NIHRDataInsights/HRCSData huggingface dataset:
Title: Fine-Scale Regulation of Notch Signalling Dynamics: in the Context of Vertebrate Segmentation Clock
Funder: Medical Research Council

Abstract: Notch is a major pathway regulating development. Abberant Notch signalling leads to developmental defects, congenital abnormalities and cancer. Notch signalling is highly conserved and essential for embryonic development. When activated the Notch receptor is cleaved releasing the intracellular domain (NICD), which moves to the nucleus and regulates gene expression. NICD is highly labile and its turnover restricts Notch signalling. Despite the importance of NICD turnover in development/disease, the molecular details remain uncharacterised. Notch is crucial for somitogenesis the periodicity of which is regulated by a molecular oscillator which drives oscillatory gene expression within the presomitic mesoderm (PSM) from which somites are derived. CDK-regulated NICD stability affects the clock period which in turn affects somite size. The overall objective is to identify the molecular mechanism regulating Notch signalling strength and duration and the in vivo significance using somitogenesis as a paradigm. Aims: 1)Investigate mechanisms regulating Notch signal duration in vitro. Use HEK293, ES, iPS cells, mass spectrometry and biochemistry to identify NICD interacting partners, NICD phosphorylation sites and kinases involved in phosphorylation-dependent proteosomal degradation of NICD. 2)Generate a quantitative model describing how Notch signal duration coordinates patterning during somitogenesis. Use a reporter mouse to quantitate the effect of specific kinase inhibitors in perturbing NICD turnover in real time (e.g. amplitude, frequency of oscillations). Generate an inducible conditional mouse mutant in which the phosphosite regulating NICD degradation is rendered non-phosphorylatable. Determine how this affects i) NICD turnover ii) oscillatory dynamics. 3)Define the mechanisms through which Notch functions through global transcriptomic/proteomic analyses of the Notch programme in ES or iPS-derived PSM/ NMPs. Functionally test selected hits.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Investigating the mechanisms for building the embryonic body plan: harnessing a paradigm for cell differentiation
Funder: Medical Research Council

Abstract: The mechanisms by which the embryo lays down its body plan, and in particular, constructs the tissues along its AP axis, are fundamental to our understanding of biology. They are also crucial to understanding of in vitro differentiation of pluripotent cells. During AP axis development, populations of progenitors are found in the posterior end of the embryo, These include neuromesodermal progenitors (NMPs), stem cell-like progenitors that produce both more NMPs as well as the spinal cord and musculoskeleton in a head-to-tail sequence. However, their gene expression normally changes over time. Despite successfully producing functional NMPs from pluripotent mouse and human cells, these are a heterogeneous mixture of early and mid-stage progenitors. We plan to explore the significance of temporal change in NMPs, first by defining in vitro conditions that promote NMPs of early, middle and late identities, then by inducing differentiation from each progenitor type and defining the in vitro phenotype of cells. Functional cell types will be explored by grafting to cultured embryos. This addresses an important question in regenerative medicine: how similar do cell types need to be to functionally integrate in a tissue? A second fundamental question in developmental biology that is also crucial for developing in vitro differentiation protocols is: how do cells commit to given cellular identities? We will investigate this issue by first defining at single cell level the plasticity of cell types in the epiblast and region containing NMPs. Using transcriptomic comparisons between cells at specific regions where plasticity is known we will identify candidate factors governing plasticity versus commitment. One such factor is Oct4, which also changes prospective late axial identity towards an early/mid-stage, and using DamID-seq technology we will investigate differential targets in NMPs versus subregions of the epiblast.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: MICA: InterdisciPlInary Collaboration for efficienT and effective Use of clinical images in big data health care RESearch: PICTURES
Funder: Medical Research Council

Abstract: The core programme focuses on 3 key areas: (1) Complex cohort building from noisy, heterogeneous data: we will develop algorithms for text mining and standardising imaging metadata. We will use machine learning classification techniques to group images and natural language processing to pre-process and mine knowledge features from the free-text data and remove the identifiable data. We will utilise imaging processing algorithms to search for features within the core dataset to build new cohorts based upon pixel data. (2) Scaling and handling big data: we will develop algorithms and optimisation processes for handling petabytes of imaging data and investigate how to optimise the use of GPUs within a virtual environment. (3) Cybersecurity: we will ensure that our systems are secure but also meet the requirements of the research community. Exemplar 1: Using CT scans provisioned from the national resource, we will use Deep Learning to train an algorithm to detect lung nodules and coronary artery calcification. The algorithm will be implemented as a Medical Device and made available within NHS Clinical PACS reporting workstations for Clinical performance evaluation and validation. To determine the risk of lung cancer and cardiovascular events we will use the nationally available longitudinal health outcomes data linked to the results from the CT scans. Exemplar 2: To develop a risk score for dementia and an understanding of which data is most important for prediction, we will use voxel based feature selection and support vector machines within a cross-validation framework for MRI brain images. Non-imaging analyses will be primarily cross-sectional and longitudinal including time variable exposure clinical covariates as well as genomic covariates. Risk predictions using image, genetics and clinical data for individual patients will be combined using decision tree methods to create a best overall predictor. Algorithm validation will use the national resource.


Research activity codes: 8.5 RESOURCES AND INFRASTRUCTURE (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: UK Consortium for MetAbolic Phenotyping (MAP UK)
Funder: Medical Research Council

Abstract: The overarching goal of the partnership will be to develop, optimise, transfer, harmonise and validate efficient, high-quality research and training methods, specifically tailored to the growing need of high quality biomedical studies that require metabolic phenotyping. We propose to: i) conduct a comprehensive review of current capabilities and the requirements of the epidemiology community in relation to assays, computational workflows in collaboration with the epidemiology community in the UK and globally; ii) conduct a comprehensive assessment of compatibility and complementarity of analytical methods (including untargeted profiling and targeted quantitative methods), workflows and data processing pipelines and establish best practice; iii) develop untargeted method characterisation databases and novel targeted quantitative methods and protocols to meet gaps in molecular coverage of key disease-related pathways; iv) create a system for protocol and information exchange; v) develop a framework for Method harmonization, and coordination of results and databases; vi) validate the NMR-MS integrated analysis pipeline for comprehensive coverage of the metabolome in clinically-relevant cohorts; vii) improve capacity building and application of metabolic phenotyping in epidemiology through training, education and outreach. We envision this will create a core UK capability for delivering high quality metabolic phenotyping data to academics, clinicians and industry to serve the emerging priority area of population phenotyping. Ultimately this UK partnership will provide the network, tools and expertise to improve understanding of lifetime disease risks, provide a framework for making collective decisions for future disease and healthcare roadmaps and inform future global public health policies.


Research activity codes: 2.4 SURVEILLANCE AND DISTRIBUTION
Health categories: GENERIC HEALTH RELEVANCE
Title: Population-level imaging, genomic and phenotypic analyses to determine how bone marrow adiposity impacts human health
Funder: Medical Research Council

Abstract: Bone marrow adipose tissue (BMAT) accounts for up to 70% of total bone marrow volume and 10% of total fat mass in healthy humans. BMAT further increases with ageing and in diverse clinical conditions, such as osteoporosis, obesity, type 2 diabetes and radiotherapy. Unlike other adipose depots, BMAT also increases in states of caloric restriction, including anorexia nervosa. Thus, BMAT is a major feature of normal anatomy; is distinct to other types of adipose tissue; and is altered in many clinical contexts. However, study of BMAT has been extremely limited, and therefore how BMAT impacts human health and disease remains to be established. This proposal will fill in this critical gap in knowledge by leveraging the power of the UK Biobank (UKBB). Magnetic resonance imaging (MRI) is emerging as a key tool to measure BMAT, but this has never been done on a population level. UKBB is now MRI scanning 100,000 of its participants; hence, using this data, Objective 1 is to measure BMAT of each participant by developing machine learning-based algorithms for automated MRI analysis. Establishing these new automated MRI analysis tools will yield extensive academic, clinical and commercial benefits. Objective 2 is to use GWAS and PheWAS to identify genetic and phenotypic factors associated with altered BMAT. No previous MRI study has analysed BMAT in more than 600 subjects; hence, our population-level BMAT analysis will provide unprecedented power to identify these associations. Finally, Objective 3 is to use Mendelian randomisation in UKBB and other large-scale cohorts to determine if SNPs associated with altered BMAT are causally linked to physiological and pathological outcomes. This will reveal if BMAT directly influences physiological traits and/or the aetiology of diverse diseases. In summary, this work will yield cutting-edge approaches for automated MRI analysis while revealing fundamental new knowledge about the impact of BMAT on human health and disease.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.4 SURVEILLANCE AND DISTRIBUTION
Health categories: GENERIC HEALTH RELEVANCE
Title: Migration, gender and health system responses in South Africa: A focus on the movement of healthcare users and workers
Funder: Medical Research Council

Abstract: This research project is situated in the field of health policy and systems research and develops a novel analysis to understand better how gendered aspects of migration and mobility affect the health system, drawing on a case study of health workers and patients in South Africa. It specifically examines the complex interactions of migration, gender and health systems taking an intersectionality approach. Research will analyse the movement of patients out of and into the public health system in South Africa, through novel investigation of existing data sets and generation of new quantitative and qualitative data by tracking mobile healthcare users over time using the social media application whatsapp. Applying this highly innovative approach, we will develop new understanding in the field of health systems, including methodological approaches to researching migration and mobility, and to applying intersectionality and gender as a lens in health systems research. This builds directly on the work by Gilson and Sheikh conceptualising the health system as consisting of software and hardware aspects, and especially Gilson's work that has highlighted how the complex and 'messy' interactions between people - patients and providers - shape the health system. Moreover, the research proposed takes forward the work by the RiNGs Consortium which has developed a framework for integrating a gender perspective into health systems work, and drawing on the field of intersectionality by Hankivsky, examines specifically the intersection between gender, migration and health system. It thus applies some of the most exciting theoretical approaches and frameworks in health systems to some of the most pressing issues.


Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: GENERIC HEALTH RELEVANCE
Title: Trials Methodology Research Partnership
Funder: Medical Research Council

Abstract: Clinical trials provide the highest quality of information about new health interventions. They require large financial, patient and healthcare system resources to be successful. It is a priority for medical research that methodology for increasing the efficiency of clinical trials is developed. In this Trials Methodology Research Partnership we propose to bring together several networks and institutions that have strong expertise in particular areas of trials research. The partnership will consist of an executive committee that will oversee eight working groups, each working in a distinct priority area for trials. Funding will be used to coordinate the partnership and its working groups. The partnership will also provide funding for several smaller research projects, which are linked with three priority areas for future trials research: stratified medicine, health informatics and global health. The initial projects are: 1) a review of methodology gaps for which future trials research is needed to help stratify patients better; 2) collation of ongoing studies followed by a workshop to bring together expertise in health informatics; a prioritization exercise to design Studies Within A Trial (SWATs) that could be embedded within future trials to build an evidence base for best use of digital technology in trials; 3) a pump-priming funding stream to enable international collaboration between researchers from resource-poor countries and those based in UK and Ireland, to encourage methodology research for global health trials. The partnership will also create a national cohort of PhD students who will work on clinical trials methodology, and continue support for successful initiatives such as the International Clinical Trials Methodology Conference and online guidance packs for best trial practice. The initial investment in this Partnership will lead to future proposals for larger, focused research projects that will make future trials more efficient.


Research activity codes: 6.9 RESOURCES AND INFRASTRUCTURE (TREATMENT EVALUATION);8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: HOD2: Data driven semi-automated approaches to comparative effectiveness research using electronic health record data
Funder: Medical Research Council

Abstract: Propensity score methods are often used to assess treatment effects in electronic health record (EHR) data, but enthusiasm has waned amid prominent examples providing misleading results. Traditional propensity score analysis relies on investigators selecting confounding variables to be included in the model. EHR contain a wealth of data, in the form of codes (prescriptions, diagnoses, etc.); these data may collectively contain important confounding information, which could help remove bias apparently due to unmeasured confounding. How best to incorporate information from thousands of codes remains unclear. Data-driven approaches such as the high dimensional propensity score (HDPS) offer a semi-automated algorithm for selecting relevant codes to include in the propensity score model. The HDPS relies on a relatively crude algorithm, based on marginal associations of codes with the exposure and outcome. Other, more sophisticated, approaches are likely to provide superior inference. A key aspect of our proposed work seeks to identify the optimal way of selecting which codes to include in the analysis, exploring various data-driven approaches that have been proposed in this context. This work will also explore optimal methods for handling missing data. Data-driven approaches can be perceived as a "black box", reducing the investigator's ability to understand the data and therefore to fully consider potential biases, leading to a lack of confidence in the results. Therefore, we propose to develop a suite of visual diagnostics to provide intuition about the key drivers of the results in a clinically interpretable way. Through the dissemination strategy outlined elsewhere, our research will enable practitioners to obtain robust estimates of comparative effectiveness, in a timely and cost-effective manner, while also having the tools to fully understand the results of these analyses.


Research activity codes: 6.1 PHARMACEUTICALS;7.4 RESOURCES AND INFRASTRUCTURE (DISEASE MANAGEMENT)
Health categories: GENERIC HEALTH RELEVANCE
Title: MRC Centre for Environment and Health
Funder: Medical Research Council

Abstract: We propose to focus our research efforts on three ubiquitous environmental challenges: air pollution, noise pollution and non-ionising radiation. We will study these exposures at the population, individual and molecular levels, taking a systems approach to understand the influence of the environment on disease development, progression and exacerbation. We will focus on the influence of urban environments on health, exploiting developments in i) low-cost environmental sensor technologies that will improve individual exposure assessment at scale; ii) comprehensive assessment of biological signatures through omic technologies applied to our cohorts; iii) remote sensing (including satellites) and other data sources that capture the complexity of human interactions with the city environment; iv) multi-dimensional approaches to data integration and analysis. To further a causal understanding of the effects of environmental contaminants on health, we will investigate the pathophysiological pathways and accompanying mechanisms behind such effects using omic technologies, cell cultures and model organisms. We will combine high-resolution locational data (space, time), experimental data, biomarker and mechanistic studies, and analyses of large cohorts, using advanced exposure modelling and hierarchical statistical techniques. To address the high computational and data analytic needs, we will link to Health Data Research (HDR) UK (both Imperial and King's are part of the HDR UK London substantive site), and utilise and further advance developments in computational biology and bioinformatics. Such advances are essential to better understand the mode of action and toxic properties of a range of environmental contaminants, and help identify individuals at greatest risk. The results of our research will inform the design and implementation of policies to control, as necessary, and reduce the population disease burden from environmental hazards.


Research activity codes: 2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: GENERIC HEALTH RELEVANCE
Title: Elucidating the molecular basis of nucleotide sugar transport in health and disease.
Funder: Medical Research Council

Abstract: This project builds on the technical expertise of the Newstead group on studying the structural and functional basis of transport across cellular membranes. In particular the application of recent developments in eukaryotic expression systems, lipid-based crystallisation and nanobody technology have enabled the advancement of the study of eukaryotic transporters. We will use in house expression systems to produce milligram amounts of human, fungal and parasitic nucleotide sugar transporters. Using our cubic phase crystallisation platform, we will screen these proteins for x-ray crystallisation providing insight into the molecular basis for ligand recognition. Crystals of the CMP-sialic acid transporter have already been grown and diffract to medium resolution. We will experimentally phase this new structure using heavy atom and long wavelength methods. Further biophysical characterisation of ligand binding and the role of specific residues identified through the structural approaches will be validated through the use of differential scanning fluorimetry, nanoDSF. Facilitating the structural and functional studies we will generate libraries of single chain antibodies, nanobodies to both native and conformationally locked variants. Insights into lipid specificity will be gained through the study of reconstituted protein in defined lipid environments and monitoring transport through the use of radioactive nucleotide-sugar derivatives. Identification of specific lipids binding events will be facilitated through the use of native mass spectrometry including an analysis of lipid mediated dimerization.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Towards a molecular, mechanistic, understanding of bacterial type three secretion
Funder: Medical Research Council

Abstract: We seek to determine the structures of mechanistically informative sub-complexes of the entire type 3 secretion machinery in functionally informative states to design mechanistic hypotheses to be tested in vivo. We will use a combination of high resolution single particle cryo-EM and X-ray crystallographic studies as our main structural methodologies. These methodologies are well established in the lab as demonstrated by the prior publications and preliminary data supporting this application. Many of the protein complexes to be studied are integral membrane complexes and we will study these either in detergent or SMA peptide extracted forms and image in either detergent micelles or lipid nanodiscs with our choices of extraction and purification regimes guided by native mass spectrometry to characterise complex composition, heterogeneity and stability. This approach was crucial to our recently determined structure of the export gate complex that provides the strong start point for further studies designed to understanding the process of substrate selection and gating. Specific initial targets are founded on strong preliminary data that suggest these are likely to be tractable over the five year timescale requested and include: 1. Structure of a FliPQRB complex at a resolution sufficient to allow us to build the structure of the unknown N-terminal portion of B and gain insight into this critical component. 2. Structure of full-length FlhA as found in vivo either by determining the structure of the nonameric complex or by determination of the structure of the monomer and modelling of the nonamer into existing tomographic data 3. Structure of the C-ring/pod-ATPase complexes by determination of structures of sub-complexes of the full assembly and modelling into tomographic data of the full assembly. 4. Structures of the Mot complexes that power flagellar rotation using ion-flow 5. Structures of the non-flagellar host-cell pore


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: GENERIC HEALTH RELEVANCE