University of Leeds

UKRI Gateway to Research · FY 2025 · 2025-07

Proteins are the molecular workhorses of the cell and to elicit their biological functions must undertake an intricate molecular choreography by interacting, sometimes weakly and transiently, with other proteins, nucleic acids, small molecules, lipids. It is vital to comprehend the structural basis of these interactions to understand the molecular basis of life, understand dysfunction/disease and to harness the powers of proteins for biotechnology. Several methods now exist to study protein structure, interactions and function, including high-resolution methods such as cryo-electron microscopy, X-Ray crystallography and nuclear magnetic resonance spectroscopy. Structures can even be predicted with high confidence computationally. However, these methods often fail (especially for intrinsically disordered proteins), and they cannot be used to study proteins that form heterogeneous assemblies or describe the motions of malleable proteins.  Mass spectrometry-based methods for structural biology can overcome the challenges posed by disordered, heterogeneous and dynamic proteins and their assemblies, and can provide valuable structural information to elucidate the molecular mechanisms underpinning life. Research in the Astbury Centre for Structural Molecular Biology at the University of Leeds aims to understand life in molecular detail. This proposal will embed an advanced mass spectrometer for structural biology within our Mass Spectrometry Facility. This multi-purpose, multi-user instrument will enable protein structural characterisation using two mass spectrometry-based technologies called hydrogen-deuterium exchange and native mass spectrometry. Using the new capabilities of this mass spectrometer we will be able to define the structural arrangement of proteins and their assemblies, understand how structure/interactions change in different disease states, and define ligand binding sites on proteins. These fundamental insights into protein structure and function are uniquely accessible using mass spectrometry-based methods and will provide crucial information to illuminate the molecular basis of life. Crucially, this instrumentation will be equipped with new capabilities for peptide/protein fragmentation that will enable us to define these structural features of proteins and their assemblies in unprecedented detail. We will use this new mass spectrometry equipment in projects spanning the biosciences and biotechnology: this includes projects that will inform on molecular mechanisms underpinning antimicrobial resistance, neurodegenerative diseases, virus replication, cardiac disease, immune dysregulation, and for biopharmaceutical characterisation. By embedding this new mass spectrometer in our Mass Spectrometry Facility, that has a track record of supporting research by a broad and diverse user base, we will make this equipment and these methods available to users across Leeds, as well as to others in academia and industry, to ensure broad impact across bioscience research. We will also deliver a hands-on training programme with the instrument manufacturer, alongside symposia for mass spectrometry-based structural biology, to facilitate new collaborative bioscience research and embed these technologies into the UKs bioscience ecosystem.

UKRI Gateway to Research · FY 2025 · 2025-07

Two of the great quests of humankind are the hunt for habitable planets and the search for the signatures of life beyond planet Earth. We have now discovered more than 5,600 planets orbiting other stars, the so-called exoplanets. Of these, 29 have a similar size to Earth and also orbit their host star in the habitable zone, a temperate region where liquid water may be able to survive on the planet surface. However, a planet's presence within this temperate zone is only one of several criteria that determines whether or not a planet is truly habitable. So far, we know of only one place in the universe where life has begun and thrived, planet Earth. It is still not well understood why the Earth is seemingly the only planet in the Solar System where life has flourished, especially because our neighbour, Venus, also orbits within the temperate region around the Sun, yet has an atmosphere and surface that is not friendly for life. Rocky planets like the Earth and Venus are formed from cataclysmic collisions of moon-sized bodies, the energy from which would have created a molten, hot surface from which volatiles, such as water, would have boiled away to space. So what happened to make the Earth friendly for life? One theory, supported by the enhancement of heavy isotopes in the Earth's atmosphere and oceans, is that impacts from comets, icy leftovers from the formation of the Solar System, delivered a substantial volume of water and life-friendly (carbon-rich) ingredients to the surface of the young Earth when the crust cooled and solidified. This replenished the planet with the ingredients needed for life to begin. However, this then raises questions on the role of comets in seeding *all* potentially habitable planets with life-friendly ingredients. Are cometary impacts a vital process in the formation of a habitable planet? If so, are comets that are formed around other stars also carriers of carbon-rich and life-friendly material? This research will scrutinise the criteria needed for habitability by investigating the role of comets in seeding life on *all* potentially habitable planets, using state-of-the-art computational chemical and climate models, to contrast with state-of-the-art observations of comets and exo-comet forming regions around other stars. My team and I will determine i) whether or not the comet-building material in exoplanet-forming systems are universal carriers of organic-rich material needed to seed life, and ii) whether or not cometary impacts on the atmospheres of rocky exoplanets are an observable phenomenon. The outputs from this research will provide strong constraints on the commonality of habitable planets, and provide a suite of diagnostics to search for evidence of cometary impacts using next generation telescopes that will target potentially habitable exoplanets. This research will revise the definition of "habitability" and will provide atmospheric diagnostics of habitability beyond the already proposed biosignatures.

UKRI Gateway to Research · FY 2025 · 2025-07

Glioblastoma (GBM) is the most common and most deadly form of adult brain cancer. GBM patients receive a standard treatment of surgery, radiation and chemotherapy but tumours fatally recur 6-9 months later, causing this cancer to result in more years of life loss, per patient, than any other. This is because complete surgical removal of GBM is not possible; cancerous cells invade the healthy brain and cannot be removed. Research focused on characterising the remaining cells to understanding why some of them survive chemoradiation, has revealed that these cells can adapt their characteristics to survive and seed tumour regrowth. My own research in this area has identified the likely mechanism that underpins this adaption, and discovered that tumours can be stratified into two subgroups based on how their tumours adapt. These subgroups, termed Up and Down responders, employ different mechanisms to resist treatment, eliciting great promise that patient stratification and personalised medicine may lead to more effective treatment of this deadly disease. However, my work has also shown that the GBM tumour microenvironment (TME) is crucial for driving the responder subtype and this has raised two challenges that must be overcome to facilitate patient impact: 1) which cells (cancerous or TME) are expressing the pathological signatures and drivers of adaptive responses? and 2) which experimental model(s) can be used to further explore the drivers of adaption and targets for personalised medicine? The former is the focus of my fellowship renewal as it directly impacts the prioritisation of therapeutic targets for follow on study in, as well as feeding into the identification of, the correct experimental models. My overarching goal for my renewal is to identify the most clinically relevant personalised medicine targets for GBM via single cell analysis of responder subtypes. To achieve this, I have the following aims and objectives: Aim 1: Identify changes in GBM cellular landscape through treatment in the responder subtypes Obj.1.1. Redefine cell types in GBM by consolidation of RNA and chromatin accessibility data (Establishment and maintenance of cell type); Obj.1.2. Characterise and compare the cellular composition and landscape of primary and matched recurrent GBMs and how this differs between responder subtypes; Aim 2: Identify the subtype-specific drivers of plasticity within neoplastic GBM cells Obj.2.1. Characterise spatiotemporal changes in chromatin accessibility between primary and matched recurrent GBM and how this differs between responder subtypes; Obj.2.2. Characterise and compare regulatory networks driving changes in gene expression from primary to matched recurrence and how this differs between responder subtypes; Obj.2.3. Characterise the cell-cell interactions associated with tumour adaption in both responder subtypes. Aim 3: Create a list of prioritised targets for downstream work Obj.3.1. Integrate single cell and bulk datasets to identify subtype-specific therapeutic vulnerabilities and prioritise targets based on translational criteria

UKRI Gateway to Research · FY 2025 · 2025-06

UNRISK is a consortium of the University of Leeds, University College London, the University of Exeter and 40 non-HEI partners. UNRISK will train 41 students with the multidisciplinary knowledge and skills across climate science, data science and decision science to tackle the pressing challenge of reducing the risks associated with rapid climate change. Students will undertake research to improve our understanding of uncertainty in climate projections and impacts to inform decisions and decision-making tools, thereby reducing the rapidly increasing societal and economic risks associated with climate change on local, national and global scales. UNRISK will deliver highly qualified graduates to help make the UK a leader in the rapidly growing climate services sector – graduates capable of providing data, information and expertise to help individuals and organisations make appropriate decisions about how to manage and adapt to the risks of climate change. UNRISK is vital because of the large uncertainty and low confidence in projections of climate change and associated hazards such as extreme storms, urban heat waves, sea-level rise, and declining crop yields. Uncertainty is a major barrier to climate policy development and has an estimated global economic cost of trillions of dollars by delaying investment decisions, weakening multi-lateral agreements, and reducing uptake of climate services. The holistic training programme combines climate science, data science and decision science to address identified skills gaps in the climate services sector. Skills will include understanding and quantifying uncertainty in models and observational data (relevant to operational centres), propagation of uncertainty through to risk assessments, uncertainty in decision systems and tools (consultancies, public and regulatory bodies, consultancies, financial organisations), and two-way risk communication and visualisation with users (e.g., policy makers and humanitarian organisations). The research and training programme has been co-developed with 40 partner organisations offering 43 CASE collaborations and a direct plus in-kind contribution of £1.6M. Partners will contribute to the UNRISK core training programme through lectures and workshops covering climate datasets, methods of risk assessment in industry, measurement uncertainty, and the decision-making process. Partners will also co-develop and lead annual Challenge Weeks where students will apply their knowledge and skills to solve partner-related challenges proceeding from raw data through to policy decisions. UNRISK takes an equitable approach through open and continuously updated Areas of Research Challenge that will identify, at an early stage, the highest priority research and training needs to fill evidence gaps and meet the evolving requirements of the climate services sector. The success of UNRISK will be measured by the placement of students across key sectors, graduates pursuing careers in climate services, uptake of the research outcomes and tools, development of thought leadership, and scientific diversity in the research collaborations. We will ensure the legacy of UNRISK by integrating it into the existing Priestley Centre for Climate Futures, with established structures for continued engagement and business development, enabling our ambition to create a professional community of practice in climate services. In all aspects of the programme, UNRISK will set the highest standards of a positive and inclusive research culture. Key aspects include strong peer interaction through team-based learning and highly interactive Challenge Weeks, cohort programmes that acknowledge the value of host-university interactions, training that accounts for multiple levels of student preparedness, mentor schemes, and tailored support schemes to enable equitable access to our training programmes.

UKRI Gateway to Research · FY 2025 · 2025-06

Gravitational tidal interactions play crucial roles in the formation and evolution of planetary systems and binary stars. There is exciting new evidence for: tidally-induced orbital decay of hot Jupiters, including WASP-12b and Kepler-1658b, tidally-driven spin-up of planetary host stars, and tidal evolution of the distribution of stellar obliquities. The circularisation periods (essentially the maximum orbital period for which orbits are primarily circular) of hot Jupiters and close binary stars of various spectral types are thought to be explained by dissipation of tidal flows excited inside planets and stars. The mechanisms of tidal dissipation remain poorly understood however, despite their key roles in driving dynamical evolution and in the interpretation of current and future observations in these systems from e.g. WASP, NGTS, TESS and PLATO (ESA-funded with significant UK contributions, launching in 2026). We shall use numerical simulations from first principles to tackle the following key questions: (a) How does realistic differential rotation modify excitation and dissipation of tidal waves in stars and giant planets? (b) How do realistic magnetic fields affect tidal dissipation in stars and planets? Our results will be used to construct simplified, physically-motivated parametrisations of tidal processes for modelling observations. We will make these ready-to-run codes publicly available on GitHub so they can be incorporated in planetary and stellar population synthesis models. This project comes under STFC’s Science Challenge B (also a scientific priority of ASTRONET 2022-2035): How do stars and planetary systems develop and how do they support the existence of life? We will undertake the first global linear and nonlinear magneto-hydrodynamical (MHD) simulations of tidal flows in convection zones of planets and stars with realistic differential rotation (e.g. as observed for the solar convective envelope and Jupiter's atmosphere), density, and global magnetic field configurations, to understand dissipation of tidal waves in these bodies. This project will significantly advance our understanding of tidal dissipation in stars and planets, allowing us to make predictions for exoplanet systems and stellar binaries during the early stages of the PLATO mission. Our research is internationally unique and distinct in that we primarily undertake simulations from first principles, by directly solving the governing MHD equations. Our approach complements the tidal theory being developed elsewhere, and the results we obtain will guide our construction of new physically-motivated parametrisations that we will use (and publish for the community) for modelling observations.

UKRI Gateway to Research · FY 2025 · 2025-06

Neutron stars have the strongest magnetic fields in the universe, reaching 1015 G. These enormous fields determine their observational properties such as magnetar giant flares or magnetar-powered supernova explosions; see for example the review by Igoshev, Popov & Hollerbach (2021). Our group previously computed the first three-dimensional simulations for magnetic field and temperature evolution in the crusts of neutron stars for a range of initial configurations, including simple dipoles, also with additional toroidal components (Igoshev, Hollerbach, Wood & Gourgouliatos 2021a), off-centred dipoles (Igoshev, Hollerbach & Wood 2023), and stochastic small-scale fields (Gourgouliatos, Hollerbach & Igoshev 2020; Igoshev, Gourgouliatos, Hollerbach & Wood 2021b). We further presented the first three-dimensional calculations of ambipolar diffusion (in the single-fluid approximation) in neutron star cores, coupled with Ohmic decay in the crust (Igoshev & Hollerbach 2023). In the past 18 months we have also developed two new collaborations to incorporate further realism in our simulations. First, J. Guilet, R. Raynaud, et al. (France) have done numerical modelling of magnetic fields in proto-neutron stars (Raynaud et al. 2020, 2022; Barrere et al. 2022, 2023). We are collaborating with them to use the end-stages of their models as the initial conditions for our models, thereby avoiding the otherwise somewhat arbitrary nature of what initial conditions to choose. Second, A. Reisenegger (Chile), M. Gusakov (Israel) and others have been interested for many years in developing more realistic equations for ambipolar diffusion that go beyond the single-fluid approximation (Hoyos, Reisenegger & Valdivia 2010; Ofengeim & Gusakov 2018; Castillo, Reisenegger & Valdivia 2020). We have been collaborating with them on numerically solving some of these equations, with very encouraging preliminary results. The objective of this proposal is to build on this work, and ultimately conduct three-dimensional modelling that couples ambipolar diffusion in the two-fluid approximation in the core together with Hall evolution in the crust, thereby allowing us to understand how the fields in the core and crust interact, and how this affects the observational properties of magnetars. This has significant implications also for our understanding of superluminous supernovae, long gamma-ray bursts, and electromagnetic precursors to gravitational wave events from double neutron star mergers. Understanding the long-term magnetic field evolution is essential if we are to understand the diversity of observed neutron stars, and to decode future pulsar surveys including from the Square-Kilometer Array. This work addresses STFC Science Challenge A5: how do stars and galaxies evolve?

UKRI Gateway to Research · FY 2025 · 2025-06

Ultra-short period rocky planets (USPs) offer a unique opportunity to study the poorly understood interiors of exoplanets. Traditionally, interior properties are inferred from mass-radius relations, which are plagued by degeneracies and weak constraints (Rogers & Seager 2010; Dorn et al. 2017). However, the intense radiation that USPs receive means the atmospheres of USPs consist of gases evaporated from the magma pools present on the planets’ permanent daysides (e.g. Schaefer & Fegley 2009; Kite et al. 2016). We may therefore probe the interior composition of USPs by studying their atmospheres, or, for very low mass USPs, the comet-like dusty tails produced as their atmospheres escape (Rappaport et al. 2012; Perez-Becker & Chiang 2013). Models are needed to make the crucial link between the observed atmospheres and the planets’ interiors. However, a key ingredient of these models – the condensation of dust grains – is either missing or oversimplified (e.g. Perez-Becker & Chiang 2013; Ito et al. 2015; Zilinskas et al. 2022; Booth et al. 2023; Piette et al. 2023). This breaks the connection between the observed composition and the planets’ interior properties. The problem is particularly critical for the lowest mass USPs, which are probed via the deep, easy to observe, transits of their dusty comet-like tails. Dust condensation should also not be ignored for massive USPs because dust condenses in the flows from their daysides to their nightsides (Castan & Menou 2011; Nguyen et al. 2020). New models are therefore needed to leverage the wealth of JWST data that is becoming available for these systems, with current programs scheduled to observe more than 10 USPs, including multiple transits of the dusty-tail escaping from  K2-22b (GO programme 3315). We will solve this problem by developing a new dust formation model that can predict the size and composition of dust grains forming in USP atmospheres. We will couple the model to existing simulations of atmospheric escape from low-mass USPs, using the results to link the properties of dust seen in their comet-like tails to the planet’s interior composition. Next, we will characterize the mass-loss rates from low-mass USPs, needed to understand how common low-mass USPs are. Finally, we will address the cause of variability in USPs, which may be a general feature of USP atmospheres (van Werkhoven et al. 2014; Meier Valdés et al. 2023). Together, these advances will significantly increase our understanding of USP atmospheres, and consequentially their interiors.

UKRI Gateway to Research · FY 2025 · 2025-06

This project will develop the ability to measure, predict, and control the temperature-dependent scaling of the micromagnetic parameters in ultrathin magnetic films. We shall demonstrate our control by resolving a current controversy over the temperature gradient-driven motion of skyrmions. Our efforts will be based on our prior experience with the growth of magnetic multilayers, imaging of skyrmions, and recent advances in quantitative atomistic modelling. Understanding these scalings will lead to improved designs for current magnetic memory (MRAM), which are required to perform reliably at elevated temperatures at ever smaller sizes, and can also form the basis of future skyrmion-based storage technologies that offer ultralow energy storage, essential to meet the UK net zero carbon commitments by 2050. We can even envisage using these effects to scavenge waste heat by using temperature gradients to move data. Our project will establish reliable ways to determine the temperature dependence of the difficult-to-measure micromagnetic parameters (exchange stiffness A, and Dzyaloshinskii-Moriya interaction (DMI) strength D) alongside those for which well-established methods already exist (saturation magnetisation M, perpendicular magnetic anisotropy (PMA) constant K) that determine the energy of spin textures such as skyrmions in magnetic multilayers. Data from 'fruit-fly' magnetic thin films will be used to calibrate atomistic simulations, and this combination of theory and experiment will establish the effects of heavy metal interfaces, roughness/disorder and amorphous/crystalline structure so that the nature of the scalings can be controlled. We shall use this knowledge of how to control scalings to test the idea that skyrmions move either towards hot or cold ends of a temperature gradient under entropic forces.

UKRI Gateway to Research · FY 2025 · 2025-06

Protostars are born with dusty gas discs, as part of the star-forming process. Planets form within these protoplanetary discs through the gradual growth of solid dust particles into larger grains and then planetesimals, the building blocks of planets. Our current understanding suggests that planetesimal growth occurs over a timescale of around 1 million years. However, state-of-the-art observations reveal signs of planet formation such as dust rings in protoplanetary discs as young as 0.5 million years. This implies that planet formation begins far earlier than previously thought, probably as soon as the disc forms. Furthermore, we also observe some discs pulling in material from nearby gas clouds, a process known as late infall, meaning that protoplanetary discs do not evolve in isolation as our models assume. My fellowship will deliver the tools and predictions appropriate for the emerging paradigms that planet formation starts early in the lifetime of a protoplanetary disc and that late infall can occur, altering the planet-forming environment. Current models are inadequate for simulating the young discs in which planet formation must begin because they typically consider more evolved, settled discs. Young discs are over 10 times more massive and are therefore susceptible to the gravitational instability (GI) because the self-gravity of the disc becomes significant. The GI drives spiral arms, heats the disc and may cause the disc to fragment. Solid particles may clump in the spiral arms and these clumps may grow massive enough to gravitationally collapse, accelerating the growth of planetesimals. The local dust properties are closely linked to the cooling rate. This might provide a feedback mechanism to stabilize dust clumps against gravitational collapse and allow them to grow more massive. My primary goal is to develop disc simulations that link the thermal processes to the dust evolution for the first time. I will then simulate how dust clumps evolve in young discs to explore how the first planetesimals form. A further aim is to study how late infall changes the structure of the disc, and for how long, so that we can construct models to explore how ongoing planet formation is affected. I will also test how the addition of fresh interstellar gas to the evolved disc material alters the raw materials available for forming planets by modelling the chemical evolution. The results could explain the poorly understood diversity in the distribution of molecules among observed discs and the wide variation in the makeup of exoplanet systems. Alongside my research, I will develop and deliver Encounter Physics, a programme to link up year 10 widening participation students with physics university students and researchers (the physicists) to encourage the uptake of A Level physics among young people from disadvantaged backgrounds. For each school and cohort, the physicists will discuss their work, study, and life as a scientist with the same small groups of students over 4 visits. This will forge a connection between students and 'real' physicists to help year 10 students picture themselves studying physics. This fellowship will fill gaps in our understanding of the processes acting in protoplanetary discs by developing models for little-studied scenarios that we now expect to shape planetary systems. My results will provide the theoretical basis that we currently lack for interpreting observations of young discs and unlock the potential of the latest data from world-leading telescope facilities.

UKRI Gateway to Research · FY 2025 · 2025-05

The mobility landscape is undergoing rapid changes with the advent of new technologies and the growing complexities of travel patterns. NEXUS focuses on developing next-generation mathematical models of travel behaviour that can better predict the activity and travel decisions in this changing landscape. This is being achieved by developing new frameworks that bring together Choice Modelling (CM), Ubiquitous computing (UC) and Machine Learning (ML) techniques to utilise passively generated real-world mobility traces (from public transport smart cards, mobile phones, etc.), neurophysiological signals and virtual reality (VR) to model decision making in future scenarios. The research focus for the 1st phase has been to model day-to-day activity and travel decisions (choice of travel mode, destination, time-of-travel, etc.) - in the context of current and emerging modes (self-driving cars, air taxis, hyperloops) and in regular and challenging environments (e.g. pandemic, economic and social unrests). In the next phase, I plan to focus on extending the theme of fusing different types of data and bridging CM, UC and ML in the context of emergency situations - during natural disasters and acute transport network disruptions, in particular. The limitations of the current behaviour models for emergency situations (e.g., whether or not to evacuate, when to depart, which mode and route to take, etc.) arise from multiple factors. Firstly, they assume travel choices in such situations are based on rational decision-making principles which is often not the case. Rather, the choice alternatives in such scenarios have varying levels of uncertainty and the decisions very often are impulsive and based on 'gut feeling'. Secondly, the current models do not account for the myriad of psychological factors that could influence an individual's decision in such difficult situations, for example, the risk-taking propensity, the perceived effect of stress or the thinking process in general. Thirdly, very often there is an element of 'collective behaviour' in such situations where a group of decision-makers influence each other's decisions consciously or unconsciously. This is challenging to capture in the modelling framework. Finally, the data used for developing the models rely on small-scale surveys where travellers are asked to report/log their past behaviour or to state their choices based on descriptions of hypothetical scenarios.These very often are not reliable measures of real-world travel behaviour. On the other hand, advanced technologies and machine learning methods have made it possible to measure the 'cognitive state' of travellers with simple wristbands, discreet clip-ons and smartphone-based sensors and infer their 'thinking process' from brain images. Further, advances in virtual reality (VR) technology have made it possible to immerse travellers in simulated emergency scenarios (e.g. VR replications of wildfire, stormy weather preceding hurricanes, collapsed tunnels, etc.) and obtain more realistic responses. These advances hold promise for producing more realistic inputs leading to a step change in modelling travel behaviour in emergency situations. The focus of the renewal phase of NEXUS will be to address the research gaps in modelling travel behaviour for emergency situations by leveraging novel forms of data. These will include (a) real-world mobility data generated from mobile phones, social media and other passive sources; (b) experimental data on travel behaviour from VR settings of hypothetical emergency scenarios. The applicability of the framework we are developing in the 1st phase of NEXUS to unify CM, UC and ML will be extended to achieve the objectives. In addition, other approaches like 'simulation-based data fusion' will be explored and compared. The developed models will enable planners and policymakers to test the impact of alternative scenarios in emergency situations in a more robust manner.

UKRI Gateway to Research · FY 2025 · 2025-05

The last 20 years have witnessed a remarkable growth in the field of terahertz (THz) frequency science and technology.  Supported by strong and on-going research investments in the UK, and internationally, and the progressive translation of research into industry, the field has matured into a vibrant and impactful area of international research, with a global market estimated to be worth $600–900 million in 2023. Previously, the University of Leeds led the UK Network “Teranet” (funded 2014–2018) that had a primary aim of overcoming the fragmentation of UK THz science and technology, which had previously been driven by several separate UK scientific communities, each developing complementary but different technologies.  Through an inclusive approach to a series of large national meetings, and engagement with professional bodies such as the Royal Society of Chemistry, we successfully brought the UK THz community together; a particular highlight was the community-driven generation of international THz Science and Technology Roadmaps in 2017 and in 2023, both published in the Journal of Applied Physics. We will now establish a new NetworkPlus based on a systems-level approach to bring about deeper collaboration between the UK and international terahertz communities, and act as a focal point for UK research in terahertz science, devices, systems and their applications.  The potential benefits to the UK from the new collaborations will be substantial, ranging from fundamental science to commercially relevant applications with significant potential for economic and societal impact.  Our network will complement existing research programmes, build UK capability and future leaders, and drive and facilitate multi-disciplinary collaboration and knowledge exchange across research and stakeholder communities in the UK and internationally. These aims will be delivered through the following Objectives.  We will: Develop new, and enhance existing, connections and collaborations between the UK and international terahertz communities (including, for example, through UKRI lead agency agreements), with an immediate focus on capitalizing on the opportunities afforded by the current DFG INTEREST programme. Establish six thematic and inclusive Special Interest Groups (SIGs) representing the diverse, interdisciplinary UK terahertz community, to drive technical and collaborative research, and knowledge exchange. Showcase the best of UK science and technology, and the new research engendered by the NetworkPlus and the current EPSRC call for research projects in Terahertz Technology and Systems, accelerating knowledge transfer through annual national meetings. Facilitate and enhance collaborations by funding travel, mobility and small-scale innovative pump-priming activities, pilot projects and feasibility studies using a flexible funding scheme. Encourage greater impact through sector-specific terahertz Industrial Engagement meetings, training events led by Industry, showcase meetings, and SIG workshops. Support early and mid-career academics, and empower them to engage widely, and effectively, with business and with international colleagues through a structured programme of career development activities. Develop a ten-year Roadmap for Terahertz Science and Technology, co-created by the NetworkPlus stakeholder communities. This will identify important research and innovation opportunities, and the pathways needed to deliver significant impact, along with potential interventions needed by policy makers and funders. Deeply embed ED&I considerations in the Network’s management, governance and all its operations, supported by ringfenced Access and Outreach funds. Provide advocacy for the terahertz community and EPSRC investments on behalf of all NetworkPlus stakeholders.

UKRI Gateway to Research · FY 2025 · 2025-05

Plasmodesmata (PD) are crucial signalling hubs in plants mediating the cell-to-cell transport of signalling molecules, metabolites, proteins and the spread of viruses. The cell walls surrounding PD are enriched in the beta-1,3 glucan polymer callose. Changes in callose metabolism, in response to developmental and environmental cues, coordinates intercellular transport and plant growth. Despite its importance, the properties of callose and the impact of its accumulation in cell wall architecture, elasticity, ductility and adhesion are virtually unknown. PD-Wall Mech is an interdisciplinary project that aims to dissect the mechanical and structural properties of PD cell walls with the goal of exploiting this knowledge in crop improvement and biomaterial development. The research through my FLF revealed that callose populations, of different size and structure, differentially accumulate at PD and interact with cell wall glycans. My work also found that callose increases cellulose plasticity and water holding capacity which impacts cell wall biomechanics. During the renewal, this knowledge will be applied in the identification of molecular factors for the design of strategies to improve fruit growth. The regulation of calloses and callose-glycan interactions will be analysed in (tomato and strawberry) fruits at different developmental stages and after mis-expression of endogenous callose-metabolic enzymes. Changes in cell wall biomechanics will indicate the potential effects of callose regulation in cell/organ growth and resilience to mechanical stresses. Molecular tools developed to study callose and glycan-interactions during the FLF, will be applied in screening the composition of fruit lignocellulosic waste (leaves and stems) aiming to identify its suitability for biomaterial development. This project key strength is its interdisciplinarity bringing physical and biological sciences together to address real world challenges. In brief, the renewal objectives are to:   R.Objective 1: identify markers and the regulation of callose structures during organ growth. R.Objective 2: determine the contribution of callose structures to cell/ tissue biomechanics. R.Objective 3: apply callose knowledge and molecular probes in biomaterial development.   The work tackles pressing global issues related with the impact of climate change on food security and sustainability. The work has applications in improving the growth, shelf-life and nutritional value of fruit crops through translation of fundamental knowledge on PD and cell wall regulation. The UK Fruit & Vegetable retailers industry is valued at £12.4bn in 2024 (ibisworld), but only 16% of fresh fruit were produced domestically. By addressing fruit growth, the project will benefit farmers and the UK economy and eventually decrease fruit imports. The project will also generate value from crop biomass through exploitation of our molecular tools and callose plasticizing properties in bioengineering cellulose. This will support the design of sustainable and eco-friendly cellulose-based products to substitute plastic and reduce agricultural waste. The project addresses BBSRC priorities on ‘sustainable agriculture and food security’, ‘transformative technologies’, and ‘Frontier Bioscience’. It aligns to the EPSRC themes ‘manufacturing the future’, ‘soft polymer physics’, and the cross-councils strategy on ‘Engineering Biology’. This project will deliver academic impact and contribute to build the UK workforce by training researchers in an interdisciplinary area. Working in partnership with industry and academia will maximise the research impact and contribute to UKRI five-year strategy: ‘Transforming tomorrow together’. Ultimately, the research will provide a roadmap for exploitation of knowledge in cell walls and PD on the improvement of other crops and on the sustainable use of lignocellulosic resources.

UKRI Gateway to Research · FY 2025 · 2025-05

Chronic pain is a debilitating condition that affects up to a third of the world’s population. This not only brings suffering to people affected by the condition but also costs our economies billions in healthcare costs, lost productivity etc. Current treatments are often inadequate and may even cause other socioeconomic downfalls, such as the prescription opioid abuse epidemic. Development of new analgesic therapies is hampered by low success rates and underinvestment. This highlights both, the insufficient understanding of pain mechanisms and limitations of our preclinical models to study pain. We will capitalise on two significant advancements by our team in both of the above areas: (i) We discovered that specific neural structures residing outside the brain and the spinal cord can control how much of a ‘pain’ signal is delivered by a nerve to the central nervous system (CNS). These structures are called ‘dorsal root ganglia’ (DRGs) and these can be targeted for pain relief with drugs and treatments that do not affect the brain in the way opioid drugs do. (ii) We developed a reduced preparation that we call ‘decerebrate arterially perfused preparation’ (DAPP), which allows an unprecedented level of access for measurement of neural processes associated with pain and excludes animal suffering. It combines advanced electrophysiology with computational processing of recorded signals and allows precise, unbiased measurement of key signals mediating pain responses, circumventing analysis of behavioural responses to painful stimuli. Furthermore, the approach allows a unique opportunity to precisely quantify how DRG controls pain. As DRGs are outside the CNS and are accessible to circulation, this creates a window of opportunity to discover therapies with much better safety profiles than currently available drugs. Moreover, our approach helps to develop an understanding of an effective approach to treat chronic pain, whereby an electrical stimulation of the DRG via implanted electrode is performed, it is called ‘DRG neuromodulation’. The approach is powerful but controversial, as it involves electrical stimulation of a nerve that can trigger pain in a person. Yet, our approach reveals a possibility of how such stimulation of a DRG can effectively block the painful signals travelling through the nerve. The overall objective of this proposal is to use our innovative approach to develop a precise understanding of how DRG controls pain, with an overarching aim to develop better pain treatments. This objective will be achieved through four focused aims: Aim-1: To understand how DRG controls pain using DAPP. Aim-2: To understand how DRG neuromodulation produces analgesia and to develop a way for selecting the best parameters for such neuromodulation. Aim-3: To understand how chronic pain changes the DRG’s function and how to adjust DRG neuromodulation to combat chronic pain better. Upon completion of this project, we will establish a new preclinical approach for pain research, will provide critical new insight into the mechanisms of pain control by the structures within the peripheral nervous system and will provide a basic understanding of an efficient but poorly understood clinical procedure to treat chronic pain. Additionally, we will develop guidelines for adjusting this therapy for more efficient pain control. This project may shape new and innovative approaches for analgesia and chronic pain management, bringing far-reaching benefits not only for the fundamental science but, ultimately, for individuals suffering from chronic pain.

UKRI Gateway to Research · FY 2025 · 2025-04

High performance computing (HPC) is an essential tool for science and society. From weather forecasting to large-scale data analysis, HPC enables efficient simulations and predictions. At the fundamental level high-performance computers are good at performing many basic operations, such as addition and multiplication, upon which more complicated operations and applications are built. As an example, the fastest supercomputer in the TOP500 list, Frontier, has almost 9 million processors and has been observed to perform ~1.1 * 10^18 operations per second. In the push for performance, high-performance computing often trades off accuracy for speed, by simplifying basic building blocks in the hardware and increasing the rounding errors induced in the basic operations. The shortcuts taken by the hardware designers can make devices diverge from the standard well-known behaviour, and often the differences are not documented. Two pieces of hardware from different manufacturers may perform operations at different speeds and give different results, because designers implement features such as rounding differently or use a different number of digits in adding and multiplying. Due to this, applications are not reproducible and we cannot predict in advance what will happen on a new device. We now understand well that the hardware from 2016 onwards started along this path. As we are running various computations directly relevant to the public on these computers, such as climate and weather simulations, the discrepancy between devices requires investigation through a systematic study. For example, Met Office in Exeter have a high-performance computer that allows them to make 215 billion weather observations from all over the world every day. Computer Scientists and Mathematicians have come up with ways to run carefully designed programs that inform us about the underlying numerical features of the devices, such as rounding or precision of calculations. However, the state-of-the-art approach involves a lot of manual work based on very specialized mathematical knowledge. It is prone to human errors—when new devices appear, engineers have to change the software to determine what differences they have compared with the previous devices. This project is about improving the existent methods, by focusing on three core aspects: automating, removing the need for specialized knowledge, and informing the public about the features of the current hardware. In more detail, the project has three main outcomes: theoretical methods to search for undocumented hardware’s mathematical features automatically; a library of known behaviours of hardware, which will be publicly available and continuously updated by us and the community that we will develop, as the hardware is converging to standardisation over the next decade; and software that can report numerical features to users, which will not require highly specialised knowledge. These outcomes will impact the industry that is creating mathematical hardware, the users that depend on the accuracy and consistency of it and are not always getting that due to the shift in how the hardware is designed, and ultimately the standardisation of mathematical hardware. As hardware converges to standardisation in the next decade, the tools developed in this project will become a test for compliance.

UKRI Gateway to Research · FY 2025 · 2025-04

Antheia is a timely, innovative project that will use Earth observation data to quantify changing surface water pools on northern peatlands. Peatlands represent one of the world's most carbon-dense ecosystem types, and pools are hotspots for peatland-atmosphere carbon gas fluxes, biogeochemical processing, and aquatic biodiversity. Worryingly, evidence is growing that peatland pools across a range of northern biomes are beginning to change, in some cases rapidly, in response to climate change, with important potential consequences for peatland ecosystem functions and services. Pools are hotspots for methane emissions, and increasing pool area leads to increased emissions. In high latitudes, thaw pools are expanding across some permafrost peatlands. At the same time, longer, warmer growing seasons are causing these and other peatland pools at lower latitudes to be overgrown by semi-aquatic plants, causing some pools to shrink rapidly. Further still, shifting snowmelt regimes are affecting seasonal meltwater pools and reducing local water availability during growing seasons. However, the evidence for these changes in pools is typically based on studies of individual sites, and there is currently no global system capable of monitoring peatland surface water cover at large scales. As such, it is unclear how widespread these changes in peatland pools are, how quickly they are proceeding, or whether pool area is growing or shrinking on a net basis in different climatic zones. Named after the ancient Greek deity of swamps and wetlands, Antheia will be the first system capable of providing such monitoring, using three decades of satellite radar data to look down upon the wet places of the world and assess their changing condition. Antheia will combine, refine and validate preliminary methods that we have developed and trialled, using satellite radar data to detect open water surfaces on peatlands, including beneath tree canopies. We will compare predictions from the new system to in situ monitoring of peatland pools, and to very-high-resolution satellite data that are available for recent years. We will then apply the system to current and historical satellite radar data from the northern hemisphere to estimate changes in the size of permanent peatland pools, and changes in the timing and extent of seasonal pools, such as those that develop after spring snowmelt. Finally, the project will deliver a free, public, online data portal that will allow users to query, visualise and download the latest estimates of peatland surface water cover from locations of their choice, based on automated processing of near-real-time satellite data. Antheia is unprecedented in terms of its scale and ambition for peatland monitoring, incorporating the entire northern peatland domain, and spanning more than three decades. The global nature of the project means that it will provide important benefits for NGOs and policy makers involved in peatland conservation and restoration, both in the UK and internationally, and to scientists involved in large-scale Earth surface modelling, and the study of catchment biogeochemistry and aquatic ecology. Antheia will deliver the first estimates of long-term changes in surface water cover across northern peatlands. This information will be of direct use in assessing the impacts of climate change upon these ecosystems, and directing conversation efforts such as hydrological management to those locations most in need of it. Targeted expert-user workshops throughout the project will leverage additional impact amongst scientific and stakeholder communities.

UKRI Gateway to Research · FY 2025 · 2025-04

Cardiac myosin is the molecular motor that drives heart contraction, powered by the energy-source ATP and through its interaction with actin tracks. Direct modulators of cardiac myosin function are promising treatments for inherited heart disease and heart failure. The inherited heart disease hypertrophic cardiomyopathy affects 1 in 500 people and is the most common cause of sudden onset cardiac death in the young, causing approximately 12 deaths in the UK every week. Heart failure is an increasing worldwide public health issue with an estimated prevalence of 64 million people, a mortality rate of approximately 50 % within five years of diagnosis, and an estimated cost to the economy of $346 billion. Current treatments improve heart function but not patient survival. Direct myosin modulators have the potential to do both. A first-in-class cardiac myosin inhibitor, Mavacamten, was approved by the FDA for the treatment of symptomatic obstructive hypertrophic cardiomyopathy (oHCM) in 2022. Whilst the muscle activator Omecamtiv mecarbil (OM) has been shown to improve cardiac function in patients with systolic heart failure, modestly decreasing heart-failure events and deaths in a Phase III trial. Consequently, the potential use of direct myosin modulators for the long-term treatment of various muscle diseases has been more broadly recognised and many other myosin modulators have entered clinical trials. Importantly, despite a range of pre-clinical studies, we still have very little idea as to how these modulators work at the molecular level. This hinders their clinical usage and development. Mavacamten is only available under a restricted programme because it can reduce systolic function (ventricular contraction). OM has just been withdrawn from further clinical trials after failing to obtain FDA approval following a lack of evidence for long-term effectiveness. Thus, understanding the molecular modes of action of these modulators is crucial to understanding how they may work as therapeutics, to enable the identification of patient populations that can most benefit from them, to predict prospective adverse effects, and to inform on the design of improved myosin modulators with better long-term outcomes. Here, we will study the effects of Mavacamten and OM on diverse structural states of myosin, and the dynamics of those states, as myosin cycles through non-force producing off-actin states crucial for relaxation of muscle and on-actin force-producing states crucial for contraction. We will achieve this using our well-established cryo electron microscopy pipeline to study myosin structural states coupled with structural mass spectrometry approaches to capture myosin dynamics, complemented by kinetic assays to assess myosin function. With this structural, dynamic, and functional knowledge, we will predict the effects of these modulators on myosin function in the presence of HCM disease-causing mutations and test these predictions for specific mutations. This will provide unprecedented detail of the effects of the modulators Mavacamten and OM on the cardiac myosin functional cycle in health and disease, provide an experimental pipeline for the assessment of the molecular mode of action of other modulators, currently in clinical trials, and for the structure-guided design of improved myosin modulators with the potential for improved patient outcomes.

UKRI Gateway to Research · FY 2025 · 2025-03

The challenges associated with developing new medicines are very significant indeed. The cost of bringing each new drug to the market is over £2 bn, in large part because of crippling (>95%) attrition rates in the drug discovery/development process. Even when successful, the process typically takes about 12 years from laboratory to patient. The pharmaceutical sector therefore faces the major challenges of increasing both productivity (by reducing costs and time-to-patient) and innovation (by finding drugs with new modes of action and/or for new disease areas). Most drug molecules function by modulating the function of a protein that is associated with disease. In most cases, these drugs bind into a pocket on the protein in a manner that is analogous to a key fitting into a lock. Recently, however, there has been a resurgence of drugs that function by forming a covalent bond to their target protein. Such drugs provide new therapeutical opportunities, and include ibrutinib (which treats cancers including chronic lymphocytic leukaemia) and nirmatrelvir (which treats COVID-19). Most commonly, covalent inhibitors are designed to target a nucleophilic cysteine, a strategy whose success relies on the presence of a suitable residue that is not susceptible to mutation. In this grant, we will develop a new chemical approach to drive the discovery of covalent inhibitors of specific protein kinases. The envisaged high-throughput synthetic approach will enable structure- and function-diverse kinase probes to be prepared by linking pairs of functionalized building blocks. Our approach is expected to be general because protein kinases contain a conserved lysine residue that may be capable of forming a direct connection to covalent inhibitor. Furthermore, the approach is expected to be important because the protein kinase class comprises around 700 different proteins, many of which are central to disease (including many cancers). It is envisaged that our approach will enable the discovery of useful chemical tools (which can be used to investigate the fundamental disease biology of specific protein kinases) and to provide new starting points for drug discovery. The approach therefore has the potential to unlock many new opportunities for addressing unmet patient needs. To maximise the impact of our approach, we will engage extensively with end-users of our research, including through a workshop and end-user-focused scientific meetings. To highlight its value to drug discovery and biomedical scientists, we will demonstrate that our approach can drive the discovery of specific chemical probes. We will make our probes openly available to the biomedical community (including Dundee Drug Discovery Unit, the largest such unit in Europe), enabling them to be exploited as chemical tools to address biomedical problems beyond this project. The availability of these chemical probes may provide new insights into disease biology that may be translated into drugs that benefit patients. In addition, drug discovery is a topic of great interest to the public, which will enable us to develop and deliver impactful public outreach activities.

UKRI Gateway to Research · FY 2025 · 2025-03

Although glaciers cover only ~10% of Earth's surface, their meltwater rivers are used extensively for hydropower, irrigation and water supply by almost 2 billion people worldwide. Aquatic organisms in these rivers, such as micro-organisms, algae and invertebrates, maintain these critical services by efficiently transferring matter into aquatic and terrestrial food webs, moderating nutrient fluxes, and breaking down pollutants. Conversely, some aquatic organisms pose threats to human health if conditions enable their proliferation. However, glaciers are losing mass at accelerating rates worldwide and many will disappear by 2100, creating huge uncertainties about how these ecosystems will respond. Understanding of biodiversity and functional processes influencing river water quality, and how they change as glaciers are lost, is especially poor for the Himalayas yet this is where the demand for clean water is highest, and people are most vulnerable. This project will develop and implement a standardised, multi-organism research strategy for high-elevation rivers in Nepal, in which ecological understanding is integrated with modelled glacier retreat scenarios to predict how and where species distributions and water quality will change in future. The objectives are to (i) determine the biodiversity of these unique river ecosystems; (ii) discover the functional roles of micro-organisms and invertebrates influencing key water quality and carbon cycle processes; (iii) unravel the importance of physical, chemical and biotic processes alongside dispersal barriers for governing where species can live now and in future. In doing so, we will (iv) reveal how species, communities and ecosystem processes that are critical to maintaining high-quality water will respond as climate change drives high-elevation warming and glacier recession. The project will develop a new strategy for monitoring high-elevation rivers, leveraging expertise from academic and local sources, including DNA-based surveys and logistical support for expeditions in challenging mountain environments. The research will focus on three regions (Annapurna, Langtang, Sagarmatha (Everest)) with high biodiversity and varied river conditions, with an emphasis on Archaea, Bacteria, Fungi, Algae and Invertebrates. Repeat sampling in Sagarmatha will track seasonal dynamics to melt cycles and monsoon rainfall. The project consists of work packages focusing on (i) current population dynamics, (ii) community structure and functional processes influencing water quality, and (iii) modelling studies to determine the processes structuring these communities as well as predictions for how future glacier loss to 2100 will impact rivers. Key findings from these linked work packages will inform reports, scientific publications and data packages for a variety of users. The Himalayas are experiencing rapid warming and ice loss, posing a significant threat to their rich biodiversity. Therefore, this research will be a vital baseline for biodiversity and water quality monitoring to benefit conservation, government, and businesses. As glaciers recede, new land will be exposed attracting extractive industries and increasing dam construction, further endangering biodiversity and requiring sustainable solutions. Changing water sources may also expose communities to pathogens requiring upgrades to drinking water treatment. The project will benefit scientists by advancing wider understanding in ecology, in particular mechanisms of ecosystem resilience to climate change and disturbance, and trait-based approaches to predict ecosystem structure and processes. Students and the public will benefit via website and media dissemination. Open-access data will allow other researchers to compare findings and contribute to global comparative analyses. Through existing roles, the team will communicate findings to IPCC assessments ensuring the research informs global policymakers.

UKRI Gateway to Research · FY 2025 · 2025-03

Background: Complex climate-health emergencies (CCHEs) are crises/disasters caused by co-occurring and compounding medical, social, cultural, political, and environmental stressors that overwhelm health systems, create economic and political instability, undermine social systems, and exacerbate poverty1-4. CCHEs increase morbidity and mortality associated with a variety of health risks, including food insecurity, (non)communicable diseases, and the impacts of environmental and climatic change5-7. In an interconnected world that is undergoing rapid change, CCHEs are becoming increasingly common, posing significant threats to marginalised populations such as Indigenous Peoples , who make up ~5% of the global population4,8-10. CCHEs pose a major threat to health in the global South, especially for Indigenous Peoples who face unique health challenges, while also inhabiting areas seeing rapid environmental change10-13.  These challenges are linked to the social determinants of health including poverty, inadequate access to health services, discrimination, land dispossession, and colonization which continue to restrain and undermine Indigenous values and decision-making structures10,14-17.  Interventions and policies targeting Indigenous health are often ineffective as they fail to consider local understandings of health and health seeking behaviours, inappropriately ‘scaling-up’ from the experiences of non-Indigenous populations16-20. Indigenous Peoples have been uniquely impacted by COVID-19 and will face highly context-specific combinations of factors creating CCHEs in the future2,9,21. There is a lot we can learn from the ongoing experience of such complex health emergencies including the recent COVID-19 pandemic and extreme climatic events in terms of: i) characterizing how different health risks combine to create CCHEs in specific places, and for health and food systems; ii) understanding the factors that shape the creation and evolution of CCHEs, and determine health and food system resilience and vulnerability, and iii) generating evidence on the strengths and weaknesses of different policies and interventions. To do this, a transdisciplinary approach offers the tools to promote collaboration across sectors, disciplines, and ways of knowing, and will be employed here to deliver a research project that will have real impact on Indigenous People's lives. Our Overarching goal is to document, understand, and monitor the factors affecting the creation, evolution, and impact of CCHEs among Indigenous communities in the global South, examining the interaction between climatic and non-climatic stresses, and co-generating knowledge and capacity to build resilience in health and food systems and support pilot interventions. Conceptual underpinnings: This study starts from the premise that Indigenous Peoples are active players in how they experience and respond to environmental crises like climate change and biodiversity loss15,22,23. Resilience and vulnerability to climate impacts are socially constructed and closely linked to issues of sovereignty, power, social justice, land tenure, development, and history15,24-27. To further the design and implementation of co-produced health and food systems resilience and adaptation for Indigenous Peoples, research needs to focus on these root causes, which vary by location and Peoples15,23 . Methods: We will work with on-the-ground Indigenous Peoples Observatories we have established in the global South, working in 6 countries, and partnering with 12 Indigenous groups living in 30 communities: Asháninka and Shawi (Peru); Batwa (Uganda); Coastal-Vedda (Sri Lanka); Mapuche (Argentina); Yukarés and Tacana (Bolivia) and Paniya, Kattunayakan, Kurichiya, Pahari Korwas and Gond (India). These regions and Indigenous Peoples are experiencing wide-ranging food system shifts due to social, economic, and political transitions rooted in colonization and globalization, which are exacerbated by climate and environmental change. While focusing on CCHEs in their broadest sense and thus covering a diversity of health risks specific to each location, across the study regions an in-depth focus will be directed to the intersection between climate-related hazards (e.g. wildfires, flooding, storms, drought) and food and nutrition sovereignty and security. Within each country, the Observatories will be composed of i) community observers ii) policy observers, and ii) in-country researchers. We will complete repeated semi-structured interviews with our community observers monthly for 1 year to collect real-time information (e.g. observations, stories, perceptions, understanding) about the presence, experience and responses to extreme climatic events as they intersect with health and food systems. Study pillars and principal research questions: The study is structured around 5 Pillars. Pillar 1 provides the scientific grounding, asking: based on the experience of recent extreme climatic events, what combination of factors interact to create CCHEs for Indigenous communities in the global South? Pillar 2 focuses on supporting health systems, asking: what types of intervention can strengthen health and food systems to manage CCHEs? Pillar 3 asks what can we learn from the study regions for Indigenous communities more broadly? Pillar 4 focuses on catalyzing impacts at local and global levels, and Pillar 5 supports individual and institutional capacity strengthening and development. Team overview: The project will leverage and strengthen cross-cultural transdisciplinary partnerships, building from existing partnerships and creating new ones. Team members have expertise in climate research, public health, geography, epidemiology, international development, ecology, food and nutrition security, sociology, philosophy, ethics, Indigenous studies, and medicine. The gender-balanced team includes researchers who identify as Indigenous (including the PI), globally renowned senior researchers, directors of global research institutes, early and mid-career researchers, and is multilingual (e.g. Spanish, English, Portuguese, Indigenous languages), and are building leadership in applied climate-health. Each country partner had identified Indigenous Knowledge holders to collaborate with in the implementation of the research and intervention activities. Our proposal has the support of UN officers from the FAO Indigenous Peoples Unit, Alliance of WHO for Health Policy and Systems Research, and PAHO to help us translate our findings from specific communities and regions to inform global policies. This project brings together researchers who have been working in the study regions collectively and independently for over a decade. In addition to our past individual productivity, in coming together to build this proposal, the team has already co-authored 6 articles, including in the Lancet Planetary Health.

UKRI Gateway to Research · FY 2025 · 2025-03

Hepatitis E virus (HEV) is the most common cause of acute viral hepatitis worldwide, for which there is no treatment or vaccine. Although generally HEV infection has a low mortality rate, in some situations (e.g., during pregnancy) this can reach 25%.The WHO estimates that there are >20 million cases of HEV infection p.a., resulting in >3% of all viral hepatitis-related mortalities. The virus is transmitted through consumption of contaminated food/water, however, it also infects animals (e.g., pigs) from which it can be transmitted to humans zoonotically. HEV was unrecognised until the 1980s and many fundamental aspects of the viral replication-cycle are not understood. Understanding how HEV replicates to cause disease can identify therapeutic targets. All viruses related to HEV produce a large polyprotein that is digested by a virally produced proteolytic enzyme to generate functional protein units and is essential for controlling virus replication. However, we are starting to understand that HEV breaks this dogma. Instead, we propose HEV does not produce a protease and is dependent on a host cell protease such as thrombin for replication, making HEV biologically unique. The aim of this proposal is to understand how thrombin acts as a key, novel, regulator of polyprotein processing to control HEV replication. Importantly, HEV replication is sensitive to clinically used thrombin inhibitors. A greater understanding of how the HEV polyprotein is processed and the function of host proteases would benefit global populations through the identification of novel therapeutic targets.

UKRI Gateway to Research · FY 2025 · 2025-03

Recent Artificial Intelligence (AI) research has given rise to a paradigm shift brought by Large Language Models (LLMs). Though LLMs arose from research in Natural Language Processing (NLP), it is well-known today that zero-shot and few-shot transfer learning methodologies as well as novel prompting strategies make their deployment possible beyond the NLP field, achieving impressive performance on a significant range of domains and downstream tasks. However, the deployment of LLMs in geographic information systems is still in its infancy. The Geo-R2LLM project aims to create a novel paradigm for building knowledgeable and multimodal geographic LLMs by rethinking LLMs generation mode with retrieval and reasoning over multiple multimodal external knowledge sources to ground predictions. The improved multimodal geographic LLMs will be integrated in a geospatio-temporal AI (GeoAI) system prototype and evaluated on a pilot application related to context-aware navigation systems in a complex urban environment. Navigation services can be considered as one of the most critical and widely adopted location-based services in modern society, hence the project has potentially strong impact also outside of academia. This research will lead to fundamental advances in multiple disciplines spanning GeoAI, spatio-temporal reasoning, information retrieval, and natural language understanding, laying the groundwork for more effective AI platforms for various domains that relate to geography and geographical information science.

UKRI Gateway to Research · FY 2025 · 2025-03

Oligonucleotides (OGNs) are an important class of biomolecules, but until recently somewhat neglected in structural biology research. Well-known functions range from storage of inherited information to gene regulation; but short DNA and RNA sequences can also provide interaction motifs for proteins and antibody-like high-affinity binding e.g. for small molecules (aptamers). Recently there has been a surge of interest in OGNs and their derivatives for potential use as drugs and vaccines, but also as targets of pharmaceutical intervention. Following the hypothesis that structure informs function, we need to understand fundamental principles of structure-function relationships for OGNs, which can also be dynamic and partly unstructured. Currently our insights and toolkit are limited: many of the interesting sequences are either too small for cryo-EM or too dynamic to easily yield x-ray structures. NMR spectroscopy has delivered valuable insights, e.g., for single-strand DNA aptamer and G-quadruplex sequences, but is neither fast nor routine and requires considerable expertise and amounts of sample. Mass spectrometry (MS) has become a breakthrough technology for biomolecular characterization in the last 25+ years. It can link information on small changes in the protein sequence (such as post-translational modifications or mutations) with higher-order structure (folding) and interactions, and deliver exceptional insights into intrinsic disorder and lipid interactions. While not actually providing high resolution images, structural MS approaches such as native MS, ion mobility, chemical crosslinking and labeling, and hydrogen-deuterium exchange (HDX) can nevertheless characterize dynamic and heterogeneous distributions of conformational states and interaction stoichiometries, at high sensitivity and with little bias. They are often used in conjunction with other approaches including computational modeling. For OGNs, some work has been done with native MS and ion mobility (which determines global size and shape) to study structure and interactions of aptamers, G-quadruplexes and DNA nanostructures, but there is much left to understand and explore. Here we propose to develop and apply hydrogen-deuterium exchange (HDX)-MS approaches for the study of dynamic oligonucleotide structures of biological interest. This work aims at gaining fundamental insights into OGN folding and interactions to guide pharmaceutical strategies. We will pioneer HDX-MS for OGN structure, an almost entirely unexplored approach. For proteins, the technique has become a key enabler for studying binding interfaces, allosteric effects and biopharmaceutical design, with substantial recent investment across research institutions in academia and industry. No equivalent methodology exists yet for OGNs due to lack of knowledge of exchangeable residues and their timescales, quenching conditions and back exchange, and suitable digestion strategies and chromatographies. In order to address these challenges, we will initially explore the ability of HDX-MS to detect defined structures (single/double-stranded DNA, mismatches/kinks and crosslinks, stem-loops etc.), using simple short test sequences. The approach which we will take to reach the aims detailed above includes three objectives, with work packages built around them: 1. Establish comprehensive OGN HDX-MS methodology 1.1 "Global" HDX of native OGNs with UVPD fragmentation 1.2 In-line digested LC-MS analysis to mirror protein HDX 2. Demonstrate structural characterization using simple motifs 2.1 Detection of single vs. double-stranded sequences 2.2 Aptamer folding and ligand interactions 2.3 Characterization of G quadruplexes 3. Apply OGN HDX-MS to biological questions 3.1 Collaboration with Wu (Leeds) 3.2 Collaboration with Dillingham (Bristol)

UKRI Gateway to Research · FY 2025 · 2025-03

A number of hereditary muscle disorders cause muscle weakness coupled with susceptibility to malignant hyperthermia (MH), a potentially fatal reaction to the most commonly used general anaesthetics. These disorders which include the core myopathies, and the recently described STAC3 myopathy, affect childhood development and quality of life, and shorten life expectancy. All involve genetic variants affecting constituents of the calcium signalling machinery required for normal function of skeletal muscle, but the mechanisms by which these variants cause progressive muscle weakness or malignant hyperthermia are poorly understood. In the last 10 years, STAC3 protein has been found to be a key protein in skeletal muscle development, with a role in excitation-contraction coupling. Much of the progress in understanding the role of STAC3 led from the discovery that a missense variant in the STAC3 gene caused a congenital myopathy associated with MH. However, the possibility of further advances with the previously available tools is limited. Our aims are to use a new transgenic mouse model of STAC3 myopathy to define the specific role of the STAC3 protein in muscle calcium signalling, and the mechanisms by which dysregulated calcium signalling lead to myopathy and to MH. Our hypothesis is that the clinical features of STAC3 disorder result from skeletal muscle cellular calcium dysregulation and consequent mitochondrial dysfunction, both of which represent viable targets for drug treatments for STAC3 myopathy, for which there are currently no specific treatments. The work encompassed within this application builds on our successful bid for a Stac3 knock-in mouse under the MRC 'Genome Editing Mice for Medicine' call. Here, we propose to execute the work described in the justification of our GEMM application. We will characterise the morphological, histological and MH susceptibility phenotypes of the Stac3 mice and detail the developmental changes that result in the post-partum phenotypes. We will perform detailed studies of the skeletal muscle molecular pathophysiology in myotubes derived from Stac3 pW280S homozygous, heterozygous and wild type mice. The first strand of myotube studies will focus on the detailed mechanism of the primary derangement of Ca2+dysregulation. Using appropriate fluorescent Ca2+ indicators we will measure changes in cytosolic Ca2+ concentration, sarcoplasmic reticulum (SR) stores, SR leak, evoked SR release and different mechanisms of Ca2+ entry. As part of this work we will establish whether dantrolene, the clinical antidote for MH associated with the more prevalent RYR1 variants, is likely also to be of benefit in STAC3-associated MH. The second strand of myotube studies will focus on the mitochondria, as targets for secondary effects of skeletal muscle Ca2+ dysregulation. We will use confocal microscopy with appropriate indicators to quantify mitochondrial mass and turnover, and to measure mitochondrial membrane potential. Respirometry (Seahorse FX96) will be used to measure mitochondrial oxygen consumption and evaluate respiratory chain complex function. We will add to the evolving understanding of the intimate relationship between cytosolic Ca2+, SR function and mitochondrial bioenergetics by measuring the effects of exaggerated Ca2+ signalling in Stac3 myotubes on mitochondrial Ca2+uptake, oxygen consumption and free radical production. Finally, we will use transcriptomic analyses of muscle from 2 stages of embryonic development to integrate coordinated changes in mRNA and protein expression with functional and histological data to identify potential novel therapeutic targets.

UKRI Gateway to Research · FY 2025 · 2025-03

Mathematical models of human behaviour are used in many societally important contexts, such as transport, economics, robotics, and epidemiology, to make predictions about the impact of new technologies or policies, or directly as part of technological solutions. These human behaviour models are typically either machine-learned from large datasets, or mechanistic models, based on assumptions about human cognition. However, there are hard constraints on the scope and accuracy of these approaches: machine-learned models can in principle account for behaviour in diverse real-world situations, but only as long as there are large amounts of real-world human behaviour data. In modelling of behaviour where data are scarce (e.g., safety-critical situations) cognitive models may account well for selected scenarios, but do not scale to arbitrary real-world situations. Furthermore, neither approach is able to generalise to entirely novel situations, e.g., human interaction with not yet deployed technologies or interventions. However, thanks to recent advances in both cognitive and machine-learned modelling, a novel approach can now be envisioned with the potential of high-fidelity behaviour emulation across both common and more inaccessible aspects of behaviour, and with high capability of generalisation to new situations. This modelling approach builds on the theory of human behaviour as boundedly optimal: maximising rewards, but under human perceptual, motor, and cognitive constraints. It is argued here that models of this nature can now be achieved for complex real-world human behaviour, by leveraging (1) large-scale integration of existing mechanistic models from fundamental computational cognitive science, to model human constraints, and (2) powerful deep reinforcement learning methods, to learn boundedly optimal behaviour under these constraints. This requires a new type of research programme, spanning state of the art methods both from cognitive science and ICT, in addition to domain knowledge from the applied contexts in question. The PI of this discipline-hop project has a world-leading track record in integrative cognitive modelling in the domains of road traffic safety and vehicle automation. A primary objective of this project is for the PI to be immersed in the relevant subdisciplines in ICT, to establish the cross-disciplinary bridge needed to pursue the envisioned research programme, primarily within his home discipline, but also with a wider range of application areas in sight. At King's College London, the PI will be hosted within a research team with cutting-edge research expertise in the required ICT domains, and with relevant cross-disciplinary experience. During this immersion, research toward a second main objective will be pursued: A proof of concept demonstration in the form of a model of safety-relevant pedestrian-vehicle interaction, with capabilities beyond what is possible with purely machine-learned or mechanistic approaches. This proof of concept will make use of an existing naturalistic dataset from two Leeds locations, in collaboration with Leeds City Council, to investigate the potential of the developed models for simulation-based design of traffic safety interventions. The developed models will have high value within their specific applied domain, but a third objective of this project is to also engage with fundamental and applied behaviour modelling researchers and ICT researchers more widely, to promote the proposed cross-disciplinary line of modelling research for use also in other domains. This will be done within international networks, but with a specific emphasis on strengthening UK capabilities for human behaviour modelling in key application areas, with potential for truly major academic and societal impact.

UKRI Gateway to Research · FY 2025 · 2025-03

Topology is a branch of mathematics that describes properties of objects that remain robust under smooth deformations. Landmark discoveries in the field of condensed matter physics over the past four decades, recognised by three Nobel prizes in 1985, 1998 and 2016, have shown that certain materials in the regime of the fractional quantum Hall effect can exhibit similar insensitivity to external perturbations. This "topological" robustness underpins many remarkable properties, for example dissipationless currents circulating along the boundary of the material sample, while the bulk hosts novel quasiparticle excitations that behave as neither fermions nor bosons. These exotic properties could be harnessed to make ultra-low power electronic devices, and they could revolutionise the burgeoning field of quantum computing by shielding the computation from unwanted sources of errors. This proposal brings together a new UK-Ireland team of theorists, with experimental Project Partners at UCL and LENS (Florence, Italy), tasked with revealing the true nature of fundamental quasiparticle excitations of topological quantum matter. Our hypothesis is that these particles are "partons", i.e., fractionalised electrons with rich geometrical properties that emerge from strong interactions and quantum effects present within the topological material. In ordinary circumstances, partons are tightly bound within the constituent electrons of the topological matter, hence they have remained invisible to previous experiments. However, when the material is taken out of its equilibrium state, partons can exhibit observable signatures, which we will elucidate. The overarching goal of this proposal is to establish a new UK-Ireland partnership for topological quantum matter out of equilibrium. We will employ the emerging quantum technologies, such as quantum simulators made of ultracold atoms in optical lattices and digital quantum computers, as "parton accelerators": by exciting topological matter to high energies, we will study partons via their characteristic imprints on the dynamics of the system. We will develop state-of-the-art numerical simulations of fractional quantum Hall systems based on partons, and we will ultimately formulate an effective quantum field theory for describing topological quantum matter based on partons. The success of our objectives will advance the understanding of nonequilibrium properties of topological materials, which is key to their applications as platforms for fault-tolerant quantum computing. It will also pave the way towards an experimental observation of a new kind of particle that emerges from the interplay of strong correlations and geometric fluctuations in quantum materials, which will impact diverse condensed matter systems including fractional Chern insulators, quantum spin liquids and twisted van der Waals materials. Our use of quantum simulators for observing real-time dynamics of partons will boost the impact of results across a broad spectrum of synthetic matter platforms that are increasingly used for studying many-body phenomena outside of solid state materials. Finally, through collaboration with visual artists and by developing pedagogical workshops that target pupils in areas of low progression to higher education, our suite of public engagement activities will raise the profile of topology and quantum matter among the general public.