Lancaster University

UKRI Gateway to Research · FY 2027 · 2027-01

Healthy freshwater ecosystems are crucial to life. Despite hosting approximately 10% of all known species and providing vital ecosystem services, from climate regulation to food supplies, they are often neglected by research. Global changes add more pressure to freshwater ecosystems, which are more endangered than terrestrial or marine ones. While the freshwater biodiversity crisis remains hidden beneath the water's surface, one-quarter of freshwater fish are currently threatened with extinction. Tropical freshwater ecosystems are especially vulnerable as the region experiences some of the world's most intensive agriculture and infrastructure development, alongside additional impacts from climate change. My research centres on the Amazon, the largest and most biodiverse river basin globally, which hosts 40% of the world's remaining free-flowing rivers. Despite its vital importance, deforestation, climate change, and infrastructure development are causing rapid transformations in the Amazon. These terrestrial impacts reach Amazonian rivers via a large network of headwater streams, which constitute the most widespread and extensive freshwater ecosystem in the basin. Recently, ecological restoration has gained traction in the Amazon as a solution to reverse its widespread degradation. However, ensuring that restoration initiatives also benefit and safeguard Amazonian watercourses has largely been overlooked. Amazonian streams host an outstanding biodiversity and provide irreplaceable ecosystem services to 40 million people, including clean water, leisure and fish. Small streams are thought to be home to half of the basin's fish species. However, streams are the most understudied components of Amazonian and other tropical freshwater ecosystems, with fisheries in larger river channels attracting most research to date. The future of the Amazon River basin relies on the health of its headwater streams. My main goal is to address significant knowledge gaps about tropical freshwater ecosystems and promote biodiversity conservation in the world's largest river basin. I will achieve this by building on the efforts made during the first phase of my Future Leaders Fellowship and collecting new data to address my long-term research objectives. First, I will conduct the second phase of a pioneering field experiment on stream fragmentation. Road-associated infrastructures, such as culverts, are a major driver of freshwater degradation and biodiversity loss worldwide. Road culverts block and fragment streams, disrupting the movement of water, nutrients, and species. Despite their ubiquity in the Amazon, the effects of road culverts on stream habitats and fauna are poorly understood. I will evaluate stream resilience to fragmentation after experimentally removing culverts and restoring hydrological connectivity. This is the first field manipulative experiment to examine the impacts of road-induced stream fragmentation in the tropics. Second, I will combine the findings obtained during both phases of my FLF to estimate the extent of stream degradation across the Amazon River basin and identify priority areas for restoring the hydrological connectivity of streams. I will use this evidence to integrate freshwater conservation into current environmental policies in Brazil and inform policies that regulate the maintenance and decommissioning of road-associated impoundments. I anticipate making a significant contribution to the science and practice of stream conservation by advancing our understanding in the tropics and linking these findings to urgent policy and management issues in the Brazilian Amazon.

UKRI Gateway to Research · FY 2026 · 2026-09

Cosmology, our pursuit of the fundamental properties of the Universe, is at a crossroads. In the last decade multiple cosmological probes, spanning the entire expansion history of the Universe have been deployed, but the standard model, LambdaCDM, built upon Einstein’s General Relativity (GR) has stood its ground: able to match all observations. However, despite the success of  this model, 95% of the contents of the universe are still unexplained. Yet in the last 2 years, by combining information from different probes at different epochs, LambdaCDM has started to crack at the edges: the model is compatible with all observations, but not all observations simultaneously. In particular, late-time Universe measurements from type Ia supernovae (SNeIa) of both the expansion rate (H0) and the time evolution of ‘dark energy’ (wa), which is causing a late-time acceleration, differ from those predicted from early universe observations by between 3-5sigma. These tensions arise across multiple probes, so two options remain: either an unknown systematic bias dominates one dataset or the standard model of cosmology is wrong. To know if these tensions are real, we must measure them precisely and  independently. For SNeIa, several distant Universe surveys have been conducted, resulting in multiple independent datasets, each with more than 1500 measured distances. Unfortunately the power of SNeIa as a cosmological probe comes from measuring relative changes in distance across cosmic time: a nearby comparison sample is always required. As intrinsically rare events, finding SNeIa in the nearby Universe requires regular monitoring of the entire sky: something impossible until the recent implementation of wide-field surveys. As a result, all previous SNIa analyses have relied upon the same low-redshift sample. This sample, of only 200 events, is heterogeneously selected, with distances derived from more than 30 different facilities, many of which are obsolete. The low-redshift anchor of the current SNIa Hubble diagram is thus the opposite of precise and independent. This uncertainty represents the most likely source of bias in SNIa cosmology today. An independent, homogeneous and precisely measured sample is thus required. Over the last 7 years, the Zwicky Transient Facility (ZTF) has discovered and classified over 8,000 SNeIa in the local universe. This high-cadence survey, with dedicated spectroscopic follow-up to ensure completeness, has generated a large, homogeneous and unbiased sample of SNeIa. The first major sample from ZTF (ZTF-DR2; Rigault, Smith, et al., 2025), of 3600 SNeIa has just been publicly released to the wider community. The ZTF dataset is thus primed and ready to independently test the cosmological model. In this small award we will do just that. We will use all of the data from ZTF to create the largest homogeneous sample of SNeIa in the local Universe by a factor of 30, ensuring precise and unbiased distance measurements. Combining this dataset with those in the distant Universe, we will independently determine if dark energy is evolving with time. With no other large-scale, homogeneous low-redshift sample planned within the next decade, the ZTF SNIa sample will form the legacy sample from which all future cosmological analyses will be anchored. These include those from the next-generation transient experiment, the Vera Rubin Observatory (VRO), which aims to measure the evolution of dark energy to <1%. The distances measured from this small award are critical to ensure that all future high-redshift searches can accurately test GR.

UKRI Gateway to Research · FY 2026 · 2026-03

Twilight Commons is a cultural research initiative addressing persistent barriers to participation in Morecambe and Barrow—two coastal towns undergoing regeneration, yet marked by high deprivation, limited transport, and restricted access to culture after dark. As highlighted in Key Cities: On the Waterfront (2025), seaside urban areas report “some of the lowest levels of arts engagement in the country,” while also holding “rich heritage, identity, community energy and environmental distinctiveness.” Twilight Commons responds to this dual condition by using twilight—a time of ecological and perceptual transition—as both method and metaphor. It produces tangible data and visual evidence of how marginalised groups experience night-time spaces and uses art to reimagine twilight as a time of connection, experimentation, and belonging. The project brings together Lancaster University and six grassroots cultural partners to co-design access routes into culture and influence regional strategy. It focuses on the specific challenges of access, safety, and perception that these partners have identified—particularly for low-income residents, women, disabled people, and children. Together, the partnership will: Co-design twilight sensory walks to map and challenge lived barriers to cultural participation after dark Support artist-led commissions exploring how people live in relation to nature and place in their waterfront towns Deliver immersive policy workshops using those creative outputs, connecting strategic bodies with community imaginaries using high-tech environments -- turning them into new policy and strategy recommendations Create a digital toolkit and launch the MB_CultureResearch network to sustain collaboration, shared learning, and cultural planning across the Bay By involving local stakeholders at every stage, the project builds the capacity of cultural organisations to develop place-specific, time-sensitive programming grounded in lived experience. Cross-town insight and research expertise support partners—including the university itself—to embed inclusive cultural planning into long-term strategies for the Bay, aligning with Key Cities’ call for deeper collaboration across public, private, and community sectors. As a legacy of this shared approach, the project supports the development of the Morecambe Bay Triennial—a future-facing festival designed to model accessible, ecologically engaged cultural tourism along the 100-mile stretch from Fleetwood to Barrow. Its final stages will establish the MB_CultureResearch network as a formal commitment to cultural innovation in this unique region. Twilight Commons is led by Lancaster University through three specialist research centres: Dark Design Lab (light and sensory urbanism), CeMoRe (more-than-human and mobile methods), and Security Lancaster (urban safety and public space), and is embedded in the Morecambe Bay Curriculum’s schools networks with event access for teachers in early years, primary, secondary, and further education. Cultural delivery is led by Deco Publique, with key partners Art Gene (Barrow), Good Things Collective (Morecambe), Full of Noises (Barrow), More Music (Morecambe), and Julie Brown (Chair, Lancaster and District Arts Partnership). Together, this team offers deep expertise in place-based practice, experimental programming, and cultural strategy. Outputs include: A new Morecambe Bay cultural research network Twilight mapping methodologies and ecological-social experience artworks Policy tools and co-designed cultural strategy frameworks A replicable digital toolkit for cultural planners on coastal urban spaces

UKRI Gateway to Research · FY 2026 · 2026-03

Please see application APP70417: Hyper-K - CIC Grant from the lead organisation (University of Oxford).

UKRI Gateway to Research · FY 2026 · 2026-03

Dementia affects over 55 million people worldwide, with nearly a million in the UK alone - a number that continues to rise. Despite growing awareness of dementia, the syndrome still remains widely misunderstood and deeply stigmatised within society. As a result of the stigma that surrounds it, many people diagnosed with dementia feel a pronounced sense of shame - a feeling which can, in turn, delay diagnosis, hinder access to care and discourage participation in research. At the same time, the general public often lacks accurate knowledge of dementia, for example with many people wrongly assuming it to be an inevitable part of ageing or being unsure as to how to communicate with those diagnosed with it. This project tackles the urgent problem of dementia stigma by focusing on how the condition is represented in public communication - especially through language and imagery. While previous work has shown how certain kinds of language use and imagery can reinforce negative stereotypes around dementia, this new project takes a crucial next step: understanding and promoting more authentic, stigma-challenging representations that reflect the real-life experiences of people living with the syndrome. To do this, the research team will study three types of public texts: popular science articles, news stories and content created by generative AI tools. These texts often shape how the public thinks and communicates about dementia, yet they rarely include the voices of people actually living with it. The project will examine how these texts represent dementia, and how such representations differ from lived experiences, ultimately seeking to work towards proposing ways in which such communication might better reflect such lived perspectives in the future. A key innovation of the project is its participatory approach. The team will run focus groups involving people with dementia, their carers and families, healthcare professionals and media professionals. These groups will help interpret findings, suggest improvements to how dementia is portrayed, and co-design guidelines that seek to support ways of communicating about dementia that better reflect authentic experiences. For example, participants will react to samples of AI-generated text and suggest better ways to prompt AI tools to produce portrayals of the syndrome that are more accurate and less stigmatising, and which incorporate the perspectives of those with first-hand experience of it. To realise this impact, the project will produce practical, evidence-based communication guidelines for journalists, charities and others who communicate with the public about dementia. By combining advanced language analysis with direct input from people affected by dementia, this research aims to challenge stigma and promote more informed and compassionate public attitudes towards the syndrome and those affected by it. It will also make a lasting academic contribution by demonstrating how focus groups can be effectively incorporated into large-scale (corpus) linguistic studies. Ultimately, the project hopes to make it easier for people with dementia to be seen and heard in society, on their own terms. In this way, the work contributes to broader efforts to help society move away from fear and misunderstanding of dementia, and toward dignity, understanding and inclusion.

UKRI Gateway to Research · FY 2026 · 2026-03

The British far-right is more active than it has been for many years (Hope not Hate, 2023). This fellowship will help law enforcement agencies deal with the burgeoning problem of far-right extremism. Until recently, my research focused predominantly on online language abuse, covering topics like trolling, abusive language, and anti-science. Yet, in investigating these, a common denominator emerged – each was, to a greater or lesser degree, being used by the British far-right to further its cause. In interpreting my findings, the scale of the far-right, and the impact of its online activism, became starkly apparent. With this fellowship, I will refocus my work to address this problem. The problem is complex: the far-right is a multidimensional entity, comprising a relatively diverse range of groups and individuals from radical right-wing populists to revolutionary neo-Nazis. My work so far has shown that it exploits uncertainty, pseudoscience, and xenophobia to sow doubt and recruit. This activism is enabled by the internet, which has become the most important way that extremists spread propaganda, plan events and protests, recruit, raise finance, and communicate. Language is key in this process. This represents a challenge. Policing the far-right online is problematic as it entails identifying, in the huge volume of far-right content produced, those communications which pose a substantial risk. One reason for this is that we lack a sophisticated linguistic understanding of the far-right that draws on multidisciplinary intelligence to systematically identify how far-right groups vary, what features and repertoires are shared, and how the most extreme compare. Multi-Dimensional Analysis (MDA) could provide this. This hugely influential technique, developed in the 1980s, has been successfully applied to thousands of datasets to uncover the major patterns of linguistic variation and the way that texts differ in relation to those patterns, including to distinguish fake news (Grieve and Woodfield, 2023). Yet MDA has a longstanding methodological problem: it cannot be reliably applied to short texts (>1000 words). Short texts provide little evidence for frequency-based analyses, producing datasets with many zeros. To date I have developed 3 effective approaches for the analysis of short texts, including a short text version of MDA, which works well on short texts of up to around 200 words. Nevertheless, an approach to MDA which works irrespective of text length is needed to explore the far right, and many other application areas (e.g. child sexual abuse), because far right texts vary from short (e.g. social media posts) to long (e.g. manifestos). The first 4 years of my fellowship will deliver this. In its following three years, I will evolve MDA to deal with visual as well as textual data as many messages online blend both. This fellowship will allow MDA to work with texts of a range of lengths, and meaningfully analyse the textual and visual, to the benefit of society by allowing security and law enforcement agencies to systematically identify (a) how far right groups vary (b) what features and linguistic repertoires they share and (c) identify high-risk individuals. Given the broad appeal of MDA in a wide range of application areas to date, the techniques developed by this project will also have impact in a much broader set of areas.   References Grieve, J. and Woodfield, H. (2023) The Language of Fake News. Cambridge University Press. Hope not Hate (2023). https://hopenothate.org.uk/2023/02/26/state-of-hate-2023-rhetoric-racism-and-resentment/.

UKRI Gateway to Research · FY 2026 · 2026-03

Human perception relies on a delicate balance of excitatory and inhibitory (E/I) neural processes. Disruptions to this balance can lead to elevated levels of cortical hyperexcitability, destabilizing perception and resulting in perceptual distortions or hallucinations. This phenomenon underlies aberrant experience across a range of neurological and psychological disorders, such as migraine, anxiety, depression, epilepsy, psychosis, and schizophrenia, but can also occur in neurotypical individuals. Understanding hyperexcitability in the visual cortex is crucial, as it opens new possibilities for targeted interventions to alleviate symptoms in affected individuals and provides insight into the fundamental neural mechanisms of sensory processing. This project aims to utilise advanced, computer-modelled multi-channel transcranial direct-current brain stimulation (MtDCS) to selectively target early and late visual processing regions. Early and late visual processing areas play distinct roles in perception and in the visual aberrations generated and are implicated in conditions like pattern-glare—a phenomenon where high-contrast striped gratings elicit visual distortions due to latent cortical hyperexcitability. By refining stimulation techniques, this study seeks to explore the independent and most notably, combined contributions, of early and late visual regions to aberrant perceptual experiences. Additionally, it aims to investigate compensatory interactions between these networks, where one region can be 'excited' while another is simultaneously 'inhibited', which is an extremely novel methodological approach.  By investigating these areas, we aim to uncover new ways to advance our understanding of sensory processing mechanisms in the brain, with the potential to alleviate symptoms in affected individuals. Key Objectives: Develop and validate multi-channel brain stimulation protocols to selectively modulate early and late visual areas and assess their role in producing specific forms of aberrant perceptions.  Modern multi-channel systems, guided by realistic computer generated brain models can now facilitate these tantalising questions.  Examine the role of latent cortical hyperexcitability in mediating visual pattern-glare distortions in the laboratory.   Investigate compensatory dynamics between visual processing networks through simultaneous stimulation. Applications and Benefits: This research will enhance understanding of cortical hyperexcitability by clarifying how early and late visual areas mediate specific perceptual distortions. It has significant potential for developing targeted non-invasive interventions for disorders involving hyperexcitability while also offering insights for neurotypical populations. Moreover, this work advances foundational knowledge of visual system dynamics, offering transformative implications for perceptual neuroscience and treatment strategies. The innovation contained within this project dovetails neatly with the BBSRCs research and innovation priorities and development plan.  MtDCS is a cutting edge technology and computer-modelled montages based on realistic brain models have only recently come to the fore, now allowing for more detailed questions to be examine.  As well as furthering our knowledge of perceptual neuroscience, the present project will help inform future clinical treatment interventions where bespoke tailor-made montages for each patient could be derived building on the foundational knowledge revealed here.

UKRI Gateway to Research · FY 2026 · 2026-03

Rigidity theory is an interdisciplinary field which aims to provide techniques for understanding the rigidity and flexibility properties of discrete geometric constraint systems. The paradigmatic example is that of a bar-joint framework, which consists of stiff (fixed length) bars that are connected at their ends by freely rotational joints. Mathematically, a framework is a graph that describes how the bars are connected, paired with a mapping of the graph’s vertices (representing the joints) into d-dimensional space. The framework is "locally rigid" if any small perturbation of the joints that preserves the bar lengths results in a framework congruent to the original. However, even for a locally rigid framework, there may still be distant, non-congruent frameworks with the same bar lengths. The framework is "globally rigid" if the graph and bar lengths uniquely determine its shape in d-space, up to rigid body motions. The origins of rigidity theory date back to the work of Euler and Cauchy on the rigidity of convex polyhedra and Maxwell’s studies of articulated engineering structures. Over recent decades there has been a surge of interest in rigidity theory due to both theoretical and computational advances as well as the emergence of a range of new application areas. The geometric constraint systems studied in rigidity theory are suitable mathematical models for a wide range of both natural and engineered structures and their rigidity and flexibility is crucial for their form, behaviour and function. The local and global rigidity of a framework depends on both the underlying graph and the specific locations of the joints, and it is in general very difficult to determine whether a given framework is locally or global rigid. However, these problems become more tractable if the joints are placed generically, because in that case both global and local rigidity only depend on the combinatorics of the underlying graph. While the local rigidity theory is well-established, advances in global rigidity have only gained momentum recently, due to new mathematical breakthroughs and emerging application areas such as structural biology and sensor network localisation. Real-world structures are rarely generic and often display non-trivial symmetries, leading to unexpected rigidity or flexibility. Motivated by practical applications, a very robust theory for the local rigidity of symmetric frameworks, including a combinatorial theory for frameworks that are "symmetry-generic'' (i.e. as generic as possible with the given symmetry), has been developed in recent years. However, due to significant mathematical obstacles, the corresponding challenges in symmetric global rigidity remain largely unexplored. The aim of this project is to establish ground-breaking results regarding the global rigidity of finite symmetric and infinite periodic frameworks. The main objectives are: (1) to create algebraic-geometric certificates for symmetric frameworks to be globally rigid via the novel approach of a detailed investigation of symmetric measurement varieties, and (2) to develop a combinatorial theory for symmetry-generic global rigidity by synthesizing recently developed combinatorial tools from the non-symmetric theories of local and global rigidity. The project will yield significant theoretical results, thereby establishing a substantial new mathematical research area, while also providing tangible benefits to applied science and technology. In particular, the results will lead to new design tools for material-efficient engineering structures and improved decentralised control algorithms for autonomous multi-agent systems, and will deepen our understanding of molecular stability in biological and chemical systems.

UKRI Gateway to Research · FY 2026 · 2026-01

Computers have become integral and indispensable tools in our society. With the advent of artificial intelligence into almost every aspect of our lives and quantum computing on the horizon, it is no surprise that significant efforts are being devoted to improving and better understanding these technologies. However, a critical gap is emerging. As software capabilities grow, they increasingly demand more powerful and smaller computer chips. Traditional hardware development, now constrained by physical limitations, faces immense complexities and escalating costs. Moreover, as computer chips shrink to near-atomic sizes, noise and thermodynamic fluctuations in individual components become significant challenges that cannot be ignored. To effectively address these challenges, a paradigm shift in how we think, design, and operate computers is essential. I propose a novel approach inspired by natural phenomena and rooted in thermodynamics, the driving force of nature. This new computing paradigm, called stochastic and thermodynamic computing (STC), leverages the inherent noise and fluctuations in computing chips to adapt and optimize chip operations, transforming a detrimental problem into a strategic advantage. This approach not only mitigates issues associated with heat dissipation in computer chips but also introduce more powerful method of computing that mirrors the dynamic and adaptable processes observed in nature. Imagine a computer that, instead of being hindered by the heat it generates, actually uses that heat to run more efficiently, much like our bodies use heat and energy. My aim is to develop novel quantum electronic devices that utilize noise as a resource, complementing the transistors in existing computers. STC stands out by allowing basic building blocks (stochastic bits or s-bits) to adjust their behaviour, driven by thermodynamic fluctuations and energy losses in the environment. This idea is distinct from neuromorphic computing, which mimics the brain's biology. STC instead focuses on exploiting thermodynamic principles. This research will focus on realizing s-bits and the first reconfigurable and adaptable computer chips that could implement STC. I will lead the development of this innovative technology using semiconductors and electromechanical devices, laying the experimental foundation of STC in nanoscale systems. The support of this fellowship will enable me to establish and grow a team that will explore how noise and random fluctuations can effectively process information and drive adaptation in computer chips, akin to biological systems. The research promises significant scientific advancements by enabling computation near fundamental efficiency limits. STC has the potential to excel in solving complex problems that elude optimal solutions in both current classical and quantum computing, such as stochastic diffusion models and time series forecasting. This could be a game changer in fields like artificial neural networks, climate modelling, financial modelling, and the simulation of biological systems. Developing strategies to engineer noise in micro and nanoscale systems will not only advance STC but also provide necessary insights to enhance both classical and quantum technologies. The Future Leaders Fellowship will support me to grow and lead a skilled interdisciplinary team that will spearhead the experimental innovation of this novel computing paradigm. Through this project, I anticipate overcoming significant technical challenges, including the stability and reliability of s-bits under variable operational conditions. Addressing these challenges will not only advance STC but will also allow the development of versatile, more efficient, and accessible computing technologies, thus propelling the UK's position as a frontrunner in computational innovation.

UKRI Gateway to Research · FY 2025 · 2025-12

Meeting internationally-agreed climate goals requires a strong partnership between citizens and government, and therefore strengthened and enhanced democratic structures. The first stage of my Future Leaders Fellowship successfully designed and implemented democratic innovations designed to engage citizens in energy and climate governance, including ‘deliberative mini-publics’ (DMPs, an umbrella term for Citizens’ Assemblies, Juries and Panels). We worked closely with policy actors including the UK Parliament, the Climate Change Committee and the International Institute for Democracy and Electoral Assistance (IDEA). The renewal phase of this Fellowship will move beyond consideration of specific innovations such as DMPs, to look at the wider democratic and institutional context for citizen participation in energy and climate decision-making. Our overall research question for the renewal stage will be: How can democratic processes and institutions change to ensure that citizen voices are integrated into energy and climate governance? We will work through firstly, analysing the progress to date in embedding citizen deliberation. We will conduct two case study analyses of policymaking processes, collaborating with policy actors to analyse how decisions are made, in real time. Secondly, we will take these findings and develop proposals for democratic innovations beyond DMPs. We will ask what changes to institutional procedures and practices are necessary to embed citizen perspectives. Thirdly, we are asked for advice and resources for embedding citizen deliberation. This is why we are proposing a specific impact-focussed work package. This will include a dedicated resource hub, signposting to our own and others’ work, and bespoke support to key policy actors. We will also extend our international reach through collaboration with IDEA and the International Climate Councils Network (ICCN) to investigate comparative approaches to citizen engagement across different legislatures. Through this integrated programme of conceptual and empirical research, and partnership-focussed impact work, we will contribute directly to the development of climate strategy which enhances democratic institutions and processes.

UKRI Gateway to Research · FY 2025 · 2025-12

Integrated Pest Management (IPM) aims to reduce the risks and impacts of pesticide use and promote ecologically-sound agricultural practices. This relies on an intimate understanding of the ecology of pest and beneficial insects and how their population dynamics can be influenced to maintain crop productivity and profitability. IPM is increasingly prominent in national and international regulations because it aligns with a broader drive to sustainably transition the farming system; but it is also a very knowledge-intensive approach, and the evidence to support and accelerate that transition is still lacking. Monitoring is a core principle of all IPM frameworks to identify the connection between interventions, pests, and natural enemies, and continually adapt practice accordingly. A significant barrier is that due to the complexity of rapid and accurate identification, traditional surveillance methods focus on just a small number of insect pests and have a limited capacity to scale up. The quality and quantity of information generated by traditional approaches is therefore insufficient to address dynamic pest behaviours at scale, and non-target insect biodiversity samples are often discarded. As a result, automated identification using Deep Learning (DL) tools to process imagery has the potential to transform how we achieve early detection, run predictive models, and enhance decision-making for pest control. However, the challenge is that developing effective DL tools require large volumes of training data. Previous studies have successfully demonstrated the potential automated imaging for insect identification, but tools that make use of easily accessible data simply reinforce existing biases, so ensuring reference databases are accurate and representative of target agroecosystems is key. The greatest gaps in our understanding are among diverse taxonomic groups of natural predators and parasites/parasitoids that are key to understanding how to sustainably suppress pest populations and minimise crop losses. Such groups underpin, without the need for human intervention, the biological control services we gain form ecosystems. Reducing the taxonomic bottleneck during sample processing would transform the rigour by which we can test different agroecosystems. Our project integrates the strengths of molecular and DL methods to produce a novel generic pipeline for labelling large volumes of images. Molecular identification is the gold standard by which we can consistently identify taxa, and there are increasingly large-scale efforts to catalogue the diversity of life to facilitate confident assignment of DNA sequences to species. Integration of sequencing with techniques like imaging has been constrained by the fact that it remains costly and time consuming to apply at the individual level. Instead, we will employ a phased approach to train algorithms to build associations between thousands of specimens and generated sequence-labels that are then trained to discriminate taxa consistently across samples. Our aim is to develop the first image classifier trained using high-throughput sequencing (HTS), and that has the capacity accurately process large volumes of field data. The techniques are all separately proven methods within their fields, but this is the first time multiple DL tools will have been combined in this way. Our real-world understanding of processing constraints are informed by our industry partner Fera, and our goal is to alleviate the longstanding constraints in their workflow. In future the same approach can be developed in countries where the availability of taxonomic expertise is low and will accelerate new avenues of research that support the global transition to sustainable agricultural management.

UKRI Gateway to Research · FY 2025 · 2025-11

Depression is a multifaceted mental health condition affecting millions globally, arising from disruptions in the brain networks and hormonal systems that regulate mood, stress responses, and emotional well-being. These systems are deeply interconnected, yet studying their dynamics is challenging due to variability across individuals and limitations in obtaining comprehensive hormonal measurements. Mathematical modelling provides a powerful tool to address these complexities by capturing the interplay between brain networks and hormonal systems in a structured and quantifiable framework. Such models can integrate diverse biological data, simulate intricate feedback loops, and yield insights otherwise unattainable through direct observation. They enable researchers to test hypotheses, predict outcomes, and illuminate the mechanisms of depression, providing critical guidance for developing targeted interventions. This is especially vital given the limitations of current treatments, such as antidepressants and therapy, which often take weeks to act and fail for many patients. My research focuses on creating mathematical models that integrate real-world data to elucidate the dynamics of depression. In the model-building stage, I will incorporate data from advanced sensing technologies, such as fMRI and EEG, to capture how brain networks influence hormones. I will also embed inferred interactions for hormones thought to be implicated in depression, even when time series data is scarce, to examine their role in the downstream behaviour of measurable hormones like cortisol. These models will be tuned to fit human parameter values and account for complexities like time delays in hormonal signalling. By integrating diverse data sources and ensuring consistency across them, my work will unify brain networks and hormonal rhythms into a comprehensive framework. Upon deriving these models, I will use structured pseudospectra, which is a key innovation in my approach. Unlike standard pseudospectra, which analyse how systems respond to general perturbations, structured pseudospectra evaluate how specific perturbations—such as changes in hormone levels caused by medication or alterations in brain network structure from therapy—affect the system. This enables a detailed exploration of the bidirectional influences between brain networks and hormones, revealing the most sensitive components of these systems and guiding the development of more precise treatments. With advances in sensing technologies like real-time hormone monitoring and high-resolution brain imaging, I will derive data-driven models that I can also explore with structured pseudospectra. This will complement the mechanistic insights gained from my equations and in particular allow me to validate my equations and explore bio-variability across populations. The societal implications of this work are profound. By minimising trial-and-error prescribing, reducing unnecessary side effects, and enhancing the likelihood of successful outcomes, this research has the potential to transform mental health care. Simulating personalised responses to interventions offers tailored solutions for patients, while advancing our understanding of depression’s mechanisms could alleviate its societal and economic burdens, ultimately improving countless lives.  Recognising the sensitivity of this topic, my research will include a component of Public and Patient Participation, ensuring that end-users of any potential technology are actively consulted and included throughout the research process. This engagement will help align scientific advancements with the needs and experiences of those they aim to benefit.

UKRI Gateway to Research · FY 2025 · 2025-11

Within contemporary chemical science the drive towards sustainable innovation is paramount, particularly as finite natural resources continue to diminish. With an annual production exceeding 100 million tons, aromatic compounds represent a fundamental feedstock across various sectors, including pharmaceuticals, agrochemicals, and materials science. These compounds typically form flat, C(sp2)-rich molecules, which, while versatile, often lack the three-dimensional complexity needed for modern applications. One powerful approach to enhance the utility of these aromatic compounds involves dearomatisation, typically through hydrogenation, to give saturated analogues. However, this method fails to introduce new groups which constrains its value in synthesising complex molecules important for drug discovery and materials innovation. Our research develops an innovative dearomative functionalisation approach that efficiently converts simple aromatic compounds such as pyridone and pyridine into functionalised, bicyclic Dewar-heterocycles. Given that on average 6 new ring systems enter drug-space each year and 28% of new drugs contain a new ring system, this research represents an important capability for long-term innovation. Our aims centre on leveraging the photochemically induced [4p]-electrocyclisation of simple heterocycles like pyridone and pyridine to generate Dewar-heterocycles. This reversible process gives a racemic mixture, which will enable the selective capture and functionalisation of one enantiomer over the other. Using an enantiopure metal catalyst, the alkene fragment within these photogenerated Dewar-heterocycles will be targeted for selective hydrofunctionalisation. We will harness stereomutation of Dewar-heterocycle enantiomers to implement a dynamic kinetic resolution that facilitates the enantioconvergent synthesis of topologically unique 3D structures in a single synthetic operation. The question must be asked: Why has the development of a comprehensive catalogue of synthetic methods for functionalised Dewar-heterocycles remained elusive? Synthesis of Dewar-heterocycles necessitates light irradiation, often triggering concomitant side-reactions which render reactions inefficient and purifications challenging. In particular, photogeneration of Dewar-pyridone has historically been both inefficient and unselective. However, we have recently developed a solution to overcome these drawbacks. Specifically, we have discovered a new approach that allows for efficient photogeneration, and reversion, of Dewar-pyridone with exceptional fidelity. This advance provides the basis necessary for capture and stereoselective functionalisation, enabling the synthesis of unique, high complexity bicyclic structures with well-defined spatial configurations. Our research will specifically target the enantioconvergent metal-catalysed hydroarylation of Dewar-heterocycles, selectively giving functionalised, rigid bicyclic structures with well-defined substituent orientations. This rigidity offers substantial benefits in medicinal chemistry by reducing entropic penalties associated with conformational reorganisation at biological targets and by increasing the concentration of bioactive conformers. This synthetic concept will enable selective and efficient access to a diverse array of new bioisosteres, key for enhancing molecular efficacy in pharmaceutical and agrochemical applications. The use of a wide variety of commercially available aryl-boronic acid reaction partners expands the ability to generate a broad diversity of compounds, facilitating strategic design of core structures. Consequently, our generic platforms are geared to promote the development of compounds with optimised target interactions and potentially improved pharmacokinetic properties.

UKRI Gateway to Research · FY 2025 · 2025-11

The United Nations Office for Disaster Risk Reduction reports that 476 million people in more than 90 countries identify as Indigenous and ~20% of the Earth is covered by Indigenous territories. Globally, Indigenous peoples live at risk from natural hazards (e.g., volcanic eruptions, landslides, earthquakes). In the case of volcanoes, the focus of this work, all of the ~450 active volcanoes located in Canada, New Zealand, South America, and the USA are located within Indigenous territories and pose a risk to 10s of millions of people. However, despite both the potentially lethal nature of volcanic eruptions and the wealth of information preserved by Indigenous peoples, few attempts have been made to respectfully braid this Indigenous Knowledge with science during the modelling of volcanic processes and the forecasting of their associated hazard footprint. Thus, any associated hazard products and mitigation strategies are inherently limited. Currently no international partnerships or frameworks exist to co-create knowledge and hazard products that braid both Indigenous Knowledge and volcanology. This new partnership of global experts and Indigenous communities will address this gap. This ‘seedcorn’ project will assemble an international team with expertise not available in the UK. All team members are experts in, and involved with, civil defence, hazard mitigation and volcano monitoring. All live near an active volcano and have a direct, well established, and meaningful connection with local Indigenous communities, and, in some cases, are Indigenous themselves. Throughout the course of this grant, the partnership proposes to achieve three aims: (1)   Form a ‘direct line of communication’ between volcanologists, Indigenous scholars, and Indigenous communities to effectively braid the ‘missing knowledge’ into the next generation of state-of-the-art numerical volcanic hazard models. This will form the basis of a long-term, self-sustaining ‘Indigenous Volcanology Partnership’ that encompasses academic institutions, government stakeholders, and local community groups. (2)   Quantify the global overlap between Indigenous peoples and volcanoes and identify knowledge currently ‘missing’ or ‘overlooked’ when constructing volcanic hazard products that affect Indigenous territories. Highlighting this need/gap will support the case of future national and international grant applications by the partnership. (3)   Determine successful methods to co-produce (volcanic) hazard products such that numerical model results can be effectively utilised by communities at risk. This will form proof-of-concept data for future grant applications by the partnership. These aims will be met through a series of meetings and workshops involving all team members wherein a database will be created that quantifies the global spatial overlap between volcanic hazards and Indigenous peoples, illustrating how information can be shared for mutual benefit whilst improving physical models of volcanic processes and their hazards. We will also engage in-person with four different Indigenous communities from the USA, New Zealand, Canada, and Argentina, to co-create and co-produce a volcanic hazard product. The final outcome will be a novel long-lasting partnership that is equipped to tackle timely and interdisciplinary research questions surrounding volcanic hazards, eruption processes, and disaster risk reduction. Subsequent research led by this team will, for example, identify how Indigenous Knowledge can be woven into volcanic hazard models to improve forecast accuracy, and uncover the most suitable products to communicate volcanic hazard and risk. Ultimately this will minimise the human and economic cost of volcanic eruptions around the world and is an outcome only achievable through a complimentary, global partnership.

UKRI Gateway to Research · FY 2025 · 2025-10

Packaging is necessary for the protection and transportation of products. However excessive packaging increases both material and transportation costs, and in turn has a negative impact on the environment. It is therefore important to minimise packaging as far as possible. In the United Kingdom the impetus towards reducing packaging has recently grown due the new Extended Producer Responsibility (EPR) regulations which require businesses to report data on how much packaging they use and pay associated waste management fees. This challenge is particularly important for eCommerce businesses which use large amounts of cardboard packaging to dispatch thousands of orders each day. For logistical reasons such as limited physical space, such businesses usually only have a limited number of boxes available that they can use to dispatch orders. This selection of boxes must be carefully chosen. On the one hand, the selection of boxes must contain boxes large enough to pack the vast majority of orders. On the other hand, the selection of boxes must contain smaller boxes so that smaller orders can be packed efficiently. What makes this problem particularly complex is that the range of possible orders is extremely large, consisting of combinations from a range of hundreds or possible thousands of different products. Previous research has resulted in a mathematical optimisation framework which is able to optimise the selection of boxes for dispatch. The framework takes as inputs a large set of order data and a large set of potential boxes. It analyses which boxes can be used to pack each order, and then selects the subset of boxes which would then optimise packing efficiency. This framework has been implemented as a software tool and been demonstrated to produce significant improvements over previously used packaging for several real world data sets. However, the tool, which is implemented as a suite of command line programs and application programming interface, requires a high level of technical expertise to set up and use, and a relatively high amount of computing power to run. The aim of this project is to therefore create a web-based graphical user interface (GUI) for this framework. The GUI will lower the technical barrier required to use it, and it being hosted in the cloud would enable it to be used from any computer with internet access, including low-power devices. This GUI will therefore open up the box optimisation tool to a larger range of users and empower them to experiment with it directly. For example, the tool could be used to investigate the effect of allowing different numbers of boxes to be used for dispatch, and the solutions can be customised according to which key performance indicators are most important. It will thus serve as an effective decision support tool for optimising packaging options. This will allow businesses to reduce to the costs associated with packaging including both direct costs from packaging materials, and the waste management fees associated with the EPR regulations. Ultimately, this work will benefit the environment by reducing the total of packaging being used.

UKRI Gateway to Research · FY 2025 · 2025-10

  Modern slavery affects around 50 million people worldwide. In the UK, large companies (=£36m turnover) must publish annual modern slavery statements, but the quality and consistency of these reports vary widely, making effective oversight difficult. Manual review at scale is slow, costly, and inconsistent, which limits the ability of investors, civil society, regulators and companies themselves to identify risks and drive improvement. Our research with the Financial Reporting Council and the UK Independent Anti-Slavery Commissioner examined statements from 100 major companies and found systemic weaknesses: only about one-third were clear and readable; just 25% disclosed key performance indicators (KPIs); and only 12% showed evidence that KPIs informed decisions. These findings confirm that today’s approach does not reliably support accountability or better outcomes. Anti-Slavery Intelligence is an AI-powered platform that automatically analyses corporate modern slavery statements, producing transparent compliance scores, benchmarking, and practical recommendations for improvement. The tool converts a manual, months-long process into minutes, enabling portfolio-scale analysis for investors, standardized evaluation for regulators and CSOs, and immediate feedback for companies seeking to strengthen their reporting and practices. Aims and objectives • Build and refine an explainable AI model aligned to recognised reporting expectations to evaluate statements consistently at scale. • Provide clear, evidence-based recommendations that help companies move beyond generic disclosures to KPI-driven action. • Create a benchmark database to track trends over time and enable sector and portfolio comparisons. • Run structured pilots to validate usability, impact, and pricing across investor, corporate, regulator and CSO segments. • Ensure ethical use by analysing only public statements and enabling access for CSOs, not just well-funded institutions. Why this matters now Stakeholders across the ecosystem have validated the need. CCLA Investment Management has provided over 100 labelled statements to support model development; WikiRate, the Slave-Free Alliance, and Business for Social Responsibility (BSR) have all affirmed the demand for standardized, scalable assessment. We also submitted written evidence (FLS0006) to the UK Parliament’s Joint Committee on Human Rights inquiry on forced labour in UK supply chains (published 2 July 2025). In 2025, UK parliamentary reviews and government updates— including the Joint Committee on Human Rights’ inquiry into forced labour in supply chains and the Home Office’s revised Transparency in Supply Chains statutory guidance—have intensified the need for reliable, comparable metrics to assess modern-slavery disclosures. Potential applications and benefits Investors can conduct rapid, portfolio-wide screening and monitoring to strengthen ESG due diligence and stewardship. Companies receive a concrete improvement roadmap tied to identified gaps, helping them meet legal expectations and respond to stakeholder scrutiny. Regulators and policymakers gain macro-level visibility of compliance and quality to inform supervision and policy development. Civil society organisations (CSOs) and the wider public get easier access to comparable evidence that supports advocacy and encourages better corporate behaviour.   Building on an ARC Launch experience and an Impact Acceleration Account award, we have a working live prototype and active engagement with stakeholders including the GLAA, Unseen and the Home Office. ARC Accelerate will help us complete market validation, refine the business model (including social-venture options), and scale the technology and user experience so that Anti-Slavery Intelligence can become the sector’s reference standard for modern slavery statement assessment.  

UKRI Gateway to Research · FY 2025 · 2025-09

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

UKRI Gateway to Research · FY 2025 · 2025-09

The explosion in the volume and velocity of data now collected means that, across a range of scientific disciplines, there is a pressing need for general-purpose detection methods capable of identifying changes and other anomalous phenomena in real-time. This project will focus on the development and deployment of leading edge real-time change and anomalous detection methods into the science base. Working closely with internationally leading research groups in Materials Science, Digital Futures and Frontier Physics this project will (i) disseminate current state of the art change and anomaly methods to accelerate scientific discoveries; (ii) identify, develop and trial new approaches inspired by new change and anomaly challenges that emerge from the Science base; and (iii) seek to develop understanding and a shared vision which will help catalyse interdisciplinary partnerships for future trans-disciplinary research.

UKRI Gateway to Research · FY 2025 · 2025-09

Lancaster Policing Academic Centre of Excellence (L-PACE) Lancaster University’s case to be recognised as a Policing Academic Centre of Excellence (L-PACE) is based on its world leading reputation for the application of social and behavioural sciences to policing Areas of Research Interest (ARI). Lancaster is already a member of the N8 Policing Research Partnership (N8PRP), a collaboration between 8 research-intensive universities and 11 police forces in the North of England include Cheshire, Cleveland, Cumbria, Durham, Greater Manchester, Lancashire, Merseyside, North Yorkshire, Northumbria, South Yorkshire and West Yorkshire. In addition, L-PACE works with national forces including Police Scotland, the NCA, Counter Terrorism Police, Border Force and Immigration. This proposal showcases Lancaster’s strengths in policing research which is not only cross-disciplinary, but also built around expertise in the analysis of visual, linguistic and sensor data, and in partnership with organisations who are signed up to the Police-Industry Charter. L-PACE will demonstrate expertise in the two required Areas of Research Interest (ARI) (Enduring Challenges and Crime Prevention) and will highlight our strengths in two additional ARIs (Personal Safety and Surveillance and Sensing). In the Enduring Challenges ARI we have strengths in building and maintaining trust as well as future workforce and training. In the Crime Prevention ARI L-PACE has expertise in both safer physical and online public spaces, as well as new evaluation tools and approaches to risk mitigation. In the Personal Safety ARI, L-PACE specialises in research on the wellbeing of officers in a variety of contexts, and leads the first ever project seeking user perspectives on uniform design, usability and safety which will set 2025 objectives for the National Uniform Portfolio. In the Surveillance and Sensing ARI, L-PACE specialises in research on effective interviewing of vulnerable citizens; on the use of digital technologies in a practical, ethical and forensically informed manner; and on improving situational awareness, particularly in emergency contexts where interoperability is key. The L-PACE will deploy a range of mechanisms to support new activities during the lifetime of the Centre. These include a mix of smaller, data science mini-projects, partnership funding with larger Lancaster based networks like the £3.5M Network Plus for Analytical Behavioural Science (NABS+), collaborative small grant funding to provide proof-of-concept data for larger research bids, and a rapid response funding mechanism for responding to urgent and emergent concerns. L-PACE will also work with police forces and companies signed up to the Police Industry Charter (launched in March 2024) to inform product and service development through the highest quality evidence base. The aims of L-PACE include: increasing the number and range of academics involved in police ARI projects; fostering new relationships between academics and police forces; providing practical solutions to current policing problems; sparking new ideas that can be built into more substantial projects; tackling the policing skills and recruitment gap by creating a pathway for students consider a career in data related policing. L-PACE will be guided by a Steering Group of senior Lancaster academics with expertise across all areas of the ARI’s. L-PACE will also have an external Advisory Group, made up of senior current and former officers, industry representatives and data management experts, to ensure that the work remains focussed and relevant.

UKRI Gateway to Research · FY 2025 · 2025-09

This is requesting funding for the continued exploitation and core development in experimental particle physics for the Lancaster University experimental particle physics group and its associated core activities. The detils are given in the case for support. The group’s research activities encompass the themes of Energy Frontier (ATLAS, ATLAS upgrade, future colliders), Flavour Physics (NA62), Neutrino Physics (DUNE, Hyper-K, MicroBooNE, SBND, T2K), Dark Matter (Darkside-20k), GridPP and Detector R&D. In each area, future/upgrade activities proceed in parallel with exploitation of current datasets and data-taking operations. Common interests within the group span these theme areas and focus on investigations of flavour oscillation, CP-violation, (in)direct searches for new physics, software development and computing. In the requested grant period, we will continue to pursue each theme area. ATLAS will complete Run 3 data taking, and we will play a leading role in Data Preparation and Computing, make high-precision tests of the SM with huge t-tbar and B-hadron samples, study the Higgs-boson in di-tau final states, refine our understanding of QCD, and search for new particles with intermediate lifetimes. Prior to Run 4, ATLAS upgrades will be installed.  Lancaster will be crucial to the ITk Pixel upgrade, contribute strongly to integration and commissioning efforts and prepare for HL-LHC data preparation and computing operations. NA62 will continue taking data until Long Shutdown 3 and we continue leading overall coordination of physics analyses, central Data Processing activities, pursuing world-leading measurements of rare kaon decays and precision tests of lepton flavour universality. Lancaster will continue leading physics sensitivity studies for the HIKE experiment. T2K will continue to produce world-leading exclusions of the CP-conserving phase space and indications of the preferred value of delta_CP. Using data from the upgraded near detector, new samples that will provide stronger constraints on flux and cross-section uncertainties in the oscillation analysis will be developed. Hyper-K will begin data-taking in 2027, and Lancaster will continue its leading role in the DAQ, software development and oscillation analysis.  Lancaster will be at the forefront of the first Hyper-K results. Using its full dataset, MicroBooNE will produce the next generation of searches for sterile neutrinos, cross-section measurements for SM processes, and searches for rare SM and BSM processes. SBND will collect all planned data during the grant period, and the first flagship measurements for high-statistics precision measurements will be published. Together with the other SBN detectors, they will produce the first search results for sterile neutrinos and BSM processes.  DarkSide-20k will publish first dark matter searches and detector instrumentation technology articles.

UKRI Gateway to Research · FY 2025 · 2025-09

The world requires urgent action to rebuild damaged ecosystems. Large businesses have a critical role to play in this effort – not only are they collectively responsible for a large amount of environmental damage, but they also have significant resources and major incentives to restore nature. Indeed, many large corporations are already attempting to restore nature – in recent years, businesses have collectively pledged to plant billions of trees, hundreds of thousands of corals and tens of thousands of mangroves. These efforts, however, are often hampered by poor planning, a lack of evidence-based interventions, inadequate monitoring and reporting, and “greenwashing” practices. The potentially transformative power of the corporate world is being wasted. In project ENTERPRISE (ENsuring Transformative Ecosystem Restoration in the PRIvate SEctor), I will build an interdisciplinary team to carry out critical research that ensures business’ environmental efforts result in genuine real-world benefits. I will bring together academics who are experts in restoration ecology, corporate accounting and business consultancy, with policy makers and business leaders who have powerful influence in the real world, to create solutions for more effective business-led ecosystem restoration. In three complementary work packages, we will: Address knowledge gaps in business reporting and transparency. Exciting new data will soon emerge as a result of recently developed international requirements for business transparency. I will use this new data to evaluate the impacts of business’ environmental restoration efforts in unprecedented detail. This will reveal how impactful business-led restoration currently is, and which industry leaders are setting the best examples for other businesses to follow. It will also help us develop more policy interventions that further improve the rigour of corporate reporting on biodiversity. Develop mechanisms for scaling-up restoration of critically threatened ecosystems. For some of the world’s most endangered biodiversity hotspots – tropical marine ecosystems – we have very little understanding of how to best achieve large-scale ecosystem restoration. Applying fundamental theories in ecology has already helped overcome this problem in terrestrial ecosystems, and it could do the same for tropical marine biomes. I will work with large corporate-led programmes that offer unrivalled scale of resources and ambition, to test these ecological theories. I will identify mechanisms for increasing the scale of coral, mangrove and seagrass restoration, and quantify realistic targets and costs for each of these ecosystems. Modelling strategies for corporate environmental impact. Businesses attempting to deliver environmental benefit are often trying to apply the ‘mitigation hierarchy’ – reducing the negative impacts of their environmental damage before investing in additional positive impacts through ecosystem restoration. This is difficult in practice, because we don’t understand the likely impacts of different environmental strategies. I will calculate estimates of optimal investment (reducing operational impacts vs additional ecosystem restoration) for businesses in different scenarios. I will run workshops with local and national businesses to test, implement and refine these decision-making processes in the real world. These ambitious plans combine scientific excellence, innovation in ecosystem restoration and impactful engagement with industry and society. They will facilitate much greater clarity on the role of business in rebuilding nature, and how the power of the private sector can be best leveraged to help achieve global sustainability targets. Delivering this programme will launch my independent science career, supporting me as I develop into a global research leader guiding transformative environmental restoration.

UKRI Gateway to Research · FY 2025 · 2025-09

The oxidising capacity of the atmosphere determines the lifetime of major air pollutants and short-lived greenhouse gases such as methane, and is dominated by tropical regions that support active photochemistry. It is critical to understand the processes that govern tropical oxidation and how they vary over space and time to provide reliable estimates of the future evolution of key pollutants and their impacts on climate. Observations are unable to provide direct information on the processes governing oxidation at a global scale, or how they might change in future, and hence policy decisions on Net Zero targets and climate change mitigation depend on atmospheric models. However, current models show substantial biases in their simulation of oxidising capacity, under- or overestimating the lifetime of methane by as much as 40%, highlighting major gaps in current understanding. This model uncertainty has remained persistently high for more than two decades. The DeTOX project addresses these issues by taking an entirely new approach. We will provide the first formal constraints on oxidation in the tropics, bringing together the wealth of recent observations with global chemistry-transport models using innovative statistical and machine learning approaches. We will calibrate these models at a process level for the first time, providing new insight into the processes governing oxidation and reducing uncertainty in future projections. We will achieve this through rigorous uncertainty quantification and emulation of three independent models, using existing observations to constrain uncertainty in the processes governing the hydroxyl radical, OH, which dominates oxidation in the tropics. The lifetime of methane, the second most important greenhouse gas, is a key focus, and the project will enable improved estimates of the main sink of this gas and more robust projections of its future abundance. Our approach will provide improved quantification of the current oxidising capacity of the tropics and clear identification at a process level of how and why it is changing. Observational constraints will reduce uncertainty in estimates of the lifetime of key pollutants at both regional and global scales. New process-based understanding will allow us to identify the drivers of change and fully-coupled climate projections will permit improved assessment of future changes in OH and climate-relevant pollutants such as methane. Our approach will also highlight gaps in current understanding that require further investigation through new observations or targetted model development. We will use the emulators developed here with ongoing satellite measurements to provide a new dynamic observation-based estimate of oxidising capacity and its changes along with attribution of changes to the processes driving them. This project is based on a new collaboration between atmospheric scientists and experts in machine learning. In addition to improved insight into oxidation processes, a key outcome will be development of new statistical methodologies that will benefit the wider atmospheric chemistry and climate communities. This will be of particular value to data assimilation, reanalysis and inversion communities, allowing more reliable estimates of emissions and their variations. We will work with our international partners to encourage a paradigm shift in the way observations are used with models from evaluation towards formal constraint. Through our leadership roles in major international assessment projects such as IPCC, CMIP, TOAR and HTAP we will ensure that improved process understanding benefits future assessments of climate and air quality, providing more robust evidence in support of future environmental policy.

UKRI Gateway to Research · FY 2025 · 2025-08

We have developed a hyperactive carbon-fixing enzyme to tackle the dual challenges of food security and sustainable industry. We will produce new fast-growing plants and photosynthetic bacteria for a step change in sustainability research. In the face of a changing climate, the world faces a growing sustainability crisis and an urgent need to adapt industry to reduce greenhouse emissions and environmental impact. A growing population, climate change, and soil desertification mean many people are already food insecure, and millions face the same prospect in coming decades. Food security is underpinned directly or indirectly via plant-based agriculture for food and feed. A significant change is also needed in how chemicals are made to reduce fossil fuel requirements and thus make their production more sustainable. Photosynthetic carbon fixation underpins all life on Earth. The enzyme Rubisco is central to carbon fixation by photosynthesis. It is the gatekeeper of carbon entry into the biosphere, the most abundant protein on the planet, and an essential yet imperfect catalyst. Rubisco often limits photosynthetic carbon assimilation and growth. Therefore, improving Rubisco catalytic efficiency is an economically high-value strategic research goal to increase yields in agriculture and the sustainability benefits and efficiency gains through green biotechnology using photosynthetic prokaryotes. A poorly understood aspect of Rubisco biochemistry is the role of post-translational modifications (PTMs) to the primary structure that could regulate its activity in vivo. We have identified a previously unknown carbon dioxide binding site on Rubisco. We have demonstrated that ablating this binding site gives a remarkable increase in Rubisco’s carbon-fixing activity. Further, we have shown that eliminating this binding site from the chromosome of a photosynthetic prokaryote gives a new, fast-growing strain. Therefore, we have an exciting and exploitable tool for tackling sustainability challenges, and contributing toward priority efforts to use biosciences research to advance sustainable agriculture, and produce renewable resources to power clean growth. The proposal builds on these findings through three experimental streams. We will fully characterise the impact of this PTM on the biochemistry of both plant cyanobacterial Rubiscos. This will be important to understand the mechanistic basis behind changes in catalysis, and how broadly transferable this discovery will be. We will exploit our fast-growing strain as a green bio-factory for industrial biotechnology by examining the impact on the yield of high-value bio-alcohols. This objective will have a near-term impact on research in pursuit of alternative chemical synthesis routes that reduce global reliance on fossil fuels. We will generate tobacco plants with mutated Rubisco large subunits to characterise the effect of this PTM on plant-level photosynthesis and growth. This objective will establish the physiological impacts of this mutation in tobacco as a proof-of-concept for future larger scale trials and engineering of improved crop plants.   Together, the objectives will develop our preliminary findings to a technology readiness level for future exploitation with industry.

UKRI Gateway to Research · FY 2025 · 2025-08

One third of UK adults have a musculoskeletal condition, which is the leading cause of disability, sick days and early retirement. Living with a musculoskeletal disability is associated with health inequalities, deprivation and the biggest cause of reduced life expectancy. Our multi-disciplinary project aims to produce and confirm the designs for a new portable technology to measure bone health in communities. No such technology currently exists. This engineering project involves co-design to adapt an existing prototype instrument into a new, more flexible design that is portable and robust. The proposed design will use the laser-based technique (spatially offset Raman spectroscopy; SORS) to shine a light on skin to measure the bone below. This project will provide proof of safety of the design while making sure high-quality data are collected.  As part of this, we will improve the data collection methods.  This project will ensure that this new technology will meet the needs of patients and healthcare providers. As the first step, we will gather a user engagement group, including carers, people with lived experience of bone conditions (e.g. osteoarthritis/osteoporosis), and healthcare professionals. We will hold a series of workshops to develop the different parts of the technology. Learning from people with lived experience, our design will meet clinical needs and be patient friendly. Similarly, input from healthcare professionals is equally important. Both the hardware and software (including privacy and security) will be developed to suit clinical needs, so that the technology can be applied to communities, starting with the most deprived. The workshops will provide a forum to create leaflets/websites/videos/podcasts to explain the new technology with the public and will be an opportunity for patient education of bone conditions. The new instrument will give accurate and detailed information about the chemical make-up of bone. It will be able to give information about the protein in bone, and the hard minerals, at the same time. The amount of each is very important for bone health. This information can be used to predict and diagnose genetic and ageing-related musculoskeletal conditions at an early stage. It could also be used to track changes in an individual over time. Importantly, SORS does not use ionising radiation allowing safe repeated use on adults and children alike, unlike X-ray technologies used in hospitals. The device will be portable and can be placed in different places such as a GP surgery/pharmacy/community diagnostic hub/community centre/local religious building/council gym/mobile unit. This will increase access to healthcare services while reducing hospital visits. Using lots of different locations within communities, with a range of appointment times should increase the likelihood of appointments with under-served groups from deprived areas, directly addressing health inequalities. This is important because these groups are more likely to develop musculoskeletal conditions early in life. Preventing disease progression will maximise the longer-term health benefits for people and ease pressure on the NHS, reducing the need to visit hospital. Early diagnosis can also reduce the cost of treatment or surgery. Establishing this new portable technology will be a game changer for musculoskeletal management and will pave the way for other conditions, such as bone and breast cancers to be more readily diagnosed and treated. Moreover, the data will be published, creating an opportunity to improve future research and other laser-based healthcare applications.

UKRI Gateway to Research · FY 2025 · 2025-07

  Summary Context There is a rapidly growing need in the Biological Sciences and related fields to explore fundamental biological and biochemical processes at the single-molecule level. Optical tweezer technology, which uses light to trap and manipulate microscopic objects non-invasively, allows for nanoscale manipulation of biomolecules while simultaneously visualizing single-molecule events in real time using fluorescence microscopy. This technology has already revolutionized biology, biochemistry, biophysics, and bioengineering. The LUMICKS C-Trap system is the first commercially available, user-friendly platform that integrates optical tweezers with advanced imaging and microfluidics, democratising transformative single-molecule studies. However, this technology is currently unavailable in the North West region, creating a critical gap in the research capabilities of the community. Therefore, the overarching goal of this application is to establish Lancaster University as the central hub for single-molecule biophysics research in the North West by establishing a LUMICKS C-Trap system in our bio-imaging facility. The Research the Equipment Will Enable The C-Trap system will empower researchers to investigate complex molecular interactions and mechanoproperties at the single-molecule level, enhancing studies across a wide range of disciplines. The system enables real-time, dynamic experimentation, combining optical tweezers, precision force measurements, and confocal fluorescence microscopy under temperature-controlled and advanced microfluidics. Key research areas in the North West region supported by the C-Trap will include: Protein-nucleic acid interactions crucial for DNA replication, repair, gene expression and innate immune sensing.  Protein-protein and protein-lipid interactions, including those relevant to signal transduction and membrane biology.  Mechanoproperties of macromolecular assemblies, cells, and membranes, underpinning cell function and disease biology.   Photosynthetic and plant biochemistry pathways critical to food security and climate sustainability.  This technology will significantly enhance collaboration and research outcomes in the Northwest region by providing access to advanced single-molecule techniques that are not currently available.   Aims and Objectives Research Capacity Building: Develop advanced biophysics capabilities complementing other imaging and biophysical platforms and enabling access to cutting-edge C-Trap technology for academic and industrial partners.  Regional Impact: Establish Lancaster University as the central hub for single-molecule biophysics research in the Northwest.  Collaborative Research: Foster synergies across the North West’s research community, including through the BBSRC-funded NorthWestBio Doctoral Training Partnership (DTP) and Doctoral Landscape Award (DLA), to accelerate shared scientific goals.  Training and Skills Development: Provide hands-on training for researchers across all career stages, including PhD students and early career researchers (ECRs), in single-molecule methods.  Potential Applications and Benefits The installation of the C-Trap system will have wide-ranging benefits: Generate high-impact data to advance understanding of fundamental biological mechanisms, including disease biology and therapeutic targets.  Facilitate insights into photosynthetic pathways, supporting food security and sustainability efforts.  Provide a state-of-the-art research platform for academia and industry, promoting technology transfer and knowledge exchange.  Position the North West as a leading region for biological, biochemical, and biophysical sciences, strengthening its reputation nationally and internationally.  Support the training of future UK scientists in dynamic single-molecule biophysics, equipping them with cutting-edge skills that span biology, biochemistry, and physics.  Upon installation, expert support will be provided by LUMICKS and collaborating institutions with existing C-Trap platforms (Universities of St Andrews and Sheffield) to establish the C-Trap system as an accessible and versatile resource. The Bioimaging Facility in Lancaster University’s Division of Biomedical and Life Sciences (BLS) will serve as the base for this transformative technology, ensuring its integration into ongoing and future research programs.