University of Manchester

UKRI Gateway to Research · FY 2024 · 2024-09

The central limit theorem, which, in simple terms, states that a suitable standardisation of the sample mean is approximately normally distributed for large samples is one of the most fundamental results in probability and statistics, underpinning statistical tests used throughout the sciences. Quantifying the error in this distributional approximation was a major problem in the early part of 20th century, which culminated in the celebrated Berry-Esseen theorem (1941-42) that gives a precise quantification of this error. Amongst its numerous applications, the Berry-Esseen theorem can be used to derive conservative confidence intervals and provide rigorous justification of rules-of-thumb used in the implementation of statistical tests. An essential assumption of the central limit theorem is that the observations have finite variance. However, this assumption can be too restrictive for real world observations exhibiting extreme values, such as insurance gains/losses due to rare, high impact events like severe flooding. Removing the restriction of a finite variance leads to a new family of approximating distributions for suitably standardised sample means, the so-called alpha-stable distributions. This distributional approximation, known as the stable central limit theorem, is one of the most important generalisations of the central limit theorem. It is a fundamental problem to quantify the error in approximating the distribution of a suitably standardised sample mean by an alpha-stable distribution, with an analogue of the classical Berry-Esseen theorem being the most coveted such result. Recent advances in the Stein's method literature have put a resolution of this problem within reach. The purpose of this project is to combine these recent methodological advances with a powerful smoothing technique to derive an analogue of the Berry-Esseen theorem for the stable central limit theorem.      

UKRI Gateway to Research · FY 2024 · 2024-09

Individuals with mental illnesses face notable disparities in physical health, a concern that is particularly pronounced among young people. The initial phase of this fellowship provided valuable insights into how digital health technologies can be employed to mitigate these disparities, especially in the early stages of mental illness. As I advance into the next phase, the overall objective remains the same as the initial plan; examining how widely-adopted digital technologies can be used to effectively address these health disparities. On the basis of the empirical data and real-world feedback obtained thus far, the central plan towards achieving this is to now to develop and evaluate an online lifestyle intervention, which can be delivered through video platforms (YouTube, and others) in order to improve health behaviours and outcomes in young people with mental illness, transdiagnostically. By engaging with clinicians, service users, and partners on major video platforms, the goal is to refine the delivery of an evidence-based lifestyle programme, making it accessible, engaging and specifically relevant to meet the needs of this underserved demographic. Within this, an entire program of co-designed lifestyle content will be created - through collaborative endeavor with stakeholders from mental health services, technology and content creation sectors, along with service users and world-leading experts in lifestyle medicine. This programme is envisioned to be a readily available resource, designed to be both engaging and informative, aiding young individuals under mental health treatment in various contexts. Furthermore, the integration of wearable and smartphone technology within lifestyle interventions for youth mental healthcare will be further explored. Establishing systems that facilitate the safe and effective use of these widely-adopted technologies, in sync with the physical healthcare and lifestyle interventions, forms a supplementary but beneficial aspect of this novel program of research. Lastly, real-world evaluations are crucial to measure the reach and impact of the digital interventions developed. By employing a mix of tech-driven metrics, routinely collected clinical data, and direct stakeholder feedback, the aim is to gauge the effectiveness and refine these digital interventions based on real-world experiences. Collectively, these objectives underline the endeavor to create evidence-based, bespoke physical health interventions that are not only widely available online but are also tailored to meet the specific needs and preferences of individuals with mental illnesses, particularly the youth and young adults. Through leveraging widely-adopted digital technologies, this renewed phase of research aims to take significant strides towards bridging the health disparities faced by individuals treated for mental illness, fostering a more accessible and effective landscape of physical health interventions.

UKRI Gateway to Research · FY 2024 · 2024-09

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 2024 · 2024-09

This research sets out to explore how energy is being rethought and understood in the context of local energy transitions. Through a 2.5 year ethnographic study of community and municipal energy projects in the UK, the research aims to understand how experiments with new technologies and practices of energy generation, distribution, conservation, supply and visualisation, are shifting understandings of what energy is and how it should be addressed as a tool of social reproduction. The research will focus specifically on the emergence of community and municipal energy projects oriented to local processes of social change and economic regeneration and to the digital and data technologies used within these projects to make energy knowable. It will seek to understand how local energy futures are being pursued by taking as a starting point two geographical areas - one in the North of England and one in London - where energy transformations are taking place. Taking these concrete locations as a starting point, the research will aim to understand how people are experimenting with and rethinking energy as an infrastructure of social reproduction. It will investigate what kinds of understandings of energy are emerging in these projects, the role of different kinds of technologies in positioning energy as a method of social and economic transformation and the possibilities and barriers that this reveals for broader energy transitions in the UK and beyond. The research aims to contribute both to academic research on the relationship between energy and social life, and to policy, community energy and business by outlining the social possibilities and conceptual barriers to an effective energy transition.

UKRI Gateway to Research · FY 2024 · 2024-09

The UKRI Fellowship as Thematic Research Lead for Crime and Justice is designed to support and promote the use of academic research in Parliamentary law- and policy-making. The role of the Thematic Research Lead is to create links between academics in the field of crime and justice with Parliament, and facilitate the sharing of research findings in this context. This is anticipated to lead to positive use of research in developing, reforming and using the law and associated policy. This proposal is designed to outline the activities and engagement over the course of the Fellowship.

UKRI Gateway to Research · FY 2024 · 2024-09

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 · 2024-09

Obesity is a global health problem affecting millions of people. It contributes to various health problems like heart disease, diabetes, and even certain types of cancer. Intuitively, this has huge societal and economic implications costing about £6 billion annually to the NHS alone, a figure projected to rise to about £10 billion each year by 2050. While healthy diet and exercise are the first line of intervention and should be promoted, they are often insufficient, and medical interventions become necessary for a significant number of people. One of the most effective treatments so far has been weight-loss surgery, but it is invasive, costly, and not practical when considering the epidemic proportion of the obesity problem. Therefore, finding an affordable, less invasive, and more universally applicable solutions is crucial. In this context, our team is set to explore a promising new drug, called Tirzepatide. This medication, originally developed for type 2 diabetes, has shown extraordinary results in helping people lose weight. In fact, its effects are almost comparable to those of weight-loss surgery, and superior to any other drug so far tested clinically. However, the exact way by which Tirzepatide achieves these remarkable results are currently unknown. That is where our research comes in. We aim to delve into the mechanisms through which Tirzepatide achieve its remarkable clinical outcomes, focusing particularly on its effects on the brain, as we believe that this is where the drug acts to exert its major impact on body weight. We will be using a 'reverse translational' approach, which means we start with what we already know from patient experiences and clinical trials, then work backward using laboratory mouse models to uncover the underlying biological processes. We will be using advanced genetic tools, which can be thought of as advanced biological controls, to find the specific brain cells that the drug interacts with to help people lose weight. These tools give us the power to flip these cells on or off whenever we want, just like switching a light on or off using a remote control. This will help us understand what exactly these cells are doing where the drug is working. In simpler terms, we are trying to find and study the 'weight loss' cells in the brain that this drug talks to. The goal of this research is to gain a thorough understanding of how Tirzepatide interacts with the body's systems to cause weight loss. We believe that this knowledge will be critical not only for a better-informed use of Tirzepatide itself, but also guiding the development of new treatments. Additionally, by pinpointing the specific 'weight loss' brain cells that this drug interacts with, we are also likely to gain a deeper understanding of the fundamental processes controlling body weight and how these processes go awry in obesity. This knowledge could offer hope for the development of more personalised and effective treatments in the future. As such, our research holds the potential to provide a more comprehensive understanding of obesity, and, importantly, to inform the development of more efficient, scalable, and affordable solutions to combat this widespread health challenge.

UKRI Gateway to Research · FY 2024 · 2024-08

The information for life is encoded in the DNA of the genes harboured in our chromosomes. The DNA in a chromosome is a very long chain consisting of four different nucleotides: G, A, C and T. For most genes this code is then converted into a messenger RNA intermediate (mRNA) that has a cap structure and a polyA tail to protect it from degradation. This mRNA is then translated in the cytoplasm into a chain of amino acids called proteins, which fulfil a function; for example an enzymatic reaction to generate energy from the nutrients we eat to allow for the electrical communication among neurons in our brain. Although the sequence of mRNA only consist of four nucleotides, many can be modified by addition of small chemical groups to increase the regulatory portfolio and coding capacity. The most prominent modification in mRNA are methyl groups added to the nucleotides adjacent to the cap structure. Animals including humans have two cap methyltransferase enzymes (CMTrs) that add these modifications. Also many parasites have a CMTr gene in their genome that is required for their propagation. In mice, CMTrs are essential and required for neuronal development, however, the biological functions of CMTrs and the mRNA cap modifications remain largely unexplained. We recently discovered that mutant Drosophila lacking both CMTrs are viable, although they suffer from neurological and learning defects. Intriguingly, we further discovered that in these mutant flies, mRNAs were not properly transported to synapses, which are the sites where signals are transmitted to neighbouring neurons. In particular, we could show that some mRNAs are only made into protein at synapses. Hence, the cap modifications have an essential role in directing the synthesis of new proteins locally at synapses suggesting that this process is required for learning of new associations, that are then stored as memory in the brain. However, we currently do not know which genes are expressed in this way at synapses nor what the sequence code is to direct mRNAs to synapses for localized expression. We now have the ideal animal model to address the very fundamental questions about how this enigmatic modifications direct local expression of genes to synapses. Our preliminary data indicate that the cap modifications vary between different animals and conditions. Since CMTrs also localize to synapses, our data suggest a dynamic code important for local protein synthesis. In a first step to crack this code, we will identify specific mRNAs that localize to synapses allowing us to build a reporter system to test the code. To complement this analysis we will further determine the sequence preferences of CMTrs in biochemical assays and identify proteins important for CMTr specificity and decoding of the cap modification code. These studies are essential to understand the vital function of the cap modifications in the regulation of gene expression and how its aberrant regulation can lead to neurological defects in humans, or can be exploited to interfere with viral replication such as in SARS-CoV-2.

UKRI Gateway to Research · FY 2024 · 2024-08

Among the many health challenges associated with ageing, degeneration of the soft tissue intervertebral discs (IVDs) in the spine is a primary feature of the ageing skeleton, contributing to pain and loss of mobility. However, we do not fully understand why age increases susceptibility to disc degeneration. The IVD separates our bony vertebraes and provides important cushioning and load-absorbing functions during regular daily cycles of activities. Recently, our group discovered functional 24-hour internal clocks in the IVD. This body clock becomes weakened and imprecise with age and its disruption through clock gene deletion leads to tissue damage and loss of characteristics of human IVD. This project aims to understand how our body clocks in the spine are regulated on a daily basis and why they weaken with age. We will establish how daily mechanical loading patterns of the spine due to physical activity keep the IVD clocks in synchrony with the rhythmic environment. We will also assess the importance of timing of exercise on spine health. Specifically, we will use a novel IVD "clockless" mouse model, treadmill exercise and cultures of cells and tissues to address the following questions: 1) Is the clock in the signalling centre of the IVD important for tissue health? 2) Do IVDs respond differently to mechanical loading depending on the time-of-day? 3) How mechanical loading keeps the IVD body clocks aligned with the external day/night cycle? This research builds on our recent novel discoveries and holds strong potential to advance our understanding of IVD circadian biology and promote tissue health against ageing. As such, there is an enormous potential for improving health and quality of life throughout our life course. Moreover, our findings emphasize the importance of exercise timing for better skeletal health, which will have a long-lasting impact on the health and well-being of the nation. This is particularly important because the greying of the population and the ever-increasing demands of our modern 24/7 society frequently disrupt our body clocks which can adversely impact on our health, wellbeing and productivity.

UKRI Gateway to Research · FY 2024 · 2024-08

Energy security and supply is of utmost importance in today's society and it is abundantly clear that nuclear fission will play an increasing critical role in delivering the net zero carbon agenda by 2050. A significant challenge for nuclear fission in the UK is its nuclear legacy, resulting from over 60 years of civil nuclear power generation and nuclear weapons production. This nuclear 'clean-up', including the decommissioning of legacy nuclear facilities and the long-term disposal of radioactive wastes, will cost upwards of £230bn and is a multi-generational project. To be able to progress safely, securely and efficiently with nuclear decommissioning and waste disposal, it is crucial to understand the underpinning chemistry of radionuclides within radioactive wastes. This project aims to deliver a step-change in fundamental understanding of uranium chemistry - a key component of radioactive waste management. Understanding uranium behaviour, e.g. uranium solubility and mobility, in engineered and natural environments is key to the safe decommissioning of legacy nuclear facilities and the long-term disposal of radioactive wastes. These systems are dynamic, with changes in chemistry likely to occur over the lifetimes of legacy nuclear and disposal facilities. It is therefore essential to understand how these changes in chemistry will impact on uranium behaviour in nuclear decommissioning and disposal scenarios including in deep geological disposal conditions. This fellowship will combine electrochemistry and advanced X-ray spectroscopies to investigate industrially and environmentally relevant reactions of uranium for the first time. Uranium behaviour is controlled by its oxidation state and the presence of complexing ligands, chemical species which are present in groundwaters and other solutions that come into contact with uranium-containing systems. These ligands can strongly bind uranium and stabilise solid- or solution-phase uranium species, significantly altering its behaviour. Changes in reduction/oxidation (redox) conditions can therefore have a significant impact on the behaviour of uranium and the chemical processes underlying these changes are not fully understood. These underlying chemical processes, or 'redox pathways', can control the eventual fate of uranium and the presence of different complexing ligands may significantly alter these redox pathways. Therefore, it is important to understand these fundamental processes to gain a holistic understanding of uranium chemistry and behaviour in dynamic systems where changes in redox and solution conditions may be expected. This fundamental understanding can then inform radioactive waste handling strategies and nuclear decommissioning approaches, promoting the safest and most efficient approaches to dealing with the nuclear legacy. In this fellowship, an electrochemical cell will be used to control the redox potential in experimental systems to change the oxidation state of uranium. Using a range of techniques, the changes in chemical bonding environment and oxidation state will be monitored during these reactions. The goal here is to produce controlled reactions whereby the changes in uranium chemistry at the molecular level can be probed during these key redox pathways, creating a step-change in the understanding of uranium redox chemistry in the presence of key complexing ligands. This analysis will be done using a multi-technique approach, measuring concentrations of uranium in solution and the chemical form of uranium in both the solid and solution phases. X-ray spectroscopy will be a key technique for analysing the chemical speciation, shedding new light on crucial reaction pathways occurring in these highly relevant systems.

UKRI Gateway to Research · FY 2024 · 2024-08

Radiotherapy is a type of cancer treatment using radiation. Every year, over 30,000 patients in the UK get this treatment for cancers in the pelvis, such as prostate, womb, bowel cancer. The good news is more people are surviving cancer because we are finding it early and treating it better. But there is a problem. Cancer treatments, including radiotherapy, cause long-term health problems, which can be tough on patients and the NHS. Sometimes radiotherapy damages people's bones making them crack or break. This condition is called Radiotherapy-Related Insufficiency Fractures (RRIFs) and usually happens between 3 months and 3 years after radiotherapy. RRIFs can be very painful, make it hard for people to move around and reduce the quality of life. We are not sure why RRIFs happen. We thought that radiotherapy causes osteoporosis (thinning of the bone) in the pelvis, making them easily breakable. However, I found that even people without bone thinning can get these fractures. Therefore, we need to dig deeper. To understand why bones break after radiation, we have to study bones that have been treated with radiotherapy. But taking samples from people is risky because their bones are fragile. So, we use mice for our studies. Mouse bones work a lot like human bones, so they are a good model for our tests. Previous studies have tested radiotherapy on long bones, like the thigh bone. However, the structure of the pelvis is very different, and I believe that radiotherapy may have different effects there. My early research showed this might be true. For this reason, I will study the impact of radiotherapy on the pelvis of mice in more detail. I will use a special machine that gives radiotherapy to mice in a similar way to that in humans. I will study the mouse bones at different times after treatment to see how they change and what makes them more fragile and prone to breaks. I will also check the effect of chemotherapy in addition to radiotherapy on bone, for the first time. My project has four main aims: 1. Check how bone structure changes after radiation 2. See how strong bones are after treatment 3. Count the cells that help to build or break down bone 4. Test the blood to measure bone health markers. This research will help us understand why these bone problems happen, and how to prevent and treat them effectively. As a result, people who get radiotherapy will have better health and quality of life and we will save hospitals time and money. For this project, I will work with experts in cancer and bone research from the Universities of Manchester and Sheffield. We have all the tools we need, and my supervisors are very experienced and committed to this research. Together, we hope to make a meaningful difference in how we understand and treat the long-term effects of cancer therapy. In addition to my research, I have developed a specialized training program that is tailored to my needs. This program is designed to help me advance my career and become a leading expert in studying the long-term side effects of cancer treatments on bones and hormones. Right now, there are not many specialists in this field, but the need for them is growing quickly due to the increasing number of these types of problems.

UKRI Gateway to Research · FY 2024 · 2024-08

Globalisation is a defining feature of the modern world. Over the past five centuries, international trade has driven economic development, restructured societies, and brought about the vast movement of goods, people and ideas. Yet, as recent de-coupling from China and conflict with Russia has shown, the globalised system can be fragile. Whereas the supremacy of unipolar 'western' institutional practices defined late twentieth century globalisation, the twenty-first century looks set to see international trade take place in a multipolar institutional context. Understanding the impact of these changes requires new ways of thinking about global institutional development: ones that recognises enduring, alternative institutional norms that have never fully been subsumed within 'western' practice. This raises important questions about how globalisation developed in the first place, as the traditional model of European imperial expansion imposing institutions on the world is unfit for purpose. We must ask instead why global actors adapted, adopted or opposed institutional transformation and how these processes shaped and reshaped what would become the common institutions of global international trade. To answer these questions, this project will use archives from across the world and an interdisciplinary methodology to deliver a global and intrinsically comparative analysis that will reveal globalisation's multipolar and adaptive institutional origins. Specifically, it will focus on institutional transformation between 1450 and 1750 in three vital nodes of the premodern world economy - the Gulf of Guinea, the Gulf of Khambhat, and the Straits of Malacca. By developing a systematic approach for analysing institutional transformation across linguistic, imperial and cultural boundaries, this project will integrate local and global analysis of premodern trade to challenge long held beliefs about the origins of capitalism, globalisation and European economic dominance.

UKRI Gateway to Research · FY 2024 · 2024-08

Rheumatoid arthritis is a long-term condition in which the immune system attacks the joints. It affects 1 in 100 people in the United Kingdom. This inflammation causes pain and, if uncontrolled, can lead to joint damage and disability. The earlier we can control the inflammation, the better the long-term outcomes. The development of biologic therapies means that we now have more options than ever before to treat rheumatoid arthritis. There are a number of types of these drugs, all affecting different immune pathways to try and reduce inflammation. We have no reliable way of predicting which type of biologic treatment will be most effective for an individual. Currently, selection is done by a process of trial and error with each new drug trialled for a period of time. During this time, if the drug does not work, a person may develop irreversible joint damage which could lead to permanent disability. The aim of this study is to see whether genetic and protein markers, identified using a blood sample, can be used to predict whether a person with rheumatoid arthritis is likely to respond to a certain treatment and inform us about the likely severity of their disease. These are known as biomarkers. This project will analyse data collected in MATURA (Maximising Therapeutic Utility in Rheumatoid Arthritis), a nationwide consortium of academics, doctors and industry groups developing personalised approaches to treatment of rheumatoid arthritis. When researching biomarkers of treatment response, it is really important to first establish what we consider a good response to be. One of the methods health professionals use in clinical practice is a scoring system known as the DAS-28 score. This score is made up of four components: number of tender joints, number of swollen joints, the patient global visual analogue score (a self-reported score from 0-100 of a patient's overall health) and CRP (C-reactive protein, a blood test which measures inflammation). Lots of factors can affect the tender joint count and patient global visual analogue score, such as presence of other joint conditions. This can result in a high DAS-28 score even though inflammation is well-controlled. As biologic drugs work by targeting inflammation, a switch in therapy would not provide additional benefit if there is no inflammation present. Research has shown that only "swollen joint count" and CRP are linked to levels of inflammation in the joints. For these reasons, a 2-component DAS-28 score would provide a better indication if these drugs are working. Adherence to therapy refers to whether patients take their medication as prescribed. For lots of reasons, including side effects, forgetting and having to stop therapy due to infections or planned operations, a patient may not take their biologic treatment as prescribed. We know that this impacts on the likelihood of treatment response. However, none of the studies to date looking for genetic and protein predictors has taken adherence to therapy into account. Taking these factors into account, I will identify the key genes and proteins involved in causing rheumatoid arthritis. I will then determine whether these factors can also tell us how likely one is to respond to medications, as well as how severe their disease is likely to be. This research will use new, cutting edge statistical techniques to narrow down the most important genes and proteins in both causing rheumatoid arthritis and those which influence the course of the disease. This research could enable a doctor to decide at disease onset which biologic drug is most likely to be effective for that individual. Ultimately, the goal is to use this work to develop a "biologics calculator", where we can use a blood sample to personalise therapy for each patient. It could also help us find new drug targets to help develop future medications.

UKRI Gateway to Research · FY 2024 · 2024-08

Bringing advanced computer vision to edge devices such as robots, consumer electronics, or sensor networks is challenging due to the constraints of power, size and communication bandwidth under which they often operate. We propose vertically integrated research into the paradigm of on-sensor computer vision, where sensing and processing are unified into single chip which produces abstract, information-rich output rather than images. We aim to demonstrate that on-sensor computer vision can be much more powerful and general than seen in previous research, and that the correct hardware design, software framework and algorithm choices permit switchable or even simultaneous computation of a broad set of vision competences (such as motion estimation, segmentation and scene classification) on a single device. We propose to work on the design of on-sensor computer vision systems through a programme of work from pixel-processing architecture design and microelectronic hardware implementation, through software platform development, to unified algorithm design and experimentation to determine how to use this hardware in a full application. This will enable camera devices that not only capture images, but have a powerful built-in vision capability to understand what they are looking at, and ultimately can go from light to decision on a single sensor/processor chip, with unprecedented speed, low power consumption and small footprint. We hope to open up a new class of edge applications where cameras can be much more efficient and independent, or for smart cameras to be used in ways never previously considered.

UKRI Gateway to Research · FY 2024 · 2024-08

Immune-mediated inflammatory diseases (IMIDs), which include diseases affecting the skin (psoriasis, eczema, and lupus) and joints (rheumatoid arthritis and lupus), lead to a substantial physical, psychosocial, and economic burden for up to 7% of people globally. New immunomodulators, which are medicines that change the immune system, have transformed the lives of people with IMIDs. These are mostly high-cost treatments that target proteins that control inflammation. Patients with IMIDs and their clinicians rely on evidence to guide their decisions to start an immunomodulator. This includes information from randomized controlled trials (RCTs), where an experimental drug is given randomly to a group of participants and another group of participants is given a comparator drug or dummy medicine; and observational studies, where large groups of people are observed in routine settings without active intervention, and these studies have complementary strengths and limitations. Observational studies are representative and large, but can be biased if not conducted robustly, at worst introducing patient harm. Conversely, RCTs are reliable but there is an under-representation of people from minority populations; it is therefore unclear from RCTs whether drugs work the same in these populations and this likely leads to an over-estimation of benefit and under-estimation of risk for the treatment overall. The aim of this fellowship is to use data from both RCTs and observational studies together to look for ways to make future studies better. Firstly, I will use results from RCTs, which often have high reliability, as a benchmark to conduct analyses of observational studies to evaluate treatment effects. I will do this by using data from IMID patient registries, which are studies that follow people with these conditions over time. By mimicking the design of RCTs in this data and using RCTs as a reference, I can understand if observational studies can give reliable estimate of treatment effect and identify situations where they should not be used. Secondly, I will test treatment effects in subgroups based on measured participant characteristics in both trial and observational data, e.g. male and female participants, giving me a much bigger sample than if I relied on one type of study. If I find that the treatment effect is different between the subgroups, and this is consistent in both the trial and observational data, these subgroup factors could then help stratify treatment for personalised clinical decision-making. Thirdly, I will use information about the UK patient population (for example the distribution between male and female patients) and "weight" the trial populations to mimic the UK patient population. This will help identify any differences in our overall understanding of the treatment outcomes if the trial was conducted in the UK patient population instead of the strictly controlled trial population. Fourthly, I will take the learnings from the analyses above and apply them to use registry data to predict the results from ongoing trials and test how closely our results can match the results from the RCT. This study will help us understand whether observational studies can produce reliable treatment effects in IMIDs; compare factors affecting treatment effects across different IMIDs; understand treatment effects in trial-excluded populations; and identify clinical subgroup effects that may help personalise treatment, leading to more efficient and appropriate use of high-cost immunomodulators to treat people suffering from a group of life-ruining conditions.

UKRI Gateway to Research · FY 2024 · 2024-08

Microbial communities inhabit almost all natural environments and perform a wide range of important natural processes. For example, microbial communities decompose organic matter and drive biogeochemical nitrogen and carbon cycles. Despite the critically important functions of microbial communities in ecosystems, our understanding of how these communities assemble and function is limited. This is in part because of the enormous diversity and complexity of such microbial communities, where a pinch of soil can contain thousands of species and billions of individual cells. To help us to understand this complexity we will build mathematical models to predict the assembly and stability of microbial communities. We will then test these models using controlled lab experiments with a simplified decomposer community; and finally, we will use our models to analyse the assembly of real-world microbial decomposer communities in the natural environment. Using this approach, we will answer three questions: First, how the individual interactions microbes have with each other determine the behaviour of the overall community they form together. Second, how variation in the environment (e.g. changes in temperature) affect this community level behaviour. And finally, how the functions that a microbial community performs together - for instance in the carbon or nitrogen cycles - can be predicted from genes that the individual microbes carry. Overall, our project will deliver a predictive understanding of how and why environmental microbial communities look and function as they do in nature, and thus enable better management of these critical components of natural ecosystems.

UKRI Gateway to Research · FY 2024 · 2024-08

DIGISURVOR is an innovative project that closely aligns with the ESRC's Digital Footprints Accelerator Scheme. It will provide vital knowledge that will enable a transformational shift in how digital trace data (DTD) - specifically individual-level browser and social media information - can be anonymized and linked to survey responses, thereby opening it up for ethically compliant secondary analysis. The project is interdisciplinary and brings together expertise from political science, social statistics and computer science. It will proceed in three main phases. Phase (1) proof of concept - where we demonstrate the feasibility of using computational methods to generate new attitudinal and behavioural variables from individuals' DTD that augment and enhance their survey data. This will be done through secondary analysis of existing datasets. Phase (2) proof of value - where we a) subject the newly generated variables to statistical robustness checks to diagnose and seek solutions to correct the potential problems of bias arising from the DTD data (e.g. device coverage, response rates); and b) open the new datasets up for trial analysis in a secure environment to investigate original research questions. Finally, phase (3) evaluation - will reflect on the results of steps 1 and 2 to develop a guide for researchers on how to produce both robust and ethically compliant linked DTD and survey data for open research. In carrying out this programme of work, DIGISURVOR will make a significant substantive, methodological and ethical contribution to the use of linked survey and DTD within academia and the wider survey research practitioner and user community. More generally, the project will contribute directly to furthering the ESRC Digital Footprints research agenda in terms of building the foundations for rigorous, ethical and societally relevant future research using DTD, and widening access to this new resource across the research community.

UKRI Gateway to Research · FY 2024 · 2024-08

One in three deaths are caused by cardiovascular disease (CVD), and three-quarters of early CVD could be prevented. To avoid untimely deaths, those at risk must be identified early to allow targeted preventative strategies. CVD risk is currently assessed using calculators based on health information and blood tests. The hypothesis driving this proposal is that the accuracy of these assessments can be enhanced using eye scans. The eye is the only part of the body where the nerves and blood vessels can be directly visualised. The appearance of these structures provides important insights into an individual's cardiovascular health. Two types of scans can be used on the eye: (1) photographs of the inner lining of the eye (the retina), known as fundus photographs, and (2) more detailed 3D scans of the eye known as 'optical coherence tomography' (OCT). Using these, almost every high street optometrist can now take low-cost, risk-free, sophisticated eye scans in just a few seconds. At present, eye scans do not form part of CVD risk assessment in primary care. The tool currently used is a questionnaire-style risk calculator which considers health and lifestyle information called "QRISK3". An emerging tool proposed as a future risk assessment solution is "polygenic scores". Polygenic scores are measures of disease risk based on genetic information, and these are currently being explored in research settings. Although it is known that eye scans can be used to predict CVD, it is not known how much more information they offer compared to these established and emerging tools. Furthermore, it is not clear why certain features in eye scans aid prediction of CVD, or if it will be possible to accurately predict CVD in patients who have eye disease. If these problems can be addressed, it is possible that eye scans could be used in the community to identify people in need of medical attention to prevent CVD. To address these problems, I have outlined three key objectives: 1. To explore why the presence of certain OCT/fundus photograph features predict CVD risk. 2. To measure the level of improvement to the accuracy of CVD predictions obtained by adding eye scan data to an established (QRISK3) and an emerging (polygenic score) risk tool. 3. To evaluate how well the developed tools function in people with common eye diseases and begin to address any effects on prediction accuracy. To perform my research, I will use health data from over 115,000 people available via biobanks and collaborators. I will begin by comprehensively studying what biological factors account for the role of known eye markers in CVD. Next, I will develop OCT plus fundus photograph-based CVD prediction tools using artificial intelligence. I will compare the accuracy of CVD predictions derived from QRISK3, polygenic scores, and an enhanced tool that incorporates OCT and fundus photographs. It is known that age-related macular degeneration (AMD) reduces the accuracy of risk assessments based on eye scans, so I will train my software to identify AMD from the images and mitigate this effect. Finally, I will test the accuracy of my software in two other common eye diseases, cataract and diabetic retinopathy, to assess how well my tool works in people with these problems. This work will represent progress toward cheap, accessible, accurate, opportunistic screening to identify those at risk of future CVD.

UKRI Gateway to Research · FY 2024 · 2024-07

During pregnancy, the placenta forms the physical connection between a mother and her baby. One of its jobs is to transfer food and oxygen from maternal to fetal blood so that the fetus can grow properly. The placenta must transfer the right amount of nutrients because too little can cause the baby to grow less well and be born smaller than it should be. Poor growth is a major problem: many small babies die or, if they do survive, they are more likely to be ill or disabled during childhood. There's also a life-long impact on health as these infants have an increased chance of being overweight and developing heart disease or diabetes as adults. One of the reasons the placenta might not work properly is when mum is overweight or is living with obesity. This is increasingly common in the UK with half of pregnant women having a body mass index in the overweight or obese range. This project is about helping these mums to have a better outcome for their babies by trying to find a treatment that will help the placenta do its job as it should. It's already known that fetal growth is better if expectant mums eat a diet rich in fruit and vegetables. We don't know exactly how the fruit and vegetables have this effect but one idea is that there is some component within fruits and vegetables that makes the placenta work better. Our previous work has tried to find out what this component might be because a treatment based on a natural product is a particularly good idea for pregnancy disease, where unanticipated side effects could have devastating consequences for both mum and/or baby. So far, our experiments have shown that very tiny particles from mashed-up watermelons can alter the way a laboratory model of the placenta works. We've also shown that when we give these watermelon particles to normal pregnant mice, the placenta grows better and produces more of the proteins needed to transfer nutrients from mum to fetus. We believe that the placenta is responding to messages from mum's gut as our preliminary investigations have shown that the watermelon particles alter the 'good' bacteria in mum's gut and reduce the number of harmful immune cells in the gut so that there is less inflammation. In this project, we will give these watermelon particles to pregnant mice that are obese and see how they affect the placenta and the growth of the pups. We will also look at how communication between the gut and the placenta is altered. Finally, we will see how the pathways in obese mice that are 'rescued' by treatment with watermelon particles map onto those known to be affected in women living with obesity to gauge whether a trial in pregnant women would be the logical next step. We expect that the data from all of these experiments will enable us to identify what links maternal diet to good placental growth and function. This will allow us to develop and eventually recommend, dietary changes based on fruit and vegetables that will help the placenta to work better in pregnancies at risk of poor fetal growth. In addition, we think that our data will be useful to other scientists working on plant-based therapies for other conditions such as cancer and cardiovascular disease. New ways to prevent babies from being born too small are desperately needed. Not only do fetal growth problems cause distress for individual families, but they also leave hospitals with expensive obstetric/neonatal care bills and the prospect of looking after adults with long-term health problems. Society is left with an adult population that will have a poorer quality of life; life expectancy continues to increase but we are not aging healthily as in addition to obesity, the incidence of diabetes and cardiovascular disease is also increasing. So unless we find ways to prevent these conditions, many of our extra years will be plagued by illness.

UKRI Gateway to Research · FY 2024 · 2024-07

My Future Leaders Fellowship has proven that analysing data in real-time before it is stored can increase the precision and reduce the costs associated with the enormous amounts of data produced by large-scale, cutting-edge science experiments. In my Fellowship continuation, I will apply the lessons learned in the first fellowship period to the future of Particle Physics experiments, where, in the quest to understand our universe, data rates are expected to be even larger. Traditionally, experiments have reconstructed particle collisions in 3D, providing an image of the collision which can be studied by analysts to look for new physics. As collisions become larger and more complicated, this reconstruction becomes increasingly challenging with current computing technologies. In my continuation I will add a fourth dimension, timing, to the real-time reconstruction of particle collisions in order to reduce this complexity and increase the precision to which we can probe the universe at the smallest scales. I will lead international R&D activities to study the way in which we process this data using commercially available technologies to ensure that future experiments can continue to process the wealth of data they are expected to produce.

UKRI Gateway to Research · FY 2024 · 2024-07

This project will develop an optimised robust continuous fermentation process for the bioproduction of succinic acid from crude biorefinery glycerol capitalising on previous successful BBSRC funding, with the aim to create a licensable technology, hence bridging the gap between bioscience and real-world impact. As such, it fully fits the scope of this call. Succinic acid is a platform chemical with a vast array of applications in the chemical, food and pharmaceutical industries. Its petroleum-derived chemical production from the hydrogenation of maleic anhydride suffers from low sustainability. Biochemical production routes for platform/commodity chemicals are gaining traction worldwide due to their inherent sustainability but are hampered by chronically low yields and productivities. Hence, optimisation and de-risking are critical for making bioprocessing economically viable and competitive with chemical production methods. Traditionally biochemical processes operate in batch or fed-batch mode incurring several challenges towards their profitable implementation such as: -The need for manual intervention to load/unload each batch, inevitably slowing down productivity, potentially compromising product quality through contamination. -Substrate and product inhibition, as accumulation of substrate and product(s) usually has an inhibitory effect on the bioprocess yields. -Difficult integration with, usually continuous. downstream processing (DSP) units, requiring the use of holding tanks and appropriate scheduling designs. Continuous bioprocessing can overcome these challenges as (i) continuous operations are inherently more/better automated (ii) substrate and product are continuously removed from the fermenter, diminishing their inhibitory effects and (iii) there is seamless integration with the continuous DSP units. Continuous fermentation of crude glycerol therefore offers a promising and sustainable bioproduction route for this highly important platform chemical. Importantly, crude glycerol is a viable carbon substrate as the main by-product of biodiesel production. It is not usually further processed by the biodiesel industry, so it has little (to zero) commercial value.

UKRI Gateway to Research · FY 2024 · 2024-07

"Sickness" is the response of animals and humans to illness and disease, to protect well-being and the functioning of vital organs. We and others have shown that the brain is responsible for the coordination of behaviour, metabolism and the immune system - though how it achieves this is largely unknown. Counterintuitively, when energy is required to fight disease, sickness results in a reduction of appetite, foraging, ingestion and digestion of food. This allows for recovery, reducing unnecessary energy expenditure and keeping the individual safe from possible harm while it is vulnerable. It also prevents further consumption of pathogens or poisons, which may have been the primary cause of illness. Instead, energy is partitioned away from movement and digestion to vital organs: glucose is required for the brain, while the heart, muscles, liver and kidneys increase the metabolism of fats. Furthermore, some of the drugs we take to combat disease will also make us feel sick; perhaps the most obvious example being cancer therapies. When cells become injured, they send out emergency signals, one of which is a messenger called GDF15. For example, GDF15 is secreted by cancer cells, but also by otherwise healthy tissues following cancer treatments. If fact, GDF15 is commonly released by most tissues if they are diseased or damaged. This project will examine how the brain coordinates each of the important sickness responses: nausea and vomiting, aversion and avoidance, digestive function and the partitioning of energy. In our work leading up to this project, we have characterised the only cells in the body that can respond directly to GDF15. They are brain cells (neurons) located in a very small and distinct region at the back of the brain. These neurons are the only cells that have the receptor for GDF15 - a kind "lock" that is the gateway to the rest of the brain. The GDF15 receptor is known as GFRAL. Thus, the gateway is formed by GFRAL neurons. We have now discovered that there may be at least three separate brain pathways downstream of GFRAL neurons which we hypothesise may mediate different facets of the sickness response. Already, we have strong evidence that one GFRAL pathway is responsible for the nausea and anorexia experienced by many people taking drugs to treat cancer or diabetes. In this new, ambitious proposal, we will examine precisely the different pathways that diverge from this important gateway into the brain to gain a full understanding of each of the key sickness responses. Thus, we will define three separate brain circuits that regulate appetite, digestion and metabolic adaption (including energy partitioning). The project is divided into these three overarching Objectives, which will utilise the most up-to-date neuroscience, genetic and behavioural approaches and train research staff in their use. The impact of the research will itself be multi-faceted. We will shed light on the brain circuitry that controls normal functioning in animals and humans, while identifying mechanisms which lead to pathological processes, such as nausea, vomiting, indigestion and even organ failure. This research is timely due to the increasing prevalence of chronic diseases (notably in older people) which are invariably associated with multiple morbidities and treated with drugs for which the mechanisms of action are not fully appreciated.

UKRI Gateway to Research · FY 2024 · 2024-07

Our elastic tissues such as skin, lungs and large diameter blood vessels contain string-like elastic fibres as part of their extracellular matrix. Fibrillin is an essential protein in elastic fibres and provides our tissues, such as the aorta - the major blood vessel from the heart - with elasticity. Symptoms of ageing are associated with a loss of elasticity, for example abdominal aortic aneurysm, hypertension and eye deterioration result from reduced levels of fibrillin. Fibrillin provides an essential link between the cell and its surroundings through its interactions with cell surface receptors termed integrins. This interaction allows the cells to feel the stiffness of the surrounding tissue and respond accordingly. Therefore, the interactions between fibrillin and integrins are crucial to maintaining normal tissue structure, elasticity and function. Altered interactions can also drive disease; for example, mutations in fibrillin give rise to genetic diseases with aortic aneurysms and skin stiffness. As well as providing our tissues with mechanical support, fibrillin also stores growth factors in connective tissues, which is needed for correct development, repair and maintenance of our tissues. These growth factors are activated by force, resulting from pulling between the cell and matrix, which involves fibrillin and integrin. Our limited knowledge of the structure of the complexes formed between fibrillin and integrin receptors presents a major obstacle to understanding their tissue sensing mechanism. The main aim of our work therefore is to deduce the structure of fibrillin-integrin complexes, which we believe will allow us to precisely locate the integrin binding regions and to understand how these regions work in synergy. We will use cryo-electron microscopy to determine the structure of fibrillin in complex with different integrins, to determine how interactions vary between integrin subtypes with different cellular functions. We will also compare the complexes formed with fibrillin to other integrin-binding ligands to understand any commonalities and structural differences. We will use our structural data to understand how changes in stiffness alter integrin binding by fibrillin and if this changes the signalling response. Given the importance of fibrillin microfibrils in the structure and maintenance of the aortic vessel wall, we believe that understanding these molecular details will prove essential in understanding how they perform their "mechanosensing" function and could enable the future design of fibrillin-specific integrin inhibitors as potential therapeutics for vascular pathology. Understanding these molecular events for maintaining aortic health could have significant health and economic benefits to the UK. Stiffening of the blood vessels and valves of the heart are major causes of heart disease, which affects more than 6 million citizens in Europe each year. Heart disease has a huge economic impact, due to the high medical costs and work disability. Our research findings could be of future interest to the pharmaceutical industry in developing treatments to maintain the elasticity of these tissues. Effective treatment would significantly improve the quality of life of an ageing population.

UKRI Gateway to Research · FY 2024 · 2024-07

"Early career research staff, commonly known as Postdocs, are vital to the success of research and innovation in UK universities. They deliver the research funded by grants and ensure research is of maximum benefit to society. Postdocs plan, carry out, and analyse a wide range of research across all subject areas; share findings through research papers, research conferences, media and public engagement events. They are also crucial to the wider activity in universities, developing knowledge and research skills of students. All this whilst navigating short-term contracts and career uncertainties, despite being highly trained, and the majority educated to PhD level. Without postdocs we would not have research impact, but their hard work often goes under the radar. The initiative in this nomination, ‘Postdoc Appreciation Week’ (PAW), is about raising awareness and celebrating the contribution this community makes to university life and wider society. However, whether a postdoc gets celebrated is highly dependent on their institutional funding, and whether they have circumstances that preclude participation. Therefore, the UK National Postdoc Appreciation Week (UKNPAW) flagship event, an online, free and recorded event, was created to ensure all postdocs, regardless of their background, personal circumstances, employment, etc.,gets to enjoy an uplifting event that is also useful. It helps researchers recognise their valuable contribution, and raises awareness amongst other groups, including university staff and students. Since 2020, around 1000 postdocs have attended these events live; recordings created as watch-on-demand resources for researchers who missed the live events also attracted over 840 views."

UKRI Gateway to Research · FY 2024 · 2024-06

This CDT will focus on challenging aspects of developing, deploying and assessing AI and data-driven solutions for semi or complete automation of real-world systems. Such systems usually involve several decision-making agents, including humans, and typically require coordinating hundreds to thousands of decisions. The CDT will specialise in training a new generation of AI researchers with the theoretical and practical skills to develop and test new machine learning models and approaches that can efficiently cope with uncertainty in complex systems. The CDT understands systems in a broader sense, including multi-agent systems in robotics, supply chain management and team sports, to systems in scientific domains such as astronomy and molecular biology. A consortium between the University of Manchester and the University of Cambridge will lead the CDT. It will bring together researchers in machine learning with a strong track record in developing methodologies and applying these to real-world data and domain scientists with a strong track record of data-driven learning. The consortium has significant experience in the type of translational AI research that is at the core of the CDTs vision. The team is a balanced mix of AI experts, from Turing World-Leading Researcher Fellows to early-career rising stars, domain experts from selected fields of science, decision scientists, and a diverse set of companies. The priority area for the CDT will be Science and Research, starting with three fields of research, physics/astronomy, engineering biology and materials science -- and generalising the solutions to decision-making broadly in complex systems. We will train the students with the relevant knowledge and skills such that the CDT will also contribute to AI for increasing business productivity as a cross-cutting theme. PhD projects will be co-created between AI specialists and domain experts. During their first year, students will receive foundational training in AI and ML, relevant training in the specific field of research related to the student's project, and research training through individual and group projects. From the second year and throughout their programme, students will have access to a wider training experience in entrepreneurship and public engagement. At the same time, students will engage in cohort training activities, including journal clubs and a yearly conference. Furthermore, students will benefit from the strong institutional support around Responsible Research and Innovation and Equality, Diversion and Inclusion, already in place at both Universities.