Veterinary Inflammation and Metabolism
The Veterinary Inflammation and Metabolism research group investigates the disease processes and develops novel therapies for inflammatory and metabolic diseases.
This includes important diseases such as equine metabolic syndrome, pituitary disease (equine ‘Cushing’s syndrome’), laminitis and sepsis (the systemic inflammatory response to bacterial toxins) in domestic animals. Our aim is to understand the disease processes and risk factors, and to develop new ways of treating and preventing these conditions.
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Our group is skilled in many techniques including analytical biochemistry, in vitro pharmacology (particularly pharmacodynamics), cell culture and measurements of cytokines plus a wide range of other metabolic and inflammatory disease biomarkers.
We are also skilled in performing in vivo measurements of insulin sensitivity in horses and ponies; metabolic responses to feed challenges and long term diet studies.
Our researchers.
Our people
Professor Simon Bailey
Professor of Veterinary Preclinical Sciences
Simon Bailey is a Diplomate of the European College of Veterinary Pharmacology and Toxicology. His main research areas are endocrinology, equine laminitis, novel anti-inflammatory therapies, sepsis and cardiovascular pharmacology.
Dr Nick Bamford
Lecturer in Veterinary Biosciences
Nick Bamford is a Diplomate of the American College of Veterinary Internal Medicine. His research focusses on equine metabolic disease, including Equine Metabolic Syndrome and Pituitary Pars Intermedia Dysfunction (PPID).
Dr Jenni Bauquier
Senior Lecturer in Equine Medicine
Jenni Bauquier is a Diplomate of the American College of Veterinary Internal Medicine. Her research focusses on equine sepsis and equine critical care.
Group leader
Group members
Our group engages in translational research, integrating cell culture, in vitro and ex vivo techniques with live animal studies, in order to understand the pathophysiology of metabolic and inflammatory diseases and evaluate novel therapies.
We also use large scale field studies to understand disease risk factors and associations at the population level.