NIHRDataInsights/HRCSData huggingface dataset:
Title: Language Processing for Literature Based Discovery in Medicine
Funder: Engineering and Physical Sciences Research Council

Abstract: The amount of published material in biomedicine has been growing exponentially in recent years, particularly in very productive areas, such as genomics. The knowledge it contains is now so vast and fragmented that it is no longer possible for any individual or research group to keep up with the advances relevant to their area. The research literature is also fragmented and researchers naturally concentrate their attention on their own area of expertise, meaning they may not identify research that is relevant to their own if it does not appear within the literature of their scientific discipline. However, medical research is becoming increasingly interdisciplinary with progress being made by combining outputs from various fields. Hidden knowledge occurs when a connection can be inferred by combining information from multiple documents, but that connection has not been noticed. Literature Based Discovery (LBD) provides tools that analyse the research literature to identify hidden knowledge automatically. Connections it has been used to identify include treatments for diseases (e.g. that fish oil can be used to treat Raynaud's syndrome) and cases of diseases (e.g. that migraines can be related to magnesium deficiency). Despite these successes, the knowledge that has been discovered has been limited by the relatively simple techniques used to analyse the research literature. This project will develop new approaches to LBD by applying recent advances in the automatic processing of biomedical literature. This analysis will provide a LBD system with more detailed and accurate information about this literature than has previously been possible. In particular, the project will make use of two language processing technologies, Information Extraction and Word Sense Disambiguation, which can now be applied to the biomedical literature on a large scale. Information Extraction will be used to identify connections between items mentioned in documents and will provide more accurate analysis than the simple techniques used by previous LBD systems Word Sense Disambiguation will be used to avoid the problems caused by polysemy and synonymy (the suggestion of spurious connections and connections being missed) which can adversely effect LBD performance. The project will implement a LBD system and test it on two domains: oncology and neuroscience. The effectiveness of the system will be judged by researchers working in these areas with interests in melanoma and Parkinson's disease.


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR
Title: Functions and therapeutic potential of vascular Orai/CRAC channels
Funder: Medical Research Council

Abstract: We have obtained data suggesting importance and therapeutic potential of the recently-discovered Orai proteins and associated CRAC channels in angiogenesis, vascular remodelling and endothelium-dependent relaxation. We have also identified a chemical blocker of the mechanism that has nanomolar potency, strong specificity and approximately 100-fold selectivity for the vascular compared with immune CRAC channel. We propose a project that will test the significance of these findings and the relevance to tumour vasculature and therapeutics. Specific aims of the project include: (i) To generate in vivo conditional disruption of Orai in the mouse to investigate its roles in growth factor-evoked angiogenesis, vascular tone and remodelling in response to injury; (ii) To investigate Orai/CRAC channel function and expression in colonic endothelial cells and endothelial cells from colorectal tumours and associated liver metastases; and (iii) To further explore and develop pharmacological approaches for manipulation of the mechanism, including investigation of chemical blockade, antibody inhibitors and lentiviral delivery of DNA-encoded Orai inhibitor. Through this work we hope to significantly enhance knowledge of Orais in the vasculature and determine whether Orais provide an attractive foundation for developing therapeutic agents that could be used to address problems of colorectal cancer and other important human diseases.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;5.1 PHARMACEUTICALS
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR
Title: Precision Drug Theraputics: Risk Prediction in Pharmacoepidemiology
Funder: Medical Research Council

Abstract: The project will develop statistical and machine learning algorithms to analyse NHS datasets to build predictive models to support precision therapeutics focusing on the following two areas: 1) Cancer chemotherapy 2) Cardiovascular therapies HDR UK will provide the data repositories for linkage of established patient cohorts to further phenotypic resources. This will provide deeper phenotyping and should allow more precise prediction algorithms to be developed. Advanced statistical modelling (logistic regression, least absolute shrinkage and selection operator (LASSO) regression, Bayesian modelling) and machine learning approaches (neural nets, deep learning algorithms) will be used as part of this approach. The precision and incremental value of additional datasets will be assessed as will automated approaches to optimising algorithms. Existing research in the use of Bayesian hierarchical point-mass models, based around body-systems, to detect safety signals in clinical trials may be extended for use in observational studies. This approach is designed to use the additional information given by the relationships within and between body-systems in a statistical analysis. The outcomes of the project, in this case the prediction models, will be translated into Clinical Decision Support (CDS) tools which will promote learning health systems. User and usability experience data will be captured during CDS design and development. The output will be a prototype intervention suitable for evaluation through the MRC Complex Intervention Framework to support clinicians in making informed choices and highlighting the risks in the different possible prescribing choices.


Research activity codes: 4.5 RESOURCES AND INFRASTRUCTURE (DETECTION)
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR
Title: Leucine-rich alpha-2-glycoprotein 1 (Lrg1) as a novel modulator of TGFbeta signalling in disease
Funder: Medical Research Council

Abstract: The objectives of this research are to gain insight into the cellular and molecular mechanisms that mediate the regulatory effects of Lrg1 on TGFbeta signalling. The interconnected cell systems in which we will perform the research are vascular endothelial cells, cancer cells and cells of the immune system. In preliminary work we have used surface plasmon resonance (Biacore) to demonstrate a direct interaction between Lrg1 and Endoglin, and here will develop this approach to establish the binding parameters and hierarchy of binding of Lrg1 to other endothelial receptors including TbRII and ALK5. We will use mutagenesis to define the binding domains on both Lrg1 and its targets, with expression of mutants both as recombinant proteins for biophysical studies, and in cell culture models for functional studies. We will investigate the effects of Lrg1 on both canonical and non-canonical TGFbeta signalling, and also explore possible interactions between Lrg1 and signalling via bone morphogenetic proteins and their receptors. Studies at the cellular level will be complemented by experiments using in vitro, ex vivo and in vivo models of angiogenesis. We will also investigate the role of Lrg1 as a modulator of TGFbeta signalling in cancer by using a range of tumour cell lines that vary in their expression of Lrg1, TGFbeta and Endoglin. We will manipulate Lrg1 expression in these cell lines in order to determine the consequences on proliferation, signal transduction and tumour cell characteristics such as anchorage-independent growth and migration. We will extend this work into animal models of tumorigenesis using the RIP-TAG mouse, tumour cell grafting and metastasis, and direct tumour induction in control and Lrg1 KO mice. Since Lrg1 also impacts on cells of the immune system we will investigate leukocyte infiltration of tumours, and follow up preliminary data in which we have shown that Lrg1 modulates lymphocyte and macrophage phenotype.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR
Title: Over three years to investigate the relationships between sleep, obesity, technology use and academic performance in a sample of contemporary UK adolescents – a prospective cohort study.
Funder: Action Medical Research

Abstract: Obesity has become a major public health problem. The condition is now affecting children and we know that this will have serious consequences for their health and wellbeing. An estimated 17 per cent of boys and 15 per cent of girls in the UK aged between 2 and 15 are classified as being obese. Around 30 per cent of children are either overweight or obese in the UK and many of these cases will continue into adulthood. Obesity is associated with other conditions such as heart disease, diabetes, breathing disorders, some cancers, infertility, arthritis, depression and can seriously affect an individual’s physical and mental wellbeing. There is a major need to understand factors that contribute to obesity so that this serious condition can be prevented and treated effectively. While obesity occurs as a result of eating too much high calorie food and reduced physical activity, we don’t understand all the factors that increase food intake or affect activity levels. Several studies have shown that children who actually have shorter sleep duration tend to be obese. There is a need to examine this relationship further in children in a modern setting who are at risk of both obesity and sleep deprivation. This research will involve Year 7 children in schools in the Midlands over a period of three years. The team will assess their sleep, activity, use of technology and academic performance. They want to determine how sleep is related to obesity and what factors could influence this relationship. The study should help decide if sleep should be taken more seriously to improve the health of adolescents. Understanding this relationship could allow us to give better advice and treatment, and to help prevent obesity in children.


Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR
Title: An experimental study into the effect of radiation and electromagnetic interference upon cardiac devices and leads implanted in cancer patients receiving external beam radiotherapy.
Funder: Tenovus Cancer Care

Abstract: With an ageing population, the number of cancer patients fitted with cardiac devices (pacemakers / implantable cardioverter defibrillators) and being treated with radiotherapy is increasing. Over the past three decades the use of complementary metal-oxide semiconductor circuitry in devices has increased, these are more sensitive to radiation and electromagnetic interference. Whilst most medical treatments pose little danger, radiotherapy has the potential to cause malfunction. This may be temporary and changeable; however, consequences can be serious and permanent, as electrical breakdown in the device may result in failure of the cardiac conduction system of the heart and ultimately patient death. It is not possible to predict the exact behaviour of a pacemaker when it is within, or close to, the radiotherapy treatment field. Published literature based on research from 1994 is inconsistent in its findings or recommendations, with conflicting information regarding the safe levels of radiation dose delivered to a device. There are no UK guidelines for the use of radiotherapy in cancer patients fitted with cardiac devices, policies (where in place) in UK radiotherapy departments are based on old evidence and do not take into account subsequent advances in device technology. Working in conjunction with pacemaker manufacturers and Cardiff University, we will undertake a series of experiments in the radiotherapy department at Velindre Cancer Centre, to determine the effects of radiation and electromagnetic interference upon cardiac devices. The results will be used to produce UK guidelines on the safe use of radiotherapy for cancer patients fitted with a cardiac device.


Research activity codes: 5.5 RADIOTHERAPY AND OTHER NON-INVASIVE THERAPIES
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR
Title: Evaluation and Qualification of Non-Invasive MRI Biomarkers Associated with Platelet-Derived Growth Factor (PDGF) Signalling In Vivo.
Funder: Wellcome Trust

Abstract: The process of new blood vessel development, angiogenesis, is essential for tumour growth. The final steps of angiogenesis involves the recruitment of a particular cell type, pericytes, to blood vessels, stimulated by secretion of a growth factor called platelet-derived growth factor (PDGF), providing a scaffold for more complete, ordered and mature blood vessels to develop, and enabling a tumour to grow and spread. The extent of mature blood vessels influences the sensitivity of tumours to therapy. The blood supply of tumours is chaotic, and delivering drugs through such a network to all tumour cells challenging. Furthermore, secretion of PDGF can increase the pressure exerted on patent blood vessels, furthering hindering drug delivery through them. Novel therapeutic strategies are being developed to target PDGF. The development of these strategies requires methods to assess the status of mature blood vessels and their subsequent response in a tumour in situ. This proposal is concerned with the use of magnetic resonance imaging, from which images of tumour blood vasculature can be obtained in vivo completely non-invasively, to evaluate the degree and responsiveness of mature blood vessels. The aim is to identify clinically translatable MRI-derived measurements associated with PDGF to help individualized patient treatment approaches.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR
Title: Statistical Genomics and the Analysis of High Dimensional Data
Funder: Medical Research Council

Abstract: Motivated by important biomedical collaborations, the broad aim of this programme is to enrich the statistical toolkit that is commonly used in genomics analyses by developing and implementing new analytical strategies for integrative and translational `omics’ as well as for the analysis of single cell data. The core of the proposed models and inference will be embedded within state of the art statistical developments in Bayesian modelling and computations, although analogous penalised approaches will also be investigated and compared to Bayesian implementations. We will focus on modelling and computational strategies where the multidimensional (e.g. complex multiple-phenotype) and multivariate aspects (many explanatory features) of complex data sets are investigated and exploited at key steps of the analysis strategy. The analysis of complex `omics’ phenotypes will be investigated through the extension of sparse regression approaches to large number of responses, as well as by the use of graphical modelling approaches, which target estimation of the network structure and direct associations between the omics features of interest. Both approaches deal with the large p (large number of features) small n (number of samples) context by using sparse formulations or shrinkage. One important focus will be to use context specific (e.g. clinical, epidemiological or biological) information to build hierarchical relationships between different sources of data and informative priors based on substantive knowledge. Model uncertainty will be taken into account as part of the Bayesian modelling process. In complement, a programme of work tackling stratification in precision medicine will be developed. The approach chosen is focussed on formulating semi supervised (outcome guided) integrative clustering models and algorithms to uncover subpopulations of patients that have diagnostic, prognostic or theranostic meaning, using a collection of high dimensional biomarkers We will use the methods to search for new associations and structures in a range of exemplar case studies demonstrating multiple facets of the applicability of the novel methods that will be developed. In particular, we will investigate gene expression profiling and eQTLs for autoimmune diseases, integrative clustering for subtyping breast cancer in link with survival, and integrative genomics of cardiovascular diseases. Scalability of the algorithms developed will be a focus of attention. The computer programmes implemented will be open source and made publicly available.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR;GENERIC HEALTH RELEVANCE;INFLAMMATORY AND IMMUNE SYSTEM
Title: Consumer Lab: Building academic-industry partnerships to ensure sustained acceptance of healthy foods
Funder: Medical Research Council

Abstract: Diet is a major risk factor for a range of noncommunicable diseases. At a population level this is attributed to a rapid transition to modern food systems and energy-rich foods. In response, The National Food Strategy (2021) highlights an important role for food reformulation. However, technical innovation may be wasted if consumers are unwilling to accept a modified product. The UK can claim considerable expertise in biological, social, and psychological controls of human dietary behaviour. However, academics often fail to deliver the kind of actionable research that is needed by the food industry. Current methods i) lack ecological validity, ii) involve acute observations that fail to account for changes in food acceptability over time, and iii) use unrepresentative 'convenience samples' (typically university staff and students). This hub will transform opportunities for product innovation by building academic-industry partnerships that address these long-standing concerns. Specifically, our vision is to develop a distributed UK-wide 'Consumer Lab,' comprising a portfolio of methods and approaches. Accordingly, we will prioritise industry-relevant research studying food choice in real-world settings, and we will deliver this capability for use across the entire OIRC network. To achieve this ambition, this hub brings together a highly experienced multi-site team that comprises complementary academic and industry-relevant experience, together with considerable expertise in the day-to-day management of networks of this kind. In addition to addressing the development of early career researchers, our hub will also prioritise research that adheres to high scientific standards (e.g. the use of pre-registration and Open Science). Finally, we recognise the need to ensure that our research and all hub operations are underpinned by the principle that the provision of equal opportunity, valuing diversity, and promoting a culture of inclusion, is vital to its success.


Research activity codes: 1.5 RESOURCES AND INFRASTRUCTURE (UNDERPINNING);3.1 PRIMARY PREVENTION INTERVENTIONS TO MODIFY BEHAVIOURS OR PROMOTE WELL-BEING
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR;GENERIC HEALTH RELEVANCE;METABOLIC AND ENDOCRINE;ORAL AND GASTROINTESTINAL
Title: The Ex-Preterm Infant in Childhood (EPIC) Study
Funder: Medical Research Council

Abstract: Background: Preterm birth is associated in epidemiological studies with adverse cardiometabolic health in later life. The mechanism for this is unknown. Altered adiposity, primarily increased internal abdominal adipose tissue (IAAT), has been observed in cross sectional studies of preterm infants at term age and young adults born preterm. I hypothesise that IAAT tracks from birth to adulthood, conferring a lifelong risk of poor cardiometabolic health. Aim: I will test the primary hypothesis that the pattern of increased IAAT observed in preterm infants (at term equivalent age) in comparison with full-term infants, is detectable in the same children when investigated in childhood. Research objectives: to characterise the adiposity of preterm and term born children using the following investigative techniques: 1) Magnetic Resonance Imaging (MRI) to quantify whole body adipose tissue and discrete adipose tissue compartments, hepatic lipid content and the supra-clavicular fat fraction of Brown Adipose Tissue (BAT) 2) Infrared thermography (thermal imaging) to measure the activity of Brown Adipose Tissue (BAT) following application of a cold stimulus Sample size: I will recruit 110 children (preterm=55) to enable a minimum difference of 0.045l in IAAT to be detected between the two groups. I will capture objective data on physical activity, energy expenditure and measure blood pressure. Children recruited will be drawn from a cohort of preterm and term born children who all underwent whole body MRI scans to measure adipose tissue distribution in infancy. Scientific and medical opportunities: Whole body MRI is considered the gold standard approach to quantifying adipose tissue quantity and distribution. This study will follow-up a cohort of preterm and term born infants through childhood to assess if differences in adipose tissue distribution persist, which potentially underlies the increased risk of cardiometabolic disease in young adults born preterm.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR;GENERIC HEALTH RELEVANCE;METABOLIC AND ENDOCRINE;ORAL AND GASTROINTESTINAL