IMPERIAL COLLEGE LONDON

UKRI Gateway to Research · FY 2025 · 2025-09

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

UKRI Gateway to Research · FY 2025 · 2025-09

Dementia is a global health challenge, with an estimated 55 million individuals globally, projected to increase to 152 million by 2050. The leading cause of dementia is Alzheimer’s disease (AD), a neurodegenerative disease accounting for 60–70% of all dementia cases.  There is an urgent need for a therapeutic breakthrough that stops and even reverses the cognitive decline in a broad range of AD patients. Since cognitive functions arise from the interactions between many neurons organised in circuits, the central question of this project is how AD-induced abnormalities in individual neurons eventually impair the function of the embedding circuits. We hypothesise that neural hyperexcitability contributes to the pathogenesis of cognitive impairments in early-stage AD. Toxin aggregates trigger neural hyperexcitability but escalate by a deficit in homeostatic plasticity during sleep. This project aims to establish the scientific evidence of the neural plasticity mechanism in people with early AD and then demonstrate a neuromodulation strategy to ameliorate it. It involves a stepwise experiment that includes two studies with repeated measurements of neural activity during sleep, neural excitability, and cognitive performance before and after in a cohort of people with early-stage AD. We will also use novel non-invasive brain stimulation technology to augment the neural activity during sleep that is known to have a homeostatic plasticity effect, first acutely and then repeatedly over days. If successful, the project will elucidate a pathogenesis mechanism in the early stages of AD that is critical for developing clinically meaningful therapies and demonstrate the feasibility of a neuromodulation therapeutic strategy.  

UKRI Gateway to Research · FY 2025 · 2025-09

We inhabit a three-dimensional universe, and so the classification of three-dimensional shapes (or 3-manifolds) has been a major area of research since at least the 19th century.  Poincaré famously conjectured in 1904 that the simplest 3-manifold, the three-dimensional sphere, could be identified in purely algebraic terms through an object called the fundamental group.  This question motivated nearly a century of progress until its celebrated resolution by Perelman in 2003, as part of his proof of the even more general Geometrisation Conjecture.  Even so, many important questions about 3-manifolds remain unanswered to this day. One important approach to the construction and understanding of 3-manifolds is through the use of knotted circles in ordinary three-dimensional space.  Knots form crucial building blocks for 3-manifolds, because every 3-manifold can be built from knots by a process called Dehn surgery: we cut several knots out of the three-dimensional sphere and glue them back in by some sort of twist, and different knots and choices of twisting can lead to radically different spaces.  Understanding these knots allows us to describe both the geometry of the resulting spaces -- how are they naturally curved? -- as well as their topology, meaning the properties of their shapes that don't change when we bend or stretch them. This means that understanding knots gives us an important window into the world of 3-manifolds.  Fundamental questions about these building blocks include the construction of knot invariants, algebraic tools which help us to distinguish different knots; the effectiveness of these invariants at telling knots apart; and discerning what these invariants have to say about the 3-manifolds created by surgery on a given knot. This proposal seeks to answer such questions through the use of Floer homology, a package of powerful invariants of knots and 3-manifolds that traces its origins back to mathematical physics in the 1980s.  These invariants are generally hard to work with, because their definitions involve solving partial differential equations, but one incarnation, Heegaard Floer homology, is unusually computable and can in many cases be described purely combinatorially.  It comes with an associated knot invariant, called knot Floer homology, that can even be computed quickly by existing software.   Due to their accessibility, these invariants have led to an astounding number of breakthroughs in low-dimensional topology since their introduction in the early 2000s. In the proposed work, I plan to extend and make use of a deep relationship between Heegaard Floer homology and periodic Floer homology, an invariant of symmetries of surfaces that arises in a very different way from the world of symplectic geometry.  This relationship was established by Lee and Taubes in 2012, but its usefulness in attacking topological questions has only started to become apparent in the last few years, and I will build technical tools that will greatly extend its applicability.  I will apply these tools to show that knot Floer homology can positively identify many knots of arbitrary complexity.  I will also use them to answer long-open questions about the geometric structures that can be realised by surgeries on knots, and to determine the extent to which surgeries on many knots are unique.  Each of these goals will greatly enhance our understanding of both the geometric meaning and the strength of knot Floer homology, and its relationship to fundamental questions about topology in three dimensions.

UKRI Gateway to Research · FY 2025 · 2025-09

This proposal focuses on the analysis of partial differential equations and probability, motivated by the kinetic theory of particles, waves, or phonons in non-equilibrium or equilibrium statistical mechanics. The primary aim is to investigate the mathematical foundations of macroscopic physical laws, particularly the derivation and validation of Fourier's law of heat conductivity. By exploring its microscopic origins, the proposed research contributes to the Hilbert's Sixth Problem from various perspectives in kinetic theory. The first part of the proposal examines the derivation of Fourier's law of heat conductivity in microscopic models involving networks of interacting oscillators perturbed at the boundaries by heat baths. Significant results in this model have emerged from the stochastic analysis and statistical mechanics community, including contributions by Fields Medallist Martin Hairer. This project aims to characterize non-equilibrium steady states of this model, quantify scalings in terms of the number of particles, and finally validate the thermodynamic limit, through rigorous mathematical analysis and methods from spectral theory, optimal transport theory, functional inequalities, and probability. The second part investigates non-equilibrium steady states in the context of the kinetic theory of gases, focusing on the Boltzmann equation for dilute gases. This equation has been extensively studied, with breakthrough results by leading figures including Fields Medallists Cedric Villani and Pierre-Louis Lions. The goal is to study the Boltzmann equation under non-isothermal boundary conditions, which induce energy currents in the stationary state. Understanding them is critical towards validating Fourier's law macroscopically. These first two parts may have implications for environmental sciences by refining climate change prediction models through a better understanding of Fourier's law. Additionally, they could contribute to energy technologies and material sciences by aiding in the design of more efficient thermodynamic materials. The third part addresses Hilbert's Sixth Problem through the kinetic theories of waves and phonons. The main objects of study are the wave kinetic equation and the phonon Boltzmann equation, which arise in weak wave turbulence theory. The wave kinetic equation is the kinetic limit of several wave systems and nonlinear Schrödinger equations, while the phonon Boltzmann equation is the kinetic limit of anharmonic crystals, such as the historically significant Fermi-Pasta-Ulam-Tsingou (FPUT) oscillator chains, which were among the first problems to be simulated on early digital computers. We aim to understand the rich phenomenology of the long-time behaviour of solutions to these equations. Wave turbulence theory finds applications in various fields, including oceanography, nonlinear optics, plasma physics, astrophysics, condensed matter physics and acoustics. The fourth part proposes a novel consistency-stability approach to quantitatively derive the hydrodynamic limit from discrete stochastic particle systems to macroscopic partial differential equations. The main objectives include understanding the emergence of shocks in hyperbolic equations and providing a quantitative hydrodynamic limit for non-gradient systems. This quantitative understanding of macroscopic behavior emerging from microscopic interactions could lead to more efficient algorithms for multi-agent systems and autonomous decision-making.

UKRI Gateway to Research · FY 2025 · 2025-09

We aim to develop an innovative genetic control strategy to address the increasing challenges posed by insect agricultural pests, particularly Tephritid fruit flies. The proposed work is set against the backdrop of climate change, which will exacerbate the range and impact of pests as well as the increasingly unsustainable use of chemical pest control. Our target is Ceratitis capitata, the Mediterranean fruit fly, which significantly impacts agriculture globally and is predicted to arrive in the UK within 2 decades. In malaria vectors we have pioneered gene drive technology that promises to provide a powerful alternative for the area-wide control of harmful insect populations. Gene drive technology, by biassing inheritance, allows desired genetic traits to be spread through populations which can also lead to their elimination. It is an equitable-access technology that is environmentally friendly due to its species-specific mode of action. No gene drive has ever been tested in the environment, however, for medically-relevant mosquito species the technology has reached a stage where gene drives can rapidly propagate through and eliminate vector populations in the laboratory. Today, agricultural insect pests are considered the next frontier to which gene drive technology could impactfully be applied. We already made significant strides towards this goal during previous BBSRC-funded research programmes and have: Established the CRISPR genome-editing toolkit in the medfly  Built and tested the first generation of homing gene drives in the medfly Demonstrated gene drives that convert medfly females into harmless XX males Identified and validated female fertility genes that could host such gene drives combining sex conversion with the sterilisation of females These advances present a unique opportunity. To date no agricultural insect pest species has been successfully eliminated under lab containment by gene drive which we are in now a position to accomplish. In the medfly the completion of gene drive technology is currently prevented by insufficient germline activity of the CRISPR genome editors. This is due to the availability of few well characterised and effective regulatory elements for transgene expression which in turn requires a better understanding of gene expression programs in the ovaries and testis of the medfly. Our aims in this project are to: Demonstrate that caged medfly populations can be eradicated in the laboratory by gene drive Gain a deeper understanding germline biology and to improve the efficiency of genome editing in the medfly Study the biology and competitiveness of sex converted males, a unique window into sexually dimorphic traits offered only by the medfly system Combine these insights to build improved suppressive gene drives for sex conversion The project is relevant to the BBSRC's long-term research and innovation priorities as it seeks to develop a sustainable alternative to chemical pesticides. By focusing on the genetic control of agricultural pests, the project aligns with the BBSRC's goals of advancing agricultural productivity and environmental sustainability. If successful, the resulting intervention could lead to significant reductions in medfly populations, decreasing crop damage and economic losses for farmers. The project's approach could offer a more cost-effective alternative to currently applied interventions and has the potential to be adapted to other Tephritid species, thereby having a broad impact on global agriculture. As an engineering biology project it also provides training opportunities in sought-after-skills for staff as well as students that form part of our team every year.

UKRI Gateway to Research · FY 2025 · 2025-09

Our cities and towns are facing increasing challenges related to public health, sustainability, and climate change. The environments we live in significantly impact our physical and mental well-being, yet we often lack the tools to understand and improve these complex urban systems effectively. Urban planners, policymakers, and communities need innovative ways to create healthier, more sustainable living spaces. However, the interactions between urban environments, human health, and sustainability are highly complex and interconnected, making it difficult to predict the outcomes of interventions or policy changes. The AI4URBAN-HEALTH Network aims to revolutionise how we design and manage urban environments to promote better health and sustainability. We will bring together experts from diverse fields including artificial intelligence (AI), health sciences, urban planning, and environmental studies. Our goal is to develop advanced AI tools that can analyse complex urban systems and predict the impacts of changes, while also creating a framework for inclusive decision-making that involves communities in shaping their environments. At the heart of our approach is the use of cutting-edge AI techniques to create 'digital twins' of urban environments. These virtual models will allow us to test different scenarios and interventions, predicting their effects on health and sustainability. Importantly, we'll combine this technical approach with community engagement, ensuring that local knowledge and priorities are central to our work. We will test our approaches in real-world settings through case studies in Bradford, Guildford, and London's World's End Estate, each presenting unique urban challenges and opportunities. Our research could lead to numerous practical applications. We envision smarter urban planning tools that optimise for health and sustainability, AI-powered systems for managing air quality, energy use, and traffic flow in cities, and personalised health recommendations based on environmental conditions. These innovations could provide evidence-based policy recommendations for creating healthier urban spaces. The potential benefits of our work are far-reaching. We aim to improve public health through better-designed urban environments and reduce the environmental impact of cities, contributing to climate change mitigation. We aim to bring about more efficient use of resources in urban areas and empower communities with a greater say in shaping their living spaces. There are also potential economic benefits through the creation of new technologies and more efficient urban management systems. By bringing together advanced technology, scientific expertise, and community involvement, the AI4URBAN-HEALTH Network aims to create a blueprint for healthier, more sustainable cities of the future. Our interdisciplinary approach, combining AI innovation with deep community engagement, positions us to make significant contributions to urban health and sustainability research. We believe our work will not only advance scientific understanding but also provide practical tools and insights that can be applied in cities around the world, ultimately leading to improved quality of life for urban dwellers and more resilient, sustainable urban environments.

UKRI Gateway to Research · FY 2025 · 2025-09

Neutrinos are the least understood particles we know of. They have extremely small mass and rarely interact, yet they are extremely abundant and critical for our universe's evolution. Neutrinos come in three flavours (electron, muon and tau neutrinos), and since the 1990s, we have known that a neutrino can change its flavour as it travels. This phenomenon is called neutrino oscillations. There are still two big questions left to address about neutrinos. The first is that, surprisingly, we do not yet know which is the lightest neutrino-finding that the third neutrino is heavier than the other two would have implications for many Grand Unified Theories that seek to explain particle interactions as different manifestations of a single force. If that is not the case, how we think about the natural forces in the universe will be completely changed. The second question is whether neutrinos and antineutrinos oscillate in the same way. Answering this question might solve one of the biggest mysteries about the universe's origin: the Big Bang should have created equal amounts of matter and antimatter, but today, everything around us, from the smallest microorganism to the largest stellar object, is made almost entirely by matter. If neutrinos and antineutrinos oscillate following different rules, they might be the reason why the universe evolved to be dominated by matter rather than antimatter, hence allowing the existence of stars, planets and even us. This award allowed me to use a coherent strategy to start solving these two mysteries, following the ambitious programme of the two best equipped experiments to answer them: NOvA and DUNE. NOvA is a world-leading long baseline neutrino experiment: an intense beam of muon neutrinos is produced at the Fermi National Accelerator Laboratory (FNAL), near Chicago, and directed 810 km away towards Minnesota. NOvA uses a near and a far detector to measure the flavour of the neutrinos produced at FNAL, and the flavour of the neutrinos that arrive in Minnesota. DUNE is the future world flagship experiment for neutrino oscillation measurements. It is fully funded, approved by the US Department of Energy, and currently in construction. DUNE will use the intense muon neutrino beam from FNAL and direct it 1300 km away towards South Dakota. DUNE will use a more powerful beam, a much bigger far detector, and better detector technology than NOvA. While the first part of the fellowship focussed on making neutrino interaction measurements, the renewal proposal focusses on their impact on neutrino oscillation analyses and the development of specific techniques for measuring neutrino oscillation parameters. As neutrinos can only be detected when they interact with the matter in the detector and produce other particles, theoretical neutrino interaction models are currently the cause of the most significant systematic uncertainties in neutrino oscillation analyses. My strategy is to exploit the measurements made during the first part of the fellowship to make these experiments more sensitive to neutrino oscillation parameters - my team and I will do this both within the NOvA experiment and the NOvA-T2K joint oscillation analysis. With significant more data than the previous version of these analyses, these experiments have the potential to understand which neutrino is the lightest. Focussing on the future of neutrino experiments, my team and I will develop a new statistical technique to extract neutrino oscillation parameters, to ensure we hit the ground running once DUNE starts taking data. Finally, we will play a leading role in the installation of the DUNE far detector and perform checks to ensure the data taken is of the highest quality. All of these objectives will ensure that my team and I are at the forefront of these neutrino ground-breaking discoveries.

UKRI Gateway to Research · FY 2025 · 2025-08

Reducing emissions requires advances in separations (replace energy-intensive distillations), fuel cells (use robust, low-cost membranes), and high-efficiency lighting (encapsulate halide perovskites), all relying on efficient control of chemical transport. Metal-organic frameworks (MOFs), consisting of metal nodes linked by organic molecules in characteristically porous networks, are poised to accelerate energy savings if we can harness their structural and chemical selectivity. Yet device integration is challenging. Most often prepared as crystalline powders, fusing MOFs with polymers or glasses made from other MOFs creates device-compatible forms. In turn, interfacial interactions boost gas uptake, proton conductivity, and luminescence. However, the defining non-periodic structures remain unresolved. This project will unveil the microscopic structural variety in MOF composites by determining the atomic structure of amorphous components, distortions in crystals, and changes at interfaces. My ambitious research programme will build a nanoscale version of the technique known as electron pair distribution function analysis for MOF/MOF, MOF/polymer, and MOF/perovskite composites using scanning transmission electron microscopy. Now uniting cryogenic, low-dose microscopy and precession electron optics, I will make direct microscopic observations to answer questions on how MOFs melt and form glasses, how guest molecules move through MOFs, and how molecules traverse MOF/polymer membranes. Together with dynamic and multi-scale microscopies, I will combine these tools to track water transport in a model fuel cell membrane. Only through developing nanometre-resolved imaging of amorphous microstructure (domain size, shape, composition, and atomic structure descriptors across interfaces) will it be possible to determine precise structure-function relationships and rationally design host-guest and matrix-filler interactions to realise the potential of MOF technologies.

UKRI Gateway to Research · FY 2025 · 2025-08

Streptococcus pyogenes, also known as group A streptococci (GAS), is a disease-causing bacterium contributing to more than half a million deaths globally each year. It is a major cause of invasive infections and can lead to rheumatic heart disease, an autoimmune condition resulting from recurrent streptococcal infections, especially throat infections. To survive, this bacterium uses two enzymes, SpyCEP and ScpA, to prevent the immune system white blood cells (neutrophils) from being recruited to the infection site. SpyCEP and ScpA are cell surface serine proteases (CEPs) which enzymatically cut critical regions from host proteins that activate the immune system, thereby disabling them. SpyCEP targets and degrades the entire family of CXC immune signalling molecules, while ScpA dismantles C5a, as well as C3a. Despite their importance, there is striking lack of a detailed understanding of how these proteins disarm immune system components and current models are insufficient to define their precise mechanisms of action.  Furthermore, SpyCEP and ScpA could be key players in developing a multicomponent vaccine as they trigger protective immune responses, however, there is no vaccine for Streptococcus pyogenes yet. These important knowledge gaps are hindered by our lack of comprehensive structural information on these enzymes assembled with their target immune molecules and antibodies. To better understand how these molecular systems work and help design a potential vaccine, we plan to employ a sophisticated structural biology approach combining cryo-electron microscopy (cryo-EM) and Nuclear Magnetic Resonance (NMR).  By employing both methods synergistically, we can reach atom level detail and understanding that is not available from each technique alone. Specifically, we aim to determine how these CEP proteins recognise their host immune system targets and change their shape in the process. We will also test observations from our structural insight with incisive biochemical and cellular experiments to derive more accurate functional models for the CEPs. We also aim to visualise precisely how antibodies recognise the CEPs and determine which regions are most immunogenic. With a better understanding of how these proteins carry out their roles and react with antibodies, we hope to create a smarter vaccine.  We will combine important immunogenic features of both enzymes in novel antigens that can be tested in vaccination studies.  This would provide a powerful defence strategy for our immune system to offer protection against this harmful bacterium. In summary, this new research proposal addresses the urgent need for a vaccine against Streptococcus pyogenes. By exploiting advanced structural and biochemical techniques, we aim to gain deeper insights into the virulence mechanisms of SpyCEP and ScpA, paving the way for the development of an effective vaccine to combat this significant global health threat.    

UKRI Gateway to Research · FY 2025 · 2025-08

Context and challenge the proposal addresses: Craniofacial malformations, resulting from abnormal embryonic development, account for over one-third of all congenital birth defects. Cranial neural crest cells (CNCCs) are a developmental cell type essential during craniofacial development, as they differentiate into various structures in the skull, including craniofacial bones, cartilage and connective tissues. CNCC specification and differentiation into derivatives is regulated by fine-tuned gene expression, which is influenced by the accessibility of chromatin. Chromatin remodellers, like the Nucleosome Remodelling and Deacetylase Complex (NuRD) can modify chromatin accessibility. Mutations in CHD3 are the only known cause of Snijders Blok Campeau Syndrome, a congenital disorder characterized by distinctive craniofacial abnormalities. Moreover, CHD3 is one of the most frequently mutated genes in cleft lip and palate patients. Currently the cellular and molecular mechanisms by which CHD3 alterations lead to craniofacial defects are unknown. We are in possession of unique resources to address this knowledge gap, including Snijders Blok Campeau patient-derived iPSCs with CHD3 mutations, CRISPR iPSC lines with CHD3 heterozygous and homozygous knock out, a CHD3-dTAG iPSC line, two different mouse models with Snijders Blok Campeau patient-specific mutations, and CHD3fl/fl mouse models. Our preliminary data indicate that CHD3 regulates response to BMP signalling pathway.  The latter is one of the key signalling pathways involved in both CNCC specification and in craniofacial osteoblast formation. Therefore, we will use these tools to investigate the role of CHD3 in CNCC specification and in CNCC-to-osteoblast differentiation, and more broadly to elucidate the molecular mechanisms underlying the craniofacial abnormalities typical of the CHD3-associated syndromes. Hypothesis: We hypothesise that CHD3 depletion impairs the ability of the cells to respond to BMP signalling. As a result, the differentiating cells undergo mesodermal fate upon exposure to Wnt signalling, and more specifically because of a Wnt/BMP imbalance. Aims: Define the genetic requirements for CHD3 in CNCC specification and differentiation. Model the functional consequence of CHD3 patient variants on development of the CNCC lineage. To investigate the regulation of BMP responses by CHD3 during craniofacial skeletogenesis Potential applications and benefits: The findings will advance our understanding of CHD3's function in craniofacial development and its broader implications in congenital disorders involving chromatin remodelling mechanisms.  Understanding tissue-specific dynamics of the CHD3-NuRD complex will provide insight into how major signalling pathways essential for development integrate with chromatin remodellers, and thus, shed light on other diseases associated with dysregulation of the same genes and pathways. The proposal will have a major impact on our understanding of craniofacial development and has the potential to elucidate target genes potentially amenable to pharmacological treatment applicable to a wide range of diseases. Importantly, this proposal has the potential to generate insights into the molecular mechanisms underlying the syndrome, hence benefiting the patients and their families.  

UKRI Gateway to Research · FY 2025 · 2025-08

Context Mpox, caused by the monkeypox virus (MPXV), has been spreading rapidly in Central Africa. In August 2024, the World Health Organization (WHO) declared a Public Health Emergency of International Concern due to rising cases, particularly in the Democratic Republic of the Congo (DRC) and neighbouring countries, including Burundi and, more recently, Angola. While parts of DRC have begun vaccinating against mpox, Burundi and Angola have yet to introduce vaccines. The region faces many other health threats, including outbreaks of Ebola, Marburg virus disease, and cholera, which are exacerbated by ongoing conflict and population displacement in DRC. The Challenge Two mpox strains (clades) are spreading in DRC under different circumstances. Clade Ia, historically present, circulates mainly in rural areas via zoonotic and household transmission. Clade Ib, a more recently emerged strain, is spreading in cities, and disproportionately affecting sex workers. In Burundi, however, clade Ib presents differently, with a higher fraction of cases in young children. The reasons for this are unclear: potential explanations include differences in transmission patterns, or underreporting of adult cases due to isolation policies - many cases of mpox may go, making it important to estimate population exposure. In Angola, the mpox clade(s) circulating, and extent of spread, remain unknown. With limited resources, optimising mpox vaccine allocation is essential. Data-driven evidence is needed to determine the priority population groups for vaccination to reduce transmission and severe outcomes. Aims and Objectives This project will generate such evidence for the mpox response as well as transferable knowledge and methodologies applicable to other outbreaks. First, researchers will use modelling to estimate mpox spread and assess potential vaccine impact across different sub-national regions in DRC and Burundi, informing vaccine distribution strategies. Second, clinical records on patients and their contacts will be digitised and analysed to identify likely transmission routes and risk factors for severe disease. Third, a pilot serological (blood test) study will determine the feasibility of a larger survey measuring how many people have antibodies against mpox in Burundi and better understand household transmission. Fourth, a genomic study will be conducted to sequence the first 100 mpox cases in Angola to determine which strain(s) are circulating, how the virus is spreading, and how it is evolving over time. Finally, local expertise will be strengthened through a combined training workshop and hackathon in Burundi and research training fellowships bringing Central African scientists to the UK. Public health professionals, data scientists, and policymakers will receive hands-on training in outbreak data analysis, modelling, genomic epidemiology, and digital tools to improve epidemic response. Potential Applications and Benefits This project will improve outbreak control, inform vaccine decisions, and strengthen response systems in a region experiencing frequent and severe public health threats,  thus improving global pandemic preparedness. Findings will be shared with local public health agencies, WHO and the African CDC to ensure direct public health impact. Via knowledge-sharing, bi-directional training, and capacity-strengthening, researchers in DRC, Burundi, Angola and the UK will be equipped with the skills needed to manage future health crises more effectively.

UKRI Gateway to Research · FY 2025 · 2025-08

Human movement relies on the communication between the brain and the muscles via the nerves. Suppose this communication is limited or non-existent due to peripheral nerve trauma. In that case, performing daily tasks will be difficult or impossible. To simplify or enable communication, efforts have been put into recording biological signals from the limb to communicate with a robotic arm or machine, i.e., a neural interface. A neural interface can rehabilitate people with spinal cord injuries, control upper limb prostheses, and assist people using exoskeletons. Today's neural interfaces are based on detecting spinal motoneuron activity with surface electromyography (EMG). However, surface EMG only detects superficial muscle activity and is biased towards subjects with characteristics rarely coinciding with most patient categories. Thus limiting their usefulness and applicability. Therefore, we must shift the focus to other techniques that can provide a natural neural interface that overcomes such limitations. Preferably a technique that could potentially interface all motoneurons innervating the muscle. This proposal aims to develop a neural interface between spinal motoneurons and 3D ultrafast ultrasound using local muscle movements as a proxy for identifying neural activity. For this purpose, methods will be developed, and the technology will be demonstrated using upper limb prostheses as a representative case study. The three specific objectives are: 1) To develop and evaluate a method that compensates probe shifts and tracks muscle deformation in ultrafast ultrasound imaging during muscle contractions. 2) To develop and evaluate a robust decomposition method of ultrafast ultrasound images for real-time motoneuron identification. 3) To evaluate the precision of the neural interface using standardised hand movements from healthy subjects and trans-radial amputees as a representative application scenario.

UKRI Gateway to Research · FY 2025 · 2025-08

Buildings are responsible for about 40% of carbon emissions and consume about 40% of all produced energy in the UK. Transforming how buildings use and produce energy is a fundamental steppingstone to achieving net-zero carbon emissions and sustainable economic growth. The abundance of data, flexible technologies and advanced control approaches open exciting opportunities to achieve cost-effective system decarbonisation and create places where people love to live for the increased comfort standards. A radical transformation of the building sector is possible using real-time monitoring, learning capabilities, advanced control strategies, distributed optimisation and coordination. Our research demonstrates that the energy consumption of buildings has a vast potential to be flexible and support an efficient grid operation. However, it is unclear how to design distributed control architectures and schemes managing millions of buildings in real-time to simultaneously achieve societal and individual consumer benefits. The proposed project seeks answers to critical open questions: How can we efficiently harness the adaptability of millions of diverse buildings to support the entire energy system while optimizing individual objectives concurrently? How can we harness data reliably to develop scalable, transferable control methods, bringing them closer to practical application? The aim of this research is to develop distributed solutions to reliably manage energy use across groups of buildings. We will consider for the first time the advantage of dynamically forming coalitions according to the environment's variability and individual real-time energy needs. To realise this, we have set the following objectives: 1. Extend the latest data-driven behavioural control and uncertainty modelling approaches, state-of-the-art distributed optimisation methods and reinforcement learning techniques. These methods should be scalable to bridge the gap between lab-scale demonstrations and real-world implementation. 2. Apply these innovative methods to models of building clusters. This will offer insights for shaping policies and driving innovation, bolstering their role in supporting the entire energy system. The close collaboration with UK Power Networks and SSE Energy Solutions will support the data-driven modelling and development of novel adaptive distributed control architectures to maximise the research output impact. A pressing question we will address is how to achieve both individual and societal benefits. Existing distributed solutions are focused on directly achieving a centralised objective. Such solutions do not fit the objectives of simultaneously achieving societal and individual objectives. Substantial performance limitations arise when pursuing exclusively conflicting objectives, since the buildings connected to the grid are strongly coupled.

UKRI Gateway to Research · FY 2025 · 2025-08

Background: Atopic Dermatitis (AD) is a debilitating inflammatory skin condition that lacks a curative therapy. AD patients suffer dysbiosis of their skin microbiome, with domination by the pathogen Staphylococcus aureus, which drives immunopathology and disease progression. The extensive use of antibiotics for AD treatment has fostered the spread of antibiotic resistance, underscoring the urgent need for new therapies that can effectively combat AD and skin dysbiosis without promoting antibiotic resistance. Current AD Animal Model Drawbacks: The AD research landscape is dominated by animal models that inadequately recapitulate human disease and cause significant animal suffering. Our project aims to replace these models by integrating mathematical and machine learning models of the skin microbiome in AD with a more physiologically relevant experimental platform - a human skin explant model. PhD Project Goals: The aim of this NC3Rs PhD is to use these computational and human explant models to design and test beneficial skin microbes to eradicate Staphylococcus aureus and prevent inflammatory damage in AD. This research will achieve two significant outcomes: replacing the use of animals in AD research and developing a novel, targeted therapeutic approach that reconfigures the skin microbiome to prevent AD. We have support from labs around the world that currently use mouse models of AD who are eager to switch to our non-animal models. A Multidisciplinary Collaboration Based on a Commitment to the 3Rs: Our project is a collaboration between Dr Thomas Clarke (Department of Infectious Disease) and Prof. Reiko Tanaka (Department of Bioengineering) at Imperial College London. We will also collaborate with Dr Alex McCarthy (Department of Infectious Disease), an expert in human skin explants. Our collective expertise spans the microbiome, mathematical modelling, inflammatory and infectious disease models, and ex vivo human skin models. Our multidisciplinary team and expertise will ensure the feasibility and success of the project. Multidisciplinary Training and Support: Beyond its impact on the 3Rs and AD therapeutics, this PhD project will also provide exceptional multidisciplinary training, equipping the trainee with cutting-edge skills in the microbiome, human immunology, computational biology, and bioengineering. Our collaboration is well-established, all computational and wet lab models are in place, and we have state-of-the-art facilities. We believe our team is ideally positioned to provide the mentorship, training, and support to ensure the successful completion of this project.

UKRI Gateway to Research · FY 2025 · 2025-08

Influenza viruses impose a significant disease and economic burden through seasonal epidemics in humans and outbreaks in livestock such as chickens, pigs and recently cows. Their zoonotic nature also poses a persistent pandemic threat, as demonstrated by the four flu pandemics since the early 1900s. The challenge in combating influenza viruses stems from their fast evolutionary rates. The influenza RNA polymerase (FluPol) is essential for viral gene expression and genome replication, but it is highly error-prone, leading to the emergence of new variants and drug resistance. This rapid evolution necessitates frequent updates to vaccines, presenting a major challenge for public health systems worldwide. The development of new antivirals is critical to outpace these evolving viruses, especially in the context of drug-resistant strains. The activity of FluPol is highly dependent on its cellular environment as it relies upon and is influenced by a plethora of host proteins. My research strategy involves a systematic approach to identify, validate, and characterise the host proteins that interact with FluPol across different influenza subtypes. The objective is to elucidate the molecular mechanisms behind critical host proteins that drive either viral transcription and/or replication. I will use a novel proximity proteomics technique, HyPro mass spectrometry (HyPro-MS) to map the full repertoire of host proteins interacting with FluPol. By applying HyPro-MS to human cells infected with circulating subtypes of influenza I aim to uncover universal proteins or networks that are appropriated by all influenza viruses and those that may be specific to certain subsets. I will then employ a synergy of virological, cell-based and molecular approaches to functionally characterise the roles of these proteins in FluPol activity and virus growth. Additionally, I will implement cross-linking mass-spectrometry to gain detailed structural insights of the interfaces of crucial host-virus interactions. This comprehensive approach will enhance our understanding of the complexes that form to regulate the diverse states of FluPol throughout the viral life cycle. This study will not only deepen our knowledge of influenza virus biology but also illuminate the fundamental mechanisms through which viruses hijack host cellular machinery. Host proteins also serve as an untapped source for host-targeted therapeutic interventions which have the potential to address current challenges of antiviral resistance as well as providing broad-spectrum potential against a wide-array of influenza strains. My ultimate goal is to develop innovative antiviral strategies that target host proteins to deliver comprehensive protection against influenza.

UKRI Gateway to Research · FY 2025 · 2025-08

‘Tackling menstrual problems’ is the top priority of the Department of Health and Social Care ‘2022 Women’s Health Strategy’. Functional hypothalamic amenorrhea (FHA) is one of the most common causes of menstrual disturbance in women of reproductive age. It is the result of decreased energy availability due to a combination of excessive exercise and insufficient energy intake. FHA leads to significant psychological distress, subfertility, and adverse effects on bone. It also places affected women at increased risk of cardiometabolic disease. However, the mechanistic basis for FHA is not fully understood, and there is no effective pharmacological therapy available for affected women. Context Recent research has established the role of the neuropeptide kisspeptin in regulating the female reproductive axis. Kisspeptin-neurons in the hypothalamus exhibit intrinsic activity, and their episodic release of kisspeptin onto GnRH neurons generates the pulses of luteinising hormone (LH) that are essential for female fertility. In FHA, kisspeptin neurons become largely unresponsive to oestrogen, leading to the suppression of their episodic activity. While the molecular basis for this effect is unknown, it is likely responsible for the reduction in LH pulses and the associated infertility in women with FHA. Therefore, using kisspeptin to restore LH pulses in women with FHA has been proposed as a valid therapeutic approach. Promisingly, data from our research team has shown that a short-term infusion of kisspeptin can induce LH pulses in a woman with FHA. This finding raises important questions about hypothalamic LH pulse generation, and whether chronic kisspeptin infusion might also restore ovulation in many/all women with FHA. This proposal aims to understand the mechanistic basis for the loss of LH pulses in women with FHA, determine how these pulses are restored by kisspeptin infusion, and test whether kisspeptin-induced pulses can be maintained over a chronic time scale in women with FHA. Hypothesis Understanding the mechanistic basis for the suppression of LH pulses in women with FHA will facilitate the development of a novel and testable therapeutic strategy for the condition. Aims Understand the molecular mechanism of kisspeptin neuron pulse suppression in a mouse model of FHA (Applicants: BMO and AH) Recent mechanistic work by the applicants has demonstrated that the oestrogen receptor (ESR1 or ERa) in kisspeptin neurons plays an essential role in normal LH pulse generation. This aim will utilize a validated mouse model of FHA to investigate how the condition affects ERa gene-regulation and kisspeptin neuron activity. Understand the mechanisms that re-establish pulses upon continuous infusion of kisspeptin (Applicant: AH) It is not known how a continuous infusion of kisspeptin can induce LH pulses in some women with hypothalamic amenorrhea. Understanding this process is crucial, as it will inform which women are likely to benefit from this future therapy. The team will employ state-of-the-art imaging techniques, already validated in the lab, to address this question using a mouse model of FHA. Determine the potential utility of kisspeptin infusion in women with FHA (Applicants: AA and WSD) The team will investigate whether a chronic infusion of kisspeptin is sufficient to restore LH pulses in women with FHA. Overall, this project addresses the top priority of the 2022 Women’s Health Strategy by providing mechanistic insight into an understudied disease, and a rational pathway to clinical translation.

UKRI Gateway to Research · FY 2025 · 2025-08

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

UKRI Gateway to Research · FY 2025 · 2025-08

Overview The "pattern effect" refers to the contribution of the spatially-varying pattern of temperature change to the global-mean climate feedback. The role of the pattern effect in climate sensitivity is generally probed and quantified in targeted numerical experiments forced with prescribed sea-surface temperatures. The current approaches have two shortcomings: 1) The current numerical set-up is focused on climate models forced with fixed surface temperatures. Whether the set-up provides a robust estimate of the time-varying climate feedback in coupled climate simulations and observations remains unclear. 2) The current numerical experiments do not prescribe land-surface temperatures. Thus the contribution of the spatially-varying pattern of land-surface temperature change to the climate feedback is unknown. The proposed research will address the two shortcomings through two research Streams. The first Stream is guided by the hypothesis that statistical methods provide a practical and physically-meaningful approach for investigating the pattern effect, and can be applied to both observations and coupled climate model output. The research will include developing and testing a hierarchy of statistical methods that quantify the pattern effect in observations and existing coupled climate simulations. The results will provide new insights into the regional physical processes that drive variations in the global feedback due to both internal variability and external forcing in both models and observations. The second Stream is guided by the hypothesis that land-surface temperatures have a substantial influence on local and remote clear-sky feedbacks and cloud-radiative effects, and thus on the global feedback parameter. The research in Stream 2 will quantify the role of land-surface temperatures in the global radiative flux and climate feedbacks by performing the first numerical surface temperature patch experiments that apply the Green's function approach to both ocean and land areas. The proposal is a joint NSF/NERC project. The research will be led by Drs David WJ Thompson and Maria Rugenstein in the Department of Atmospheric Science at Colorado State University, and Dr Paulo Ceppi in the Department of Physics at Imperial College London. It will include collaboration with Drs Timothy Andrews and Duncan Ackerley at the UK Met Office, who will serve as scientific advisors on the project and facilitate the development of the numerical patch experiments. Intellectual Merit The research will lead to new insights into our understanding of the physical processes that determine the global climate feedback parameter and thus climate sensitivity. Together, the research in Streams 1–2 will provide tools that can be used to estimate the global climate feedback parameter with statistical methods alone and thus from observations – potentially opening new opportunities to observationally constrain climate feedback and sensitivity. The research will provide insights into the importance of land-surface temperatures in the global radiative response, and thus potentially a refined estimate of the global climate feedback parameter and its time variation. It will provide a numerical template for exploring the role of land-surface temperatures on radiative feedbacks and climate sensitivity. Broader Impacts The impacts for society include improved understanding of the global climate feedback and thus the amplitude of the climate response to increasing greenhouse gases. In the process, the work will foster international collaboration between experts on climate dynamics and feedbacks at Colorado State University in the US, Imperial College and the Met Office in the UK. It will provide a framework for prescribing land-surface temperatures in climate models and thus a potential new template for surface temperature patch (Green's function) experiments. The proposal will provide mentoring and funding support for two graduate students at CSU and for a postdoctoral researcher at Imperial College. It will foster international collaboration between students and early career researchers working in the UK and USA, and provide funds for the students to attend meetings and seminars relevant to their graduate education. It will support a series of outreach activities in the local school district in Fort Collins, CO. The research will additionally contribute to ongoing model development efforts for the upcoming phase 7 of CMIP. In particular, the prescribed land-temperature template developed for Stream 2 will be employed by the UK Met Office for new experiments run for the Radiative Forcing Model Intercomparison Project (RFMIP). The model source code modifications and new Green’s functions will be made publicly available to the international research community.

UKRI Gateway to Research · FY 2025 · 2025-08

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

UKRI Gateway to Research · FY 2025 · 2025-08

Because of their ability to bind most molecular targets tightly and specifically, antibodies are increasingly used in biomedical research, diagnostics, and medicine, where they are the fastest-growing class of therapeutics. The rapid surge in the size and quality of structural and biological databases is allowing to introduce innovative computational methods of rational antibody design. The goal of the proposed research is to develop and establish novel computational technologies of antibody discovery and optimisation, by using a multidisciplinary approach that encompasses fragment-based rational design, the development and deployment of artificial intelligence methods, in vitro experimental validation, and in vitro affinity maturation. Rational design at a computer substantially lowers the time and costs required to discover novel antibodies for a target of interest, does not exploit animals, and enables a much better control over the properties of the obtained antibodies. For example, it allows to obtain antibodies binding to specific regions of interest (epitopes) within the target (antigen), which remains a critical challenge with established technologies of antibody discovery, but is of key importance for many applications. Computational design also offers a better control over other properties essential for successful antibody development, including stability and solubility. The proposed research represents a significant step forward towards the establishment of computational design as a competitive technology for the generation of novel antibodies. Computational approaches promise to enable the reliable and inexpensive generation of drugs to combat - and tools to study - many crucial diseases. Overall, the unique opportunities offered by these approaches will enable to address new questions, accelerate discoveries by facilitating experiments, streamline therapeutic antibody development, and provide novel avenues for industry investment.

UKRI Gateway to Research · FY 2025 · 2025-08

Cerebral small vessel disease (cSVD) is the commonest vascular cause of neurodegeneration and causes at least 40% of all-cause dementia. cSVD affects >50% of people over 65. It is defined by progressive injury to cerebral small arteries, manifest by key imaging features on MRI. The underlying pathology remains unclear despite our demonstration of strong associations with endothelial dysfunction, impaired white matter perfusion and impaired control of cerebral blood flow. There is currently no specific treatment for SVD. PDE5 inhibitor drugs target the endothelium-dependent, nitric oxide-driven vasodilatory pathway, with the potential to reverse cerebrovascular dysfunction in cSVD. Recent Mendelian Randomisation analyses identified PDE5 underactivity as potentially causally associated with both imaging markers of cSVD and risk of dementia. We have recently shown that PDE5-inhibition improves cerebral blood flow and cerebrovascular reactivity, reversing SVD-associated dysfunction, but important knowledge gaps remain. These include the mechanism and locus of action for PDE5 effects on cerebrovascular dysfunction, and specifically, the balance of PDE5 effects on systemic perfusion, cerebrovascular function and cerebral tissue-level effects on neurodegeneration. The small molecule Mirodenafil® is a higher-specificity, higher-potency, CNS-penetrant PDE5 inhibitor (PDE5i) compared to alternative PDE5is, with excellent tolerability. Mirodenafil reduced biomarkers of Alzheimer’s Disease (AD) in phase-2 studies, and is being tested for efficacy in the POLARIS-AD phase-3 trial.  However, the effects of mirodenafil in vascular causes of neurodegeneration, particularly in SVD, are unknown. Mirodenafil thus provides a readily-available intervention to test the site and role of PDE5-mediated vascular versus tissue-level dysfunction, with a clear pathway to translation for patient benefit via clinical trials. Hypotheses: PDE5-mediated dysfunction is present in both vascular and tissue-specific mechanisms in cSVD. PDE5-inhibition with the highly-selective, brain-penetrant PDE5i mirodenafil will reverse this dysfunction at multiple sites. PDE5-inhibition with mirodenafil has a predominant effect on cerebrovascular vasodilatory function across different doses. We propose an experimental, randomised, blinded, crossover, placebo-controlled, dose-ranging study, to test the effects of PDE5 inhibition at each site in the cerebral perfusion pathway, on mechanisms of cerebrovascular regulation compared to tissue-specific mechanisms. We will quantify the dose-dependent effects of mirodenafil on physiological measurements for which we have established expertise, but which are not used in clinical practice. Older people with chronic SVD defined on MRI (N=82), will receive placebo, 10mg, 30mg and 60mg of mirodenafil in randomised order, for 4 weeks on each dose. After detailed clinical and cognitive phenotyping, at each visit they will undergo: physiological testing with transcranial ultrasound for cerebral blood flow, cerebrovascular reactivity, and systemic cardiovascular function; plasma biomarkers for tissue-specific mechanisms; cognitive testing (DSST). On placebo and 60mg, they will have a physiological-MRI including reactivity, neurovascular coupling and blood brain barrier breakdown. The primary outcome is grey matter cerebrovascular reactivity on MRI for placebo versus 60mg mirodenafil. Secondary outcomes will determine the dose-response relationship of mirodenafil with: cerebral perfusion; cerebral blood flow velocity ; blood-brain barrier permeability; plasma biomarkers of amyloid, endothelial activation (VCAM/ICAM), blood brain barrier function (S100b) and neuronal injury (NFL) Impact. This experiment will provide detailed mechanistic information on a potentially causative pathway in cSVD. Specifically, it will delineate the role of nitric oxide-PDE5 vascular and tissue-specificpathways relevant to neurodegeneration, and identify opportunities to modify them. The existing strong relationship with our industry partner AriBio will enable future translation and development of novel therapeutics in SVD-related dementia, a major untreated patient group.        

UKRI Gateway to Research · FY 2025 · 2025-08

The MRC Centre for Global Infectious Disease Analysis (MRC-GIDA) is a world-leader in infectious disease modelling and training, collaborating closely with public and global health agencies such as the WHO and governments worldwide. With over 200 researchers, we have a unique capacity to respond to emerging threats with real-time analysis and predictive modelling, providing evidence-based input for urgent policy decisions on endemic and emerging diseases such as COVID-19, Ebola, mpox, and influenza. This proposal will extend our research capabilities with high-performance general-purpose Graphical Processing Units (GPUs). These resources will enable transformative advances in infectious disease modelling leading to faster public health responses to the increasing threats of infectious diseases in the UK and worldwide. Currently, our high-performance computing (HPC) resources are CPU-based. There is an urgent need for infrastructure capable of supporting advanced machine learning techniques - methods crucial for the next generation of infectious disease research. The proposed GPU technology will allow us to develop methods that can significantly improve our response times in meeting these demands. The primary objective of this project is to establish GPU infrastructure that our diverse research community will use to transform the computational approaches relied on when responding in real-time to public health emergencies. These will reduce turnaround times for critical analyses, enhance pandemic preparedness, and support policy-making with high-resolution insights into health inequalities and complex disease dynamics. Additionally, the infrastructure will foster cross-institutional collaborations with other MRC centres in Imperial, providing a shared resource for initiatives focussing on modelling the health effects of environmental hazards, air pollution and climate change. Importantly, transitioning from CPUs to GPUs will enhance environmental sustainability by enabling faster, energy-efficient computation, reducing the carbon footprint of our research. Centre researchers will leverage the GPU infrastructure to drive advancements across a range of applications. These include machine learning models capable of emulating mechanistic infectious disease models, significantly reducing computational times and allowing real-time modelling of interventions during emerging outbreaks. These emulators can be orders of magnitude faster, enabling more detailed representation of transmission dynamics and key socioeconomic determinants of health inequity. More nuanced intervention strategies can also be designed, ensuring targeted, equitable interventions for future pandemics and endemic diseases disproportionately affecting marginalised groups, such as TB and sexually transmitted infections. In genomic epidemiology, GPUs will also facilitate evolutionary analyses, vaccine design and development of novel algorithms to manage the growing volume of genetic sequence data underpinning surveillance systems. Lastly, GPUs will advance climate and health modelling by examining the effects of environmental changes on vector-borne diseases such as malaria and dengue. The benefits will reach beyond MRC-GIDA. National and international impacts will be delivered through existing partnerships with academic institutions and agencies such as UKHSA, WHO, The Global Fund, Gavi, and ministries of health across the world. With the ability to deploy lightweight GPU-enabled models, we can also support more requests during health crises and democratise access to complex infectious disease modelling, especially in lower-resource settings. The software tools will be developed as open-source packages for researchers worldwide, and we will support their dissemination through short courses, bespoke training at international conferences, and hackathons. This will ensure advanced computational tools can be used globally, bridging technology gaps, and continuing to position the UK at the forefront of global infectious disease modelling and response.

UKRI Gateway to Research · FY 2025 · 2025-07

Warm cumulus are the fluffy clouds onto which people project shapes of familiar objects. They are aerosols of liquid water droplets contained within a turbulent body of air and sometimes yield rain, although this is an intermittent process with only around one in a million droplets needing to become big enough to trigger the raindrop-formation process. Turbulence is the chaotic motion of the air within the cloud, and is a familiar source of discomfort for airline passengers. Cloud droplets form at small sizes and grow through condensation of water vapour into liquid, however this growth rate is too slow to explain the observation that rainfall can develop within approximately 30 minutes of a cloud's formation. It is increasingly clear that turbulence within the cloud could be a vital factor in accelerating this droplet-growth since it causes collisions between droplets, which then coalesce making them larger. Current estimates suggest that turbulence increases the rate of collisions two- to three-fold. However, the physics behind this turbulence-enhanced collision and coalescence is not well understood meaning that they are not well parameterised for numerical weather and climate modelling. Droplets within turbulence are exposed to aerodynamic and gravitational forces which determine their trajectories, and hence likelihood of colliding/coalescing. An exact equation exists to describe the motion of a very small droplet in turbulence. However, full implementation of this equation in high-fidelity numerical simulations is extremely expensive meaning that typical simulations rely on an abbreviated form of the equation, only considering some of the aerodynamic forces. Unfortunately, cloud turbulence is intermittent, meaning that there are patches of clouds that are significantly more turbulent than average and in these patches the abbreviated form of the equation is insufficient to accurately describe the motion of the droplets, and indeed the full equation is stretched to breaking point. Our research will focus on understanding and then modelling these intermittent turbulent physics on the behaviour of cloud droplets, in particular the rate at which they collide and coalesce. To achieve this we will exploit a combination of experiments in a national wind tunnel and state-of-the-art simulations on supercomputers. We will identify features of intermittent cloud-turbulence that induce a strong contribution from the "new" forces, currently neglected in today's simulations and therefore with an unknown effect on rain-formation. Next, we will test one of the assumptions behind the particle-force equation to destruction: namely that the droplets are sufficiently small that they do not themselves modify the cloud-turbulence. We expect that this assumption will be violated when the droplets pass through particularly "rough"/turbulent patches of a cloud. Once we have learned how these intermittent cloud physics affect the behaviour of droplets within a cloud our final objective is to take these newly-discovered physics and parameterise them into a form that will be useful for numerical weather prediction (NWP). We are partnering with the UK Met Office and Centre for Climate Research Singapore and will implement our parameterised intermittent cloud physics into their NWP models and validate their predictive capabilities against satellite data. As these NWP becomes ever higher-fidelity accounting for the effects of cloud turbulence becomes increasingly important to improving forecasting accuracy, especially as climate change is expected to increase levels of atmospheric turbulence. Cloud/precipitation formation/decay are key uncertainties in global climate modelling and our research will help to reduce these uncertainties.

UKRI Gateway to Research · FY 2025 · 2025-07

Biological life is only possible because of its inherent biomolecular building blocks such as sugars, lipids and proteins. In order to understand the myriad of biological functions that these biomolecules undertake we need to be able to characterise their detailed structure. A particular emphasis will be placed on sugars, sometimes also referred to as glycans or carbohydrates, in the form of polysaccharides or glycoconjugates (bound to proteins and lipids), as they are the most abundant and structurally diverse class of biomolecules on the planet. Glycosylation is also the most important protein modification in terms of the number of proteins modified and the functional diversity it generates, which directly impacts on their stability and half-lives. Glycoproteins, glycolipids and glycan-binding proteins, which specifically recognize particular glycan structures, are located on the cell's surface. As this is the cells primary interface with the external environment, many biologically significant events can be linked to specific glycan recognition between cells. The structural characterisation of biomolecules requires the development and exploitation of high sensitivity analytical methods. Mass spectrometry is such an analytical method that is particularly well suited to characterize biomolecules. A mass spectrometer provides two important pieces of information about a biomolecule, or a portion of a biomolecule: its mass and its charge. This key information can be used to derive the detailed structure of the biomolecules which is vital for working out their function. In this application we propose to purchase a state of the art high performance Bruker neofleX MALDI mass spectrometer that is particularly well suited to allow the characterisation of biomolecular structures. The applicant team from Imperial, the Francis Crick Institute, the Quadram Institute, the Pirbright Institute and the Animal and Plant Health Agency, are world leading scientists supported by >£26M of relevant current BBSRC-funded research and >£6M of relevant UKRI-funding, whose research is underpinned by structural data generated by MALDI-MS instrumentation. This is being held back by aging and increasingly unreliable current MALDI instrumentation at Imperial and the Quadram, and lack of such instrumentation at the Francis Crick Institute, the Pirbright Institute and the Animal and Plant Health Agency. Because of the diverse research activities of the applicant team the new instrumentation will be used to address some of the most important biomolecular structural research challenges within the UKRI-BBSRC strategic research priorities such as understanding the rules of life, transformative technologies, bioscience for sustainable agriculture and food, bioscience for renewable resources and clean growth and bioscience for an integrated understanding of health. It will advance the development of new medicines, antibiotics, vaccines and diagnostics to tackle disease in both humans and animals thereby improving health, enhancing sustainable health and food production and protecting biodiversity, it will allow the characterisation of emerging viruses to facilitate the assessment of their pandemic potential, and it will accelerate the production of microbial food proteins to enhance sustainability. The Bruker neofleX MALDI  will be integrated into the existing Centre for Integrative Systems Biology and Bioinformatics (CISBIO) Mass Spectrometry facility at Imperial. It will therefore be made open–access to all members of Imperial and the broader academic and industrial research community. The Imperial funded facility manager will interact closely with Bruker to ensure efficient and timely installation of the neofleX and will receive detailed training which he will subsequently pass on to new instrument users.

UKRI Gateway to Research · FY 2025 · 2025-07

Bacteria naturally release portions of their cell membrane. These outer membrane vesicles (OMVs) are essentially tiny molecular packages containing proteins, fats and other molecules. Bacteria use OMVs to communicate with other cells and to transfer molecules. OMVs are also attractive for use as vaccines or as vehicles for delivering drugs and other therapeutic agents because of their ability to interact with host cells and their natural immunogenic properties. OMV vaccines for use in humans include GSK’s Bexsero®, a Neisseria meningitidis vaccine, that has received MHRA, EMA and US FDA approval and has achieved sales of £218m in Q1 of 2023 alone. Future OMV-based animal vaccines are also likely to have economic and food security importance, or as an exemplar, could help to protect the broiler industry from losing significant numbers of chickens each year due to avian pathogenic E. coli (APEC) related diseases. Further to this, APEC isolates have genetic similarities in terms of virulence markers, with human uropathogenic E. coli (UPEC), and as such may have zoonotic potentials. Worryingly, some APEC strains have also been reported to be resistant to all classes of antibiotics. It may therefore, become increasingly desirable for OMV-based cross protective vaccines to be developed to protect against UPEC and/or APEC in poultry and humans. However, whilst OMV vaccines and therapeutics are promising, our engagements with industry have highlighted important challenges. For example, OMV vaccine manufacturing is typically non-standardised and requires the culture of weakened or highly infectious bacteria to generate the relevant vaccine antigens. Furthermore, the custom engineering of each new bacterial strain to ensure commercially viable OMV yields can slow down OMV vaccine development. Additionally, widely used OMV isolation methods during the manufacturing process might not produce OMVs at suitable yields, purity or bioactivities required for specific applications. Further advancements in OMV engineering approaches are also desirable to enable the manufacture of OMVs with novel therapeutic modalities to treat additional animal or human diseases. To help accelerate next generation OMV therapeutics we have developed an Outer Membrane vEsicle enGineering and mAnufacturing (OMEGA) platform technology to create better and scalable methods for manufacturing new kinds of vaccine or therapeutic OMVs. Our approach differentiates itself from competing technologies through the way in which we have specially engineered our OMEGA bacterial strains to help make it easier to biomanufacture many kinds of therapeutic OMVs in a modular or "Lego-like" fashion. Importantly, our approach also incorporates methods that help simplify our OMV manufacturing process making it easier to produce and isolate OMVs at larger scales. BBSRC FoF support will be used to further scale our OMV manufacturing platform technology, strengthen OMEGA IP, and to carry out focused comparative studies that derisk and show the competitiveness of our approach. Importantly, we will also develop a panel of OMV R&D products and candidate OMV-based APEC vaccines that alongside our continued engagement with the EV industry and other stakeholders will help us to shape and expedite a responsible translational pathway for OMEGA-OMV vaccine and therapeutic manufacturing for the future benefit of animal and human health.