University College London

UKRI Gateway to Research · FY 2025 · 2025-01

The Optical and Acoustic imaging for Surgical and Interventional Sciences (OASIS) Hub aims to improve our ability to detect the earliest signs of cancer and improve surgical visualisation to optimise tumour resection. Our vision is to establish a vibrant world-leading ecosystem of scientific and industrial innovators to advance the clinical state-of-the-art in optical and acoustic imaging hardware and software. Each year in the UK ~375,000 people are diagnosed with cancer and >50% will receive a surgical intervention, yet our conventional imaging tools are limited to replicating human vision. Our reliance on human eyesight is limited by poor contrast for cancer, which leads to high miss rates in surveillance and diagnosis, then incomplete resection and propensity for recurrence in surgery. There is a critical unmet need for improved cancer visualisation, which if met could impact over a million procedures annually in UK and tens of millions worldwide. Optical and acoustic imaging tools are uniquely able to provide low-cost, portable, high contrast, visualisation of disease in miniature medical device systems. We focus on three core challenges: enhancing contrast for tumour visualisation; enabling depth resolution for tumour staging; and providing multi-resolution multi-modal information to overcome the limitations of standalone technologies without adding burden to clinical workflow. To maximise the potential of optical and acoustic imaging tools through the OASIS Hub, we propose the following five objectives: O1: Develop new minimally invasive devices that augment current standard-of-care using optical, acoustic and photoacoustic tissue interactions, by unifying the disparate UK research community in a hub and spokes model where spokes are engaged through pump-priming, training events and workshops. O2: Establish infrastructure for single- and multi-centre clinical trials specialising in imaging devices, from feasibility towards Phase I, building on the leadership teams’ track record of first-in-human optical and acoustic devices and standards development. Developing the first structured, annotated clinical datasets from emerging imaging modalities across diverse populations that span domains of variation representative for clinical needs. O3: Create an engaged ecosystem of academic, industry, public and NHS hospital partnerships to accelerate technology development and translation. Capitalising on our >20 industrial partners, from UK SMEs to global strategics with significant UK presence, and the vibrant UK investment community to finance new ventures. O4: Cultivate a portfolio of public and patient involvement and engagement (PPIE) that fosters dialogue and promotes co-creation of solutions optimised for clinical translation, considering accessibility and explainability of quantitative optical and acoustic imaging biomarkers. O5: Provide a portfolio of high-quality training in an inclusive environment to equip future leaders with multidisciplinary, translational and entrepreneurial mindsets to catalyse new research and spin-offs. These objectives demand the partnerships enabled by OASIS, uniting academic and clinical teams to interface with industrial partners and investors, and to co-create solutions with patients and the public. We have engaged a vibrant industrial ecosystem from UK SMEs to global strategics, generating excitement for our vision that has led to contributions to training activities, co-sponsorship of projects and PhD students, advice on regulatory processes, joint standards development, hosting of internships, among others. Our investment in training will maximise opportunities for PPIE through funds for innovation and novel approaches to science communication. Our flagship programme will co-create new technological capabilities to catalyse sustained impact on the NHS by providing more information-rich, less invasive interventions that are accessible to the UK population and beyond.

UKRI Gateway to Research · FY 2025 · 2025-01

While humanity has faced countless Environmental Health Crises (EHC) throughout its history, in recent times such crises have increased rapidly not only in their occurrence and intensity but also in their global spread and consequences. Developing humanities-based strategies to better understand EHC and to identify and raise human responsibilities that lead to individual and societal actions to mitigate the destructive repercussions of these crises is, therefore, of critical importance at present. Current approaches to creating public understanding of such crises, however, stem from disparate disciplines and fields of concern. As such, these approaches on their own are unable to deal with the divisive prevalent narratives and evolving representations of the complex multidisciplinary nature of EHC. CHRYSES will take an interdisciplinary approach to creating a more common understanding of EHC by bringing together the perspectives provided by humanities and science using the medium of maps, as a physical and metaphysical representation form for journeys across space and time. We will investigate the interplay between myths and science in the ways our societies conceptualise and represent EHC, and utilise maps to unify the corresponding perspectives and approaches of myths and science to foster better public understanding of such global crises. To achieve this, CHRYSES will focus on four objectives: 1) investigate the uses of the concepts of maps and journeys in ancient and modern mythology to narrate and represent EHC, 2) investigate the role of maps as a scientific tool to visualise, analyse, understand, and explain EHC, 3) investigate the role of maps in visual narratives as a metaphor and storytelling medium for unifying mythical and scientific approaches and perspectives on EHC, and 4) develop strategies for creating better public understanding of EHC through more effective societal engagement of the public and other stakeholders by combining myths and science.      

UKRI Gateway to Research · FY 2025 · 2025-01

Aim: To develop a treatment for patients with Duchenne Muscular Dystrophy (DMD), a genetic disease marked by muscle wasting and death in early adulthood, due to mutations in a protein called dystrophin. Unmet Need: Gene therapy has been developed for DMD, where shortened forms of dystrophin, called microdystrophins, are delivered to patient muscle via gene therapy. The use of shortened dystrophins is required due to constraints on the capacity of gene delivery technologies. However, clinical trials have revealed that these shortened microdystrophins can elicit damaging immune responses in some patients and the stability of dystrophin in muscle is compromised. As such, approximately 10% of all DMD patients are now excluded from receiving microdystrophin gene therapy. Our solution: We have identified a specific region of all microdystrophins used clinically to date, which is likely to be the cause of immune responses. We have identified this region via a combination of molecular analyses and computational biology, which enabled us to design new versions of microdystrophin which lack this feature and therefore can circumvent the safety issue. We are currently screening a batch of new microdystrophins in early preclinical research, with plans to progress a lead candidate to clinical trial. Objectives Validate microystrophin constructs with optimal functionality in DMD patient myotubes in vitro (months 0-3): We will demonstrate the functionality and stability of optimised microdystrophins lacking the immunogenic region in DMD patient cells containing N-terminal deletions in vitro, to identify those with the greatest stability and functionality in the cells representing the target patient population. Demonstrate safety and efficacy of microdystrophin constructs in a DMD mouse model in vivo (months 3-18): We will progress the most promising new microdystrophins to in vivo studies in 'mdx' mice which are a standard preclinical model for testing DMD gene therapies. We will identify a construct that shows optimal localisation and stability in muscle fibres without eliciting toxicity. Demonstrate lack of immunogenicity of microdystrophin constructs in dystrophin-null mice (months 3-16): An important motivation in our study is to avoid immune responses that affect existing microdystrophin gene therapies. We will validate avoidance of this aspect with our optimised microdystrophins, using a mouse model lacking the dystrophin gene locus, as these mice will not inherently recognise dystrophin hinge-1 as self, similar to patients with N-terminal deletions lacking hinge-1 coding sequence.

UKRI Gateway to Research · FY 2025 · 2025-01

This proposal is bringing together R&I related staff by a complementary set of participating organisations that will use multidisciplinary technological approaches to provide a proof-of concept framework for designing and introducing greener practices in pharmaceuticals. Knowledge will be transferred around the core technical activity that will be the introduction of HME as a novel production method, based on AI-ML tools and supported by environmental assessment for greener pharmaceuticals.

UKRI Gateway to Research · FY 2024 · 2024-12

This proposal is for refurbishment and expansion of the core equipment used to provide the UKRI NRF in XPS (The National XPS Service also known as HarwellXPS). Our NRF serves academic and industry scientists who need to analyse the surface of a material. This is especially important for research into materials, semiconductors, catalysts, engineering, medical devices, as well as being useful for fundamental scientific study of physical phenomena at surfaces, which underpins a large number of technologies. We will use the funding to the extend the range of services we are able to offer, mainly though expanding the sample types that we can accept, and the conditions we can measure under. This allows our service to be used by a wider range of scientific disciplines, helping towards one of our key goals which is to diversify our user base. We will also invest to save by refurbishing existing equipment to keep it running in the most efficient, sustainable and productive way.

UKRI Gateway to Research · FY 2024 · 2024-12

The National Dark Fibre Facility (NDFF) is the UK National Research Facility that provides a UK communications network research infrastructure that can be shared between researchers across different communities, supporting research on the underpinning communications technologies for the future internet. NDFF can be directly accessed at the physical layer (OSI Layer 1), enabling experiments at all network layers to be carried out with unprecedented flexibility and control. Its two main categories of Users are: 1) Researchers that require a dedicated infrastructure slice (hardware, software or both), undisturbed for long periods of time e.g. performing disruptive long haul optical transport research; 2) Researchers that can use a shared infrastructure (hardware, software or both) slice, on time sharing or soft scheduling basis e.g. performing research on protocols or high-performance computing. To meet the needs of both categories of Users, NDFF provides secure, multi-layer, flexible and repeatable infrastructure slicing enabled by the unique connectivity topology of NDFF, programmable and sliceable network elements, flexible optical transport technologies and flexible interfaces, as well as powerful and flexible experiment lifecycle management and integration with the existing 5G UK Exchange multi-layer network service brokering mechanism and the developing JOINER Layer 2 network and control plane. NDFF includes some 1,300km of single mode optical fibre linking University College London (UCL) with the Universities of Bristol, Cambridge, Southampton and Surrey, with the National Physical Laboratory (NPL) and with major co-location sites, including Telehouse North, Harbour Exchange, Reading and the Layer-2 5G UK Exchange at Slough. NDFF also includes a small-scale dark fibre Metropolitan Area Network (MAN) in Cambridge and a connection to a separately funded metro network in Bristol. NDFF will interconnect with the JOINER Layer 2 network at UCL, Universities of Bristol, Cambridge and Southampton enabling access for researchers throughout the UK via Layer-2 connections. The Facility includes software configurable switching, amplification, dispersion compensation and filtering and is a pioneering example of a software defined optical network. The NDFF User community includes researchers on wireless and optical communications, quantum communications, time and frequency distribution, immersive and virtual reality, sensing and metrology, THz transmission, and software defined networking. With the increasing reliance on electronic communications infrastructure NDFF provides a vital training resource at doctoral and post-doctoral level in the skills required to create the communications networks of the future. In order to carry out their experiments on NDFF Users require access to advanced optical and radio frequency test and measurement equipment so that they can confirm correct operation of their experimental transmission equipment, set desired launch and modulation parameters and determine the transmission performance of their experiment. The objective of this application is to provide new and upgraded test and measurement capabilities for our Users.

UKRI Gateway to Research · FY 2024 · 2024-12

This is a proposal for investment in equipment to benefit researchers in at least 20 UCL centres and departments across six faculties. It will support researchers with cutting-edge equipment to progress UCL's vision to transform how the world is understood, how knowledge is created and shared and the way that global problems are solved. Across the portfolio of equipment requested the items fulfil the EPSRC objectives of "benefit multiple users in one or more departments", “invest to save activities"; and “providing demonstrable benefit to early career researcher and doctoral training activities”. Governance of the Core Equipment funding is provided by grant holder Professor Geraint Rees, UCL Vice-Provost (Research, Innovation and Global Engagement), and through relevant UCL Faculty structures. The requested UCL equipment items are: Item A: Transformative high-resolution 3D prototyping: beyond photonics and proof of concept; Item B: Immersive VR Lab Upgrade; Item C: Customized probing system for the characterization of electronic devices in controlled atmosphere and temperature; Item D: Oligonucleotide Synthesis Capacity at UCL; Item E: Ultrafast fluorescence lifetime spectrometer. The Project Co-Leads are academics and research technical professionals acting as leads for each requested item, and will be responsible for managing the equipment locally, ensuring that benefits are realised and progress made against the objectives of the EPSRC call. Benefits will be realised in areas such as: Sustainable Manufacturing, Engineering for Healthcare, and Microfluidics (Item A); Virtual Reality and Mixed Reality Systems (Item B); Neuromorphic Devices,  Semiconductor Nanostructures, and Silicon-based Integrated Optoelectronics (Item C); Synthetic Biology and Biochemical Engineering (Item D); Design of New Materials, Imaging Tools and Green Chemistry (Item E).

UKRI Gateway to Research · FY 2024 · 2024-11

Metabolic imaging of the human brain provides valuable insights into brain function and crucial information for treatment planning and monitoring, especially in brain tumours and neurodegenerative diseases. The clinical standard for metabolic imaging is positron emission tomography (PET).  However, PET requires the use of radioactive tracers which target only one specific metabolite at a time. Instead, more detailed metabolic information, from multiple metabolites simultaneously, can be obtained using magnetic resonance spectroscopic imaging (MRSI) without radioactive tracers. However, MRSI’s use is limited clinically, because it currently only targets well-localised, focal pathologies, restricting our ability to analyse metabolic patterns in diffuse pathologies or those with unknown localisation. To overcome this limitation, our international collaborator Dr. Hangel from the Medical University of Vienna, has developed Magnetic Resonance Spectroscopic Imaging (MRSI) with whole-brain coverage, PET-comparable spatial resolution, and a clinically feasible measurement time of 15 minutes. This method has proven its robustness in both healthy and clinical cohorts, but only in Vienna. This project will bring this advanced technology to the United Kingdom in order to enable cutting edge metabolic imaging in clinical research at the University College London, King’s College London, the University of Oxford, and the University of Cambridge. To enable this, the project will harmonise the acquisition, quality management, processing and analysis of outputs of this MRSI method across all sites. This project will perform the essential groundwork to enable future multi-centre clinical studies that address unmet needs for the resolution of metabolic patterns in diseases in clinical research and allow our institutions to participate in global research efforts to unlock the clinical potential of metabolic neuroimaging. MRSI leverages the increased sensitivity, spectral resolution, and signal-to-noise ratio of 7 Tesla MRI compared to lower field strengths and relies on a series of technical innovations made by Dr Hangel and his team over the past decade. MRSI shows great potential for international deployment, especially since 7 Tesla MRI scanners were clinically certified in 2017 and are becoming more widely available (7 in UK, more than 150 worldwide) After the study, all four participating UK research centres will be fully capable of performing advanced MRSI. In addition, a unique dataset, consisting of normative, whole-brain metabolic data from the same twenty healthy volunteers on all systems will have been acquired. This dataset will enable us to determine the robustness of the MRSI approach, and establish the variability of neurometabolic concentration measurements between scanners. It will also become a shared resource for community-driven processing, e.g. exploiting machine learning developments. This project is uniquely possible in the UK, the four Southern England 7T MRI sites are the closest, well-connected by public transport, same-vendor MRI scanners worldwide, facilitating easier coordination of research participant scans. These facilities are all close to hospitals and world-leading clinical research centres, providing direct connections to clinical collaborators and patient cohorts. A multi-site harmonisation of 7T MRSI is crucial for future multi-site studies of brain pathology and has not been attempted anywhere in the world so far. With this foundation, we can conduct advanced studies of pathologies such as brain tumours, epilepsy and neurodegenerative diseases or unravel the workings of the healthy human brain better than before and remain at the forefront of global neuroscientific research. A first multi-site study could be the resolution of glioma infiltration into healthy tissues under treatment.

UKRI Gateway to Research · FY 2024 · 2024-11

The problem. Epilepsy is a common brain condition, affecting 65 million people around the world(1). About 20-30% of patients are misdiagnosed with epilepsy, leading to unnecessary treatments with potential side effects, including psychological issues (2),  and, conversely, an epilepsy diagnosis is often overlooked or delayed, leading to significant morbidities, including injury and death. Currently, the gold standard technique for diagnosing epilepsy is ictal video- electroencephalogram (EEG), rarely  accessible in medical emergency settings and ineffective if not used during an attack. Together with resolving uncertainties in diagnosis, another related unmet need is the unpredictability of seizure onset, representing a huge risk for patient safety with a considerable emotional burden. The solution. Profiling of volatile organic compounds (VOCs) in exhaled breath is an attractive biomarker approach that is gaining traction in the scientific, medical and pharma communities both for diagnostic and also for prognostic aims. VOC-based tests are non-invasive and quick, making them very acceptable to patients even when performed in acute situations(3). VOC analysis emerges as an ideal strategy as their release relies on metabolic processes and not electrophysiological signals. Rationale. The potential role of volatile compounds in seizures has already been evidenced by the ability of seizure-alert dogs to warn their owners of an impending seizure up to 50 minutes in advance(4). Studies suggest this ability is based on scent only, as dogs can distinguish between sweat samples collected from individuals at rest, after physical activity or after seizures (5). We undertook a first observational trial (VIBES) aimed at identifying seizure-associated VOCs. Breath samples were collected before and after seizures, at different time points, and then analysed with state-of-the-art mass spectrometry techniques. The study protocols were well accepted by patients, carers, and hospital staff. Our results suggest that there are several volatile molecules potentially associated with the occurrence of seizures. We also identified a panel of compounds increasing in patients experiencing a seizure within 24 hours, in accordance with anecdotal reports. The gap These observations need validating in a new patient and control group, to confirm their specificity and accuracy and predict seizures correctly and reliably. This would unlock the next phase of device development. Aims. In this work, we aim to Validate the diagnostic breath-VOCs profile for people with epilepsy and  non-epileptic (psychogenic) attacks and healthy volunteers. Validate the predictive breath VOCs profile for people with epilepsy. Carrying on this work will unlock the product development phase for a diagnostic and prognostic tool. Objectives. Validation of a breath test for the diagnosis of epilepsy and another one for seizure prediction. Identification of minimum viable product characteristics for the development of portable devices. Potential applications and patient benefits. An accurate and timely epilepsy diagnosis can lead to effective therapies, offering immediate relief for individuals and their families. Seizure prediction could also offer a better quality of life, and increased patient safety and independence. Plan of the research. Recruitment of a new cohort of people with epilepsy affected by different types of epilepsy and healthy volunteers (50 and 25) for the validation of hit biomarkers. Collection of breath VOC samples before and after seizures. Analyse samples with state-of-the-art mass spectrometry techniques, such as gas chromatography time-of-flight mass spectrometry. Scrutinise and interpret the data using advanced computational tools.

UKRI Gateway to Research · FY 2024 · 2024-09

Our project aims to build capacity in the skills required by researchers to access and use data effectively, with the ultimate aim of increasing the quantity and quality of world-leading research undertaken for public benefit. We will support researchers to use a substantial new piece of data infrastructure – the Integrated Data Service (IDS) – and to understand and process one of the main sources of data available via IDS: education administrative data. Our work will support current and prospective new users to overcome the ‘skill bar’ to utilise these vital data infrastructures effectively. Access to administrative data is tightly controlled. These restrictions are necessary to ensure the rights of individuals are appropriately protected, but also act as a barrier for researchers to access the data, which may limit the amount and quality of research undertaken for public benefit, one of the main justifications for it being shared. The secure environments through which these datasets are shared are also undergoing a period of significant change, moving from a standard server-based system using one set of software, to the cloud-based IDS using a completely different range. For many researchers, this will represent a seismic change to their day-to-day research activities, necessitating a substantial upskilling of existing and new users of these services. Some of the most widely used datasets for which users will face this change are the education administrative data owned by the Department for Education (DfE), the backbone of which is the National Pupil Database (NPD), containing the school records of millions of pupils in England. The NPD has been linked to a range of other administrative and survey datasets, including the Longitudinal Education Outcomes (LEO) data and ECHILD, to create invaluable resources for research purposes. This means supporting users of these datasets in particular to transition to IDS – and building capacity to access and use these large and complex datasets more generally – will contribute significantly to broadening and deepening skills amongst the UK research community. We will achieve our aims by: providing training in the new software available in IDS; providing training in the contents and use of NPD, LEO and ECHILD, including where these datasets are linked to the UK’s rich array of survey datasets; enhancing guidance materials and sharing code to support the use of NPD, LEO and ECHILD; complementing existing plans for NPD and LEO to create ‘low fidelity’ synthetic (mock) data for ECHILD which replicates the structure and format of the data, and supplementing this with ‘high fidelity’ synthetic data subsets for NPD, LEO and ECHILD which replicate some of the relationships between variables; we will also share code to facilitate the creation of synthetic versions of other datasets; providing training in appropriate statistical methods for analysis of such data. Our proposal will contribute to the realisation of UKRI’s vision by providing resources to support the use of data within trusted research environments, thus accelerating the benefit of these infrastructures and the resources stored within them. Through the creation of synthetic data, it will reduce unnecessary access to personal data and help maintain public trust and confidence in the use of data. It will additionally develop skills and facilitate career progress by enabling more researchers to successfully access and use new data infrastructure resources, including new software, datasets and methods.

UKRI Gateway to Research · FY 2024 · 2024-09

This proposal is in response to the invitation received by Professor Mark Wilkinson, Director of STFC’s DiRAC High Performance Computing Facility, to bid to the UKRI Call: ‘Digital Infrastructure: New Approaches to Skills or Software’. The original invitation to bid was sent to e-mail address miw6@leicester.ac.uk. With the environmental impact of large data centres an increasing concern, every opportunity to push towards a reduced carbon footprint by improving workload efficiency and energy footprint reduction must be exploited.  The goal of achieving maximum scientific benefit from the resources provisioned, whilst minimizing both the total resources required and the accompanying environmental impact, applies across all computational areas in the UKRI ecosystem. The hardware platform chosen to run scientific codes can have a significant impact on performance: whilst GPUs may demand more power to operate, performance speedups can result in an overall energy advantage of between 2 and 5 times over CPU-centric workloads. Whilst there is no one-size-fits-all solution and the best choice of hardware depends on the specific application, in general GPUs offer higher scalability than CPUs for parallel tasks that require higher throughput and lower latency, and their improved performance can reduce energy use for the same or better science output. Recent work by DiRAC has also demonstrated that careful tuning of the system settings can also have a positive effect on the energy budget, with little negative impact on code performance and time-to-results.  The need to encourage computational researchers to adopt accelerator hardware, and to optimise system settings for energy efficiency, has led us to propose a novel approach to delivering Performance Portability Training that will help to both fully leverage the scientific benefit of GPUs and reduce our infrastructure’s carbon footprint. Using our technical, academic and industrial contacts, DiRAC will assemble a team of leading specialists with the knowledge and experience to define and develop a series of on-line lectures demonstrating how to harness hardware performance by using techniques such as optimum code structure,  algorithm design and energy profiling (WP1 & 2).  The learning will be reinforced by a series of code “deep-dives” where experts from DiRAC Project Teams who have already optimised their codes for GPUs will highlight and practically demonstrate the strengths and weaknesses of their refactoring approaches (WP3). These code deep-dives will be extended to the IRIS and ALC communities in the last year of the programme to foster knowledge exchange and enhance opportunities for collaboration (WP4). Drawing on our extensive experience of presenting hackathon-style training events, we will also hold two in-person five-day workshops with the aim of reinforcing the learning with practical applications (WP5). All lecture material will be delivered self-paced on DiRAC’s established Training Platform and will be enhanced via the development of a customized chatbot assistant to improve engagement through personalise learning (WP6). By trialling this new multi-faceted approach to providing training on code refactoring and hardware optimization, we will showcase its immense value to other communities, such as Biomedical Science, Condensed Matter and Materials Science, and Fusion, in the long term enabling researchers from across UKRI to fully leverage cutting-edge technologies.

UKRI Gateway to Research · FY 2024 · 2024-09

CLOSER is a unique research centre that works to increase the visibility, use and impact of United Kingdom (UK) social and biomedical longitudinal population studies (LPS) data and research, in strategic partnership with LPS teams and data services. Founded in 2012, CLOSER’s team of specialists serve the biomedical and social science communities, providing a suite of core services and resources to connect LPS studies and their users and enabling LPS data and research to drive forward an evidence informed society. In the UK, there are at least 65 LPS [1] mainly funded by the Economic and Social Research Council (ESRC), Medical Research Council (MRC), Wellcome Trust, and UK Government.   In the period 2024 to 2028, CLOSER will continue to deliver its core services of data discoverability, knowledge exchange, education and training, and policy engagement. These services will be strengthened based on over a decade of experience and will be continually tailored towards the evolving landscape of LPS users including researchers, professional research services staff, non-profit organisations, parliamentary staff, civil servants, charities, and think tanks. Through its international networks, CLOSER will continue to craft a space wherein CLOSER is highly visible on the global stage, bringing further opportunities for external funding and impact.   During 2024 to 2028, CLOSER will contribute to Population Research UK (PRUK) through representation on the PRUK management team and by collaborating with LPS organisations and users across the UK. In doing so, CLOSER will connect and strengthen the LPS landscape in the PRUK spoke areas of data discoverability, cross-community activities, and capacity building.   CLOSER will support the ESRC’s Data Infrastructure Strategy using its strategic position in the landscape and status as a centre of excellence for providing LPS resources. By continuing to provide high quality, state-of-the-art resources in collaboration with other LPS organisations, data and research infrastructures and informed by user experience, CLOSER will help improve academic and professional skills and capacity for data use, and will engage, lead, and connect LPS users and organisations. Accordingly, CLOSER will help the ESRC build and sustain the foundation for LPS data infrastructure in the UK.

UKRI Gateway to Research · FY 2024 · 2024-08

Context Biodiversity is unevenly distributed over the surface of the Earth. Extremely high numbers of species are found within small geographic regions, known as ‘biodiversity hotspots’. Today, global marine biodiversity is concentrated in the Indo-Australian Archipelago, where many groups reach their greatest species richness. However, the fossil record suggests that the spatial distribution of marine biodiversity hotspots has changed through time, with the existence of at least four different hotspots throughout the Cenozoic recognised. The challenge the project addresses Considerable research effort and resources have been dedicated to delineating the present-day Indo-Australian Archipelago marine biodiversity hotspot and testing the processes that govern it. However, the evolutionary history and drivers of Cenozoic marine biodiversity hotspots is vastly understudied in comparison. This knowledge gap prevents an understanding of the full life-cycle of biodiversity hotspots, from initial emergence and maintenance to ultimate decline. In order to truly understand the general mechanisms governing marine biodiversity hotspots, we must first consider and compare the evolutionary history of all Cenozoic marine biodiversity hotspots. By doing so, we can begin to test macroecological and macroevolutionary hypotheses across multiple biodiversity hotspots to identify general ‘laws’ governing their existence. Fortunately, the palaeontological record provides a wealth of data which enables the study of Cenozoic marine biodiversity hotspots. This project will use the rich fossil record of stony corals (Scleractinia) to address this knowledge gap by reconstructing diversity dynamics and diversification rates for Cenozoic marine biodiversity hotspots and testing their drivers within a spatially-explicit mechanistic framework. To do so, this project will take advantage of recent advances in Earth System modelling (i.e. palaeoclimatic modelling) and computational biology (i.e. spatially-explicit mechanistic models), which have provided the necessary tools, to test longstanding hypotheses on the drivers of marine biodiversity hotspots. Aims and objectives This project aims to advance understanding of Cenozoic marine biodiversity hotspots by combining fossil occurrence data with a suite of novel and interdisciplinary tools. The objectives of this project are to: (1) develop the first comprehensive and standardised dataset of Cenozoic marine biodiversity hotspots; (2) reconstruct temporal diversity dynamics for Cenozoic marine biodiversity hotspots; (3) reconstruct diversification rates for Cenozoic marine biodiversity hotspots; (4) test the drivers of hotspot diversity dynamics within a spatially-explicit mechanistic framework; and (5) fill temporal and spatial data gaps in our record of Cenozoic marine biodiversity hotspots. Potential applications and benefits As part of this project, a new and comprehensive dataset of Cenozoic reef corals will be built, novel high-resolution palaeoclimatic data and palaeogeographic reconstruction will be produced, and interdisciplinary state-of-the-art approaches will be implemented. This project will be the first to holistically apply such methods and data to disentangle the macroecological and macroevolutionary history of Cenozoic marine biodiversity hotspots, and their potential drivers. The data produced from this project (e.g. palaeoclimatic data) will be assimilated into an open-access online database. This will ensure that these resources are available for the wider research community to test hypotheses related to the co-evolution of life and climate throughout the Cenozoic. Finally, the proposed project will generate major advancements in our understanding of marine biodiversity hotspots in the past, present, and future, as well as their potential drivers. Through understanding and testing the drivers of Cenozoic marine biodiversity hotspots, predictions can be made about additional biodiversity hotspots throughout geological time, and potentially under projected global climatic conditions.

UKRI Gateway to Research · FY 2024 · 2024-08

Note: invitation to apply was sent to Igor Tkalec, the project lead, on Tue 6/18/2024 4:56 PM. The project proposes to imbue researchers with skills in data storytelling, which is a data communication approach whereby the interaction of narratives, data insights and supporting visuals renders data more digestible and provokes a call to action. It is proven as an accessible and engaging pathway to improved research communication and impact. An integrated series of face-to-face workshops and online materials will enable researchers at any career stage to present data-intensive research in new and compelling ways. The materials will be grounded in ESRC Digital Research Infrastructure (DRI). The workshop programme will be delivered through the interdisciplinary and Integrated Smart Data Research Service (ISDRS) which has supported 200 research publications over the last 10 years. Core to the value proposition is extension of research skills beyond purely technical training to thematic deployment of graphical and statistical outputs that drive data stories. These will enliven active communication and dialogue between researchers and stakeholders beyond academia (such as policymakers) and thus empower researchers to reach new audiences for their work. The narratives of data stories will both frame and enable policy applications by providing evidence for decision making and building research impact. The project addresses the skills gap as UKRI DRI strategic priority/theme. The vision is to establish data storytelling as a mainstream approach to the communication of data insight and to accelerate adoption of DRI through associated developments in data service provision. The project entails four skill-oriented objectives. We will: Provide in-person data storytelling training to 400+ all-career-stage researchers. Publish five open-source data storytelling roadmaps that supplement the workshops and allow re-use and development by DRI providers and users. Demonstrate to 300+ all-career-stage researchers how programmatic approaches (Python) enhance the delivery of data stories. Develop two open-source data storytelling addenda that enable continuous professional development for those who engaged with Objective 3. The core recurring workshops will offer (a) a conceptual introduction to data stories and training in their development and (b) the skills to enhance data story narratives with training in using interactive solutions (e.g., widgets, dashboards) with Python. Each workshop type will be repeated nine times throughout the funding period at multiple UK venues. Seven sets of supplementary materials will support story development and writing and guide learners how to craft data stories from machine learning and visually enhance them by using text-to-image (AI) software tools. The project will bake in contributions from policy practitioners on data communication, tailored to provisions of specific ESRC DRI investments in order to target workshop content. To this end, workshops will feature a representative of existing ESRC DRI who will frame worked examples and case study demonstrations.

Fonds de recherche du Québec – Société et culture · FY 2023-2024 · 2023-04

Volet: Grands défis de société - Science et Société; Domaine: S.O.

Fonds de recherche du Québec – Santé · FY 2023-2024 · 2023-04

Volet: Formation en recherche post-diplôme professionnel (fellowship); Domaine: Vieillissement; Objet: Maladies neurodégénératives; Objet: Maladies cardiovasculaires; Application: Sciences et technologies; Application: Fondements et avancement des connaissances; Mots-clés: OPHTALMOLOGIE, OCULOMIQUE, IA, MALADIES CARDIOVASCULAIRES, MALADIES NEURODEGENERATIVES , IMAGERIE RETINIENNE