explore the causal relationships between livestock ownership and child nutritional outcomes in a refugee camp context. Formulate evidence-based recommendations for decision-makers and project-staff on livestock in refugee settings. It will achieve these in a novel way through three connected experiments. Firstly, a systematic literature review will be conducted to synthesise existing literature and valuable insights. Secondly, through a cross-sectional, observational study of nutritional outcomes and household characteristics in Dadaab Refugee Camp, Kenya. Lastly, through system dynamics modelling and fuzzy cognitive mapping to explore the wider impacts of livestock ownership in the camp context and causal relationships leading to nutritional outcomes. Potential application and benefits This study will for the first time gain empirical evidence on the nutritional impact of livestock ownership in the refugee camp context and the causal relationships behind this. Through identifying target areas for enhancing refugee child health and improving livelihood opportunities, this research has the potential to positively benefit displaced communities both in the short and long term. The work proposed in this application has the opportunity to impact humanitarian and global health planning across non-governmental organisations, international organisations such as the United Nations, as well as influence national and international policy. While based in Kenya, this study's findings can be applied to many contexts across sub-Saharan Africa and the Middle-East. As a result, it has the potential to improve the lives of millions of displaced people who are reliant on livestock for their nutrition, their children's nutrition and for their livelihoods.

UKRI Gateway to Research · FY 2025 · 2025-02

In December 2023, at COP28 in Dubai, the Food and Agriculture Organisation of the United Nations launched a new 'Global Roadmap' with a plan for attaining global food security by 2050 without breaching 1.5C. The enormity of this task was captured in an analysis finding that even if fossil fuel emissions were immediately halted, current trends in agri-food systems would prevent the achievement of the 1.5C target. Despite the urgent need to transition to sustainable agri-food systems to meet human nutrition, net zero, and biodiversity goals, there continues to be a massive implementation failure. Over the past 3 years, I have been evaluating a unique government programme in the state of Andhra Pradesh, India, called 'Andhra Pradesh Community-managed Natural Farming (APCNF)'-previously 'Zero Budget Natural Farming (ZBNF).' Through this programme, the government aims to transition the entire state-home to more than 50 million people including 6 million farmers-to organic farming. My project, entitled, BLOOM (Co-Benefits of Largescale Organic Farming On HuMan Health), aims to determine if APCNF is an effective approach to transforming agri-food systems for health and sustainability. In collaboration with the state government and Ashoka University, I am leading a cluster-randomised controlled evaluation of APCNF. The two primary outcomes are urinary biomarkers of exposure to pesticides and dietary diversity. Secondary outcomes include crop yields, household income, adult body mass index, blood pressure, anaemia, type 2 diabetes, kidney function, musculoskeletal pain, clinical symptoms, depressive symptoms, women's empowerment, and child growth and development. As part of the Fellowship renewal, BLOOM participants will be followed for an additional 2 years for a total of 5 annual assessments (2022-2026). The biggest challenge to date has been low uptake of organic farming by farmers in BLOOM's intervention villages. The main innovation of the Fellowship renewal is to adapt tools from implementation science to understand barriers and facilitators to adoption of organic farming practices. Implementation science arose from the evidence-based healthcare movement, and is the scientific study of methods to promote the systematic uptake of research findings into routine practice. The Fellowship renewal will provide me with the necessary support and flexibility to further leverage my background in public health, gain skills in implementation science, and apply them to agri-food systems. The way we produce food has changed rapidly within a generation. We have achieved what few thought we could in terms of increasing productivity. There is reason to believe, with strong scientific evidence, societal demand, and political will, that we can transform agri-food systems again over the coming decade to meet human nutrition, net zero, and biodiversity goals. But this will require investment in R&D because there is not a clear pathway toward transformational outcomes. The BLOOM project will provide rigorous scientific evidence regarding the population health co-benefits of organic agriculture and how to take evidence of impact to scale. Given that we do not anticipate that the UK will transition entirely to organic cultivation, this represents a unique scientific opportunity to learn from a state-of-the-art cluster-randomised controlled evaluation, the benefits and unexpected consequences of such practices. Overall, findings from BLOOM will have important implications for countries around the world looking for evidence-based solutions to failing agri-food systems.

UKRI Gateway to Research · FY 2025 · 2025-02

The architecture and deployment of mobile networks has undergone remarkable transformation in recent years through disaggregation in various forms, that in turn led to a growing diversity in the vendor ecosystem as evident with Open RAN. As we head towards 6G, we envision that this path to openness in mobile networks should continue to become holistic to focus on data-driven RAN control leveraging AI as well as with an expanded scope to bring in its fold openness to the mobile core architecture as well as in the operator ecosystem leveraging private networks. Doing so will unlock unprecedented efficiency gains, enable greater automation, result in significant cost savings and make nextG network infrastructure environmentally sustainable. In this project, we set out to address the whole host of technical challenges to enable this bold vision. The project team with partners in the UK (University of Edinburgh) and across India (IIT Hyderabad and IIT Dharwad) reflects a synergistic union of expertise spanning mobile networking system designs, AI for mobile networks and testbed driven experimental research. Systems and methods developed in this project will be prototyped and evaluated at scale through a campus-scale O-RAN compatible experimental private 5G network in Edinburgh.

UKRI Gateway to Research · FY 2025 · 2025-02

Money, despite being the central medium of exchange, unit of account, and store of value in society, is virtually absent from many of the new data infrastructures being developed by UK research bodies to serve research communities over the coming decades. Even in surveys or censuses, the difficulty of collecting financial information at snapshots in time has meant that financial data is often limited, sometimes inaccurate, and rarely timely. Yet this data has enormous potential to support research across a variety of scales; for example, the impact of macroeconomic shocks on household finances, the effects of extreme weather on small-scale enterprise cashflows, the affordability of the transition to Net Zero, or the way we take from or give to our own futures. In comparison with other sectors, the financial industry—in part due to stringent regulation and constant innovation—typically holds high-quality and timely data, making it near research-ready1. However, data sharing between the private sector and academia is difficult, resource-intensive, and is not supported by any coordinating or supporting agency. This is true despite the cross-sector efforts of the open finance and open data movements highlighting clear demand for new research and innovation over the past decade2. At the same time, many researchers are often unaware of the opportunities that this type of data provides. The University of Edinburgh (UoE), working through Smart Data Foundry (SDF) and EPCC (formerly the Edinburgh Parallel Computing Centre) has developed, over the past five years, a proven approach to gaining researcher access to financial data. Building on the Edinburgh and South-East Scotland City Region Deal, the Data-Driven Innovation Initiative, and UKRI Strength in Places Funding, we have created a service through which researchers can securely access financial data about both consumers and businesses and see their research through all the way to generating concrete impacts. SDF was founded to manage and provide this service with this UKRI funding, with a mission to open financial data for good. However, scaling this provision to a national service is an ambitious aim that will require significant additional investment. The aim of the Financial Data Service (FINDS) project is to make financial data readily available to researchers across the UK, turning it into a fundamental tool for research by the end of the decade. With SDR UK support, we would achieve this through: Growing our data relationships with leading industry data partners, Providing a high-quality, safe, secure, and user-centred service that optimises research-ready data, promoting a culture change towards novel data use in research, Collaborating closely with other data services, Innovating and safely normalising privacy-preserving data linkage, and Providing impactful research-driven insights that enhance policymaking in the UK, in a way that is demonstrably trusted by the public. The potential applications of this project are wide-ranging and enhanced by the near-real-time capabilities of this data source. Researchers can see the effects of macroeconomic shocks or targeted policy interventions practically as they happen, allowing for better policy and more efficient allocation of resources for societal betterment. As we continue to unlock these high-value financial data assets, we can continue to propel progress in key thematic areas of prosperity, health, and sustainability. Now is a pivotal time to invest in data to create a better future.

UKRI Gateway to Research · FY 2025 · 2025-02

This project aims to build a new model to incorporate satellite radar data into groundwater applications by translating surface deformation measurements into groundwater flow paths and fluxes. This requires subsurface structures and total water storage changes constrained by geophysical imaging, satellite gravity, and hydrological measurements. We have pulled together a brand-new interdisciplinary partnership with colleagues specialising in geodesy, hydrology, hydrochemistry, and geophysics. This partnership allows us to conduct a proof-of-concept study in the Gobi Desert. We will use our prior velocity mapping with the Sentinel-1 data to guide our data collection and fieldwork in China which will be led by our Chinese partners and joined by the UK partners. We will also welcome the Chinese partners to the UK to co-develop the model using the most comprehensive geodetic, hydrological, and geophysical datasets. We will organise workshops in both the UK and China to expand our networks on groundwater science and management and foster long-term stakeholder partnerships and wider applications.

UKRI Gateway to Research · FY 2025 · 2025-02

In an economy in which the UK software industry added £139 billion of value to UK GDP in 2018 alone, this fellowship will transform the way developers write software. By offering a radically new way of composing and customising programs, I will empower software developers to build more flexible, maintainable, and robust software. Computers must interact with the real world. In computer programs real world effects are pervasive, e.g.: concurrency (performing two computations at once), distribution (performing computation in different places), input, output, and probability (e.g. for machine learning). Effect handlers are a general programming feature that can be used to implement all of these effects. They were introduced by theoretical computer scientists as part of a mathematical model of effects. Thanks in part to my efforts they now show promise as a practical programming tool. Interest in effect handlers in industry is growing. For instance, Meta's React Fiber, the core of the market-leading React user interface library for web applications, is directly inspired by effect handlers, and Uber's Pyro tool for probabilistic programming and statistical inference makes essential use of effect handlers. Preliminary results suggest effect handlers have the potential to support efficient implementations. Nevertheless, existing implementations are in their infancy and research is required to make them scale, both in terms of ease of programming and in terms of performance. I will develop the theory and practice of Effect Handler Oriented Programming as a uniform foundation for modular and efficient implementation of effects. I will create both high-level (for humans) and low-level (for machines) effect handler designs and implementations. In collaboration with my project partners I will ensure that EHOP has direct impact through two key technologies. + OCaml. OCaml 5 (released 2022) is the first industrial-strength language with efficient native support for effect handlers, and this support is already bearing fruit, e.g, the Eio 1.0 library (2024) depends on effect handlers to offer seamless high-performance fine-grained control over a range of concurrency and asynchronous I/O features. I will develop an ergonomic effect type system for OCaml, enabling more flexible, maintainable, and robust software to be written in OCaml. Eventually these benefits will transfer to other languages, ultimately improving the user experience for billions of end users. + WebAssembly. I am designing and implementing an effect handler extension for WebAssembly, a portable low-level bytecode supported by the top four browser vendors and designed to supersede JavaScript as the target language for the web. Currently, languages such as JavaScript provide a collection of ad hoc overlapping concurrency features, each of which is hard-wired and must be maintained separately. However, all of them can be implemented with minimal effort using effect handlers. Rather than hard-wiring and maintaining several ad hoc features, compiler developers will be able to rely on a single implementation of effect handlers in WebAssembly. This will enable more flexible, maintainable, and reliable programming language implementations, ultimately improving the user experience of billions of web users. A "killer app" for effect handlers is concurrency and distribution, central to which is communication. For communication to be safe, secure, and reliable, all parties must comply with appropriate protocols. Session types are a nascent technology for enforcing protocol compliance. Unifying the two main threads of my research over the last decade, I will extend the theory and practice of effect handlers to enable session-typed concurrency and distribution features to be defined as effect handlers. Ultimately, this will enable safe, secure, and reliable communication infrastructure for billions of end users.