NIHRDataInsights/HRCSData huggingface dataset:
Title: Project ACE: Active, Connected and Engaged Neighbourhoods
Funder: Medical Research Council

Abstract: BACKGROUND/AIMS: Programmes that effectively increase physical activity in older people will yield large improvements in quality of life, independence, social activity and health and care costs related to cardiovascular disease, diabetes, dementia. Unfortunately, little evidence exists for effective interventions and at a national level, resources for prevention are scarce. The Active, Connected and Engaged (ACE) neighbourhoods project will develop and pilot a low cost, pragmatic, and sustainable intervention programme in which retired volunteers promote physical activity. The specific objectives are to: a) refine and manualise the intervention; b) monitor recruitment, retention, attendance and adherence rates; c) determine participant reactions to the intervention; d) estimate the variance in outcome measures to enable calculation of sample size for a future multi-centre RCT and e) estimate resource use/costs and develop methods for economic evaluation. METHODS: We will conduct a two phase, 24-month pilot study involving two paid neighbourhood coordinators, 20 activity promotion volunteers [ACE activators] and 100 participants. In Phase 1, we will refine the ACE programme, develop the activator training manual and refine the role of the ACE co-ordinators. In Phase 2, 100 sedentary older adults aged 65?85 years will be recruited in two neighbourhoods in Bristol and will be randomised to the intervention and control groups. In the intervention group, the ACE activators will deliver up to five individual sessions over six months to engage and motivate participants and support maintenance, following a theoretically-driven behaviour change model. Controls will receive a booklet with information about local physical activity opportunities and will be offered the ACE programme at the end of the study. The main outcomes (on which the study is powered) are: Recruitment rate and study completion rate. Intervention concordance (the proportion attending =3 of the 5 individual sessions) and intervention fidelity will also be assessed. To pilot the trial measures, we will assess physical activity (by accelerometry), well-being, neighbourhood quality of life, perceptions of competence, autonomy, relatedness, and resilience, for both intervention participants and volunteers. Focus groups will explore topics related to recruitment, training and delivery of the ACE programme and discuss strategies that facilitate the lifestyle change process and that might improve the programme or the delivery of the research. OUTPUTS: The main output will be a well-informed and grounded intervention that has potential for generalisation throughout the UK and is ready for evaluation in a definitive effectiveness and cost effectiveness trial.


Research activity codes: 3.1 PRIMARY PREVENTION INTERVENTIONS TO MODIFY BEHAVIOURS OR PROMOTE WELL-BEING;7.1 INDIVIDUAL CARE NEEDS
Health categories: GENERIC HEALTH RELEVANCE
Title: Robust Analysis of Signal Transduction Underlying Cellular Variability in Stem Cells
Funder: Medical Research Council

Abstract: The aims of this research are - developing inferential and modelling tools to capture the complexities of signal transduction and cellular decision making at the level of single cells. - Understand what causes cell-to-cell variability in cell-fate decision. - Develop control mechanisms that manage to guide such cellular variability - Apply these methods in the context of signal transduction pathways in stem cells. I will address this problem - as appropriate for this fellowship - using a combination of mathematical and statistical modelling approaches. In particular I will look at single cell signal transduction data related to cell-fate decision as regards differentiation and proliferation. Sequential statistical approaches are ideally suited to studying such processes, especially for experimental techniques, which do not track cells over time but assay different cells at the different time-points. Moreover, for the purposes of control they offer perhaps the most flexible framework to direct interventions (e.g. administration of growth factors) in response to real-time dynamics. The proposed research will provide new methodologies, which in turn will offer new insights into the molecular mechanisms underlying cell-to-cell variability in molecular and cell-fate decision phenotypes. I will then apply these tools to models and real data of signal transduction and cellular decision making processes in stem cells (especially haematopietic stem cells). Of particular interest is the development of novel design protocols for stimuli and therapeutic interventions that can interfere with the processes that principally determine the levels of cell-to-cell variability.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: GENERIC HEALTH RELEVANCE
Title: Mathematical and Computational Modelling of Transcription Factor Target Finding in Eukaryotic Organisms
Funder: Medical Research Council

Abstract: Site-specific transcription factors (TFs) are proteins that bind to specific sites on the genome and regulate the activity of one or more genes. TFs control gene activity by either increasing or reducing the transcription rate of their target genes. Thus, TFs play a crucial role in the fine-tuned cellular response to developmental, physiological or environmental signals. Eukaryotic gene regulatory programmes usually require the concerted binding of a defined combination of TFs to cis-regulatory modules, short genomic regions that may be many kilobases away from the actual transcription start sites around the genes‘ promoters. Much of transcriptional regulation is already understood; but while the in vitro biochemistry of TF-DNA interactions is increasingly well established, we still have no clear picture how TFs target the appropriate binding sites in a large genome. Therefore, the central question addressed in this fellowship is: how do TFs find their genomic binding sites? Approximations to this question can be provided by statistical physics, in particular the law of mass action, but also using mathematical and computational methodologies that I worked on as a PhD student. Current biophysical models often assume that all TF molecules diffuse in a perfectly homogeneous reservoir around a one-dimensional genome, from where they can bind only to more-or-less specific sites on the DNA. Spatial aspects are frequently ignored in these models, and thus, any deviations from the assumption of one-dimensionality etc. will undoubtedly introduce an error in these analyses. In order to get a better understanding of the target finding process, it is essential to consider spatial dimension since nuclear processes occur non-homogeneously in three dimensions. In the proposed research, I aim to develop a mathematical model that describes how TF molecules target their genomic binding sites under consideration of the local chromatin environment. Model building will be informed by genome-wide data on nucleosome occupancy, experimentally determined transcription factor binding sites and chromatin modification data. Using the model, I will address questions such as: How do chromatin modifications influence target site finding? What role does nucleosome occupancy of the DNA play? My aim is to establish under which specific conditions these spatial aspects make the strongest contribution to gene regulation and if there are any situations where the local chromatin environment can be neglected. A reliable mathematical/computational model of transcription factor target site identification under consideration of the local chromatin environment will advance the theoretical understanding of the biophysical laws governing the gene regulation process in eukaryote organisms


Research activity codes: 1.4 METHODOLOGIES AND MEASUREMENTS
Health categories: GENERIC HEALTH RELEVANCE
Title: Analysis of cell fate choice regulation in organiser/primitive streak stem cells and neuroectoderm progenitors.
Funder: Medical Research Council

Abstract: A fundamental challenge in stem cell biology is to understand how cells acquire distinct fates. During early vertebrate embryogenesis a stem cell-like progenitor population located in a structure called the primitive streak gives rise to structures that run the length of the body, notably, the neural tube (future spinal cord) and somites (future muscle and skeleton). The organizer is a specialised structure at the anterior tip of the primitive streak. Stem cell-like progenitors located in the organiser give rise to two specific tissues namely the floor plate, which lies in the ventral floor of the neural tube and the notochord, a rod of mesoderm lying directly below the floor plate. The floor plate and notochord provide a critical signal, sonic hedgehog, which patterns the neural tube regulating where and when distinct neuronal subtypes differentiate. The organiser/primitive streak are thus of fundamental importance to the developing embryo and a detailed understanding of the molecular mechanism that regulates allocation of appropriate numbers of these stem-like progenitor cells to these various embryonic tissues is crucial both to the understanding of embryogenesis and the generation of means of treating embryonic defects. Very little is known about which signalling pathways regulate cell fate choice among these progenitors in amniote embryos. We have recently shown Notch regulates cell fate choice in the organiser. We identified a second novel role for Notch which is to influence cell fate decisions of neural progenitors (by modifying their competence to respond to SHH), and thereby affect dorsoventral patterning of the neural tube. We aim to 1) Identify which pathways Notch interacts with in the organiser to ensure appropriate numbers of cells adopt each fate. 2) Establish if Notch also regulates cell fate choice in the adjacent primitive streak stem-like progenitors. 3) Investigate how Notch regulates the response of neuroectodermal cells to the morphogen Shh. 4) We will determine if these are conserved roles in higher vertebrates. The analyses will involve gain and loss of function assays treating progenitors to pharmacological reagents or electroporation of relevant constructs followed by grafting progenitors to a host embryo. We will then lineage trace the derivatives of the treated progenitors. We have also devised a screen using Next Generation Sequencing technology to identify pathways regulating these cell fate choices. For the Notch-Shh interplay we will analyse the effect of Notch misexpression on components of the Shh pathway known to affect efficacy of signal transduction.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Evaluating the role of expertise-based trial designs in trials of surgical interventions
Funder: Medical Research Council

Abstract: While many surgeons accept the need in principle for RCTs to evaluate surgical interventions, they struggle to reconcile their personal involvement with their surgical experience. Under a standard 2 arm surgical trial design, participating surgeons are expected to delivery both interventions. Where interventions differ substantially, surgeons may routinely only conduct one or the other of the interventions. It is likely even where surgeons perform both they have a preference and/or have more expertise in one than the other. As a consequence some surgeons may be reluctant to participate in a standard RCT. The expertise-based trial design, where participating surgeons provide only the intervention in which they have expertise, has been proposed to overcome this problem. Other purported benefits include increased surgical compliance with randomisation, addressing the learning curve effect along with patient preference for such a design. While such a design is not new, the profile of the design has been raised and the use of it is becoming more common. However, this approach has been criticised on a number of grounds including its impact upon sample size, practicality, generalisability and ethics. The aim of this research is to evaluate the relative merit of expertise-based designs over the standard trial design in surgical evaluations. A three year programme of methodological research is proposed which would seek to answer the following research questions: 1. Under what circumstances is the expertise-based approach an acceptable and feasible design? 2. What impact do the various trial design options have upon the statistical efficiency? The specific elements of research are: 1. Systematic (methodology) review of the use of expertise-based trials in the surgical and non-surgical medical literature focussing on when the design has been used and implemented. 2. Assessment of the acceptability and feasibility of expertise-based designs through semi-structured interviews with surgeons and trialists. This will consider areas in which the design could be used and is practical. 3. An extensive simulation study evaluating the various options for expertise-based trial design and corresponding statistical analysis and their impact upon statistical efficiency. This will inform design of surgical trials and assessment of the relative trade-off between approaches. 4. Statistical analyses of two expertise-based trials assessing the impact of different analysis strategies. 5. Guidance documentation on the use of expertise-based designs in surgery summarising the published evidence to date and the knowledge gained from elements 1-4 above and recommendations for their use.


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: A graphical model approach to pedigree construction using constrained optimisation
Funder: Medical Research Council

Abstract: Our proposed research aims to construct pedigrees (family trees) from genetic marker data. Uncovering relationships between groups of individuals is important for epidemiological and genealogical research. For example, when investigating the genetic risk factors underlying the common complex diseases of major public health concern it is difficult to discover rare genes unless *related* individuals are used as they are more likely to share longer haplotypes around susceptibility loci and are hence biologically more informative than unrelated `cases and `controls . We propose a novel cross-disciplinary approach to the task of pedigree reconstruction by formulating it as a probabilistic graphical model selection problem and exploiting state-of-the-art methods from combinatorial optimisation for model selection within a Bayesian framework. We will focus on applications where we may not have complete marker data for each individual. We do not assume age or sex information but can exploit it when it is available. Any known relationships can also be incorporated. We will not be restricted to small pedigrees and in many cases can guarantee to return a most probable pedigree, conditional on the available information. Where this is infeasible, the degree of approximation will be precisely quantified. By being able to deliver multiple high probability pedigrees, we will also allow for a more complete picture of the inherent uncertainty in any particular pedigree reconstruction. Our method is most reliably evaluated when the true pedigree is known and so we will make extensive use of simulated data for testing purposes. However, we will also use real data from the Avon Longitudinal Study on Parents and Children (ALSPAC) which will serve as an important test case for the potential usefulness of our approach to medical research. Being able to construct pedigrees from such existing data is faster and cheaper than starting a family-based study from scratch.


Research activity codes: 1.4 METHODOLOGIES AND MEASUREMENTS
Health categories: GENERIC HEALTH RELEVANCE
Title: Bayesian Discovery of Regression Structures: a tool kit for genetic epidemiology and integrative genomics analyses
Funder: Medical Research Council

Abstract: Finding important health determinants through regression analyses is a fundamental approach in all the health sciences. In this project, we focus on two domains, genetic epidemiology and integrative genomics, where advances are made by taking full advantage of new high-throughput technologies, leading to the collection of a vast set of explanatory variables. In these domains, desirable statistical outputs are reproducible regression models that select only a few relevant predictors (i.e. risk factors, SNPs, transcripts) amongst a very large set of possible candidates, together with good assessment of how uncertain their role is. Our approach is to build upon the unifying Bayesian hierarchical modelling paradigm to construct parsimonious regression models that can translate the underlying biology and facilitate the interpretation of results. The team of investigators have recently completed the development of a sophisticated algorithm, the Evolutionary Stochastic Search algorithm, which efficiently implements a Bayesian variable selection procedure for linear regression models in spaces containing thousands of predictors. The project?s aim is to capitalise on this foundation work and substantially expand it to build a powerful and versatile tool kit of regression models applicable to a wide range of ?cross-omics? analyses, i.e. analyses that involve two or more different types of ?omics? data, each of large dimensions. Such cross-analyses will become a major focus of research in functional genomics in the years to come, in parallel with the advent of new biotechnologies. We will develop a set of models aimed at Bayesian variable selection (i) in the presence of interactions; (ii) with multiple responses; (iii) including biologically structured prior knowledge. The scope of the algorithms will be considerably expanded by integrating new parallel computing techniques and novel software architecture (CUDA, Compute Unified Device Architecture) that enormously reduce computing time. We will use the methods to discover new associations and structures in three challenging case studies concerning: (a) the genetic regulation of lipid mechanisms in a large Finnish cohort; (b) multifactorial pathways in breast cancer; and (c) the genetic influence on brain activation of psychotic patients. These case studies are embedded in large collaborative projects coordinated by the epidemiology investigators and have been chosen to highlight different facets of the tool kit modules. The computer programmes implemented in the tool kit will be open source and made publicly available. Dissemination plans will benefit from the extensive network of collaborators in the case studies and also include two purposely designed workshops.


Research activity codes: 1.4 METHODOLOGIES AND MEASUREMENTS;2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Is "end-of-life" care more valuable? Measuring societal views using the new Q2S method
Funder: Medical Research Council

Abstract: In 2009, the National Institute for Health and Clinical Excellence (NICE) issued supplementary guidance to their technology appraisal methods to be applied to end-of-life (EoL) technologies. As a result, higher cost effectiveness thresholds (beyond the standard #30,000 per quality adjusted life year gained) can be applied to EoL technologies if certain criteria are met, although how high is not stated. The criteria include patients with relatively rare conditions for whom life expectancy is less than 2 years and treatment will extend life by at least 3 months. In practice, and in terms of the therapies appraised by NICE and other similar organisations (e.g. the Scottish Medicines Consortium), these conditions tend to apply to drugs for rarer types of cancer. Denial of such drugs has often been highly controversial, has led to negative news headlines and patient campaigns, and, in part, has led to the introduction of a new ?Cancer Drug Fund?. However, little is known about the societal views on this subject, especially regarding the priority that might be afforded EoL technologies relative to all other NHS treatments. Rigorous research is required to aid decision-makers in delineating, describing and measuring such societal views. Such research requires methods capable of addressing qualitative questions, ?What is the nature of societal views around the relative value of EoL therapies??, as well as quantitative questions, ?How are such views distributed in the population??. Existing approaches keep qualitative and quantitative methods, associated with distinct and different paradigms, separate, even when applied in the same project. In this project we will develop a single, integrated framework for both: first, using Q methodology to elicit and describe the views that exist; then devising quantitative Q methods to extend these findings into rigorous survey design and analysis. This is the ?Q sort to survey? (Q2S) approach. Using data from previous, exploratory work to pilot different analytic techniques and different questionnaire designs we will establish the most effective Q2S approach, which will then be applied to the exploration of societal views regarding EoL issues and their distribution in society. This will be done via a ?traditional? Q methodology study, the results of which will form the basis of a more?parsimonious, nationally-representative survey. Analysis of the survey data will require testing of different statistical methods. Once established, these methods can be generalised to any study of societal perspectives.


Research activity codes: 7.2 END OF LIFE CARE;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Systematic Techniques for Assessing Recruitment to Trials (START): a programme to test recruitment interventions
Funder: Medical Research Council

Abstract: Our aim is to improve the evidence-base concerning recruitment to trials, enhance recruitment rates and make research more accessible to the public. Randomised controlled trials (RCTs) are critical to evidence-based practice, but recruitment is often problematic, with little rigorous evidence to assist research teams in recruitment and retention of participants. Without the development of reliable methods, the policy goal of improving health and wealth through research will be hard to realise. A robust test of the effectiveness of a recruitment method is an RCT comparing one method with an alternative, nested in a host trial. Such nested studies are rare, largely delivered in an ad hoc way, and always tested in the context of a single host trial, limiting their utility Our vision is to develop a methodology to develop, deploy and test recruitment interventions nested within ongoing host RCTs, to rapidly and systematically improve the evidence base. To achieve this, we propose a programme of three interrelated work packages: (a) Methodology ? We will develop methods for design and analysis of nested recruitment studies (b) Interventions ? We will develop recruitment interventions (c) Implementation ? We will recruit a cohort of host RCTs and test our recruitment interventions through nested studies across multiple trials


Research activity codes: 6.9 RESOURCES AND INFRASTRUCTURE (TREATMENT EVALUATION);8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE