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Department of Cardiovascular Science


The Department of Cardiovascular Science performs research into coronary artery disease, pulmonary hypertension and bleeding disorders. Working closely with clinicians, much of our research involves use of patient samples to translate discovery science from basic programmes. The Medical Research Council (MRC) Centre for Developmental and Biomedical Genetics is a key discovery engine in the science of the group.


Our funding sources include the National Institute for Health Research, the Medical Research Council, BBSRC, EPSRC, the European Union and the British Heart Foundation.


Our research


Our research makes demonstrable impact in clinical medicine. Examples include: • The development of new antiplatelet regimens in coronary artery disease.


• The development of informatics systems for the collection of routine clinical data for research.


• The integration of routine patient follow-up visits into research protocols which have ensured that follow-up occurs in a timely manner.


Our research groups benefit from access to the Clinical Research Facility (CRF), a purpose-built unit which provides a specialist and dedicated environment for the conduct of high-quality clinical research.


Our main research areas are:


Cell biology Regulation of inflammatory responses, specifically on events related to receptor function and cell signalling.


Coronary artery disease Biology of coronary artery disease, both its aetiology and mechanism of presentation.


Haemostasis research Concentration on the biology of unexplained bleeding in patients.


“Our work addresses the biggest health challenges facing our country, our health services and our world today.”


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Inflammatory signalling Molecular and cellular regulatory mechanisms of inflammatory signal transduction networks, with a special focus on vascular cell types.


Medical Physics Research focuses on modelling and simulation in medicine and the group is a core contributor to the Virtual Physiological Human programme. We are developing predictive tools that will be used to improve clinical diagnosis and interventional planning.


Credits : AZ / IS / S. Kaulitzki, M. Abildgaard, V. Yakochuk


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