University of Leeds

UKRI Gateway to Research · FY 2025 · 2025-02

A cell ensures its survival and proliferation by sensing and responding to environmental cues through a series of intracellular signals that modify its internal functions. These signals can provide mutually exclusive cellular outcomes whilst functioning alongside a multitude of other signals responding to different cues. However, most of our understanding of intracellular cell signalling has been gleaned from reductionist approaches which trace processes of isolated individual pathways. These approaches fail to encapsulate a complete understanding of complex cellular regulation that includes multiple signalling pathways, transcription/translation and heterogeneous responses to stimuli associated with cell fate. One of the most acute manifestations of this failure is the huge burden of drug discovery that is seldom successfully delivered to the clinic. Understanding of the heterogeneous and refractory responses to therapeutics requires adopting a holistic approach to understanding the intricate communication networks of cell fate. In this proposal we aim to deepen our understanding of pathways through engineering of cells to produce a reproducible outcome when they are triggered by external stimuli or therapeutic drugs. The engineering process will involve data-driven modelling of cell fate pathways, transcription and translational regulation, and the design and implementation of synthetic components and circuits. This will be achieved through the collective efforts of an international consortium of experts in cell, computational and synthetic biology. We will provide bespoke research training across the international collaboration network to foster the next generation of interdisciplinary scientists and research leaders in biological engineering.

UKRI Gateway to Research · FY 2025 · 2025-02

Context Climate change is rapidly increasing extreme weather in Africa, threatening lives and livelihoods. Access to electrical power has numerous benefits across society, and the energy sector in Ghana is developing rapidly, but is vulnerable to lightning and storms, and would benefit from warnings tailored to its needs. Addressing the urgent need for improved early warnings in Africa, as recognised by the UN’s Early Warning for All initiative, requires greater capacity in Africa throughout the complete chain, from observations, through predictions to warnings. Numerical Weather Prediction systems developed in the Global North are much less effective in the tropics where the weather is dominated by convective storms, but there is much greater scope for nowcasts (predictions based on observations). Nowcasting in Africa has been held back by a shortage of ground-based radar observations, but AI/ML is revolutionising nowcasting and satellite-based nowcasting has proven effective. Now, for the first time, we have high-frequency satellite observations of lightning, providing a new opportunity for improved nowcasts of storms and lightning. The Challenge There is currently no ground-based lightning observing instrumentation in Ghana, for real-time information for warning, or comparison with satellite data, and limited capacity in the atmospheric physics of lightning-generating storms. Nowcasting is in its infancy in Ghana, with key systems run in the UK, and with no products tailored to the energy sector. There is an under-representation of females within physics, and a shortage of physics skills to provide climate solutions. EW4Energy addresses these challenges. Objectives EW4Energy will deploy the first ground-based lightning observing systems in Ghana, developing technical capacity in developing, building and running sensor networks. Together with ground-based data, it will exploit new space-based lightning observations to provide a new understanding of the physical processes governing the occurrence of lightning in West Africa. Exploiting synergies with ongoing UK projects on storm warning systems for Africa, EW4Energy will use its new physical insights to improve systems for the prediction of storms and lightning, and subsequent warning systems in Ghana. This will have a focus on information for the energy sector but have much wider benefits. EW4Energy builds from strong existing UK-Ghana partnerships, to deliver research and build the capacity of physics ECRs in Ghana, including female ECRs, with a leadership team that will allow an equitable partnership between institutions. Project activities addressing ECRs beyond the project team will deliver much wider capacity development. Applications and Benefits The physical science in EW4Energy will be rapidly translated to societal benefit, both within and outside the project. EW4Energy will work directly with the energy sector to co-produce information and warnings to meet their needs, and develop Ghana’s public storm and lightning warnings. EW4Energy will also work with other ongoing projects to deliver a wider impact at scale. Leeds and UKCEH are already running and developing storm nowcast systems for Africa, with the FASTA phone App used by thousands in Africa. EW4Energy will inform this ongoing development, giving rapid pull-through of EW4Energy’s physics to early warning, with benefits far beyond the energy sector. EW4Energy will transfer these  nowcast systems to Ghana, building the essential physics capacity that is needed to innovate, develop and run such systems long-term, training the new generation of male and female physicists that are required to meet the challenge of addressing climate change in Africa.

UKRI Gateway to Research · FY 2025 · 2025-02

Metal-organic frameworks (MOFs) are porous materials comprised of metal nodes/clusters and organic linkers. MOFs have attracted extensive interest from academia and industry owing to their unprecedented porosity and structural and functional diversity; the MOF market is set to reach >£20bn by 2032 (Global Market Insights Inc.). Applications of MOFs including sensors, catalysts (e.g. to transform carbon dioxide into chemical feedstocks), drug delivery and in pollutant capture offer huge potential for addressing key global challenges in healthcare, energy, and mitigation of environmental pollution. However, there is limited understanding of the formation processes of MOFs and current methods for discovering and optimising MOFs rely on trial-and-error and are poorly reproducible. Consequently, a targeted materials discovery and optimization is not possible, the complexity of materials produced is limited, and scale-up takes many years/is not possible as conditions optimised in batch are not readily translatable to scaled up processing. The proposed research will revolutionise the way in which MOFs are discovered, prepared, and applied by redressing gaps in mechanistic understanding of reactions and providing new synthetic protocols for targeted synthesis, including routes to scale-up. This will be achieved by developing automated flow microwave platforms equipped with real-time analyses capable of self-optimization guided by evolutionary algorithms; underpinned by new fundamental understanding of crystallisation processes for MOFs. This will enable faster production of MOFs for targeted applications (e.g. catalysis, drug delivery) without wasting time, energy, or chemical resources and overcome considerable issues with reproducibility, which currently hinders MOF research and their commercial exploitation.

UKRI Gateway to Research · FY 2025 · 2025-02

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 · 2025-02

The ever-increasing energy consumption of data centres presents a large-scale global research challenge: how to fundamentally change the computing hardware inside such centres so that it runs more efficiently, with less waste heat?  Magnetic materials underpin this hardware and combining them with ferroelectrics promises a scalable and energy-efficient technology.  Here we will combine ferroelectric (FE) superlattices and ferromagnetic (FM) multilayers to create, for the first time, a multi-skyrmion material, in which magnetic-polar skyrmion pairs can be created and driven with an electric field.  Skyrmions are nanoscale whirls in the order parameter in FE or FM materials and show great promise for data storage and computing applications.  A multi-skyrmion material where FE and FM skyrmions are coupled at an interface holds the key to energy efficient devices.  This project supports two UN sustainable development goals. (1) Responsible consumption and production: turning the tide on the rising energy consumption of data centres.  (2) Industry, innovation and infrastructure: generating employment and income by exploiting multi-skyrmion materials for the information and communication technologies of the future.  Our team is comprised of experts in magnetic skyrmions, ferroelectric materials and FE-FM coupling and brings together complementary experimental techniques across groups at the Universities of Leeds and Nagoya to prepare and characterise multi-skyrmion materials. At the research level, the challenge is to create the ferroelectric-ferromagnetic heterostructure in which the two types of skyrmion, polar and magnetic, co-exist, and to test for the coupling between them.  The international nature of this project will provide early career researchers with opportunities to travel between the UK and Japanese partners and share knowledge and learn complementary techniques.  Benefits are likely not only in terms of fundamental knowledge but also the technical skills for the researchers involved and the experimental techniques that will be developed for the fabrication and characterisation of multi-skyrmions.

UKRI Gateway to Research · FY 2025 · 2025-02

Religion plays an important role in the construction of gender and sexualities, and subsequently, in the production of the frameworks of belonging, nationhood, and global citizenship. The research will investigate changing regimes of sexuality in Muslim Republics of the Caucasus and Central Asia that underwent multiple transitions in the 1980s-90s. The term 'transitions' signifies two interconnected processes: (1) political and cultural re-orientations that occurred in the context of shifting centres of power; and (2) artistic re-imaginings of cultural heritage and creation of new practices in the context of changing regimes of sexuality. Through the lens of national and inter-regional exchanges, the research will examine the role of gender and sexualities in the Muslim Republics' search for a national identity under the conditions of newly embraced nationalism and resurgent religiosity. By focusing on two cases—Azerbaijan and Kyrgyzstan—where there are thriving queer cultures and robust institutions invested in protecting cultural heritage, the research will produce a more inclusive and more nuanced framework to understand the relationship between Islam and changing regimes of sexuality. The research will also review critically the colonial-era concepts of 'the Caucasus', 'Central Asia', the Russian 'near abroad' and 'the Turkic world', and thus test theoretical potentialities of de-colonial geo-cultural affiliations such as SWANA. The research will produce outputs that will be of use to researchers and curators, working in universities and art institutions.

UKRI Gateway to Research · FY 2025 · 2025-02

Chronic pain is a distressing condition that, unlike acute pain, remains poorly treated by currently available medicines. Chronic pain affects over a third of the world population and costs billions to the economy. Moreover, since prevalence of chronic pain increases with age, economic burden of pain will raise due to the ageing population of our society. We will study the mechanisms for chronic pain and provide novel targets for treatment of nerve pain which results from damage to the nervous system. We have made remarkable progress in our understanding of the biology of pain and can control acute pain. However, here we wish to understand what is responsible for pain to stay; we now have evidence pointing towards pain cells outside the brain in a structure that is called 'dorsal root ganglion' (DRG). Using rodent models of chronic pain, we made breakthrough discoveries, uncovering sharing of 'packaged information' between pain nerves and other cells within the DRG. This information exchange at the DRG can control pain signals before they reach spinal cord, on their way to the brain, where pain is felt. We discovered that there are miniature capsules called 'extracellular vesicles' (EVs) that shuttle from one cell to the other within the DRG and are also able to escape into the blood. We propose that there are hubs for such EVs communication in the DRG which regulate chronic pain and can be targeted to decrease pain sensitivity. We believe that EV-mediated mechanisms can be exploited to regulate pain cell activity; this, in turn, may give raise to novel approaches to both treating chronic pain and finding diagnostic markers for such pains. The fact that DRGs are outside the brain, offers additional benefits for the development of targeted therapies which are devoid of many unwanted side effects, which are notoriously associated with current analgesics (for instance, the opioids). The high-gain objective of our research programme is to elucidate this new biological phenomenon. We will characterise vesicles released by nerve cells and other cells residing in the DRG and identify those which may have escaped into the blood; we will establish their ingredients and properties to define their role in pain mechanisms and diagnostics. This objective will be achieved through four focused aims. Aim#1) To map the direction of vesicle signals between pain nerves and other cells in DRG. Aim#2) To discover properties and composition of vesicles from specific cells. Aim#3) To investigate short-, mid- and long-term effects of cell-specific vesicles and their components on pain cell activity. Aim#4) To unveil how vesicle communication changes in chronic pain conditions, identify vesicle-associated diagnostic markers of chronic pain and explore innovative vesicle-based therapeutic approaches. We will use a variety of methods to characterise DRG-derived vesicles in animal models and in blood samples obtained from people with chronic pain. We will determine the effect of such vesicles on the nerve cells that carry pain signals and measure readouts of pain when specific EV-mediated mechanisms have been blocked. In both animal and human blood samples we will assess whether vesicles are potential biomarkers of neuropathic pain. Our research will bring novel understanding of chronic pain mechanisms and will shape innovative approaches for analgesia and pain management, thus having far-reaching benefits not only for the fundamental science but, ultimately, for individuals suffering from chronic pain conditions.

UKRI Gateway to Research · FY 2025 · 2025-02

The most significant threat of future rapid sea level rise is the collapse of ice sheets due to instability and runaway ice loss. It could lead to more than 1 m of sea level rise by 2100, submerging land currently home to 100 million people and causing further destruction in higher-elevation coastal regions through enhanced storm and flood risk and aquifer salinification. Predicting the future possibility of such instabilities and the resulting plausible 'worst case' sea level change is critical for adequately planning coastal defences and long-term infrastructures for which a rare event could have devastating consequences (e.g. nuclear power plants, the Thames Barrier, transport networks). However, this is highly challenging because ice sheet instabilities have not occurred since we started measuring ice sheet changes (the record is too short, and ice sheets have been stable in the recent past), and they depend on poorly understood mechanisms (e.g. sliding of ice) that occur in inaccessible areas (e.g. under kilometres of ice). There is a solution: ice sheet instabilities have occurred in the geological past, for example, 14,500 years ago (the time of mammoths and modern humans) when the collapse of ice sheets around the world produced up to 18 m of sea level rise in 340 years (more than five times the rates expected for the end of the century). Geological records of past ice sheet evolution provide an untapped goldmine of data that can be used to test and improve numerical models, informing future projections. However, in order to reliably translate knowledge from the past into confident future projections, the largest and most complex source of uncertainty in modelling past ice sheets needs to be accounted for: the climate. Tackling this problem requires new statistical methods and a unique combination of expertise in statistics, climate and ice sheet instabilities. The first phase of this fellowship has developed Artificial Intelligence tools and statistical (Bayesian) Uncertainty Quantification techniques that have transformed our ability to simulate realistic past ice sheets using a fast yet complex coupled climate-ice sheet model (FAMOUS-ice). These advances include tools and techniques for sampling through uncertain multidimensional model inputs and correcting model biases. We have also created an ultra-fast emulator (i.e. a statistical regression model) of the surface mass balance in FAMOUS-ice that adjusts as the ice sheet advances or retreats. Thanks to this work, my team has demonstrated that simulating the coldest part of the last ice age (~20,000 years ago) is a powerful approach for ensuring the model is able to flexibly predict climate and ice sheet behaviour different to today, thus reducing uncertainty and improving confidence in future projections of the Greenland ice sheet. We have learned that the largest source of uncertainty is how we model the albedo (i.e. brightness) of snow and ice. The project's second phase will apply our artificial intelligence tools to improve simulations of ice sheet instabilities with the higher resolution and high complexity UKESM, the flagship UK Earth System Model that can simulate how ice sheets flow and interact with the climate. We will investigate the abrupt ice sheet changes that took place during past rapid sea level rises, and will use these to improve projections of future ice sheet and sea level changes.

UKRI Gateway to Research · FY 2025 · 2025-01

Rapid diagnosis of infectious disease is critical to successful clinical intervention. Identifying the specific pathogen responsible for a patient’s symptoms and determining whether it is susceptible to antibiotics can be labour-intensive and slow. While some well-resourced hospitals can take advantage of rapid PCR-based diagnostics to identify bacterial species, identification of antibiotic-resistance requires isolation and culture of organisms which can take days rather than the hours that might be needed to treat a patient. Similarly, identification of virulent strains typically requires independent identification of individual markers such as toxins in a sample in an independent step to pathogen identification. In this project, we will use an engineering biology approach to develop artificial cells (artCells) which can bind to and identify intact pathogenic bacteria in a sample. Our approach is based upon the generation of artificial transmembrane sensors which will bind to either cell surface proteins or soluble proteins to activate production of a visible response within the artCell which can be detected using commonly available laboratory equipment. Integration of DNA-based AND gates into the artCells will then extend these to enable combined detection of bacteria together with markers of antibiotic resistance. Finally, we will carry out the key steps required to adapt our laboratory-scale technology to enable application in a clinical context addressing issues of production, stability and specificity. This international, interdisciplinary project will take advantage of specific expertise in protein engineering, vesicle production and cell-free transcription/translation to generate the artificial cells. Initially we will optimise four key underpinning technologies: producing vesicles with embedded transmembrane domains; modifying these segments to generate artificial sensors; optimisation of the genetic circuits required for sensing and finally encapsulation of this machinery. These will then be brought together by the team of researchers to generate the final artCells using the optimised approaches. The artCells will be readily adaptable to the detection of multiple pathogens and toxins based on the availability of suitable antigen-binding proteins due to the modular approach to artCell construction. Within the project we will use already available proteins to develop model artCells capable of detecting the pathogenic organism Staphylococcus aureus and combine these with sensors capable of detecting the toxin produced by cholera toxin. Beyond the project, this could be immediately adapted to detection of other pathogens (e.g. C. difficile) by the use of suitable sets of alternative antigen binding proteins. These artCells would then be used in laboratory work-flows to distinguish non-harmful (commensal) and virulent (toxin-producing) strains of a particular pathogen. In the final work package, we will develop a modular approach to assembly of the artCells at a late stage, using this approach we envision that it will be possible to generate panels of artCells with specificity for the same pathogen and different markers of antibiotic resistance to enable rapid identification of candidate therapies for immediate use in the clinic. Critically, this approach will not be dependent upon specific high-cost equipment and, subject to optimisation of product stability, would be potentially applicable in healthcare environments in low and middle-income countries.

UKRI Gateway to Research · FY 2025 · 2025-01

There is a growing need for highly skilled biomedical data scientists in academia and industry to tackle important societal challenges. Whilst there are a multitude of early career training opportunities in data science, there remain barriers to progression into leadership roles which make careers in the area less attractive and less accessible. In academia, one of the key challenges for data scientists is that they often take supporting roles in developing and implementing methodology alongside a wide range of academics in different scientific and clinical fields. Current academic promotion pathways focus on an individual's contribution as a leader on research papers and grant applications, and place value on a clear academic vision and direction. Such benchmarks create a challenge for those in supporting roles and recognition of the valued contribution made by skilled biomedical data scientists to research is often limited. Beyond academia, data scientists are a key workforce in industry and the public sector, including the NHS. In these sectors, with the strong recent influence of AI methodology, these new careers are much more varied and less well understood. As a result of this, interactions, knowledge exchange and career permeability between academic and other sectors are presently limited. Equally, there remains a need to increase the level of commercial exploitation of academic research in biomedical data science and to increase entrepreneurship among biomedical data scientists at all career stages. This project aims to address the issues above through several related objectives. It will map career pathways and barriers to progression in academia and make recommendations to address the issues raised. Career pathways in partner organisations in other sectors will also be researched, and results will be collated into career advice materials for data scientists, and for use with students and early career researchers in academia. Results from these investigations will be used to inform a new mentorship programme for biomedical data scientists at relevant career stages. Alongside this, the project will implement initiatives to encourage research and career interactions and exchanges between academic and other sectors. Finally, steps to increase entrepreneurship in the biomedical data science workforce will be taken, increasing awareness and providing effective training, and increasing the level of commercialization of academic research. Academic partners on the project are the Universities of Leeds, Sheffield, York, Teesside and Newcastle. Their active involvement will ensure that best practice in academic and data science careers is identified, and that any recommendations from the project are broadly applicable. The project will also have partners from industry and other sectors. At the time of writing this summary, a broad range of industrial and public sector organizations have been contacted to request involvement. Several have already become formal partners: these include small and large companies, for example Pinpoint Data Science, AstraZeneca and GlaxoSmithKline, the NHS (West Yorkshire Integrated Care Board) and a trade body (the Association of British Health Tech Industries). The project will improve biomedical data science careers in all sectors, attracting talented individuals to this area and helping to retain valuable individuals in the workforce. Data science is increasingly involved in almost all biomedical research projects in academia, industry and other sectors, and ultimately this project will benefit the UK by significantly increasing the quality of this research.

UKRI Gateway to Research · FY 2025 · 2025-01

The award will deliver new research equipment to be used by a wide range of scientists and engineers at the University of Leeds (as well as external academia/industry). The instruments will provide new or improved capabilities and will be housed in dedicated facilities with full support and training from dedicated research and technical professionals. Access to the instruments will be open to researchers at all career stages, with a special focus on supporting the training and development of those undertaking doctoral degrees. Sustainability of the equipment, its operation and the userbase has been built into the decision making process for the items selected. Overall the equipment encompasses both core work-horse instruments that support a large number of users for one aspect of their work, through to more bespoke instrumentation that supports a smaller number of multiple users (many early career) across multiple departments  more comprehensively, building on specific areas of strength in Leeds and aligning with both University and EPSRC strategic priorities. The five specific items of equipment are: 1) Scanning Electron Microscope (SEM) and Energy Dispersive X-ray (EDX) analysis system representing core equipment benefitting multiple users for the general morphological, microstructural and elemental characterisation of materials which is a key component of research within the Bragg Centre for Materials Research at Leeds comprising over 400 researchers, and across the wider campus. 2) High resolution liquid chromatography-mass spectrometry (LC-MS) system representing core equipment for the routine mass measurement of proteins, nucleic acids, peptides and small molecules which is critical for research within the Astbury Centre for Structural Molecular Biology and the Faculties of Biological Sciences (FBS), Engineering and Physical Sciences and Medicine and Health. 3) Tensile Stage for operando Small/Wide-Angle X-ray Scattering (SAXS/WAXS) that will be a new add-on capability to existing EPSRC-funded X-ray scattering facilities enabling users across Leeds to study nanostructure deformations under tensile strain/stress and at variable temperatures. This can be applied to a wide range of systems from elastomers and rubbers, to antimicrobial coatings, electrospun nanofibres, protein-based food systems and advanced nonwoven textiles. 4) Spinal Disc Simulator representing a bespoke biomechanical test simulator enabling loads or motions to be applied to sections of the spine and associated implants and measured in six degrees of freedom under extended cyclic loading. It can also be used for testing other musculoskeletal joints and implants including the wrist and ankle and complements an existing range of equipment at Leeds which houses the largest academic facility worldwide for the simulation of joint replacement implants. 5) Thermal Conductivity Measurement Equipment for testing the thermal behaviour of structural and geological materials and targeting the Engineering Net Zero priority area, and the Energy and Decarbonisation theme. The equipment will support many research areas across multiple Faculties at Leeds including: ground engineering, materials engineering, built environment, structural engineering, water engineering, energy storage and carbon capture and storage.  It will replace existing delicate equipment and provide much more efficient testing of samples. The research discoveries enabled by this investment in equipment will be disseminated through publication in appropriate open-access journals as well as numerous outreach activities. The facilities will also support the growth of collaborative work between the University and business, from SMEs (including spin-outs of the University) to major international companies, improving their products and processes and ultimately returning benefit to the UK taxpayer.

UKRI Gateway to Research · FY 2025 · 2025-01

The Condensed Matter Physics (CMP) group at Leeds proposes the purchase of a Physical Properties Measurement System (PPMS) to characterise electrical, magnetic, and thermal properties of advanced functional materials with emergent phenomena over a range of temperatures (0.4-400 K) and magnetic fields (=16 T) with horizontal axis rotator. These capabilities are currently not available in our region. The development of nanoscale devices across applications from healthcare to quantum technologies requires a broad capability to investigate the magnetic, electrical and thermal properties of advanced materials. From the understanding of these fundamental properties comes our ability to exploit effects in new applications aiming to e.g. reduce the energy overhead of operation. The research challenges here include the study of topological superconductivity, where heat capacity measurements will address the urgent need for information on the effective mass and phase transitions. These are key scientific advances for quantum and energy efficient computing. In the area of triplet-based superconductivity, revealing the local microscopic details of the magnetic structure is necessary and the ability to measure magnetometry (VSM, AC susceptometer, CryoFMR) and transport in the same instrument is of unparalleled advantage. To exploit the potential for low-energy applications and high-density memory, we need to manipulate skyrmions in a wide range of conditions using the transport and magnetic capabilities of the PPMS. Uniquely for the region, we shall also study spin injection via ferromagnetic resonance and simultaneous inverse spin Hall measurements. We have world-class advanced thin film growth capability and EPSRC funding for researchers. Our aim is to bring our characterisation facility up to the same internationally competitive standard. The objectives are (i) to improve throughput by having a turn-key, measurement-optimised system, (ii) to obtain fundamental results that will lead to breakthroughs in our understanding and (iii) offer support to leading academic, SMEs and industrial research. This will increase the number and impact of outputs locally and in the region. The market leader, Quantum Design's PPMS, is a cutting-edge instrument accessible to a diverse range of researchers, enabling us to attract, train and hire advanced materials experts from different disciplines and backgrounds. The instrument has become a must-have in leading advanced materials laboratories because of its state-of-the-art capabilities, accessibility and multi-functionality, comprising a base unit and inserts to explore different materials and properties. The PPMS offers as well scope for cost-effective future expansion as new materials are discovered. A reliable implementation of high magnetic fields is important for fundamental work, but it is challenging for cryogen-free systems to ramp the field around high values due to eddy current heating. A wet system using liquid helium is more suitable for reducing the heating issue significantly so that ramping the full field range is easily achieved. It is also more cost-effective thanks to recent investments from the University of Leeds (UoL) in cryogenic facilities. The instrument also replaces our 23-year-old vibrating sample magnetometer, used by 21 academics at UoLA1. It will support 12 EPSRC and 2 EU grants, help to diversify our funding streams and open new horizons to characterise composite metals, complex oxides, nanomaterials and molecular systems matching the objectives for the Bragg Centre, the Henry Royce Institute and EPSRC's major areas and priorities.

UKRI Gateway to Research · FY 2025 · 2025-01

The Healthy and Sustainable Smart Places (HASSP) Data Service will build a new integrated platform for place-based research utilising Smart Data, enabling our most pressing and persistent challenges in health and sustainability to be assessed together, intersecting and in place. HASSP will have particular focus on two thematic pillars: (1) Healthy and Sustainable Food and Lifestyles; and (2) Healthy and Sustainable Mobility. Through extensive partnerships with data owners in the SDRUK defined retail and business and in mobility and infrastructure domains, HASSP will introduce new Smart Data into established challenge areas, providing unprecedented opportunities for generating novel research questions that cut across disciplines and maximise the benefit and impact of Smart Data research. HASSP draws on a long-standing track-record of building data partnerships, secure data-focused technical infrastructure and associated professional services led support which has resulted in award-winning research and impact. Tried-and-tested processes, driving best practice at the intersection between academia and business, have been developed by the applicant team over ten years in their leadership of the Consumer Data Research Centre at Leeds (CDRC-L). Building on this infrastructure, capability and the trust of both users and data owners, HASSP will deliver benefits to the Smart Data community from day one. This encapsulates support for the entire research lifecycle: from negotiating data access, through analytical support, to dissemination and impact support, HASSP will deliver a service that reduces barriers to entry for users of Smart Data. The HASSP focus on place is fundamental. Places frame how people live their lives - they are settings where we work, shop, socialise, and move; they influence our decisions, lifestyles, and health; and represent the confluence of a diverse set of intersecting social systems. They are increasingly recognised as central to the future of UK policymaking - be it in relation to Levelling Up12, tackling health inequalities11, or promoting innovation13. Stakeholders must adapt to this changing landscape, supported by a data service landscape that provides equitable access to, and promotes responsible use of, Smart Data. Smart data provides new opportunities to examine and understand challenges in places. The diversity of emerging data, available with fine spatial and temporal granularity, allow us to combine intelligence from diverse perspectives in specific, shared settings. By combining smart data and place, we become less constrained by conventional geographies, or traditional practices around preferred analysis boundaries, smoothing pathways for interdisciplinary collaboration and hypothesis building. HASSP focus on health and sustainability reflects the need to address the most pressing challenges of our time, and the fact of their intricate connectivity in place. Partnership and responsible research is inherent in the HASSP approach, and a facet established through years of practice, process, and trust-building through CDRC-L. Partnership within HASSP is taken to the next level. New Delivery Partners will work with us to deliver benefits from co-produced Smart Data research. An Advisory Board, consisting of senior industry, third sector and academic figures who are expert in using Smart Data, aligned with HASSP thematic areas, will be given a strong remit to hold the leadership team to account. A Fellowship programme will introduce new ways for the Smart Data Community to work with and within HASSP. New research partnerships, supported by in-kind PhD students, will ask pressing questions on the interface of Smart Data research and responsible practice.

UKRI Gateway to Research · FY 2025 · 2025-01

Net-Zero Digital Research Infrastructure – Vision and Expertise (NetDRIVE) will address the enormous challenges of establishing a sustainable United Kingdom Research and Innovation (UKRI) digital research infrastructure (DRI), reversing a growing dependency on rapidly depleting resources. The UKRI DRI plays a critical role in delivering world-leading research and innovation for the UK. Advancing digital technology is transforming research and innovation just as digitization is transforming society. NetDRIVE will channel the momentum of this transformation into sustainable pathways. The carbon footprint of the DRI is diverse, ranging from high performance computing (HPC) to personal laptops, data infrastructure supporting open research to cybersecurity, software and the people using and operating it. This complexity is further increased by transdisciplinarity, highly distributed decision making, and the rapidly expanding role of the DRI. The footprint is modest compared to elements of the physical research infrastructure but nevertheless demands attention. NetDRIVE will deliver immediate and tangible progress, provide confidence in our pathway to sustainability, and demonstrate national and international thought leadership so that the DRI can continue to serve community needs well into the future. The challenges of organisational complexity and rapidly evolving technology will be turned into strengths by exploiting the diversity of the stakeholder community and the agility of the infrastructure. NetDRIVE will recruit a team of Champions for Sustainable Research Computing, convene a Network for Transformational Change, and fund a portfolio of Community Activities. Progress will be measured through community backed metrics, based on both the physical reality of observable quantities, such as power consumption and embedded carbon budgets, and the experienced realities of individuals, such as trust and confidence, in the DRI and the broader academic community. The Champions for Sustainable Research Computing will provide leadership across all aspects of technological advance and community transformation. They will be responsible for condensing and synthesizing outputs from across the project to formulate timely and actionable advice for UKRI and the academic community.  The Network for Transformational Change will bring together domain experts, community leaders, visionaries, critics, and the leaders of tomorrow, from inside and outside of academia, to engage in free discourse on emerging questions and challenges for sustainable research computing. The Network will not only be a place to share the latest innovation but will itself become a new coalition to drive cultural transformation.  Through embracing a diversity of views and opinions, NetDRIVE will ensure that emerging recommendations and advice have been well tested in an active and representative forum thereby establishing itself as the go-to place for questions on Net Zero DRI priorities and opportunities. Community Activities will address the need for technical innovation and organisational transformation, promote knowledge exchange, and build trust and confidence. Demonstrators and proof-of-concept studies will enable the community to explore and test new ideas, develop best practice guides and community resources, and provide training to empower individuals to realise necessary behavioural change. Working groups and task forces will bring together relevant teams to provide in-depth reports on subjects of interest and focus meetings will engage local actors, industry bodies and stakeholders in discussion forums on topical issues. Seizing opportunities to place focus meetings within or alongside existing large community gatherings and conferences will broaden reach and enable synergies to be exploited.

UKRI Gateway to Research · FY 2025 · 2025-01

Cancer incidence is rising worldwide, increasing pressure on already strained healthcare systems. Robotic-assisted surgery is gaining traction to tackle surgical waiting lists, which are at an all-time high. Surgical robots, however, only act as smart tools in the hands of the surgeon; the surgeon still performs the operation with the robot providing a passive role. Adding a level of autonomy to robotic systems would decrease the reliance on surgical assistants, reducing surgical staffing requirements and increasing surgical precision and workflow efficiency. In turn, this would result in shorter operating times, better patient outcomes, and cost savings for healthcare providers. Although surgical robots provide a significant technological advance in how surgery is performed, they suffer from inherent limitations, chiefly a lack of tactile feedback from the instruments to the surgeon, which can lead to imprecise tissue handling and the risk of injury to vital organs. This New Investigator Award aims to increase autonomy in robot manipulation tasks by increasing the sensory inputs available to the surgeon. Current methods for measuring the forces used to grasp and retract tissues must be more precise and accurate. My sensors will provide the robot with sensations comparable to the human fingertip and use them to allow the robot to act as a semi-autonomous operating assistant. The proposal has two key objectives: Design and manufacture sensing skins mounted on the robot's end-effector (grasper). Current methods of force sensing are insufficient and too large to fit within the tip of a surgical tool. Using mechanical and magnetic simulations, I will optimise the design of a magnetic-based sensing skin to provide force information about the contact between a gripper and soft tissues in the body. Introduce intelligence to the robot to allow it to manipulate bodily tissues autonomously and safely. We will leverage recent AI and computer vision advances to visually identify relevant areas for the robot to grasp. Once it has traction, my sensors will calculate the optimal grip and traction forces to prevent trauma while the robot lifts and moves the tissue to reveal a region for the surgeon to operate on.

UKRI Gateway to Research · FY 2025 · 2025-01

Cells in the human body have proteins that help them to sense and response to forces that are created e.g. by the heart. Malfunction of such proteins is associated with a number of diseases including cardiovascular diseases e.g. heart failure, arrhythmia, hypertension, and abdominal aortic aneurysm and neuronal diseases e.g. Alzheimer's. There are different forces that are created in organisms which these proteins are required to sense and respond to, including forces that different cells in the cardiovascular system experience. The mechanism of force sensing by proteins in the cardiovascular system is poorly understood. Our study will focus on PIEZO1, a critical mechanical sensor found in the membrane of cells that line the inner wall of blood vessels (endothelial cells). Despite recent progress, our molecular understanding of PIEZO1 is mostly based on static structural data. This study aims to change the current paradigm by combining computer simulations with experimental validation to provide novel insights into the regulation of PIEZO1 sensitivity to mechanical tension. Importantly, this study will focus on a novel mechanism that we identified, referred to as the handshake interaction, which our pilot data suggest that regulates how PIEZO1 senses force. Our data also suggest that anionic lipids that are found within the cell membrane are critical for the regulation of the handshake interaction and other aspects of PIEZO1 force sensing. New knowledge about PIEZO1 force sensing will result in a major breakthrough in this field as it will help us to understand how force is sensed in cellular processes; this can explain how the same protein can sense different tensions in different cells that have different membrane lipid compositions. As such, the outcome of this study will allow structure-based drug design for human diseases that are related to PIEZO1. Our hypothesis is that PIEZO1 uses a novel handshake mechanism between subunits to regulate the channel's mechanical sensitivity in lipid-dependent ways. The main aim of this study is to use our established simulation protocols to explore our hypothesis and test its validity in laboratory experiments. Objectives: Determine how handshaking in PIEZO1 channels regulates their activation and sensitivity to tension and shear stress in the endothelial membrane. Determine how anionic lipids in membranes regulate handshaking and PIEZO1 sensitivity. Evaluate and refine the computational models using patch-clamp electrophysiology and molecular biology techniques. The outcome of this study will be novel as it will rationalize how a very biologically important channel senses force and explain for the first time PIEZO1's capacity for context-dependent mechanical sensitivity. Moreover, basic principles derived from these studies i.e., how force is sensed by mechanosensitive channels in a lipid-depended manner may eventually be generalised to other mechanosensitive channels, especially channels with curved TM region such as PIEZO2. Therefore, this study has the potential to change the way we think about the role of the cell membrane in mechanosensation. This work fits extremely well with the BBSRC priority area: Understanding the rules of life (Theme 1: Advancing the frontiers of bioscience discovery) as we propose to use state-of-the-art computational and lab-based techniques to answer fundamental questions in biology that can be transformative for science and society. It is also aligned with BBSRC's Forward look for biosciences that identified data-driven methods as key to unlocking key complex biological questions.

UKRI Gateway to Research · FY 2025 · 2025-01

Only one in five thousand drug molecules that are developed, reaches the market. One of the main factors for this low statistic is the fact that these drugs cannot be formulated in a way that can be easily dissolved and made readily available in the body to have the therapeutic effect required. For decades, researchers in academia and industry have been trying to improve this physical property of drugs by growing stable solid forms with other safe molecules. However, the success rate of finding a winning combination of drug and a co-former that is stable and has improved solubility is dwindling. With only eight such formulations known in the market, we need improved methods to enable higher success rates. Machine learning is now fast becoming the method that tackles such combinatorial issues. This project brings together key experimental information such as the molecule’s solubility in solvents and cutting-edge inter-molecular interaction information from synchrotron X-ray scattering techniques, together with state-of-the-art computational methods. All this information on how the drug molecule behaves in liquid state as well as in solid state will be probed using machine learning models build on known successful solid forms and will be tested to predict the formation of new solid forms. This project would advance finding solutions to challenges in data science such as brining in different kinds of data together in a single model as well as help advance technical abilities at central facilities for the study of soft matter systems. A successful model that continues to be developed and added to, would see the production of new stable drug solid forms with improved solubility reaching the market in record times. This would also prove to be a leap towards being able to personalise medicine in a sustainable way.

UKRI Gateway to Research · FY 2025 · 2025-01

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

UKRI Gateway to Research · FY 2024 · 2024-12

The ocean covers 71% of the globe, yet only 8% is protected. Human activities mean many ecosystems are now damaged beyond the point where natural recovery is feasible. Therefore, human induced ecological restoration is vital to counteract habitat destruction and resulting biodiversity loss. Successful habitat restoration of degraded systems requires us to know timescales of recovery, differences in geographic vulnerability and differences between ecosystems. Restoration projects have been successful in terrestrial environments and to some extent coastal settings. A lack of long-term data sets and challenges in observing marine habitats have led to fundamental knowledge gaps hindering marine ecological restoration success. For example, is the timing and sequence of recovery consistent at different depths of the water column? Does long-term recovery vary regionally, responding to local climatic and environmental conditions causing differential recovery capacity? How long are stress responses observed in individuals and how does that scale-up to ecosystems? Using appropriate data sets to answer these questions will enhance our understanding of the processes of marine habitat recovery which can then be incorporated into restoration projects increasing their success and geographical scope. We will assess habitability of the Mediterranean during the latter stages of the Messinian Salinity Crisis using presence/absence data of foraminifera. We will then generate millennial-scale, high resolution stable isotopes records of marine fossilised plankton and benthos to understand the timing and mechanisms of both surface and deep ecosystem recovery from near-complete habitat destruction 6 million years ago when the Mediterranean Sea dried up. We will apply statistical techniques to understand how these fossil communities re-established themselves and returned to previous levels of diversity within the context of their local climatic conditions. This research will not only provide a unique insight into how marine ecosystems recovered from one of the most fascinating periods of Earth's history, but it will also provide fundamental information about the timings and drivers of recovery. As anthropogenic habitat destruction combined with climate change continue the need for restoration in all marine environments will only increase and this research will provide the fundamental knowledge, across relevant timescales for marine habitat restoration to be successful.

UKRI Gateway to Research · FY 2024 · 2024-12

Neuromodulatory systems play pivotal roles in shaping behaviour and cognition. In particular, the cholinergic system has important roles in regulating food consumption, attention, learning and memory. Cholinergic function declines with age which directly impacts cognition. Additionally, insulin, a key player in brain function, is implicated in overlapping roles. Age-related declines in insulin sensitivity have independently been associated with diminished brain health and cognitive abilities. Notably, our research has pinpointed a central cholinergic hub, that is sensitive to insulin, highlighting a potential nexus for understanding and addressing the challenge of age-related cognitive decline. The overarching goal of this research is to understand the consequences of insulin sensing by the basal forebrain cholinergic nuclei (BFCN) and the underlying mechanisms. To deliver this new knowledge we will complete 2 aims using a multi-disciplinary approach combining behavioural analysis, cellular physiology, and targeted viral knockdown: Aim 1: Determine the functional consequence of insulin regulation of the BFCN. We will employ targeted knockdown of insulin receptors in the basal forebrain, specifically focusing on assessing the impact on three key functions linked to established projections from the BFCN: food intake, activity levels, and cognitive performance. By selectively rendering BFCN neurons resistant to insulin, we aim to unveil the repercussions of such resistance on these functions. Our preliminary data indicate that activity levels are affected in both sexes whereas food intake is affected only in males, the consequences on cognition are yet to be addressed. Aim 2: Determine the cellular and molecular components required for insulin modulation of BFCN projection neurons The BFCN is composed of different types of projection neurons including, glutamatergic and gabaergic neurons in addition to the cholinergic neurons for which it is named. Using subtype-specific mouse lines we will determine how insulin affects the activity of these projection neurons and the basis of sex-specific effects of insulin action. This work, exploring the normal physiology of the brain, is a close fit with the BBSRC priority themes of 'Bioscience for an integrated understanding of health' and 'Understanding the rules of life'. Mechanistic insight into how a key neuromodulatory centre is itself modulated by brain insulin could have implications for life long health, particularly as insulin resistance is a consequence of both ageing and poor metabolic health. This project will also develop people, supporting the BBSRC theme of 'Building strong foundations', both a postdoctoral fellow and a technician will be trained in cutting edge techniques, expanding the highly skilled bioscience workforce.

UKRI Gateway to Research · FY 2024 · 2024-12

Populations of most marine species are functionally, demographically, and genetically connected by planktonic dispersal of tiny larvae. Understanding the spatial distribution of dispersal events (the dispersal kernel) is a fundamental goal of marine ecology and is critical to predicting population dynamics and evolutionary outcomes. Yet, general principles for predicting dispersal outcomes across communities remain elusive. We propose to develop the first-ever data-assimilated biophysical models of larval dispersal by: 1) applying isolation-by-distance (IbD) theory to estimate mean parent-offspring distance (sigma IbD) for six reef fish species co-sampled and RAD-seq genotyped at three isolated South Pacific archipelagos that each replicate the IbD process with relatively continuous reef systems; 2) using our empirical estimates of sigmaIbD to constrain biophysical models of larval dispersal, which will be iterated over twenty years of high- resolution hydrodynamic models, we will test hypotheses about the relative role of species traits and seascape characteristics in shaping larval dispersal kernels; and 3) developing a new conservation portfolio approach to design managed area networks that capture temporal variability in larval dispersal over many generations, and engage with local stakeholders in each archipelago to implement this approach.

UKRI Gateway to Research · FY 2024 · 2024-11

Rainfall over mountains plays a crucial role in the Earth system, with a large proportion of the Earth's population dependent on water resources from mountain catchments for drinking water, agriculture and hydroelectric power. Extreme storms can also contribute to a range of natural hazards including lightning, flooding and landslides. Accurate predictions of rainfall, particularly intense convective rainfall ("thunderstorms"), over mountain areas on both weather and climate timescales are therefore crucial for society. All weather and climate models rely on parametrisation schemes. A parametrisation scheme is a simplified set of equations which attempt to represent the large-scale impact of an unresolved physical process based on the resolved large-scale flow. Convective clouds are not resolved at the relatively coarse (>10km) horizontal resolutions used for global weather and climate models and so the effects of the convection need to be parametrised through a convection scheme. High resolution (~1km) weather forecast models can now explicitly represent convective clouds however they are computationally expensive and so limited to a particular region and relatively short time periods. These high resolution simulations demonstrate improvements in the timing and organisation of rainfall however they do not capture the smaller scale processes which trigger convection or the details of what happens in the clouds and so these processes still need to be parametrised. Parametrisation schemes are typically developed and tested for relatively idealised situations over flat ground. This often leads to biases in the location, timing and intensity of rainfall over mountain areas. There is therefore a pressing need to improve the representation of convection over mountain areas in weather and climate models across a range of scales through improved model parametrisations. The project will use the unique observational dataset from the international TEAMx field campaign in the Alps alongside high resolution numerical weather forecasts to improve our understanding of the processes controlling the initiation and development of convection over mountain regions and the role of water vapour transport through valleys in supplying the moisture to drive the convection. We will evaluate how well the current Met Office forecast model (the MetUM) and the next generation model (Momentum Unified Earth Prediction Framework) capture these processes at a range of resolutions. We will use our process understanding to improve the parametrisation of convection over orography through improving the initiation of convection in the new CoMorph convection parametrisation scheme being developed for Momentum and to identify the extent to which other parametrisation schemes such as the turbulence and orographic drag schemes represent the impact of orography on transport of moisture through mountain ranges. By working to improve the representation of orographic convection in the Met Office model we will ensure wide benefit to end-users of Met Office rainfall forecasts including the general public, emergency response services and flood forecasters leading, allowing mitigation of high impact rainfall events to prevent loss of life and reduce damage and disruption from flooding. Improved seasonal and climate predictions of rainfall will benefit hydrologists, water authorities, farmers by enabling them to better manage and utilise water resources and will allow government and planners to design infrastructure resilient to changes in rainfall in a changing climate.

UKRI Gateway to Research · FY 2024 · 2024-11

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 2024 · 2024-11

The cells in our bodies communicate with their environment and with neighbouring cells through the transmission of information across the cell membrane, which separates the cellular content from the extracellular environment. One major mechanism of communication is the movement across cell membranes of ions - mainly sodium, potassium, calcium and chloride - through protein molecules called ion channels. Ion channels have key roles in physiology and many human diseases result from or are made worse by abnormal function of ion channels. Indeed, many successful therapeutic drugs work by activating or blocking ion channels. Despite the significant increase in our understanding of the 3-dimensional structures of ion channels, underpinned by recent developments in electron microscopy, we still face major knowledge gaps that hinder our understanding of their biological mechanisms and limit our ability to design effective drug candidates. An important class of ion channels is formed by the 28 different proteins of the Transient Receptor Potential (TRP) family, with each channel made up of four TRP proteins (or potentially five in some cases/circumstances). A prominent example is the capsaicin receptor/heat sensor TRPV1 (topic of the Nobel Prize in Physiology & Medicine 2021). Our research focuses on the related TRPC ion channels, and especially those formed by the proteins called TRPC1, TRPC4 and TRPC5. TRPC1/4/5 channels are important players in biology and are being tested in the clinic as potential new targets for the treatment of major depressive and post-traumatic stress disorders. In addition, TRPC1/4/5 channels are thought to be mediators for diseases of the heart, blood vessels and kidneys, as well as some forms of cancer. In the body, TRPC1/4/5 channels consist of different combinations of TRPC1, TRPC4 and TRPC5 proteins. Importantly, the TRPC1 component gives these channels unique properties, but despite >20 years of research, we have limited understanding of how it does this. We and others have previously studied the structures of TRPC4 and TRPC5 channels, revealing many aspects of their function and interactions with drug-like substances. However, the structures of TRPC1-containing channels have not been determined so far. In this project, we will make use of Leeds' cryo-electron microscopy facility (>£22m investment in state-of-the-art equipment, support staff and training since 2015) to determine the first 3-dimensional structures of TRPC1/4/5 channels that incorporate the TRPC1 subunit. In addition, we will investigate which parts of TRPC1 give it its special function by making small changes to the protein and measuring activities of resulting channels in cells. This work will provide the first detailed 3-dimensional models of how TRPC1-containing channels form and how TRPC1 contributes to their unique properties and interactions with drug-like molecules. We expect that such new fundamental insights into this fascinating family of biological molecules will allow more precise design of new therapeutic drugs.

UKRI Gateway to Research · FY 2024 · 2024-11

The global food system emits about 18% Green House Gas (GHGs), due to its reliance on animal-sourced ingredients such as proteins. Therefore, to reduce the environmental impact of the food system and improve sustainability, plant, insect, and microalgae-based protein sources are being investigated. However, these proteins suffer from poor sensory perception of bitterness and astringency, leading to poor adoption by society. Previous research projects have failed to provide mechanistic insight and strategies to minimize these negative sensory perceptions at an ingredient level. Therefore, the question remains, whether these proteins are inherently bitter and astringent or does the protein extraction process leads to protein modifications that cause these sensory perceptions. PROTSENS aims to understand and minimize these negative perceptions using green extraction methods that preserve protein structure. Protein extracts resulting from these novel processes will be thoroughly characterized. The mechanism of astringency and bitterness will be studied from macro to nanoscale using physical methods, while bitterness will be investigated using sensory cells in vitro in a simulated oral environment. The in vitro, ex vivo and physical tools will serve as a novel toolbox to investigate astringency and bitterness perception. The link between protein properties, extraction methods, and their sensory perception will be captured in a Machine Learning (ML) model. The model will provide a guide on protein extraction routes, based on protein source to preserve protein structure and improve sensory perception. Overall, PROTSENS, through its novel experimental toolkit and ML model, improves the sensory perception of novel proteins and adoption. PROTSENS will open new horizons in European academic research on food proteins. The success of PROTSENS will help drive the adoption of novel proteins, decrease GHGs in the food system, and help mitigate climate change.